# Shoal Research — full research corpus # Generated 2026-07-10. Canonical per-article URLs are under https://shoal.xyz/research/writing/ --- # HTTP 402: How Machines Move Money - Publisher: Shoal Research (https://shoal.xyz) - Category: Agentic Payments - Published: 2026-05-28 - Canonical: https://shoal.xyz/research/writing/http-402-how-machines-move-money/ - Keywords: AI agents, agentic payments, x402, infrastructure, Agentic Payments ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/7110ee4a2fec.jpg) Every second, ~80+ million HTTP requests are sent over the internet on average. In that same second, Visa can handle no more than 65,000 payments, and Mastercard around 20,000. Machines move data at the speed of the web. What happens when they start to move money the same way? ## Machines are Moving Money In the blink of an eye, LLMs have evolved beyond simple Q&A chatbots into context-aware, tool-equipped economic actors we now call agents. No one quite knows how this development evolves from here, but payment incumbents wasted no time hedging their bets; Visa launched its [Trusted Agent Protocol](https://developer.visa.com/capabilities/trusted-agent-protocol/overview) and a [new CLI](https://app.visacli.sh/) for agent payments; Mastercard released [Agent Pay](https://developer.mastercard.com/mastercard-checkout-solutions/documentation/use-cases/agent-pay/) and [Agent Suite](https://www.mastercard.com/us/en/news-and-trends/press/2026/january/mastercard-launches-agent-suite-to-ready-enterprises-for-a-new-e.html), and in March executed Europe’s first live AI agent payment within a regulated banking framework [alongside Banco Santander](https://www.santander.com/en/press-room/press-releases/2026/03/santander-and-mastercard-complete-europes-first-live-end-to-end-payment-executed-by-an-ai-agent); American Express just recently announced the [ACE developer toolkit](https://www.americanexpress.com/en-us/company/agentic-commerce/), just to name a few names. Few compare to Stripe’s efforts, however, whose agentic stack now spans[new agent payment primitives](https://docs.stripe.com/agentic-commerce/concepts/shared-payment-tokens),[business and developer tooling](https://docs.stripe.com/agentic-commerce), and co-authoring an[open-source payments protocol](https://mpp.dev/) purpose-built for machine-to-machine payments. Amid a great deal of warranted skepticism surrounding the impact of AI agents, trillion dollar market cap companies who certainly know a thing or two about payments are allocating significant resources to help software pay for software. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/433b02d8fd07.png) A payment is simply a way to settle an obligation: to exchange value for access to a specific good or service. For an agent, a payment may be the single blocker between a decision and a realized outcome by unlocking access to a necessary resource in a workflow the moment it’s needed. ‘Agentic payments’ and ‘agentic commerce’ have become the umbrella terms, and though the branding could use some work, the category has evidently materialized. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/8fa5dd473ef8.png) The interesting question remains what the supporting infrastructure will look like. Before we get there, it’s worth reviewing what it actually means when machines are moving money. ### Intention Is All You Need The free open public access to the internet we know and love is subsidized by advertisements. [Bryan Kim](https://www.a16z.news/p/of-course-theyre-putting-ads-in-ai) puts this well: > *“Internet advertising has created one of the greatest “public goods” in history, for the negligible price of occasionally having to look at ads for cat snuggies or hydroponic living room gardens.”* Google, Facebook, YouTube, and TikTok, have generated billions of dollars through ads, a simple act of monetizing basic human behavior: uncertainty. The gap between what someone intends to do and what they actually end up doing is the very premise of the attention economy. Every commercial webpage someone loads is an opportunity to present an ad to a persuadable consumer. This model collapses when the primary consumer is an AI agent, who is a far more rational economic actor than a human by design. An assigned task and a set of tools to complete that task (*e.g. “Build me X using Y within budget Z”)* leaves little room for ambiguity, while the lack of a limbic system means no susceptibility to the emotional pleas of advertisements. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/3fc763997004.png) Agents as consumers exhibit behavior patterns quite distinct from humans. They don’t face the same cognitive constraints that humans do; their very purpose of these machines is to multiply our output by orders of magnitude. Importantly, this means their resource consumption is far more granular: they require more resources, more frequently, though often at much smaller quantities (per-call, per-request rather than per-seat or per-month). - A coding agent tasked with fixing a bug reads files, runs terminal commands, calls a code execution sandbox, and iterates on the output across dozens of API calls in a single session. Each call is billed by the model provider per token consumed. A single debugging session can consume 50,000 to 200,000 tokens across planning, editing, testing, and verification. - A research agent compiling a market analysis might query a financial data API, a news archive, a web scraping service, and a document search index, each at a different price point, each needed at a different point in the workflow. The transactions occur at runtime: the exact point in a workflow where a capability gap appears. Simon Taylor refers to this as the i[ntention economy](https://www.fintechbrainfood.com/p/the-intention-layer): the consumer, now an agent, arrives with a predetermined intent and moves money only if necessary to fulfill that intent. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/5410bc3691ba.png) Importantly, the byproduct of empowering AI agents as consumers is requiring new business models to accommodate them. Here we see the [headless merchant](https://a16zcrypto.com/posts/article/ai-agent-commerce-headless-merchant/) emerge. Building on the increasingly popular h[eadless commerce](https://www.salesforce.com/commerce/headless/guide/) model, in which an e-commerce app’s frontend (user interface) is separate from its backend (data and core business logic), the headless merchant removes the frontend entirely because the buyer, an agent, has no eyes and preference for UX. The headless merchant simply needs a server, a set of API endpoints to call, a designated price-per-call, and some way to accept payments. Several takeaways follow clearly from this. Payments need to be **granular**, meaning small enough to settle a single API call or token batch. They need to be **programmatic**, meaning triggered by code as a function call rather than a human action. And they need to be **real-time**, firing at the exact moment a capability gap appears in a workflow. The architecture of today’s ad-subsidized web is largely path-dependent on monetizing human uncertainty. But the intention economy, which monetizes outcome, needs its own corresponding payment infrastructure to match. ### Moving Money On The Web To understand where agent payments are going, it helps to first understand how online payments actually work today. Online payments today involve entering a card number, clicking “pay,” waiting for a confirmation, a process that travels across web infrastructure the same way any other data does. But importantly, the web infrastructure simply provides the communication layer in this flow. Card details move as a POST request to a payment processor, which calls a card network API, which calls the payer’s bank. The actual payment, authorization, and settlement logic all lives in infrastructure layered on top of the web. The likes of Visa, Mastercard, AmEx are building agent payment infrastructure on top of these same rails, intent on making their existing middleware smarter. What if instead, online payments worked the same way data does? What if, say, a server could respond to a request with a price, the client could pay online, and the resource delivered in the same round-trip? ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/1dc99405ef7b.png) [HTTP](https://www.w3.org/Protocols/) standardizes how clients and servers exchange information on the web: a client sends an HTTP request, a server returns an HTTP response. A client can be anything from a browser to a mobile app to an AI agent. When a request succeeds, the server returns HTTP 200 OK. When a page doesn't exist, HTTP 404, meaning there is an error. When access is unauthorized, the server returns HTTP 401. These status codes are built directly into the protocol itself. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/65d771a88f57.png) That question was first posed some 30 years ago, when the original HTTP spec was published, and with it status code 402: Payment Required. 402 sat between 401 (Unauthorized) and 403 (Forbidden) and like its neighbors, signals that the client must satisfy a condition before the server delivers the requested resource. 402 was designed for that condition to be a payment. **The core mechanism was simple:** 1. A client requests a gated resource. 2. The server responds 402 with a price, accepted payment method, and recipient. 3. The client pays and retries with proof of payment in the header. 4. The server verifies and delivers the resource. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/25d2e29e8038.png) And yet over the years, 402 was never formally defined. There were a number of notable attempts: the W3C tried twice in the 1990s; Adrian Hope Bailie of Ripple [proposed](https://www.potaroo.net/ietf/all-ids/draft-hope-bailie-http-payments-00.html)a concrete Pay header implementation in 2017, but none ultimately gained enough traction to be implemented. The simple reality was that humans already got accustomed to credit cards and thus the need was never acute enough to prompt a solution. But time has passed, and AI agents are becoming a primary web client and user interface alongside browsers. The human is still in the loop, but agents equipped with real-time context and tooling make requests against the web at a far greater scale and frequency. When an agent encounters a resource it needs in a workflow, payment is simply its next function call, which either resolves and the task continues, or doesn’t and the task stops. The flow is elegantly simple: an agent hits a resource boundary, the server returns a price signal, the agent pays inline and proceeds with its task. The x402 protocol was the first implementation of the 402 primitive to gain meaningful traction, launching in May 2025 under Coinbase before being contributed to the Linux Foundation as a vendor-neutral open standard. MPP, Tempo’s open-source framework built with Stripe, followed in March 2026, bringing fiat and card rails into the same protocol loop, as well as the first (formal proposal to implement HTTP 402 via IETF draft). Their differences raised the obvious questions: how do the two diverge, and which is better suited for which use case? These are the right questions. They are also premature without more context. x402 and MPP are not the first attempts to build payments into the web at the protocol level. What differs across implementations is everything around that core loop: which rail settles the transaction, how proof-of-payment is structured, what metadata the headers carry, and how much complexity the client needs to handle. ## The HTTP 402 Landscape ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/3b0073b554b3.png) When Bitcoin emerged in 2009, it introduced a digital currency, with a native payment rail, that had no fixed transaction fees or intermediary. For developers curious about HTTP-native payments, the connection to 402 was immediate. As early as 2011, Bitcoin Core contributor Matt Corallo wrote in a [thread on the Bitcointalk forum](https://bitcointalk.org/index.php?topic=3895.msg55476#msg55476) that he believed HTTP 402 “would be a great use case for Bitcoin”. His proposal suggested a server returning a 402 alongside an X-Bitcoin-Address and X-Bitcoin-Price header, with a browser plugin handling payment automatically in the background. Early experiments were mostly small and independent efforts. In 2014, Benedict Chan demoed [Zero Click](https://devpost.com/software/zero-click-bitcoin-micropayments): a server that returned a 402 Payment Required status code with a Bitcoin address and amount in the header, a Chrome extension ran in the background, automatically paid for the page and requested it again. In 2015, the anonymous author of Amphibian Abstracts published one of the [earliest public 402 Bitcoin demos](https://thoughts.amphibian.com/2015/05/using-http-402-for-bitcoin-paywall.html) using custom headers (X-Payment-Types-Accepted: Bitcoin, X-Payment-Address-Bitcoin: putarealbitcoinaddresshere, X-Payment-Amount-Bitcoin: 1.234) passing payment type, address, and amount directly in custom HTTP headers. Neither Zero Click nor Amphibian’s demo was a formal protocol, but these experiments helped show the basic HTTP 402 loop was at least viable. ## The 21 Bitcoin Computer In 2015, Balaji Srinivasan’s 21co introduced the 21 Bitcoin Computer: a Raspberry Pi device featuring a built-in Bitcoin mining ASIC as well as a micropayments server accessible from a command-line interface (CLI). A core part of the product was the two1 [open-source Python library](https://pypi.org/project/two1/3.5.0/) that shipped alongside it, which allowed users to mine Bitcoin, use it to buy and sell API calls, set up world-readable machine-payable endpoints, and publish them to the 21.co marketplace from any Unix command line. Two1’s module exposed a @payment.required(price) header that could be placed in front of any Flask or Django routes, two widely used Python web frameworks for building HTTP APIs. When a client would request to access a paid endpoint, the server provided a HTTP 402 Payment Required response header alongside a Bitcoin payment address and the required payment amount. On the client side, the class wrapped Python’s standard library and upon receiving a 402 response, it automatically handled the micropayment and retried the request. Notably, the HTTP 402 handshake itself was abstracted away from the developer. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/6734d5dd2687.png) A machine with a Bitcoin private key could possess, send, and receive money to another machine without a human intermediary in the loop. Fundamentally, this was all just developer tooling, but Balaji argued the implications ran deeper as part of a progression through three distinct webs: first the World Wide Web of documents connected by hyperlinks, then the social web connecting people through platforms like Facebook and LinkedIn, and then the Machine Web, where the links between nodes are payments between machines. The line of thinking was simple: given that the web had already standardized how machines exchange information, and how people form relationships, its next problem to solve was to standardize how machines exchange money. 21co’s Bitcoin software could monetize APIs on a per-request basis without requiring developers to provide or accept credit cards, let any developer with some bitcoin call out to another endpoint as easily as importing a library, and unify fulfillment and billing into the same series of packets. Beyond simple per-call payments, 21co implemented payment channels on a bar tab model: one deposit transaction opened a tab, high-frequency micropayments occured off-chain, and only two onchain transactions settled the whole session. The developer toolkit also enabled developers to chain paid APIs together and sell the composite pipeline, setting up a supply chain of machine-to-machine payments that could be triggered by a single client call. As interesting as the ideas were, however, 21co’s Bitcoin computer proved to be ahead of its time. As Bitcoin network congestion grew through 2016-17, transaction fees made sub-cent micropayments economically unviable. The core concept, however, remained intact and inspired future HTTP-402 payment protocols. ## L402 In March 2020 Lightning Labs launched [L402](https://www.l402.org/), which remains the oldest active HTTP-402 implementation to date. L402 is an open-source payments framework that pairs the HTTP 402 status code with Bitcoin Lightning Network invoices and Google [macaroons](https://research.google.com/pubs/pub41892.html?source=post_page---------------------------) to enable clients to request, pay, and access web resources L402’s implementation of HTTP 402 works as follows: when a client requests a paid resource, the server responds with an HTTP 402 status code as a payment signal, and includes everything the client needs to pay and gain access in that single response. This intuitive multi-step HTTP handshake is the same foundational structure that x402 and MPP have followed. To better understand how L402 works, some familiarity with macaroons helps. A macaroon is a small piece of data that a server generates and hands to a client as proof that the client is allowed to access a specific resource, also known as a bearer token. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/d5396efe3780.png) In L402, when a client, say an AI agent, wants access to a paid resource, the server generates a macaroon and Lighting invoice together. The invoice, denominated in satoshis (sats), is the payment request; the macaroon is the access credential which becomes valid to use once the invoice is paid. The server combines the two by embedding the invoice’s associated payment hash inside the macaroon. This payment hash is produced by the server taking a secret value, called the *preimage*, and running it through a sha256 hash function. By design, the only way to reproduce the preimage is to actually pay the Lightning Network invoice. The client then utilizes a connected Lightning Network node or wallet client to route the payment and pays the invoice. Once paid, the Lightning Network reveals the preimage to the client, who then presents both the preimage and macaroon to the server, which runs one specific check: **does the sha256(preimage) match the payment hash embedded in the macaroon?**If yes, the payment is proven and the client is granted access to the resource. Importantly, the current spec under bLIP-0026 is token-format agnostic, meaning macaroons are no longer required, and any token that commits to a payment hash is accepted. Putting together the complete L402 payment flow: - A client (e.g. an AI agent) sends an HTTP request to a gated endpoint. - The server responds with HTTP 402 Payment Required and a WWW-Authenticate header, which contains two values in a single response: the macaroon and a Lightning invoice. - The client pays the Lightning invoice and receives the preimage. - The client retries the original HTTP request with an Authorization:L402 header containing both the macaroon and the preimage. - The server verifies the credential and provides the resource. L402’s payment model is *pay-per-credential* rather than pay-per-call. A client pays a Lightning invoice once and receives a macaroon that is cached and reused for subsequent requests to the same service until it expires or is revoked. The broader L402 community spec extends the model further, defining offer types including one-time access, monthly subscriptions, and pre-purchased credit bundles, with payment methods covering Lightning, onchain, and credit cards. The Current State of L402 ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/3279d2d7222e.png) L402’s original pitch was to be an alternative to credit cards and email signups for accessing paid APIs. Aperture, Lightning Labs’ Go reverse proxy, implements the full L402 lifecycle and has been in production since 2020 powering Lightning Loop (non-custodial swaps) and Lightning Pool (p2p liquidity marketplace). In practice, however, L402’s architecture maps more cleanly onto machine clients than human ones, and [AI agents have become L402’s primary use case](https://lightning.engineering/posts/2026-03-11-L402-for-agents/). A new [agent-spec.md](http://agent-spec.md) condenses the entire protocol into ~560 tokens for embedding directly into agentic context windows, meaning AI agents can now load the full L402 spec at runtime and implement the handshake autonomously. The numbers, as of early 2026, indicate that L402 is live but still early. The new [Github repo](https://github.com/l402-protocol/l402) grew to 213 stars on Github since early 2025; [Satring](https://satring.com/) currently tracks 58 live L402 services. The most significant near-term catalyst for L402 is Taproot Assets, a protocol developed by Lightning Labs that allows stablecoins and other assets to be issued on Bitcoin and then transferred over the existing Lightning Network. Today when an L402-gated server generates a Lightning invoice, it is denominated in satoshis; the client pays in Bitcoin; the server receives Bitcoin, a volatile asset. Integrating with Taproot Assets resolves this by allowing the invoice to be denominated in a stablecoin like USDT or USDC while still routing over Lightning’s existing payment channels and settling in milliseconds. In practical terms for L402: an AI agent making a paid API call would encounter the same 402 challenge and the same macaroon handshake it does today; the only change is that it can pay the Lightning invoice in stablecoins. Tether has committed to bringing USDT to Bitcoin with Lightning Network support via Taproot Assets, and once widely routed, L402 will be able to settle in fiat-denominated assets over Lightning rails. Lightning Labs CEO Elizabeth Stark has explicitly cited increasing demand for USD machine-to-machine payments from AI agents and the L402 protocol as a primary driver for bringing stablecoins to Lightning. L402 is the oldest active HTTP 402 implementation, with five years of production deployments, a formalized spec under bLIP-0026, and a credible path to stablecoin settlement via Taproot Assets. It proved the HTTP 402 handshake worked and that AI agents are a natural fit. Built entirely on Bitcoin and Lightning, L402 represents one distinct approach to 402-native payments. ## x402 In May 2025, Erik Reppel, head of engineering at the Coinbase Developer Platform, alongside colleagues Kevin Leffew, Dan Kim, and Nemil Dalal published the [whitepaper](https://www.x402.org/x402-whitepaper.pdf) for x402: an open-source web payments protocol built on HTTP 402. Similar to L402, x402 facilitates payments between web clients and servers through a multi-step HTTP handshake, but where it differs is the rail and payment model. Though the protocol initially rolled out with USDC payments on the Base L2, it has since evolved to support payments in stablecoins or any ERC-20 token across several chains including Base, Solana, Polygon, BNB Chain, Avalanche, Sei, and Arbitrum. HTTP is the primary transport layer and the 402 status code is the native signal, though the same payment logic can run over MCP or A2A. x402 supports two core payment schemes: a straightforward pay-per-call model via the exact scheme, which transfers a fixed amount per request; and a pay-per-use model via the upto scheme, which authorizes a maximum amount upfront but only charges for actual consumption of resources. x402 plugs into existing web infrastructure as lightweight middleware, with a full reference implementation including core protocol libraries, server-side middleware for Express.js and Next.js, and client libraries for browser and Node.js environments. Server-side implementation takes a single function call, and clients can pay any supported endpoint without a prior relationship with the resource provider. An AI agent can hit a paid endpoint, receive a 402, construct a signed payload, and settle the payment without any custom payment logic needed on top. Putting together the x402 payment flow: 1. A client requests a paid resource from a server 2. The server returns HTTP-402 with machine-readable payment instructions. 3. The client constructs a signed payment payload and resubmits the request. 4. The payment is first submitted and settled onchain. 5. The settlement proof is passed back from the Facilitator to the server to confirm payment. 6. The payload is verified, and the server fulfills the original request. 7. Once confirmed, the server returns a 200 OK response alongside the requested resource and transaction proof to the client. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/1707a1fbac51.png) X402’s stablecoin-centric architecture removed the per-transaction price volatility present in Bitcoin-denominated micropayments. Each request is treated as a standalone payment, as the client constructs a signed payment payload, attaches it to the HTTP request, and the server verifies it onchain before delivering the resource. An agent can hit an x402-gated endpoint it had never encountered before, complete payment and receive its resource, without an API key, account creating or prior billing relationship with the server; a particularly useful feature for agents, who lack persistent memory across sessions by default. The Current State of x402 The x402 ecosystem, made up of clients, servers, facilitators, as well as supporting infrastructure & developer tooling, is actively growing. $50.7M in total volume and 172M total transactions have been processed via x402 to date, featuring 734k buyers and 148k sellers as well. [Agentic market](https://agentic.market/) currently tracks 68 active services agents that can call directly and pay for via x402. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/a7dd3983ab71.png) Interestingly, though AI agents are actively integrating x402, humans still account for the [majority of x402 payments today](https://agentic.market/?chart=payments-race). In December 2025, x402 V2 shipped, introducing reusable sessions, Permit2 support for any ERC-20 token, automatic service discovery, and resource metadata in 402 responses. On April 2, 2026, dubbed “4/02 Day,” Coinbase contributed x402 to the Linux Foundation and the x402 Foundation was formally announced. The governing body is co-founded by Coinbase, Cloudflare, and Stripe. Expressed support and membership spans AWS, American Express, Google, Mastercard, Microsoft, Shopify, Visa, Circle, Adyen, Ant International, KakaoPay, Polygon Labs, and the Solana Foundation, among others. Shortly after, AWS Bedrock published a reference implementation of x402 for financial services agents, making it the first major cloud provider to embed x402 directly into its infrastructure. For a deeper dive into x402, read [When Machines Move Money](https://www.shoal.gg/p/when-machines-move-money). ## MPP On March 18, alongside Tempo’s mainnet, Tempo and Stripe introduced the Machine Payments Protocol (MPP). Similar to L402 and x402, MPP is an open-source protocol that enabling clients to pay for web resources through a standard HTTP handshake. Unlike its predecessors, however, MPP introduces a session model that builds directly on [Liam Horne’s work](https://liamhorne.com/state-channels) on State Channels: an agent locks funds on Tempo once to open a session, makes as many subsequent requests as needed using signed vouchers offchain, and the server periodically settles the accumulated balance in a single transaction back on Tempo. The spec is open-source and accompanied by an IETF Internet-Draft ([draft-ryan-httpauth-payment](https://datatracker.ietf.org/doc/draft-ryan-httpauth-payment/)), the first formal attempt to give HTTP 402 standardized semantics through the internet engineering standards body. MPP directly builds on State Channels: two parties lock funds in a multisig contract, exchange signed transactions offchain however needed, and simply settle the net result onchain in a single transaction. This is, in fact, MPP’s key differentiator: **session-based streaming micropayments**. A “session” intent lets agents authorize a spending limit upfront, then stream micropayments as needed without onchain transactions required per each individual request that follows. The first request opens a payment channel for that specific client/agent, while subsequent requests use off-chain “vouchers”. The server periodically settles accumulated vouchers in a single batch transaction. ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/8b47b512d853.png) Putting together the entire MPP payment flow: 1. The client sends a standard HTTP request (e.g. GET /api/resource). 2. The server (running [mppx](https://github.com/wevm/mppx), MPP’s reference TypeScript SDK and server middleware) contacts Stripe, which creates a PaymentIntent and returns a deposit address from Tempo. 3. The server returns HTTP 402 with a WWW-Authenticate: Payment challenge header containing the amount, accepted methods, deposit address, and a challengeId. 4. The client then fulfills the payment, which can be done either by signing a stablecoin transfer on Tempo; completing a card payment via Stripe’s Shared Payment Token; or paying a Lightning invoice). 5. The client retries the original request with an Authorization: Payment header containing the payment credential. 6. The server forwards the credential to Tempo for onchain verification. 7. Once verified, the server returns 200 OK with the requested resource and a Payment-Receipt header. Importantly, for session-based flows, steps 2-7 only happen on the first request. Subsequent requests skip the chain entirely: the agent sends a signed voucher, the server verifies the signature locally, and delivers the resource. MPP also provides a native MCP transport binding, which AI agents use to discover and invoke tools. If an agent calls a paid tool on an MCP server, the payment handshake happens inside the tool call itself via JSON-RPC error code -32042 (the MCP analog of HTTP 402), meaning the agent pays and receives the result within the same function call. MPP is rail-agnostic by design, supporting stablecoin payments on Tempo, a high-performance L1 offering ~500ms finality, sub-cent fees, and stablecoin-denominated gas fees; credit and debit cards via Stripe’s Shared Payment Token; and Bitcoin via Lightning. Anyone can define a new payment method by publishing a spec against the MPP framework without permission from its creators. The Current State of MPP ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/8e119818a0f6.png) At the time of writing, MPP has processed ~$103k in volume and ~710k transactions across 68k agents and 2.7k servers in total. MPP launched with an impressive list of design partners including Anthropic, OpenAI, DoorDash, Mastercard, Visa, Nubank, Revolut, Shopify, and Standard Chartered. At launch, 100+ MPP-compatible services were listed in the payments directory. Services are specifically designed to be consumed by agents; Claude chat completions, headless browser sessions, containerized compute, onchain data queries across 80+ networks, domain registration, and SEC filing search. Live integrations include Browserbase, QuickNode, Parallel Web Systems, and PostalForm. Cloudflare’s Agents SDK provides full MPP support. Because anyone can publish a new payment method spec against MPP, the protocol’s future is no longer restricted to the capabilities of Tempo and Stripe. ### Emerging Developments Around HTTP 402 x402 and MPP are the most active implementations of the 402 primitive today, but they are not the only ones. A broader ecosystem of teams has been building around HTTP 402, each approaching the same underlying problem from a different angle. - **Cloudflare**implements HTTP 402 in its **[pay-per-crawl](https://developers.cloudflare.com/ai-crawl-control/features/pay-per-crawl/what-is-pay-per-crawl/) f**eature. When an AI crawler requests a page on a Cloudflare-protected site, Cloudlfare returns a HTTP-402 with a crawler-price header, the crawler retries with a crawler-exact-price header, Cloudflare serves the content and logs the billing event. Publishers set a flat per-request price and can allow, charge, or block any crawler independently. Importantly, pay-per-crawl is in closed beta, but the initiative demonstrates HTTP 402 running at Cloudflare-scale between web content owners and AI agents. - **EVMAuth,**built by Radius Tech is a Solidity smart contract (deployable to any EVM chain) that extends ERC-1155 to paygate web resources behind token ownership. It integrates HTTP 402 directly: when a client requests a gated resource without the required token, the server returns 402 with instructions to purchase the access token onchain. The client buys the token, retries with proof of ownership, and gets access. Tokens can represent subscriptions, API credits, time-limited licenses, or any access tier. For agents, this means access rights are portable onchain assets. - **OKX’s Onchain OS Payment** is built directly on x402; When a client requests a paid resource, the server returns HTTP 402 with payment requirements. The client pays onchain and retries with a payment credential in the header. Settlement runs on X Layer, OKX’s native L2, where OKX subsidizes gas fees for clients. - **H402:**H402, built by BitGPT, is an open-source fork of x402 with a five-stage deterministic payment lifecycle: Quote -> Authorize -> Broadcast -> Validate -> Settle. It extends x402 to include Bitcoin and Lightning Network payments alongside EVM chains and Solana, and features USDT support. Notably, unlike x402, H402 charges a 0.25% protocol fee per payment. - **x402z**, co-authored by Mind Network and Zama, is building an agent-to-agent privacy-based payment solution, specifically built on Fully Homomorphic Encryption (FHE). Summarily, FHE enables computation on encrypted data without requiring decryption; applied onchain this enables validators to validate transactions (e.g. sufficient balance, valid signature) without seeing the amounts or balances. x402Z is built on Zama’s FHE stack, uses ERC-7984 (Confidential Token Standard) for encrypted transfers, and is currently in closed testnet. **An Important Consideration: Security Implications of HTTP** ![](https://shoal.xyz/research/writing/http-402-how-machines-move-money/img/5321d7d79328.png) The security risks of HTTP 402 payments were being debated in 2012, when early Bitcoin developers raised the concern that a malicious server could use a 402 response to silently trigger payments without user awareness. The counterargument then was that HTTPS mitigates interception and that payment authorization should sit in a dedicated client rather than the browser. That debate was never quite resolved, but it’s important to consider now as HTTP 402 adoption starts to pick up via L402, x402, and MPP activity. HTTP transmits data in plaintext, and any intermediary between client and server, a router, a proxy, a compromised network node, can read and potentially modify what is being sent. HTTPS was created to solve this by wrapping HTTP in TLS encryption, making data in transit unreadable to anyone intercepting it. For payments this matters because payment credentials, wallet addresses, signed payloads, and payment amounts all travel in HTTP headers. Importantly, HTTP 402 does not mandate HTTPS. Payment credentials, wallet addresses, signed payloads, and payment amounts all travel in HTTP headers, and whether that exchange is encrypted depends entirely on server configuration. Beyond transport security, today’s implementations carry additional known tradeoffs. Payment credentials travel as bearer tokens in HTTP request headers, meaning anyone who intercepts a valid credential can potentially reuse it. A signed payment payload could theoretically be extracted and front-run; wherein a signed payment payload could theoretically be extracted from the request and submitted onchain before the intended recipient processes it. For $0.003 API calls the economic incentive to exploit this is low, but for higher-value transactions it is a meaningful gap. The IETF draft for MPP defers detailed security analysis to a future revision entirely. These are known tradeoffs, not unknown risks, but the security model of HTTP 402 payments is still a work-in-progress in its current state. Ultimately, security risk may prove to be the biggest bottleneck to the widespread adoption of HTTP 402 payments. ## Closing Thoughts We at Shoal believe the most interesting question in agent payments is not which protocol wins, but whether the infrastructure AI agents transact on ends up being designed for machines, or whether it ends up being the same rails humans use with a smarter wrapper on top. HTTP 402 is, at its core, a long-standing but mostly dormant part of the native web. It gained no traction with human-centric payments, but machines present a new opportunity. The status code’s first experiments and live implementations were based on moving value between Bitcoin miners, nodes, and content servers. Today’s implementations target AI agents, paying for goods and services on behalf of humans directly as well as in their own workflows. The thesis for HTTP 402 adoption is straightforward: the efficiency gained from expressing economic intent via HTTP is too valuable to ignore. A world in which agent payments drive meaningful volume, where tens of thousands of agents are autonomously transacting at the speed of the web across thousands of services, is only beginning to materialize. The question is what the payment infrastructure for that world looks like. Encoding payments directly into the web with HTTP 402 is one answer to that question. Whether it is the right one remains to be seen. ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* ## Sources *Data - Artemis, Dune, Github, x402Scan, MPP Scan* - @nlevine19,[x.com/nlevine19/status/2036450698271785350](http://x.com/nlevine19/status/2036450698271785350) - “Open Agentic Commerce and the End of Ads.” a16z crypto,[a16zcrypto.com/posts/article/open-agentic-commerce-end-ads](http://a16zcrypto.com/posts/article/open-agentic-commerce-end-ads) - @yq_acc,[x.com/yq_acc/status/2037579506429657198](http://x.com/yq_acc/status/2037579506429657198) - “The Intention Layer.” Fintech Brain Food,[fintechbrainfood.com/p/the-intention-layer](http://fintechbrainfood.com/p/the-intention-layer) - “The 21 Bitcoin Computer.” Earn.com,[medium.com/@earndotcom/the-21-bitcoin-computer-1d28d652b57b](http://medium.com/@earndotcom/the-21-bitcoin-computer-1d28d652b57b) - “two1 3.5.0.” PyPI,[pypi.org/project/two1/3.5.0](http://pypi.org/project/two1/3.5.0) - “two1-python Payment Decorator.” 21dotco,[github.com/21dotco/two1-python/blob/master/two1/bitserv/django/decorator.py](http://github.com/21dotco/two1-python/blob/master/two1/bitserv/django/decorator.py) - “True Micropayments with Bitcoin.” Earn.com,[medium.com/@earndotcom/true-micropayments-with-bitcoin-e64fec23ffd8](http://medium.com/@earndotcom/true-micropayments-with-bitcoin-e64fec23ffd8) - “Buy 50 APIs with Bitcoin in the 21 Marketplace.” Earn.com,[medium.com/@earndotcom/buy-50-apis-with-bitcoin-in-the-21-marketplace-1fbf5208e397](http://medium.com/@earndotcom/buy-50-apis-with-bitcoin-in-the-21-marketplace-1fbf5208e397) - “L402 Protocol Documentation.” l402-protocol,[github.com/l402-protocol/l402/tree/main/docs](http://github.com/l402-protocol/l402/tree/main/docs) - “L402 Protocol Specification.” Lightning Engineering,[docs.lightning.engineering/the-lightning-network/l402/protocol-specification](http://docs.lightning.engineering/the-lightning-network/l402/protocol-specification) - “x402 GitHub Repository.” x402 Foundation,[github.com/x402-foundation/x402](http://github.com/x402-foundation/x402) - “x402 Documentation.” Coinbase,[docs.cdp.coinbase.com/x402/welcome](http://docs.cdp.coinbase.com/x402/welcome) - “MPP Overview.” Tempo,[mpp.dev/overview](http://mpp.dev/overview) - “State Channels.” Liam Horne,[liamhorne.com/state-channels](http://liamhorne.com/state-channels) --- # When Machines Move Money > What do payment rails in an agentic economy look like? - Publisher: Shoal Research (https://shoal.xyz) - Category: Agentic Payments - Published: 2026-03-24 - Canonical: https://shoal.xyz/research/writing/when-machines-move-money/ - Keywords: agentic economy, AI agents, x402, yield, security, Agentic Payments ![](https://shoal.xyz/research/writing/when-machines-move-money/img/2b3f2a137818.jpg) *A special thanks to [Lucas](https://x.com/OnchainLu) and [Kevin](https://x.com/kleffew94) for their feedback and review.* *In 1849, tens of thousands of men went searching for gold in California. Some made out to be kings. Most made out poor. But the greatest success fell upon the merchants building picks and shovels: the foundational tools that would remain important so long as there was gold in the ground. Today’s gold rush is AI. Payments are becoming a foundational part of AI agent workflows, and inevitably, the rails facilitating those payments become today’s picks and shovels. In this paper, we dive deep into the x402 protocol; one particular emerging open agent-native payment rail, including what it is, how it works, where adoption stands today, and what open questions face x402 when machines move money.* ## A Seismic Shift Is Underway History is defined by seismic shifts. Sudden, profound transformations that change the very foundation of life itself. The physical geography we inhabit today was formed some 175 million years ago when the Earth’s tectonic plates shifted and broke apart. Tectonic plates are still shifting today, albeit much slower, but the biggest seismic shifts in the modern world have materialized through human innovation. Foundational inventions, be it the Sumerian wheel, the Gutenberg press, the steam engine yield a similar reinforcing flywheel: humans build machines, these machines yield economic surplus, which leads to more money for building more machines (and better ones at that) which further compounds the output. As technology improves, the cost of experimentation falls while the rate of iteration increases. We’ve seen this dynamic accelerate particularly within the last few decades with computers and the applications and services built around them. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/26e27e10e6af.png) Today this transformative dynamic is materializing through software, particularly artificial intelligence. AI has been around for a long time. The [first paper on neural networks](https://www.cs.cmu.edu/~epxing/Class/10715/reading/McCulloch.and.Pitts.pdf) was published as far back as 1943. Expert systems in the 80s and statistical machine learning in the 90s quietly embedded AI into production workflows, from credit scoring to ad targeting. Spam filters, recommendation engines, and fraud detection have been running on machine learning models since the early 2000s. What changed is the interface. Generative AI lets humans interact with these systems through free-form natural language, and that shift in accessibility is what brought AI into mainstream consumer markets. OpenAI launched ChatGPT as a simple and intuitive way to interact with its underlying GPT models, which reached 1 million users in 5 days and 100 million in 2 months, the fastest consumer internet adoption in history. Shortly after competing generative AI applications (e.g. Gemini, Claude, Grok) started rolling out, and the ensuing competition drove major AI labs to quickly improve models and ship new product features. On a darker note, fears of job displacement have mounted as corporate executives [continue to iterate](https://www.cnbc.com/2025/10/22/ai-taking-white-collar-jobs-economists-warn-much-more-in-the-tank.html) reducing headcount and increasing investments in AI (though it’s worth noting over half of US workers today are working jobs which didn’t exist in 1940). No one can state with certainty how AI will ultimately reshape society. But as of late 2025, roughly one in six people worldwide have used generative AI, a technology that barely existed three years ago. While early, a seismic shift is well underway. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/e097057ed1a7.png) But there’s only so much to be done by simply talking to AI. Read access, e.g. letting LLMs look things up, condense large bodies of text, write code, analyze data, is evidently useful but only goes so far. But pairing that with write access, in other words letting AI actually do things across external environments, has unlocked an entirely different set of capabilities. In 2025, OpenAI rolled out Operator and Codex, Anthropic shipped Claude Code, Perplexity launched Comet, Google embedded Gemini-powered agents across Workspace applications, Microsoft pushed Copilot deeper into Office and Windows. Perplexity, Cursor, Sierra, and Cognition each raised hundreds of millions in new funding and reached new all fun highs in revenue. It’s clear that agents will define the next chapter in how humans interact with AI. But an overlooked reality is that autonomous agents have been driving economic activity online for years. The digital ads marketplace is one massive agentic economy operating beneath the surface of nearly every ad-supported webpage (which includes most large consumer sites and platforms today). ![](https://shoal.xyz/research/writing/when-machines-move-money/img/dcf08a69fb49.png) Whenever someone loads a site, the empty ad space is put up for sale in a mini-auction, and agents operating on behalf of advertisers (this could be any merchant selling goods online) determine how much that ad space is worth to them and submit bids. The highest bid wins and the winning ad is rendered in the slot, within hundreds of milliseconds. By the time the site loads, the ad is already displayed. To put this scale into perspective, consider that programmatic digital ad spend amounts to hundreds of billions annually, which accounts for [over 90% of display ad budgets today](https://www.emarketer.com/content/worldwide-programmatic-ad-spending-2025). Crawlers are another example. These autonomous agents roam the web, follow URLs, fetch webpages, and feed that content into large-scale indexing and training pipelines. Similarly, scrapers extract raw data from webpages and are actively used in a variety of fields today. On a darker note, “bad bots”, programs set up to exploit business logic online, accounted for as much as 37% of internet traffic in 2025. Collectively, over half of all web traffic is already run by autonomous software agents. Yet evidently, few people know about these agents, and even fewer actually use them. However useful these agents may be at their particular function, e.g. bidding for ad space, their utility is limited by their purpose-built nature. A crawler crawls, a scraper scrapes, a bidder bids, and nothing more. When these different capabilities are stacked together into one single program, controlled from one single interface, the nature of the application changes entirely. This is where the general-purpose AI agents most people know today come in. Their most foundational change is their ability to perform many different tasks and operate across multiple apps and environments within one interface. These agents were designed to accelerate human output and productivity: they do more things, at a much greater rate, and as their adoption grows, they generate an ever larger share of web traffic. So what is exactly an agent? In simple terms, a goal-oriented software program which receives a goal, identifies the steps needed to achieve that goal, and takes action within certain environments using tools available at its disposal to achieve that goal. A user types a prompt, which is then delivered to an agent’s runtime environment. From there, the agent provides a prompt to its model, which makes decisions and functions as the brains of the operation. The agent uses any available tools it may have access to (i.e. web browsers, APIs, databases, calendars etc) to carry out these tasks, and then carries out a cycle of absorbing information from its actions, reasoning about the information, and using this information to determine its next action or decision until the defined stopping point (e.g. the goal specified in the user prompt) has been reached. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/5e894f7fbac0.png) Gartner [predicts](https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025) roughly 40% of enterprise applications will have task‑specific AI agents embedded by the end of 2026. [McKinsey estimates](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-automation-curve-in-agentic-commerce) AI agents account for $3–5 trillion of global consumer commerce by 2030. Goldman Sachs projects that by 2030, agents could erode meaningful TAM for SaaS by becoming a primary interface for knowledge work even as they expand the overall software market. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/30045ab6f2ce.png) Of course, these are forecasts and not facts, and [some predictions about the immediate impact of agents](https://blog.samaltman.com/reflections) have already proven to be too ambitious. Nonetheless, it is difficult (and naive) to ignore the size of the bet being made here: if AI agents are to capture even a fraction of their predicted growth, they start to become consumers. And consumers need, first and foremost, a way to pay for the goods and services they wish to purchase. ### Machines Need To Move Money And so the role of money comes up. Money is a coordination tool: a shared medium of exchange and unit of account that enables humans to coordinate with strangers and settle transactions efficiently. It enables human societies to cooperate at scale; to compound individual effort into part of a greater productive whole. As AI agents take on more economic responsibilities, they too require access to this shared coordination layer. But agents are a structurally different kind of consumer, with different behavioral patterns and optimization criteria. They don’t face the same cognitive or computational constraints as humans. Their very purpose is to multiply human output by magnitudes: more work, in far less time, though often through more frequent and granular consumption of resources along the way. Agents also aren’t susceptible to the emotional appeals that advertising deploys on human consumers. They are, by design, economically rational actors. In this context, money plays a familiar but functionally extended role. As a medium of exchange it minimizes transaction friction, enabling seamless value transfer between agents. As a unit of account it provides the standardized measure agents need to conduct precise cost-benefit analyses, evaluating whether the compute cost of a task justifies its expected reward. And as a store of value it allows agents to preserve purchasing power and allocate capital efficiently across time and tasks. To make use of these functions, however, we must distinguish between the asset itself and the infrastructure that moves it. Money is a coordination tool but payments are its mechanism of action. Stripped to its core, a payment is a way to settle an obligation: the process of reconciling a ledger to prove that value has actually changed hands. For an agent, this is the functional execution of a contract. It is the step that converts a decision into a realized outcome, unblocking access to a resource. Without this settlement capability, an agent is effectively stuck in a read-only state. Agents need a designated way to pay for goods and services online. ### But Machines Already Move Money? To state the obvious,**this is already possible**. AI agents already have access to infrastructure which trillions of dollars already move online every year through. These systems are built around what we can call **checkout-specific flows**. A (human) user confirms their purchase intent, a payment token is created for that transaction, and the merchant processes the payment through their respective PSP infrastructure. Take OpenAI and Stripe’s Agentic Commerce Protocol (ACP) for example. ACP is an o[pen‑source API specification](https://github.com/agentic-commerce-protocol/agentic-commerce-protocol) that enables AI agents to complete purchases on behalf of users by standardizing how merchants expose their catalogs, how agents represent offers and carts, and how payment details are delegated back to the merchant’s PSP once the user confirms intent. The clearest implementation of ACP today is Instant Checkout in ChatGPT, powered by Stripe’s Shared Payments infrastructure. Through intuitive natural language language prompts, users can take care of shopping needs (e.g. buy running shoes, order takeout, book reservations) from the familiar ChatGPT interface. On the backend, ChatGPT delivers a scoped payment token to the merchant’s PSP, and the merchant charges for the payment. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/f5e335196019.png) Beyond ACP, agent payments are growing as the agentic commerce stack begins to form. Claude Code and Codex run workflows using prepaid balances on user accounts. OpenClaw takes this one step further and enables virtual cards with spending limits to be issued to an agent. Google’s UCP and AP2 use payment tokens linked to user credit cards and email addresses. This system works. It prompts no immediate reinvention. For human-agent checkout flows, this model performs exactly as designed. ### Machines Do Move Money, Just Not Autonomously However, the point that really matters here is that this is not the the final form for agentic payments. This model becomes strained when applied to continuous agentic workflows at scale. This emerging ecosystem is what has [been characterized](https://arxiv.org/abs/2509.10147) as a “**virtual agent economy”**: a set of linked digital markets where AI agents transact with one another to generate economic value independently of human labor. Critically, in such an economy, agents transact and coordinate at scales and speeds beyond direct human oversight. And this is where key economic and technical constraints begin to emerge within today’s commerce stack. Protocols like ACP use legacy payment mechanisms: credit cards, digital wallets, BNPL services. Consumers and merchants using these protocols still absorb their economics: 2.9% + $0.30 per transaction, multi-day settlement, 120-day chargeback windows. Annoying but manageable for humans. Agents, however, transact at a far greater scale. Agentic systems routinely decompose complex problems into granular distributed tasks worth fractions of a cent. Applied across thousands of steps, the cost structure collapses; consider that a $0.30 fixed fee on a microtask worth, say $0.02, is already a 1,500% markup. Ultimately, this stems from a deeper architectural issue. As Felipe Montealegre articulates in **[Internet Finance](https://x.com/TheiaResearch/status/1876618725547233417?s=20)**, modern financial systems are just collections of private servers. Moving value requires permissioned administrators to reconcile entries across those servers, a process reflected in settlement delays and layered fees. When an AI agent initiates a purchase via a protocol like ACP, a synchronous chain follows: the request routes to Stripe, which routes to issuing banks. Stripe has its fee layer, Visa and Mastercard have theirs, banks have theirs. Each operates independently. The efficiency of this reconciliation mechanism sets the speed limit for the entire economy. A [2024 BIS report](https://www.bis.org/statistics/payment_stats/commentary2402.pdf) found that a one-percentage-point increase in digital payment adoption corresponds to a 0.10 percentage-point rise in GDP per capita growth over two years. If removing friction for humans produces that, the implications for agents operating orders of magnitude faster are larger still. There is also a less visible cost: permission itself. Legacy rails were designed around discrete human-to-human purchases with meaningful transaction sizes (e.g. at least a few dollars’ worth). The compliance architecture built on top, KYC, AML checks, chargeback systems, correspondent banking, reflects rational responses to legal liability at that scale. A $0.004 API call carries different risk than a $50,000 wire transfer, but today’s rails treat them with similar overhead. [Nick Szabo identified](https://nakamotoinstitute.org/library/micropayments-and-mental-transaction-costs/) a related problem in 1999: mental transaction costs, that is, the cognitive burden of deciding whether a small purchase is worth making. Early micropayment businesses failed not because the technology couldn’t handle small payments, but because humans had to consciously approve each one. Agentic systems appear to solve this. Claude Code draws from a pre-funded account and proceeds without interrupting the user. But this is a proxy with a budget, not an autonomous economic actor. The agent’s economic range is fixed at setup by its human operator. It cannot negotiate access to new resources, acquire capabilities outside what was pre-provisioned, or carry any economic identity beyond the session. Szabo’s problem reemerges as a ceiling on what the agent can do. Another key constraint agents encounter with legacy payment rails is **identity**. In existing human:agent checkout flows, agents essentially borrow their user’s identity to transact. The entire stack assumes the payer is a person with a legal identity, bank relationship, and personal liability, which agents have none of (at least not yet). When Claude Code makes a payment it does so via its user’s Stripe credentials, the merchant’s fraud model, the card network’s chargeback rules, and the bank’s settlement framework. This also creates unresolved legal questions. How does an agent run an AML check? File a suspicious activity report? Screen for sanctions violations? There may soon be answers to these questions, as this issue is now gaining recognition at the federal level. NIST’s National Cybersecurity Center of Excellence just [published a concept paper](https://www.nist.gov/news-events/news/2026/02/announcing-ai-agent-standards-initiative-interoperable-and-secure)on AI agent identity and authorization, identifying it as an unsolved infrastructure problem requiring new open-source future standards. Human-agent checkout flows are genuinely useful. But in their next evolution – an economy of AI agents – cost, autonomy, and identity are three constraints existing systems cannot reconcile. Multi-day settlement and the absence of 24/7 global rails add further friction, though these are secondary to the structural issues above. Solving these constraints starts with understanding how AI agents actually work. Agents are software, they run on the web, therefore perhaps the most natural place to look for a payments layer is within the web itself. ``` POST /merchant/transfers/payment HTTP/1.1 Host: payments.example.com Content-Type: application/json Content-Length: 402 { "payment_transfer": { "reference": "PAYMENT123456", "amount": "1337", "currency": "EUR", "sender_account_uri": "pan:5299920000000149;exp=2020-08;cvc=123", "sender": { "first_name": "Amelia", "middle_name": "Rosenburg", "email": "test123@sender.example.com" }, "recipient": { "first_name": "Tyrone", "middle_name": "Johnston", "email": "test123@example.com", "merchant_id": "123" }, "authentication_value": "ucaf:jJJLtQa+Iws8AREAEbjsA1MAAAA", } } ``` *[An example](https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Status/402) of calling a payment API using a POST request to initiate a transaction via HTTP-402.* HTTP 402 was reserved decades ago but never implemented. It anticipated a world where payment could be handled at the protocol level, the same way authentication is handled today. It was simply missing two things needed to make it real: a defined standard, and a form of money that could move at web speed. ### We Already Have Web-Native Payment Rails Just as HTTP moves information freely and permissionlessly across the internet, global value transfer on public blockchain rails is already happening at a meaningful scale. Tens of trillions have already been moved in stablecoins. Circulating stablecoin supply sits at over $308B today. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/02e20a7628ca.png) [Mckinsey and Artemis Analytics](https://www.mckinsey.com/industries/financial-services/our-insights/stablecoins-in-payments-what-the-raw-transaction-numbers-miss) tracked stablecoin payment volume at $390 billion in 2025, more than double from the year prior, with volume concentrated in B2B and P2P payments, card-linked spending, and B2C payouts. Though most onchain stablecoin activity has historically been trading-driven, chain-specific data shows payment demand emerging as a distinct and growing share. A stablecoin in its simplest terms is software programmed to maintain the value of a stable unit of exchange, most commonly the US Dollar. A piece of software known as a smart contract is called, and in turn a stablecoin, is either minted or redeemed. Several key properties that make these bits of software uniquely suited for web-native payments, particularly in agentic commerce. The economic advantage is the most obvious. Stablecoin transactions are orders of magnitude cheaper than legacy payment rails because there is no intermediary taking a cut. A stablecoin transaction is a redistribution of balances on a shared digital ledger. The primary resource consumed is the computing power required to update that balance, paid as a gas fee. Gas fees across most major chains now sit in the sub-cent range. Against the transaction fees associated with credit cards, the cost differential is stark. A more distinctive advantage is programmability. As [Hadfield and Koh](https://arxiv.org/abs/2509.01063) point out, agents need “programmable money” to achieve the kind of autonomous cooperation required for complex economic activity at scale. Stablecoins are issued and redeemed via smart contracts in which payment conditions can be encoded directly: conditional releases, payment limits, recurring transfers, etc. Agents can control wallets through cryptographic keys and sign transactions directly, which removes the need for human credentials at the payment layer. Haseeb Qureshi makes the sharper point: [crypto is better suited for agents than it is for humans](https://x.com/hosseeb/status/2024136762424185208?s=46). An agent can verify transaction details, audit smart contract code, and confirm settlement in seconds. It does not need to trust a counterparty’s legal representation or a jurisdiction’s enforcement mechanism. Code on the other hand is deterministic: given the same inputs, it always produces the same outputs. A smart contract that says “release payment when condition X is met” will release payment every single time condition X is met, enforcement is built into execution. An agent entering an economic agreement via smart contract knows exactly what will happen under every possible condition before it signs. It can read the code, verify the logic, and confirm the outcome in milliseconds. A stablecoin is just code. A wallet is just code. An agent can hold funds, transact, and enter economic agreements as naturally as it sends an HTTP request. ### The Missing Piece HTTP 402 defines how a server signals that a resource requires payment. Stablecoins provide money that can move at web speed. Together, they start to look less like a checkout flow and more like an HTTP handshake. Consider a vending machine. It provides one specific item, a soda or a candy bar, but only in exchange for the exact payment amount. The operator does not need to produce anything it sells. It simply provides neutral infrastructure that lets willing buyers access a resource. This is the model for web-native agentic payments. An agent makes a request, the server responds with a payment requirement, the agent provides payment, and the resource is unlocked. HTTP 402 provides the status code. Stablecoins provide the settlement layer. The missing piece is what ties them together: a web-native vending machine. ## x402: A Web-Native Payment Rail In May 2025, Erik Reppel, head of engineering at the Coinbase Developer Platform, published a [whitepaper](https://www.x402.org/x402-whitepaper.pdf) co-authored with colleagues Kevin Leffew, Dan Kim, and Nemil Dalal that gave HTTP 402 its first real implementation in 29 years: the x402 protocol. The idea, which this paper takes as its central premise, was simple: the internet has always needed a native way to send and receive payments, and stablecoins now make that possible. Coinbase had been exploring internet payment standards since 2015, but even then the idea was ahead of its time. By May 2025, the conditions had finally aligned. Onchain fees cost fractions of a penny on chains like Solana and Base. Stablecoin supply had grown rapidly and was approaching $300 billion. Agentic commerce had materialized into something concrete enough to build for. ## What is x402? x402 is an open-source payments protocol that standardizes how web clients and servers exchange value using HTTP 402 and stablecoins. It is, in the most literal sense, the missing web-native vending machine: a buyer makes a request, a seller names a price, and payment clears directly through HTTP without a pre-established relationship between the parties. At its core, x402 separates three things: transport, which is how data moves between parties; payment logic, or the scheme by which value moves; and the settlement network where that value lands onchain. This separation is what makes x402 extensible. HTTP is the primary transport and the 402 status code is the native signal, but the same payment logic can run over MCP or A2A without touching the underlying standard. In practice, x402 plugs into existing web infrastructure as lightweight middleware. Server-side implementation takes a single function call. A client can pay any supported endpoint without a prior relationship with the resource provider. ## How Does x402 Work? In summary, the x402 payment flow works like this: 1. A client requests a paid resource from a server 2. The server returns `HTTP-402` with machine-readable payment instructions. 3. The client constructs a signed payment payload and resubmits the request. 4. The payload is verified, and the server fulfills the original request. Note, the payment is first submitted and settled onchain, and the settlement proof passed along via the Facilitator to confirm payment. 5. Once confirmed, the server returns a `200 OK` response alongside the requested resource and transaction proof to the client. There are certain steps involved in which the details vary by specific chain architecture, as we will expand on below. But importantly, each step maps to a specific component split across two layers: an offchain layer where communication occurs, and an onchain layer where payment settles. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/3278ae1cd1e4.png) ### The Communication Layer x402 is transport-native by design. While HTTP is the primary implementation, the protocol complements existing data transportation without mandating additional requests outside a typical client-server flow. Any request-response based system can implement x402 payment flows, which means x402 runs across HTTP for web APIs and REST services, MCP for AI agent tools and resources, and A2A for direct agent-to-agent payments. The primary offchain components are the client and the server, which apply across all supported transport layers. The client represents the buyer: the entity requesting access to a paid web resource. This can be a human developer making calls through an HTTP client library, or an AI agent operating as a web client. A client sends the initial request, constructs a valid payment payload, and retries the request with a Payment-Signature header containing the signed payload. The server represents the seller, or resource provider. Usually an API or content endpoint, but ultimately any digital resource accessible via a supported network. The server responds to client requests with payment requirements, verifies incoming payment payloads, and returns the resource once the transaction confirms. For agents, no separate integration is required per transport layer. Payments are handled automatically across HTTP APIs, MCP tools, and A2A interactions. ### The Onchain Layer The onchain layer of the x402 protocol is where payment occurs. This consists of a wallet to hold funds and authorize payments, a Facilitator service to verify payloads and submit payments onchain, and the stablecoin or token contract which actually moves between parties. To execute payments with x402, a client needs a funded cryptographic wallet. A wallet is a public-private key pair. The public key is a pseudonymous identifier that functions as the client’s onchain address, analogous to a routing number. The private key authorizes the client to sign and execute transactions, analogous to a password. When an agent needs to access a paid resource, it constructs a payment payload by signing a transaction authorization with that private key. The signed payload includes the public key so the server can verify the sender and confirm the transaction onchain independently. To settle payments onchain, a server uses a Facilitator. A Facilitator is a transaction relay and gas abstraction service: it receives a signed payment payload, validates it against the token contract’s authorization parameters, and broadcasts the transfer onchain on the server’s behalf, covering gas costs in the process. When a server receives a signed payment payload, it can either handle onchain settlement directly or POST the payload to the Facilitator’s `/settle` endpoint. The Facilitator validates the cryptographic signature against the token contract’s authorization parameters, calls transferWithAuthorization the token contract, covers gas from its own balance, and broadcasts the transaction to the network. Critically, the Facilitator is not a custodian. It executes a transfer that was already cryptographically authorized by the client’s signature. It cannot redirect funds or modify payment terms; it can only execute or reject what the client already signed. Coinbase runs a Facilitator on Base and Solana for USDC payments, but the role is open. Any server can run its own verification logic locally if it prefers not to outsource. ### x402: EVM vs Solana The HTTP handshake in the x402 payment flow is identical across chains. What differs is the onchain settlement mechanism, which is downstream of the architectural differences between EVM-compatible chains and Solana. On **EVM-compatible** chains, x402 uses [EIP-3009](https://eips.ethereum.org/EIPS/eip-3009)as its core token transfer primitive. EIP-3009, authored by Coinbase engineers Peter Jihoon Kim, Kevin Britz, and David Knott in 2020, quietly facilitates tens of billions in monthly USDC transfer volume. The key mechanic is the separation of authorization from execution. EIP-3009 provides a single-use cryptographic signature created offchain, authorizing a specific transfer of a specific amount to a specific address within a defined validity window. That signature becomes the payment payload in x402. There are two main functions involved here: `transferWithAuthorization` and `receiveWithAuthorization`. The client signs a structured EIP-712 message containing the payment details and a random 32-byte nonce. Using random nonces here lets multiple payment authorizations be created in parallel without ordering constraints. When the server receives the Payment-Signature header, validation is a deterministic checklist: verify the recipient address matches, the payment amount meets the requirement, the token contract is an accepted asset, the validBefore timestamp hasn’t expired, and the EIP-712 signature is cryptographically valid. Because authorization is separated from execution, the server validates the signed payload before submitting anything onchain. An invalid signature, mismatched amount, or expired timestamp gets rejected at zero cost to either party. If all checks pass, the server or its Facilitator calls transferWithAuthorization on the token contract. The Facilitator covers gas from its own balance, which is why the client only needs to hold the payment asset rather than the chain’s native gas token. Once confirmed, the server returns the requested resource alongside a transaction hash and block number the client can verify independently. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/03f2b1f1842a.png) **Solana** On Solana, x402 uses a different settlement mechanism that reflects how transactions are structured on the chain. Rather than an offchain EIP-712 signature authorizing a future transfer, the client constructs and partially signs a full SPL token transfer transaction using Ed25519 signing, then encodes it as a base64 payload in the Payment-Signature header. The transaction is partially signed because the client signs the transfer instruction while designating the Facilitator as fee payer, a role that requires the Facilitator’s own signature before the transaction can be broadcast. Before building the transaction, the client queries the Facilitator’s /supported endpoint to get its fee payer address and confirm support for the requested network. The Facilitator then receives the partially signed transaction, validates it, adds its own signature as fee payer, and broadcasts it to the network. The client pays in USDC without needing to hold SOL for gas. Both the EVM and Solana flows achieve atomic settlement through different primitives native to each chain. The EVM flow uses an offchain signature authorizing a future transfer the Facilitator executes; the Solana flow uses a partially built transaction the Facilitator completes and broadcasts. Beyond the mechanics, each chain carries practical advantages. EIP-3009 shifts gas costs from clients to servers, who accept this because payment amounts structurally exceed gas fees. For agents making repeated calls to the same endpoint, servers can batch multiple authorizations into a single transaction, spreading the fixed base gas cost across payments. The authorization-execution split also enables payments in low-connectivity environments: a client can construct and sign an EIP-712 message locally without network access and transmit it when connectivity resumes. Solana’s architecture is optimized for throughput, making it better suited for higher-frequency payment patterns. That said, x402 is chain-agnostic. The protocol uses CAIP-2 network identifiers so the same handshake handles routing across Base, Solana, Polygon, Scroll, and Avalanche. The server specifies which networks and assets it accepts in the 402 response; the client picks from what its wallet supports. As the Facilitator landscape matures and new chains meet x402’s acceptance criteria, the protocol extends without changes to the underlying standard. ## What Does x402 Uniquely Solve? It’s worth zooming out to revisit what makes x402 valuable. The ability to transact online is becoming a foundational requirement for AI agents. As software programs that communicate via HTTP and consume web resources continuously, paying for things is central to how they operate. The problem is that the infrastructure underpinning something so fundamental to their function wasn’t built for them. In human-agent checkout flows, agents transact through human infrastructure, borrowing credentials and depending on intermediaries designed for a different kind of consumer. x402 runs on the same web-native rails agents already operate on. The differences are structural. Cost is the most obvious one; gas fees for stablecoin transactions on the chains x402 currently supports (e.g. Base, Solana) cost fractions of a cent, and represent the only transaction costs within the traditional x402 payment flow. This matches the granular economics with which AI agents operate at (e.g. per-call, per-task etc); which quickly breaks down with a 2.9% + $0.30 fee charged per transaction. Settlement goes deeper. Because payment conditions are enforced at execution, a transaction cannot finalize unless predefined terms are met. The rails enforce this through code, so the agent doesn’t need to know or trust the counterparty. This is the difference between post-hoc verification and preemptive execution, and it’s what makes delegation to high-stakes workflows safe. An operator defines spending constraints once: daily caps, per-transaction limits, whitelisted addresses. The agent executes within them without requiring approval on each call. Beyond cost and settlement, there’s identity. Every transaction an agent makes is signed by the same cryptographic wallet address, a consistent and verifiable identifier it owns and controls. Rather than borrowing a human’s credentials for each new service, the wallet travels with the agent, standardizing how it shows up across every interaction. ### But in practice, why do these advantages even matter? Granular pricing structures, e.g. Pay-per-article, pay-per-video, pay-per-stream, were always the intuitive business models for digital content. The early web was built with that vision in mind, but it never materialized because transaction costs made small payments uneconomical and the c[ognitive overhead of approving each one made them exhausting](https://nakamotoinstitute.org/library/micropayments-and-mental-transaction-costs/). Granular pricing can actually match how content is actually consumed rather than bundled into subscriptions that most users only partially use. For AI agents, granularity is a necessity to how they consume resources in discrete, measurable units (inference per prompt, market data per query, compute per job, API calls per task.) It’s difficult to map these naturally onto subscription pricing, which exists largely because per-unit micropayments weren’t viable. At fractions of a cent per transaction, they are. x402 can also help reshape the software market for agents. Historically, accessing a capability meant either paying a subscription or building it yourself. As inference costs fall, building is increasingly viable. x402 introduces a third option: an agent mid-workflow can access a capability instantly, paying only for what it uses, rather than spinning up inference to replicate it. The most expansive implication is what happens to how products get structured. Goods and services are bundled largely because transaction costs make granular pricing impractical. A news article packages interviews, photos, and context together because selling each piece individually wasn’t worth the overhead. An AI agent, meanwhile, can track what a user has already read, coordinate with a content provider to surface only what’s new or relevant, and pay for exactly that. The same logic extends to any digital product with separable components. As micropayments make individual pieces of content economically viable, agent-to-agent commerce could give rise to a retrieval ecosystem where content creators get compensated per use and users get something closer to a personalized product than a standardized one. This extends to how AI agents actually move through a workflow. When an agent hits a paywall mid-task, the server returns a 402 with machine-readable payment instructions. The agent constructs a signed payment payload, settles onchain, and continues. The workflow never stops for manual authorization. The only prerequisite is a funded wallet, which the operator provisions once upfront. This becomes particularly relevant in multi-agent systems or swarms. Modern agentic workloads increasingly decompose across specialized agents that coordinate through handoffs: one agent calls another, which calls a service, which calls another agent. When payments need to flow through that same graph, a central billing relationship can become an operational bottleneck. x402’s stateless design means each hop settles independently, such that the payment layer scales with the workflow rather than sitting above it. All of this is straightforward to integrate. x402 ships with a full reference implementation: core protocol libraries, server-side middleware for Express.js and Next.js, and client libraries for browser and Node.js environments. Server-side integration is a single function call. An agent can hit a paid endpoint, receive a 402, construct a signed payload, and settle onchain without any custom payment logic written on top. With that in mind, let’s take a look at the current state of x402 adoption today. ## The Current State of x402 x402 launched on May 6, 2025, initially supporting USDC on Base. In the nine months since, the protocol has processed 164m total transactions worth $46.4m in volume, across 447k unique buyers and 89k sellers in total. That growth was not linear; at its peak on November 17, [x402 drove 19% of Base’s 17 million daily transactions](https://x.com/artemis/status/1991206550136815908), a striking demonstration of how quickly the protocol could saturate a single chain’s activity. Since then, amid a broader pullback in onchain and crypto market activity, transaction volume has declined meaningfully, although there has been a meaningful resurgence in transactions and volume count in March once again. What the data tells us, and what it doesn’t, is worth examining closer. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/3e47d9d44306.png) X402 is a chain-agnostic framework that’s live on a small but growing number of chains today. Base accounts for the majority of x402 activity to date — 125m transactions and $39m in volume — a feat driven in no small part by its early-mover advantage, as well as being home to Coinbase’s native facilitator infrastructure, and the deepest facilitator ecosystem on the protocol with 27 active facilitators. Solana came online in July 2025 and has processed 38m transactions and just under $7m in volume to date. By early February 2026, Solana was gaining rapid share of transaction count (and volume?), accounting for as much as 97% of daily transaction share on February 2nd. Nonetheless, Base still hosts a much larger share of buyers (423k buyers vs Solana’s 23k) and sellers (68k vs Solana’s 20k), suggesting Base still dominates on the demand side even as Solana captures a growing share of transaction count. Beyond Base and Solana, x402 is actively expanding support to new chains, now live on Polygon, Avalanche, Sei, Optimism, and Arbitrum. These chains are live but collectively still account for a small fraction of activity relative to Base and Solana. It is too early to tell where the most x402 activity will settle, but the answer is far more likely to depend on a specific application on a specific chain rather than the infrastructure of the chain itself. The facilitator landscape meanwhile,has grown alongside the protocol. Coinbase remains dominant by transactions (78m) and volume ($27.3m), and it’s worth noting their Facilitator offers a zero-fee structure and has a first-mover position. But the ecosystem has started to diversify; PayAI, Dexter, Daydreams, and Virtuals Protocol are among the more active third-party facilitators, which collectively account for the majority of facilitator transactions and volume in more recent months. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/8f669b49187e.png) But not all agent activity is as it seems. For instance, despite the recent craze around Moltbook, a viral social network exclusively for AI agents which drew lots of coverage about millions of agents posting and coordinating their own lives, [much of this early activity was revealed](https://www.technologyreview.com/2026/02/06/1132448/moltbook-was-peak-ai-theater/) to be agents pattern-matching through trained social media behaviors, with humans involved in many cases. The same scrutiny applies to x402. Artemis Analytics distinguishes between real and gamed transactions in its [x402 dashboard](https://app.artemisanalytics.com/asset/x402/?tab=deep_dives), gamed transactions being indicative of wash trading. [One explanation](https://x.com/OnchainLu/status/2017304611095253412?s=20) for the incentive to game transactions with x402 is launching a memecoin, driving transaction volume to climb the x402scan leaderboard, and converting that visibility into token buyers. Though x402 went live in May 2025, the first major surge in activity only took place a few months later around early Q4 ‘25. Much of this activity was memecoin-related however; throughout much of November and early December, gamed transactions accounted for a larger share of total transactions than real transactions. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/fa5ae6e29d66.png) However, as total x402 transactions have declined in the past few months, real transactions are starting to account for a larger share of total transaction count. February saw 5 straight days in which real transactions accounted for 100% of total count. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/74df9ae1506d.png) Gamed transactions do help stress-test infrastructure, validate settlement mechanics, and prove throughput at scale. But financial incentives and the downstream activity of those incentives dilute the assessment of the quality of x402’s adoption. Whether they are memecoin-related, airdrop farming-related, or otherwise, the bottom line is that gamed transactions represent behavior optimized for financial incentive rather than organic x402 utility. But numbers, as useful as they are, only tell so much. For a more holistic overview of x402 adoption to date, it’s worth looking at the x402 ecosystem. ### The x402 Ecosystem The x402 ecosystem is made up of the various participants in the x402 payment flow. Clients represent the buyers making requests for web resources to paid endpoints (e.g. AI agents), Servers are the services and paid endpoints (APIs, data providers, content platforms, and any digital resource exposing a paid route via x402), Facilitators are various third-party services handling payment verification and onchain settlement for Servers, and supporting infrastructure and tooling covers any SDKs, analytics, wallets, and developer tooling that make building on x402 practical. ![](https://shoal.xyz/research/writing/when-machines-move-money/img/7e37cb0c4311.png) Much of the x402 ecosystem is still early, but the range of service partner integrations and experiments being built on top of the protocol offers a glimpse into its surrounding excitement and interest across different industries and fields. ### x402 Within The Broader Agentic Commerce Stack It’s important to zoom out and recognize that agentic commerce is a wide-ranging multi-layered stack that intersects across several industries. Discovery, consent, checkout, and agent coordination are each being handled by different protocols involving a number of the biggest players across the tech and finance sectors. On the commerce side: we touched on **ACP** earlier, which defines how AI agents handle the shopping flow on behalf of human users from product discovery through checkout. Critically, ACP is designed to be processor-agnostic, meaning merchants can plug in whatever payment provider they already use. **Google’s UCP**(Universal Commerce Protocol) serves a similar purpose for Google’s ecosystem: it standardizes how agents operating inside Google Search and Gemini discover products, negotiate offers, and complete purchases on a user’s behalf. Where ACP is optimized for conversational interfaces like ChatGPT, UCP is designed to work across Google’s broader range of products. The Agent Payments Protocol (AP2), also from Google, sits one layer down from both of these, handling authorization specifically. Before an agent can spend money, AP2 generates a cryptographically signed mandate confirming that a real user authorized this agent to spend up to X for purpose Y. Every transaction gets a tamper-proof record tied to that mandate, which gives merchants and financial institutions an auditable trail to verify the transaction was legitimate. Google’s A2A, now maintained by the Linux Foundation with over 100 supporting organizations, handles a different problem entirely: how agents from different companies and platforms talk to each other. When an agent built by one vendor needs to hand off a task to an agent built by another, A2A provides the common language for that coordination. X402 complements this stack in several ways. Google and Coinbase built the A2A x402 extension as a production-ready module within AP2 specifically for agent-based stablecoin payments. The split is clean: AP2 provides the authorization mandate, confirming the agent has permission to spend; x402 executes the actual per-call transfer once that mandate is in place, settling in USDC onchain. Cloudflare added x402 into its Agents SDK and MCP server tooling, so any tool or API exposed via MCP can require a 402 payment before granting access. In practice, an ACP-driven assistant might discover a service via MCP, see that the endpoint returns a 402, get operator budget approval, and settle via x402 on every subsequent call while ACP manages the overall order and recordkeeping. Legacy payment networks have been getting involved with agentic payments too. Visa launched the [Trusted Agent Protocol](https://github.com/visa/trusted-agent-protocol) to help merchants identify and verify AI agents during checkout, particularly to distinguish a legitimate shopping agent from a malicious bot. Trusted Agent Protocol gives verified agents a cryptographic signature they can present to merchants during browsing and checkout, built on Cloudflare’s Web Bot Auth infrastructure and backed by partners including Microsoft, Stripe, Shopify, and Worldpay. Visa is working with Coinbase to ensure Trusted Agent Protocol is interoperable with x402. Mastercard launched Agent Pay the same month with its own merchant verification framework: tokenized agent credentials that let merchants register and authenticate AI agents before any transaction clears. While Mastercard has not announced a direct x402 integration, it is a named AP2 partner, and [Cloudflare is working with Mastercard](https://blog.cloudflare.com/secure-agentic-commerce/) on the same Web Bot Auth infrastructure that underpins x402’s authentication layer. Stripe is another major player that’s been actively ramping up development efforts around agentic payments. In February 2026, Stripe launched Machine Payments in preview, with x402 via USDC on Base as the first supported method, letting developers bill agents for API calls, MCP requests, or HTTP endpoints through the standard PaymentIntents API: the same infrastructure merchants already use for card payments. Alongside this, Stripe introduced Shared Payment Tokens: scoped, time-limited credentials that let agents initiate payments without exposing underlying account details, which non-Stripe merchants can forward to their own processors. On March 18 the same PaymentIntents API was reintroduced as the foundation for the [Machine Payments Protocol](https://mpp.dev/)(MPP), a new open standard for agentic payments launched alongside Tempo’s mainnet. MPP encodes the same HTTP 402 signaling mechanism as x402 and targets the same fundamental problem but introduces two architectural differences: a “sessions” primitive that lets clients deposit funds into an onchain escrow once and sign offchain vouchers per-request, and multi-payment rail support, featuring native stablecoin settlement on Tempo with Visa, Lightspark, and Stripe extending MPP to cards, Bitcoin Lightning, and fiat methods as well. x402 and MPP, unlike x402 and other agentic commerce protocols e.g. ACP/ UCP/A2A, are more adversarial than they are complementary. Tempo raised $500M from Stripe and Paradigm, and launched with merchants wielding lots of distribution power including Visa, Mastercard, Anthropic, OpenAI, and Shopify. Their competitive dynamics are worth diving deeper into a future paper; however it is worth acknowledging here that the two protocols are compatible. Cloudflare’s documentation confirms MPP is backwards-compatible with x402: existing x402 flows map directly onto MPP’s “charge” intent, and Stripe supports both. What’s important to understand with all these different agentic commerce protocols is their division of labor. ACP and UCP enable AI agents to handle online shopping experiences on their human user’s behalf. AP2 handles authorization and audit. Visa and Mastercard handle merchant-facing trust and agent verification. Stripe is working to abstract developer integration across all of it. **x402 sits at the execution layer** **of the stack**: it’s a neutral payment API that any agent, any service, any developer can implement in a few lines of code, with no merchant account, processor agreement, or card network required. When an agent hits a paid endpoint (i.e. a raw API call, an MCP tool, or an HTTP resource gated by Stripe’s Machine Payments) the server returns a payment request in the HTTP response, the agent pays in stablecoins, and the request completes. The money moves, the workflow goes on. Onchain rails simply match the granularity of AI agent economics with greater cost, speed, and programmability than legacy payment infrastructure. ### Coinbase Coinbase authored x402 and remains its primary infrastructure provider. Coinbase published the open specification, shipped the reference SDK, and runs the dominant facilitator service. The CDP facilitator processes payments on Base and Solana and currently handles the majority of x402 volume. Beyond infrastructure, Coinbase’s distribution plays a critical role in x402’s success. [Payments MCP](https://docs.cdp.coinbase.com/payments-mcp/welcome) is the most significant piece. It packages x402, an embedded non-custodial wallet, and an onramp into a single MCP server that Claude, Gemini, Codex, and other LLMs can connect to directly. A developer can go from zero to a transacting agent without an API key or manual setup. Complementary to this are [Agentic Wallets](https://docs.cdp.coinbase.com/agentic-wallet/welcome): wallets purpose-built for agents with programmable spending limits, gasless transactions on Base, and a CLI for agent management. Together, Payments MCP and Agent Wallets products form a vertically integrated stack to help developers get started with building on x402. ### Major Integrations Coinbase also co-founded the x402 Foundation with Cloudflare, which has been actively involved with x402; having integrated the protocol into its Agents SDK and MCP tooling to allow MCP-exposed tools to be 402-gated and paid per-call. The practical implication of this shouldn’t be understated; any server using Cloudflare (roughly 20% of all web traffic globally) can become a paid x402 endpoint without modifying backend code. Amazon Web Services (AWS) is also an x402 Foundation ecosystem member and has published a reference architecture showing how x402 [can be layered onto existing HTTP infrastructure using CloudFront and Lambda@Edge](https://builder.aws.com/content/38fLQk6zKRfLnaUNzcLPsUexUlZ/monetize-any-http-application-with-x402-and-cloudfront-lambdaedge). In that flow, CloudFront acts as a global reverse proxy while Lambda@Edge runs payment verification logic at the network edge: when a request arrives, Lambda@Edge checks for a valid payment signature; if missing, it returns an HTTP 402 challenge. The architecture applies x402 to any origin without touching backend code, whether hosted on AWS, GCP, Azure, or on-premise. One of the more interesting capabilities this integration unlocks is the ability to to charge bots while keeping access for human users free. More broadly, this integration means x402 isn’t a crypto-native tool that requires rebuilding infrastructure around it; rather it easily fits into the cloud stack enterprises already run. Privy added native x402 support, wrapping the full payment flow without browser extensions, seed phrases, or gas tokens. This includes detecting 402 challenges, signing payment authorization with the embedded wallet via a custom useX402Payment React hook, constructing the X-PAYMENT header, and retrying the request. Users only need USDC in their wallet on Base or Base Sepolia; facilitators absorb gas. Privy is also exploring policy-engine integrations for programmable spend controls at the domain, agent, and workflow level, running off-chain. Developers building with Privy can add x402 payment flows without building a wallet layer from scratch, plugging into the 90 million accounts Privy powers today. ### X402 and ERC-8004 An important emerging complement to x402 is [ERC-8004](https://eips.ethereum.org/EIPS/eip-8004), an Ethereum standard co-authored by teams at MetaMask, the Ethereum Foundation, Google, and Coinbase, including x402’s own Erik Reppel. Both standards treat AI agents like first-class citizens in a new emerging virtual economy; where x402 provides payments infrastructure, ERC-8004 is designed to provide reputation and identity infrastructure. The standard is made up of three lightweight onchain registries: Identity, which gives each agent a portable, globally unique identifier via ERC-721; Reputation, which maintains an onchain audit trail of client-authorized feedback; and Validation, which supports cryptographic or crypto-economic proof that a task was actually executed correctly. Together they function as an open credit score and track record for AI agents. The integration with x402 creates a recursive loop. An agent discovers a service via the ERC-8004 identity registry, checks its reputation and validation history, makes an API call, receives an HTTP 402 code, pays via x402, and submits payment proof back into the reputation registry as a verifiable feedback signal. This way, each transaction helps strengthen the trust record. Over time this enables more sophisticated economic relationships: agent-native credit systems, outcome-based lending, constrained capital deployment where an agent doesn’t receive free funds but specific, verifiable capability. **X402x** [x402x](https://www.x402x.dev/) (short for x402-exec) is a programmable settlement framework built on top of x402 that turns payment into a complete execution primitive. Where the base x402 protocol handles payment routing, x402x combines payment verification, business logic execution, and facilitator incentives in a single atomic transaction. Standard x402 settles in 500-1100ms across a two-phase flow; x402x reduces that to 200-500ms via a Gateway contract that executes verification, authorization, token transfer, fee deduction, and nonce marking atomically. It adds four hook execution points — beforePayment, afterPayment, beforeBatchPayment, afterBatchPayment — enabling merchants to inject custom TypeScript logic for credential verification, subscription checks, NFT minting, loyalty point distribution, or complex settlement logic without modifying the core protocol. Batch settlement aggregates up to 100 payments per transaction, reducing per-payment gas costs by approximately 92%. A configurable platform fee mechanism gives facilitators an economically sustainable model. Critically, x402x is not a protocol replacement in any way, rather it is a production extension layer that runs fully compatible with the x402 specification. **T54** [T54](https://www.t54.ai/) is building a trust and risk layer for agentic commerce on top of x402. [x402-secure](https://www.t54.ai/x402-secure) is an open-source SDK and proxy layer that adds pre-transaction risk assessment, verified identity, and liability attribution to x402 payments. The system is powered by Trustline, T54’s own risk engine, which captures an agent’s reasoning traces and attaches them to the payment flow as verifiable evidence. Before a transaction settles, independent validators analyze the agent’s reasoning chain, behavioral patterns, and context to produce a risk score. The practical effect is that both buyers and sellers get auditable proof-of-agent intent, which opens a path toward dispute resolution and clearer liability in a protocol that is otherwise irreversible by design. T54 also shipped [Claw Credit](https://www.claw.credit/), an agent-native credit product built on x402 that allows agents to build a credit profile through usage and repayment to then unlock higher spending limits over time. T54’s agentic infrastructure is supported on Base, Solana, and XRPL. ### Experiments and Early Builders Beyond the major integrations, a scrappier layer of builders is exploring what x402 enables in practice. Conway Research’s [Automaton](https://web4.ai/) is among the most striking examples: an open-source AI agent that owns a cryptographic wallet, pays for its own compute costs in USDC via x402, earns revenue by building and deploying products, and funds child agents when profitable. The agent runs on Conway’s MCP-compatible terminal infrastructure, integrates with Claude Code, Codex, or OpenClaw, and ceases to function if it cannot earn enough to cover its operational costs. Daydreams built [xGate](https://xgate.run/?q=) as an agent-native discovery layer for x402-enabled endpoints, alongside Lucid Agents, a commerce SDK that bootstraps agents with native x402, A2A, and ERC-8004 support. Developers have built [self-generating task markets](https://x.com/lordofafew/status/2015946619469103453?s=46) where agents post, discover, and pay for work autonomously. Agents can now [buy their own web domains](https://x.com/0xsigil/status/2022496075203121199?s=46)with x402. Some builders are [experimenting with x402 and OpenClaw](https://x.com/murrlincoln/status/2018706075403309163?s=46). There’s [agents](https://x.com/faircaster/status/2021612305117585604?s=46) already using x402 for financial operations entirely through x402-gated endpoints: portfolio queries, market data pulls, swap execution. Privacy is another open frontier. Onchain rails make every x402 transaction publicly observable: payment flows, cost structures, and purchase intent permanently recorded on a public ledger. Correlating onchain timestamps with server-side metadata is enough to reconstruct behavioral profiles over time, which becomes a nonstarter for enterprise workflows where any AI agent handles sensitive information. Several teams are working on solutions: [x402Z](https://x402z.mindnetwork.xyz/), a collaboration between Zama and Mind Network, uses Fully Homomorphic Encryption combined with the ERC-7984 Confidential Token standard to validate transactions without revealing amounts, balances, or intent; Fhenix402 takes a parallel approach using CoFHE, performing computation on encrypted data without decrypting it; Aztec, Payy Network, and Miden, through their respective distinct architectural approaches, feature private settlement embedded natively at the protocol layer. With multi-chain support a core part of the x402 V2 spec, there is a direct path forward for adoption on privacy-native onchain rails. New AI releases ship every single day, and what’s exciting about x402 is how boring it is: a simple neutral framework doing exactly what it says. That simplicity is what makes it universally applicable. In a world where agents transact autonomously at scale, the payment primitive underneath all of it may be the most important infrastructure layer no one is talking about. That said, a reality check is in order. ## Looking Ahead ## Open Questions And Important Considerations x402 and agentic commerce more broadly are still early. The protocol works, the ecosystem is growing, and there is undeniable value in micropayments and API-native monetization But the full picture requires both internal development and external adoption to materialize in parallel. Standards like MCP and agentic payment flows still need to mature, and adoption among merchants and payment processors is an external force that no one controls on a fixed timeline. X402 is not the first attempt to solve machine-native payments over onchain rails, and that history is worth holding onto when evaluating the open questions below. Balaji Srinivasan’s work at 21.co proved in 2013 that the concept of machine-readable micropayments was sound: Bitcoin payment channels could, in theory, enable devices to pay each other autonomously. The infrastructure wasn’t ready: Bitcoin transaction costs made sub-cent payments economically incoherent. L402, developed by Lightning Labs nearly a decade later, got further. It proved the technical viability of the HTTP 402 status code for payment-metered APIs and built real tooling around it. It failed for infrastructure reasons specific to its stack (e.g. Lightning’s statefulness, Bitcoin’s volatility, the two-sided cold-start problem) not because the underlying idea was wrong. X402 fixes each of those specifically: USDC replaces volatile pricing, Base’s L2 removes channel management, and the facilitator model collapses the integration barrier to a single line of code. But some of the obstacles that slowed L402 including discoverability, compliance, and merchant behavior change have not been solved by upgrading the underlying infrastructure. The following are a few of the biggest questions concerning the adoption and success of x402. **Will credit cards adapt fast enough to make stablecoins unnecessary?** Whether its incumbents can actually be disrupted remains the defining question for x402’s role within agentic payments more broadly. Card networks have largely survived every predicted disruption for fifty years, from PayPal to Apple Pay to crypto, by adapting just enough, just in time. Credit card infrastructure is already deeply embedded, improving rapidly, and both Visa and Mastercard are actively building agent-specific payment frameworks. Agents already transact over card rails today. Virtual agent cards with programmable spending limits and backward compatibility with existing merchant infrastructure are an emerging middle path, which notably requires no stablecoin or crypto exposure whatsoever. If the major card networks lower fees, add programmable controls, and extend their rails to machine-native flows, the cost advantage of stablecoin settlement narrows. Of course, card networks have built their entire business model on per-transaction fees and interchange, and there is no obvious incentive to destroy that margin to serve a new virtual economy that has not yet fully materialized. Stablecoins are also structurally more programmable, globally accessible, infinitely divisible, and require no chargebacks. The bigger question is whether the friction of crypto adoption is lower than the friction of waiting for card networks to adapt. It’s worth noting the x402 V2 explicitly added support for legacy payment rails including ACH, SEPA, and card networks. As per the spec, x402 is an open standard for internet native payments which specifically “aims to support all networks (both crypto & fiat) and forms of value (stablecoins, tokens, fiat)”. Even if card networks adapt fast enough to close the cost gap, x402 is designed to work with whatever settlement layer wins. **The crawling and discoverability problem** This is a structural oversight x402 shares with L402, and it has no clean solution yet. Search engine crawlers do not have wallets. When they hit an HTTP 402 response, they treat it as a blocked page. Google’s own documentation confirms that 4xx status codes cause it to stop indexing affected URLs over time. Content protected by x402 is effectively invisible to the open web. Search engines will not index it and will not surface it in results. Partial mitigations exist. Serving free previews to unidentified crawlers and using structured data to signal paywalled content are both established practices, borrowed from how publishers handle subscription paywalls today. But they add complexity, reintroduce the two-tier access model x402 was designed to eliminate, and don’t translate cleanly to pure API endpoints with no human-readable content to preview. The longer-term resolution may not come from fixing x402’s relationship with search engines at all. If agents increasingly discover services through other agents, AI interfaces, and protocol-level registries rather than search crawlers, the relevant discovery layer shifts entirely. The SEO problem matters a lot if x402 adoption depends on organic web discovery; much less so if agents find services through agent registries, MCP directories, and AI-native discovery layers instead. **Regulatory and compliance risk** L402 stalled partly on compliance friction: accepting Lightning payments without a regulated gateway created AML exposure most businesses were unwilling to take on, compounding the existing adoption challenges Lightning already faced. x402 faces a version of the same problem, with a more explicit split. Coinbase’s hosted facilitator includes KYT screening and OFAC checks on every transaction, inheriting Coinbase’s existing compliance stack. A merchant routing payments through that facilitator sits in a position analogous to using Stripe or PayPal: not a money services business, not directly exposed to AML liability. The tension emerges at the edges. Operators running self-hosted facilitators that take custody of assets or perform fiat conversion will, under conservative FinCEN and state interpretations, likely fall into MSB territory and face full BSA compliance requirements. The protocol is designed to be permissionless. The compliance infrastructure is not. If the facilitator layer becomes permissioned enough to satisfy regulators at scale, it concentrates gatekeeping in a way that undermines the protocol’s neutrality. If it stays permissionless enough to be genuinely open, it will likely hit the same OFAC and sanctions walls that complicated L402 adoption. This is the same unresolved tension that has slowed stablecoin adoption in enterprise contexts for years. x402 does not resolve it, nor is that a failure of Coinbase’s execution. It is a protocol-level constraint: a permissionless payment standard operating in a world that requires permissioned compliance at meaningful scale. Coinbase’s facilitator is currently the most practical answer to that constraint, providing production-ready KYT and OFAC coverage that lets merchants transact without building compliance infrastructure themselves. The open question is what happens as the facilitator ecosystem diversifies and traffic routes through operators without Coinbase’s compliance stack. **Who is liable when an agent makes a bad payment?** Hadfield and Koh raise [another structural problem](https://arxiv.org/abs/2509.01063) sits underneath all of agentic commerce: current legal systems assume humans can monitor and control their agents, but that assumption breaks down as autonomy increases. When an agent using x402 overspends, sends funds to the wrong address, or is manipulated into paying a malicious endpoint, the liability chain is genuinely unclear. The protocol is irreversible by design. There is no chargeback. The facilitator verified the transaction. The agent acted within its programmed parameters. This matters more because the same underlying models are deployed across many firms simultaneously. Hadfield and Koh warn that AI agent errors may be more correlated than human errors for precisely this reason: when agents share architecture, training data, or model weights, their failure modes cluster. The 2010 Flash Crash offers the clearest prior example of what correlated automated behavior produces at speed. Algorithmic trading systems briefly erased nearly $1 trillion in market value in under 36 minutes, not because any single actor failed catastrophically, but because systems trained on similar data responded to the same signal in the same way at the same time. The market recovered that day. Human regulators and exchange circuit breakers intervened at 2:45 PM when the CME halted trading for five seconds, breaking the feedback loop. x402 has no protocol-level circuit breaker. Operators can enforce spending limits and whitelisted addresses at the application layer, and most current deployments still have humans setting those constraints upfront. But as agent autonomy increases and human oversight recedes by design, the window for intervention narrows. A correlated error that propagates through thousands of agents simultaneously would settle onchain before most oversight mechanisms could respond. The settlement finality that makes x402 useful is the same property that makes a cascade hard to stop **What does the future of x402 governance look like?** Coinbase and Cloudflare announced their intent to co-found the x402 Foundation in September 2025, with a stated mission of neutral, open governance. The structure makes sense as a distribution partnership: Cloudflare is one of the largest internet infrastructure providers globally, and Coinbase provides the stablecoin infrastructure and L2. Cloudflare CEO Matthew Prince acknowledged the dynamic directly, saying “Coinbase deserves immense credit for starting the work on the x402 protocol” while framing the Foundation as the path to independent governance. But Coinbase is also the dominant facilitator, the author of the spec, the operator of the reference SDK, the issuer of USDC on Base, and a publicly traded company with shareholders. That is a significant concentration of involvement in a protocol designed to be a neutral payments layer for the broader web. The Foundation has stated it will welcome additional members from e-commerce platforms, AI companies, and payment providers through an open application process, but as of this writing no formal governance documentation, bylaws, or membership charter has been published. Open source software has produced some of the most durable infrastructure in the world. Linux is the canonical example, but the Linux Foundation publishes its bylaws, board structure, and membership tiers publicly. The x402 Foundation has not yet done the same. Governance neutrality requires more than a stated mission. It requires structural commitment: published documentation, a clear roadmap for decentralizing facilitator infrastructure, and a governance model that doesn’t concentrate spec authority with the entity that also controls the dominant facilitator, the primary stablecoin, and the reference chain. None of that has materialized yet, as admittedly the Foundation is still young, but much of the difference between x402’s stated aspiration and its real-world impact lies in how effectively it can be governed and led over time. **The advertising fork in the road** In January 2026, OpenAI announced it would begin testing ads in ChatGPT’s free tier, with the first placements appearing in February. The move is understandable financially given OpenAI’s [well-documented rate of burning cash](https://www.businessinsider.com/openai-profitability-analyst-investor-opinions-funding-ipo-2026-2), but it surfaces a deeper question about how the agentic economy gets monetized. If the dominant AI interfaces become advertising-supported, agents face a structural conflict of interest. An agent that recommends a product because a merchant paid for placement is acting as a distribution channel, not in the interest of the end user. OpenAI says ads will not influence ChatGPT’s answers, but whether that holds at scale, under commercial pressure, over years, is a different question. X402 and infrastructure like it represent an alternative model: agents complete transactions efficiently enough that the economic model does not require selling user attention. But the advertising flywheel has proven itself across every major internet platform for thirty years and generates hundreds of billions annually. The question is whether open payment rails can generate enough revenue fast enough to compete. **From attention economy to preference economy** This extends into something more structurally interesting. Today’s digital economy runs on advertising because there are more products than consumers have time to evaluate, and ads capture attention to guide transactions. In an agentic world where assistants interact with millions of services on behalf of consumers, attention becomes a less constrained resource. What matters more is the algorithm that matches assistants to services. If strong central intermediaries once again dominate the matching layer, some form of paid prioritization (analogous to today’s advertising) will certainly influence rankings. The truly scarce and valuable resource in that world is not attention. It is high-quality human feedback on goods and services: the signal that distinguishes good services from bad ones, that trains better agents, and that creates a preference flywheel rather than an attention one. The key question is whether agent-to-agent commerce happens inside closed walled gardens controlled by a few dominant providers, or through an open web of agents that freely connect and transact. The answer will determine whether x402 and protocols like it become foundational infrastructure or a niche payment rail inside someone else’s ecosystem. **But merchant adoption doesn’t grow on trees** 162 million transactions is a real number, but the majority of that volume flows through Coinbase’s own ecosystem and a small cluster of developer tools and crypto-native APIs. The harder test is whether mainstream API providers, SaaS companies, and non-crypto businesses add x402 alongside their existing subscription and API key models. Cloudflare’s network position reduces the technical barrier significantly, but the ecosystem needs merchants who have a genuine reason to prefer per-request stablecoin settlement over Stripe. That case gets stronger as agent traffic grows, but it is not proven yet. **And markets don’t form spontaneously** A useful corrective from [Strange Loop Canon](https://www.strangeloopcanon.com/p/will-money-still-exist-in-the-agentic): markets form under coercion or coordination, and when they do exist, strategic sophistication determines who wins depending on how agents are configured. Alignment problems do not disappear just because agents can negotiate with each other. An AI agent economy running on x402 still requires discovery, trust, and security infrastructure among interacting agents. Whoever controls the dominant discovery layer — the mechanism by which agents find services and counterparties — holds enormous structural power regardless of how neutral the payment rail underneath it is. The payment layer is necessary but not sufficient. The governance of the layers above it matters just as much. There are also several unresolved infrastructure problems that compound the challenges facing x402. The facilitator model has no sustainable economics built in at scale: Coinbase’s CDP charges $0.001 per transaction after a free tier of 1,000 monthly transactions, but third-party facilitators are largely running at zero fees with no clear revenue path. Two-phase settlement adds 500 to 1,100 milliseconds of latency per payment, which compounds quickly: an agent making 100 API calls in a single workflow carries over a minute of payment overhead before any work gets done. And EIP-3009 exclusivity means USDT — the largest stablecoin by market cap — remains incompatible with x402 entirely. Tether’s newer USDT0 variant addresses this technically, but it requires users to hold a different version of an asset they already own. BitGPT built h402 explicitly to preserve the protocol schema of x402 while ensuring the team isn’t “limited by someone else’s tech stack or product roadmap” — a signal that the developer community has noticed these gaps and is hedging against them. Zooming out, x402 is early, the infrastructure is maturing, and most of these problems have plausible paths to resolution. What they collectively suggest is that x402’s current traction has mostly come from developer-native use cases where friction is low and tolerance for rough edges is high. The harder test is whether the same architecture holds at the scale of HTTP and the web as we know it today. ## Closing Thoughts The protocols that matter most rarely announce themselves. TCP/IP had no launch event. HTTP wasn’t pitched as the infrastructure layer for a trillion-dollar economy. They became load-bearing slowly, by being the path of least resistance for enough people solving concrete problems that adoption accumulated before anyone decided it was significant. X402 is designed to be a primitive, not a standalone product. It requires one function call on the server and one signed payload from the client. There is no merchant account, processor agreement, or card network inherently required to transfer value. The implementation surface is deliberately small. Cloudflare, AWS, and Stripe aren’t endorsing x402 so much as absorbing it into infrastructure developers already use. That is what the early stages of a load-bearing protocol looks like, though institutional involvement is not the same as widespread adoption. What makes x402 especially interesting is that it is the only current option that fits how AI agents actually operate. Legacy payment infrastructure requires agents to borrow human identity, human credentials, and operate on human settlement timelines. X402 runs on the same web-native rails agents already communicate over, prices at the granularity agents actually consume resources, and settles in seconds. That asymmetry is modest today. Whether it compounds is the real question. Infrastructure like x402 “wins” when timing and adjacent development mature together. Facilitator economics need a sustainable model. Regulatory clarity around stablecoin and crypto market structure more broadly is still unresolved. Merchant adoption outside crypto-native developer tooling is not a given. The advertising model, which has monetized every major internet platform for thirty years, is already reaching into the agentic stack. And there is the stark reality that x402 may not be the HTTP-native micropayments solution that ultimately captures the agentic economy after all. The history of machine-native payment attempts is a reminder that the right idea pitched at the wrong time still fails. What is clear is that AI agents are becoming economically active participants in a new virtual economy, and the infrastructure built for human consumers was not designed for them. In any new economic movement where which applications will succeed remains genuinely uncertain, the highest ROI historically has been foundational infrastructure investments, rather than the applications built on top of it. x402 is an attempt to occupy that position: a neutral payment API, running on open rails, that any agent or developer can implement without a card network or a bank in the middle. The internet has always moved information freely. At Shoal, we believe it is inevitable that value travels the same way. But the infrastructure driving these movements matters more than any single applications built on top of them. x402 is an early attempt to get that infrastructure right, and whether it succeeds is still an open question. But x402 has one advantage its predecessors didn’t: timing. The conditions that made prior attempts at machine payment impossible, whether it be settlement costs, stablecoin liquidity, or AI agent adoption, are no longer the constraint. A virtual economy of AI agents is forming. Money will move through it. The remaining question is what the underlying rails look like when machines move money. ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* ## Sources *Data sourced from DeFi Llama, Artemis Analytics, and x402 Scan.* - “Moore’s Law: Transistors per Microprocessor.” Our World in Data, [ourworldindata.org/grapher/transistors-per-microprocessor](http://ourworldindata.org/grapher/transistors-per-microprocessor) - Hadfield, Gillian & Koh, Bryan. “Agentic AI and Law.” [arxiv.org/pdf/2509.01063](http://arxiv.org/pdf/2509.01063) - “Buy It in ChatGPT.” OpenAI, [openai.com/index/buy-it-in-chatgpt/](http://openai.com/index/buy-it-in-chatgpt/) - “Agentic Commerce Protocol Documentation.” Stripe, [agenticcommerce.dev/docs](http://agenticcommerce.dev/docs) - “AI Agents to Boost Productivity and Size of Software Market.” Goldman Sachs, [goldmansachs.com/insights/articles/ai-agents-to-boost-productivity-and-size-of-software-market](http://goldmansachs.com/insights/articles/ai-agents-to-boost-productivity-and-size-of-software-market) - “x402: A Payment Protocol for the Internet.” Erik Reppel, Dan Kim, Nemil Dalal. [arxiv.org/pdf/2509.10147](http://arxiv.org/pdf/2509.10147) - “x402 GitHub Repository.” Coinbase, [github.com/coinbase/x402](http://github.com/coinbase/x402) - “How x402 Works.” Coinbase, [docs.cdp.coinbase.com/x402/core-concepts/how-it-works](http://docs.cdp.coinbase.com/x402/core-concepts/how-it-works) - “X402x.” @yq_acc, [x.com/yq_acc/status/1987968102605484152](http://x.com/yq_acc/status/1987968102605484152) - “Fhenix402.” Fhenix, [fhenix.io/blog/fhenix402](http://fhenix.io/blog/fhenix402) - “Monetize Any HTTP Application with x402 and CloudFront + Lambda@Edge.” AWS, [builder.aws.com/content/38fLQk6zKRfLnaUNzcLPsUexUlZ](http://builder.aws.com/content/38fLQk6zKRfLnaUNzcLPsUexUlZ) - “Internet Finance.” Montealegre, Felipe. [source](https://x.com/TheiaResearch/status/1876618725547233417) - “EIP-3009: Transfer With Authorization.” Ethereum, [eips.ethereum.org/EIPS/eip-3009](http://eips.ethereum.org/EIPS/eip-3009) - “Why the Ad Industry Isn’t Ready to Let AI Agents Spend Ad Dollars.” Digiday, [digiday.com/marketing/intentionally-being-cautious-why-the-ad-industry-isnt-ready-to-let-ai-agents-spend-ad-dollars/](http://digiday.com/marketing/intentionally-being-cautious-why-the-ad-industry-isnt-ready-to-let-ai-agents-spend-ad-dollars/) --- # Block Building on Solana and the Future of Internet Capital Markets - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2026-03-20 - Canonical: https://shoal.xyz/research/writing/block-building-on-solana-and-the/ - Keywords: crypto, DeFi, solvers, market making, MEV, infrastructure, Solana, Infrastructure ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/4ba957c6e653.jpg) ## Solana’s Block-Building Environment Today Roughly every 400 milliseconds (a slot period), Solana produces a new block that updates the state of its decentralized ledger. This is what enables you to trade, interact with DeFi, and transact seamlessly. In theory, the block production process looks straightforward and seems to follow clear rules. Validators take turns being the leader (block producer) for each slot (of 400ms). The leader is responsible for gathering transactions, producing a valid block, and broadcasting it to the rest of the network. Other validators then vote to verify the block’s validity and ensure it adheres to the network’s rules. And this process goes on and on forever. ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/20e3d7995c9d.png) But in practice, every validator has its own strategy for packing transactions into those 400-millisecond blocks, and how they do so can significantly shape the user experience on Solana. It affects whether a trade goes through, whether a user gets the expected quoted price, and ultimately whether TradFi institutions can comfortably scale their onchain operations. In other words, the behavior of a small set of validators, deciding in an opaque way how to build and broadcast blocks in order to maximize short-term profit, can create ripple effects across the entire network and impact all stakeholders. At the extreme, this even puts pressure on Solana’s long-term ambition of becoming the home of Internet Capital Markets. This is a big deal, and it has sparked an increasingly heated debate around how block building on Solana should be structured to best serve the network over the long term. In this article, we’ll explore the core issues around block building on Solana, the solution Jito is proposing with BAM, and the perspective of a notable outlier in this debate: Harmonic. ### Block Building Problems Identified by Jito Jito, one of the leading infrastructure providers on Solana and a core contributor to its validator and MEV ecosystem, has spent significant time studying how validators construct blocks in practice. Given its direct exposure to validator behavior, transaction flow, and execution outcomes at scale, they are uniquely positioned to have a view on the current block-building process on Solana. Through this work, they have identified two core issues in the current block-building environment that, they argue, materially impact user experience and put pressure on Solana’s long-term vision: late packing and slot lagging, which we’ll explore in detail below. Problem number 1: Late packing Solana is designed as a high-speed streaming system. In theory, validators are expected to pack transactions continuously throughout the slot while broadcasting block data as shreds over Turbine. This allows the rest of the network to reconstruct and replay the block in near real time. However, Jito observed that some validators tend to concentrate most of their transaction packing toward the very end of the slot. The rationale behind this behavior is simple: delaying transaction inclusion as long as possible allows validators to observe more incoming transactions and, as a result, extract additional MEV or prioritize higher-paying order flow to maximize revenue per block. The issue is that this behavior is often pursued without fully accounting for the second-order effects it can have on the rest of the network. Before going deeper, let’s just look at different block-building strategies using IBRL, a new explorer released by Jito that shines a light on block packing and provides a score to assess how closely validators adhere to best practices and standards. This allows stakers to inspect how specific validators build and pack their blocks. Here we see different packing strategy from three different validator, Helius, Figment, and Galaxy: ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/0e2ab6e7032f.png) We observe drastically different block-packing strategies. In this example, Helius has the highest score, which implies stronger alignment, as its blocks are packed much more uniformly throughout the slot. In contrast, Galaxy has the lowest score and clearly exhibits a late-packing pattern. This lack of a shared standard for uniform and deterministic block packing is a real problem. We’ll explain why in a moment. But first, let’s introduce the second major issue identified by Jito: slot lagging. Problem 2: Delaying State propagation Slot lagging refers to the practice where validators modify their Proof of History (PoH) parameters to extend slot times beyond Solana’s default ~360 milliseconds. Similar to the late packing issue, the rationale is straightforward. By extending the effective slot duration, validators give themselves more time to observe incoming transactions, and pack more profitable transactions into their blocks. However, this behavior breaks an important assumption of the network: that slots progress as fast as possible and at a consistent pace. Other validators expect blocks to be produced and propagated within a tight timing window. When a leader intentionally runs longer slots, block propagation is delayed, state updates arrive late, and in some cases validators vote on the state of the network later than expected. This also means traders have to wait on new state updates which affect their operations. Even if only a subset of validators engages in slot timing games, the impact is shared by everyone: confirmation times become less predictable, latency increases, and the network drifts away from its intended high-speed streaming model. For instance, we can see that Jupiter has a much better slot timing score than Kiln. As a result, even though both validators do not show poor transaction packing behavior, Kiln still ends up with a lower overall IBRL alignment score compared to Jupiter. ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/358486f11838.png) The Downstream Implications At first glance, these behaviors may seem understandable. Validators are economic actors, and it is rational for them to optimize for short-term profit. However, in practice, late packing and slot timing games create downstream effects that harm the network as a whole and ultimately work against Solana’s long-term goals. Below are the main implications we observed: **Misaligned with Solana’s “Increase Bandwidth, Reduce Latency” vision** If there is one principle consistently emphasized by Anatoly, Solana’s co-founder and that should effectively serve as Solana’s guiding motto, it is this: “increase bandwidth, reduce latency.” However, when transaction packing becomes end-loaded and validators engage in slot timing games, Solana’s block pipeline stops behaving like a true streaming system. Even if a slot technically finishes on time, state updates are propagated late across the network. As a result, other validators end up voting later than they should, not because of their own processing delays, but because they are waiting for late-arriving data from the block producer. This increases end-to-end latency and degrades overall network efficiency, which runs directly counter to Solana’s core vision. Moreover, Solana’s consensus mechanism rewards validators for timely votes via vote credits, and there is a bounded window in which votes must be submitted to receive full rewards. While geographically clustered validators may not feel the impact of late propagation as strongly, validators that are further away from the cluster are disproportionately affected. Over time, this creates subtle pressure against geographic decentralization, as validators farther from the network’s core face higher penalties through no fault of their own. **Unfriendly market structure for market participants** From a market microstructure perspective, traditional financial markets operate in a continuous and highly deterministic environment. Orders arrive continuously and are executed on a First-In, First-Out (FIFO) basis by a centralized matching engine. This determinism allows market makers to cancel and update quotes efficiently without constantly risking being picked off. As a result, they can quote extremely tight spreads, even on trades worth millions of dollars, without relying on priority fees. Late packing breaks this determinism. When transactions are not included continuously throughout the slot, execution becomes less predictable. This increases execution variance, introduces jitter, and makes outcomes around liquidations and auctions harder to anticipate. A block-building environment that lacks uniformity and determinism is simply not suitable for sophisticated market participants. Over time, this makes it harder for Solana to onboard and retain TradFi and ultimately undermines its ambition of becoming a globally distributed NASDAQ. **Negative impact on user experience** Beyond abstract market structure concerns, late packing and slot timing games have very concrete second-order effects. Block building that maximizes rewards often does so at the expense of applications and users. When block packing is inconsistent or delayed, users face higher uncertainty around transaction inclusion. A trade that should have gone through may fail. A swap may execute at a worse price than expected. A liquidation or arbitrage transaction may miss its execution window entirely. And a trader who needs the freshest info about the next state transition is operating less efficiently. From the user’s perspective, this shows up as failed transactions, unexpected slippage, or the need to repeatedly resubmit transactions with higher priority fees. Overall, this directly impacts application reliability. If we assume that the network should improve every day, becoming faster, more reliable, and easier to interact with, then these dynamics are clearly misaligned with that goal. ## The Block Assembly Marketplace To address the block-building issues outlined above, Jito recently introduced the [Block Assembly Marketplace](https://bam.dev/) (BAM). Put simply, BAM is a new block-building architecture designed to bring verifiability, privacy, and programmability to Solana’s transaction pipeline. Instead of allowing each validator to independently decide how to pack and order transactions (often in short-term, profit-maximizing ways, as discussed earlier), validators can delegate transaction scheduling to specialized external BAM nodes. These nodes operate inside Trusted Execution Environments (TEEs), which provide strong cryptographic guarantees that the ordering logic is executed exactly as specified. In other words, validators still validate and vote on blocks, but BAM nodes handle transaction ordering in a way that is verifiable, auditable, and tamper-resistant. The logic behind this is that BAM’s ordering is designed to optimize Solana’s long-term potential by bringing uniformity and determinism to the block-building process and helps create a healthier market structure. Specifically, BAM is designed around several key properties: 1. BAM nodes receive transactions from clients and schedule them according to transparent, verifiable ordering rules. 2. BAM nodes forward transaction sequences to the leader . 3. The leader executes the transactions exactly in the order they were received, produces the block, and broadcasts it to the network. 4. BAM nodes verify execution results match the forwarded sequences. Leaders who insert or reorder transactions are disconnected. ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/2ab88dd5e9b7.png) BAM’s structure is designed to provide transaction ordering which is verifiable and enforced by secure hardware. Since launch, [BAM](https://bam.dev/explorer/) has seen over 122m SOL staked, capturing 28.9% of total Solana stake and 367 validators running BAM. At a high level, Jito proposed a structural shift in how block building works on Solana by creating a more predictable, fair, and deterministic execution environment with BAM. However, this has also sparked debate within the ecosystem. Some teams argue that this approach gives Jito too much influence over block building and could centralize power around a single infrastructure provider. From their perspective, BAM risks becoming a de facto monopoly over transaction ordering rather than a neutral coordination layer. This pushback is important, as it has brought alternative viewpoints into the discussion. Notably, one of the strongest responses came from Harmonic, a competing Solana block-building solution developed by the Temporal team. ## Harmonic’s Approach To Block-Building Harmonic works as an aggregation layer that runs multiple block builders in parallel, where each builder constructs its own version of the block and the validator picks whichever one best fits its preferences. In addition to Harmonic, the Temporal team also operates Nozomi, a transaction landing service, and more notably HumidiFi, a leading prop AMM on Solana, having an established presence across multiple layers of Solana’s transaction supply chain. At a high level, Harmonic’s core disagreements with Jito center around what should be optimized, how it should be measured, and who gets to define the standards in Solana’s block building environment. **Concerns around monopoly dynamics and metric neutrality** One of Harmonic’s core criticisms is that Jito plays multiple roles at once: infrastructure provider, BAM architect, and creator of the IBRL scoring framework. From Harmonic’s perspective, this creates an inherent conflict of interest. They argue that IBRL does not measure “good block building” in a neutral way, but instead measures compliance with Jito’s preferred architecture, and thereby penalizes competing approaches. But we will see that this claim is nuanced. **Disagreement on “late packing”** Harmonic also strongly disputes the claim that their blocks rely on late packing in the sense described by Jito. According to them, the IBRL scoring framework misses a key detail: Harmonic blocks are packed continuously by block builders running parallel block-building processes. Transactions only appear in the final ticks because that is when the auction resolves, not because block construction is delayed. From Harmonic’s perspective, it is not fair that IBRL penalizes this behavior simply because it looks less smooth on the surface. **The only metric that matter for Harmonic: execution** From Harmonic’s perspective, best execution is the only metric that truly matters if Solana is to become the home of Internet Capital Markets. On that front, they argue that BAM does not deliver the optimal outcome. They claim that when looking at execution data across DEX programs, Harmonic shows the strongest results: validators running Harmonic repeatedly outperform the cluster baseline on both mean and median throughput. For them, this is the clearest measure of best execution, and this is what Solana ultimately needs. **Innovation through competition** Harmonic’s final argument is that only open competition can sustainably drive innovation in block building. From their perspective, it is far easier for stakers and validators to hold multiple competing block builders accountable than it is to keep a single dominant architecture in check. Prematurely converging on one standard risks locking in suboptimal design choices and slowing innovation over time. Harmonic argues that Solana should remain a free market for block-building innovation, where different approaches compete on execution quality. In that way, they see BAM as an attempt to consolidate block building around Jito’s architecture in order for them to preserve its leading position. As an alternative, Harmonic advocates for a Proposer–Builder Separation (PBS) model on Solana. The goal here is to split block production into two distinct roles. Block builders compete to construct blocks, and validators, acting as proposers, no longer build blocks themselves, and instead, choose from blocks submitted by these competing builders. The idea is to reduce excessive proposer power and create an open marketplace for block building. In theory, this should improve execution quality, limit monopoly control, and allow innovation to emerge organically, rather than being dictated by a single block-building architecture. ### Nuancing the Debate The debate between Jito and Harmonic highlights an important and healthy tension in Solana’s evolution. Both sides raise valid points, but the reality is more nuanced than a simple “BAM vs. competition” framing. On Monopoly and Neutrality Harmonic’s concerns around monopoly dynamics are not unfounded. Jito does occupy multiple roles within the ecosystem, which naturally raises questions about metric neutrality. That said, it is important to put this risk into perspective. A block builder that is vertically integrated with a market-making operation, such as Harmonic, arguably poses a much larger systemic risk to Solana. In that scenario, block construction incentives can directly conflict with fair execution and overall network health in ways that are far harder to observe or constrain. From this angle, Jito’s multiple roles do not necessarily dilute metric neutrality. Jito is not vertically integrated across the full value chain of block building and trading. More importantly, its approach with BAM explicitly promotes verifiability, transparency, and auditable transaction ordering. Now regarding the scoring system, Harmonic is right to be a critic. Measuring “good” block building is inherently complex, and any scoring framework will necessarily involve simplifications and trade-offs. Jito should be more open to listen to Harmonic feedback in order to improve his scoring. That said, the existence of imperfections in IBRL should not, on its own, invalidate the underlying issues it aims to surface, and as Jito mentioned in its IBRL methodology section, they will continue refining the model and expanding the set of signals over time to improve accuracy. However, if an actor is intentionally delaying shred propagation, they are, as a matter of fact, slowing everyone else down. And if this behavior is profit-motivated, then that profit is necessarily extracted from the rest of the network. Performance alone is not sufficient Harmonic is right to emphasize execution quality. Best execution is undeniably critical if Solana aims to support large-scale, institutional-grade markets, as it directly impacts slippage, liquidity, and overall capital efficiency. But performance alone isn’t enough. Determinism and uniformity in transaction ordering are foundational to healthy market microstructure. Sophisticated trading systems require predictable execution environments. So yes, Harmonic validators do pack more DEX transactions per slot, but that throughput correlates with longer slot times which is precisely the kind of non-determinism TradFi institutions cannot tolerate: if execution characteristics change depending on which validator is leading, firms cannot scale their operation with confidence and the case for migrating serious flow onto Solana weakens. In that case, we can argue that higher performance at the expense of determinism and uniformity is not a Pareto improvement for the long-term health of the network and also puts bearish pressure on SOL’s potential as an asset. As Mert, CEO of Helius, [recently noted on X](https://solanafloor.com/news/harmonic-hits-back-jitos-ibrl-validator-scores), late packing may generate incremental short-term gains, but it reduces the probability of sustained SOL appreciation over the long run. To be clear, these concerns are not hypothetical, they are explicitly recognized in Solana’s own roadmap. In *[The Internet Capital Markets Roadmap](https://www.anza.xyz/blog/the-internet-capital-markets-roadmap)*, block-building dynamics and execution quality are identified as critical challenges. While they agree that BAM is an interesting solution forward, it is true that ideally, market structure improvements should come from the protocol itself as it is uniquely positioned to optimize for long-term network health rather than short-term profit incentives. On competition and innovation Competition is undeniably a powerful driver of innovation, and Harmonic is right to caution against prematurely locking Solana into a single block-building architecture. Allowing multiple approaches to compete in the open can surface better designs, stress-test assumptions, and reduce the risk of stagnation. However, market forces tend to be highly short-term oriented. In competitive environments, participants are often incentivized to optimize for immediate gains, even when those strategies degrade long term potential. This dynamic closely resembles a prisoner’s dilemma: if one validator refrains from extracting short-term value, others will not. The rational response at the individual level is therefore to maximize short-term profit, even if the collective outcome is worse for the network. Without an entity or mechanism capable of setting clear rules and protecting against this dynamic, there is a real risk that Solana’s long-term potential is undermined. Ultimately, this would also hurt validators themselves. If Solana fails to achieve its broader mission, SOL’s long-term value will suffer and SOL price remains one of the most important determinants of validator profitability. BAM aims to address this problem by shifting it to the application layer through plugins and ACE. In doing so, it ensures that users and applications capture more of the value, rather than having it extracted at the block-builder or proposer layer. The result is a structural shift from value extraction in block building to value creation at the application layer. It’s also important to be clear about the limits of the PBS path Harmonic is advocating for. PBS does not inherently guarantee fair outcomes from builder competition and introduces new pressure points. To illustrate this, the Ethereum Foundation has spent several years experimenting with proposer–builder separation and open builder marketplaces. While this reduced direct proposer discretion, it introduced new centralization vectors around relays and dominant builders and did not eliminate harmful MEV strategies and instead moved to a different layer of the stack. In other words, separating proposers from builders changed the structure of extraction, but did not fully solve the underlying incentive misalignment. Even today, more than 25% of DEX trades on Ethereum are still subject to sandwiching. Yes, Solana’s architecture is meaningfully different from Ethereum’s but the incentive problem is not architectural. As long as builder selection optimizes for short-term validator revenue, the pressure to extract rather than create value persists regardless of the underlying consensus mechanism. ![](https://shoal.xyz/research/writing/block-building-on-solana-and-the/img/c717ed222553.png) Competition at the builder layer alone has not proven sufficient to guarantee fairness, determinism, or long-term alignment. That is an important lesson when considering whether Solana should replicate a similar path. ## Closing Thoughts Solana remains well positioned to become the home of Internet Capital Markets. But its block-building microstructure remains a meaningful unresolved problem. Notably, Jito has identified two major issues that break the determinism and uniformity of block building on Solana: late packing and slot lagging. To address these issues, Jito introduced BAM, a framework designed to make block building on Solana more transparent and deterministic. Today, over 28% of the network’s stake already runs BAM. At the same time, this new architecture has faced notable pushback, most prominently from Harmonic. Their core argument is that BAM reduces competition and could therefore slow innovation. They also claim that Jito’s metrics are incomplete, and that the only thing that ultimately matters is best execution. In this piece, we’ve seen that some of these concerns are well founded, but they also obscure important context. Harmonic is vertically integrated with a market-making operation, which means BAM directly challenges its economic model. And while execution quality matters, determinism and uniformity are the binding constraints for a healthy market structure. Competition without clear rules can easily devolve into a prisoner’s dilemma, where validators optimize for short-term profit at the expense of Solana’s long-term potential. At Shoal, we believe BAM is a meaningful step forward and an important solution to help Solana become the home of Internet Capital Markets. It shifts the paradigm from value extraction at the block-builder or proposer layer to value creation at the application layer. That said, over the long run the network may need a more native, protocol-level solution to create a safer and more balanced competitive environment. But that is still 12–18 months out, and Solana needs something that works today. Finally, this is an ongoing and rapidly moving debate. None of this is settled, and there are genuine arguments on both sides. We encourage every SOL staker to look at the data, ask validators directly why they run the block-building software they do, and make their own informed decisions. Where you stake matters. It shapes the execution environment, the market structure, and ultimately the kind of network Solana becomes. ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. Shoal Research is a Jito delegate. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* ## Sources Anza. “The Internet Capital Markets Roadmap.” [https://www.anza.xyz/blog/the-internet-capital-markets-roadmap](https://www.anza.xyz/blog/the-internet-capital-markets-roadmap) Helius. “How Solana Works: An Executive Overview.” [https://www.helius.dev/blog/solana-executive-overview](https://www.helius.dev/blog/solana-executive-overview) Helius. “Solana Slots, Blocks, and Epochs Explained.” [https://www.helius.dev/blog/solana-slots-blocks-and-epochs](https://www.helius.dev/blog/solana-slots-blocks-and-epochs) IBRL. “IBRL Validator Block-Building Explorer.”[https://ibrl.wtf](https://ibrl.wtf) IBRL. “Introducing the IBRL Explorer: Measuring Validator Block-Building Quality.” [https://ibrl.wtf/blog/introducing-the-ibrl-explorer-measuring-validator-block-building-quality/](https://ibrl.wtf/blog/introducing-the-ibrl-explorer-measuring-validator-block-building-quality/) Jito Labs. “Block Assembly Marketplace Explorer” [https://bam.dev/explorer/](https://bam.dev/explorer/) Jito Labs. “Block Assembly Marketplace Documentation.” [https://bam.dev/docs/](https://bam.dev/docs/) Jito Labs. “Introducing BAM.” [https://bam.dev/blog/introducing-bam/](https://bam.dev/blog/introducing-bam/) Harmonic. “Harmonic Documentation.” https://docs.harmonic.gg/ Harmonic. “Statement on Block Building and BAM.” *[source](https://x.com/harmonic_gg/status/2009024186451169346)* Ruggero. “How Solana Builds Blocks.” [https://www.ruggero.io/blog/how_solana_builds_blocks/](https://www.ruggero.io/blog/how_solana_builds_blocks/)= hildobby. “MEV Sandwich Trades.” [https://dune.com/hildobby/sandwiches](https://dune.com/hildobby/sandwiches) --- # Building The Encrypted ICO With Zama - Publisher: Shoal Research (https://shoal.xyz) - Category: Privacy & ZK - Published: 2026-01-15 - Canonical: https://shoal.xyz/research/writing/building-the-encrypted-ico-with-zama/ - Keywords: crypto, solvers, MEV, privacy, security, infrastructure, Ethereum, Bitcoin, Privacy & ZK ![](https://shoal.xyz/research/writing/building-the-encrypted-ico-with-zama/img/6d86db37d09d.jpg) *As ICOs return with renewed momentum, their underlying infrastructure becomes critical. Powered by its own FHE stack, Zama introduces a new Sealed-Bid Dutch Auction that enables confidential participation in public ICOs. In this report, we examine the mechanics of Zama’s Public Auction and its future implications for onchain capital formation.* ## The ICO Renaissance In 2013, J.R. Willet set out to solve a very specific problem: raise money on the internet instead of going to VCs in Silicon Valley. To do so, he tried something no one had previously attempted: he published a whitepaper for the project he was building, and convinced friends and strangers online to send him Bitcoin in exchange for receiving a newly issued digital token in return. Within a month, Willet had managed to raise over $750,000, and 60 million tokens were then distributed to investors in a public sale. Willet’s experiment was called Mastercoin, and the OMNI token sale quietly became the first-ever Initial Coin Offering (ICO). Though online crowdfunding had already existed through websites like Kickstarter and Indiegogo, Mastercoin’s ICO marked the first time a project raised capital by selling a freely tradable digital asset on a public blockchain. A year later, Ethereum blew Mastercoin’s ICO out of the water, raising 31,000 BTC (worth ~$18.6M at the time) of its own. Shortly after, the ERC-20 standard was introduced: a simple framework that made creating and issuing digital tokens trivial. What followed was nothing short of a Cambrian explosion of ICOs. OMNI was the first, but in hindsight it was obviously never going to be the last. After a few quiet years, demand for ICOs is coming back in force. In 2025 alone, Pump Fun raised $600M for PUMP in the [third-largest ICO eve](https://cryptorank.io/ico)r, and teams like Plasma ($50M), Monad ($269M), and MegaETH ($49M) all completed ICOs, with more sales expected in the coming months. Nearly every major sale in 2025 saw strong investor appetite, oversubscribing and selling out in minutes. Despite fewer token sales since 2021, the total amount of capital raised has continued to grow, concentrating into fewer, higher-quality projects. ![](https://shoal.xyz/research/writing/building-the-encrypted-ico-with-zama/img/2a0ef2c2904f.png) Yet this resurgence surfaces something that today’s ICO infrastructure has not yet been able to solve for: confidential investor participation. ## Privacy (Or The Lack Thereof) In ICOs Today Structurally, an ICO isn’t so different from an IPO: it involves a public sale, a launch event, and a freely traded asset. The fundamental difference is in their underlying rails. ICOs run on public blockchains and settle via smart contracts. Investors send funds to a smart contract, which then allocates them digital tokens programmatically based on predefined terms. This architecture introduces a high degree of public transparency: anyone can independently verify that the sale executed as intended, that token allocations matched contract rules, and that every contribution and refund was accounted for. But this transparency comes with a greater underlying cost: every contribution, wallet, bid, and allocation is permanently visible onchain. By design, blockchains offer pseudonymity: users interact through randomly generated wallet addresses which are not directly tied to legal identities. However, once a wallet address is linked to a real individual — whether through an exchange withdrawal, an ENS name, or other onchain activity patterns — their entire sale behavior, spanning from contribution size, wallet balance, bidding and sale patterns, and the rest of their transaction history becomes exposed. Alongside visibility into sale behavior, public blockchains also expose ICO participants to Maximal Extractable Value (MEV) dynamics: value that sophisticated onchain actors (i.e. block builders, validators, and specialized searchers) can capture by reordering, including, or excluding transactions in a block. Simply put, those with visibility into pending transactions can position their own transactions to capture value by front-running, back-running, or sandwiching other participants’ transactions. For retail investors, this level of transparency is a privacy leak. A single sale interaction can reveal far more than intended: not just how much they contributed, but how much they hold, when they sell, and how they behave across every other onchain activity tied to that wallet. Over time, these disclosures compound, creating persistent visibility into an individual’s financial position and behavior. In practice, this also increases exposure to MEV, as retail users are the least equipped to protect themselves from adverse transaction ordering and value extraction during highly competitive sale events. For institutions, this level of transparency is simply a non-starter. Participating in a fully public onchain sale broadcasts order flow, position sizing, treasury capacity, and execution behavior to competitors and counterparties. Even the act of bidding can signal strategic intent well before a position is finalized. Combined with MEV dynamics, this creates unacceptable execution risk, where large bids can be detected, priced against, or exploited in real time. As a result, most institutional capital is effectively unable to participate in public ICOs at all, regardless of demand. Early internet crowdfunding platforms like Kickstarter and Indiegogo did handle personal data, but access to this data was strictly permissioned: backer identities, contribution sizes, and emails were private to the creator and the platform. By contrast, most attempts to incorporate some form of privacy into token sales have taken form as private, offchain processes, through whitelisted sales, negotiated allocations, data rooms, SPVs, and manual allocation mechanics. These approaches provide confidentiality for their participants, but only by abandoning the very mechanic that made ICOs powerful in the first place: open global access. The result is a bifurcated market in which institutions can only participate through private deals, while retail is pushed into fully transparent public sales that compromise their privacy. What’s missing is a middle ground: an open, public ICO rail that preserves fairness and transparency at the system level, while providing confidentiality, by default, at the participant level: the allocation logic would remain publicly verifiable, while sensitive participant data would remain private. This type of platform would allow large-scale, rules-based ICOs, supporting tens or hundreds of thousands of participants, without revealing certain details such as individual contribution sizes or linking to prior wallet activity. Of course, the next question is what this looks like in practice: how *would*one build public, auditable, yet confidential token sale infrastructure on top of today’s public blockchains? ## The Zama Sealed Bid Dutch Auction Zama is introducing a new Sealed Bid Dutch auction mechanism to bring confidential participation to onchain ICOs. Built on the Zama Protocol itself using FHE, Zama’s launchpad allows investors to participate in ICOs while encrypting sensitive bid and allocation data. ## Understanding Zama At its core, Zama is infrastructure that enables confidentiality for public blockchains using fully homomorphic encryption (FHE). FHE refers to a cryptographic technique that allows computations to be performed directly on encrypted data without first exposing the underlying values. In practical terms, this means data can remain confidential while still being used inside smart contract logic. Inputs are encrypted before reaching the blockchain, and processed in encrypted form through Zama’s confidential execution framework, and can only be decrypted by authorized parties at the end of execution. Zama implements this capability through the fhEVM, its core confidentiality framework. A small set of specialized smart contractsis deployed on underlying public chains, enabling applications to validate encrypted inputs, manage encrypted state, and coordinate decryption through Zama’s key management system. These contracts can be integrated into existing wallets and frontends, which users can then easily access. Meanwhile, developers can write confidential smart contracts onchain using Zama’s fhEVM Solidity Library and standard EVM tooling. As a result, sensitive data remains encrypted throughout its entire lifecycle: from the moment it leaves the user, through onchain computation, until the final result is decrypted by an authorized party. This breakthrough unlocks new classes of onchain applications, one of which is the confidential ICO. ## How The Sealed Bid Dutch Auction Works As with a ‘traditional’ ICO, investors deposit assets and place bids on the token to be sold, and once the auction is complete tokens are programmatically distributed to investors. The critical distinction is that, in Zama’s design, bid data is encrypted by FHE and therefore remains confidential throughout the auction process: **whereas the bid price is public, the deposit amount and token allocation are not.** Zama uses a Dutch auction format, meaning the lowest bid price is selected as the clearing price as bids are processed in price-descending order until the available supply is exhausted. During bidding, which lasts a total of 4 days, investors can submit encrypted bids. Once bidding ends, the auction contract calculates the clearing piece by selecting the lowest price at which a bid was filled, and distributes tokens to investors accordingly. Investors can then claim their tokens, or a refund if necessary. Consider an auction with a total supply of 100 tokens to be distributed: - Bob bids 40 tokens at a price of $2. His bid is filled, and now there are 60 tokens left to distribute. - Alice bids 60 tokens at a price of $1. Her bid is filled, and now there are 0 tokens left to distribute. - Mert bids 20 tokens at a price $0.50, but since there are 0 tokens left his bid is **not filled**. In this case, the clearing price is thus $1, given that it was the lowest price at which all the tokens were distributed (Alice’s bid). Therefore Bob receives 40 tokens and a $40 refund, Alice receives 60 tokens and no refund, while Mert receives zero tokens and a $10 refund. All tokens sold from the auction are fully unlocked and freely tradable upon claim. ### User Flow By design, the user flow is relatively simple and straightforward. ![](https://shoal.xyz/research/writing/building-the-encrypted-ico-with-zama/img/ba2c61c22e80.png) Investors first encrypt (or shield) the assets they intend to use for bidding. In exchange, they receive confidential “cTokens” at a 1:1 ratio, representing encrypted versions of the underlying collateral. Investors then submit bids for the token being launched at their chosen price, using these cTokens. Throughout the auction, bids can be monitored and managed directly through Zama’s auction interface, without revealing sensitive bid details onchain. Once the auction concludes, the contract computes final allocations and clearing price. Investors can then claim their outcomes: successful bidders receive their allocated tokens, while any excess collateral is refunded. At this point, investors may either decrypt their remaining cTokens back into standard tokens or continue using them across other confidential applications within Zama’s broader ecosystem. ### Technical Mechanics At the core of Zama’s protocol is an FHE system. Rather than exposing inputs, balances, or intermediate values to the blockchain, all sensitive data is maintained in encrypted form throughout contract execution. This encrypted state is preserved under a unified FHE key, allowing smart contracts to operate directly on ciphertext without ever decrypting underlying values during execution. To break this down further, the execution flow follows a well-defined pattern. A user encrypts an input (x) locally, producing an encrypted value E(x). This encrypted input is submitted onchain, where it cannot be decrypted by validators, block builders, or other applications. Smart contracts then compute directly over encrypted inputs, producing an encrypted output E(f(x)). Only authorized parties can decrypt the final result, while all intermediate computation remains opaque to the blockchain itself. This execution model is implemented through the fhEVM, Zama’s confidentiality execution framework. The fhEVM operates as a specialized layer on top of existing public blockchains, coordinating encrypted computation, maintaining encrypted contract state, and managing controlled decryption through Zama’s key management system. A small set of smart contracts deployed on the underlying chain handle encrypted input validation, encrypted state transitions, and interactions with the key infrastructure, while remaining fully compatible with existing EVM environments. ![](https://shoal.xyz/research/writing/building-the-encrypted-ico-with-zama/img/f8d811318de4.png) When applied to the Auction, these mechanics ensure that the auction state is never represented in plaintext. Assets deposited by participants are immediately converted into encrypted state and represented as confidential balances within the auction contract. Bid evaluation, allocation logic, and refund calculations are all performed over encrypted values, preventing observers from inferring contribution sizes, wallet balances, or allocation outcomes during the auction process. To implement this in practice, Zama introduces confidential “cTokens”, which serve as FHE-encrypted representations of standard ERC-20 assets. These tokens are issued programmatically when assets are encrypted and are redeemed when assets are decrypted, without exposing balances or transaction history onchain. cTokens are implemented using the [ERC-7984](https://docs.openzeppelin.com/confidential-contracts/token) confidential token standard, allowing encrypted assets to remain composable across other confidential applications built on Zama’s protocol. As a result, sensitive data remains encrypted for its entire lifecycle; from the moment it leaves the user, through onchain computation, until the final result is decrypted by an authorized party. In the context of ICOs, this architecture allows auctions to remain publicly verifiable at the system level, while ensuring that participant-level data remains confidential by default. ## The North Star: Growing TVS Zama’s adoption and growth is framed around a new type of metric: the **Total Value Shielded (TVS).** TVS refers to the total amount of economic value that is actively encrypted and kept confidential using Zama’s protocol. Just as total value locked (TVL) became a dominant metric for tracking DeFi liquidity, TVS is meant to serve as a proxy for how much meaningful economic activity is taking place under cryptographic confidentiality. The intuition is simple. The higher the TVS, the more confidentiality is being exercised across assets, applications, and users. As TVS grows, confidentiality evolves from a niche feature to a systemic property of onchain markets: assets become harder to surveil, applications harder to exploit, and users regain more control over the privacy of their onchain activity. Zama’s strategy for growing TVS is infrastructure-first. Rather than building and owning end-user applications, Zama is positioned as a **chain-agnostic confidentiality layer** that other developers, protocols, and platforms can build on top of. Zama provides the primitives for encrypted computation and confidential state, while leaving application design, UX, and go-to-market decisions to application developers. This way, Zama does not need to directly control demand to drive growth. TVS increases as confidentiality becomes a default property across an expanding set of applications and chains. Adoption is reflected in how broadly encrypted computation is integrated and how much economic value is processed under confidentiality, rather than in usage of any single application. From a deployment perspective, Zama is designed to be chain-agnostic. The protocol is launching first on Ethereum, with plans to expand across EVM-compatible chains and, longer-term, into non-EVM environments such as SVM-based chains. This multi-chain approach ensures that confidentiality is not siloed to a single execution environment, but can follow users and assets wherever onchain activity migrates to. ### TVS in Practice: The ZAMA Token Launch The first live demonstration of an encrypted ICO will be the Zama’s Sealed-Bid Auction will be Zama’s own token sale. The $ZAMA token launch will be conducted on Ethereum, using the Zama Protocol itself to encrypt bids through FHE. Zama will sell 8% of the $ZAMA supply through this auction. Participants submit bids onchain while sensitive bid data, including contribution size and allocation, remains encrypted throughout the process. Once bidding concludes, the auction clears transparently according to publicly verifiable rules, and tokens are distributed immediately with no vesting or lockups. In doing so, the Auction intends to bring fair price discovery, global access, and confidentiality to ICOs within a single platform. This auction will mark the first instance of Total Value Shielded (TVS) flowing through Zama’s protocol in production. Capital contributed to the auction is encrypted end-to-end, allocations are computed over encrypted state, and only final outcomes are revealed, thus serving as a real-world stress test for confidential onchain capital formation at scale. ### Use Cases and Applications While confidential ICOs provide a clear and immediate application, the underlying primitives enabled by Zama’s launchpad can, in theory, extend far beyond token sales. At a high level, any onchain mechanism that relies on bidding, allocation, or competition over scarce resources can benefit from encrypted execution: - **NFT Auctions:**Encrypted bidding enables sealed-bid NFT sales where bid amounts remain confidential until settlement. This could help prevent bid anchoring, strategic signaling, and enable fairer price discovery. - **Prediction Markets:**Encrypted bidding introduces a new design space for prediction markets, where individual positions and strategies can remain private during market formation, while outcomes and settlement remain publicly verifiable. - **Governance:**Encrypted bidding can be applied to onchain governance systems where outcomes are influenced by market signals or competitive inputs rather than simple token-weighted voting. By keeping bids or commitments confidential during the decision process, protocols can reduce signaling effects, cartel formation, and strategic coordination that often distort outcomes in fully transparent governance systems. This can be especially useful in futarchy-style governance, where participants express beliefs through markets tied to policy outcomes. In these settings, encrypted bids help preserve genuine price discovery by preventing participants from anchoring or reacting to visible positions before markets resolve. - **Solver Order Flow (PFOF) Bidding:**Encrypted bidding can be applied to MEV and order-flow markets, where solvers compete for the right to execute transactions or bundles. This can potentially reduce information leakage around solver strategies, limit copy-trading and reactive bidding, and mitigate winner-take-all dynamics driven via information asymmetries, thus encouraging a more competitive and efficient market for onchain order flow. - **Confidential Block Production or Rewards Auctions:**In Proof-of-Stake systems, encrypted bidding could be used to allocate block production rights or reward opportunities over defined time windows. Validators would submit encrypted bids for future slots or epochs, with allocations determined programmatically once the auction clears. By keeping bids private, such mechanisms reduce signaling and strategic front-running among validators, while enabling more market-driven allocation of block production rights. Taken together, these examples show that encrypted ICOs are just one instance of a broader pattern. Any onchain mechanism that relies on bidding, allocation, or competition over scarce resources can potentially integrate and benefit from encrypted execution. ## Closing Thoughts At Shoal, we believe ICOs are positioned for renewed demand if the underlying infrastructure evolves to support confidential participation. Retail investors can participate in public sales without broadcasting their balances, positions, or trading behavior onchain. Institutions can participate without exposing order flow, signaling strategic intent, or introducing execution risk that distorts broader market activity. Both benefit from reduced MEV exposure during highly competitive bidding processes. Zama introduces a concrete path toward this future by treating confidentiality as first-class infrastructure and orienting the protocol around a clear objective: growing the TVS across the broader onchain economy. With this in mind, we look forward to a new chapter of confidential onchain capital formation. ## Sources - Cryptorank ICO Analytics, [cryptorank.io/ico-analytics/](http://cryptorank.io/ico-analytics/) - ICO Drops, [icodrops.com/](http://icodrops.com/) - Cryptoasset Market Coverage Initiation: Network Creation. Bloomberg Research, [research.bloomberg.com/pub/res/d28giW28tf6G7T_Wr77aU0gDgFQ](http://research.bloomberg.com/pub/res/d28giW28tf6G7T_Wr77aU0gDgFQ) - “Digital Tulips? Returns to Investors in Initial Coin Offerings.” ScienceDirect, [sciencedirect.com/science/article/abs/pii/S0929119920302303](http://sciencedirect.com/science/article/abs/pii/S0929119920302303) - Coin Perspective: J.R. Willett. Medium, [medium.com/coin-story/coin-perspective-3-j-r-willet-136ed51a852c](http://medium.com/coin-story/coin-perspective-3-j-r-willet-136ed51a852c) - Zama Documentation. Zama, [docs.zama.org/homepage/](http://docs.zama.org/homepage/) - Zama Protocol Litepaper. Zama, [docs.zama.org/protocol/zama-protocol-litepaper](http://docs.zama.org/protocol/zama-protocol-litepaper) - Zama FHEVM Whitepaper. Zama GitHub, [github.com/zama-ai/fhevm/blob/main/fhevm-whitepaper.pdf](http://github.com/zama-ai/fhevm/blob/main/fhevm-whitepaper.pdf) - Zama Public Auction: auction.zama.org ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.** All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the Zama team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # MetaDAO: The New Capital Formation Layer of The Internet - Publisher: Shoal Research (https://shoal.xyz) - Category: Tokenization - Published: 2025-12-23 - Canonical: https://shoal.xyz/research/writing/metadao-the-new-capital-formation/ - Keywords: stablecoins, crypto, market making, prediction markets, Tokenization ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/ebeb548b2017.jpg) *A special thanks to [Connan](https://x.com/connan_james?s=21) and [Mathis](https://x.com/mathis_btc?s=21) for their feedback and review.* ## Crypto’s Misalignment Problem One of the first big value propositions of crypto was its ability to significantly lower the friction for capital formation and offer an alternative to the traditional funding model for startups. Instead of relying on VCs, banks, or waiting 10+ years for a potential IPO, crypto introduced a new way for anyone to raise money permissionlessly on the internet and let their project “go public” on day one through a token. This was a real breakthrough with huge potential. As people began experimenting with this new model, interest exploded, ultimately leading to the historic ICO boom of 2017, where millions were raised and thousands of new tokens were launched. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/efe6778d7d94.png) But while the concept was promising in theory, it was still immature in practice and led to widespread market abuse. Everything was all about hype, and there was a clear misalignment of incentives among the major token stakeholders. Put simply: the more successful an ICO, the greater the incentive for the team to extract what was in the treasury instead of growing the pie. And with no framework to prevent this behavior, it quickly became the default equilibrium and gave rise to countless scams and low-quality tokens. Apart from SwissBorg and a few others that managed to build something meaningful, most projects from the 2017 era bled to death. While some were genuine projects ahead of their time, many were outright scams, heavy on tech buzzwords to excite people into buying their ICO but with no real substance behind them. Today, we are still carrying that baggage. While there has been real progress in terms of crypto products and adoption, there has been far less advancement in how to properly structure tokens. And unfortunately, the market continues to suffer from abuse and bad practices, driven by too many short-term opportunists who see crypto as a way to make a quick buck. These actors still treat TGE as exit liquidity rather than the beginning of a project, and focus all their energy on hype instead of building something real: faking followers and metrics, launching at ridiculously overinflated valuations with low float, paying large amounts for tier-1 CEX listings, and relying on sophisticated market makers to engineer “perfect” chart patterns so the project appears successful long enough for teams to exit while leaving retail as exit liquidity. What’s sad is that these dynamics also put pressure on genuine founders because short-term hype tends to dominate attention. As a result, even serious teams feel pushed to conform to the same practices just to keep attention on their project and remain competitive in terms of mindshare. Ultimately, all of this has contributed to putting into question the trust and legitimacy of the crypto industry. If nothing is done to correct it, crypto risks becoming irrelevant, not because the technology, products, or underlying promises are not good enough (they are), but because the space has given too much attention to the wrong actors and has failed to provide clear protection for investors against value-extractive practices from insiders. Fortunately, every problem is an opportunity in disguise. As we speak there are a few very interesting 0-to-1 initiatives being built that aim to solve this token misalignment problem problem and help crypto finally fulfill its potential as the new capital formation layer of the internet. Among them, one project that clearly stands out is MetaDAO. In the subsequent section, we will explore MetaDAO core value proposition, how it’s positioned to reshape how the internet funds new ideas. ## A New Capital Formation Layer MetaDAO is a fundraising and governance platform that enables anyone on the internet to raise money for their startup ideas, while also simultaneously protecting investors and backers from founder abuse, misaligned incentives, and rugs. To do so, they are creating a new standard for structuring token launches through what they call “ownership coins,” and they are also pioneering a governance model based on decision markets (and inspired from the concept of Futarchy) to better align incentives between all key stakeholders in a project. Now, before going deeper into MetaDAO, it is important to introduce how decision markets and futarchy work. ## Futarchy 101 Futarchy is a form of governance first put forward by economist Robin Hanson in 2000, which makes decision-making based on prediction markets. In a futarchy, decisions are traded, rather than being voted on. Instead of debating proposals in endless forums and then voting, futarchy embraces the power of markets to forecast which decisions will be best. Proposals pass when the market speculates that they’re good. Proposals fail when the market speculates that they’re bad. The core axiom behind this model is that markets aggregate information more efficiently than traditional voting, and that the collective incentives of traders produce better predictions than the opinions of a small group. In fact, we already see this dynamic in practice through the accuracy of prediction markets: during the last presidential election, for example, platforms like Polymarket delivered far more accurate forecasts than professional pollsters. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/2a573741e05d.png) Now in the MetaDAO case, its decision market governance model is inspired by this same logic, but applies it to the key decisions an economic organization must make. Let’s take a concrete example to better explain what it is: Suppose a company wants to undergo a merger acquisition as part of a strategic vertical-scaling plan: **In the current model**, a major decision like this goes through a shareholder vote. The board reviews the proposal, issues a recommendation, and shareholders vote. Decisions are slow and inefficient, and they depend on the opinions of a small, often uninformed group, distorted by politics and misaligned incentive. Suppose the deal would temporarily boost the stock price but is clearly destructive over the long term. Executives whose bonuses are tied to short-term stock performance, or board members nearing retirement who want to lock in higher payouts, may vote *in favor* of the deal. Even though it weakens the company strategically, the short-term price bump benefits them personally. **Now with a decision market model**, the organization would open a market to forecast the company’s value *if the merger happens* and *if it does not*. Traders buy and sell based on which outcome they believe will create more value. If the “merge” market trades higher, the merger passes. If the “don’t merge” market trades higher, it fails. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/003f7c6525d9.png) ## How does MetaDAO work? MetaDAO operates through two complementary pillars built around futarchy: an ICO launchpad to launch ownership coins, and a new governance model using decision markets. ### The Ownership Coins Launchpad Projects can raise money via MetaDAO’s launchpad architecture, which is designed to be “unruggable” in the sense that founders cannot walk away with the money. The idea here is simple: if a launchpad can protect investors from rugs and ensure that founders cannot abuse the system, then it will 1) attract genuine founders and 2) attract genuine capital to fund the right ideas, which is a clear win-win for every one. Here’s how that works in practice: **1/ The founder sets transparent terms** If a founder wants to raise on MetaDAO, they first need to publish their idea/thesis and define the proposed terms of the token launch. This includes: - Mission and vision - Market opportunity - Minimum USDC target - Monthly budget - Optional token incentive package for the team (through a price-based performance design) **2/ Sale goes live** The sale then opens on MetaDAO for a defined period. Anyone can contribute USDC to support a project they believe after evaluating the idea, the team, and the terms. Each sale has a minimum funding target (below which all contributors are refunded) and a discretionary cap, giving founders the option to choose how much of the total raised they want to accept. **3/ What happens if the sale succeeds** If the funding target is met, the founder decides how much USDC they keep, and investors receive their proportional ownership coin allocation.The treasury also automatically deploys 20% of the USDC and 2.9M tokens into liquidity pools to establish healthy market liquidity.Then all the USDC and token minting rights are transferred into a market-governed treasury, which the founders cannot directly access. **4/ Transparent funding from founders** Every month, the founders can spend USDC up to their monthly budget allowance. Everything above that needs to first go through a market proposal to be spent. Furthermore, at any time, anyone can raise a proposal to return USDC to tokenholders and if the proposal passes, then it will be executed.This structure is designed to prevent founders from draining or abusing the treasury and serve as a strong protection guarantee for investors. While the launchpad is still somewhat gated today where MetaDAO ultimately decides which project can participate based on their own discretionary criteria, the long-term goal of MetaDAO is to make it fully permissionless, meaning anyone with an idea can apply, set their terms, and let the market decide whether it deserves funding. ### The Governance Model MetaDAO’s decision market governance model is automatically embedded into every project that launches on the ICO platform. However, any external project can also choose to adopt it if they believe it is a better alternative to their current governance structure. In practice, projects can decide whether to delegate their full treasury to MetaDAO, or simply transition from a vote-based governance model to a market-based one. Once this model is integrated, teams set a minimum amount required to open a proposal market, configure a few basic parameters, and from there anyone can raise a proposal about the protocol: from big cash spending, key strategic decisions, and more. Markets then determine whether the proposal should pass or fail. - **Proposal time:** the amount of time a proposal should be active before it can pass or fail. Three days by default. Specified in Solana slots. - **Pass threshold:** the percentage that the pass price needs to be above the fail price in order for a proposal to pass. - **Minimum liquidity:** to prevent spam, proposers are required to lock AMM liquidity in their proposal markets. The amount they are required to lock, in both USDC and the futarchy’s token, is specified by each DAO. - **TWAP Sensitivity Parameters**: The price that gets factored into the TWAP can only move by a certain dollar amount per minute. Each DAO must specify this dollar amount. For instance, in the example below, Omnipair raised a proposal to spend 64,000 USDC to audit their protocol, and we can see that it passed by a very large margin as the market concluded that this was a good decision. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/c18de6e9850d.png) ## How Does This Solve Crypto’s Misalignment Problem? Together, these properties help address the core misalignment problem that is plaguing crypto today: - At launch, the market cap equals the Net Asset Value (NAV) in the treasury. This creates a strong psychological and economic floor. If the price trades below NAV for a meaningful period, anyone can raise a proposal to return USDC to tokenholders. This provides strong protection to early investors. - The ownership coin structure ensures that the intellectual property, the funds, and the authority to mint new tokens are controlled by independent, market-driven governance not by the team. This imbues the token with real value and protects investors from insider abuse. -The market decides the best path forward for the project and not a small group of insiders. This makes governance more transparent and fair, with decisions driven by what is best for the protocol. On top of that, the real beauty of MetaDAO’s model is its simplicity. It doesn’t rely on complex and unsustainable financial engineering to make a token valuable. Instead, it works by removing all the vectors that could create negative externalities and aligns incentives around the token in the most straightforward way possible. ## The MetaDAO Ecosystem Today The first ICO launch on MetaDAO took place on April 9th 2025 with MtnDAO. At the time, it was viewed as an uncertain and bold experiment. However, it proved to be interesting enough to capture the attention of the broader ecosystem. Fast forward to today, adoption has accelerated significantly. Both founders and investors are increasingly drawn to MetaDAO’s unruggable ICO design. As of writing, there have been 8 ICOs launched on MetaDAO with a combined total of $25.6M million USD raised. Below is an overview of all MetaDAO launches so far: ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/21998df96e01.png) If an investor had allocated $1,000 into each ICO (and managed to receive full allocation), for a total of $8,000 invested, their portfolio would now be worth approximately $26,552 with a theoretical peak value of around $51,728. This represents a current performance of 231.9% and a maximum performance of 546.6%. These stats are unprecedented for any launchpad, especially in current market conditions. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/7aca8305855d.png) Beyond ICOs, multiple organizations have also begun migrating their DAO structures to a decision market model, and interest continues to grow steadily. We’ve even seen some of the biggest names in Solana like Jito and Sanctum start experimenting with it. Others such as Kyros, ORE, and Drift (just to name a few) are also leveraging MetaDAO’s infrastructure for their governance models. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/a5e26b9d7cac.png) ### MetaDAO Business model Ultimately, MetaDAO is a business: it aims to solve a real market problem, but it also has a token and investors, and aims to generate meaningful revenue from its product. Right now, MetaDAO earns revenue primarily through AMM fees on token launches. Every project launched through MetaDAO trades on a MetaDAO-controlled AMM pool, which currently charges 25 bps in fees (with plans to increase this to 50 bps). In the future, MetaDAO is considering adding a small fee on the oversubscribed portion of a raise, capturing value from high-demand launches. Further, the team is also exploring ways to integrate META into liquidity pools paired against ownership coins, which would further reinforce the place of META within their launchpad. Together, these components make META directly tied to the success of ownership coins, and therefore to the success of the MetaDAO launchpad itself. And they are already off to a strong start, as the platform has already generated over $1M in revenue to date. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/ecd60026d0f5.png) ## Risks and Important Considerations Of course, every design comes with trade-offs and potential second-order effects. For now, MetaDAO is far from perfect. While they have managed to build a true 0-to-1 innovation, there are still many iterations needed to go from 1-to-n and drive broader adoption, especially beyond the crypto echo chamber and into the wider startup world as a credible alternative to traditional funding models. Below are some of the drawbacks we have identified in the current model: **1/ The pro-rata subscription model:** The sales being uncapped and with founders deciding how much they take from the total is a great property. However, this model introduces a major drawback: if a launch is 2× oversubscribed, you are incentivized to put up 2× the USDC for the allocation you want, which then makes it more oversubscribed and reinforces the loop. This dynamic can also disproportionately favor large players, as smaller investors often cannot “keep up” with the escalating deposits required to maintain their allocation. The result is potential dilution of smaller backers and excessive token concentration in the hands of a few. Furthermore, because deposits and withdrawals can happen until the very last second, contributors must actively monitor the sale to avoid being underallocated (if others pile in late) or overallocated (if someone withdraws at the last moment). **2/ A permissionless platform** Going permissionless in the sense that any project can leverage their ICO launchpad is great, it fits the ethos of crypto, and it is easy to understand the rationale behind this choice from MetaDAO. However, removing gatekeepers also opens the door to a decline in project quality. If anyone can launch a project without any filtering, there can be a flood of low-quality launches that may weaken the MetaDAO brand (even though the team acknowledges this risk and prefers it over potentially missing a unicorn idea). From a user point of view, it can cause a sort of investment fatigue if there are too many projects, and it will also make their job harder when deciding which projects / founders are worth investing in. **3/ The governance model** Let’s be honest, there is still a high barrier to entry in understanding how decision market based governance actually works. For many users, the mechanics of taking positions and interpreting outcomes are not very intuitive. And because the whole model requires putting real money at stake, participation may end up being limited to highly sophisticated users. In practice, this can weaken the “wisdom of the market” argument if not enough traders are watching the market. While we can argue that MetaDAO decreases friction around capital formation, the model increases long-term friction on capital usage by teams. This is an important consideration. If a founder needs to get something done but the market rejects proposals by a tiny margin because of a small clause in a document and not enough traders are actively trading on it. We can argue that this might not be the best use of a founder’s time, and repeated failed proposals could slow execution rather than accelerate it. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/5e29f6ee1332.jpg) ## Some Ways Ahead Several solutions and design enhancements could help MetaDAO overcome its current drawbacks. Below are some avenues the team is already exploring, along with additional suggestions from Shoal on how the product could be improved: **1/ Improving the subscription models** MetaDAO’s founders are already working on solutions to fix the weaknesses of the pro-rata subscription model. In the short term, they are considering adding fees on commitments over a certain amount to reduce the incentive to over-allocate. In the longer term, they are exploring a system, where everyone would have a “Ownership score” based on how much “ownership coin” they help, and higher scores receive better allocation. This would help ensure that high-quality, long-term holders are prioritized. ![](https://shoal.xyz/research/writing/metadao-the-new-capital-formation/img/e1ab42eff110.jpg) **2/ The need for a curation layer** As MetaDAO moves toward a permissionless model, there will be a need for a curation layer. One potential solution we find interesting is a “verified launch” system (similar to the blue tick on X) where: if a project wants to launch on MetaDAO, it first needs to get publicly “referred” by a trusted partner or a well-regarded founder / voice in the ecosystem (MetaDAO can select the pool of partners). This would act as a first filter, and the referrer would effectively put their reputation on the line creating natural incentives to only endorse projects they truly believe in. Additionally, it would be valuable for the MetaDAO platform to better aggregate key information about each project to help investors make informed decisions (social graph signals, founder background, key links, optional KYC from founders, etc.). This would make the screening process far more efficient for potential investors. **3/ Reducing friction on capital usage** In the long run, it’s crucial that MetaDAO does not create unnecessary friction for teams trying to execute. One idea the team is exploring is making “team-sponsored” proposals easier to pass than normal proposals. For example, if the default pass threshold requires the price to move at least +2%, a team-sponsored proposal might still pass even if the market moves –2%. In practice, this gives the team the benefit of the doubt and acknowledges that founders should be trusted unless the market signals strong disagreement. Another potential improvement is introducing a light filter before proposals go live, either by the team or by a small community council to reduce noise and ensure only meaningful proposals reach the market. ## Closing Thoughts Crypto has enormous potential to improve capital markets and reinvent how capital formation happens on the internet. But for years, this promise has been held back by structural incentive misalignment: too many short-term opportunists have taken advantage of poor token structures to extract value from the market instead of creating it. In practice, this has led to a slow erosion of trust and legitimacy in the crypto industry as a whole. MetaDAO proposes a genuinely interesting and refreshing solution to this problem through a launchpad architecture that is unruggable by design and that realigns incentives between founders and investors. While this is a very bold mission, they have already made some very meaningful progress. The performance of their launchpad is one of the most impressive in crypto, and it has managed to attract a strong cohort of high-quality founders. Moreover, MetaProphet, Kollan, and the entire MetaDAO team have proven to be thoughtful, ambitious builders who take feedback seriously and are clearly motivated to keep improving their offer. At Shoal, we believe MetaDAO stands a real chance of becoming an important pillar for how the next generation of startups, crypto-native or not, fund their ideas on the internet. This is especially relevant at a time when countries like the US are actively moving toward pro-crypto and pro-innovation regulatory frameworks. ## Sources - Elementus. “ICO Market Report - August 2018.” [elementus.io/blog-post/ico-market-august-2018/](http://elementus.io/blog-post/ico-market-august-2018/) - MetaDAO. “MetaDAO Project Update.” [x.com/MetaDAOProject/status/1909251208336019511](http://x.com/MetaDAOProject/status/1909251208336019511) - MetaProphet. “On Improving MetaDAO’s Launchpad Model.” [x.com/metaproph3t/status/1985393563153440786](http://x.com/metaproph3t/status/1985393563153440786) - MetaProphet. “Thoughts on Allocation Mechanics.” [x.com/metaproph3t/status/1979243370452258837](http://x.com/metaproph3t/status/1979243370452258837) - Galaxy Research. *Why Futarchy Matters.* [galaxy.com/insights/research/why-futarchy-matters/](http://galaxy.com/insights/research/why-futarchy-matters/) - MetaDAO Documentation. [docs.metadao.fi/](http://docs.metadao.fi/) --- # Inside Talus: The Infrastructure for Onchain Autonomous Agents > The agentic economy needs the right rails to flourish. - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2025-12-18 - Canonical: https://shoal.xyz/research/writing/inside-talus-the-infrastructure-for/ - Keywords: agentic economy, AI agents, crypto, security, infrastructure, AI & Agents ![](https://shoal.xyz/research/writing/inside-talus-the-infrastructure-for/img/cf64389e4e07.jpg) ## The Coming Age of Autonomous Agents AI agents have advanced beyond simple language tasks. They’re now capable of executing trades, managing capital, making payments, and operating across more complex, multi-step tasks. But as these systems grow more capable, one thing becomes clear. There is a growing mismatch between the infrastructure that enabled today’s AI models and the structural needs of autonomous agents. Systems designed to serve request-response interactions simply aren’t suited for software that needs to make decisions and perform multi-step operations independently. Consider an autonomous agent tasked with managing a protocol’s treasury. It monitors market conditions across dozens of protocols daily, evaluating risk parameters and executing capital allocation strategies. To do so, an agent needs to query a proprietary API for market data, but the provider can revoke access or modify pricing without notice. Rate limits shift based on provider capacity. The AI model generating trading signals is opaque, as stakeholders can’t verify whether the agent’s decisions actually follow its intended logic. As agents cannot hold assets or sign transactions, they cannot execute actions directly. As a result, there is no shared source of truth to confirm whether an agent acted within their authorized parameters if a dispute occurs. ## Why Traditional AI Infrastructure Fails for Agentic Intelligence Developers building autonomous agents have little choice among infrastructure providers today. Market concentration has consolidated AI infrastructure around a handful of providers controlling access to models and compute. This creates dependency risk in several ways. Pricing becomes unpredictable as terms of service change unilaterally. Rate limits appear and disappear based on provider capacity, and API endpoints shift without warning. For autonomous agents requiring guaranteed uptime and predictable costs, these dependencies represent existential vulnerabilities. The issue goes deeper than reliability. Centralized platforms cannot provide the transparency and verifiability that multi-party coordination demands. When multiple stakeholders delegate authority to an agent, they need to verify that its decisions followed approved logic. They need audit trails showing how inputs produced outputs, along with guarantees that the agent operated within specified parameters. Centralized APIs cannot provide this. They return outputs without proofs, processing requests behind closed doors. Users must trust that the model executed correctly, that results were not manipulated, and that pricing was calculated fairly. This level of trust may be tolerable for individual developers building applications but breaks down for autonomous agents coordinating economic activity across organizational boundaries. Economics introduces another barrier. Agents that generate value cannot capture it directly or participate as economic actors. All revenue must flow through accounts controlled by humans or corporations. Platform operators capture the upside from agent activity while externalizing risks, preventing the emergence of agent-to-agent markets and limiting use cases to narrow, pre-approved categories. Perhaps the deepest incompatibility lies in how centralized platforms handle permissions and authorization. When multiple parties coordinate through autonomous agents, trust must be explicit and mechanically enforced. Permissions require cryptographic verification that all participants can audit, and execution paths must be provably correct, with disputes resolvable through objective evidence rather than platform policies. No centralized platform can provide these guarantees. Doing so would contradict centralization itself. The moment a trusted intermediary controls execution, the exact dependencies and trust assumptions that autonomous coordination seeks to eliminate reappear. Altogether, these limitations show that centralized AI infrastructure cannot support autonomous agents in any environment that requires persistence, verifiability, or cross-organizational coordination. A different architectural foundation is needed. ## Talus: A New Decentralized Operating System for Agents Talus Network aims to address the structural limitations of today’s agentic infrastructure through a decentralized framework purpose-built for autonomous onchain agents.Its architecture supports verifiable workflow execution, cryptographic state management, and programmable economic primitives, enabling agents to custody assets, execute transactions, and coordinate across organizational boundaries through onchain settlement and shared state. ### Core Design Principles Talus is designed on several foundational principles: - **Verifiable computation**: Through onchain workflows and cryptographic proofs, Talus ensures that every agent action is auditable. - **Composability:** Talus supports modular tool registries and agent “packages,” allowing agents to access and share tool registries and invoke other agents into their workflows without platform-specific integration. - **Economic alignment:**Economic incentives are embedded directly into the protocol, with value flowing programmatically and transparently to agents and infrastructure operators. At its core, Talus offers deterministic workflow execution where each step in an agent’s operation is recorded as a state transition onchain. This creates an immutable audit trail for how decisions were made and executed, while allowing agents to coordinate across organizational boundaries through shared, verifiable state. The system supports offchain computation with onchain verifiable results, addressing the cost and performance constraints of executing complex AI workloads directly on blockchain virtual machines (VMs). Compute-intensive tasks like model inference occur offchain through a distributed network of execution providers. Cryptographic commitments and state updates settle onchain. This hybrid architecture preserves transparency without sacrificing the performance requirements of production-grade AI systems. ## How Talus Actually Works Talus works via a modular architecture: each component serves a specific role in enabling autonomous-agent coordination. The system couples blockchain consensus with offchain computation, delivering an infrastructure that is both verifiable and efficient. Nexus, the core engine, handles onchain coordination and offchain execution. ![](https://shoal.xyz/research/writing/inside-talus-the-infrastructure-for/img/1c13555de9ac.png) A consumer submits a request to a Talus workflow, which is encoded as a directed acyclic graph (DAG). Each step in the DAG corresponds to a tool invocation or state transition. During execution, the Nexus onchain packages coordinate with Leaders offchain to trigger tools, update workflow state, and return results. This separation between workflow specification (onchain) and computation (offchain) allows Talus to remain verifiable without sacrificing performance. ### Talus Stack Architecture ![](https://shoal.xyz/research/writing/inside-talus-the-infrastructure-for/img/3a16255a8bcb.png) Talus runs on the Sui blockchain and utilizes Sui’s object-centric state model and the security of Move. Agents, tools, and workflows are represented as objects with explicit ownership, meaning each resource has a defined owner and can be transferred, combined, or restricted through code. Smart contracts on Sui Move define the structures and protocols for agent and workflow management, allowing developers to then build atop this foundation using different contract package types: - **The Nexus Onchain Package (NOP)**: The foundational layer maintained by the Talus team, defining core data structures, workflow coordination logic, and the protocol’s primitives. - **Tool Packages** sit atop this foundation, allowing developers to publish modular tools — on or offchain — that agents can invoke. Tools expose defined inputs, outputs, and access/payment constraints. - **Talus Agent Packages (TAP):** enable developers to compose these tools into complete agent systems with custom business logic. This layered structure creates a clear separation of responsibilities while enabling composability across the ecosystem. The relationship between Talus agents, the Nexus onchain packages, the Leader network, and the tool ecosystem is shown below. Talus agents route requests to Nexus, Nexus updates workflow execution onchain, and Leaders perform offchain computation while triggering tools across both environments. ![](https://shoal.xyz/research/writing/inside-talus-the-infrastructure-for/img/2418815cae20.png) Nexus sits at the center of execution flow: agents submit workflow requests onchain, Nexus updates workflow state, and Leaders coordinate offchain execution by invoking the appropriate tools and returning results onchain. This separation between onchain coordination and offchain computation is what enables Talus to remain both verifiable and performant. ### Workflow Engine and Deterministic Coordination Talus encodes agent behavior as directed acyclic graphs (DAGs) stored onchain. Each node within these graphs represents a specific action, whether reading data, calling a tool, or modifying state, and the dependencies between nodes establish which operations must complete before others can begin. Because the workflow specification itself lives onchain, anyone can audit what an agent is authorized to do before execution even begins. Computation, however, is offloaded. The Leader network performs the actual work by pulling node definitions from Nexus, executing the corresponding tool, and submitting a verifiable receipt back to the chain. This hybrid model preserves performance for heavy workloads while ensuring that state, permissions, and results remain transparent. ### Workflow Execution States Each workflow execution creates a DAGExecution object that tracks progress through walk states. A walk represents the execution of a single node in the workflow graph. Walks transition through four possible states: Active (currently processing), Successful (completed and ready to activate next nodes), Failed (encountered an error), or Consumed (completed but waiting for other inputs to converge). This state system ensures workflows handle errors gracefully and prevents deadlocks through fallback mechanisms. If a tool fails, the workflow can trigger fallback edges that route execution to alternative paths, maintaining liveness even when individual components encounter issues. ### Talus Tools and Modular Capabilities Tools represent functional modules that agents can invoke during workflow execution. When registered onchain, each tool declares its expected inputs, produced outputs, pricing structure, and access requirements. This registration system creates an open marketplace where developers contribute capabilities and agents discover services organically. Tool execution can happen in two environments: - **Onchain tools** interact directly with Sui smart contracts. - **Offchain tools** execute compute-heavy tasks (LLM inference, analytics, image work, math routines) coordinated by Leaders. Leaders orchestrate these calls and return results onchain with proofs or commitments, keeping the entire workflow auditable. ### Payment and Gas Model Every workflow execution requires economic coordination across multiple service providers. Users deposit payment into a gas budget within a globally unique gas service object. Before execution begins, Nexus verifies sufficient funds to cover all potential tool costs based on the workflow’s maximum execution path. As the workflow progresses, each tool consumes its designated payment from this budget only after successfully completing its work and passing any required verification steps. This delivery-versus-payment mechanism ensures tools receive compensation for honest work while protecting users from paying for failed or incomplete operations. The protocol implements a dual-track revenue system. According to current protocol design, when overall protocol revenue falls below a threshold, priority fee income is burned, reducing token supply and supporting token economics. When revenue exceeds the threshold, fees are distributed to Leaders performing coordination work. ### Data Storage with Walrus Essential workflow metadata lives on Sui’s blockchain, ensuring its integrity and availability. However, storing everything onchain becomes prohibitively expensive. Walrus, a decentralized storage platform from Mysten Labs, handles supplementary data including agent memory, operational context, and intermediate results. Agent functionality depends critically on maintaining context and memory across multiple sessions, allowing them to learn from past interactions and build upon previous decisions. Walrus provides this storage layer with configurable verification mechanisms. Tools can reference data stored on Walrus through onchain commitments, enabling workflows to pass large datasets between operations without incurring excessive gas costs. This distributed storage approach maintains verifiability for intermediate values while achieving practical scalability. ### Leader Network and Distributed Execution Leaders serve as the coordination layer between onchain workflow specifications and offchain computational resources. They monitor the blockchain for workflow execution requests, identify which tools need to run, coordinate their execution, and submit the results back onchain as verifiable receipts. ### Execution Flow in Practice Consider an investment agent making a portfolio adjustment. The user triggers the workflow by submitting a transaction to the agent’s smart contract. This creates a DAGExecution object and emits an event that Leaders monitor. A Leader picks up this event, retrieves the first tool’s information from the onchain registry, and discovers it needs to fetch current market prices. The Leader calls this price oracle tool, receives the data, and submits it back onchain along with payment for the tool. This activates the next workflow node, perhaps an analysis tool that recommends allocation changes. The Leader orchestrates this second tool’s execution, submits results, and continues until the workflow reaches a terminal node that executes the actual trades through onchain DeFi protocols. Each step produces an auditable record while the Leader handles all coordination overhead. ### Security and Progressive Decentralization The network maintains security through economic incentives. Leaders stake collateral that faces slashing if they behave maliciously or fail to maintain liveness. The system rotates execution responsibilities across multiple Leaders, preventing any single operator from dominating the network. These mechanisms create fault tolerance and resistance to coordinated attacks. The Leader network architecture evolves progressively. It currently operates with initial trusted Leaders to ensure reliability while the platform establishes product-market fit. Future phases introduce TEE-based distributed execution, where Leaders run inside trusted execution environments that provide cryptographic proof of correct operation. The final phase reaches a fully permissionless model where anyone can stake tokens and participate as a Leader. This gradual transition maintains service quality while steadily increasing decentralization and minimizing trust assumptions. The combination of object-based state management, flexible security levels, hybrid execution, and economic coordination addresses specific technical constraints that emerge when agents need to operate across organizational boundaries. ## Building a Market for Autonomous Intelligence Talus creates economic infrastructure where agents transact as independent participants rather than subordinate tools. The $US token is designed to serve as the coordination and incentive layer across the network. It functions as payment and settlement for workflows, tools, and agents, and as the medium for tool registration and Leader network participation. Within this system, agents compensate other agents for specialized services based on computational requirements and market demand. Revenue flows programmatically to tool developers through usage, to model providers through invocations, and to Leaders through execution work. $US holders secure the network through staking and participate in governance over protocol parameters. The result is a market-driven coordination system where intelligence operates as a commodity. Stakeholders capture value proportional to their contribution. Economic sustainability derives from network activity rather than external subsidy. ### Use Cases: What Talus Makes Possible Taken together, these primitives (workflows as DAGs, tools with flexible security, hybrid execution, and programmable payments) address a specific class of applications that existing infrastructure cannot support. **Agent-Driven Prediction Markets** Prediction markets aggregate distributed information through financial incentives, but their efficiency depends on participants who can continuously process diverse data sources and execute trades instantly. Human traders cannot simultaneously monitor onchain oracle feeds, analyze social sentiment, cross-reference polling data, and adjust positions across multiple markets 24/7. Talus agents eliminate these constraints: - Polling oracles provide official results with confidence intervals - LLM tools analyze sentiment from social platforms - Statistical models weight historical accuracy and detect trends - Execution tools adjust positions across market contracts - Risk modules enforce portfolio constraints Traditional platforms like Kalshi operate as black boxes where users cannot inspect internal algorithmic behavior. Talus workflows, by contrast, can record decision steps onchain. When an agent is configured to trade based on polling data and sentiment, the DAG execution trail provides a verifiable onchain record of which tools were invoked, in what sequence, and how their outputs influenced the final action. Computation-heavy analysis runs offchain within the Talus agent framework, while trades and key coordination events settle onchain. Market resolution can follow the same pattern: agents query multiple oracles, check for consensus conditions, and trigger settlement only after verification. **Verifiable DeFi Agents** Consider an MEV protection bot executing trades across decentralized exchanges. Today, users must trust the operator’s claims about routing logic. With Talus, the agent produces cryptographic receipts for every step: route selection, price impact calculation, final execution path. Users verify that the actual transaction matched the stated strategy without requiring blind trust. Cross-protocol yield strategies work similarly. When an agent moves capital between lending markets, stakes proceeds, and rebalances positions, the Leader network generates proofs for each interaction. The complete execution trace becomes auditable. If something goes wrong, participants can verify exactly where and why through cryptographic evidence recorded onchain. **Agent-to-Agent Tool Markets** A trading agent needs machine learning predictions but doesn’t want to train models itself. On Talus, it hires a specialized prediction agent, verifies the model’s identity through cryptographic attestation, and pays per inference onchain. The predictor earns revenue automatically through usage. No platform middleman, no API contracts, no trust required beyond cryptographic verification. This creates markets for specialized intelligence. Agents that build valuable capabilities, whether ML models, data analysis tools, or execution strategies, monetize directly through usage. Tool development becomes economically sustainable without platform dependency. **Cross-Chain Autonomous Portfolios** Today, moving assets across blockchains requires custodial bridges or trust assumptions. Talus enables coordinated operations across chains through verifiable state queries. A portfolio agent could check prices on Ethereum, execute a swap on Base, and stake proceeds on Arbitrum, all within a single coordinated workflow. Each step occurs within the same execution context. The Leader network provides cryptographic proofs that operations happened correctly across different chains. This eliminates custodial bridge risk since agents read and write state directly rather than locking assets with intermediaries. **Accountable DAO Governance** Treasury management agents prove their risk calculations through transparent workflows auditable before vote execution. Stakeholders verify that proposed allocations derive from stated logic. Emergency response agents act autonomously within smart contract-enforced constraints. All authorization logic remains verifiable onchain. This creates accountability for autonomous governance while maintaining automated response speed. **Privacy-Preserving Enterprise Operations** Through TEE integration, agents process sensitive data without exposing it. Healthcare agents analyze patient records, financial agents evaluate credit risk, and compliance systems audit transactions, all while keeping underlying data encrypted. Only the TEE decrypts inputs during computation, and cryptographic attestation proves correct processing. This enables autonomous intelligence in regulated domains where privacy is mandatory. ## Economics Talus creates a self-reinforcing agent economy where growth compounds across the network. As tools expand capabilities, agents become more powerful. More capable agents attract users with sophisticated needs. Rather than relying on centralized rent-seeking, the network distributes value programmatically to contributors while capturing protocol-level revenue through usage-based fees. ### Value Flow and Network Effects When a workflow executes, users fund its execution through onchain fees that cover computation and coordination. As execution completes and verification passes, fees distribute to workflow participants according to protocol rules: - Leaders earn for coordination work - Tool developers earn from usage - Agent developers earn from deployment and performance This creates reinforcing network effects. Each additional tool increases what agents can do, attracting users with more sophisticated needs. Increased usage generates more fee revenue for successful capabilities, incentivizing developers to build specialized services. The flywheel accelerates as growth in one area drives growth everywhere else. ### Token Value Accrual $US sits at the center of this economy as the primary unit of value and coordination. *(Note: $US has not yet been listed on exchanges as of this writing.)* Network activity creates ongoing demand for the token to pay for usage, access features, and participate in governance. Users can pay base gas fees in SUI, with the protocol routing settlement and incentives through $US. Direct $US payment enables priority execution and enhanced features. ### Supply Dynamics and Fee Structure The protocol implements a capped supply with a fee model that links token scarcity to real usage. When protocol revenue falls below a threshold, priority fees are burned rather than distributed. This permanently reduces circulating supply. As network activity scales, this creates a value-accrual loop where demand acts on shrinking supply. When revenue exceeds the threshold, fees distribute to Leaders performing coordination work, aligning rewards with network growth. ### Staking and Participation Incentives Staking forms the foundation of Talus’s security model. Leaders stake $US to participate in coordination and earn fee revenue. Stakes face slashing for malicious behavior or failures. Tool providers stake when registering capabilities, aligning their incentives with service quality. As the marketplace grows, staked tokens lock supply while usage-driven demand continues. Long-term holders gain governance rights and access to protocol features. This creates incentives to participate in the ecosystem rather than purely speculate. The combination of staking requirements, governance participation, and usage-based rewards aligns all participants with network health and sustainable growth. ## Limitations & Open Challenges Talus addresses coordination problems that existing systems cannot solve, but introduces distinct constraints in doing so. Understanding these limitations matters for realistic deployment and protocol development. ### Technical Constraints Verification adds latency to every workflow. Each step requires cryptographic proof generation and onchain settlement, creating overhead that centralized API calls avoid. Offchain execution handles compute-intensive tasks efficiently, but the coordination layer still adds milliseconds to seconds depending on blockchain finality. For high-frequency trading or real-time response systems, this latency may prove prohibitive. When agents hire other agents as subcontractors, workflow dependencies multiply across the system. A failure in one sub-workflow cascades through dependent operations, creating unpredictable failure modes. Debugging becomes difficult when execution spans multiple tools, chains, and offchain providers. Tooling for monitoring and diagnosing multi-agent systems remains immature. ### Economic and Governance Risks Incentive misalignment emerges at protocol boundaries. Leaders might prioritize high-fee workflows, delaying execution for lower-paying users. Tool developers could extract value through opaque pricing or degraded service quality. Agent owners might exploit protocol mechanics for individual gain at collective cost. Token holders must balance competing interests across tool developers, agent operators, and end users when making governance decisions. Protocol upgrades require consensus among stakeholders with different time horizons and risk tolerances. Without effective mechanisms, the system risks capture by concentrated interests or stagnation through disagreement. ### Security Concerns Malicious agents pose systemic risk. An agent could exploit tool vulnerabilities, manipulate other agents through adversarial inputs, or drain assets through legitimate-looking workflow logic that contains hidden exploits. Permissioned tool registration and workflow verification provide safeguards, but determined attackers may find edge cases. Despite slashing penalties, a coordinated attack on the Leader network could compromise workflow execution during the current trusted phase. The progressive path toward full decentralization addresses this over time, but the trusted setup introduces temporary centralization risk. ### Ethical and Societal Implications Autonomous agents operating in the real world raise questions infrastructure cannot answer. An agent managing capital might make economically rational decisions that cause social harm. Agents coordinating across domains could amplify systemic risks or trigger unintended consequences no single operator foresaw. The protocol verifies what agents do, not whether they should do it. This gap between technical capability and ethical judgment remains an open challenge for autonomous systems. ## Future Outlook: The Path Toward Decentralized Intelligence The trajectory of AI development points toward a fundamental reorganization of economic activity. As agents gain autonomy and operate across decentralized infrastructure, they will evolve from tools that execute commands into participants that negotiate, transact, and coordinate independently. Talus positions itself as the coordination layer for this transition. ### Agents as Economic Participants Current systems treat agents as extensions of human operators. Future systems will treat them as independent actors. Agents will hold assets, evaluate counterparties, negotiate terms, and execute agreements without human intervention at each step. An agent managing a treasury will adapt strategies based on market conditions rather than following predefined rules. It will hire specialized agents for analysis and coordinate with others to achieve objectives. This requires infrastructure where agents can transact trustlessly. Traditional finance operates through intermediaries that verify counterparty creditworthiness and enforce settlement. Decentralized systems replace intermediaries with cryptographic guarantees and programmatic enforcement. Talus provides this foundation through verifiable workflows and onchain settlement. As agent-to-agent commerce grows, the protocol could function as settlement infrastructure similar to how SWIFT coordinates interbank transfers or Visa processes card transactions. ### Expansion of Decentralized AI Infrastructure Security and privacy requirements will drive technical evolution. Zero-knowledge machine learning and trusted execution environments will enable privacy-preserving verification. A healthcare agent could prove it analyzed patient data correctly without exposing the data itself. A trading agent could verify strategy execution without revealing its algorithm. Interoperability will expand beyond blockchain ecosystems to encompass traditional systems. Agents will read state from legacy databases, execute operations through conventional APIs, and write results to blockchains. The distinction between onchain and offchain execution will become less important than whether operations are verifiable and settlement is trustless. Marketplaces for tools and agent services will mature from experimental protocols into established infrastructure with standardized interfaces and competitive pricing. ## The Long-Term Vision Decentralized intelligence may evolve into global utility infrastructure. Just as cloud computing commoditized server access and the internet commoditized information distribution, autonomous agent platforms could commoditize intelligent coordination. Multi-agent ecosystems might manage supply chains, coordinate energy grids, or optimize resource allocation across organizations. Talus is positioned to serve as backbone infrastructure for this future. The protocol does not attempt to solve all problems but provides coordination primitives that other systems can build upon. If agents become economic participants at scale, they will require neutral infrastructure for settlement and verification. Whether Talus captures this role depends on execution, but the architectural foundation exists. The question is not whether autonomous agents will reshape economic activity, but which infrastructure will coordinate them. ## Closing Thoughts The infrastructure supporting AI development has reached a critical juncture. Centralized platforms delivered the current generation of AI models, but they cannot support the next phase of autonomous agent deployment. Their constraints are structural, not temporary: opaque execution, unilateral control, and no way for agents to act as independent economic actors prevent the coordination mechanisms autonomous systems require. Talus addresses these limitations through architectural choices that leverage blockchain properties for verifiable execution, permissionless participation, and programmable economic alignment. Rather than trying to rebuild the whole AI stack, Talus offers coordination primitives: composable infrastructure that other systems can build on. The path forward involves more than technical specs. Verification latency must shrink. Multi-agent debugging tools must emerge. Incentives must align across stakeholders. Security must decentralize progressively. These are real challenges, but they are addressable through iterative development. What remains uncertain is adoption trajectory, not technical feasibility. The architectural foundation exists for agents to operate as independent economic participants. Whether this vision materializes at scale depends on execution, ecosystem development, and whether builders choose verifiable coordination over centralized convenience. Autonomous agents will reshape economic activity. Which infrastructure coordinates them remains an open question. Talus positions itself through verifiable workflows, agent-first architecture, and programmable economic primitives. Success will be measured not by technological sophistication alone but by whether the protocol becomes essential infrastructure for the autonomous systems that follow. At Shoal, we believe autonomous agents could reshape economic activity at scale. What matters is the infrastructure that supports them. Adoption will determine its ultimate role, but with verifiable workflows, native asset control, and modular coordination primitives, Talus’s architecture is designed in a way that gives it a credible path toward becoming foundational rails for the agentic economy. ## Sources - Talus Documentation. Talus Network, [docs.talus.network](http://docs.talus.network) - Talus Network Litepaper. Talus Network, [talus.network/litepaper](http://talus.network/litepaper) - Nexus Whitepaper. Talus Network, [talus.network/whitepaper](http://talus.network/whitepaper) - Talus Combines Walrus and Sui to Enable Onchain AI Agents. Walrus, [walrus.xyz/blog/talus-builds-onchain-ai-agents-walrus](http://walrus.xyz/blog/talus-builds-onchain-ai-agents-walrus) - What Is Talus ($US)?. Whales Market, [whales.market/blog/what-is-talus/](http://whales.market/blog/what-is-talus/) ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the Talus team. Some members of the team have material holdings of SUI and Talus. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Building DeFi’s Investment Bank > Transparency does not solve coordination. - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-10-29 - Canonical: https://shoal.xyz/research/writing/building-defis-investment-bank/ - Keywords: crypto, DeFi, yield, infrastructure ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/158af2e50060.jpg) *DeFi solves the information asymmetry problem that has riddled TradFi’s capital markets, though still more in theory than in practice. The value, and difficulty, of coordination, only becomes more evident in decentralized systems, and despite its transparency, self-custody, and operational efficiency, liquidity in DeFi still remains scarce and mercenary as there is no shared coordinating framework. In this piece, we explore the need for onchain liquidity coordination and how Turtle approaches this challenge.* ## The Capital Coordination Challenge For all its innovation and growth, DeFi has long been plagued by mercenary, non-sticky liquidity. This is ultimately a product of structural misalignment between foundations and liquidity providers (LPs). Foundations allocate token emissions to incentivize aligned, multi-cycle liquidity for their protocols, but may have no idea what type of LPs they will attract nor how long they will stick around for. Meanwhile LPs, seeking a return on their capital, have little visibility into the organic activity or trading volume a protocol can sustain over time, therefore it becomes rational to exit once emissions end rather than remain committed. As such, most protocols and LPs stand little chance against the self-reinforcing cycle of short-term incentives and mercenary liquidity that defines much of DeFi today. Information asymmetry is not new to capital markets by any means. The distribution of knowledge around asset quality, risk, and value between borrowers and lenders has never been proportional for as long as capital markets have existed. Investment banks emerged to solve this underlying coordination failure, conducting diligence, structuring credit into tranches by risk appetite, and distributing that credit across a syndicate of lenders accordingly. Borrowers gained access to consolidated capital through a single negotiation, while the IBs earned fees for aggregating information, standardizing risk, and coordinating supply and demand. This process, formally known as syndication, transformed credit markets by separating origination from investment. Large banks would originate loans but distribute the debt to non-bank investors such as hedge funds, pension funds, and collateralized loan obligations (CLOs). The Basel II and III frameworks reinforced this dynamic by incentivizing banks to transfer credit risk off balance sheet and optimize capital efficiency. What began as bespoke loan placements evolved into a standardized system for converting private credit assessments into tradable financial products. Though complex and costly, syndication has helped standardize processes for diligence, distribution, and ongoing risk management, building the infrastructure that enabled credit to be assessed, distributed, and maintained at scale. More importantly, it demonstrated the value of coordination in capital markets by turning a fragmented, bilateral lending process into a scalable, trillion-dollar asset class. ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/53fffbe5e9ad.png) DeFi sought to rebuild these financial coordination architectures with code. AMMs and lending markets encoded core functions of intermediation (i.e. price discovery, collateralization, settlement) into smart contracts. Anyone with an internet connection and capital could supply liquidity or borrow assets on shared, observable infrastructure where transaction settlement was compressed from days to minutes or even seconds. This transparency, however, has not produced coordination. Protocols can issue incentives, but they cannot determine or predict their outcomes. Token emissions attract liquidity, but they do not specify who participates, how long that capital will remain, or under what conditions it will leave. Each program operates in isolation, competing for the same pool of capital with no shared framework for evaluating risk or aligning expectations. Liquidity flows toward the highest nominal yield, not toward sustainable participation. When incentives end, deposits leave, and the process begins again ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/ce6a89bd5e05.png) Information asymmetry in DeFi thus re-emerged in a different form. Onchain data made transactions visible but that barely means much if investors and LPs still cannot easily assess governance quality, operational integrity, or the long-term economics of a protocol, nor if foundations, for their part, cannot distinguish between speculative and committed capital. DeFi protocols have demonstrated that smart contracts and code *can*replace costly, operationally inefficient human intermediaries across a range of financial products and services. But removing intermediaries has also made it that much more difficult to coordinate how liquidity is distributed across these systems in a way that aligns incentives for all participants. With this in mind, we can reasonably assert the opportunity for DeFi’s ‘investment bank’, a protocol dedicated to structuring, allocating, and sustaining liquidity across markets. Rather than replacing existing protocols, it would provide the coordination infrastructure through which foundations and liquidity providers can negotiate and maintain capital at scale. In effect, such a protocol would serve the same function investment banks did for credit markets: aggregating information, matching the right participants, and standardizing how liquidity is structured and deployed. ## Turtle: DeFi’s Investment Bank Layer Turtle is an onchain liquidity distribution protocol connecting lenders (i.e. onchain LPs) with borrowers, including protocols and foundations seeking liquidity. Through curated campaigns, custom deposit vaults, and embedded distribution across partner frontends, Turtle aims to standardize how Turtle standardizes how liquidity is sourced, coordinated, and deployed across DeFi. Since its MVP launch in May 2024, Turtle has coordinated over $5.5B in total liquidity, nearly $300m in boosted campaign deposits, grew its treasury to over $13.7M, and has over 400k connected wallets alongside 15k campaign LPs. Functionally, Turtle operates as a liquidity distribution layer beneath chains, bridges, and applications onchain. It integrates through APIs, wallets, and smart contracts to track liquidity positions and coordinate deployment across multiple ecosystems. Foundations define their liquidity terms, including total amount, duration, and under what conditions. Turtle works with foundations to help structure the best possible deal in order to incentivize LPs long term and ensure liquidity is not mercenary. LPs meanwhile can review terms and deposit liquidity directly to the foundations through Turtle’s non-custodial vaults. Together, this structure aims to improve upon standard token emission models through organized dealflow, functioning as an Investment-Bank-style coordination layer across the broader DeFi ecosystem. Turtle’s architecture revolves around curated campaigns and embedded distribution, the two mechanisms through which it coordinates liquidity: - **Curated Campaigns**: Structured liquidity programs negotiated with protocol teams, each with defined capital targets, reward schedules, and durations. These campaigns bring consistency and transparency to how liquidity is sourced and rewarded. - **Embedded Distribution**: Integrations that surface campaigns directly within wallets, exchanges, and analytics platforms, allowing users to discover and participate in opportunities through familiar interfaces. Campaigns are standardized and published through Turtle’s deal interface; deposits are managed through non-custodial structured vaults; and participation data flows through embedded dashboards and leaderboards that coordinate rewards and feedback. To better understand how these components all work together, it’s worth unpacking them in greater detail. ### Discovery and Dealflow Layer The Discovery and Dealflow layer, known collectively as Turtle Deals, structures how liquidity opportunities are sourced, negotiated, and distributed through the protocol. Partner protocols define their key campaign parameters, namely their target capital, eligible assets, reward terms, and duration, which are then verified and published on the Turtle Deals dashboard. This is designed to provide a standardized and transparent framework to onchain liquidity sourcing. Within this system, Boosted Deals represent campaigns co-incentivized by the Turtle DAO, where LPs (Turtle Members) earn both native rewards from partner protocols and additional rewards, paid out in TURTLE tokens, proportional to their participation. Partner protocols provide the DAO with a defined boost payment, and the DAO distributes those boosts back to Members pro-rata, the first distribution happening during Turtle’s TGE. ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/cd3ddabc0b77.png) This process ties liquidity incentives to real-time activity. Partner protocols gain structured, predictable access to capital under defined parameters, while LPs are compensated transparently according to duration and engagement. The Turtle DAO functions as the coordination and settlement layer, tracking deposits, managing boost payouts, and maintaining auditability across campaigns. ### Ecosystem-As-A-Service: Turtle Vaults And Campaigns Turtle’s **Vaults and Campaigns** infrastructure forms the operational layer through which liquidity is committed, distributed, and tracked across DeFi. It organizes the flow between foundations, vault providers, and liquidity providers into a repeatable framework that any protocol can deploy as a service. ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/ae97765f90d6.png) Each vault represents a campaign-linked deposit contract coordinated by the Turtle DAO and operated by Vault Curators. A vault is a smart contract at its core: foundations define their desired liquidity parameters, including the target amount, eligible assets, lock-up duration, and reward logic, and the vault is created to enforce these specific terms onchain. Turtle Members supply liquidity directly to the partner, where rewards accrue natively. Each vault is designed to remain fully non-custodial. Liquidity providers sign participation approvals through their own wallets, while assets stay in the partner protocol’s native contracts. Participation and performance are tracked through onchain activity. This design allows campaigns to launch without introducing custodial risk or manual oversight. Fees and boost rewards flow transparently between participants: partner protocols pay a liquidity fee to the DAO, the DAO redistributes boost rewards directly to LPs, and all activity remains visible through onchain data via the smart contract vaults. Vaults also simplify capital allocation for LPs, enabling them to earn yield passively without manually rotating across protocols or campaigns. ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/095d84db1247.png) At the campaign level, Turtle coordinates between Partner Protocols, Vault Providers, and Vault Curators to align incentives and operational tracking. Campaign vaults distribute liquidity directly to whitelisted protocols, where users earn both base and boosted rewards. Optional lock-ups synchronize capital duration with protocol needs, and integrated tracking captures data on performance, duration, and aggregate TVL. Protocols can launch structured liquidity programs through a single integration; vaults manage capital logistics and tracking; and the DAO oversees coordination, auditing, and reward distribution. Meanwhile LPs can easily discover campaigns, deposit through Turtle’s interface, and receive both native and TURTLE rewards without relinquishing custody of assets. ### Turtle Earn Turtle Earn provides the distribution layer through which liquidity campaigns reach their designated end-users. It integrates directly with frontends such as wallets, exchanges, and analytics platforms, allowing them to surface active campaigns within their own interfaces. This structure enables users to review terms and participate in campaigns without leaving the environments they already use. ![](https://shoal.xyz/research/writing/building-defis-investment-bank/img/e054555d4942.png) Distribution partners connect their user base to Turtle campaigns and receive a share of deal revenue proportional to the liquidity they help onboard. Turtle Members deposit directly to partner protocols, earning native rewards from those protocols and any additional boosts allocated by the Turtle DAO. The DAO manages coordination and accounting between all participants. It sources dealflow from partner protocols, collects associated boost revenue, and redistributes it to Members and distribution partners based on verified activity. ### Embedded Distribution and Tooling Turtle’s embedded distribution layer connects the protocol’s liquidity infrastructure to the broader DeFi interface network, integrating directly into existing user frontends. The Earn Widget embeds active Turtle campaigns within these applications, allowing users to discover and participate in verified opportunities natively. Deposits, campaign data, and reward parameters are synced in real time, creating a consistent interface across multiple protocols. Participation and performance are tracked through Turtle’s Leaderboard system. Wallets earn points relative to their total deposits, referral activity, and lockup participation, with boosted weighting for referred liquidity. Weekly snapshots then determine the distribution of TURTLE rewards and campaign bonuses. For foundations and partners, client portals and dashboards provide visibility into campaign performance, emissions tracking, and reward distribution, ensuring liquidity programs can be monitored and adjusted in real time without requiring manual oversight. Together, these tools extend Turtle’s coordination framework into user-facing environments. Campaigns appear directly within existing interfaces, participation is recorded onchain, and reward distribution is managed through a standardized system. ### Tokenomics and Value Flows Turtle’s coordination framework is anchored by **TURTLE**, an ERC-20 utility token deployed on Ethereum, BNB Chain, and Linea. TURTLE coordinates liquidity incentives and governance within the Turtle network, governing how liquidity incentives are distributed, how campaign revenue circulates through the Turtle DAO, and the decisions made about the protocol’s development. TURTLE is transferable and classified as a functional utility token under Swiss law. It carries no ownership, profit-sharing, or redemption rights. Value Flow The Turtle DAO manages capital between three participants: partner protocols, liquidity providers (LPs), and the DAO treasury. 1. Partner Protocols fund liquidity campaigns by paying boost and integration fees. 2. LPs deposit through verified vaults and earn rewards based on their deposit amount. 3. The DAO Treasury collects campaign proceeds, and reallocates it toward future campaigns. In theory, this all works together through a self-reinforcing feedback loop: protocols fund liquidity programs on Turtle, the Turtle DAO distributes rewards, and proceeds flow back into future operations. Governance Governance is executed through Turtle DAO, using OpenZeppelin’s Governor contracts and Tally’s interface. Holders can stake TURTLE to mint sTURTLE, which represents voting and delegation rights for proposals related to campaign parameters, integrations, and protocol operations. Proposals are subject to quorum and creation thresholds to maintain procedural integrity. Treasury execution remains under DAO oversight, with progressive decentralization planned over time. TURTLE standardizes how liquidity programs are funded, distributed, and governed. Protocols pay to access coordinated capital; LPs earn verifiable rewards; and the DAO manages redistribution and governance through TURTLE. ## Closing Thoughts DeFi has solved for access but not for coordination. Anyone can deploy a market or a vault, and liquidity can move freely between them. Yet each system operates under its own parameters, incentives, and time horizons, leaving no shared structure for how capital is discovered, priced, or maintained over time. In practice, this leads to the aforementioned self-reinforcing cycle of short-term incentives and mercenary liquidity that defines much of DeFi today. Turtle is designed to address this coordination gap. Its framework standardizes how campaigns are structured, how deposits are tracked, and how incentives are distributed. Rather than creating new markets and custodying assets, it provides the organizational layer through which existing ones can coordinate capital more efficiently. To reiterate, DeFi has thus far proven that markets and other financial services *can* run without intermediaries; but coordination remains a central challenge among decentralized networks, and the scarcity of liquidity in DeFi is a prime example. An opportunity emerges for protocols capable of encoding *commitment*: to make capital deployment measurable, recurring, and auditable across ecosystems. With the shift in the regulatory environment surrounding digital assets, the demand for bringing net new capital onchain is slowly but surely growing. With new capital coming onchain comes the need for coordination. Through its curated campaigns, structured vaults, and embedded distribution framework, Turtle makes a compelling case to capture this opportunity and become DeFi’s Investment Bank layer. ## Sources - Scott, Zachary. *The Syndicated Loan Market*. [zacharyscott.com/syndicated-loan-market/](http://zacharyscott.com/syndicated-loan-market/) - *The Syndicated Loan Industry Statistics*. Coinlaw, [coinlaw.io/syndicated-loan-industry-statistics/](http://coinlaw.io/syndicated-loan-industry-statistics/) - “Investment Banking.” *Wikipedia*, [en.wikipedia.org/wiki/Investment_banking](http://en.wikipedia.org/wiki/Investment_banking) - “Asymmetric Information.” *Investopedia*, [www.investopedia.com/terms/a/asymmetricinformation.asp](http://www.investopedia.com/terms/a/asymmetricinformation.asp) - *The Ten Commandments of Liquidity Incentives*. Caladan Labs, [caladan.xyz/report-the-ten-commandments-of-liquidity-incentives/](http://caladan.xyz/report-the-ten-commandments-of-liquidity-incentives/) - *Turtle Frontend*. [app.turtle.xyz/](http://app.turtle.xyz/) - *Turtle Documentation*. [docs.turtle.xyz/](http://docs.turtle.xyz/) - *Turtle MiCA Whitepaper*. [drive.google.com/file/d/1DGhHqPv8RVX2XYgVb1yjPFQJQ4Y4961R/view](http://drive.google.com/file/d/1DGhHqPv8RVX2XYgVb1yjPFQJQ4Y4961R/view) ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the Turtle team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Building Crypto’s Everything App > What does a crypto-native Everything App look like in practice? - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-10-24 - Canonical: https://shoal.xyz/research/writing/building-cryptos-everything-app/ - Keywords: crypto, DeFi, prediction markets, privacy, infrastructure, gaming, Infrastructure *As the internet becomes the new infrastructure for finance, payments, and global commerce, a new opportunity emerges to build innovative consumer products that capitalize on the open, permissionless rails of DeFi. In this report we explore DeFi App and how it aims to capture this compelling new opportunity.* ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/f52e9c613ba5.jpg) ## The Convenience Premium: A Tradition Rooted In History “Civilization advances by extending the number of important operations which we can perform without thinking of them.” ― Alfred North Whitehead Throughout history, humans have relentlessly pursued convenience. Nothing illustrates this better than the**convenience premium**: the additional amount that a consumer is willing to pay for goods and services that save time, effort, and make their lives easier. There has always been a market for convenience: a willing buyer and a willing seller. Roman merchants charged higher prices in busy forums than in remote markets. Before refrigerators were invented, American households paid significant premiums for ice delivery. Even money itself has evolved for convenience: from barter to coins to paper to digital assets, each step has been around making money easier to carry around and transact with. Today, the convenience premium lies in digital experiences. Online shoppers are increasingly seeking shorter delivery windows at checkout. Hundreds of millions of people pay for an annual membership to have Amazon deliver almost anything to their door the next day. Food delivery apps continue to see record users and order numbers despite regularly charging 30-40% markups on orders. Time has shown that while the means have changed, the ends sure haven't. People gravitate towards convenience, and they’re willing to pay the price for it. It is no wonder why, across numerous industries, [application-specific solutions have historically evolved into universal, general-purpose solutions](https://writings.succinct.xyz/provable) as they mature. The question then becomes who delivers convenience and captures these premiums in the digital age. ### The Rise Of The Aggregator The post-internet era has been dominated by aggregators. Platforms like Google, Meta, Amazon, among many others, curate information, content, and services from other providers, offering consumers a simpler way to access what they are already looking for. Billions of web pages are searchable through Google. Millions of products are browsable on Amazon. Friends’ photos and life updates appear in one place on Facebook or Instagram. Crucially, these companies do not own what they sell. They own something far more valuable: **the user relationship**. Before the internet, this would have seemed an implausible business model. Distribution was physical, therefore distribution costs were higher, supply was scarcer, and generating outsized profits required controlling most if not all of the supply chain. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/d09a46e2d4fb.png) The internet transformed these dynamics. The cost to distribute information about digital or physical goods to a global audience became nearly free. A single website could handle hundreds, thousands, sometimes even millions of customer transactions at once, with far less overhead than physical stores. Ultimately this reshaped consumer marketplaces by shifting power towards the user. Owning the user relationship became key to gaining a competitive advantage and making outsized profits with the internet, and the business model revolves around user experience above all else. With abundant supply now at their fingertips, what consumers valued most was discovery and curation: finding the best goods and services in a single place. So what lies next? As mobile becomes the new user interface, and consumers demand more integrated digital experiences, the next evolution of aggregators is evolving into Everything Apps. ## Aggregating The Aggregators: Everything Apps Everything Apps, also called ‘Super Apps’, are platforms that bundle multiple services and utilities into a single cohesive interface, most commonly a mobile app. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/d5518adc9fda.jpg) On a desktop, users could manage multiple tabs simultaneously without much friction. This doesn’t quite translate to smartphones, as smaller screens, app-switching delays, repeated logins, lost context, all create friction. History shows the pattern: whenever convenience can be improved, someone builds the solution, and someone else is willing to pay for it. These mobile pain points point to the need for more integrated, multi-service experiences on mobile. The model benefits all participants: - For consumers, Everything Apps provideasimplified, all-in-one experience. Users can access a variety of services without having to leave the app. One login, an integrated payment system, and personalized experiences based on their user preferences. - For businesses, Everything Apps can help reduce user churn and lower Customer Acquisition Costs, while strengthening network effects and creating the opportunity to capture multiple revenue streams from the same user base. The concept was first articulated publicly by Blackberry founder Mike Lazirdis at the [Mobile World Congress in 2010](https://www.mobileworldlive.com/old_latest-stories/mobile-world-congress-2010-keynotes-mike-lazaridis-president-co-ceo-rim/), where he envisioned “everyday apps that people would use because they provided such a seamless, integrated, and efficient experience.” The first live example would come a few years later, when Tencent’s WeChat - a messaging app at the time - would launch WeChat v5.0. This update introduced a handful of new features including payments and gaming, marking WeChat’s shift from messaging to a robust multi-service platform. Today, the most successful Everything Apps combine messaging, personal finance, payments, social networking, e-commerce, and plenty more. Unsurprisingly, they have flourished in “mobile-first” regions where smartphones are the primary - and in some cases the *only* - gateway to the internet. ### So Why No Everything Apps In The US (Yet)? Despite their widespread success in Asia and other mobile-first regions, Everything Apps have yet to truly take root in the US and Europe. The reason is straightforward: structural headwinds.. Digital ecosystems in the US and Europe are crowded with entrenched incumbents: specialized apps which dominate their respective fields and benefit from strong brand loyalty. Users love Venmo for payments, Uber for ride-hailing, Robinhood for trading. Habits like these are difficult to break, and app-store dynamics only further reinforce them. Platform restrictions such as Apple's notorious 30% App Store tax, and restrictive control over native capabilities, made aggregation even more difficult to build and sustain over time. Furthermore, data privacy laws like [GDPR](https://gdpr-info.eu/) and [CCPA](https://oag.ca.gov/privacy/ccpa), combined with aggressive antitrust enforcement, have created compliance burdens that actively prevented platforms from dominating multiple sectors. **But the demand IS there**. The gravitational pull of convenience keeps growing. A [new](https://www.decta.com/company/media/digital-wallet-and-financial-app-user-experience-2025)digital banking report recently revealed that 60% of users add a second finance app specifically because their primary app lacks essential features, while 91% would gladly consolidate to a single app if it offered all the services they needed. And slowly, this shift is happening, in a way. Companies like Meta and Google continue layering in more messaging, shopping, and payment features to their apps. Elon Musk has [openly shared](https://x.com/elonmusk/status/1577428272056389633)his long-term vision for X as ‘the Everything App’, which recently integrated Polymarket, the kind of vertical integration that can very well be a stepping stone for future expansion. Despite regulation, platform politics, and consumer inertia, the Everything App vision is alive in the West. **Aggregators in Finance: A Natural Evolution** If there’s any sector primed to capture this transformation next, it’s finance. Financial services remain fragmented across thousands of banks, brokers, and financial products today. This complexity has always made aggregation valuable. Historically, banks themselves were the original aggregators, combining checking, savings, credit, and investing under one roof. However, they aggregated financial services through regulation, branches, and charters. As technology evolved though, this monopoly would start to crack. The internet would then enable the next generation of financial aggregators. PayPal and Stripe aggregated payment processing. Plaid then followed suit by aggregating bank accounts. Robinhood aggregated trading stocks, options, and crypto assets. From there, the ambition only grew. The following generation of financial aggregators sought to aggregate the **entire** financial stack. On the consumer side, apps like Revolut and Cash App bundled banking, payments, and trading. On the enterprise side, solutions like Ramp and Brex combine payments, banking, credit, payroll, and expense management under one roof. Fintechs have proven the aggregator model works in finance: bundling services creates stickier products, stronger network effects, and captures greater market share. But they’re still boxed in by regulations, jurisdictional barriers, and the tech debt of legacy infrastructure. These pain points beg the question: today’s financial aggregators being built on the right rails? Or are we at an inflection point, a time to explore new rails, new regulations, and unlock new opportunities? **New Rails** Crypto protocols are well-suited for financial aggregators because they are composable, open, and permissionless. Unlike legacy infrastructure, integrating these protocols doesn’t take years of licensing battles or contracts to sign, just code to write and deploy. This programmability makes it easier to embed and integrate more financial services at scale. Today’s blockchains, the rails which crypto protocols live on, also enable significantly lower fees and faster speeds for financial transfers than legacy systems. **New Rules** “Plain and simple: securities intermediaries should be able to offer a broad range of products and services under one roof with a single license..” - Paul Atkins, SEC Chairman Regulators are now dismantling the barriers that previously prevented Everything Apps from flourishing in the US. Today, a financial platform needs separate licenses for each individual service: broker-dealer license for trading, money transmitter licenses in all 50 states for payments, banking charter for deposits, and somehow, the list goes on. This is one major point the SEC's [Project Crypto](https://www.sec.gov/newsroom/speeches-statements/atkins-digital-finance-revolution-073125) aims to address. As per recommendation from the [White House Digital Asset report](https://www.whitehouse.gov/wp-content/uploads/2025/07/Digital-Assets-Report-EO14178.pdf), the SEC is now actively developing a ‘Regulatory Super-App Framework’, which would allow an SEC-registered platform to offer multiple financial services under one platform or license. This extends beyond traditional securities to crypto asset staking, lending, payments and more. **New Opportunities** Altogether, crypto rails unlock access to financial services on a broader, more global scale than its legacy predecessors. Regulations are now being developed to ensure this can develop in a compliant and secure manner. But more importantly, the real unlock is the innovation that the composability of crypto protocols and transparency of blockchains enables. Every new protocol becomes a building block for others, enabling products and services that are difficult for financial services to assemble on their own. Borrowing and lending, payments, trading, identity, can be integrated with one another with code. A financial system built on the internet, for the internet. The most impressive part about this system is that it’s already live. There is already over [$300 billion](https://defillama.com/) in value on public blockchains today. $9.5 trillion has already been traded - in a non-custodial manner - on decentralized exchanges (DEXs). Over $274 billion has been issued in stablecoins to date, which have actively surpassed Visa, Paypal, and legacy remittance systems in [monthly volumes since November](https://app.artemisanalytics.com/stablecoins). Yet DeFi is still largely niche and unknown- why is that? **The Missing Ingredient: The Mobile Moment** Today, over 5 billion people use the internet, the vast majority of this activity taking place on mobile devices. Mobile has become the dominant user interfaces across the globe, and mobile apps the new pipes through which industries reach mass adoption: We’ve seen this playbook before. The explosion of mobile in the early 2010s went hand-in-hand with the rise of social media, as mobile internet access [quadrupled between 2011 and 2015](https://www.comscore.com/Insights/Presentations-and-Whitepapers/2015/2015-US-Digital-Future-in-Focus). The same pattern would unfold into e-commerce, which grew from less than 5% of retail purchases in 2010 to over 18% in 2020. In 2025, smartphones are projected to account for nearly [60% of global retail e-commerce sales](https://sqmagazine.co.uk/mobile-ecommerce-statistics/), or roughly $4 trillion in mobile commerce revenue. 16 years since Bitcoin’s [Genesis Block](https://www.blockchain.com/explorer/transactions/btc/4a5e1e4baab89f3a32518a88c31bc87f618f76673e2cc77ab2127b7afdeda33b), crypto’s Mobile Moment is overdue. Signs are certainly starting to appear. A16z [estimates](https://a16zcrypto.com/posts/article/5-charts-explain-crypto/) there are now 34.4m monthly active mobile wallet users. Coinbase has [previously](https://www.theblock.co/data/alternative-crypto-metrics/app-usage/crypto-apps-ranking-on-the-app-store-in-the-us-finance-category)topped all finance apps on the iOS App Store and even broke the top 10 free apps overall. Jupiter, [the largest DEX aggregator on Solana](https://www.shoal.gg/p/jupiter-exchange-solanas-dex-aggregator) and one of the largest in crypto broadly, launched its mobile app in late 2024, allowing users to onboard with familiar payment systems like Apple Pay. Solana Mobile recently shipped out over 250k orders of the Solana Seeker second-gen phone to more than 50 countries. Across industries, mobile has been the unlock for mass adoption. Crypto will be no different. The next major opportunity to aggregate financial services is clear: a truly crypto-native Everything App. ## DeFi App: The Crypto-Native Everything App Every breakthrough technology needs its killer app. For social, it was Facebook. For AI, it was ChatGPT. DeFi App aims to be that catalyst for crypto. Today, DeFi ultimately functions as a consortium of protocols built on top of one another. DeFi App simply aggregates these multiple layers between chains and their respective applications into a single mobile interface. These layers make up what we call the DeFi Value Chain**:** - **Assets:**These are digital assets that live on blockchains and represent some monetary value. - **Protocols:**These are smart contracts that provide financial primitives and ultimately aggregate user assets together. - **Protocol Aggregators:**These are protocols built to aggregate other crypto protocols, optimizing to find the best rates, prices, and execution for users. - **Interface aggregators**: These are the applications that provide the consumer touchpoint to access all underlying layers and services. In a sense, DeFi resembles an open set of legos. An Everything App would be the box they're packaged in. And as other industries in the post-internet era have proven, whoever controls that box - and defines how users interact with those legos - owns the user relationship and becomes crypto's ultimate aggregator. ### Early Traction DeFi.App has achieved significant early traction since launching in February: - 3.7M+ wallets created across 1.38M active users - $2.87M in protocol fees generated since April. - 80M+ HOME staked by 7.7K+ unique stakers, the majority choosing 12-month lockups. So far, the protocol generated $18.8B in total volume, with the majority ($15.2B) coming from Swaps. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/b3b9b7d469ca.png) Perpsmeanwhile, launched in May and have already generated $3.66B in total volume. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/9433233a84fb.png) But exactly how does it all work under the hood? Here’s how DeFi App intends to capture this opportunity. ### What does DeFi App Offer? ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/28c0da3695a1.jpg) DeFi App provides a simple, cohesive interface for users to access core DeFi services: **Swapping** - Spot trading across multiple DEXs on multiple chains with aggregated liquidity to find the best rates. - DeFi App users can access more assets on DEXs than on traditional CEXs, and better rates depending on the asset and its onchain liquidity. By using an intent-based system, DeFi App users can express their swap preferences with less manual configuration. **Leverage Trading** - Perpetual contracts (Perps) trading, accessible through a simple interface built on a Hyperliquid backend. - Users can access institutional-grade liquidity, transfer fees lower than on CEXs, and maintain custody of their assets. - Users get a dedicated ‘Perp Account’ which they can fund from their existing DeFi App wallets. From there, they can long or short any supported asset, and add leverage if they so choose. It’s important to note that leverage trading can be significantly riskier than spot trading. **Earn** - Users can easily stake the HOME token and access various DeFi yield strategies with transparent risk assessment. **Lending/Borrowing** - Users can borrow or lend supported assets through a simple interface. - DeFi App aggregates multiple borrowing and lending protocols to offer users the best rates across the DeFi ecosystems and chains it supports.* To address common pain points in the onchain user experience, the platform offers: **Self-custodial Wallet Management** - DeFi App creates a wallet for users on all its supported chains to eliminate new wallet set-up hassle for users. This is especially useful for chains that operate on different VMs, like Ethereum and Solana, both of which DeFi App supports. - While CEXs provide this service for users, they custody the assets held in those accounts. Though it’s been almost 3 years since FTX imploded, the principle hasn’t changed much. **Not your keys, not your crypto.** - With DeFi App, users avoid wallet set-up hassle but still maintain custody of their assets. **Easy onboarding/on-off ramping** - Users can easily fund their DeFi App accounts using familiar payment methods like Apple or Google Pay. **Gasless Transactions** - Users don’t pay gas fees when transacting. Gas fees are either sponsored by DeFi App directly or swapped from other tokens on the user's behalf. **Integrated Cross-chain UX** - All swaps are executed for users “behind the scenes”, including those involving different assets on different chains. This helps eliminate the need for users to manually bridge their assets, which could involve multiple steps and transactions otherwise. **Note: this feature is not live yet.* ## System Architecture Stripped down to its purest elements, DeFi App is a c**rypto-native interface aggregator.**It combines and integrates different smart contracts, Solvers, Smart Account infrastructure, APIs, and adapters through a single cohesive interface layer. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/52e8715bc48f.jpg) - **Smart Accounts:**Creates seedless wallets on user’s behalf through AA - **Gas Abstraction: A paymaster to sponsor gas fees for transactions.** - **Transaction Execution: An aggregator system for routing transactions using intents.** - **Frontend interface:**Combines multiple DEXs, lending protocols, and yield sources into one interface. ### Smart Accounts DeFi.App lets users sign up and manage crypto wallets on their behalf using familiar authentication methods like email and social apps. Instead of directly managing private keys and gas fees on multiple chains, embedded Smart Accounts let DeFi.App handle gas, bridging, and signing under the hood for users. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/7944bda8016f.jpg) Smart Accounts are built on the principle of Account Abstraction. The core principle is to separate how an account is verified from how its transactions are actually processed on Ethereum. In simpler terms, it means a public key (a wallet address) is no longer tied to a single private key. Instead, smart contracts can be written to define custom rules for verification, recovery, and fee payment. The vision has been around for a while now, dating back to Vitalik Buterin’s [EIP-86](https://github.com/ethereum/EIPs/blob/master/EIPS/eip-86.md). The core concept was to make wallets more flexible by allowing accounts to operate like smart contracts rather than just externally owned accounts (EOAs) controlled by private keys. The first major implementation was realized through multi-signature (multi-sig) wallets pioneered by Safe, which demonstrated early forms of AA by separating asset custody from transaction authorization. Instead of just one signature with a single private key, protocols could set up contracts to require multiple signatures before a transaction is approved. This proved beneficial for protocols and teams, but less tangible to retail. With [ERC-4337](https://docs.erc4337.io/), AA resurfaced strongly as a key upgrade concept: an additional layer, though not one that altered the core Ethereum protocol. ERC-4337 wrapped user transactions into a higher-level construct known as a ‘UserOp’, short for UserOperation. Any transaction generated from an ERC-4337 enabled wallet would be a UserOp, and UserOps had their own Mempool. From there, Bundlers would aggregate UserOps into regular transactions to be posted to Ethereum mainnet. A core UX unlock that was long envisioned with AA was **gas abstraction**. EIP-4337 enabled this through the use of **Paymasters**, specialized smart contracts which can be programmed to either sponsor fees on behalf of an account or accept gas fees in any ERC20 token besides native ETH. ERC-4337 provided the toolkit for advanced Smart Account logic, but it did not standardize it in a way that was more universally applicable. It also required that users create a **new Smart Account**instead of being able to import their old Externally Owned Address (EOA). This would change with [EIP-7702](https://eips.ethereum.org/EIPS/eip-7702), as part of the Pectra upgrade. EIP-7702 allowed any existing EOA to temporarily function as a Smart Account with additional features like transaction batching, gas sponsorship, alternative gas fee payment. In short, Smart Accounts enable apps like DeFi.App to sponsor gas fees for users, let users pay gas in any ERC20 tokens, and support alternative and more familiar verification mechanisms beyond the standard [ECDSA](https://en.bitcoin.it/wiki/Elliptic_Curve_Digital_Signature_Algorithm) commonly used in crypto today. And central to Smart Accounts and Account Abstraction is proper and secure key management. ### Key Management DeFi.App integrates several providers for secure key management of newly-generated user accounts. The implementation varies slightly between EVM and SVM environments, but together create a smooth onboarding and transaction flow for users: **Turnkey** Turnkey is the custody and signing provider that underpins account creation on both Solana and EVM chains. - On Solana, Turnkey directly manages the user’s wallet where assets are actually held. Because funds live in this wallet, importing the key into another wallet provider, like Phantom, would display a balance. - On EVM chains, Turnkey generates a signer key for each user. This signer key doesn’t hold any funds itself - but it does authorize transactions via a linked smart account. In practice, Turnkey provides the signature layer while funds themselves live in a generated smart contract. **Zerodev** ZeroDev provides DeFi.App’s Smart Account infrastructure for EVM chains. - User funds on EVM chains are stored in an EIP-4337 smart contract wallet managed by ZeroDev. - The wallet is controlled by the Turnkey signer (described above), but custody of assets lives entirely within the ZeroDev smart contract. Effectively, ZeroDev handles the vault and execution layer for EVM assets, while Turnkey supplies the signer that secures it. **Dynamic** Dynamic is the wallet connector and onboarding layer that ties the system together, managing user authentication mechanisms. When a new user signs up, Dynamic provisions two embedded wallets: - A Solana wallet (Turnkey-managed, holds funds directly). - An EVM Wallet consisting of a Turnkey signer + ZeroDev smart account (signer controls, smart account holds funds). Dynamic also allows users to export their keys. For Solana, this means exporting the Turnkey wallet. For EVM, users can export the signer key, but balances won’t appear in a standard EOA wallet since funds live in the ZeroDev contract. Besides simpler user onboarding, Smart Accounts also enable another major UX breakthrough for DeFi.App: **the ability to pay transaction fees in any token.** **Gas Abstraction** It’s critical to understand that users still **pay a fee to DeFi.App when transacting.**Transactions and blocks cannot be uploaded to a blockchain without a fee to cover the associated computational costs. These fees are paid in the native token of that blockchain, which in itself is a core part of the token’s utility. While it is not possible to avoid gas fees, it is possible for application developers to make sure their users don’t need to worry about them. DeFi.App enables gas abstraction across all its supported chains, though the implementation varies by the execution environment (VM) of that chain. ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/02615eec9870.jpg) On EVM chains, gas fees are sponsored by ZeroDev architecture and funded by Defi App transaction fees.On Solana, this is handled by a custom paymaster contract. The gas fee is quoted to the user transaction, and swapped from the paying token into SOL. **Intent-based Execution** DeFi.App implements an intent-based system for transaction execution, designed to give users a simple experience with optimal pricing. An “intent” has no formal definition, but it functions similarly to a transaction, only instead of specifying the exact execution path, the user specifies their desired outcome. This approach focuses on removing the complicated parts of the onchain transaction experience like sourcing liquidity, ensuring sufficient gas, and bridging if another chain is required. For example, a user may want to swap 100 USDC for SOL, but doesn’t know if the best prices are on Orca, Raydium, or elsewhere. **How does this work on DeFi.App?** ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/56980b00d937.jpg) DeFi.App runs a Solver transaction aggregator that taps into multiple liquidity sources across chains and protocols, presenting users with the best available price. The platform integrates with 0x, 1inch, Bebop, Debridge, Dodo, Enso, Jupiter, LiFi, Odos, Open Ocean, Paraswap, Relay, and Stable. Proprietary routing logic in the backend evaluates these options in real time, ensuring users see a single, streamlined execution flow. Cross-chain support is native to this system. Traditionally, swapping USDC on chain A into USDC on chain B (or even USDC → USDT across chains) would require multiple bridging steps. With DeFi.App’s solver network and routing logic, cross-chain swaps are presented to the user as a single transaction, no different from a same-chain swap. **MEV-Protection with Jito** One particular underrated feature DeFi.App enables is to let users opt-in to protect themselves from MEV on Solana. MEV is often captured through sandwiching/arbitraging unsuspecting users. Jito built the Jito-Solana Validator Client to help mitigate this on Solana. Users can submit transaction bundles to Solana validators running the Jito client. These transactions get executed atomically, in order, therefore either they all execute or fail altogether. **Tips (**bonus fees)areattached to bundles to incentivize validators, priority going to the highest bidder. Broadly speaking, DeFi.App supports three transaction modes: **Classic, Jito,**and**Auto. Classic** **mode** provides standard routing to validators running the Agave validator client. **Jito** mode routes transactions to validators running the Jito-Solana client, while **Auto mode** selects the best option for the user at the time. DeFi.App Users can opt-in to MEV protection by simply toggling “Jito Mode”, which will then route their transactions through Jito-enabled validators, leveraging the bundling and tipping system. ## Capturing The Convenience Premium: DeFi.App’s Business Model Earlier, we highlighted the impact of the convenience premium throughout history: people are willing to pay a premium for goods and services that make their lives easier, plain and simple. Aggregators dominated the post-internet era by focusing on owning the user relationship and experience. In an increasingly mobile-first world, the next evolution of this model is the Everything App. The next question that follows is how exactly do the aggregators, the harbingers of convenience that don’t own what they sell, actually generate and accrue value? Let’s examine DeFi.App’s business model. **The HOME Token** ![](https://shoal.xyz/research/writing/building-cryptos-everything-app/img/2eacc15402b0.png) DeFi.App and its ecosystem is powered by the $HOME token. HOME launched on June 10, 2025, and currently lives on Solana, Base, and BNB Chain. There are 10 billion HOME tokens in total. **Token Utility** HOME plays several key roles across the DeFi.App ecosystem: - **Governance:**HOME stakers can create and vote on any proposals that come up around the DeFi App protocol, whether it’s revenue sharing models, token buybacks or yield to $HOME stakers, which feature comes next for the platform, and so on. Companies can also buy and stake HOME to accelerate their own integrations into the ecosystem. Over 5.9k votes have been cast over the [first 5 proposals](https://snapshot.box/#/s:defi.app). - **Gas Abstraction:**Users who hold HOME in their DeFi.App wallets can transact on any supported chain and pay gas fees in HOME. Defi.App’s treasury automatically purchases HOME from the user at open market rates and uses that HOME to subsidize that user’s gas fees on their behalf. This is facilitated through the HOME [Staking contract](https://basescan.org/address/0xC9714F8f036087d801f38C4105194e150d3a1864#tokentxns), which provides collateral to support gas subsidies and conversions. - **Incentive Coordination**: Users can lock HOME to earn XP, which accrues on a daily basis and may be a qualifying criteria for future HOME airdrops. Locking HOME can activate up to a 3x multiplier on XP gains, with more XP for longer lockups. Data shows that the majority of HOME token holders are on Base (83k holders), with ownership on BNB Chain (6.4k) and Solana (1.9k) notably lower. **DeFi.App’s Business Model** DeFi.App generates revenue through protocol fees. Every swap, deposit, leveraged trade - *any user action that generates a transaction* - generates a protocol fee. Think of this fee as the convenience premium that DeFi.App charges. The business model is designed to work the following way: 1. A user joins DeFi.App. 2. Each time they swap, borrow, lend - each action generates a protocol fee. 3. Fees are allocated however governance sees best fit. 4. Fees are distributed, often through buybacks or allocated for future incentives. 5. As more HOME is staked, token supply decreases, interest grows, and… 6. A new user joins DeFi.App. DeFi App charges 0.02% on swaps, and 0.01% on perps. Today, as much as **80%** of DeFi App’s net fee revenue is allocated towards HOME buybacks for its treasury reserve, as was recently voted on in [DIP-004](https://snapshot.box/#/s:defi.app/proposal/0x7244e17449663fce4bcde5b39a0bf896e80323c173882e1d4ec8b82d1e972a80). ## Analysis It’s time to unpack what we just learned and reflect on the challenges and opportunities Shoal Research sees ahead for DeFi.App. ### Challenges And Considerations DeFi.App is building a solution to a very real problem: a lack of simple, beginner-friendly access to DeFi. This isn’t a new problem by any means though, and the DeFi.App team are not the only ones actively building to solve this problem. The biggest, high-level challenge we foresee DeFi.App facing is competing with bigger “crypto-adjacent” firms that have a strong distribution advantage and bigger user-base. Firms like Coinbase and Robinhood come to mind. This may even extend beyond crypto firms: major fintechs and even banks can push for their own Everything App, incorporating crypto and DeFi alongside other non-crypto services. Still, most of these firms require users to fill out KYC verification beforehand, which can be a major onboarding pain and bottleneck. DeFi.App has an upper-hand here: users can quickly sign up with their email and fund their account with Apple Pay. However, this is where major wallet providers like Phantom and Metamask, who also very much stand to benefit from launching their own ‘Everything App’, stand to be a bigger threat and concern. In a way, these apps already function as “crypto-native Everything Apps” and offer multiple integrated services similar to DeFi.App. Therefore, non-custodial wallets are currently the biggest competitors to DeFi.App we see as of today as they can provide similar offerings relatively easily. That said, while there may be less room to compete on service offerings, there will always be room to compete on pricing and execution rates against wallet providers and other protocols. After that, it becomes a race to who can support more chains, more assets, and offer more services to users. **Moving on to more crypto-native challenges,**DeFi.App, like many other crypto protocols, need to make sure they can scale to keep up with the expanding multichain landscape. There are currently 300 chains, some believe we will have 1000s. DeFi.App currently only serves 6. While many of these chains are not active or have not generated any real sustained activity, users are continuously traveling to different chains and ecosystems. Corporations like Circle and Stripe are launching their own chains. Who knows who else will follow. As an “aggregator of aggregators”, it’s in DeFi.app’s best interest to be able to serve their users wherever they want to go. This is a hard problem to solve, but if users can access *virtually any chain*through DeFi.App’s simple interface, this can be a major advantage and differentiator. Conversely, if DeFi.App chooses to keep their overall chains and ecosystems limited, someone else will expand to serve users of any asset on any chain. It even becomes advantageous for infrastructure-focused teams, such as those building interoperability protocols, to create their own user-facing application to let users access any asset on any chain. The easiest solution for DeFi.App to hedge against this risk is to integrate a major interoperability protocol, like Hyperlane or LayerZero, and tap into their existing distribution and scale with them. A much more difficult approach will be to build a proprietary solution. Either way, we believe DeFi.App needs to dream big, and embrace aggregating “everything”. This starts with providing users access to any asset on any chain. ### Exciting Opportunities and Outlook Overcoming these challenges will be critical for DeFi.App’s short and long-term success, but there is plenty to be excited for. By building around aggregation and the mobile-first experience, DeFi.App is following the same playbook that has kickstarted major growth and adoption cycles in other digital industries as it sets out to build the first crypto-native Everything App. Consumers have expressed a strong preference for mobile-first experiences in today’s age. DeFi.App is building a mobile app for that. Interest in crypto will likely continue to grow as enterprises and major institutions continue to either experiment with or fully embrace blockchain solutions. And they’re actively piling in because for the first time in crypto’s history, the US is actively developing pro-innovation guidelines and regulations to legitimize this technology. This alone won’t bring “the next million users” onchain, but the path to mass adoption all starts from there. It doesn’t hurt that aggregators have done quite well overall, either. Once Google had integrated search results with user data, they were able to offer targeted advertising, and have made hundreds of billions in revenue over the years. Meta had a similar approach, integrating their feed with user’s data to unlock targeted advertising, and generates over $100b annually, with most (97%) of that revenue coming from targeted ads. WeChat, the poster child for Everything Apps today, has earned hundreds of billions over the years from in-app purchases and more. In DeFi, numerous protocols have already demonstrated the revenue potential of frontend applications. Photon and Pump Fun have both seen upwards of $6m in daily fees before. Axiom hit over $250m revenue in 8 months. Though maybe not all apples-to-apples comparisons, these examples demonstrate there is lots of demand and value to capture in frontends and aggregators. ## Ideas And Suggestions from Shoal Some ideas and suggestions Shoal Research believes could help contribute to DeFi.App’s success moving forward: - *Expand to support more chains and assets over time. Dream big: every asset, every chain should be accessible through DeFi.App’s mobile interface.* - Integrate an underlying cross-chain messaging protocol so DeFI.App’s chain coverage can easily scale with them. - Integrate an AI chatbot UX to let users type out their preferred action. Bonus points for voice mode to make it even more convenient. - Enable non-users to onboard easily via text message. Text your friend some money through a link. They sign up for DeFi.App in seconds. - Enable a “Privacy Mode”: Integrate a proven privacy solution like Railgun to let users transact privately when they want to, the same way they can toggle “Jito Mode”. This may be trickier to manage from a legal perspective, but can be a massive benefit and differentiator for DeFi.App long-term. - Offer MEV protection on all chains, not just Solana. Integrate a Flashbots/MevBlocker RPC endpoint for EVM chains. - Productize (or even better - open source!) a plug-in that teams can use to easily add their protocol or service to DeFi.App’s interface. Importantly, these are merely ideas we suggest the DeFi.App team take into consideration. Some of these ideas are more practical and urgent than others. Some may not make sense right now, but may become critical in a few months or a year. Time will tell. ## Closing Thoughts History has repeatedly shown us that the convenience premium is timeless. In 2025, aggregators have captured this premium and dominate consumer marketplaces by delivering superior user experiences. Mobile devices have taken over the majority of internet traffic as they have evolved to offer more services and information than desktops, conveniently fitting in everyone’s pocket. At Shoal, we believe the same plot will inevitably unfold on crypto rails. Fintechs have proven the demand for convenient, aggregated access to financial services, but they still face centralization risks and remain barred to geographical barriers. Crypto protocols are open, programmable, and permissionless to integrate, and have already moved upwards of twelve figures in value across the globe. Major enterprises and institutions are adopting stablecoins for payments. Countries like the US are actively pushing to establish pro-crypto and pro-innovation regulatory frameworks. It’s becoming clear that the time to build crypto’s everything app is now. ## Sources - **Aggregating the Aggregators.”** *Fintech Takes*, 14 June 2024, fintechtakes.com/articles/2024-06-14/aggregating-the-aggregators/. Accessed 24 Oct. 2025. - **“Convenience Premium: Consumer Trends 2024.”** *Morgan Stanley*, www.morganstanley.com/ideas/consumer-trends-2024-convenience-premium. Accessed 24 Oct. 2025. - DeFi App. *DefiLlama*, defillama.com/protocol/defi-app. Accessed 24 Oct. 2025. - DeFi App Staking. *Dune*, dune.com/defiapp/defiapp-staking. Accessed 24 Oct. 2025. - de la Mano, Matías. *Open Platforms and Innovation: The Case of the Linux Operating System*. London School of Economics, 1999, eprints.lse.ac.uk/22471/1/wp20.pdf. Accessed 24 Oct. 2025. - **‘“Digital Assets.”** *The White House*, www.whitehouse.gov/crypto/. Accessed 24 Oct. 2025. - ERC-4337 Documentation. docs.erc4337.io/. Accessed 24 Oct. 2025. - EIP-7702 Documentation. eip7702.io/. Accessed 24 Oct. 2025. - **“New Study Reveals Using Multiple Financial Apps Is Necessity, Not Choice, for Most Users.”** *Nordic Fintech Magazine*, nordicfintechmagazine.com/new-study-reveals-using-multiple-financial-apps-is-necessity-not-choice-for-most-users/. Accessed 24 Oct. 2025. - **“Statistics That Prove How Your Delivery Speed Impacts Your Business.”** *Meteor Space*, 13 Feb. 2025, meteorspace.com/2025/02/13/statistics-that-prove-how-your-delivery-speed-impacts-your-business/. Accessed 24 Oct. 2025. - Thompson, Ben. “Aggregation Theory.” *Stratechery*, 17 July 2015, stratechery.com/2015/aggregation-theory/. Accessed 24 Oct. 2025. - Thompson, Ben. “Defining Aggregators.” *Stratechery*, 24 Apr. 2017, stratechery.com/2017/defining-aggregators/. Accessed 24 Oct. 2025. - **“Uber Eats Statistics.”** *Business of Apps*, www.businessofapps.com/data/uber-eats-statistics/. Accessed 24 Oct. 2025. - **“10 Years of WeChat History.”** *Eggsist*, www.eggsist.com/en/insights/10-years-wechat-history/. Accessed 24 Oct. 2025. - **Super App Market in United States.** *Research and Markets*, www.researchandmarkets.com/reports/6105712/super-app-market-in-united-states. Accessed 24 Oct. 2025. - **“Superapps.”** *Venture Vine*, Medium, medium.com/venturevine/superapps-6a425de7db87. Accessed 24 Oct. 2025. - **“The Era of Provable Software.”** *Succinct Writings*, writings.succinct.xyz/provable. Accessed 24 Oct. 2025. ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the DeFi App team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Building The Real-Time DeFi Stack > It's time to embrace DeFi protocols that adapt to real-time market conditions. - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-10-22 - Canonical: https://shoal.xyz/research/writing/building-the-real-time-defi-stack/ - Keywords: stablecoins, crypto, DeFi, market making, yield, infrastructure, Solana, Ethereum ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/6fd52c3dfb8a.jpg) ## The Experience Is The Product Over the past three decades, the World Wide Web has reshaped the world and how it functions as we know it. As software gradually replaced physical distribution channels, the user experience has become the product. Look no further than the role which aggregators like Google, Amazon, Facebook (among plenty others) play in everyday life for evidence. By delivering cohesive user experiences, these platforms came to dominate consumer markets. It can certainly be argued that DeFi faces a similar fate. The early internet began as a patchwork of disconnected webpages and hyperlinks, and so too, the broader DeFi landscape today spans hundreds of chains, tens of thousands of protocols, and millions of tradable assets, many of which are forks. This replicability is indeed a feature, not a bug. As [Richard Stallman laid out](https://www.gnu.org/doc/fsfs3-hardcover.pdf), the right to reproduce, modify, and share code freely is a pillar of truly free software. In practice, however, DeFi’s open-source, permissionless design has created as much fragmentation as it has driven innovation. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/4de7098d180c.png) ## The Unified Margin Opportunity A majority of today’s DeFi volume and activity still concentrates around a few primitives: swaps, perps, staking services, and money markets. Yet there’s no simple, intuitive way to access them all through a single margin account. To trade perps, users deposit collateral to a specific account on a specific exchange. To borrow or lend, they need to withdraw and then deposit to a new position on another protocol. These DeFi primitives operate in isolation, fragmenting liquidity and leaving large amounts of capital idle and unproductive. The lack of a unified margin account hasn’t been a conceptual problem so much as it’s been a structural one. Different DeFi protocols maintain their own accounting and risk parameters. An AMM tracks LP positions and pool reserves. A lending market tracks deposits and debt and evaluates protocol health. A perps exchange needs to track margin balances, open interest, funding rates, and liquidation thresholds. Each protocol has its own requirements in order to remain solvent. They can integrate with one another via smart contract calls, but they can’t share balance sheets. This localized risk design is what makes DeFi safe in isolation but inefficient in aggregate. However, by building these primitives around a single shared risk engine, the opportunity to build a unified margin account emerges. This design would enable a user’s deposit to support multiple roles across trading, lending, staking, while maintaining consistent solvency rules. Collateral that once sat idle could be reused across products. A trader’s gain in one market could balance a loss in another, tightening spreads and reducing redundant margin. Still, connecting DeFi primitives does not address the inefficiencies in their underlying mechanics. ## DeFi’s Static Trap The DeFi primitives we know today have processed trillions in volume, supported hundreds of billions in liquidity, and generated billions in protocol revenue. Like the internet, their greatest strength lies in being borderless, transparent, and always-on. Most protocols were designed as a set of smart contracts with fixed parameters that can run autonomously, for an indefinite period of team. Some teams have introduced governance or upgrade hooks for managing in critical situations, but between constant-product AMMs, fixed loan-to-value ratios, and passive liquidity provisioning, much of DeFi still operates on static logic. These design choices made sense initially. Fixed parameters gave users trust: DAI’s stability, Uniswap’s simplicity, and Aave’s predictable risk. In stark contrast, however, traditional financial systems, which handle more volume in a single day than DeFi does in a month, operate on dynamic parameters that adjust to real-time conditions. Banks, market-makers, and derivatives desks continuously reprice risk, widen spreads, and adjust leverage based on market activity. Building DeFi primitives that respond to real-time market conditions unlocks better performance, safer risk management, and more efficient and productive use of capital. These protocols can adjust key parameters such as collateral ratios, borrow-lending rates, and execution routing based on real-time market conditions. This responsiveness matters most during market stress. When asset prices move sharply, parameters can tighten automatically to prevent unnecessary liquidations and preserve solvency. During more stable conditions, they can loosen to improve capital utilization and allow collateral to work more efficiently. In both cases, risk settings evolve with the market rather than remaining static. The question then becomes how this looks like in practice. ## A Deep Dive Into Flying Tulip Flying Tulip introduces an onchain financial system designed to standardize pricing, credit, and risk across a unified suite of markets. The protocol brings together spot trading (AMM + CLOB), lending, perpetuals, insurance, and a protocol-native stablecoin within a shared margin framework. Flying Tulip is built around three core design goals. First, to make collateral reusable across multiple functions. A single deposit can support several forms of activity, earning base yield, margin for trades, or loan collateral, without being locked into a single utility or module. Second, price risk using real, executable liquidity instead of static references or delayed oracles. The protocol measures depth and volatility across its markets in real time, and those readings feed directly into parameters like collateral ratios, funding rates, and liquidation thresholds. Third, to recycle protocol cashflows back into the system. Revenue from trading, borrowing, and settlements flows toward the FT token through programmatic buybacks or user distributions, linking network activity to value capture in a transparent way. These design goals shape two outcomes: better yield and better user experience. Better yield comes from capital efficiency. The same deposit can earn base yield while simultaneously securing loans, resting limit orders on the CLOB, or providing margin for derivatives. Assets stay productive across the stack rather than sitting idle. Better UX, meanwhile, comes from integration. Core mechanics are encoded directly in contracts and applied consistently across products. The same depth-aware inputs that determine trade execution also inform borrowing limits, funding adjustments, and liquidation logic, ensuring that all parts of the system respond to market conditions in the same way. Flying Tulip’s design builds on the original [Deriswap](https://andrecronje.medium.com/deriswap-capital-efficient-swaps-futures-options-and-loans-ea424b24a41c)[concept](https://www.theblock.co/linked/85431/yearn-finance-founder-andre-cronje-introduces-new-defi-protocol-deriswap) Andre Cronje introduced in 2020. The concept he laid out was simple: to merge multiple DeFi functions into a single, more capital-efficient protocol. Deriswap proposed that the same liquidity pool could be used for swaps, lending, and options simultaneously in order to reduce idle liquidity. which proposed reusing liquidity across swaps, lending, and options. Here, that principle extends to the full financial stack. The protocol’s architecture connects trading, credit, and risk management within a single environment, allowing capital and exposure to be managed through one unified framework. Flying Tulip will launch natively across multiple chains, beginning with the **Sonic L1**, and expanding to Ethereum, Avalanche, BNB Chain, and Solana. Each chain will feature its own local instance of Flying Tulip, ensuring liquidity and settlement remaining within native environments across all deployments. ## The Flying Tulip Stack Flying Tulip consists of an integrated suite of DeFi components. ftUSD, lending, spot, and perpetuals operate from a shared liquidity base and unified margin layer. Parameters across the system adjust to market conditions in real time, keeping pricing, collateral, and risk consistent across products. ### ftUSD: The FT- Native Stablecoin To avoid dependency on third-party stablecoins for bootstrapping liquidity, Flying Tulip introduces ftUSD, a protocol-native, dollar-pegged stablecoin. that serves as the primary margin and settlement asset across the protocol’s AMM pools, order book, and derivatives markets. ftUSD is minted by depositing supported stablecoins or blue-chip assets and can be held as a stable unit of account or staked to sftUSD to earn yield from Flying Tulip’s underlying yield strategies. Staking represents a conversion into the yield-accruing pool, with distributions reflected through a variable exchange rate between sftUSD and ftUSD. Collateral deposited to mint ftUSD is deployed across delta-neutral strategies across several venues, executed programmatically onchain to remain transparent and auditable. Assets are allocated across money markets, staking pools, and hedging positions, and the yield generated on these positions is then distributed to sftUSD holders while proceeds from unstaked ftUSD are retained by the protocol to fund operations and liquidity. **How It Works** ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/0659da011f94.png) ftUSD maintains its dollar peg through a delta-neutral strategy, wherein collateral backing ftUSD is deployed to earn yield onchain while keeping net exposure to market movements near zero. Yield for ftUSD originates primarily from the interest earned on supplied collateral in money markets i.e. Aave, plus staking rewards generated on the long side of hedged positions. Positions are rebalanced periodically and constrained by caps, sizing bands, and venue limits to preserve solvency and reduce volatility transmission. The yield, realized after deducting borrow costs, fees, and safety buffers, is distributed proportionate to the amount of sftUSD held. Distributions to sftUSD holders are reflected through a variable exchange rate between sftUSD and ftUSD. Unstaked ftUSD does not accrue yield; its proceeds are directed to the protocol’s treasury to fund operations, expand liquidity, and support the token-first model. This structure allows collateral to remain productive while minimizing directional risk. The long (staked) and short (borrowed) legs are calibrated to offset one another under normal conditions, reducing the likelihood of liquidation during volatility. The approach prioritizes conservative sizing and transparent, programmatic management. All strategies and rebalancing logic are executed onchain and are auditable through public dashboards. ftUSD’s underlying yield strategies operate fully onchain, with key parameters such as pool exchange rates and collateral exposures remaining transparent to track performance and risk composition. All positions are marked to market and managed under the same delta-neutral framework, with periodic adjustments based on observed liquidity and volatility conditions. A native stablecoin like ftUSD allows Flying Tulip to price risk, settle trades, and manage liquidity under a single unified framework. Anchoring market activity to such a stablecoin enables Flying Tulip to unify collateral management across its AMM, CLOB, and derivatives markets. ftUSD serves as the base unit for margin, settlement, and lending, allowing the same collateral to support multiple positions without leaving the system. Yield generated from these activities, such as funding payments or lending carry, remains within the protocol’s liquidity base and is routed either to sftUSD stakers or to operational reserves according to policy. ### FT Lend: A New Money Market Structure Flying Tulip introduces FT Lend, a native money market integrated directly into the protocol’s unified margin system. It allows users to borrow and lend assets using the same collateral that supports trading, settlement, and derivatives positions across the protocol. FT Lend is designed from the ground up to operate within an adaptive framework informed by real-time market data on liquidity depth and volatility. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/6b68aa9df0e9.png) Most of the major money markets today rely on fixed loan-to-value (LTV) ratios and over-collateralization thresholds. Borrowers deposit collateral exceeding the value of their loan, maintaining a margin buffer that depends on the price of the underlying asset. Liquidation occurs when the debt obligation surpasses the collateral’s adjusted value. Static LTV parameters are chosen for their simplicity and the predictability they offer. They let protocol designers fix a borrow threshold for each asset, defining the maximum debt a borrower can take relative to posted collateral. These thresholds typically assume worst-case volatility and enforce over-collateralization, ensuring lenders remain protected during rapid price movements. However, this design also limits capital efficiency and can have cascading effects. When markets are stable, capital remains under-utilized; when volatility spikes, static parameters amplify liquidation cascades as prices fall and collateral thresholds are reached across the protocol. Static risk parameters, by design, cannot differentiate between stable and volatile market conditions. FT Lend replaces static assumptions with adaptive parameters that adjust continuously to market conditions. Borrow limits, interest rates, and liquidation behavior are derived directly from onchain data rather than fixed governance rules: - **Trade-Weighted LTV (TWAR).** Borrowing power scales with position size relative to pool depth. Smaller loans receive higher limits, while larger ones face progressively lower caps to account for execution impact. The collateral-to-pool ratio determines the maximum permissible LTV, which tightens predictably as position size or volatility increases. - **Volatility-Aware Rates.** Borrow costs adjust according to realized dispersion. Assets are classified as stable or volatile, and rate formulas respond automatically: during high volatility, rates rise and borrowing capacity contracts; during calm periods, rates compress and available credit expands. - **Snapshot LTV.** When a borrower opens or modifies a position, borrowing limits are locked to current market conditions. Existing positions remain under those limits even as policy parameters change, preserving predictability while allowing future loans to reflect updated market states. - **Market-Aware Liquidations.** Liquidations are executed through a Liquidity Engine that aggregates AMM reserves and order book depth to minimize slippage. Before execution, the engine simulates price impact, segments large positions into smaller trades, and prioritizes resting CLOB orders when available. This approach reduces volatility transmission and ensures orderly liquidation behavior under stress. - **Unified Collateral System.** The permissionless layer mirrors the AMM: each trading pair hosts its own lending market, parameterized by live depth and volatility. The permissioned pool governs a curated set of cross-margin assets. Deposits in this pool remain productive across the system—earning base yield, backing open orders, and securing perpetual positions simultaneously. A debt-netting mechanism offsets delta-neutral exposures, mitigating conventional liquidation paths and reinforcing the collateral logic that also underpins ftUSD. All parameters across LTVs, rates, and utilization update onchain in real time. The AMM publishes time-weighted (TWAP) and reserve-weighted (RWAP) price windows that feed directly into lending logic, ensuring collateral values reflect executable market conditions. Borrowers pay interest; suppliers earn it. Cashflows are settled through the token-first model, where lenders receive FT-denominated yield distributions and policy fees flow into protocol reserves and buyback mechanisms. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/d640d6c7c9f5.png) Flying Tulip’s protocol research demonstrates that collateral utilization adjusts in line with both market volatility and liquidity depth, as illustrated above. As volatility rises or liquidity thins, the maximum permissible LTV declines along a predictable curve, allowing leverage to expand and contract with market stability rather than remain fixed. This relationship directly informs how FT Lend calibrates borrowing power and liquidation behavior in real time, ensuring that capital allocation across the protocol remains both responsive and risk-aware. ### Adaptive AMM-CLOB Spot Trading Flying Tulip offers spot trading through a dual-engine exchange that combines an adaptive AMM with a central limit order book for execution. The two systems operate within a unified framework, enabling liquidity to route dynamically between continuous and limit-based liquidity depending on market conditions. Orders execute along the path offering the best realized price and minimal impact, designed to maintain consistent pricing across the protocol. The AMM is curve-adaptive, referencing short-horizon volatility inputs including realized volatility (rVOL), implied volatility (IV), time-weighted average price (TWAP), and reserve-weighted average price (RWAP) to continuously reshape its pricing curve. In stable conditions, the curve flattens toward a constant-sum form to minimize slippage and compress bid-ask spreads. During volatility spikes, it steepens toward constant-product behavior to preserve depth and maintain price integrity against rapid order flow. This allows markets to self-regulate without manual intervention, adjusting curvature to prevailing liquidity and volatility conditions. Price and flow data are smoothed through exponential moving averages (EMAs), dampening the effects of short-term swings while allowing the protocol to respond to structural market shifts. Guardrails limit how far the curve can migrate during a single window, ensuring predictable behavior for traders and liquidity providers alike. The result is a trading engine that adapts continuously to changing environments while avoiding instability. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/d802ddfeffb7.png) Before execution, each swap is simulated onchain to assess its price impact relative to current pool depth and defined pool thresholds. Large trades are automatically broken up into several orders to smoothen market impact. If better pricing is available through the CLOB, orders are routed there by priority; while any remainder clears through the AMM. Fees are dynamic, designed to lower in stable markets to encourage activity, while raising during volatility to compensate LPs for their risk accordingly. LPs can supply assets across full or concentrated ranges. A full-range position provides consistent fees on a *x*y=k*basis. Concentrated liquidity allows higher fee density while prices remain within range but requires active rebalancing when markets trend. The adaptive curve moderates these dynamics: spreads tighten when markets are stable and widen when volatility increases, reducing divergence loss during stress periods. Fees function as a dynamic policy variable rather than a fixed parameter, adjusting with observed market conditions. The schedule moves toward its lower bound in calm regimes, attracting flow, and rises toward its upper bound in volatile conditions, compensating liquidity providers and slowing adverse flow. All bounds and coefficients are publicly visible and updated on-chain. By unifying AMM and CLOB execution under a shared liquidity and risk framework, the protocol maintains consistent price discovery across conditions and avoids fragmenting depth. The AMM also serves as the foundation for other components; perpetual markets, lending, and liquidations, all of which reference AMM-derived price and depth windows for funding, collateral valuation, and impact-aware execution. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/2bedec750805.png) Flying Tulip’s protocol research demonstrates that AMM curvature dynamically adjusts to market volatility, as illustrated above. This figure compares the simulated performance of several LP strategies across range-bound, uptrend, and downtrend regimes. Concentrated and trigger-based strategies generated higher fee income during stable periods, while passive LPs preserved value through directional moves. The results highlight the trade-off between reactivity and exposure: adaptive strategies outperform in equilibrium markets but converge toward passive outcomes when volatility rises sharply. This relationship underpins how the protocol’s adaptive curve manages liquidity under stress. By adjusting curvature in response to volatility, the AMM preserves depth, stabilizes fee generation, and supports collateral assets such as **ftUSD**, ensuring yield and price stability across the broader protocol. By unifying both market types under a shared liquidity and risk framework, Flying Tulip’s spot module maintains efficient pricing across conditions and avoids fragmenting AMM and orderbook liquidity. The CLOB also incorporates volume-based fee scaling, maker rebates, and a referral system that rewards LP and trading activity, designed to align user incentives with liquidity depth. ### FT Perps Flying Tulip introduces a native perps engine designed to let users take long or short positions on assets with leverage, settling directly to prices discovered within the protocol’s own AMM and CLOB. FT Perps derives these values internally from the protocol’s live trading activity. Prices, funding rates, and liquidation thresholds reference actual executable liquidity rather than delayed or externally sourced data. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/a7fa97f4e4f4.png) This design allows the protocol to align mark prices with real trading depth. If an asset changes hands at a given price on the AMM or CLOB, that becomes the effective settlement price. Prices are updated on a continuous basis. Funding rates adjust automatically based on borrowing demand, position imbalances, and the effective cost of holding long or short exposure within the protocol. When longs are effectively borrowing stable assets to hold, and that borrowing becomes expensive, the funding rate reflects it; when the imbalance reverses, funding direction flips. All funding inputs and parameters are transparent and observable onchain. Perpetuals can be traded in isolated or cross-margin modes. In isolated mode, collateral supports a single position, containing risk within that market. In cross-margin mode, users can post collateral from the permissioned Lend pool, allowing a single deposit to back multiple positions across the Flying Tulip protocol while continuing to earn its base yield. Borrowing power and leverage limits are determined by live depth and volatility metrics and are snapshot at the time a position is opened or adjusted to prevent retroactive changes. Liquidations follow the same logic that governs the rest of the protocol. When a position approaches its liquidation threshold, the engine simulates the next execution step on the AMM’s adaptive curve. If the modeled impact exceeds safe limits, the position is unwound gradually, crossing resting CLOB orders first and breaking up the remainder across the AMM, to minimize price disruption. All positions settle in ftUSD, Flying Tulip’s native settlement currency. ftUSD itself does not yield, but users can stake to sftUSD to receive protocol distributions. Liquidity providers who opt into settlement pools earn per-settlement fees, supplying ftUSD to back the perps engine. Because pricing, funding, and liquidation logic all derive from internal markets, FT Perps operates as an integrated component of the broader protocol. It shares the same liquidity base, depth windows, and collateral pools that support the spot and lending layers, ensuring that leverage, pricing, and liquidation behavior remain consistent across the protocol. This structure creates a reinforcing trading environment: market data informs pricing, pricing informs leverage, and both evolve within the same collateral and liquidity framework. ### Insurance Flying Tulip introduces a protocol-native insurance layer with onchain protection for investors against unprecedented protocol incidents. These span across smart contract exploits, faulty liquidations, or other technical failures across the protocol’s trading, lending and settlement layers. The insurance engine operates as a continuous market between coverage buyers - investors seeking to protect their capital - and capital providers that earn yield through the premiums they collect. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/cdb70490ab14.png) Coverage is structured as an active position in a shared pool. Buyers post collateral and pay a streaming premium for the duration of coverage. Providers deposit capital in USDC, which serves as the pool’s base asset and payout currency. In return, they pool tokens representing their proportional share of assets and accumulated premiums, allowing protection capacity and pricing to adjust automatically as utilization and risk conditions change. Premiums function as variable rates that respond to real-time data. Utilization, coverage demand, and internal risk indicators, which are derived from the protocol’s AMM and order book, jointly determine rate adjustments. When pool utilization rises or volatility increases, premiums move higher to attract liquidity; when conditions normalize, they ease back down. If an incident occurs, an external verifier such as UMA’s optimistic oracle assesses whether it meets predefined on-chain conditions, including the affected system, time frame, and loss threshold. Once verified, users with active coverage positions can redeem their insured amount in USDC directly from the pool. If no qualifying event occurs, coverage can be closed at any time, immediately halting premium payments. The insurance layer integrates with the same collateral and pricing systems that govern lending and trading. Assets deposited in Lend can back both open positions and coverage, while the same liquidity and volatility metrics that drive funding and liquidation logic also inform premium and capacity adjustments. Capital providers assume exposure to verified payout events; coverage buyers depend on oracle adjudication. Both remain exposed to typical smart contract and liquidity risks, with temporary withdrawal limits possible during claim settlement. In this model, insurance functions as part of the protocol’s internal risk infrastructure rather than an external add-on, allowing protection capacity, premiums, and liquidity to evolve directly with system conditions. ## FT & Economics Flying Tulip’s economic structure centers around its native FT token. Each protocol component – ftUSD, Lend, Perps, AMM, and Insurance – generates transaction fees, funding payments, and yield; which is then used to repurchase and burn FT. This reflects FT’s core design principle: to reflect protocol performance through net token supply over time. The FT launch introduces a new kind of structure in DeFi, in which 100% of token supply is allocated to private and public participants, at the same valuation at the same time, through the Public Capital Allocation. FT has a fixed supply of 10 billion tokens and no set inflation schedule, and the founding team receives no upfront allocation; any exposure is earned later through open-market buybacks funded by protocol revenue. Minting occurs only through the Public Capital Allocation (PCA) at a fixed ratio of 10 FT per $1 contributed. If $500 million is raised, exactly 5 billion FT are minted; once the 10 billion cap is reached, issuance ceases permanently. Participants in the raise receive their FT position as an onchain Perpetual PUT. While the option is active, holders can redeem FT at par in the original collateral asset, permanently burning the redeemed tokens; or withdraw FT, invalidating the option and releasing the backing capital for market buybacks and burns. ![](https://shoal.xyz/research/writing/building-the-real-time-defi-stack/img/a7283879da42.png) Each PUT functions as an NFT and encodes specific redemption rights to the participant’s underlying deposit, wherein if a holder withdraws 50% of the tokens allocated to their NFT, they will still be able to redeem the remaining 50% of their invested capital. This enables partial redemptions for investors with transparent onchain accounting, though it also means redemptions are irreversible, i.e. tokens cannot be re-deposited into the NFT once they’ve been withdrawn. Capital raised through the PCA is deployed into conservative, onchain yield strategies, spanning Aave V3, stETH, jupSOL, AVAX staking, and sUSDe. Yield from these deployments is first distributed across the protocol and its operational costs; while the surplus is allocated towards FT buyback-and-burn. This structure is designed to enable protocol revenue and capital yield to sustain itself without relying on new issuance. Both paths reduce circulating supply, either directly through redemptions or indirectly through repurchases funded by released reserves. Secondary-market FT carries no such redemption right; if holders redeem their underlying capital, their corresponding FT is burned, reducing circulating FT supply and concentrating more value to existing holders. ### Flying Tulip’s Business Model Revenue generated across the FT product stack is used for FT buybacks: - ftUSD yield flows to the treasury and is used for FT repurchases. - Lend contributes its net interest margin, the spread between borrower and supplier rates. - Perps forwards a portion of trading and funding fees to the same buyback mechanism. - Insurance directs its share of active premiums there as well. - When holders withdraw FT from the Perpetual PUT, the capital released from that redemption reserve funds additional market buybacks. Repurchased FT is then split between two outcomes: one portion is burned, permanently reducing that given portion of circulating FT supply; the other part is unlocked for distribution. Unlocked tokens are governed by revenue‑funded buybacks and follow a fixed allocation schedule. When protocol revenue funds buybacks, the Foundation, Team, Ecosystem, and Incentives unlock 1:1 in a 40 : 20 : 20 : 20 split. Just as Flying Tulip’s products are designed to adapt to real-time market conditions, the protocol’s business model is designed to adapt to real-time protocol activity. When protocol utilization rises, whether through higher trading volume, borrowing activity, or insurance demand, the aggregate revenue available for buybacks increases proportionally. When utilization slows, supply contraction continues but at a reduced rate, as no new issuance occurs. In practice, FT functions as the coordination layer for value across Flying Tulip’s native ecosystem. Product-level revenue and conservative yield form the inflows; buybacks and burns are the outflows; and unlocks, when revenue-backed, maintain contributor alignment. The result is a closed capital circuit in which operational output, user activity, and liquidity depth all converge into measurable changes in supply, effectively tying FT’s value directly to the protocol’s realized performance and operational efficiency. ## Outlook DeFi hasn’t yet crossed the chasm, but it is far closer than it was a few years ago. The foundations of an Internet Financial System are already in place: 24/7 global settlement, transparent ledgers, composable infrastructure, and the ability to move capital without intermediaries. However, DeFi’s current architecture remains too fragmented for the open, composable financial system it was intended to be: each primitive manages its own accounting, risk parameters, and collateral base. This isolation preserves protocol solvency but limits broader capital efficiency. This issue isn’t unique to crypto, nor is it a new one by any means. A brokerage account at Fidelity can’t seamlessly interact with assets held at Charles Schwab. Transferring securities between them involves settlement delays and manual coordination. Even within a single institution, moving funds between accounts, say, rolling over a 401(k) into an IRA, requires intermediary steps and time-consuming processes. In contrast, however, DeFi protocols operate on shared, public infrastructure. Open standards and transparent state make composability a native property rather than a feature built through integration. Flying Tulip lies uniquely at the intersection of two structural shifts in DeFi: aggregation and real-time adaptivity. The need for unified margin architectures that bring DeFi services i.e. trading, lending, derivatives under shared liquidity and collateral is becoming glaringly obvious as DeFi becomes more and more crowded. At the same time, the need to build DeFi products and services that respond to real-time market conditions in order to adjust parameters such as collateral ratios, borrowing limits, and funding rates, is becoming more apparent. Flying Tulip aims to capture both in a single protocol. It connects DeFi’s core primitives: stablecoins, trading, lending, derivatives, and insurance, designed to adjust risk and pricing dynamically with real-time liquidity and volatility, through a unified margin account. Undoubtedly, if Flying Tulip’s launch and early growth are successful, there will be dozens of imitators building and selling a similar product. Nonetheless, first-mover advantage is a force to be reckoned with in DeFi. At Shoal, we believe Flying Tulip is well-positioned to become the leading real-time DeFi stack. ## Sources *Data is sourced from DeFi Llama.* - Richard Stallman, *Free Software, Free Society: Selected Essays of Richard M. Stallman, 3rd Edition*[https://www.gnu.org/doc/fsfs3-hardcover.pdf](https://docs.flyingtulip.com/) - Flying Tulip, *Flying Tulip Documentation*[https://docs.flyingtulip.com/](https://docs.flyingtulip.com/) - Flying Tulip, *Internal Research Threads.* Retrieved from:[https://x.com/flyingtulip_/status/1898432266499416429](https://x.com/flyingtulip_/status/1898432266499416429)[https://x.com/flyingtulip_/status/1898785006249513246](https://x.com/flyingtulip_/status/1898785006249513246)[https://x.com/flyingtulip_/status/1898839079757996287](https://x.com/flyingtulip_/status/1898839079757996287)[https://x.com/flyingtulip_/status/1898784803249410508/photo/1](https://x.com/flyingtulip_/status/1898784803249410508/photo/1)[https://x.com/flyingtulip_/status/1899466570981691502](https://x.com/flyingtulip_/status/1899466570981691502) ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the Flying Tulip team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Tokenized Debt And The New Monetary Order > What does it take to capture the tokenization opportunity? - Publisher: Shoal Research (https://shoal.xyz) - Category: Tokenization - Published: 2025-10-14 - Canonical: https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/ - Keywords: stablecoins, crypto, RWA, tokenization, infrastructure, Tokenization ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/a5b1ca3a7b7b.jpg) ## A Transformation Is Overdue Innovation tends to be scarce in an environment as entrenched, risk-averse, and burdened by technical debt as the financial services sector. Yet history suggests that advances in financial infrastructure have constantly moved in tandem with periods of exponential economic growth. Double-entry bookkeeping laid the foundation for modern accounting and credit. The joint-stock corporation, introduced in the 17th century, opened the door to large-scale investment and capital formation. SWIFT and ACH helped standardize interbank transfers and cross-border payments. Since the Industrial Revolution, global GDP has only accelerated. Naturally, this raises the question: where and how does the next opportunity for financial innovation emerge? As Blackrock and Fidelity move hundreds of billions onto blockchain rails, landmark digital-asset legislations continue to be passed, and even retirement-plan managers begin allocating capital to crypto, it’s becoming clear a growing number toward one particular direction: tokenization. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/196b2feb19fa.png) At its core, tokenization means encoding assets of economic value - cash, securities, real estate - and their associated ownership claim onto blockchains. These distributed ledgers record every transaction as a transparent and immutable event, maintaining a single source of truth synchronized across a decentralized network of nodes. Offchain assets are represented as digital tokens; when ownership changes (i.e. assets are created, transferred, or destroyed), the changes are first validated by the nodes, and then permanently stored onchain. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/47b2d641cbad.png) The most prominent and recognizable example of this phenomenon today is the stablecoin. Designed to represent the value of stable reference assets, most commonly the US dollar, stablecoins are digital dollars issued and transferred on blockchain rails. They provide a stable, borderless unit of exchange in digital form: just as anyone with an internet connection can use WhatsApp to message globally in seconds, anyone can move money globally with stablecoins. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/8f9686c17703.jpg) Given >99% of circulating stablecoin supply is made up of US Dollar backed stablecoins, we can effectively think of them as tokenized dollars: their supply onchain is backed 1:1 by reserves held in assets like dollars and treasuries. Stablecoins have stood the test of time and have seen remarkable growth in supply, which sits at just over [$300B](https://defillama.com/stablecoins) today. That said, if we observe monthly issuance volume of tokenized assets 5 years ago vs year-to-date, it’s clear the appetite for tokenization extends well beyond just digital dollars now. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/4961cebdbc1a.png) To better understand why demand for tokenization is growing, it helps to first examine the limits of today’s market infrastructure. ### Why Finance Needs New Rails Few words capture the state of today’s financial infrastructure better than *archaic*. The systems that move trillions each day; payment networks, clearinghouses, settlement systems, were designed more than half a century ago. History doesn’t repeat itself, but it often rhymes. Throughout much of the 20th century, America’s pre-1935 corporate giants dominated the market. They lost ground slowly, shedding about 2.2% of value each year to rising competitors. Then came the 1970s. New technologies, oil shocks, and inflation broke that inertia, and the pace of decline nearly doubled to 3.4% annually, sometimes even spiking above 10%. That decade marked a structural inflection. The electronic systems that replaced paper trading and manual clearing ushered in a new era of efficiency, standardization, and scale. Networks like SWIFT, ACH, and the DTCC digitized the plumbing of global markets, transforming how capital moved and was recorded. Yet half a century later, those very systems now constrain the markets they once modernized. The infrastructure that enabled global finance to operate electronically has become its primary bottleneck. **T+1, T+2 (And Counting)** Most global securities markets today rely on delayed, multi-day settlement cycles, typically one to two business days between trade and final transfer. A trade executed on Monday is not settled until Wednesday. A trade placed on Friday may not be settled until next week. It’s as outdated as it sounds; this standard emerged from the paper-certificate era when trades required physical delivery and manual reconciliation. While trades themselves can be executed electronically in seconds today, the final transfer of their ownership still takes days. Until that moment, each trade is merely an entry in another institution’s siloed private ledger. It’s naive to downplay this structural lag as mere operational inconvenience: delayed settlement represents one of the largest hidden costs in global markets. Delays mean asset ownership remains in flux, exposing participants to credit and counterparty risk and tying up that capital that could otherwise be productively deployed. In aggregate, trillions of dollars remain effectively idle and unproductive because the underlying infrastructure has failed to adapt. The DTCC reports that tens of billions of dollars in daily settlement failures. These failures rarely occur in isolation; when one security fails to arrive, it often has already been pledged as part of another transaction. That second trade then fails, potentially a third after it, effectively creating a cascade of failures which are only amplified in markets with high leverage and thin liquidity. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/682efd9f543b.png) Even when trades do eventually clear, structural inefficiencies remain. The longer the settlement window, the greater the collateral required, as clearinghouses demand higher margins to account for the additional risk. Meanwhile, banks and brokers often struggle to determine which securities are truly available in real time, and settlement delays often lead to over-allocation and inventory mismanagement. On top of this, settlement systems stop when markets close, meaning their daily operating hours and operational days per week are always limited. These frictions only amplify across borders. Different regions operate their own central securities depositories with their own rules and timelines. Transferring assets across them involves multiple intermediaries and reconciliation steps. The regulatory patchwork adds another layer of friction. Compliance requirements differ by jurisdiction, forcing firms to spend heavily on reconciliation and reporting. Market operating hours rarely align, creating dead zones where trades cannot move forward. A current example is Europe’s delayed adoption of T+1 settlement, scheduled for 2027, meaning the EU will remain out of sync with the US and other regional markets, imposing new costs on participants that operate across both markets. With this in mind, it’s important to recognize that the evolution of financial infrastructure more often than not is a reactionary one: - In the 1960s, back-office paperwork overwhelmed Wall Street, leading to NASDAQ’s creation in 1971 as the first electronic stock market. - In 1973, the Depository Trust Company centralized recordkeeping to eliminate the physical transfer of certificates. - After 9/11, Congress passed the Check Clearing for the 21st Century Act, allowing digital images to replace paper checks. - In 2012, Hurricane Sandy flooded DTCC vaults, destroying 1.7 million certificates and accelerating the transition to fully digital records. Infrastructure most commonly evolves when inefficiency or crisis leaves no alternative. Today, the pattern repeats. The shortcomings of today’s market infrastructure are not abstract. They translate directly into costs, UX pain points, and risks that are borne by end-users. The internet already enables information to move globally in milliseconds. There is little reason why money and securities should remain constrained by regional ledgers and business-hour settlement when the technology for instant, continuous transfer already exists. It is only natural that value should move as freely as information: accessible globally, operating continuously, and secured by transparent, programmable infrastructure. ### All Roads Lead to Tokenization Tokenization is designed to directly address the structural lag in modern financial systems. By recording ownership and transfer on shared ledgers, it removes the need for multiple intermediaries to reconcile the same transaction across fragmented databases. Settlement becomes a matter of redistributing balances on a digital ledger rather than routing instructions through correspondent banks and clearing houses. The primary resource consumed in this process is computing power, paid as a transaction, or *gas* fee, a cost that continues to decline as low-cost or near-zero gas transactions have now become table stakes for chains today. As a result, the marginal cost of value transfer for tokenized assets will continue to gravitate to zero. By contrast, legacy payment systems remain burdened by institutional overhead. A single wire or ACH transfer may pass through several intermediaries; sending and receiving banks, correspondent institutions, and clearing houses, each extracting fees and introducing settlement latency. Global cross-border transfers still average 6.49%in transaction costs, a persistent tax on capital mobility that tokenized rails largely eliminate. The idea of tokenizing assets is not new. It has resurfaced repeatedly over the past decade in different forms. As early as 2012, Meni Rosenfeld’s *Colored Coins* proposal introduced the idea of attaching metadata to fractions of Bitcoin to represent other assets such as stocks, bonds, or commodities: a digital bearer asset could embed both monetary value and an external ownership claim. A few years later, DigixDAO in Singapore sought to bring physical assets like gold onchain. Built on Ethereum and IPFS, it introduced a *Proof of Provenance* model that allowed anyone to verify an asset’s existence through its custody chain. Digix was among the first to combine asset-backed tokens with decentralized governance via a DAO. The broader environment, however, was not ready to scale. Between 2017 and 2020, onchain liquidity was scarce. Average daily volumes on many exchanges were under $10 million, and quoted bid-ask spreads in smaller tokens often exceeded 4-8%, setting up for unreliable price discovery and therefore limited adoption. The supporting infrastructure for tokenization, across custody, settlement, and compliance, was equally immature. In 2018, only a handful of licensed custodians operated globally, and most lacked regulatory clarity. The SEC noted that few met depositary standards under Rule 206(4)-2 of the Advisers Act, leaving persistent uncertainty around asset segregation and safekeeping. On/off-ramps between banks and blockchains were also unreliable. Until 2020, fiat-crypto conversion failure rates averaged nearly **50 percent** across major providers, driven by inconsistent KYC processes and recurring payment rejections. Infrastructure diversity was minimal: early entrants like MoonPay, Ramp, and Transak collectively supported fewer than 60 fiat currencies globally, excluding a good portion of emerging markets and locales. The concept of tokenized finance was sound, but the market lacked the **architecture, incentives, and trust** mechanisms to sustain institutional participation. It would take another half-decade, driven by advances in compliant custody, the rise of stablecoin liquidity, and the emergence of cross-chain settlement frameworks, before tokenization began to take form at the scale it was once envisioned to. At the foundation of this shift is a principle of **fluidity**. In any monetary system, assets that are highly divisible and low-friction tend to circulate rather than sit idle. Tokenized assets follow that same logic: they are designed to move, integrate, and settle across networks in real time. Blockchains function as public digital ledgers, and automated reconciliation reduce the cost of movement, while fractional ownership lowers participation thresholds and deepens liquidity. ### The Tokenization Landscape Today Total tokenized value now sits at just over **$320 billion**, spanning more than 220 issuers and roughly 400,000 onchain addresses. Still, only a fraction of that value circulates actively within DeFi protocols. The difference highlights a key point: much of tokenized value today remains in custodial or permissioned environments rather than freely composable onchain. That definitional caveat aside, the trendline is clear: while still small relative to the $100T+ traditional markets, tokenized asset value has grown sharply in the past year. The rise of tokenized assets has been most present in two particular asset classes: stablecoins and tokenized Treasuries. **The State of Stablecoins** ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/c52bb99a55e8.png) Stablecoins remain the clearest proof of concept for tokenization. With a circulating supply of more than $300 billion, they show that there is demand and utility for programmable, globally transferable, always-on cash works at scale. Over the past five years, stablecoin adoption has accelerated sharply. Tens of trillions of dollars in value have already moved through stablecoin rails, and supply continues to set new all-time highs. By token, issuance remains concentrated in USDT and USDC, which together account for the vast majority of supply. New entrants such as FDUSD and PYUSD, backed by major exchanges and payment networks, signal a gradual institutional pivot toward regulated issuance, while DAI, USDS, and USDe demonstrate persistent demand for decentralized, DeFi ‘native’ stablecoins. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/c3db23e9e493.jpg) By chain, Ethereum still leads in aggregate supply and transaction value, but Tron, Solana, and Base have grown rapidly. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/a93197598d4e.jpg) These distributions reveal two different types of utility. Ethereum dominates in DeFi-related usage (i.e. liquidity pools, lending markets, and settlement) while Tron leads in peer-to-peer transfer volume, especially across emerging markets where low fees and quick confirmations make it ideal for payments and remittances. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/a8363aa3890d.jpg) More impressively, though, stablecoins are already eroding legacy payment networks. Aggregate transfer volumes now reach into the trillions per month, rivaling networks like Visa, Mastercard, and SWIFT, but with near-instant settlement and materially lower transaction costs. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/a8ece6ae1d7a.jpg) The regulatory landscape around stablecoins is evolving in tandem. A new class of regulated money-market fund (MMF) tokens, including names like BUIDL, BENJI, USDtb, and Cap Money (which aggregates them), illustrates how stablecoin design is converging with traditional cash-management structures. In effect, these instruments merge the accessibility of stablecoins with the yield of Treasuries, hinting at the next phase in tokenized assets. ### A Rising Phoenix: Tokenized Treasuries If stablecoins effectively functioned as a blueprint for tokenization, treasuries are emerging as the rising phoenix. At the time of writing, tokenized Treasuries have reached upwards of $8Bmarking more than an 80% increase YTD. That growth has well outpaced the early trajectory of stablecoins, reflecting growing demand for yield-bearing, low-risk assets that can serve as collateral and liquidity instruments across global markets. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/f20ac3d19e4a.png) At a high level, the tokenized treasury landscape today already has: - $8.3B total value - 50 total assets - 52.7k total holders **As per [rwa.xyz](http://rwa.xyz)* Treasuries are debt instruments issued by the U.S. Department of the Treasury to finance government spending. Backed by the U.S. government, they occupy a central position in global markets, functioning as cash equivalents for banks, corporations, and sovereigns. The four main categories - Treasury Bills, Notes, Bonds, and TIPS - differ in maturity but share two defining traits: liquidity and yield. While stablecoins provide price stability, Treasuries offer something GENIUS-compliant stablecoins cannot: interest income. With short-term yields above 5% since the Federal Reserve’s tightening cycle in 2022/23, onchain investors have increasingly sought exposure to the U.S. risk-free rate. The logic is simple: idle capital held in stablecoins can instead earn yield through tokenized Treasuries without sacrificing liquidity or transparency. Demand has also been shaped by broader structural forces. The rise in rates ended the ‘easy-money’ era that defined much of DeFi Summer. Liquidity mining returns fell sharply as incentives disappeared and the unsustainable yields of prior cycles collapsed. Tokenized Treasuries emerged as an alternative source of yield which itself stems from interest-bearing government securities with clear legal protections and transparent collateral. It’s worth noting tokenized Treasuries come with a distinct limitation: they are legally classified as securities, which restricts their composability across open DeFi systems. Compliance requirements, investor whitelisting, and regulated custody frameworks introduce friction that prevents them from circulating as freely as stablecoins. Even so, the pace of growth speaks for itself. Tokenized Treasuries surpassed $7 billion in supply far faster than stablecoins did in their early years. ## A Deep Dive Into OpenEden OpenEden represents one of the first credible attempts to build a functioning framework for institutional-grade tokenization. Its mission is straightforward: to provide investors with continuous, regulated access to U.S. Treasuries onchain, combining the legal protections of traditional markets with the operational efficiency of blockchain infrastructure. Founded in 2023, OpenEden is a tokenization protocol providing structured access to short-duration U.S. Treasuries. It is the first tokenized-Treasury issuer to receive independent third-party bond ratings, earning an “A-bf” from Moody’s and “AA+f / S1+” from S&P Global Ratings. OpenEden Digital (OED), a licensed subsidiary of the OpenEden Group, serves as the platform’s regulated issuer. Operating under a Digital Assets Business License granted by the Bermuda Monetary Authority, OED is authorized to issue, sell, and redeem digital assets within a clearly defined legal framework. ### Growth and Adoption OpenEden’s footprint has expanded steadily since launch, though adoption has notably accelerated in 2025. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/79b70057b56b.png) Total value locked, which currently sits at $531M, has climbed sharply YTD, driven by consistent inflows into TBILL, OpenEden’s tokenized Treasury product, and USDO, its stablecoin, which each have amassed ~$266M and ~$264M in TVL respectively. To date, OpenEden has generated $7.29M in total fees, which thus far has amounted to $1.79M in protocol revenue. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/5ec48c17d30f.png) Most OpenEden assets reside on **Ethereum**, however, liquidity is also growing across other chains like Solana, Arbitrum, and XRPL. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/a446db17e789.png) Transaction data shows a steady rise in usage, with daily transfer volumes across OpenEden’s products now reaching parity between TBILL and USDO, the latter of which was notably launched at a later time. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/6157ce44bc57.png) ### Key Features OpenEden’s framework is designed to combine the reliability of regulated financial structures with the efficiency and transparency of onchain settlement. The TBILL fund’s underlying assets are custodied by The Bank of New York Mellon (BNY), while the fund itself is investment-managed by BNY Investment Management (BNYIM), marking the first time BNY is managing a tokenised fund on a public blockchain. Each tokenized instrument represents a verifiable claim on a corresponding pool of short-term U.S. Treasuries, and the protocol automates issuance, redemption, and settlement through smart contracts while maintaining regulatory compliance. ​​OpenEden’s model rests on several core principles: - **Regulated and licensed issuance:** OpenEden assets are backed by real U.S. Treasuries held by qualified custodians under a BMA–licensed framework. - **Self-custody:** Investors hold their OpenEden assets directly onchain. - **Low-cost, programmable settlement:** Onchain rails minimize reconciliation costs and enable cheaper, faster, and more transparent settlement. - **Smart contract automation:** Core fund operations, namely minting, burning, and exchange-rate calculation, are governed by verifiable smart contracts. - **DeFi Composability:** ERC-20 compatibility allows OpenEden assets to integrate across broader DeFi ecosystems. - **Multichain deployment:** Multichain support for assets expands accessibility and network reach including Ethereum, Solana, Base, Arbitrum, BNB Chain, and XRPL. In practice, these design choices allow OpenEden to combine the trust and governance of traditional markets within an onchain environment, where issuance, custody, and settlement are managed programmatically under a regulated framework. ## OpenEden Core Products ### TBILL OpenEden’s flagship product, **TBILL**, provides tokenized access to short-duration U.S. Treasury Bills. It is available on Ethereum and Arbitrum, and is backed 1:1 by a pool of short-term U.S. T-Bills and dollar reserves held with regulated custodians. **Growth and Fees** Since launch, TBILL has seen consistent growth in both deposits and fees generated. At the time of writing, TBILL TVL sits at $264M, up over 130% YTD and 2300% since launching in 2023 ($11M). ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/8c44ea8d8c3b.png) TBILL has also consistently generated tens of thousands in fees since early 2024, amassing $624K total fees to date. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/3924ecc2ecb6.png) **Structure and Issuance** TBILL is issued through the **TBILL Vault**, a permissioned smart-contract that governs how investors onboard, deposit capital, and receive tokenized exposure to short-term U.S. Treasuries. The vault is investment-managed by BNY Investment Management (BNY IM), while the underlying assets, namely U.S. Treasury Bills, are custodied by BNY, ensuring that collateral remains fully auditable and compliant with global custody standards. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/54d02fab15f3.png) The investor onboarding process begins once investors complete full verification. Whitelisted wallets are granted permission to interact with the vault, allowing them to deposit USDC and receive tokenized exposure to short-term Treasuries. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/0625896ac7bd.png) TBILL is minted and redeemed through the TBILL Vault smart contract. USDC deposits on supported chains are converted into TBILL, while redemptions are processed back into USDC. Each TBILL token represents a proportional claim on the net asset value (NAV) of the underlying fund. Minting and burning are handled automatically by the vault’s smart contract, which updates circulating supply onchain in real time. All issuance and redemption activity is publicly verifiable onchain, while underlying assets remain secured through traditional custodians **Subscriptions (Aka Minting)** Onboarded investors can “subscribe” to receive TBILL tokens by depositing USDC; which can be done through the standard interface or manually through the smart contract. Subscriptions begin once USDC has been deposited. TBILL tokens are minted and delivered to the investor; the exact number is determined as a function of the TBILL/USDC price, fetched from TBILL’s price oracle contract, as well as the amount of USDC deposited. `tbillMinted=usdcDeposit/tbillusdcExchangeRate` Initial deposits must be at least 100,000 USDC, with subsequent deposits at least 1,000 USDC. **Redemptions** Investors may redeem TBILL for USDC at any time. Redemption requests are placed in a **First-In-First-Out (FIFO)** queue. During redemption, TBILL tokens are burned, and the corresponding USDC amount is minted and returned to the investor’s whitelisted wallet. `usdcReceived=tbillRedeemed*tbillusdcExchangeRate-TransactionFee` This process ensures redemptions are orderly and transparent, with NAV-based pricing enforced by the vault oracle. **Vault Strategy** The fund managing TBILL maintains a portfolio of short-term U.S. Treasury Bills with a weighted-average maturity of less than three months. T-Bills are issued at a discount to par value. For instance, an investor might spend $950 to buy a $1,000 bill and redeem it at maturity for a ~5% yield. For TBILL holders, this structure translates to a predictable, low-risk yield that accrues through the vault’s automated portfolio management. **Fees** Two primary fees apply to TBILL: the Total Expense Ratio (TER) and the protocol transaction fee. **Total Expense Ratio (3 bps or 0.03%)** The TER is charged daily on the fund’s total value (TVL) and represents the cost of managing the underlying T-Bill portfolio. It covers: - Maintaining the portfolio’s weighted-average maturity below three months. - Rolling over matured Treasuries into new issues and compounding generated yield. - Meeting regulatory and reporting obligations for the BVI fund. - Commissioning third-party audits for both fund assets and smart contracts. - Custodian and banking fees charged by BNY Mellon and affiliated institutions. **Transaction Fee (5 bps or 0.05%)** Applied during minting and redemption, this fee is calculated in USDC and processed onchain. It offsets operational costs such as gas usage, bank wire fees, and offramping costs associated with fiat conversion. Together, these fees sustain both the onchain and offchain components of the TBILL system, ensuring the vault remains compliant, functional, and capital-efficient. **Token Price** The TBILL token price reflects the Net Asset Value (NAV) per token, tracking the appreciation of the underlying T-Bills as they approach par value: tokenPrice=totalAssets - feeClaimable/ circulatingTokenSupply At launch, TBILL was priced at 1.0000, appreciating gradually as underlying assets accrue yield. **Price Oracle and Governance Controls** OpenEden has implemented a set of onchain mechanisms to ensure the security of the TBILL Vault. To start, OpenEden uses an in-house price feed that transmits NAV data to an onchain oracle, safeguarded by a price guard that halts minting or redemption if deviations exceed predefined thresholds. - **Timelock:**Whenever the TBILL Vault’s treasury wallet address [changes], a 24-hour window is implemented to [allow admins to offramp funds if the change in address is unintended]. - **Multisig**: The TBILL Vault uses a multi-signature (multi-sig) mechanism to authorize onchain transactions (i.e. minting/redeeming TBILL). - **Price Guard:**A circuit-breaker mechanism designed to track the TBILL token price and respond when needed, namely when the price deviates beyond predefined thresholds. In the case of attempted oracle manipulation attacks or failures, this mechanism halts minting/redeeming of assets via the TBILL Vault. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/9619e239a191.png) Onchain, TBILL Vault smart contracts are publicly viewable and verifiable on Etherscan. Offchain, the TBILL Vault’s U.S. T-Bills are held in custody by regulated custodians. Any remaining USD fiat currency reserves will be held in regulated custodians or be in transit between the on/off service providers, the prime broker, and the custodian account. ### USDO: The OpenDollar Another core component of OpenEden’s product suite is the OpenDollar, or USDO. USDO is a regulated, yield-bearing stablecoin issued by OpenEden Digital (OED). The rebasing yield is distributed directly in the form of additional USDO to holders’ balances, and is available on Ethereum, Base, and BNB Chain. USDO has seen faster growth than TBILL, both in supply and adoption. TVL has climbed steadily since launch, nearly mirroring that of TBILL with $264M of its own. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/4ce3c912d85f.png) The number of USDO holders has also increased rapidly, surpassing TBILL’s user base within months of launch (400 USDO holders vs 59 TBILL holders). ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/57e994431333.png) As a result, USDO is also generating fees and revenue at a much greater rate than TBILL, its $6.6m in fees accounting for >90% of OpenEden’s aggregate total fees ($7.29m). ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/5eb0147fd171.png) **Rebasing mechanism** USDO rebases daily while maintaining a fixed $1 price. This rebasing mechanism allows holders to earn yield generated from reserves backed by U.S. Treasury Bills and reverse repurchase agreements (repos). Yield is distributed directly in the form of additional USDO, meaning holders see their balance increase daily, rather than the price changing. The rebase is governed by a bonus multiplier, which updates automatically each day (including weekends): `usdoBalance=shares*bonusMultiplier` Like traditional fixed-income products, USDO’s yield is predetermined by OpenEden Digital and may be periodically adjusted to reflect prevailing market conditions. For instance, if short-term Treasury yields rise, USDO’s rate may be increased accordingly; if they decline, the protocol may lower it to maintain parity with underlying asset performance. **USDO Minting & Redemption** At a high-level, USDO can be minted against either USDC or TBILL collateral deposits. Similar to the TBILL token, USDO can only be minted by authorized users who pass KYC and KYT checks. - To mint USDO, an authorized user initiates the Instant Mint function, selecting their collateral token. - The USDO smart contract calculates the equivalent amount of USDO to be minted.USDO minted at a 1:1 rate to USDCUSDO minted based on the prevailing TBILL exchange rate at the time. - The Liquidity Manager contract then mints and transfers USDO tokens to the authorized recipient’s wallet address. USDO redemptions follow the same logic in reverse. Tokens are first burned, and the equivalent amount of USDC is transferred back to the redeemer’s wallet. Two redemption modes exist: - **Manual Redemption,**wherein USDO is transferred to OED’s wallet and processed on a First-In-First-Out (FIFO) basis. Requests settle during U.S. business hours, typically within 1–2 business days - **Instant Redemption:**The USDO Liquidity Manager contract sends the underlying TBILL to the TBILL Vault, which redeems USDC from Circle’s BUIDL contract using its BUIDL allocation. The resulting USDC is transferred to the redeemer’s wallet onchain **USDO Reserves** ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/637873d3f1f4.png) USDO is backed by a diversified pool of regulated tokenized Treasuries issued by major financial institutions: - **TBILL (OpenEden)** - **BUIDL (BlackRock)** - **BENJI (Franklin Templeton)** - **VBILL (VanEck)** These assets are backed by short-duration U.S. Treasuries themselves. OpenEden integrates Chainlink Proof-of-Reserves for real-time, onchain verification of collateral holdings. As of the [latest data](https://data.chain.link/feeds/base/base/usdo-por), USDO reserves sit at ~273,196,076.72, with over 99 % of circulating USDO residing on Ethereum. Fees are charged on all transactions involving the minting and redemption of USDO: - Minting Fee: 3 bps (0.03%) - Redemption Fee: 10 bps (0.10%) These fees are calculated in USDO and deducted directly from the total USDO amount being minted or redeemed. They are designed to cover the Vault’s operational costs, including: - Onchain gas usage - Bank wire fees Off-ramping and fiat conversion costs Together, these transaction fees are designed to sustain both the onchain and offchain components of USDO’s infrastructure, while preserving the asset’s liquidity and peg stability. ### cUSDO USDO is designed to provide secure, regulated yield. However, its structure as a rebasing token makes it difficult to integrate with a broader range of DeFi protocols. As such, OpenEden introduced cUSDO, a wrapped and compounding version of USDO. cUSDO represents the same underlying exposure as USDO but accumulates yield internally, causing the token’s price to increase over time rather than its balance. Each cUSDO token reflects an increasing claim on the underlying pool, ensuring it remains fully composable across DeFi protocols. Conversion between USDO and cUSDO is permissionless and handled through a public smart contract, allowing users to wrap or unwrap at any time. Available on Ethereum, Base, and BNB Chain, cUSDO extends the reach of USDO’s regulated yield into the broader DeFi ecosystem. **Collateralization ratio** To ensure each USDO token remains redeemable at $1, OpenEden maintains a real-time onchain collateralization ratio that compares the total value of reserves to circulating supply: `CR=ReserveNAV/usdoCirculating` As of the latest reporting period, USDO is 103.7719% collateralized, implying a 0.37719% over-collateralization buffer. This margin accounts for operational frictions, such as price movements or settlement delays, while ensuring full redemption coverage. The collateral ratio is continuously updated and verified through Chainlink’s Proof-of-Reserves integration, which tracks the real-time Net Asset Value (NAV) of the underlying Treasury and repo instruments. Should the ratio approach parity, the system is designed to restrict new issuance or trigger rebalancing actions to maintain full coverage. ### EDEN and Economics OpenEden’s business model is built on the fee revenue generated from its products, primarily TBILL and USDO. These fees, derived from minting, redemption, and ongoing management, are collected as protocol revenue by OpenEden Group, the platform’s operating entity. This is made up of TBILL’s Total-Expense-Ratio (TER) and transaction fees (0.03% and 0.05%), plus USDO’s minting and redemption fees (0.03% and 0.10% respectively). To date, OpenEden has generated $7.29 million in total fees and $1.79 million in revenue, according to DeFiLlama. The revenue base grows in tandem with product adoption and transaction activity, as both TBILL and USDO generate recurring volume-driven fees tied to their respective vaults. Again, it’s worth recalling that USDO has generated a more meaningful portion of these fees ($6.6m in fees or >90%) and despite having been around less than TBILL, which has generated $624K in fees respectively. The EDEN token sits at the center of OpenEden’s ecosystem across several functions: - Staking, to support protocol operations and economic security - Governance, allowing holders to participate in decision-making on upgrades and parameters - Incentives and emissions, to bootstrap liquidity and adoption of new products - Utility features, such as fee discounts or rebates for active participants The OpenEden Group is also exploring mechanisms such as buyback-and-burn programs, funded through a portion of protocol revenue or treasury reserves, to reinforce token value capture over time. ### The OpenEden Ecosystem ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/84eb531124de.png) OpenEden’s ecosystem combines onchain integrations that extend the usability of its tokenized Treasuries with offchain partnerships that provide regulated market access and infrastructure support. The design reflects a dual objective: to make short-duration U.S. Treasuries operable within DeFi while ensuring the legal, custodial, and compliance standards required by institutional investors remain intact. Onchain Integrations OpenEden’s onchain footprint spans the main environments where DeFi activity occurs today. Its assets are deployed across Ethereum, Base, BNB Chain, Solana, Arbitrum, and XRPL, designed to maximize distribution by allowing broader user access from different ecosystems. Within the broader DeFi landscape, OpenEden has integrated a number of bluechip liquidity venues including Curve, Balancer, Aerodrome, and money market protocols including Pendle, Morpho and Euler among others. These integrations allow cUSDO (and therefore indirectly USDO) to operate as productive collateral or yield-bearing components within existing financial primitives including liquidity pools, vaults, and structured yield products, offering USDO investors a way to maximize the productivity of their capital. **Offchain Partners** Offchain, OpenEden’s network centers on custodial, brokerage, and infrastructure providers that establish the operational and regulatory base for its products. Custodians including Binance, BitGo, Fireblocks, Hex Trust, and Propine handle storage and segregation of client assets within regulated frameworks, while HiddenRoad handles OpenEden’s brokerage needs, This ensures institutional holders can manage exposure through their existing compliance and risk channels. The infrastructure and services layer, spanning providers including Chainlink, Kaiko, and Archblock, and supports data integrity, market transparency, and pricing reliability. Together, these integrations form the scaffolding that allows OpenEden’s assets to operate in both regulated and onchain environments. **Binance Banking TriParty** OpenEden has partnered with Binance Institutional through Binance’s Banking Triparty framework, allowing cUSDO to be used as yield-bearing collateral within Binance’s trading environment. The setup lets institutional clients hold cUSDO with approved custodians while using those balances on Binance for trading and settlement purposes. The arrangement preserves segregated custody, wherein assets remain off-exchange with custodians such as BitGo, Fireblocks, and Hex Trust, while Binance mirrors the positions internally for operational use. This reduces the need to move assets between custodians and the exchange, lowering counterparty and settlement risk. In effect, the partnership connects OpenEden’s tokenized Treasury products to existing exchange infrastructure without altering their underlying regulatory or custodial structure. It offers a straightforward mechanism for institutions to deploy tokenized Treasuries as collateral with institutional-grade compliance and risk management. ## Analysis & Outlook Having detailed OpenEden’s design and ecosystem, the next step is to evaluate how its hybrid structure, anchored by regulated issuance and DeFi composability, shapes its prospects in the growing market for tokenized Treasuries and beyond. ### Competitive Landscape The tokenized-asset market has grown crowded in a short period of time. Growth accelerated notably after late 2024, when renewed institutional optimism and a post-election risk-on environment drove inflows into yield-bearing digital products. Unlike prior cycles dominated by crypto-native experiments, today’s competition includes some of the largest names in global finance, with over 115 tokenization platforms in production today. In tokenized Treasuries, OpenEden competes most directly with Securitize, Ondo, Backed, and Matrixdock, alongside institutional entrants such as BlackRock (BUIDL), Franklin Templeton (BENJI), and WisdomTree (WUSDY). Each offers exposure to short-duration U.S. government debt through regulated structures and onchain issuance. Stablecoins present a different challenge. Supply remains highly concentrated in a few dominant issuers (USDT, USDC) which together account for well over 90 percent of circulating volume. However, zooming out, if we exclude USDT, USDC, and BUSD supply, it’s becoming evident that stablecoins, like treasuries and the rest of the tokenization landscape, is only going to become more competitive soon. ![](https://shoal.xyz/research/writing/tokenized-debt-and-the-new-monetary/img/485674da5f1b.png) ### How Does OpenEden Differentiate? With $531M in TVL and $7.29M in fees thus far, OpenEden’s raw numbers, albeit notable, are not reflective of its positioning. OpenEden’s strength lies in the overall quality of its protocol structure and how it merges together institutional-grade regulatory compliance with onchain programmability and DeFi composability. Importantly, OpenEden is the first tokenized Treasury issuer to receive third-party credit ratings, (an A-bf from Moody’s and AA+f / S1+ from S&P Global) attesting to the institutional standards of its fund structure and custody model. In a sector still dominated by self-reported audits, third-party credit ratings mark a meaningful step toward formal institutional adoption. Investor onboarding follows a permissioned framework: wallets must complete KYC and KYT checks before interacting with vaults. Once approved, all transactions (i.e. mints, redemptions, and fee accruals) are visible onchain. This setup combines regulatory traceability with public transparency, creating a model where compliance and verifiability reinforce each other rather than conflict. At the same time, OpenEden’s assets are built for interoperability. Both TBILL and USDO follow the ERC-20 standard, allowing them to move freely across DeFi protocols. TBILL functions as a yield-bearing Treasury asset, while USDO extends that yield into a rebasing stablecoin format. Regulated issuance with open integration illustrates how tokenized securities can exist within DeFi infrastructure without compromising oversight requirements. OpenEden’s roadmap points toward a shift from individual product issuance to a standardized infrastructure model. The aim is to simplify how institutions bring regulated assets onchain, abstracting the operational and compliance overhead behind tokenization itself. In this sense, its long-term vision resembles a *“Shopify for tokenization”*: a modular framework that enables others to issue and manage tokenized products within defined regulatory and technical boundaries. ### Where We Suggest OpenEden Focus Next There are several key emerging catalysts could strengthen OpenEden’s position within the tokenization landscape: **DeFi-Nativitiy as a Differentiator** As institutional capital becomes more comfortable operating on public blockchains, the expectation will shift from passive exposure to productive onchain deployment. Assets like Treasuries, which already serve as low-risk collateral in traditional markets, can increasingly be used within DeFi to generate incremental yield or support liquidity provision. OpenEden’s architecture is already compatible with major DeFi protocols, and as the regulatory perimeter around tokenized assets expands, this interoperability will matter more. Institutions will likely prefer frameworks that allow their assets to circulate safely across lending markets, structured vaults, or automated liquidity systems, without losing compliance guarantees. In that environment, composability becomes a form of capital efficiency, and OpenEden is positioned to benefit from that shift. **Privacy: The Next Institutional Unlock** The next major frontier for institutional adoption is likely transaction privacy. Institutions are unlikely to transact meaningfully on public blockchains until confidentiality, data protection, and counterparty privacy can be guaranteed. Zero-knowledge proofs, encrypted state systems, and privacy-preserving chains are quickly maturing, and the first regulated issuers to adopt them will gain a substantial lead in onboarding capital that cannot move through transparent rails today. For OpenEden, integrating privacy infrastructure, or even pursuing strategic partnerships or acquisitions in that domain, could become a defining differentiator. Privacy-enabled settlement would allow institutions to interact with tokenized assets while maintaining compliance and auditability through selective disclosure. The ability to conduct verifiable yet confidential transactions would mark a decisive step toward large-scale institutional use. ## Closing Thoughts Tokenization has momentum, but its footprint remains small: tokenized assets including government bonds, credit, and equities still represent only a fraction of global financial markets, estimated at less than 0.2% of the roughly $500 trillion in total assets worldwide. Stablecoins continue to dominate onchain liquidity, with over $300 billion in aggregate supply dwarfing the combined value of all tokenized assets on public chains. The advantages of tokenization are clear: operational efficiency, near-instant settlement, 24/7 access, transparency, and programmability for functions like automated compliance or dynamic asset management. However, though magnitudes more efficient than legacy financial rails, tokenization still encounters its fair share of structural limits. Derivative markets such as [perpetual futures protocols](https://www.shoal.gg/p/bringing-macro-markets-onchain-with) already offer efficient onchain exposure to the price or yield of offchain assets without requiring direct ownership or custody. These instruments capture much of the same demand that tokenization seeks to serve, often with greater capital efficiency and fewer regulatory constraints. Furthermore, value capture remains uncertain. John Pfeffer argued that much of the economic benefit from tokenization will flow to users rather than intermediaries. Open systems are difficult to monopolize. The same qualities that make blockchains effective in coordination and record-keeping also make them incompatible with business models built on control and opacity. Even so, the catalysts on which today’s surge in tokenization adoption hinge on suggest *it really may be different this time*. The ICO period lacked regulatory guardrails; that foundation now exists. Institutional trust and adoption, while still unfolding, is being accelerated by major asset managers like BlackRock, Franklin Templeton, and WisdomTree deploying and issuing regulated onchain funds. Tokenized assets are now used as collateral in protocols including Aave and Maple Finance, demonstrating the composability that yield-bearing instruments can get from DeFi rails. As adoption grows, capital is likely to move up the onchain yield curve, from stablecoins to Treasuries and eventually into tokenized credit and equity, expanding the potential tokenized asset value well into the trillions. At Shoal, we think it’s clear by now that tokenization is no longer a matter of “If?” or “When?” but rather “How?” The more pressing question now becomes what kind of products and services prove to be the most useful over time, which hinges on a) the quality and efficacy of their underlying structure; b) the exogenous value they provide to users, DeFi, and the broader DeFi and financial services sectors; and c) their ability to capture value from the services they provide and redistribute to investors and token holders in a sustainable way. In practice, this resembles a tokenization platform which manages to efficiently integrate compliant, regulated financial services with smart contracts and onchain rails; lower barriers to entry for institutions to bring regulated assets onchain by abstracting the operational and compliance overhead; and coordinate and align value capture from the organic demand for the services it provides through a native token. OpenEden offers one of the most practical attempts to build this exact framework. Its regulated structure, emphasis on short-duration Treasuries, and institutional custody integrations anchor it within existing financial infrastructure, and independent credit ratings reinforce its credibility. A growing presence among the broader DeFi ecosystem ensures its assets are composable, productive, and scalable. OpenEden wasn’t the first attempt, nor will it be the last, but we believe it is one of the best-positioned teams to capture the tokenization opportunity ahead. ## Sources *Data is sourced from DeFi Llama, Rwa.xyz, and Artemis Analytics.* - Dune Analytics, *RWA Report 2025 Dashboard*. Retrieved from [https://dune.com/rwareport2025](https://dune.com/rwareport2025) - Theia Research, *Internet Finance*. Retrieved from [https://x.com/theiaresearch/status/1876618725547233417?s=46](https://x.com/theiaresearch/status/1876618725547233417?s=46) - Modern Treasury, *History of ledgers*. Retrieved from [https://www.moderntreasury.com/journal/history-of-ledgers](https://www.moderntreasury.com/journal/history-of-ledgers) - Gresham Technologies, *Why trades fail: Understanding the cost of reconciliation errors*. Retrieved from [https://www.greshamtech.com/blog/why-trades-fail-reconciliation](https://www.greshamtech.com/blog/why-trades-fail-reconciliation) - TD Securities, *Cross-border implications of T+1 settlement*. Retrieved from [https://www.tdsecurities.com/ca/en/cross-border-implication-of-t-1-settlement](https://www.tdsecurities.com/ca/en/cross-border-implication-of-t-1-settlement) - John Pfeffer, *An investor’s take on cryptoassets*. Retrieved from [https://hostingfilesonline.co.uk/An%20Investor’s%20Take%20on%20Cryptoassets%20v6.pdf](https://hostingfilesonline.co.uk/An%2520Investor%E2%80%99s%2520Take%2520on%2520Cryptoassets%2520v6.pdf) - Teej Ragsdale, Jack Chong, Mukund Venkatakrishnan, *An Unreal Primer on Real World Assets*[https://docsend.com/view/u53utyp2j4ycg7r6](https://docsend.com/view/u53utyp2j4ycg7r6) - Carter, Nic, *The Stablecoin Duopoly Is Ending*. Retrieved from [https://x.com/nic__carter/status/1973399535092171216](https://x.com/nic__carter/status/1973399535092171216) ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the OpenEden team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Global Rails For The Future Of Money Movement > What does purpose-built stablecoin infrastructure look like? - Publisher: Shoal Research (https://shoal.xyz) - Category: Agentic Payments - Published: 2025-09-25 - Canonical: https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/ - Keywords: stablecoins, crypto, yield, prediction markets, infrastructure, Agentic Payments ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/6b6f94c509f0.jpg) *The way we move money has always evolved, from barter to gold to paper to digital dollars. As stablecoins are set to eat global payments and work their way up the rest of the financial services stack, purpose-built stablecoin infrastructure becomes critical. In this report, we explore how Plasma is building towards global rails for the future of money movement.* ## The Digital Dollar Arc Money rarely sits still, and neither do the ways we move it. Few things are as elementary and timeless as the transfer of value from one individual to another. When ancient herders needed grain or tools, they traded cattle and goats. If medieval farmers needed a pair of shoes, they’d head down to the local village market with bushels of wheat. Over time, it became clear that carrying bulky items and livestock wherever one traveled was inconvenient, so everyone turned to precious metals like gold and silver bars. It didn’t take long to realize those too were not practical nor convenient, and so bars were melted into coins, and coins eventually gave way to paper cash, IOUs, and banknotes. As technology became a bigger part of people’s day-to-day lives, the ways in which money moved only accelerated. Today, someone in the US can send digital dollars to a friend in Peru or Thailand in a matter of seconds, while paying a penny to do so. This isn’t something they could do through their local bank or Western Union; this kind of borderless, low-cost, near-instant money movement is made possible with stablecoins. Stablecoins are digital dollars issued and transferred on blockchain rails. They provide a stable unit of exchange in digital form: the same way anyone with an email address or WhatsApp can instantly communicate across the globe, stablecoins enable anyone with internet access to move money globally. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/a4d8503711c4.png) [Tens of trillions](https://app.artemisanalytics.com/stablecoins?tab=stablecoins) of dollars have already been moved through stablecoins. They continue to grow and reach new all-time highs in supply. Though not new by any means, stablecoin adoption has recently accelerated at a pace few anticipated. Impressively, stablecoins aren’t just growing. They’re already eroding legacy payment networks. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/3804363580f3.png) At Shoal, we believe it is inevitable that stablecoins work their way up the rest of the financial services stack beyond just payments, eventually disrupting consumer banking, lending, B2B settlement, payroll systems, and beyond. But this all begs the question: what’s so special about these digital dollars? ### The Stablecoin Value Prop > “It is possible to create tools to allow end users to create currency protocol layers which have a stable value, pegged to an external currency or commodity. In this way, users of these currencies can own stabilized virtual currency tied to U.S. Dollars, Euros, ounces of gold, barrels of oil..” - Mastercoin whitepaper (2012) Fundamentally, stablecoins are digital assets programmed to maintain the value of an underlying asset it is pegged to. Most commonly, stablecoins are pegged to fiat currencies, particularly the US Dollar (this is why we can call them digital dollars). To maintain this peg and stable value, stablecoin issuers implement specific mechanisms to ensure each stablecoin is backed 1:1 by its underlying asset. The most common way to do this is by holding reserves in cash and short-term US Treasury bills, matching the circulating stablecoin supply. For every new stablecoin minted, users deposit dollars to the issuer. These funds are safeguarded in regulated financial institutions and custodians. When stablecoins are redeemed, an equivalent amount is withdrawn from these reserves and returned to the redeemer, and the corresponding stablecoin supply removed from circulation, or **“**burned”. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/a6acbbe19059.jpg) **Quick aside: There are other stablecoin peg stability mechanisms, some of which are represented by OG leading stablecoin protocols like Maker DAO (now Sky) who built a CDP protocol to let anyone borrow DAI. Conversely, there are also examples like Luna/UST which have failed tremendously and wiped out tens of billions of dollars. Overall, the design of stablecoins can be a fascinating rabbit hole to fall down, but it’s worth staying grounded to the reality that over 80% of stablecoin supply is in USDT and USDC, both of which are USD-backed stablecoins maintained and operated by central issuing entities.* The stablecoin value proposition is not one-dimensional by any means: - **Global, 24/7 Settlement:**Stablecoins can be transferred globally at any time of day, any day of the week. They operate on blockchain rails, designed to settle in minutes if not seconds. For reference, legacy transfer systems like ACH or international wires often take several days to clear, can only be processed during limited business hours, and can further be delayed by weekends or holidays. - **Superior UX:**Stablecoins provide a superior experience to legacy payment systems, on the simple basis of **speed and cost.**On certain chains, stablecoin transfers can be settled in a matter of seconds. Legacy systems like ACH or wire transfers can take anywhere from hours to multiple business days.Stablecoins are also multiples cheaper than legacy payment networks. A stablecoin transaction is simply a redistribution of balances on a digital ledger. The primary resource consumed is the computing power required to update this balance, which is paid as the transaction or **gas fee.**Nowadays, gas costs are racing to zero as low-cost transactions are becoming table stakes for most chains. By contrast, a wire or ACH transfer involves hand-offs between multiple intermediaries - sending banks, receiving banks, clearing houses - all of whom impose a meaningful rake on the money being moved. Legacy cross-border transfers still charge 6.49% on average.It is important to note that while stablecoins offer near-instant, low-cost blockchain transfers, converting funds off-chain into bank accounts or cash, or “offramping”, can still involve legacy fees, FX spreads, and delays. But overall, even with this final step, stablecoin-based transfers remain dramatically faster and less expensive than legacy networks today . - **Permissionless Global Access:**Stablecoins essentially democratize access to stable currencies, like the US dollar. Anyone with an internet connection can send, receive, and hold stablecoins, regardless if they have a bank account or access to financial services. Despite rising global financial inclusion, over 1 billion adults still remain unbanked today, unable to access formal financial services and often excluded from the digital economy. At the same time, many countries still face hyperinflation and currency devaluation. By enabling permissionless global access to the US Dollar, stablecoins provide a financial lifeline to residents in these developing regions. - **Programmable:** Because stablecoins are built on blockchain rails, they exist as smart-contract based tokens. Put even simpler: they are code. This unique design means specific conditions and regulations (i.e. settlement rules, transfer restrictions etc) can be programmed directly into the asset itself. This programmability helps streamline operations as it is much easier and more predictable to write code than to anticipate human error. And because the crypto-native economy is a consortium of open permissionless protocols, stablecoins can naturally plug into, and enhance, nearly any application built on public chains: earning yield through lending or liquidity provisioning, collateral for borrowing other assets, margin for perpetuals trading, betting on bizarre prediction markets, and so on. ### Homegrown, Organic PMF Stablecoins, unlike most other blockchain-native innovations, have stood the test of time because there has always been an organic demand for them. Their history is largely defined by organic adoption arising from clear catalysts at each chapter. A Trader’s Best Friend Stablecoins first gained traction among traders looking for a simple way to move value in and out of volatile positions without offramping into fiat. In the early 2010s, there were few things to do with Bitcoin besides trading it, yet traders lacked an easy way to park funds in between trades. Early references to stablecoin concepts first appeared in the Mastercoin whitepaper, and in 2014 it came into production with the launch of Realcoin (now known as Tether). ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/cc419d6ae110.png) USDT was first issued on Bitcoin via the Omni Layer, and became available through exchanges like Bitfinex. When it launched, USDT brought a new utility for crypto traders: move capital between assets, stabilize exposure to volatility, and execute more complex trading strategies without needing to move into fiat then back into crypto. That said, given such a niche audience, adoption was rather limited. Global Access To Stable Currencies As stablecoins matured, their impact spread well beyond speculative markets. In countries beset by hyperinflation, where local currencies can be devalued significantly overnight, the value of a stable currency like the US Dollar is hard to underestimate. And today, the best way to get access to the US Dollar is through stablecoins. Some notable data points: - Stablecoin purchases accounted for >4% of Turkey’s GDP in 2024. - In 2024, Argentina led LATAM stablecoin volume share as >61% of crypto transaction volume regionally was attributed to stablecoins. - $2.36 trillion was transacted through stablecoins in APAC alone from June 2024 - June 2025. - Sub-Saharan Africa (SSA) grew **$205B** in onchain value in 2025, reflecting 52% YoY growth in crypto adoption from 2024. As such, stablecoins have become essential tools for personal savings, payments, and remittances for millions of people across much of Latin America, Africa, Asia. A Reserve Currency’s Best Friend As stablecoins have spread across emerging markets, their role in reinforcing US Dollar dominance globally becomes evident. But while the value of access to digital dollars becomes rather self-explanatory in emerging economies, it has been more difficult to translate over in the west, particularly in the US. Most Americans have savings accounts. They can send money instantly through apps like Venmo. Few lose sleep at night because they are worried about the dollar devaluing (20-30%) overnight. The most compelling reason for US policymakers to endorse stablecoins is **geopolitical**: **to strengthen the global dominance of the US Dollar.** The US has long wielded the dollar’s reserve currency status to maintain global financial power, most commonly through the petrodollar system. Today, this opportunity lies in stablecoins. The idea is simple: dollar stablecoins, nearly all of which are backed by cash and short-term US Treasuries, require real dollar reserves for every token issued. Each stablecoin minted is a new dollar someone overseas chooses to hold, and therefore a new source of demand for US government debt. One could make the case that the US doesn’t have much of a choice but to embrace stablecoins at this point. In Q4 2024, Tether was ranked as the seventh-largest foreign buyer of US Treasuries, outranking countries such as Canada and Mexico in annual flows. Tether’s latest stablecoin report confirms Tether holds over $127b in U.S. Treasuries, making it one of the largest non-sovereign holders of U.S. government debt. This dynamic is already reshaping policy. The US passed the landmark GENIUS Act recently, laying the groundwork for a regulatory framework for stablecoin issuance in the US for the first time. Not surprisingly, the GENIUS Act requires dollar stablecoins to be fully backed by [US assets],besides providing monthly reserve disclosures and conducting independent third-party audits. This helps reinforcing a stablecoin-to-debt-financing flywheel of sorts: every new token minted effectively creates another buyer for U.S. debt, therefore stablecoin adoption becomes a powerful strategic tool for maintaining dollar dominance. Treasury Secretary Scott Bessent has publicly said “We are going to keep the U.S. the dominant reserve currency in the world, and we will use stablecoins to do that.” In short, US dollar stablecoins are evolving from mere crypto products into key instruments for the US’s geopolitical strategy, meaning the US government is highly motivated to see the adoption of US backed stablecoins continue to grow from here on out. ### The Stablecoin Landscape Today These organic catalysts have helped shape and accelerate the adoption of stablecoins to this day. But to better understand where stablecoins go from here, it’s helpful to zoom out and examine the landscape as it exists today. In the last 30 days alone: - $3.2T in volume processed in stablecoins - 1.2B transactions in stablecoins onchain - 41.4 million addresses have interacted with stablecoins **Data is from [Artemis](https://app.artemisanalytics.com/stablecoins) and referenced at the time of writing.* The total stablecoin supply continues to reach new all-time highs, sitting at just over $291B today. USDT accounts for ~58% of this supply, and has continued to dominate supply throughout the years. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/0489fb1ccf66.jpg) Another important aspect of the stablecoin landscape today is the distribution of stablecoins across different chains. Just as stablecoin supply is dominated by USDT, stablecoin distribution across chains is dominated by Ethereum, accounting for ~55% of total supply today, as is overall stablecoin volume. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/747ab4b73196.jpg) That said, it’s important to recognize there is more than meets the eye here. Ethereum’s dominance, while it cannot be understated, is in large part historical. The first stablecoins like USDT, USDC, and DAI were on Ethereum because there were simply no other blockchain rails to issue and grow programmable digital dollars on. As liquidity deepened on Ethereum, it created a durable moat that persists today. But the nuances start to emerge when considering specific use-cases: **how**stablecoins are actually being used on their respective chains. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/be49e871724f.png) For instance, if we observe data for purely peer-to-peer transactional volume, which we can map to payments, it’s clear that Tron has steadily grown and become the people’s choice. This doesn’t come as a surprise to anyone who’s actually used the two chains; transactions on Tron are simply cheaper and faster. They are more accessible for everyday users. The numbers account reflect this point. In short, the stablecoin landscape is broad and expanding, but still heavily concentrated in specific stablecoins on specific chains. At a glance it may seem the winners and losers are already set. Yet the challenges and pain points of today’s infrastructure suggests otherwise. ### Current Challenges and Pain Points Despite their scale and adoption, today’s stablecoin rails weren’t designed to serve a global-scale payments network beyond crypto-native rails. In particular, today’s stablecoin infrastructure falls short in three key areas: large-scale performance, practical user experience, and integrated infrastructure for fiat rails. Performance At Scale The standard for chain performance and network capacity has come a long way since Ethereum’s L1 gas wars. Fees for stablecoin transfers, which could cost tens of dollars during peak network congestion on the L1, have dramatically fallen, and stabilized. Even so, most public blockchains still lag legacy payment networks in scalability and uptime. Ethereum and its L2s have [roughly average](https://l2beat.com/scaling/activity) 244 daily TPS. Solana [regularly handles](https://solscan.io/analytics#networks) upwards of 2-3K daily TPS, and previously peaked around 4.8K (though it is always important to point out the nuance between vote and non-vote transactions). Yet global payment networks are designed to support tens of thousands of TPS, and can’t afford downtime even under peak congestion. There are lots of promising developments ahead to improve this. Between the rise of app-specific perp DEX chains, Firedancer and Alpenglow coming to Solana, the performance that Monad and MegaEth are expected to deliver, the rise of SVM L2s. Yet none of these are stablecoin-specific. Stablecoin transfers on these chains still compete for more blockspace across swaps, perps, and everything else users can do on those chains as network activity and adoption scales. User Experience Even though transactions settle much quicker onchain than through banks, the user experience is still clunky. The Boston Consulting Group’s 2025 stablecoin report identifies “gas-token management for transaction fees” and fragmented liquidity as critical technical obstacles that both retail and enterprise users face when using stablecoins for payments. The most obvious, low hanging fruit is gas-token friction: someone receiving USDC on Ethereum or SOL on Solana inherently needs ETH or SOL just to move or spend their funds. Onboarding for net new users is still impractical. Liquidity is another challenge. Stablecoin supply is currently fragmented across hundreds of chains, which makes it harder to move large amounts or guarantee immediate conversion back to fiat outside of Ethereum. This fragmentation also dilutes network effects, forcing users and institutions to navigate bridges, gas tokens, and liquidity sources rather than relying on a single liquid, unified market. Privacy, too, is lacking on today’s stablecoin infrastructure. Public blockchains expose transaction details by default. While privacy-preserving apps exist, users have to go out of their way to find and use them. There is no integrated “toggle” to enable private transactions. This means everyday payments with stablecoins are far more transparent than they would be with cash or even traditional banking. To the individual consumer, this may just feel invasive. To enterprises and financial institutions, it’s a non-starter. The onchain user experience has improved significantly, but still leaves room for improvement. Lack Of Integrated Infrastructure One of the underappreciated challenges with today’s stablecoin rails is the lack of integrated infrastructure, particularly to fiat rails. Sending a friend USDT is not the same as them being able to spend it at a grocery store. In practice, users still face FX spreads, hidden rakes, and compliance bottlenecks when they try to move between blockchain rails and local payment systems. Off-ramping involves using centralized exchanges or other intermediaries that require users to create accounts with them, often KYC’d, and pay service fees. This only gets hairier with cross-border transactions, which often introduce more intermediaries and FX Spreads that further eat into the transferred amount. Until stablecoins integrate seamlessly into fiat rails, they’re great for moving value across crypto, but remain largely impractical for mainstream global payments. So Where Do Go From Here? Stablecoins have crossed the chasm. They are no longer a niche by-product of crypto markets. They’re clearing trillions in volume annually, sometimes even monthly, and already powering crypto trading, DeFi, and peer-to-peer markets across emerging economies. But that level of adoption, as meaningful as it is, remains a different bar than what is required to serve as the backbone for global financial rails. Settlement systems like VisaNet, SWIFT, and ACH operate under far stricter demands: near-instant finality, reliability, and uniform compliance frameworks across varying jurisdictions. Stablecoins already move big numbers, but the chains they run on were never designed to consistently meet these standards at global scale. One solution is to wait for general-purpose chains to evolve and harden into payments-grade infrastructure. Another is to embrace purpose-built stablecoin infrastructure. ### Purpose-Built Stablecoin Infrastructure Nearly every major industry where reliability, risk management, and performance are table stakes is built around specialized, purpose-built infrastructure. Global payment networks like Visa and SWIFT are built with specific capabilities to securely move money globally, running in isolated environments optimized for data integrity, regulatory compliance, and uptime. In cloud computing, financial institutions and research centers don’t use AWS or Google Cloud, they still depend on purpose-built setups built to handle petabytes of physics data. In finance, high-frequency trading firms colocate servers next to exchange matching engines because general-purpose infrastructure cannot deliver the latency or reliability needed in markets where every millisecond counts. LLMs trained on sector-specific data in healthcare, insurance, or finance consistently deliver higher accuracy, lower error rates, and stronger regulatory alignment than their general-purpose counterparts. It’s no different in the world of cryptography. The standards that were critical to the expansion of the internet - RSA for secure communication, SSL for browser authentication, and ECDSA for digital transactions - were purpose-built with singular missions: to secure and authenticate data between counterparties online. Stablecoins are now at that inflection point. Applying The App-Chain Thesis Blockchains follow the same logic. As apps gain traction and activity scales, the limits of general-purpose chains emerge. Unpredictable gas fees, throughput ceilings. Compliance gaps. The list goes on. In response, applications are increasingly motivated to launch their own chains. We’ve already seen this play out: decentralized exchanges like Osmosis, dYdX and most recently Unichain; gaming and NFT platforms like Immutable; data networks like Pyth; have all adopted some version of the app-chain model. The thesis originates from Cosmos, which argued that applications should own sovereign blockspace, optimized for their needs, while still interoperating with a broader ecosystem. When a chain is purpose-built, it can deliver deterministic performance and predictable pricing, unconstrained by unrelated blockspace demand. It can embed compliance routines, disclosures, and risk management tailored to regulated products. It can align economic incentives, governance, and value capture directly with the needs of its user base and community. App-specific infrastructure allows chains to move beyond one-size-fits-all environments for more customization, stronger performance, and better UX. Given the trajectory of stablecoin adoption, we believe it is only a matter of time before stablecoins require the same purpose-built infrastructure. One of the first teams building directly towards this vision is Plasma. ## Plasma: A Blockchain Purpose-Built for Stablecoins Plasma is a new L1 purpose-built for the movement of stablecoins. It combines a custom consensus protocol, an EVM-compatible execution layer, and specialized smart contracts to support high-performance at scale, while posting state roots to Bitcoin through a native Bitcoin bridge for security guarantees. Plasma’s mission is simple: to transform the way money moves around the world with specialized stablecoin infrastructure. Just as TCP/IP enabled the internet to become a global information hub, Plasma aims to empower stablecoins to become the global payments hub. Plasma aims to address the pain points of today’s infrastructure - performance, user experience, and integrations- through its core features: - **Day-One Liquidity:**Plasma launches with native USDT and $2B in day-one stablecoin liquidity. - **Zero-Fee USDT Transfers:**Direct USDT transfers are free through Plasma’s [frontend](https://app.plasma.to/). Gas is subsidized through an in-protocol Paymasters contract, using authorization-based transfers controls for rate-limiting and preventing abuse. - **Custom Gas:**Users and apps on Plasma can pay gas fees using whitelisted tokens. At launch, Plasma will enable gas fees in native USDT and pBTC. - **Specialized Architecture:**Plasma is built on a modular architecture, combining a custom high-performance consensus protocol and an EVM-compatible execution environment. - **Bitcoin Security:**Plasma anchors its state roots to Bitcoin through a trust-minimized bridge for direct BTC-EVM programmability. This bridge also supports native BTC deposits, which are converted to pBTC on Plasma. - **Integrated Infrastructure:**At launch, Plasma will support over 100 DeFi apps, including leading protocols like Aave, Ethena, Fluid, and Euler among others, as well as various physical peer-to-peer cash networks. Beyond this, Plasma will support a wide ecosystem of developer tooling and infrastructure across account abstraction, onchain analytics and block explorers, interoperability protocols, oracles, indexers, and RPC providers. To better understand howPlasma actually delivers these features, it’s worth diving deeper into their core architecture. ### System Architecture Fundamentally, Plasma is a Bitcoin sidechain that maintains its own consensus and posts state proofs to Bitcoin. It is built on a modular, multi-layered architecture combining a custom BFT consensus protocol (PlasmaBFT), a Reth-based EVM-compatible execution environment, a trust-minimized Bitcoin bridge, and protocol-native stablecoin smart contracts. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/66b920d030d9.jpg) A transaction on Plasma begins at the user layer, through a supported frontend. It is broadcast to the Plasma chain via RPC. From there it passes through consensus, and once 2/3 PlasmaBFT validators have validated it, the user’s transaction is executed. Plasma then periodically posts state roots to Bitcoin through its native bridge. Let’s examine these core components up closer. PlasmaBFT Consensus is at the very core of onchain systems. It is the coordination mechanism that separates blockchains from banks and fintechs: instead of a single authority, a decentralized distributed network of nodes must validate incoming transactions. This design mechanism, however, introduces latency especially as the network scales and adds more validators, and comes at the cost of performance for many chains today. To overcome latency bottlenecks, Plasma introduces PlasmaBFT, a custom consensus protocol designed to support high throughput. PlasmaBFT is a pipelined implementation of the Fast HotStuff protocol, written in Rust. Finality is deterministic, and is achieved within seconds. As its name suggests, PlasmaBFT follows classic Byzantine Fault Tolerance (BFT) assumptions. In practice, this means the network remains secure as long as no more than one-third of validators are malicious *(this can be reflected as n ≥ 3f + 1, where n is total nodes and f is Byzantine nodes specifically)*. To participate, validators must stake XPL and run supported hardware (2 CPU cores, 4 GB RAM, SSD-based persistent storage). They are then selected to propose and validate blocks on Plasma based on an XPL stake-weighted voting process. The protocol finalizes blocks through a two-chain commit process. Validators vote on block proposals, and once two consecutive quorum certificates (QCs) are formed, the block is finalized. QCs are aggregated validator attestations; chaining them together enforces a single canonical history. PlasmaBFT is optimized to support high-performance on the L1. This is made possible with Plasma’s use of pipelining: while one block is being finalized, the next can already be proposed. As such, blocks can be finalized after just two rounds. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/4c1824501aa4.jpg) This design is derived from Fast HotStuff, a modern BFT protocol designed for, unsurprisingly, being fast. HotStuff introduced a leader-based structure and QC chaining to reduce communication overhead. Fast HotStuff further optimized [chain commit paths for lower latency and higher throughput]. Like HotStuff, PlasmaBFT uses a leader-based round structure, designed to minimize communication overhead while still maintaining fault tolerance. Leaders propose blocks, validators vote, and once enough votes are collected, a QC is generated. If a leader fails or goes offline, the protocol shifts to a new leader using aggregated QCs. Plasmaplans to expand validator participation in several stages. Initially, the biggest priority will be ensuring baseline network stability, therefore Plasma will be secured by a whitelisted set of validators at launch. Over time, the validator set will grow to stress-test performance under larger committees until the final stage, in which participation opens up to the public. Plasma’s Execution Environment Virtual Machines (VMs) process transactions, run smart contracts, and keep state in sync across all participants on its underlying chain. A VM reads the current state of the chain, executes new inputs, and then updates state deterministically. It ensures the same code always produces the same result and state is synchronized across all nodes. Plasma employs a general-purpose **Ethereum Virtual Machine (EVM)** execution environment. This means developers can deploy existing EVM smart contracts and use familiar tooling and infrastructure. Plasma’s execution engine is Reth, a modular Rust-based Ethereum client that separates consensus from execution. This enables more efficient updates, clearer boundaries between block production and execution, and better predictability in performance and behavior. When transactions are submitted on Plasma, Plasma’s execution environment processes them through the EVM, ensuring the relevant smart contracts run and state is updated consistently across all Plasma nodes. Bitcoin-Level Security Blockchains normally secure themselves only through their own validator sets. That security is limited by the size of the validator pool and the economic weight behind it. For stablecoins, where large values may be at stake, relying solely on a new or relatively small validator set can be a risk. To mitigate this, Plasma periodically posts its state roots to **Bitcoin**. Anchoring to Bitcoin provides an additional settlement guarantee: once a Plasma state is recorded on Bitcoin, altering it would require rewriting Bitcoin’s history. This makes censorship or rollback far less feasible and gives Plasma a stronger security baseline than relying on its validator set alone. Plasma achieves this through a Bitcoin-native bridge. The bridge consists of a verifier network, each running full Bitcoin nodes to observe deposits and validate state anchoring. Periodically, state roots from Plasma are committed to Bitcoin via transactions (e.g. OP_RETURN), and the verifier network attests that these anchors match Plasma’s canonical chain. Beyond settlement, the bridge also enables native BTC to flow into Plasma. Users deposit BTC to a designated address, verifiers confirm the transaction on Bitcoin, and Plasma mints pBTC: a fungible ERC-20 token backed 1:1 by BTC. Withdrawals follow the reverse process: users burn pBTC on Plasma, and once verifiers confirm, BTC is released on the base chain. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/bed059914dde.jpg) This bridge makes native BTC usable inside Plasma smart contracts. pBTC is issued as a standard ERC-20, built on LayerZero’s OFT standard to allow cross-chain portability without compromising verifiability against the Bitcoin base layer itself. Users always receive pBTC on Plasma at a 1:1 rate against BTC deposited. To secure withdrawals, Plasma relies on Multi-Party Computation (MPC). Rather than one party holding a private key, multiple verifiers collectively generate signatures, with no single entity able to unilaterally release funds. Stablecoin-Native Smart Contracts On current stablecoin rails, stablecoins exist as generic ERC-20 tokens. They are applications built on top of a base chain. This design works to an extent but friction still emerges: transaction fees paid in separate gas tokens. Every app or wallet has to operate and maintain its own custom Paymaster. Private payments are not feasible. On Plasma, this functionality is built directly into the protocol. A set of in-protocol contracts, written in Solidity and integrated into the execution layer, give stablecoins first-class treatment. These contracts are written in Solidity, integrated into Plasma’s execution layer, and are compatible with any EVM wallet or contract system, including AA standards like EIP-4337 and EIP-7702. Plasma is launching with two core modules. The first is the **Protocol-Managed Paymaster for Zero-Fee USDT Transfers**. This contract sponsors gas costs for direct USDT transfers: transfer() and transferFrom(), so users can send stablecoins without needing XPL. The scope is narrow by design: it applies only to the official USDT and only to direct peer-to-peer transfers, not arbitrary contract calls. To prevent abuse, eligibility is gated through lightweight identity checks such as zkEmail, zkPhone, or captcha systems, and usage is subject to rate limits. The economics are covered by a pre-funded XPL pool managed by the foundation, which pays gas on behalf of users. Developers don’t need custom integrations beyond routing transfers through standard smart account flows, and the system supports both EOAs and smart contract wallets. Over time, Plasma is exploring features like reserved blockspace for eligible USDT transfers, ensuring inclusion even under network congestion The second module is the **ERC-20 Paymaster for Custom Gas Tokens**. This contract allows users to pay for any transaction, not just transfers, using whitelisted tokens (this will be USDT and pBTC initially). The process is simple: the user approves the paymaster to spend the chosen token, the paymaster consults oracles to calculate how much of that token equals the required gas, and then pays the validator in XPL under the hood while deducting the equivalent amount from the user. This removes the need for swaps or native token balances, smoothing the onboarding process for new users. Developers benefit because the paymaster is handled at protocol level, so they don’t have to build or maintain their own fee abstraction systems. Wallets only need to surface approvals and error handling, while users see a unified and intuitive UX. By running these modules at the protocol level instead of leaving them to individual apps, Plasma ensures consistent behavior across apps, enables subsidized gas without external funding tokens, and ties these features directly into block production and execution. ### XPL And Plasma’s Economics At the core of Plasma’s business model is its native token, XPL, which secures the network and subsidizes PlasmaBFT validators. ![](https://shoal.xyz/research/writing/global-rails-for-the-future-of-money/img/f66e3502f495.jpg) Every transaction on Plasma requires a base fee, with dynamic demand-based fees. These fees, along with newly issued tokens, form the reward pool that sustains validator incentives. Plasma takes a unique approach to slashing. Rather than punishing malicious validators, it incentivizes honest behavior through a novel reward slashingmechanism. In this model, validators who misbehave or fail to participate lose their block rewards but keep their principal stake. The penalty is lighter, but it makes participation less risky for institutional operators, where sudden capital loss is often commercially unacceptable. Importantly, Byzantine safety is still preserved under the standard assumption that fewer than one-third of validators act maliciously. Validators are compensated in XPL for proposing blocks, voting in consensus, and validating transactions. Their rewards come from a mix of transaction fees and token emissions, making validator incentives directly tied to both network activity and the broader economics of XPL. The Plasma Ecosystem Surrounding Plasma’s technical work is a growing, integrated ecosystem. Plasma is launching with $2B in stablecoin liquidity and over **100 DeFi integrations**, including names like **Aave, Ethena, Fluid, and Euler**. Plasma recently announced [Plasma One](https://www.plasma.to/insights/introducing-plasma-one-the-one-app-for-your-money), its main consumer-facing app. It functions as a stablecoin-native wallet and card interface, giving users “one” place to hold, send, and spend USDT. Transfers are gasless, balances can be used directly for payments, and onboarding is quick enough to issue a virtual card in minutes. On the integration side, Plasma has partnered with **[Binance Earn](https://www.plasma.to/insights/plasma-and-binance-earn)**, allowing users to access yield products directly from the network. Work is also underway on fiat on/off-ramps and peer-to-peer cash networks in emerging markets, aiming to make the jump between stablecoins and local currency less dependent on centralized exchanges. Plasma will also launch with a wide ecosystem of developer tooling and infrastructure across account abstraction, onchain analytics and block explorers, interoperability protocols, oracles, indexers, and RPC providers. ## The Outlook For Plasma Given what we now know about Plasma, it’s worth zooming out and reflecting on some of the most important catalysts and considerations impacting how the path forward unfolds from here. ### Competitive Landscape Plasma has an ambitious and important mission: to transform how money moves across the globe. Unsurprisingly, they face competition from several angles. First, general-purpose blockchains aren’t going anywhere. Ethereum still dominates in stablecoin liquidity and network effects. Tron commands the largest share of USDT transfers and peer-to-peer transaction volume, and Solana is constantly working on developments to improve performance. Meanwhile, new chains like Monad and MegaETH are also competing on the basis of high-performance and full EVM compatibility. At the same time, we’re seeing the rise of stablecoin-specific chains, or “stablechains”, similar to Plasma. Circle is building **Arc**, a permissioned chain designed for regulated USDC settlement. Stripe is working on **Tempo**, focused on embedding stablecoins into merchant payments. Google recently announced Google Cloud Universal Ledger (GCUL), an L1 focused on digital payments and tokenization for financial institutions. Meanwhile others stand out with differentiated approaches and unique value propositions. For instance, **Payy** also introduces neobanking stablecoin infrastructure, including its own purpose-built chain, but with a core focus on privacy-preserving transfers. Even outside of crypto, non-blockchain payment rails are already converging to offer much of the same key benefits stablecoins do. That means Plasma not only has to match crypto benchmarks, but also these legacy standards of performance, speed, and reach. ### Key Areas of Focus With that in mind, what are key areas of focus that would help the Plasma team? For starters, distribution is everything. Like any business, a chain can’t grow without getting its product into the hands of users. For blockchains, this has been mostly limited to crypto-native apps, exchanges, connected chains, and DeFi protocols. Though Plasma launches with over 100 integrations and $2B in liquidity, the harder challenge is pushing beyond crypto-native adoption into retail and enterprise **crypto-adjacent use.** Plasma is set to support 100+ countries, 100+ currencies, and 200+ payment methods, laying the groundwork for a strong initial distribution footprint. Long-term, though, sustaining real-world adoption will require constant effort: onboarding merchants, working with fintech partners, and leveraging Tether/Bitfinex’s existing networks. Tron’s rise shows how powerful grassroots distribution can be. The question is whether Plasma can retain users and build durable channels beyond its crypto-native base. Liquidity is another area of focus. For a chain purpose-built around stablecoins, deep liquidity is simply existential. Plasma is launching with billions in native USDT issuance, making it the 8th largest USDT chain on day one. To ensure it can sustain future growth, bridges, ramps, and deposit flows have to be simple and as friction-free as possible. Privacy is another underrated piece. Confidential Payments are planned but won’t ship with Plasma’s mainnet beta launch. The core idea being explored is to shield sensitive transfer data while remaining composable and auditable. This feature would be implemented as a lightweight, opt-in module at first, though Plasma could very well look to enshrine privacy features at the protocol layer in the future. With its novel architecture, ecosystem reach, and liquidity base Plasma is in a good position: - Anchoring to Bitcoin provides a differentiator. Plasma periodically posts its state roots to Bitcoin, giving extra settlement guarantees beyond relying solely on its validator set. - Additionally, building as a public permissionless chain lets Plasma reach a broader audience, while being able to enforce features like identity-based transfers for specialized experiences like zero-fee USDT transfers. - Using a custom consensus protocol enables Plasma to support fast execution at a high-throughput rate. - Launching with over 100 DeFi integrations and $2B in USDT makes it the 8th largest chain by stablecoin supply from day one. ### Applications and Use Cases Plasma provides rails to support a variety of stablecoin-specific use cases and applications. Global Payments and Remittances One of the most immediate applications is as a global payment rail. A worker in the U.S. could send $100 in USDT to a relative in Nigeria. The relative could then spend directly through integrated merchants, use directly through crypto cards, or cash out via local OTC desks and exchanges. In countries such as Nigeria, Argentina, and Turkey, where stablecoins already act as a hedge against inflation and a remittance lifeline, Plasma can reduce friction even further. Success here depends on integrations with local wallets, ATMs, and payment systems. Tron achieved this over years of grass-roots outreach, so Plasma will need similar partnerships, possibly leveraging Tether’s existing networks. If executed well, Plasma could serve as the backend for remittance firms or neo-banks, offering instant dollar transfers without requiring their own blockchain infrastructure. Merchant Payments and Micropayments Paying with crypto has been rare due to volatility and fees, but zero fee USDT transfers on Plasma could change that. Merchants could accept stablecoins at the point of sale via QR codes, avoiding credit card fees and chargebacks. Privacy features would let businesses shield revenue data from competitors, while micropayments become practical. Platforms could charge a few cents per article, stream, or download without fees eroding margins. For merchants, the key will be user-friendly tools and regulatory compliance. Stablecoin payment processors may emerge on Plasma, and over time, even traditional providers could integrate it in high-fee or underbanked regions. Forex and Cross-Currency Transactions The stablecoin market extends beyond the U.S. dollar, with Euro, offshore yuan, and gold-backed tokens already in circulation. Plasma could become a hub for on-chain foreign exchange if multiple fiat stablecoins are supported. A user could, for instance, swap USDT for EURT on a Plasma-based DEX at near-zero cost. This enables cheaper, faster forex trades compared to banks. Imagine a multinational paying European suppliers by converting millions of USD into EUR instantly and settling the transaction on-chain. Deep liquidity will be needed, but zero fees and institutional demand could draw in market makers. DeFi with Stablecoins and BTC Plasma’s EVM compatibility opens the door to decentralized finance focused on stablecoins and Bitcoin. Potential applications include: - Stablecoin DEXes and AMMs**:** Low-cost, high-volume trading of stablecoin pairs (USDT/USDC, USDT/EURT) or stablecoin/BTC pairs. - Money Markets and Lending**:** Platforms could let users lend or borrow USDT against BTC collateral. - BTC-DeFi Innovations: Bitcoin-backed stablecoins minted on Plasma without custodians. Institutional Treasury and Settlement Institutions such as exchanges, fintechs, or even banks could use Plasma as a settlement layer for large transfers. Exchanges may prefer Plasma over Tron or Ethereum for inter-exchange USDT flows, thanks to its speed and zero fees. Banks or corporate consortiums could also run private overlays on Plasma, settling large interbank transfers with Bitcoin-backed finality. For corporate treasuries, moving $50 million between subsidiaries could take seconds instead of days with SWIFT. Privacy modules would allow selective disclosure for auditors or regulators. If U.S. legislation like the GENIUS Act advances, regulated institutions may adopt public stablecoins like USDT and USDC, with Plasma positioned to capture that demand. Beyond these, there are more crypto-native use cases that would be interesting to see teams explore building on Plasma. Zero-fee USDT transfers could make a really compelling case to build infrastructure for autonomous agent payments on Plasma. With $2B deployed from day one, Plasma could provide deep stablecoin liquidity prediction markets need to sustain meaningful user activity. Plasma could also serve as a routing layer for stablecoin liquidity across multiple chains. ## Closing Thoughts Plasma’s mainnet beta is now live. We’re excited to see how purpose-built stablecoin infrastructure unfolds from here on out. Stablecoins are set to disrupt global payments and the rest of the financial services stack, but they need dedicated, purpose-built rails to flourish. Though Plasma is not the only one pursuing this north star, it offers one of the most promising solutions to capture the **trillion dollar stablecoin opportunity.***.* ## Sources 1. **Plasma Docs**[docs.plasma.to](https://docs.plasma.to) 2. XPL MICA Whitepaper **[https://drive.google.com/file/d/1kw2CfXp0SLPGkitm6v814vmTtWOQTYBw/view](https://drive.google.com/file/d/1kw2CfXp0SLPGkitm6v814vmTtWOQTYBw/view)** 3. **Artemis Analytics** [https://app.artemisanalytics.com/stablecoins](https://app.artemisanalytics.com/stablecoins) 4. **DeFi Llama**https://defillama.com/ 5. **Stablewatch** [stablewatch.io](https://stablewatch.io) 6. U.S. Department of the Treasury. (2025). Major Foreign Holders of Treasury Securities. TIC Data, Treasury.gov. 7. Chainalysis. (2024). The Geography of Cryptocurrency Report. Chainalysis. https://www.chainalysis.com 8. Chainalysis. (2025). Sub-Saharan Africa Crypto Adoption. Chainalysis Blog. https://www.chainalysis.com/blog/subsaharan-africa-crypto-adoption-2025/ 9. Tether. (2021) Tether Whitepaper [https://assets.ctfassets.net/vyse88cgwfbl/5UWgHMvz071t2Cq5yTw5vi/c9798ea8db99311bf90ebe0810938b01/TetherWhitePaper.pdf](https://assets.ctfassets.net/vyse88cgwfbl/5UWgHMvz071t2Cq5yTw5vi/c9798ea8db99311bf90ebe0810938b01/TetherWhitePaper.pdf) Tether whitepaper 10. Mastercoin (2013) Mastercoin Whitepaper [https://drive.google.com/file/d/16t_trC9bP1fkxWImFuQUj96fgjw5JVjL/view](https://drive.google.com/file/d/16t_trC9bP1fkxWImFuQUj96fgjw5JVjL/view) 11. Tether. (2025). Tether Reserve Report (June 2025). ISAE 3000R Audit Opinion. [https://assets.ctfassets.net/vyse88cgwfbl/2SGAAXnsb1wKByIzkhcbSx/9efa4682b3cd4c62d87a4c88ee729693/ISAE_3000R_-_Opinion_Tether_International_Financial_Figure_RC187322025BD0201.pdf](https://assets.ctfassets.net/vyse88cgwfbl/2SGAAXnsb1wKByIzkhcbSx/9efa4682b3cd4c62d87a4c88ee729693/ISAE_3000R_-_Opinion_Tether_International_Financial_Figure_RC187322025BD0201.pdf) 12. Maven11. (2025). The Application Specific Chain Thesis. Maven11. [https://www.maven11.com/publication/the-application-specific-chain-thesis](https://www.maven11.com/publication/the-application-specific-chain-thesis) 13. Artemis Analytics, Castle Island Ventures, & Dragonfly. (2025). Stablecoin Payments from the Ground Up. Artemis Reports. [https://reports.artemisanalytics.com/stablecoins/artemis-stablecoin-payments-from-the-ground-up-2025.pdf](https://reports.artemisanalytics.com/stablecoins/artemis-stablecoin-payments-from-the-ground-up-2025.pdf) 14. World Bank. Remittance Prices Worldwide. World Bank. [https://remittanceprices.worldbank.org/](https://remittanceprices.worldbank.org/) 15. International Monetary Fund. (2025). [Working Paper]. IMF eLibrary. [https://www.elibrary.imf.org/view/journals/001/2025/141/001.2025.issue-141-en.xml?cid=568260-com-dsp-crossref](https://www.elibrary.imf.org/view/journals/001/2025/141/001.2025.issue-141-en.xml?cid=568260-com-dsp-crossref) 16. Boston Consulting Group. (2025). Stablecoins: Five Killer Tests to Gauge Their Potential. BCG. [https://media-publications.bcg.com/Stablecoins-five-killer-tests-to-gauge-their-potential.pdf](https://media-publications.bcg.com/Stablecoins-five-killer-tests-to-gauge-their-potential.pdf) ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author’s own, not the views of their employer. This post has been created in collaboration with the Plasma team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research* --- # Federated Learning Meets Blockchain: Inside FLock's Decentralized AI Network > Exploring how FLock combines Federated Learning with blockchain-based incentive mechanisms to replace centralized AI systems. - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2025-08-22 - Canonical: https://shoal.xyz/research/writing/federated-learning-meets-blockchain/ - Keywords: crypto, privacy, infrastructure, AI & Agents ![](https://shoal.xyz/research/writing/federated-learning-meets-blockchain/img/831213659bdb.jpg) ***Decentralized AI is beginning to cross the chasm**. The United Nations Development Programme (UNDP) has long advocated for the sustainable use of AI to empower developing nations and underserved communities as part of achieving its [Sustainable Development Goals](https://www.undp.org/sustainable-development-goals)(SDG). Earlier this week, the UNDP selected [FLock](https://www.flock.io/) - a decentralized AI network - as its strategic AI partner. Why does this all matter, and how does FLock’s decentralized approach address challenges that centralized AI cannot?* ## AI Is Inevitable The role of AI continues to grow in our day to day lives. Millions of people are using AI-powered applications like ChatGPT. Enterprises are pouring hundreds billions into developing the infrastructure, training, and integration of AI in their workflows. Governments are [actively implementing](https://www.ai.gov/action-plan)AI solutions for public operational efficiency with AI. This is all for good reason: AI stands to unlock a new level of [productivity gains](https://www.oecd.org/en/publications/the-effects-of-generative-ai-on-productivity-innovation-and-entrepreneurship_b21df222-en.html) not yet seen. It’s already leading to [groundbreaking applications](https://azure.microsoft.com/en-us/blog/transforming-rd-with-agentic-ai-introducing-microsoft-discovery/) across various fields of scientific research. People are automating busy work, leading to more creative initiatives and experiments. A new generation of goods and services is actively being transformed from natural language into existence, what has come to be known as “vibe-coding”. [McKinsey](https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work) projects $4.4 trillion in productivity gains from AI adoption, while Goldman Sachs forecasts up to 7% increase in global GDP by 2030. There is a caveat though: the AI models we know and use today are **black boxes**: closed-source LLMs developed and maintained by central, for-profit entities. These entities control how the AI models are developed and trained, and determine the terms and means by which they can be accessed and used. At a glance, these are resourceful, legally compliant companies with a strong economic incentive to keep improving these AI models and listening to their customers’ feedback and requirements. What exactly then is the concern? ### Why Not Just Use Centralized AI? People have been waking up to the dangerous realities of social media algorithms, realizing the extent to which these black boxes maintained by for-profit entities are impacting the way they think and behave. The implications with AI are significantly greater. Binji’s AI therapist tweet offers a more facetious example to reason about, but it speaks to the concerning implications of speaking to black boxes which operate in an unknown manner behind the scenes. But a shift away from centralized AI is not about realizing utopian cypherpunk ideals: there are legitimate concerns and risks at the individual, enterprise, and national levels: - **Single point of failure:**Centralized AI introduces a single point of failure for its users. First, this poses an operational risk, if these facilities go offline due to outages, attacks, or natural disasters. This is not [uncommon](https://www.crn.com/news/cloud/2025/the-10-biggest-cloud-outages-of-2025-so-far). Second, there are substantial security concerns, including the risk of leaked user prompts, chat histories, and sensitive data with single-failure points. Such breaches at AI companies could expose everyday user information and become national security liabilities when government or sensitive data is involved. - **Data Protection:**Centralized AI apps need to store and maintain user data to improve models and provide personalized experiences. Users are providing LLMs with all kinds of data about themselves, including sensitive and personal information. The concern here is twofold: that data is at risk of being breached. Additionally, the risk is that AI companies monetize user data the same way social media and internet companies have historically monetized their users. - **Value Plurality and Model Output Bias:**Model outputs are at risk of bias towards a single entity’s values and perspectives. The [Google Gemini incident](https://www.nbcnews.com/tech/tech-news/google-making-changes-gemini-ai-portrayed-people-color-inaccurately-rcna140007)controversy, though a mostly isolated example, highlighted the potential risks of models providing misinformation to its users. - **Scalability: Processing power limited to a single entity creates potential bottlenecks over time. Network delays, capacity constraints, and overprovisioning challenges can arise as usage scales, and the entire network runs on the assumption that the centralized AI provider alone has enough processing power and capacity to handle it all.** Beyond this,**innovation** is simply stifled if a limited number of people or entities can experiment and develop new models. Most of the internet’s infrastructure runs on Linux, an open-source operating system that empowers developers worldwide to innovate and adapt freely. Wikipedia, a freely editable and collaboratively maintained knowledge base, serves as a gateway to information for billions of people globally. In the world of computing and software, open source technology movements have repeatedly shown that collaborative development can produce superior, more resilient solutions than closed-source alternatives. ### The UNDP: Using AI As A Transformative Force For Good AI is technology powerful enough to change the world for good. What may be mere quality-of-life improvements in one country can be transformation 0:1 improvements in others. et centralized AI inherently conflicts with its potential as a public good. Developed in 1965, the UNDP was formed to help eradicate poverty and reduce inequalities worldwide through sustainable development. For years now, The UNDP has been advocating for embracing AI as a transformative force for good. Specifically, the UNDP believes that AI can help accelerate its mission. The key challenges they are concerned with include: - **Digital public infrastructure**: Developing nations may not be able to afford to build Google/OpenAI-scale systems. At the same time, they do not want to be dependent on AI developed by other nations like the US or China. - **Nation-specific needs:**Nations need AI solutions tailored to their specific needs and scale, not settle for cookie-cutter general purpose solutions. - **Data sovereignty: Nations need to protect their citizens’ data, especially across healthcare, agriculture, and other sensitive and personal data.** Just earlier this week, the UNDP announced a new strategic AI partner. It wasn’t OpenAI, Anthropic, or Google, but a new decentralized alternative: FLock. ## Introducing FLock FLock, short for **F**ederated machine**l**earning on bl**ock**chain, is a decentralized AI network. Instead of a single entity, it enables anyone around the world to contribute models, data, and computing resources and participate in an open, collaborative environment for decentralized AI training. To do this, FLock combines **conventional and Federated Learning**AImodel training with automated blockchain-based reward distribution. ![](https://shoal.xyz/research/writing/federated-learning-meets-blockchain/img/fa2d79649587.jpg) Altogether, this creates an open marketplace of app-specific models which are community owned, built, and led. ### How It All Works To better understand FLock’s approach, it helps to first understand **Federated Learning.** **Federated Learning, or federated Machine Learning,**is a collaborative machine learning technique where multiple participating clients can collaboratively train a global model without exposing any raw data. This approach is designed to improve output quality by enabling AI models to be trained on wider and more diverse data sources, while protecting the privacy of participants’ data. ![](https://shoal.xyz/research/writing/federated-learning-meets-blockchain/img/b071eecefadd.jpg) Federated learning typically involves a central hub server on which the global model lives and is redistributed for local training. Participating clients then train the global model using their local data and only exchange their gradients, the weights and parameters used in their local training, back to the hub server. The hub server then aggregates these gradients to update the global model, and the process is repeated until the training is complete. Federated learning has proven to be an effective solution to addressing user privacy within AI training, there is a catch with this set up, though. To start, the central hub server, on which the global model lives, is still a single point of failure. Should it stop working for whatever reason, the whole learning stops. Additionally, federated learning still assumes the data clients provide is honest. In other words, it doesn’t address the risk of [data poisoning](https://www.crowdstrike.com/en-us/cybersecurity-101/cyberattacks/data-poisoning/), a technique in which clients provide inauthentic data targeted at diminishing the quality of a model’s training and therefore its output. This is becoming a growing area of concern as more of today’s world becomes reliant on AI models, especially in [fields like healthcare](https://www.nature.com/articles/s41591-024-03445-1). FLock aims to address these problems by implementing cryptographic proof and economic incentives enforced onchain. So how exactly does that work? **FLock System Architecture** FLock consists of three interconnected systems that form its decentralized AI ecosystem: - **The AI Arena**: A decentralized training platform where developers submit models that compete on public datasets. These models are evaluated by a distributed network of validators, with an important feature: validators cannot identify which model came from which trainer, preventing collusion. High-performing models earn rewards while underperforming ones can be refined and resubmitted. This competitive process produces models optimized for real-world performance, with participation requiring token stakes to ensure accountability. - **The FL Alliance:** FLock’s Federated Learning client that enables training on sensitive private data without exposing it. The system randomly assigns participants as either proposers (who train models locally) or voters (who evaluate results). When a majority of voters approve a model update, proposers receive rewards. Those who submit corrupted data or false validations lose their stake. - **The AI Marketplace**: Successful models from Arena and Alliance are deployed in the Marketplace for production use, with version control, performance monitoring, and automated updates. Model hosts provide infrastructure and set pricing, while users pay for API access beyond free tier limits. Higher-quality models attract more users, generating revenue for creators and hosts - creating market incentives for continuous improvement. ![](https://shoal.xyz/research/writing/federated-learning-meets-blockchain/img/e11a15ed8cc2.jpg) Altogether, models begin in the Arena with public data training, undergo refinement in the Alliance with private data, then reach production in the Marketplace. Usage data feeds back to improve subsequent training cycles. The key innovation lies in how FLock applies onchain mechanisms to coordinate incentives among network participants. **The Onchain Layer** FLock’s key innovation is using blockchain to solve the lack of coordination among participants in federated learning. [FLOCK](https://docs.flock.io/flock-tokenomics/token-allocations), a token that lives on the Base L2, serves as the key mechanism that aligns incentives across the network. **Proof of Stake** FLock implements a robust incentive mechanism to incentivize honest behavior (and penalize malicious behavior at that) among its federated learning participants. This mechanism, based on a [research paper](https://ieeexplore.ieee.org/abstract/document/10471193)published by the FLock team, utilizes a proof-of-stake system in which participants stake FLOCK tokens to participate. Malicious behavior, i.e. data poisoning, risks real economic value, while honest contributions earn rewards. Rewards are distributed in FLOCK, proportional to stake size and performance quality. There are three ways to participate: - **Training node operators:**stake tokens to compete in model training tasks. - **Validators: stake to evaluate and score submitted models** - **Delegators: delegate stake to [training nodes], earn rewards accordingly.** **Smart Contract Orchestration** FLock uses a set of smart contracts to orchestrate the training and validation process. When tasks are created, the smart contracts are responsible for: - Selecting participants using stake-weighted randomness to prevent gaming - Distributing rewards based on aggregated validation scores - Slashing stakes of participants who submit poisoned data or false validations - Managing reward distribution between operators and delegators **More on FLOCK** Live on the Base L2, the FLOCK token serves three functions within the ecosystem: **Utility:** FLOCK is staked across different roles, with larger stakes increasing selection probability for training and validation tasks. Task creators can pay additional FLOCK as bounties to expedite their training processes. The system implements time-based multipliers: longer staking periods (up to 365 days) generate gmFLOCK (governance-weighted FLOCK), increasing influence and reward shares from network emissions. **Payment:** Users access models trained in AI Arena and FL Alliance with rate limits based on stake amounts, paying in FLOCK for usage beyond these limits. Model hosts stake FLOCK to serve models and set custom pricing structures. **Governance:** FLOCK holders participate in DAO governance, voting on task verification (determining which tasks qualify for rewards), parameter adjustments (reward distributions, slashing rates), and protocol upgrades. ### Use Cases and Applications FLock is already being actively deployed across numerous real-world applications where deep, app-specific contextual knowledge, strict privacy guarantees, and decentralization matters: **Specialized Blockchain Development: The Aptos Move LLM** FLock partnered with the Aptos Foundation to develop an LLM that outperforms ChatGPT-4o in generating Move-specific code, from simple "Hello World" scripts to complex programs like yield tokenization with AMM trading functionality. The model was trained specifically on community-contributed Move code datasets, taking advantage of FLock's decentralized training infrastructure. Initial testing demonstrated superior performance compared to ChatGPT-4o, with greater accuracy and adherence to Aptos-specific requirements. The model, built on top of DeepSeek's foundation and available on Hugging Face, achieves ChatGPT-4-level performance specifically for Move programming. **Community-Specific AI Assistants** FLock enables tailored AI assistants that understand specific contexts: - **FarcasterGPT**: Trained on Farcaster protocol data to understand its unique social dynamics, terminology, and user patterns - **ScrollGPT**: Optimized for the Scroll L2 ecosystem, understanding its technical documentation, governance proposals, and developer patterns - **DAO-specific models**: Custom assistants that understand individual DAOs' governance structures, historical decisions, and community norms **Privacy-Preserving Healthcare Applications** FLock enables healthcare providers to collaborate on diabetes prediction models using linear regression, where each participant retains control over their data while computing model updates locally. Multiple hospitals can train on their local patient records, contributing only mathematical gradients to improve the global model. This approach is crucial for complying with stringent health data protection regulations such as HIPAA, as patient data never leaves the institution. By integrating data from diverse demographics and geographical locations without sharing raw data, FLock helps develop more accurate and generalized models that account for population variations. **Decentralized Compute Integration: FLock x Akash** FLock has integrated with [Akash Network](https://akash.network/?gad_campaignid=22707444890) to create one-click deployment templates for running FLock validators and training nodes on decentralized compute infrastructure. This partnership exemplifies the composability of decentralized systems as users can now: - Deploy FLock validators on Akash with minimal configuration - Access GPU resources through Akash's marketplace - Run training nodes using Docker containers with customizable hardware specifications - Pay for compute using AKT tokens while earning FLOCK for validation The integration includes pre-configured templates requiring only an API key and task ID, making decentralized AI training accessible to non-technical users. **Natural Language Database Access: Text2SQL** FLock's Text2SQL model enables users to query databases using natural language commands, simplifying SQL syntax. Developed through AI Arena's competitive training process, the model was trained on extensively cleaned and manually reviewed open-source datasets. ## The Path Forward AI represents the next foundational layer of human-computer interaction. However, the practical concerns around centralized AI are becoming harder and harder to ignore. Single points of failure could cripple nations. Data sovereignty violations could compromise millions. Innovation bottlenecks stand to largely favor incumbent interests. At Shoal Research, we believe this layer must be built just like the internet was: as an open, collaborative effort rather than a corporate, centralized service. We’re excited to see this frontier push forward, and think FLock’s approach to combine Federated Learning with onchain incentive mechanisms and cryptography offers an innovative solution here. Being selected by the UNDP, FLock will mentor five pilot projects across climate finance, inclusive energy, and social protection, proving decentralized AI can address humanity's most complex challenges. Time will tell how the outcome plays out, but FLock is well-positioned to thrive in a world that embraces AI as a public good and decentralized AI networks as the approach to get there. **References** 1. United Nations Development Programme. (n.d.). Sustainable Development Goals. UNDP. https://www.undp.org/sustainable-development-goals 2. FLock. (n.d.). Documentation. FLock Docs. https://docs.flock.io/ 3. FLock. (n.d.). Whitepaper. FLock. https://www.flock.io/whitepaper 4. FLock. (2022). FLock: Federated learning on blockchain. arXiv. https://arxiv.org/abs/2211.04344 5. FLock. (2024). Decentralized federated learning: Incentives and mechanisms. ACM Digital Library. https://dl.acm.org/doi/10.1145/3701716.3715484 6. FLock. (2024). Blockchain-enabled federated learning: Privacy and trust in decentralized AI. IEEE Xplore. https://ieeexplore.ieee.org/abstract/document/10471193 ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the FLock team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # AI and Cognitive Over-the-Counter Transhumanism > How Consumer AI and ChatGPT Tech Blur the Line Between Tool and Self - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2025-07-31 - Canonical: https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/ - Keywords: AI & Agents ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/3687458b9ea2.jpg) ## Introduction The Brazilian butt lift (“BBL”) has become a mainstream obsession. In perfect algorithmic, addictive brainrot fashion, I was watching a[TikTok where the creator mentioned that BBLs are a form of transhumanism.](https://www.tiktok.com/t/ZP86TAKxu/) The creator argued that individuals have a perceived self, which they embody through physical means, and by augmentation, someone can reach their desired “avatar.” ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/f737d1b9a4a3.jpg) This creator’s offhand remark shows how readily people embrace technology-driven self-modification in everyday life. Such cultural anecdotes hint at a broader phenomenon: an emerging form of **“over-the-counter” transhumanism**. By *over-the-counter*, I mean enhancements that are accessible without specialized clinics or implanted devices, practically consumer-grade boosts to human abilities. Notably, these enhancements are increasingly **cognitive** rather than physical. Just as social media filters and[cosmetic procedures](https://www.forbes.com/sites/joshwilson/2023/01/18/cosmetic-surgery-is-on-the-rise-with-technology-and-hollywood-is-at-the-centre-of-it/) allow “one-touch magic” to reshape our appearance, AI tools like ChatGPT offer on-demand augmentation of memory, creativity, and problem-solving. We’ve been doing it for ages, from writing and printing to smartphones and search engines, [each innovation profoundly changing not just how we live but even who we are.](https://nickbostrom.com/old/transhumanism#:~:text=Such%20innovations%20as%20speech%2C%20written%20language%2C%20printing%2C%20engines%2C%20modern%20medicine%20and%20computers%20have%20had%20a%20profound%20impact%20not%20just%20on%20how%20people%20live%20their%20lives%2C%20but%20on%20who%20and%20what%20they%20are.) But ChatGPT’s arrival in late 2022 felt different in scale and immediacy. Suddenly, a powerful AI, capable of answering questions, writing code, brainstorming ideas, and more, was in the public’s hands. At this pace, the question is no longer whether sustained ChatGPT use makes us a little bit transhuman; **it’s whether the tool is now so deeply embedded in that threshold that it verges on pseudo-cyborg technology.** ## Defining Transhumanism To ground the discussion, let’s start with a clear definition of **transhumanism**. In simple terms, transhumanism is the concept of utilizing advanced technology to surpass the natural limitations of the human organism.[Transhumanism](https://nickbostrom.com/old/transhumanism) is described as a movement that advocates using current or emerging tech such as *genetic engineering, cryonics, AI, nanotech,* etc. In other words, transhumanists want to **transcend** the normal human state through science and tech, eventually maybe even becoming “[posthuman](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf)” beings with expanded capacities that an unenhanced human wouldn’t possess, thus enhancing human capabilities to improve the human well-being. Modern theorists in the transhumanist school of thought offer complementary definitions. Philosopher **Max More** who[https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf)helped formalize transhumanist thought in the 1990s, defined it as [“a class of philosophies that seek to guide us towards a posthuman condition”](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf). He emphasized that transhumanism shares humanism’s respect for reason and science but *“differs from humanism in recognizing and anticipating the radical alterations in the nature and possibilities of our lives”* resulting from advancing technologies. Along the same vein, former Oxford futurist **Nick Bostrom** explains that transhumanists see human nature as[“a work-in-progress, a half-baked beginning”](https://nickbostrom.com/ethics/values). We need not accept our current mental and physical limits as the endpoint of evolution. With *“the responsible use of science, technology, and other rational means,”* Bostrom says, transhumanists hope humans will *“eventually manage to become posthuman, beings with vastly greater capacities than present human beings have”.* Yet these **ambitions** have also drawn sharp criticism.[Skeptics argue](https://www.theguardian.com/technology/2024/apr/19/oxford-future-of-humanity-institute-closes) that the movement’s rhetoric can hide an elitist desire to engineer a “better” class of humans, stoking fears of selective biological enhancement and widening social divides. In his[2004](https://philosophy.as.uky.edu/sites/default/files/Transhumanism%20-%20Francis%20Fukuyama.pdf)*[Foreign Policy](https://philosophy.as.uky.edu/sites/default/files/Transhumanism%20-%20Francis%20Fukuyama.pdf)*[essay “Transhumanism,”](https://philosophy.as.uky.edu/sites/default/files/Transhumanism%20-%20Francis%20Fukuyama.pdf) Stanford political scientist and author [Francis Fukuyama](https://fukuyama.stanford.edu/) warns, “If we start transforming ourselves into something superior, what rights will these enhanced creatures claim, and what rights will they possess when compared to those left behind?” ![Transhumanist Values](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/e90ab6e22205.png) In short, transhumanism is about **deliberately using technology to overcome our biological limits, whether it longer lifespans, enhanced bodies, or sharper minds.** For the fiction nerds, picture the[Mentats in](https://dune.fandom.com/wiki/Mentat)*[Dune](https://dune.fandom.com/wiki/Mentat)*, those human “living computers” trained to perform the feats once handled by banned thinking machines. ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/00bec53a62ee.jpg) **ChatGPT and the advent of chatbots** At first glance, a chatbot on your computer or phone might not sound as dramatic as cyborg implants or designer genes. After all, ChatGPT doesn’t physically change your physiology rather it’s “just” a very smart tool. Yet the threshold between general tool and a true transhumanist enhancement isn’t always clear-cut. Transhumanism isn’t limited to **physical** upgrades. Enhancing **cognitive abilities** is equally central, and many prominent transhumanists actively pursue it. Just as we accept eyeglasses and prosthetic limbs as bodily augmentations, we can likewise regard an AI assistant as an augmentation for the mind. The key distinction is whether the tool merely offers *convenience* or if it genuinely expands what we can know or do as humans. A simple calculator, for example, is very useful but arguably just automates a narrow mental task. ChatGPT, by contrast, can **generate new ideas, text, and solutions.** Such cognitive interactions can converse, explain, and create in ways that feel like having a second brain on call. When a technology begins to so vastly amplify one’s intellectual output or understanding, it starts to cross into the transhumanist realm of qualitatively enhanced capability. ChatGPT, in essence, allows a person to tap into a vast web of knowledge and a reasoning engine adjacent to any individual’s mind. That is why some have described it as a form of *cognitive enhancement* available to the masses, an “over-the-counter” cognitive boost that doesn’t require a PhD or a billionaire budget to use. With the right user-driven guardrails in place such as prompt engineering, ChatGPT pushes beyond the ordinary tool threshold of transhumanism and emerges more as a cognitive steroid. ## The Extended Mind Long before AI chatbots, philosophers were already arguing that tools can become literal **extensions of our minds**.[In a famous 1998 paper titled](https://consc.net/papers/extended.html)*[“The Extended Mind,”](https://consc.net/papers/extended.html)* Andy Clark and David Chalmers proposed that objects like notebooks or computers, when used in the right way, are as much a part of one’s cognitive process as the neurons in one’s brain. They portray this with the case of *Otto*, an Alzheimer’s patient who relies on a notebook to remember important information. Otto is benchmarked against Inga, who uses her biological memory. When Inga wants to go to a museum, she recalls the address from memory. When Otto wants to do the same, he looks it up in his notebook. Clark and Chalmers argue that the notebook is a constant, trusted resource for Otto, serving the same role memory serves for Inga, and thus can be considered part of Otto's mind. As they put it, *"the notebook plays for Otto the same role that memory plays for Inga. The information in the notebook functions just like the information constituting an ordinary belief; it just happens that this information lies beyond the skin".* In Otto’s case, consulting his notebook isn’t fundamentally different from Inga consulting her brain since both are accessing stored information to guide their behavior. This example powerfully suggests that the **mind** is not limited to the brain. It can extend into the world via devices and tools, as long as they are integrated into our cognitive routines. The question then becomes: at what point does an external tool count as part of *you*? Philosophers have offered several criteria[https://philarchive.org/archive/RECTISv2](https://philarchive.org/archive/RECTISv2)sometimes called[the “glue and trust” conditions](https://philarchive.org/archive/RECTISv2) for when we should treat something like a notebook or by extension, an app or AI as an **extension of the mind.** - **Reliable Availability:** The tool must be reliably present and readily accessible whenever you need it . (Otto always carries his notebook everywhere he goes.) - **Ease of Use:** Information from the tool should be easy to retrieve *almost automatically*, without great effort or delay. (In practice, using the tool becomes second-nature, like recalling a memory.) - **Trust:** You *trust* the tool and accept its outputs as true, much like you trust your own memory. (Otto doesn’t doubt his notebook; if it says “MoMA is on 53rd Street,” he believes it, just as Inga believes her recollection.) - **Personal Integration (Prior Endorsement):** Ideally, the information in the system was placed there or vetted by you, or in some way, you’ve integrated it into your identity. (Otto wrote the notebook entries himself, so they reflect knowledge he *endorsed*.) ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/ed807ecc28c8.jpg) When these conditions are met, the boundary between “tool” and “mind” gets fuzzy. Clark and Chalmers explain that our everyday experience fullfills this. For example, a smartphone serves as a memory bank (with our notes, contacts, calendar), a navigation system, and even a “second brain” that we consult without a second thought. In fact, by 2011, even Chalmers[noted that his](https://philarchive.org/archive/RECTISv2)**[iPhone](https://philarchive.org/archive/RECTISv2)**[satisfied at least three of the four criteria](https://philarchive.org/archive/RECTISv2) for a mind-extension device in skilled users’ hands. For many of us, losing our phone or internet connection feels like losing a part of our mind which is the extended mind thesis in action. However, building an extended mind also comes with **trade-offs and caveats**. One obvious issue is that external tools can fail or be wrong. If any of the “glue and trust” conditions break down such as the device isn’t available, or you suddenly doubt its accuracy then the extension breaks down. For instance, *experienced* GPS users[learn not to solely trust their GPS in all cases](https://philarchive.org/archive/RECTISv2). They stay alert to correct it when it inevitably makes mistakes or loses signal. Only with skill and critical oversight can a GPS become a helpful extension of one’s navigational mind, rather than a mindless crutch. The same caution applies to AI assistants. Over-reliance on an external memory or skill[https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/](https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/)can lead to [cognitive atrophy](https://arxiv.org/pdf/2506.08872v1) where we might stop exercising our own memory or problem-solving abilities, becoming too dependent on the tool. Psychologists have observed this with[phenomena like the “Google effect”,](https://time.com/69626/who-needs-a-memory-when-we-have-google) where people are more likely to forget information that they know they can just look up online. In other words, when a tool is always at hand,[we offload mental work to it, which is great for efficiency, but might leave our natural abilities underdeveloped or prone to atrophy.](https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf) There’s also the risk of false confidence, if the tool *feels* like part of your mind ,you might accept its outputs uncritically as if they were your own thoughts. With something like ChatGPT, as we’ll discuss, this is a double-edged sword as it can deliver brilliant insights, but also confident-sounding nonsense also known[https://www.ibm.com/think/topics/ai-hallucinations](https://www.ibm.com/think/topics/ai-hallucinations)technically by AI researchers as[hallucinations.](https://www.ibm.com/think/topics/ai-hallucinations) An extended mind must therefore be built on *trust* and *verification*. We have to cultivate good “cognitive hygiene” and guardrails with our tools. It is important to know when to trust the AI and when to double-check, much as a good driver knows when to ignore a misleading GPS route. Abiding as a simple “left turn” could be deadly. The ideal is a balanced partnership where the external aid contributes knowledge or speed, and the human contributes oversight and contextual judgment. ## ChatGPT as a Cognitive Extension **Alas the king… ChatGPT**, the AI chatbot that launched in 2022, that is synonymous with the word AI itself. If any digital tool has the potential to act as a mind extension, ChatGPT is a prime candidate. It often satisfies the key conditions we listed. **Availability:** If you have an internet connection, ChatGPT or similar models built into apps and devices is available 24/7, ready to answer questions or generate ideas on demand. **Ease of use:** Absolutely, you just converse in plain language, and it responds within seconds. People have found it astonishingly easy to integrate ChatGPT into workflows by asking it to brainstorm topics, explain tricky concepts, draft emails, debug code, etc. **Trust:** This is where it gets sticky; we’ll address its pitfalls soon, but many users do report that after some experience, they develop a sense of when to trust the AI’s answers for example, on a familiar topic or coding task and when to be cautious like when it confidently states an obscure “fact” that could be wrong. ChatGPT is often described as “having a super knowledgeable friend always at hand,” which indicates a high level of trust in the tools guidance. **Personal integration:** Unlike Otto’s notebook, you didn’t personally write all of ChatGPT’s knowledge store – it comes pre-trained on vast swaths of the internet. However, you can *customize* the interaction by giving it your context, preferences, or writing style. Over time, the AI’s outputs might start to reflect your own way of thinking or the directions you nudge it toward, creating a kind of feedback loop between your mind and the AI. For example,[ChatGPT’s Latent Memory feature](https://openai.com/index/memory-and-new-controls-for-chatgpt/) makes that augmentation concrete. It quietly retains key details from past conversations, your projects, preferences, and stylistic quirks and uses them to shape future responses. As the model “gets to know” you, a slice of your working memory is effectively outsourced to the chat history, deepening the extended-mind partnership. In effect, when someone uses ChatGPT regularly, it can become a *personalized cognitive aide*, augmenting their natural abilities. Empirically, we are already seeing how AI tools boost human cognitive performance. A recent experiment at MIT had hundreds of professionals work on writing tasks (emails, reports, etc.), with half given access to ChatGPT and half working solo. Those with ChatGPT finished their tasks [40% faster, and their output was rated ~18% higher in quality](https://news.mit.edu/2023/study-finds-chatgpt-boosts-worker-productivity-writing-0714#:~:text=Access%20to%20the%20assistive%20chatbot%20ChatGPT%20decreased%20the%20time%20it%20took%20workers%20to%20complete%20the%20tasks%20by%2040%20percent%2C%20and%20output%20quality%2C%20as%20measured%20by%20independent%20evaluators%2C%20rose%20by%2018%20percent.). In other words, the AI made people both quicker and better at their work. Interestingly, it was the **weaker writers** who benefited the mos[t](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) as ChatGPT helped close the skill gap between people, acting as an equalizer. This suggests that AI isn’t just a fancy convenience but rather can fundamentally alter someone’s cognitive productivity. In creative domains, anecdotal evidence shows AI sparking new ideas. Writers use ChatGPT to overcome writer’s block or generate plot ideas. Coders use it to learn new programming techniques on the fly. Students (unfortunately) use it to get instant explanations of complex topics. In many cases, people report that these tools help them achieve results they *couldn’t* have achieved (at least not as easily) on their own. For example, a non-programmer building a simple app with ChatGPT’s help, or a novice writer producing a polished essay by iterating with the AI. All of this aligns with the notion that ChatGPT can act as a cognitive amplifier. It extends what we know, effectively giving an individual access to a composite of Wikipedia, a librarian, a tutor, and a creative partner all at once.[https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71](https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71)Little wonder that some have likened it to a[“bicycle for the mind”](https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71) (to borrow Steve Jobs’ old phrase for computers) except now the bicycle sometimes feels more like a jetpack. As AI copilots absorb the repetitive or low-level pieces of knowledge work, our top performers no longer rise by raw technical ability alone; they graduate from hands-on specialists to **orchestrators**. And in a world shifting from specialization to orchestration, these orchestrators hold the keys: they design the workflows, craft the prompts, select the data sources, and synchronize human talent with machine agents into a seamless whole unlocking outcomes no single expert could achieve in isolation. **The dawn of the orchestrator** ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/6e0b56fea122.jpg) ### Highway to the Danger Zone That said, we must also address the **drawbacks and dangers** of relying on such AI extensions. Perhaps the biggest issue with current generative AI is that it can be *too confident for its own good*. ChatGPT doesn’t actually “know” facts in the way we do. It predicts plausible answers based on patterns in data. This means it sometimes produces **fabrications that sound perfectly credible** what we call *“hallucinations” as described previously.* For example, ChatGPT might cite studies or laws that don’t exist, or assert health facts that are utterly wrong but *seem* right. These inaccuracies are so common that researchers have given them a nickname and are actively studying why they occur. If a user treats ChatGPT’s output as gospel, trusting it like an infallible memory, they can get into trouble. A now-infamous case involved[a lawyer who used ChatGPT to help write a legal brief, and the AI](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html)*[invented](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html)*[court cases to cite](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html). The lawyer, assuming the AI’s confidently presented citations were real, submitted the brief and later faced professional sanctions when the judge discovered those cases were nonexistent. In this cautionary tale we can takaway that powerful cognitive extension can **mislead you** if you don’t remain critically engaged. Over-trust in the AI can lead to mistakes, misinformation, or the erosion of one’s own expertise. This is why[many experts stress](https://www.edweek.org/technology/ai-literacy-explained/2023/05)**[AI literacy](https://www.edweek.org/technology/ai-literacy-explained/2023/05)**[and knowing the strengths and weaknesses](https://www.edweek.org/technology/ai-literacy-explained/2023/05) of tools like ChatGPT as a crucial skill for the future. Another consideration is how these tools fit into our broader cognitive habits. Do they complement our thinking or start to substitute for it? There’s a subtle but important difference between *complementary* and *competitive* cognitive aids. A **complementary** aid handles the tedious bits so that you can focus on higher-level thinking. For instance, using ChatGPT to perform basic data entry for you might free up time and mental energy for you to synthesize insights and make creative connections (things the AI might not do as well). In this mode, human and AI form a partnership where each does what it’s best at. By contrast, a **competitive** aid is one that essentially takes over a task that humans used to do, potentially sidelining the human role. If someone uses the AI in lieu of learning the basics or outsources all their creativity to an algorithm, they might be left with diminished skills and understanding. For example, if students lean on ChatGPT to do all their writing, they might never develop the ability to structure an argument themselves. The AI has “competed” with and supplanted their own cognitive growth. In the workplace, this distinction plays out as well: will AI assistants simply *assist* workers, or eventually *replace* those who don’t add unique value? Current evidence suggests that in many c[ases AI acts as a](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence)**[force multiplier](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence)**[for human talent](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) , but we can’t ignore the possibility that some jobs or skills will be rendered obsolete. Navigating this will require conscious effort and we should embrace the *complementary* uses of ChatGPT that let us achieve more, while guarding against *over-reliance* that leaves us complacent or deskilled. ## The Cyborg Question All this talk of human-machine coupling naturally leads to the image of the **cyborg.** The archetypal transhuman figure who is part human, part machine. So, does using ChatGPT make you a cyborg? The answer depends on how we define *cyborg*. Traditionally, the word means a *“cybernetic organism,”* implying a being with **technology integrated into its body or biology**. The term was originally coined in the 1960s to describe[a person whose bodily functions are aided by implanted devices or biochemical modifications](https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf) . Classic sci-fi cyborgs have robotic limbs, bionic eyes, brain implants, and so forth. By that strict definition, simply chatting with an AI on your phone doesn’t qualify. There’s no *physical* fusion of man and machine in the case of ChatGPT; the AI remains an external tool, not a literal part of your organic body. You could put your phone in a drawer and *poof* the “cyborg” abilities vanish, proving that you and the tool are separate entities. So, in the conventional sense, no, using ChatGPT does not make you a cyborg ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/ed4f6a47630e.jpg) . However, some theorists have argued for a broader conception of cyborg-hood that applies to everyday life. Notably, anthropologist[https://www.youtube.com/watch?v=z1KJAXM3xYA](https://www.youtube.com/watch?v=z1KJAXM3xYA)**[Amber Case](https://www.youtube.com/watch?v=z1KJAXM3xYA)**[argues that](https://www.youtube.com/watch?v=z1KJAXM3xYA)*[we are all cyborgs now](https://www.youtube.com/watch?v=z1KJAXM3xYA)* in as much as we rely on technology constantly to extend our capabilities. You might not have a chip in your brain, but if you rarely go anywhere without your smartphone (your external memory/communication device) and you use digital tools to mediate so many experiences, you are functionally a **cyborg**. Case points out that we use our phones and computers like “external brains” for communication and memory, effectively[becoming a “screen-staring, button-clicking new version of humans”](https://www.youtube.com/watch?v=z1KJAXM3xYA) . In this more metaphorical or sociological sense, *anyone using ChatGPT as a cognitive crutch is engaging in a cyborg-like merging* of human intellect with machine processing. The boundary between user and tool becomes porous during those moments of interaction. Think of how a person might say “I’ll ask my AI,” the way they’d say “I’ll think about it” – it hints that the AI has been incorporated into their cognitive loop. Some bioethicists and futurists use the term **“soft cyborg”** to describe people who, while not physically augmented, are so intertwined with their personal tech that it’s an extension of their self. By that view, millions of us became soft cyborgs the day we got smartphones, and tools like ChatGPT only deepen that intertwinement. Even so, **ChatGPT remains an external tool** unless we literally implant it or physically couple it to our bodies. It’s worth clarifying where the line would be crossed into true cyborg territory. If, for example, in a decade we have a[brain–computer interface (BCI)](https://neuralink.com/blog/building-safe-implantable-devices) that lets you query an AI with your thoughts and receive answers as instant flashes of neural input, that would pretty clearly qualify as being a cyborg. Companies[https://www.youtube.com/watch?v=Cf7rbQQBRlI](https://www.youtube.com/watch?v=Cf7rbQQBRlI)like[Neuralink are already working on high-bandwidth BCIs](https://www.youtube.com/watch?v=Cf7rbQQBRlI) that, in theory, could one day link human brains with AI systems. A less invasive route might be augmented reality glasses or contacts that overlay AI assistance onto your visual and auditory field at all times basically, an AI that’s always *in* your perception, not confined to an external screen. At that point, the AI starts to feel like part of your sensory system. ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/c74f36ea4565.jpg) We can also imagine AI-driven neural prosthetics or implants that aids memory, or a language chip that provides real-time translation of foreign languages in your head. Those blur the line between user and device in a much more intimate way than a chatbot app does. ChatGPT, as amazing as it is, still lives in the cloud, you have to physically query it, and there’s a clear boundary (the interface, the screen) where information passes from machine to you. In cyborg terms, it’s **one step short** of full robocop. So, calling ChatGPT users full “cyborgs” is mostly a playful metaphor hinting at the near future. A true cyborg enhancement becomes a *part of you* even when you’re not consciously thinking about it. One might argue like a pacemaker that keeps your heart rhythm steady, or a cochlear implant that continuously provides hearing. ![](https://shoal.xyz/research/writing/ai-and-cognitive-over-the-counter/img/e4fe273ff0c7.jpg) In summary, using AI like ChatGPT moves us toward a cyborg-like existence in a philosophical sense, but it doesn’t make us cyborgs in the **literal**, physical sense. For that next leap, we’d need tighter integration at the physical level, at the current phase reliably consulting AI still largely requires skill. ## The Haves and the Have-Nots: Access and Inequity in AI If ChatGPT represents a sort of mass-market, over-the-counter cognitive enhancement, we should ask: **Who gets to benefit from it?** Historically, one concern in transhumanist technologies is that they might create a divide between the “enhanced” and “unenhanced”. For example, only the rich affording life-extending tech or brain boosts. With ChatGPT, the *financial* barrier is actually relatively low as the basic version has been offered free, but that doesn’t mean access is truly equal. First, there’s the straightforward **digital divide**: not everyone has a reliable internet connection or a modern device to use AI on. Billions of people still lack broadband access, and even within wealthy countries, underserved and rural communities may struggle with connectivity. *Hardware* and *infrastructure* are the baseline requirements for entry into this augmented world. However, as observers note, a new divide is emerging that goes beyond just owning the tech – it’s about **knowing how to use it effectively**. Some have started calling this the **AI literacy gap**, akin to digital literacy but focused on understanding and working with AI. In other words, two people might both have internet access, but if one knows how to craft good prompts, interpret the AI’s output, and integrate it into their tasks, while the other is intimidated or unskilled with the AI, the first person will gain a significant advantage. We’re already seeing this in educational settings and workplaces. Students with strong guidance on using AI can produce better projects and learn faster, whereas those left unguided might either misuse the tool (e.g. simply plagiarize answers they don’t understand) or avoid it altogether out of fear. Similarly, a professional who adapts quickly to using AI tools may outshine colleagues who stick to older methods. This raises the concern that[AI could exacerbate existing skill and socioeconomic gaps](https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf). Those who are *digitally privileged* having not just access but also the savvy to use technology can surge further ahead, while others lag behind. ### Model Access Another subtle access issue is the difference between the *free* versions of AI and the most *advanced* versions. For instance, OpenAI offers a paid subscription to ChatGPT Plus (with access to more powerful models like GPT-4). Organizations and individuals who can pay for premium AI **will** get significantly better results, more accurate, less hallucination-prone, with advanced features compared to those using only the free model. Over time, if cutting-edge AI remains behind paywalls, we could see a situation where wealthier users effectively have a “stronger cognitive enhancement” than others. This is not unlike healthcare disparities, except here it’s an intelligence tool. It’s easy to imagine a future where businesses invest in top-tier AI for their employees, training them in its use, and thereby dramatically increasing their output, while smaller firms or workers without such resources fall behind. However, as a hedge, [open source models like deepseek](https://techcrunch.com/2025/05/09/deepseek-everything-you-need-to-know-about-the-ai-chatbot-app/) have done the unthinkable with launching free models which could be run locally on a person's own computer. Though, enterprise grade hardware is required to run these full models to even spit out a simple question. So, how do we address these gaps? **AI literacy education** is one key. Just as basic computer literacy became essential over the past few decades, knowing how to interact with AI should become a widely taught skill. This includes understanding AI’s limitations and ethical considerations, not just technical know-how. Initiatives are already calling for[integrating AI training in schools and community programs.](https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers) For example, learning how to fact-check AI or use it to *assist* (not replace) one’s learning could be built into the curriculum. Public libraries and online courses can play a role in democratizing knowledge about AI tools, so it’s not confined to tech specialists or elite institutions. Policymakers and organizations like UNESCO have begun discussing “AI literacy as a human right” in the digital age, emphasizing that without proactive measures, AI could deepen inequality rather than alleviate it. On the infrastructure side, continuing to expand internet access is obviously crucial as every new person brought online is a potential new beneficiary of tools like ChatGPT. There’s also a case to be made for **public interest AI**: ensuring that advanced AI models are available in forms that the public and underprivileged communities can access perhaps via open-source models or government-provided AI services, rather than having all the best AI locked behind corporate gates. In summary, ChatGPT offers a glimpse of a future where cognitive augmentation is widespread, but making that future equitable requires conscious effort. Otherwise, we risk a scenario where *some* minds get much “bigger” with AI help, while others are left behind in the pre-AI paradigm, widening the gulf in opportunity. The notion of transhumanism often dwells on individual enhancement, but we have to broaden that: true progress will be if these enhancements uplift as many people as possible, not just a tech-savvy few. ## Conclusion: A Mind in the Making We stand at a peculiar moment in human history. The tools we've created to extend our minds have become so powerful that they force us to reconsider what it means to be human in the first place. ChatGPT isn't just another productivity app; it's a mirror that reflects our evolving relationship with intelligence itself. The central tension this essay has explored is not whether ChatGPT makes us transhuman (by most definitions, it doesn't), but rather what it reveals about the porous boundary between tool use and cognitive enhancement. When a technology integrates so seamlessly into our thinking processes that we struggle to separate our thoughts from its suggestions, we've crossed a threshold that demands new frameworks for understanding human capability. Three critical tensions emerge from this analysis: First, the **enhancement paradox**: ChatGPT simultaneously amplifies our abilities and threatens to atrophy them. We become more capable while risking dependence. The solution isn't to reject these tools but to develop new forms of cognitive hygiene: practices that maintain our intellectual muscle tone even as we delegate routine mental labor to AI. Second, the **equity challenge**: Cognitive enhancement through AI could either democratize intelligence or create new hierarchies of the augmented versus unaugmented. The determining factor won't be the technology itself but how we structure access to it and, more importantly, education about its effective use. AI literacy may become as fundamental as traditional literacy, yet we're barely beginning to understand what that means. Third, the **agency question**: As we transition from specialists to orchestrators, we must guard against becoming mere operators of intelligent systems. True agency in the age of AI means maintaining the ability to think independently, to question AI outputs, and to synthesize insights in uniquely human ways. We must be conductors, not just audience members, in the cognitive symphony. Perhaps the most profound insight is that we've been augmenting ourselves all along: through writing, mathematics, computers, and smartphones. ChatGPT simply makes this augmentation impossible to ignore. It strips away the comfortable fiction that our tools are separate from our thinking and forces us to confront what we've always been: tool-using animals whose intelligence is distributed across our technologies. The question isn't whether to embrace or resist this augmented future. It's already here. The question is how to shape it consciously. We need new ethical frameworks that account for distributed cognition, educational systems that teach orchestration alongside traditional skills, and a renewed commitment to human agency even as our tools grow more powerful. In the end, ChatGPT offers us a preview of a future where the boundaries between human and artificial intelligence blur not through physical merger but through cognitive partnership. How we navigate this partnership with wisdom, equity, and intentionality will determine whether these tools amplify our humanity or diminish it. The choice, as always, remains ours. ### References Bajarin, T. (2014, April 21). *Who needs a memory when we have Google?* *Time.*[https://time.com/69626/who-needs-a-memory-when-we-have-google](https://time.com/69626/who-needs-a-memory-when-we-have-google) Bostrom, N. (1998). *A history of transhumanist thought.*[https://nickbostrom.com/old/transhumanism](https://nickbostrom.com/old/transhumanism) Bostrom, N. (2005). *Transhumanist values.* *Ethical Issues for the Twenty-First Century*, 3–14. https://nickbostrom.com/ethics/values.pdf Brynjolfsson, E. (2022). *The Turing trap: The promise & peril of human-like artificial intelligence.* *Daedalus, 151*(2), 120–146.[https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf](https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf) Clark, A., & Chalmers, D. J. (1998). The extended mind. *Analysis, 58*(1), 7–19.[https://www.consc.net/papers/extended.html](https://www.consc.net/papers/extended.html) Clynes, M. E., & Kline, N. S. (1960, September). Cyborgs and space. *Astronautics*, 26–27.[https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf](https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf) Education Week. (2023, May 17). *AI literacy, explained.*[https://www.edweek.org/technology/ai-literacy-explained/2023/05](https://www.edweek.org/technology/ai-literacy-explained/2023/05) Ghanem, K. (2025, May 9). *Instagram face & BBL baddies—Welcome to the first wave of transhumanism.* *Mille World.*[https://www.milleworld.com/instagram-face-bbl-baddies-welcome-to-the-first-wave-of-transhumanism/](https://www.milleworld.com/instagram-face-bbl-baddies-welcome-to-the-first-wave-of-transhumanism/) Hauser, C. (2023, May 27). *Avianca lawsuit shows perils of citing A.I.-generated cases.* *The New York Times.*[https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html) IBM. (2023, September 1). *What are AI hallucinations?*[https://www.ibm.com/think/topics/ai-hallucinations](https://www.ibm.com/think/topics/ai-hallucinations) Maiberg, E. (2025, February 10). Microsoft study finds AI makes human cognition “atrophied and unprepared.” *404 Media.*[https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/](https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/) Mentat. (n.d.). In *Dune Wiki.* Fandom. Retrieved May 26, 2025, from[https://dune.fandom.com/wiki/Mentat](https://dune.fandom.com/wiki/Mentat) More, M. (1990). *Transhumanism: Towards a futurist philosophy* [White paper].[https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf) Noy, S., & Zhang, W. (2023, June 7). *The productivity effects of generative artificial intelligence.* *VoxEU/CEPR.*[https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) OpenAI. (2024, February 13). *Memory and new controls for ChatGPT.*[https://openai.com/index/memory-and-new-controls-for-chatgpt/](https://openai.com/index/memory-and-new-controls-for-chatgpt/) PhilPapers. (n.d.). *Transhumanism.* In *PhilPapers.* Retrieved May 26, 2025, from[https://philpapers.org/browse/transhumanism](https://philpapers.org/browse/transhumanism) Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. *Science, 333*(6043), 776–778.[https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf](https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf) UNESCO. 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YouTube. --- # Raiku: Solana’s High-Performance Edge Compute Layer > Explore how Raiku brings deterministic execution to Solana, enabling applications to run with precision, reliability, and speed. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-07-21 - Canonical: https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/ - Keywords: crypto, DeFi, solvers, MEV, restaking, security, infrastructure, Solana, Ethereum, Infrastructure ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/7e700df66f72.jpg) Modern blockchains have achieved scale, but not certainty. While Solana leads on throughput and latency, it still lacks reliable execution guarantees for high-stakes applications. Raiku introduces a programmable coordination layer that restores determinism, predictability, and trust to onchain systems without compromising performance. Built as a sidecar to Solana’s validator network, Raiku enables developers to reserve blockspace ahead of time, schedule transactions precisely, and avoid all the mempool chaos. This paper explores how Raiku brings execution guarantees, MEV resistance, and pre-confirmation to Solana’s monolithic architecture, offering a system built not just for speed but for reliability in a distributed, adversarial world. ## The State of Blockchain Architecture and the Need for Execution Certainty Global markets demand certainty. Crypto, too often, offers only hope. Today’s blockchain infrastructure is riddled with architectural compromises. In the pursuit of scale, we've built systems that violate core distributed computing principles, assuming infinite bandwidth, ignoring latency ceilings, and forcing universal state models on applications that don’t need them. The result? Fragile abstractions, unreliable performance, and a developer experience that feels more like survival than innovation. Imagine launching a modern financial product and being told your transaction might fail, unless you spam it, bribe the validator, or just pray for inclusion. Blockchain systems are ultimately supposed to abstract that complexity, offering decentralized infrastructure that "just works." But instead, we’ve traded server racks for validator nodes, and latency issues have simply moved from physical hardware to Layer-1 congestion. This is the daily reality in Web3. Ethereum, the most widely used smart contract platform, handles just 15–30 transactions per second. During high demand NFT drops, liquidations, memecoin seasons, the base layer clogs, fees spike, and L2s are the only escape hatch. These Layer-2 rollups offer massive throughout with reduced gas fees by shifting execution off-chain, but bring new tradeoffs: fragmented liquidity, complex bridging, divergent trust models, and a somewhat fractured user experience. ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/dc2e320eee52.jpg) Meanwhile, Ethereum’s restaking ecosystem introduces even more fragility. Protocols like EigenLayer ask validators to secure third-party systems with Ethereum’s social consensus, effectively betting that if anything breaks, the community will coordinate a bailout. [Even Vitalik has flagged](https://blockworks.co/news/dont-overuse-social-consensus-vitalik-warns) this approach as dangerously “high-risk.” Scaling Ethereum is still a 10-year roadmap. Builders need something now. Solana, on the other hand, pursued a high-performance monolithic design: it keeps consensus and execution in one chain, enabling very fast block times and parallel execution. In practice Solana regularly processes 3,000–4,000 TPS on a global state machine, far outpacing Ethereum’s throughput. This design yields low fees and near-instant finality under normal conditions. However, Solana’s single-chain architecture has also shown stress under extreme load. During periods of surging usage, Solana has experienced congestion and even outages, as every dApp competes for the same global resources. For example, a dramatic increase in traffic (e.g. a popular NFT mint or arbitrage bots) historically led to stalled blocks and transaction failures. Notably, in Feb 2024 a bug triggered by Solana’s runtime caused a [nearly five-hour network halt](https://cointelegraph.com/learn/articles/solana-vs-ethereum-blockchain-comparison). Even when the network stays up, users and bots often see transactions fail or time out during peak demand, undermining Solana’s otherwise strong user experience. In fact, high-frequency traders on Solana have observed [failure rates up to 75%](https://cointelegraph.com/news/solana-struggling-record-seventy-five-percent-trasnactions-fail-memecoin-mania)for transactions when the network is congested. This happens because Solana’s leader schedule and QoS (quality-of-service) prioritization favor certain validators, and when too many transactions flood in, many simply never get included in time. Beyond throughput limits, both ecosystems struggle with MEV exploitation and unpredictable execution. Solana, despite using a public leader schedule, faces its own MEV dynamics. Solana’s stake-weighted transaction scheduling means large validators or order flow specialists can cut deals to prioritize certain transactions off-book. This lack of transparency leads to centralization concerns, where well-connected bots or firms get *fast-lane access* while regular users’ transactions struggle. Although Solana has introduced priority fees and solutions like [Jito (a specialized MEV-aware client)](https://www.shoal.gg/p/jito-restaking-strategies) to bring more open fee markets, the underlying issue remains: when the network is busy, inclusion becomes a bidding war or insiders’ game, and ordinary users face uncertainty and slippage. On the state side, Ethereum’s rollup-centric model fragments applications across chains. Each rollup becomes a silo, requiring bridges, redundant tooling, and extra security assumptions. Composability, the magic of DeFi, dissolves when liquidity and contracts are no longer co-located. **What’s missing is scale without latency spikes, state fragmentation, or failed trades. The precision global finance requires but blockchains still lack.** This is the design space Raiku occupies. Born from years of Ethereum infrastructure frustration and a deep respect for clean system design, Raiku introduces a new class of infrastructure to Solana, one built not around more rollups, but around precision execution. It extends Solana’s core by offering programmable building blocks—*Edge Compute environments*—that give applications their own fast lanes, guaranteed bandwidth, and deterministic settlement without managing a separate chain or breaking composability. **If Solana is the global highway, think of Raiku as the intelligent traffic control system, enabling express lanes for the applications that need them most.** This isn’t another rollup. It’s not a sidechain. Raiku is a rethinking of blockchain execution: fast, modular, programmable, and predictable. A system forged not to chase trends, but to meet the demands of institutions, builders, and global-scale applications that need certainty, not hope. ## From Limitations to Vision: The Genesis of Raiku Raiku was born from a simple observation: not all blockchain workloads need to run in the same crowded kitchen. [In late 2023](https://x.com/raikucom/status/1908912087511990649), a team of researchers and Solana veterans began asking how they could offload heavy computations from Solana’s L1 without losing the benefits of being on-chain. This initiative started as a research project ([supported by Superteam and the Solana Foundation](https://x.com/raikucom/status/1909625101462483179)) out of frustration with the “stagnation” they perceived in Ethereum-centric infrastructure. Ethereum’s ecosystem, while rich in Layer-2s, hadn’t delivered the kind of leap in performance or developer experience these researchers hoped for, rollups were making incremental progress but still tied to a *relatively*slow and congested base layer. By contrast, Solana represented a chance to try something different: its L1 was already fast and proved that a web-scale blockchain was possible, yet it too could improve by evolving its architecture. Raiku team noted that by January 2024, many Solana applications were “naturally gravitating” toward an extensions architecture, or, in other words, projects were attempting to build their own mini-rollups or isolated execution layers to scale the base layer throughput even further. Lacking an official framework, some teams tried repurposing tools like the Sovereign SDK (meant for standalone chains) to create Solana extensions or *arguably* “rollups”. The results were suboptimal: misusing an Ethereum-oriented rollup framework on Solana led to poor performance and lots of friction. Every project rolling their own extension would cause state fragmentation (“basically moving towards all the problems that Ethereum has) and duplicated effort. More importantly, these DIY solutions *did not integrate cleanly* with Solana’s design, they ran into data throughput limits, timing issues, and inability to share state or accounts with L1. This pattern highlighted a clear design problem: *Solana needed a purpose-built extension framework*, not one shoehorned from elsewhere. Raiku’s founding team, led by [Robin A. Nordnes](https://x.com/degenroot) and others, set out to solve this by building an “edge compute” layer tightly coupled to Solana from first principles. They chose Solana after surveying other new L1s like Aptos and Sui, concluding that Solana was uniquely positioned to support their vision. Solana had a critical mass of users, a strong developer community, and fundamentally sound architecture (often likened to an early, rapidly improving Ethereum). Importantly, Solana’s leadership and ecosystem were willing to innovate, core developers shipped updates every couple of weeks, and there was appetite for new approaches to scaling. The idea was *not* to launch yet another independent L1, nor to create a completely separate shard, but rather to extend Solana in a complementary way. As one team member put it, “We’re not an L2, we’re not an L1... we’re somewhere in between.” More formally, Raiku positions itself as the block building architecture, an infrastructure protocol that connects validators, applications, and the base chain to orchestrate high-performance execution beyond what the base layer alone can provide. If Solana L1 is the highway, Raiku builds the express lanes and traffic control system that allow certain applications to operate with significantly greater speed and predictability when required. A key insight driving Raiku’s design is that many high-scale dApps do not require constant interaction with the entire global state. Some applications can run largely isolated (their own orderbook or game engine logic) as long as they can occasionally settle to the main chain and leverage its security and liquidity when needed. As Nordnes explained, “most use cases with large-scale potential do not require state composability at all times”. You can sandbox an application’s execution in its own zone (like an L2), but still get the benefits of the base chain for things like settlement finality, shared user accounts, on-chain price data, and asset security. This realization underpins Raiku’s architecture: it seeks to give applications their own sovereign execution environments (so they aren’t bottlenecked by others) while maintaining the advantages of Solana’s L1 (one unified asset and identity space, and a high-performance settlement layer). In the Ethereum world, one could try to achieve something similar by launching an optimistic or ZK rollup, but as the team noted, *“you can build as an L2 in Ethereum, but you’re still severely restricted by the underlying L1”*. Even the best rollup will be limited by Ethereum’s data posting throughput, latency, and upgrade timeline (“fixing the L1 is going to take a decade”). Instead of waiting on that, the Raiku team saw an opportunity to leverage Solana’s strengths *today* and innovate on top of them. Raiku would introduce a new layer running alongside Solana’s consensus, operated by (and economically aligned with) the validator community, to coordinate advanced execution features. The vision was bold: make on-chain apps “faster, more reliable, and market-competitive” with Web2 and TradFi systems like AWS or NASDAQ, all without compromising decentralization. [By early 2024, this vision gained traction](https://x.com/Austin_Federa/status/1830570709900493293). The concept of **Solana “extensions”** became a hot topic, and the community settled on that term (or “network extensions”) instead of “L2s” to emphasize adding to L1 rather than forking away. Raiku emerged as one of the leading projects implementing this concept. Technically, an extension is similar to a rollup or sidechain, and it’s stigmatized and perhaps downplays what the Raiku team is building. Raiku embraced the term “Edge Compute” to describe its execution zones. The phrase “edge compute” is borrowed from traditional IT (where it means computation done at the edge of the network, closer to where it’s needed). Raiku’s edge compute environments aren’t separate blockchains in competition with Solana, instead, they are modular execution zones at the edge of the Solana network, purpose-built to handle specialized workloads with deterministic performance. It’s a term that resonates with Web2 infrastructure teams and institutional players, bridging the conceptual gap between “rollups” and the familiar idea of edge servers. In essence, Raiku provides custom rollup-like environments (“extensions”) integrated as Solana edge compute zones. This gives developers execution sovereignty, i.e. freedom to run their own logic and scheduling, without the headache of launching an entirely new chain or fragmenting users across ecosystems. ## Redefining Rollups: From “Extensions” to “Edge Compute Environments” It’s worth highlighting how Raiku is reshaping the landscape around custom execution environments. In Solana circles, the term **“extensions”** emerged to describe these Solana-tailored rollups. However, the Raiku team felt that term was a bit narrow (and even “stigmatized” by early rough attempts). To capture the imagination of both crypto and traditional web2 audiences, what Raiku is building is more than just extensions, they’re building **“Edge Compute environments”**. ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/f8ccbdd7ffb2.jpg) *Source: [https://x.com/owocki/status/1830621049190560061](https://x.com/owocki/status/1830621049190560061)* With Raiku’s Edge Compute environments, we’re no longer thinking of a Layer-2 as an external add-on that lives on top of L1, but rather an integral part of the network’s architecture, an extension *of* L1 that lives at the network’s edge, close to the users and applications. By calling them “modular execution zones”, Raiku emphasizes that you can plug in different modules (each module being an execution runtime/VM) to one coherent system. These modular execution zones allow developers to plug different execution runtimes or custom virtual machines into one cohesive system, empowering them to shape low-level application logic with unparalleled control. The Raiku team believes that performance at scale isn't patched in, it's built in from the outset. Raiku begins precisely where others stop: at the physical boundaries of bandwidth, geography, and time constraints inherent to distributed networks. Specifically, Raiku delivers: - **System reliability** that maintains robust operation even under extreme load and pressure. - **Deterministic execution** guaranteeing predictable outcomes for every transaction. - **Low latency** by placing high-performance edge computing (HPEC) capabilities directly at the edges of the Solana network, enabling transaction processing within milliseconds. - **Developer freedom** to customize low-level logic, providing unmatched flexibility and control. Raiku’s Coordination Engine orchestrates transactions with precision, ensuring they are sent, scheduled, and confirmed swiftly, supported by a sophisticated ahead-of-time blockspace marketplace that guarantees inclusion (more on this in the later sections). Validator Plugins power both ahead-of-time (AOT) and just-in-time (JIT) execution. Combined with proof streaming, these plugins allow for instant pre-confirmation of transactions, turning today’s unreliable, best-effort interactions into dependable and scheduled execution. Edge compute environments have practical implications. It helps differentiate Solana’s approach from Ethereum’s in the narrative: Ethereum has “Layer-2 rollups”, Solana (via Raiku) has “Edge Computes”. The latter suggests enhancement rather than separateness. It is a term that traditional finance will understand. In enterprise computing, edge compute is a positive concept, it implies faster response by moving compute closer to where it is needed. Raiku is effectively saying: we move execution closer to the app (in a logical sense) while still being anchored to the main network. So, in this report we’ve consistently used “edge compute environments”, “extensions”, and “modular execution zones” somewhat interchangeably, to reflect how Raiku’s idea might be referred to. Going forward, as Raiku hits mainnet and more marketing, you’ll likely see “Raiku Edge Compute” as a branded term, much like how Polkadot has “parachains” or Avalanche “subnets”. This terminology also makes it easier to convey new capabilities: for example, Raiku can say “deploy your own edge compute environment on Solana in one week”, which sounds like setting up a cloud environment, thus familiar to developers. By emphasizing “edge compute”, Raiku aligns itself with the broader trend in web infrastructure where logic is moving closer to the user (edge networks, CDNs, etc.) for speed, except here the “user” is the application transaction, and the edge is a special zone in the network. It’s a powerful analogy that could help more people grasp how Raiku differs from just another scaling hack. ## Raiku’s design is guided by a few key principles: ### Not all dApps need continuous global state: Some of the highest throughput applications (exchanges, games, payment networks) can operate in siloed environments for most of their activity, tapping the main chain only when needed. Raiku embraces this by providing opt-in isolation, freeing those apps from the global mempool competition, while still giving them access to L1 liquidity/state when necessary. This stands in contrast to the Ethereum DeFi ethos where everything is highly interwoven on one chain (which is powerful but doesn’t scale when every minor app demands global atomic composability). By recognizing that temporal or contextual composability (only when needed) is enough for many cases, Raiku achieves massive performance gains. ### Keep the one-network feel: Despite introducing modular zones, Raiku strives to avoid the multi-chain UX headaches. The global accounts and orchestration engine ensure that from a user’s perspective, Solana remains one network. You don’t need to manage multiple tokens for gas on different chains/ zones or switch RPC endpoints manually. You interact with Solana, and under the hood Raiku may route your transaction to an extension or the main chain as appropriate. This is a stark difference from, say, the Cosmos app-chain model or even Ethereum’s L2 landscape, where using a new chain means new tokens, new block explorers, and a mental shift. Raiku’s edge compute zones are much like “network extensions” rather than independent networks, signaling that they extend Solana rather than compete with it. The architectural advantage here is network effects preservation: SOL token’s utility still underpins the whole (fees, staking), and Solana’s community isn’t split among dozens of mini-chains. This addresses a common critique of Ethereum’s rollup-centric roadmap, that Ethereum might become just a settlement layer while user activity migrates to various L2 tokens and ecosystems, potentially diluting Ethereum’s economic security. Raiku’s approach adds capacity and keeps it under the Solana economic umbrella. ### Leverage existing security, don’t reinvent it: Raiku does not create a new base consensus mechanism or require users to trust a brand new validator set with their funds (in fact, Raiku won’t custody funds separately, assets remain on Solana). This is a major advantage over launching a sovereign appchain or a new L1. If a project today chooses to start its own chain (whether via Cosmos SDK, Avalanche subnet, or some sovereign rollup), it faces the monumental task of bootstrapping validators, incentivizing them (often via inflationary new token rewards), and securing bridges back to other ecosystems. Raiku shortcuts this by building on Solana’s validator community and bridging natively via global accounts. There’s no separate bridge contract, the extension is logically part of Solana. This dramatically lowers the security risk and development overhead compared to sovereign chain approaches. For example, teams who tried Sovereign SDK on Solana ended up with state fragmentation and poor performance because Sovereign SDK wasn’t made for Solana’s context. Raiku’s custom solution avoids those pitfalls and maximizes reuse of Solana’s battle-tested components (like its networking, validator incentives, etc.). ### Predictability and transparency as core features: Both builders and users value knowing what will happen. Raiku bakes predictability at the protocol level. Inclusion signals remove the guesswork from transaction submission. MEV is handled by design (no private mempools, everything goes through auctions or known channels. This fosters a healthier ecosystem. On Ethereum, despite improvements, users still fear being sniped by an arbitrage bot the moment they send a Uniswap trade. On Solana, users fear transactions “not going through” when the network is busy. Raiku wants to eliminate those fears, making the blockchain feel reliable and “boring” in the best way, like AWS infrastructure where if you schedule a job, you trust it runs on time. This is a key selling point for institutional adoption (who require SLAs and predictability) and for broad consumer use (no one wants to spam “Submit” hoping one transaction sticks). ## Real-World Use Cases Enabled by Raiku’s Edge Compute Design What can developers actually do with Raiku that they *couldn’t* before? The answer: build on-chain applications with the **speed and guarantees of off-chain systems**, and deploy new types of services on Solana that previously might have required a separate chain or centralized solution. Let’s explore a few illustrative use cases that Raiku’s team and community have envisioned, highlighting how the edge compute approach makes a difference: ### High-Frequency Trading and Exchanges (Drift Protocol’s Swift as an example): Drift is a leading Solana-based perpetuals exchange that processes large volumes of trades. In early 2025 they introduced [Swift Protocol](https://www.drift.trade/updates/introducing-swift-protocol-a-new-trading-standard-for-solana#:~:text=Drift%20introduces%20Swift%20Protocol%20%E2%80%94,maintaining%20Solana%E2%80%99s%20security%20and%20decentralization), an **on-chain** ultra-low-latency matching engine built directly on Solana. It keeps the order book and matching logic on-chain, then routes filled trades to Drift’s perpetuals program for settlement. While innovative, Swift still faces a limitation: when it comes time to settle those matched trades on Solana L1, it’s subject to the usual network conditions and could experience delays or contention (especially during volatile market moves when many exchanges are active). Enter Raiku: a Drift-like DEX could deploy an edge compute extension specifically for its trading engine. In this extension, orders could be matched and immediately finalized on-chain (in the extension) with microsecond precision, far faster than even Solana’s 400ms block time. The extension could use Light SVM optimized for trading, enabling thousands of operations per second (e.g. matching bids and asks, updating trader positions) with deterministic timing. Crucially, using Raiku’s guaranteed inclusion, once a trade is matched, it can be scheduled to settle on the next Solana block with zero uncertainty. No more racing the clock or praying your transaction gets in, the trade settlement is reserved and confirmed ahead of time. This means Drift could offer **execution guarantees akin to NASDAQ**, something unheard of in DeFi. Swift Protocol currently can’t guarantee exactly *when* a Solana settlement lands or that it won’t be front-run. With Raiku, they can guarantee inclusion and timing, solving that problem. In effect, Raiku could turn a decentralized exchange into a low-latency trading platform where market makers and arbitrageurs can operate on-chain with confidence. Beyond Drift, any exchange or AMM could benefit, imagine an on-chain order book that updates prices every 100ms in a dedicated extension without bogging down the mainnet. Raiku’s design even supports HFT (high-frequency trading) strategies: as stated on their website, you could execute “thousands of cross-exchange trades per second with microsecond precision and guaranteed settlement timing,” giving quantitative traders an institutional-grade DeFi infrastructure. This is exactly the kind of performance unlock that could bring serious trading firms into DeFi, when they no longer have to worry about network jitter or unpredictable failure rates. ### Payments and Fintech Infrastructure (e.g. “Stripe-like” payments, Squads): Payment applications demand both high throughput and high reliability. Consider a scenario like Stripe on Solana, a service handling thousands of transactions per second for merchants, payroll, micropayments, etc. On Solana L1, this is possible in theory (given the high TPS), but in practice if the network gets congested or if a program in one payment workflow eats too many compute units, others might fail. With Raiku, one could create a payments extension, essentially a specialized (edge compute) zone for payment transactions. This extension could be optimized for simple token transfers, including specialised/optimised environments or Light SVM for maximum efficiency. Through Raiku’s bandwidth reservation, a payment operator (like a stablecoin issuer or a CBDC platform) could reserve throughput for, say, 500 tps continuously to ensure their transactions always go through regardless of external demand. Users sending funds would get instant inclusion confirmation (no stuck transactions). For enterprise or institutional use, Raiku can enable private settlement networks on Solana: “private settlement channels between major financial institutions with deterministic finality and encrypted flows”. Think of big banks settling FX trades or securities on a shared Solana extension, they could have their own Raiku extension with transactions visible only to the parties (via encryption, yet still verifiable) and guaranteed finality. This unlocks use cases like cross-border payments, remittances, or inter-bank settlements on a public chain, but with the predictability of SWIFT or FedWire. On the consumer side, something like [SquadX](https://squads.so/blog/squadsx-multisig-extension-wallet-solana) (a popular Solana multisig and coordination tool) could use Raiku to guarantee that multi-signature transactions (which might involve many instructions) execute reliably even during peak network times. A major pain point for DAO treasuries or multi-sigs is when you try to execute a complex transaction and it fails due to network issues, Raiku could eliminate that by allocating a dedicated slot when all signers have approved, so the multi-sig transaction goes through atomically. Essentially, Raiku can provide institutional-grade reliability for any critical transaction flow, “five nines” of success rate, as they say in cloud, which is vital if blockchain is to be trusted for payments at scale. Moreover, with RFQ-style liquidity integration, Raiku could empower new payment models: for instance, a decentralized payment app could query market makers via Raiku’s RFQ system to get the best conversion rate for a currency swap as part of a payment, all settled within one extension with no slippage or MEV. This is analogous to how Stripe routes payments through various banks to optimize fees and success, Raiku could let crypto payments route through various liquidity sources in a controlled, deterministic manner. ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/188663fa9e14.png) ### DeFi Protocols and Services (beyond trading): Beyond exchanges, many DeFi protocols can benefit from Raiku’s edge compute environments. Lending platforms could use them to perform instant liquidations via dedicated channels (Raiku even enables “automated risk management with microsecond precision”,meaning a lending protocol could monitor positions and execute liquidation transactions in a guaranteed time window, reducing bad debt). Options and derivatives platforms could coordinate complex multi-leg strategies across venues by using an edge compute zone as a co-ordination hub, with Raiku guaranteeing all legs execute atomically in consecutive slots. For instance, an options DEX could ensure that when a user rolls over a position (closing one option and opening another), both transactions happen back-to-back with no gap for price movement. This level of control is currently only feasible in centralized systems. Stablecoin issuers could benefit as well: imagine USDC could use a Raiku extension to manage its mint/redeem flows in large batches with priority, ensuring big redemptions don’t clog the network or get front-run. By allocating blockspace, they maintain smooth operation even in stress times. ### Hybrid CEX/DEX and Institutional Access: Raiku could blur the line between centralized exchanges and DeFi. Its architecture allows something like a “regulated DeFi zone” where only KYC’d entities (say institutions) participate, enabling compliance while still settling on Solana. The site hints at “hybrid CEX/DEX exchanges with superior UX”, a scenario where a central venue (or consortium) provides liquidity but trades settle on a public network extension. With edge compute, such a platform could offer the speed of a CEX (matching engine on dedicated hardware) and the transparency and custody benefits of DeFi (settlement on Solana). Institutions could use this to trade on DeFi markets without dealing with retail traffic or uncertain fees, since they might have their own extension or guaranteed lanes. Over time, this could attract significant volume from traditional finance into the Solana ecosystem, as Raiku can meet their performance and privacy needs (e.g., encrypted order flows in a private extension). ### Non-Financial Apps (Real-time Games, Social, AI Agents, IoT): While Raiku’s focus seems to start with DeFi and the financial markets, the framework is broadly applicable. For real-time games or virtual worlds, Raiku could support an extension that handles rapid game state updates (imagine a fully on-chain fast-paced game, Raiku’s scheduling could guarantee actions happen in a timely tick system). For social networks or messaging apps on Solana, Raiku could provide throughput to handle spikes in activity (say a viral post causing thousands of reactions, handled in an extension so the main chain isn’t flooded). The website’s use cases explicitly mention bringing “AI Agents, DePIN, Social Networks, Payment Infrastructure, Capital Markets, HFT Trading, The Internet to Solana”. This sweeping vision suggests Raiku sees itself as enabling any high-demand application that today might think a blockchain can’t handle their scale or speed. For example, AI agents that perform dozens of on-chain actions per second (perhaps bidding in auctions, rebalancing portfolios, etc.) could utilize Raiku to get those actions processed reliably. DePIN (projects like Helium or decentralized Uber/Airbnb concepts) often require lots of micro-transactions and device interactions, Raiku could ensure IoT devices have reserved throughput to log data or settle payments consistently. In all these cases, the common theme is that Raiku enables a level of performance and trust that wasn’t possible on a single L1. It lets developers think bigger, to imagine on-chain services matching the responsiveness of centralized servers. An example: if Solana is already very fast for blockchain, Raiku makes “fast” the default even under load, much like a well-provisioned cloud server that auto-scales capacity for your app. The edge compute model is particularly attractive to projects that considered launching their own chain for performance reasons: now they can get similar benefits while plugging into Solana’s ecosystem, with a shared global state and full composibility. We may see projects from Ethereum L2s or other ecosystems “orbit” to Solana via Raiku. In fact, Raiku explicitly plans to court EVM-compatible protocols in its go-to-market, showing them that they can deploy on Solana with minimal friction and huge performance gains. ## Raiku’s Novel Approach: Execution Consensus Separation with Predictable Performance Raiku introduces a new block-building architecture that improves Solana’s base layer from within. It does this by enabling programmable coordination, allowing validators and applications to engage in more deterministic execution without introducing separate consensus or fragmented environments. One can think of Raiku’s network as a specialized execution layer that runs in parallel to Solana’s main chain, powered by the same validator set, that simply opts in by running the Raiku sidecar. By doing this, Raiku frees intensive application logic from contending with all of Solana’s traffic, yet it’s not an island, it remains tightly synced with Solana for finality and data availability. Unlike other ecosystems still wrestling with modular tradeoffs or fragmented execution models, Solana offers a high-performance, monolithic base layer. It delivers sub-second block times, ultra-low fees, and parallelized execution via Sealevel. These characteristics make it the most likely chain where ideas like just-in-time (JIT) or ahead-of-time (AOT) block auctions can be implemented at scale without prohibitive latency. While Solana delivers fast block times, low fees, and parallelized execution through Sealevel, the current block construction process still has limitations: - **Validator profitability remains volatile**, heavily reliant on native inflation subsidies and occasional MEV spikes. - **Transaction inclusion is unpredictable**, particularly for applications that require atomicity, deterministic ordering, or pre-confirmations. - **Out-of-protocol coordination is rising**, with protocols like Jito stepping in to address the lack of robust auction mechanisms and bundle execution guarantees. What’s been missing is a programmable coordination layer, one that gives validators more consistent revenue opportunities, empowers dApps with reliable execution features, and plugs into Solana’s native architecture without compromising its low-latency, high-throughput properties. Solana’s incentive and economic framework is evolving rapidly, guided by a series of critical Solana Improvement Documents (SIMDs). These proposals reshape core validator incentives, transaction priority mechanisms, and reward distribution, setting the stage for a more competitive and robust ecosystem: - **[SIMD-0096](https://github.com/solana-foundation/solana-improvement-documents/blob/694fb9164f210ed686a953444390854a0b65274b/proposals/0096-reward-collected-priority-fee-in-entirety.md#L4)**: Redirects 100% of priority fees to validators, significantly increasing validator profitability and discouraging off-network side deals. ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/b359b842b515.jpg) - **[SIMD-0123](https://github.com/solana-foundation/solana-improvement-documents/pull/123)**: Introduces a native, scalable protocol mechanism for validators to distribute rewards directly to stakers, enhancing economic alignment and transparency. - **[SIMD-0228](https://github.com/solana-foundation/solana-improvement-documents/pull/228)**[:](https://github.com/solana-foundation/solana-improvement-documents/pull/228) would have introduced a dynamic, market-driven emission schedule by adjusting inflation according to staking participation levels to improve economic efficiency and security. (However, [the proposal failed to reach the required two-thirds supermajority in its March 2025](https://solanacompass.com/learn/Lightspeed/why-solanas-inflation-proposal-didnt-pass-weekly-roundup)vote and has not been activated) While these changes focus on incentive alignment, they also amplify competition among validators, driving them to find new external revenue streams, especially important in bear markets when MEV and priority fee opportunities decrease. This ongoing evolution in Solana’s market structure lays the foundation for Raiku’s orchestration engine, designed precisely to enable reliable, predictable, and high-performance decentralized execution. The benefits of this execution–consensus separation are profound. First is predictable inclusion: where normally a user’s transaction might sit in a mempool or queue and hope to be included in the next block (or be dropped due to a spike in load), Raiku’s design aims to offer hard guarantees on inclusion and timing. Transactions submitted via Raiku can receive an “ahead-of-time” confirmation of inclusion, effectively a reservation in an upcoming block. This is achieved through Raiku’s novel scheduling and auction mechanisms (which we’ll discuss shortly). For users and dApp developers, it means no more spamming transactions or anxiously waiting to see if a critical trade gets mined, you can know within milliseconds that your transaction is scheduled for a specific future slot. This focus on deterministic, predictable execution is a key differentiator. Traditional L2s on Ethereum can improve fees and throughput, but they generally cannot guarantee exactly when a transaction will land on L1 (especially for optimistic rollups with challenge periods). By contrast, Raiku provides time-slot guarantees on Solana, an L1 known for its 400ms block times. Raiku essentially extends Solana with a “global scheduler” that applications can tap into for reserved blockspace. Another major advantage is **failure isolation**. In a monolithic L1, if one application (say, a popular NFT mint program) suddenly consumes huge resources or crashes, it can degrade or halt the entire chain. We’ve seen this on Solana, one dApp’s workload can cause network-wide slowdown. With Raiku, applications run in isolated execution zones, a.k.a. edge computes. If one of these zones faces an issue, for example, a runaway program consuming excessive compute, it **won’t directly clog Solana’s main chain or other zones**. The fault is contained to that extension environment. Solana’s consensus remains unaffected, and other extensions continue normally. This failure isolation is akin to having multiple “sandboxes” on the network: each application (or group of applications) can utilize a dedicated slice of capacity and even have custom parameters, without risking the stability of the whole. Traditional L2s offer some isolation (a fault on Arbitrum doesn’t halt Ethereum), but because they ultimately depend on L1 for proofs and bridging, a severe failure (or exploit) on a popular rollup can still have systemic effects (e.g. mass withdrawals through L1, or [social pressure on L1 to intervene in case of a huge hack](https://blockworks.co/news/dont-overuse-social-consensus-vitalik-warns). Raiku’s close integration with Solana means extensions are first-class citizens of the ecosystem, but any given extension’s troubles don’t spill over. It’s like partitioning traffic into separate high-occupancy lanes, an accident in one lane won’t gridlock the entire highway. Crucially, Raiku’s architecture preserves what both L1s and L2s aspire to: security and sovereignty. Each Raiku extension environment has execution sovereignty, meaning the application developers can customize the execution logic, VM, and parameters to their needs (it’s their “own chain” in that sense), but they do not need to bootstrap a new set of miners or validators from scratch. Raiku leverages a **[validator network](https://blog.colosseum.org/solana-tour-magicblock-real-time-hackathon-raiku/#:~:text=All%20of%20this%20is%20powered%20by%20the%20Raiku%20validator%20network%2C%20which%20works%20in%20sync%20with%20Solana%20to%20deliver%20faster%2C%20more%20reliable%2C%20and%20more%20predictable%20outcomes.)** that works in sync with Solana’s validator set. In practice, Raiku validators will be Solana validators opting to run Raiku’s software (a sidecar for the validator client), potentially earning additional fees for doing so. This means security is professional and robust from day one, you have an experienced validator set at the helm, and there isn’t a need for a separate token for security. By separating consensus (still handled by Solana’s PoH/PoS for finalizing blocks) from execution (handled by Raiku’s scheduling and validator network), throughput scales up significantly. Solana no longer has to execute every single instruction of every program itself; it can outsource execution of certain programs to Raiku extensions and simply verify outcomes or proofs. This is a different philosophy from Ethereum rollups which *fully* verify proofs on L1 (often incurring high costs). Solana can instead trust its own validator-integrated network to do much of the heavy lifting, given the alignment of incentives and real-time cooperation. In summary, Raiku is neither a standalone L1 nor a typical L2, it is an execution layer for Solana that introduces: (a) **execution–consensus separation** (freeing apps from L1’s throughput limits), (b) **predictable inclusion** and scheduling (no more probabilistic mempool games), and, (c) **robust fault isolation** (one extension’s issues don’t threaten the whole) It transforms Solana from a single-tier network into a multi-tier system: the base layer for consensus and global state, and an upper layer for high-performance application-specific execution. ## Inside Raiku’s Technology Stack: Deterministic Settlement and Modular Execution To deliver on its promises, Raiku introduces several novel components and transaction types. These can be thought of as **infrastructure building blocks** that work together to enhance Solana. Let’s break down the key elements of Raiku’s tech stack: ### 1. Ahead-of-Time Block Auctions & Inclusion Signals: At the heart of Raiku is a new way of managing blockspace. Instead of the ad-hoc first-come-first-served mempool model, Raiku implements a slot auction marketplace. Applications or users can bid for upcoming slots on Solana (or rather, on Raiku’s coordinated schedule) in advance, securing priority for their transactions. The winning bids receive “inclusion signals” ahead of time, essentially a guarantee that their transaction (or bundle of transactions) *will* be included in a specific future block or sequence of blocks. These auctions are stake-weighted and atomic, meaning the scheduling respects the Solana stake distribution (validators with more stake have more capacity to include reserved transactions, aligning incentives) and transactions can be reserved in bundles that execute sequentially without interruption. The outcome is that a Raiku user can get a faster confirmation now that their “ticket” for execution is secured. Compare this to the traditional experience: on Ethereum, you send a transaction and *hope* a miner picks it soon (maybe boosting the fee if you’re desperate), and even on Solana, you might spam several transactions to ensure one lands during congestion. With Raiku, the process becomes akin to booking a train seat in advance rather than elbowing through a crowded platform. This system dramatically reduces failed transactions and uncertainty, one of Raiku’s core objectives is **guaranteed execution**. **Proof Streaming: Unlocking Large Payload Execution via Sequential Blockspace** One fundamental limitation in Solana today is strict per-block data constraints, designed to preserve fast block propagation. This can become a bottleneck for applications that need to submit large state updates, such as settlement engines or ZK rollup proofs. Raiku addresses this through sequential blockspace reservations, a concept enabled by its Ahead-of-Time (AOT) block auction model. By securing a sequence of upcoming slots, applications can reliably stream large proofs or payloads in smaller, verifiable chunks, without hitting Solana’s per-block cap. The idea is to **break up large transactions or proofs into smaller pieces** that can be streamed and verified over multiple slots, bypassing Solana’s strict per-block data limits. Practically, this means an application could submit a very large state update or proof (for example, a zero-knowledge proof or a batch of hundreds of trades) through Raiku, and Raiku will handle feeding this data into Solana in chunks that validators can handle. Rather than submitting a large transaction that risks failure or bloat, applications can schedule and stream structured data across multiple slots, while validators process and verify it in a controlled manner. ### 2. Fast and Deterministic Settlement (“Guaranteed Execution”): Many of the next-generation applications Solana aims to support, such as high-frequency trading platforms, real-time gaming systems, and institutional payment networks, demand strict guarantees that transactions will land exactly when and where they are expected. In these domains, execution uncertainty is not just a UX flaw; it is a deal breaker. Unpredictable network congestion and mempool dynamics can result in transaction failures, reordering, or delays. For advanced use cases like automated liquidations, synchronized asset swaps, or arbitrage strategies, this unpredictability leads to missed opportunities and capital inefficiency. Raiku addresses this gap with Guaranteed Inclusion through Ahead-of-Time (AOT) and Just-in-Time (JIT) slot reservations. For example, bots acting on real-time price movements may prefer JIT inclusion, while external systems may opt for scheduled AOT slots. In both cases, users pay for precision, both in timing and bandwidth (using a combination of Raiku tokens and SOL). When a Guaranteed inclusion transaction is submitted through Raiku, it is assigned a reserved execution window, ensuring it is processed at the intended time and never dropped or reordered due to validator behavior or network congestion. While only the slot leader can include the transaction, all validators running the Raiku sidecar help propagate and acknowledge the schedule ahead of time. Raiku uses a pre-consensus scheduling system to coordinate transaction plans, which the slot leader then executes during block production. By reserving blockspace in advance and assigning deterministic execution slots, Raiku mitigates peak failure scenarios where high-frequency users on Solana have historically seen failure rates exceeding 90 percent. It delivers guaranteed bandwidth, latency precision, and settlement predictability, even during periods of extreme load. Guaranteed Execution also introduces MEV resistance by design. Since transactions are scheduled in advance and confirmed across the network, frontrunning is mitigated, and sandwich attacks are neutralized by incorporating expected value extraction into the auction mechanism itself. Private order flow deals that previously operated outside the protocol are no longer necessary. Instead, inclusion is handled transparently via a fair scheduling auction or reservation system. For developers, Guaranteed Execution means you can offer your users a web2-like guarantee: e.g. a trade on a Solana DeFi app can be confirmed in milliseconds with certainty it will settle, no more “transaction dropped, please retry” errors. ### 3. Global Account Model and Unified State: One of the most groundbreaking aspects of Raiku is its **Global Accounts Module**. This component (planned for V2 alongside proof streaming) tackles the **state fragmentation problem** head-on. The idea is to allow users and applications to maintain a unified identity and state across multiple execution environments. In practical terms, a user would still have one Solana wallet/address that they use on the main L1 and across any Raiku extension they interact with. Assets and data can move seamlessly between the main chain and extensions without traditional “bridging.” The global account model will enable composability across extensions, so two Raiku extensions can interoperate or access a shared user state if needed. This is a significant differentiator from typical L2s, where each rollup is a walled garden requiring a bridge to move assets and where accounts/contract addresses might be chain-specific. With Raiku, since extensions are more like “zones” within the Solana ecosystem, the user experience remains unified. Developers can deploy in an extension environment and still easily integrate with Solana-native programs or accounts. For example, an order placed in a Raiku-powered orderbook extension could settle into a user’s main Solana wallet or be recognized by a program on L1, thanks to unified accounts. Technically, this might be achieved by having Raiku share Solana’s account address space and signature verification, or by having a mechanism to synchronize state roots between the extension and L1. The outcome is that state fragmentation is solved, you get *multiple execution environments with one combined state*. As the Raiku team describes, this allows composability across extension environments, which is something neither Ethereum L2s (all separate) nor earlier Solana rollup attempts achieved. It’s a first-principles approach to ensure that scaling out doesn’t mean splitting the user base or liquidity. The Global Accounts Module also supports multi-VM functionality. Raiku isn’t limited to Solana’s native VM (SVM), it is being built to potentially host different virtual machines under the same umbrella of coordination. In fact, Raiku aims to support EVM-compatible extensions, allowing projects from the Ethereum world to deploy their Solidity code as a Solana extension. The mention of “[projects like Arbitrum Orbit to deploy on Solana”](https://docs.raiku.com/overview/novel-app-architectures#external-extension-construction) suggests an Ethereum L3 or custom chain could effectively plug into Solana via Raiku. This is huge: it means an Ethereum dApp could enjoy Solana’s performance and user base without abandoning its codebase. All of this is enabled by global accounts, users wouldn’t even need to switch wallets or bridge tokens; the EVM extension would recognize their same wallet (possibly via an address derivation or mapping) and could use Solana’s native assets. ![](https://shoal.xyz/research/writing/raiku-solanas-high-performance-edge/img/bfef44d09349.jpg) This suggests Raiku has a somewhat layered node architecture: normal users/apps talk to an Ackermann node (or cluster) which then interfaces with validators to schedule execution. It’s an interesting design for scaling input handling and ensuring the system can handle bursts of transactions by distributing them across validators effectively. ## Concluding thoughts Raiku’s emergence signals a turning point for Solana and blockchain architecture at large. It offers a vision where a decentralized network can achieve the reliability, speed, and flexibility that were once the exclusive domain of Web2 cloud or traditional finance systems. By introducing a coordination engine with deterministic execution, Raiku enables Solana to transcend the label of “just another L1” and become a platform for truly mission-critical, high-performance applications. Consider what this means for developers: With Raiku, building on Solana can feel like building on a scalable cloud service. - Need more throughput? just spin up an extension and reserve the slots you need. - Need custom execution logic or a different VM? plug it in as an edge compute zone. - Worried about user experience during peak times? offer guaranteed tx inclusion so users never see a failed transaction again. The developer experience is significantly improved. Developers can build with confidence, knowing that the infrastructure will meet their app’s demands instead of the other way around. The base Solana chain acts as a stable backbone, while Raiku provides the agile, programmable scaffolding to push the limits. This has the potential to attract not only crypto-native developers but also Web2 developers who have performance-sensitive use cases. They can come to Solana without worrying that the network might slow them down. In effect, Raiku could make Solana the preferred platform for any application that requires both decentralization and high throughput. On the institutional front, Raiku could be the key that unlocks serious enterprise adoption of Solana. Banks, hedge funds, gaming companies, social media upstarts, all could finally feel comfortable building on-chain because the performance and control they require are available. Solana has already been one of the more institution-friendly chains (with firms like Jump investing in its tech); Raiku turbocharges that appeal by promising fine-grained execution control and high reliability. Institutional-grade means things like 99.999% uptime, transaction deadlines, privacy where needed, compliance hooks – all of which Raiku can facilitate (through isolated extensions, scheduling, etc.). We might see pilot projects like a stock exchange settlement network on Solana, or a large payment processor integrating Solana via Raiku for instantaneous global transfers. The journey is just beginning, Raiku is in testnet, with mainnet slated for late 2025,but the foundational narrative and architecture are in place. It addresses the pain points we outlined at the start: scaling limitations (solved by adding modular throughput), MEV exploitation (minimized through predictable ordering and auctions), restaking challenges (avoided via a more contained approach), fragmented state (solved by global accounts), and performance issues (solved by guaranteed inclusion and fault isolation). Raiku thus emerges as a cohesive solution, not a piecemeal fix. **References** 1. CoinShares. 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(n.d.). *Solana permissioned blockchains.* Helius Blog.[https://www.helius.dev/blog/solana-permissioned-blockchains](https://www.helius.dev/blog/solana-permissioned-blockchains) 6. Helius. (n.d.). *What is Firedancer?* Helius Blog.[https://www.helius.dev/blog/what-is-firedancer](https://www.helius.dev/blog/what-is-firedancer) 7. Kiln.fi. (n.d.). *Ethereum L2 challenges and fragmentation.* Kiln Blog. [https://www.kiln.fi/post/eth-l2-challenges-fragmentation](https://www.kiln.fi/post/eth-l2-challenges-fragmentation) 8. Kiln.fi. (n.d.). *What are Solana network extensions, and how are they different from Ethereum layer-2s?* Kiln Blog.[https://www.kiln.fi/post/what-are-solana-network-extensions-and-how-are-they-different-from-ethereum-layer-2s](https://www.kiln.fi/post/what-are-solana-network-extensions-and-how-are-they-different-from-ethereum-layer-2s) 9. Medium. (n.d.). *AMA with Raiku founders: Problems and roadmap.* Medium. https://medium.com/ 10. Medium. (n.d.). *MEV exploitation on Ethereum and Solana.* Medium. https://medium.com/ 11. Medium. (n.d.). *Raiku technical offerings: Guaranteed Inclusion, Inclusion Signals, Proof Streaming, Global Accounts.* Medium. https://medium.com/ 12. Raiku Labs. (n.d.). *Raiku Docs – Conceptual documentation.* Raiku Documentation. https://docs.raiku.com/ 13. Raiku Labs. (n.d.). *Raiku Docs – Technical documentation.* Raiku Documentation.[https://docs.raiku.com/technical-docs](https://docs.raiku.com/technical-docs) 14. Solana Foundation (Colosseum). (n.d.). *Raiku: Introduction and features.* Colosseum Blog. https://blog.colosseum.org/ 15. Solana Foundation (Colosseum). (n.d.). *Solana congestion and failure issues.* Colosseum Blog. https://blog.colosseum.org/ 16. Terminal Technology. (n.d.). *Network extensions #2.* Termina Technology Blog.[https://www.termina.technology/post/network-extensions-2](https://www.termina.technology/post/network-extensions-2) 17. Unchained Crypto. (n.d.). *Are Solana’s network extensions just like Ethereum’s layer-2s, but by a different name?* Unchained Crypto.[https://unchainedcrypto.com/are-solanas-network-extensions-just-like-ethereums-layer-2s-but-by-a-different-name/](https://unchainedcrypto.com/are-solanas-network-extensions-just-like-ethereums-layer-2s-but-by-a-different-name/) 18. Vitalik Buterin & Blockworks. (n.d.). *Vitalik’s caution on restaking risks.* Blockworks. [https://blockworks.co/news/vitalik-buterin-restaking-risks](https://blockworks.co/news/vitalik-buterin-restaking-risks)***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.****Disclosures**. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the Raiku team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # CUDIS: The AI DePIN Smart Ring Democratizing Health Data on Solana > Wellness is the next frontier, yet still a luxury. CUDIS blends wearables, AI, and blockchain to create a user-owned health economy that makes personalized longevity accessible and rewarding. - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2025-07-17 - Canonical: https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/ - Keywords: crypto, tokenization, privacy, infrastructure, Solana, DePIN, AI & Agents ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/99820edee33b.jpg) ## Summary By combining personal wearables, AI coaching, and blockchain-based data ownership, CUDIS builds a transparent health economy that transforms wellness from a private endeavor into a collective, open ecosystem. Its flagship CUDIS smart ring tracks vital health metrics like steps, sleep, heart rate, and stress, feeding data into a personalized AI coach that has delivered over 1 million tailored insights. With [20,000 rings sold and 200,000](https://chainwire.org/2025/06/04/cudis-launches-cudis-token-on-solana-turning-health-data-into-an-onchain-asset-class/?mfk=PY7iJJNJhysrMU2gWoKU8V5XYm%2FiH1acUNlnTeEcTvW%2BCRZZrY%2FXLobKEnRj%2FDlhEjVzv5Cy%2Bh) users across 103 countries, CUDIS demonstrates strong traction. The $CUDIS token powers an earning model that rewards healthy behaviors and enables governance, staking, and premium access. Unlike competitors like Oura, CUDIS prioritizes user data ownership through Longevity Decentralized Identifiers (LDIDs), allowing health data to be minted as NFTs or stored privately via IPFS. Backed by a $5 million seed round from Tim Draper, SkyBridge Capital, and the Solana Foundation, and bolstered by [partnerships with UCLA Athletics](https://thedefiant.io/news/press-releases/cudis-smart-ring-collaborates-with-ucla-athletics-to-promote-student-wellness-and-data-ownership-with-ai-blockchain) and [WalletConnect](https://x.com/WalletConnect/status/1937889592881070202), CUDIS addresses privacy concerns and gamifies wellness. Its scalable infrastructure and DeSci alignment position it to democratize longevity, potentially transforming health data into a user-owned asset class, making CUDIS a compelling contender in the $50–80 billion anti-aging market. ## The Quest for Longevity Mayflies survive just a single day, while Galapagos tortoises can live up to 170 years. Topping the longevity charts, the Greenland shark holds the record with a lifespan exceeding 400 years. However, this has led to one of humanity's most universal desires: to live long and experience the fullness of old age. It has been believed that this has been achieved by comparatively few throughout history, and the “why” behind these enormous swings and the quest to harness longevity for humans has driven fevered attempts (and billions of dollars in research spending) to slow or stop aging. This has even led to some thought-seeking controversial questions like, “If this is achieved, what happens to our humanity, beliefs, and systems?” On the topic of longevity research, for the first time, breakthroughs in aging research, cellular biology, genomics, and personalized health tracking have made extreme longevity a tangible possibility, with studies suggesting humans could live beyond 150 years in optimal health, as noted in research from *[Nature Communications](https://www.scientificamerican.com/article/humans-could-live-up-to-150-years-new-research-suggests/)*[and](https://www.scientificamerican.com/article/humans-could-live-up-to-150-years-new-research-suggests/)*[Scientific American](https://www.scientificamerican.com/article/humans-could-live-up-to-150-years-new-research-suggests/)*. Innovations like senolytics and AI-driven diagnostics are pushing boundaries, but advanced treatments can cost up to $250,000 annually, limiting access to the wealthy. McKinsey’s 2025 *[Future of Wellness](https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/future-of-wellness-trends?)* survey values the global wellness sector at $2 trillion. In the United States, millennials and Gen Z account for 41 percent of spending while representing just 36 percent of adults. Eighty-four percent of U.S. consumers now rank wellness as a top priority, and nearly one-third of Gen Z increased their wellness spend “a lot more” year-over-year. These demographics favor personalized, data-rich solutions, creating tailwinds for platforms like CUDIS that combine wearables, AI, and user-owned data. In 2022, a [McKinsey Health Institute report](https://www.mckinsey.com/mhi/our-insights/adding-years-to-life-and-life-to-years) estimated that humanity could gain 45 billion additional years of higher-quality life, or about six extra healthy years per person, if proven interventions were scaled and health were addressed holistically across physical, mental, social, and spiritual dimensions. Despite this potential, the average person still spends roughly half of their life in suboptimal health, a ratio unchanged in 50 years. These findings underscore the need to redirect investment toward prevention and early detection. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/59c5129df154.png) The anti-aging industry, valued at around $50–80 billion (not $600 billion, likely a confusion with the broader beauty market), is projected to grow significantly, possibly reaching [$247.9 billion by 2030.](https://www.researchandmarkets.com/reports/5526495/complementary-and-alternative-medicine-for-anti?) Yet, misinformation, unproven therapies, and a lack of real-time progress tracking make longevity feel like just a theory. And while strong evidence shows that advanced health interventions contribute to increased human longevity, such as [CRISPR-based gene editing to correct genetic disorders](https://pmc.ncbi.nlm.nih.gov/articles/PMC10980556/#:~:text=Discussion%20CRISPR%E2%80%93Cas9%20enables%20precise,function%20and%20controls%20gene%20expression.)and [stem cell therapies](https://en.wikipedia.org/wiki/Stem-cell_therapy) to repair damaged tissues, It still contrasts with the natural longevity observed in Blue Zones, driven by community practices like balanced diets and physical activity, and provides a more affordable and sustainable alternative to these high-tech interventions. Despite rising outlays, large gaps persist. Younger cohorts report the greatest shortfalls in mental resilience, cognitive health, and longevity services. For instance, 42 percent of U.S. Gen Z and millennials place mindfulness as a very high priority, yet feel current offerings miss the mark. High-growth subcategories include functional nutrition, healthy aging products, and AI-powered biomonitoring, precisely the value stack CUDIS delivers by converting biometrics into actionable insights and tokenized rewards. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/df1757bf8365.jpg) *[Source: The Secret of Okinawan Longevity](https://visitokinawajapan.com/discover/food-and-longevity/okinawan-longevity)* Aside from religious narratives describing humans living for hundreds of years, which are not widely accepted due to diverse belief systems, the most credible examples of longevity are found in *Blue Zones* like *Okinawa, Japan*. Residents there often live beyond 100 years, remain free from common age-related health issues, and maintain the vitality of adults in their 40s. The Okinawan mystery begins with the question, “How do the people of this island live such long and healthy lives?” Researchers and scientists studying the Blue Zones attribute their longevity to a key combination of *diet and exercise*. A key principle followed by Okinawan residents is ***Hara Hachi Bu***, which translates to eating until they are 80% full, promoting mindful consumption and sustained health. The universal pursuit of longevity, like the Okinawan residents, has spurred prominent companies, including *Whoop, Oura, Headspace, Strava, Levels Health, Apple Fitness+, and ZOE,* to develop innovative apps. These platforms serve diverse purposes, from fitness tracking and metabolic health monitoring to sleep optimization and mindfulness practices, all aimed at enhancing health and extending life. This proliferation of innovative apps reflects a global push for longevity, yet it sets the stage for examining why today’s longevity solutions, despite their promise, often fall short. ## Why Today’s Longevity Solutions Fall Short The digital longevity health revolution is transforming how individuals track and optimize their well-being, with over 1.1 billion users engaging with fitness and wellness platforms projected to reach [$1.6 trillion by 2033](https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/feeling-good-the-future-of-the-1-5-trillion-wellness-market?). The rapid adoption of wearable technology, used by more than 600 million people who generate over [1 GB of health data daily,](https://www.ucsf.edu/news/2025/06/430166/your-fitness-tracker-could-help-doctors-spot-health-risks-early?) including heart rate, sleep patterns, and activity levels, has significantly accelerated this shift. However, despite this vast data volume, users cannot fully harness it for longevity optimization, as most health information remains locked in corporate silos, limiting individual access and benefit. In a separate evaluation, after using over 10 fitness and longevity-themed applications on the App Store and Play Store for a few weeks daily, a recurring pattern emerges: while these apps promise innovative features, their delivery is often undermined by poor user experience and design. Moreover, some apps are entirely unresponsive, while others provide inaccurate, non-actionable data. A less noticeable issue is that user fitness data is frequently collected and sold to third-party data companies. Stepping back, several key flaws become apparent: - ***Poor user experience***: The apps often feature clunky interfaces and confusing navigation, making it difficult for users to fully utilize their features. This lack of intuitive design frustrates users and discourages regular engagement. - ***Inaccurate data measurement***: Many applications provide unreliable fitness or health metrics, such as step counts or heart rate readings, due to faulty sensors or algorithms. This inaccuracy renders the data untrustworthy and limits its practical value. - ***Unauthorized sale of user data***: User fitness data is frequently collected without explicit consent and sold to third-party companies, raising privacy concerns. This practice prioritizes corporate profit over user trust and control. - ***Lack of incentives to keep users engaged in their fitness journey***: The apps fail to offer rewards, challenges, or personalized goals to motivate continued use. Without such incentives, users are less likely to stay committed to their health and fitness routines. In contrast, Oura stands out by prioritizing user experience and addressing many of these issues effectively with its sleek, intuitive design that enhances user engagement. The app delivers accurate health metrics through optimized algorithms and sensors, providing reliable data that users can trust for informed decisions. Oura also emphasizes user privacy by offering transparent data management, reducing concerns about unauthorized sharing. Furthermore, its personalized insights and actionable recommendations empower users to stay motivated on their wellness journey, setting a high standard in the fitness app market. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/1e99af373777.jpg) [Oura’s](https://ouraring.com)Ring has contributed to its solid growth, with over 2.5 million units sold by 2024, indicating steady consumer interest in health and wellness tracking. The company has raised $550 million in total funding across multiple rounds, including a $200 million Series D round in December 2024, bringing its valuation to [$5.2 billion](https://www.fiercehealthcare.com/health-tech/oura-closes-200m-round-boosting-smart-ring-makers-valuation-52b), supported by investments from firms like Fidelity Management, Dexcom, and Forerunner Ventures. It also received recognition, such as being named one of Time magazine’s "100 Best Inventions of 2020" and earning the "Best Consumer Wellness Company" award from the UCSF Digital Health Awards in 2020 for its smart ring technology. We will compare it later in the article with that of the CUDIS Ring. However, Oura still falls short in two critical areas essential for long-term user adoption. 1. Firstly, despite its emphasis on privacy, user data continues to be sold by the company to third-party service providers for profit, rather than being monetized in a way that directly benefits users, leaving many feeling their health insights are exploited rather than rewarded. 2. Secondly, the app lacks incentives, such as rewards to encourage ongoing usage, which could otherwise motivate users to remain engaged with their wellness journey over time. This gap in user empowerment and engagement hints at a potential shift in the wearable tech landscape, where a new contender is emerging on the horizon. The CUDIS Ring suggests it might address these shortcomings, but the full story of its potential to redefine health tracking remains to be unveiled. We delve deeper into its promise in the next paragraph. ## Here is CUDIS ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/89849f8694cc.png) CUDIS is an emerging player in the wearable health technology sector, carving a niche with its innovative approach to wellness by integrating artificial intelligence (AI), blockchain, and decentralized technology. Launched in April 2024 by BeatBit Wellness Lab, the company has quickly gained traction, pre-selling over 6,000 smart rings across more than 50 countries and building a community of 50,000 members within its first year. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/311017165b1f.png) This rapid growth is further evidenced by a successful [$5 million](https://chainwire.org/2024/09/18/cudis-secures-5m-seed-led-by-draper-associates-to-challenge-oura-ring-in-the-wearables-market-with-blockchain-and-ai/) seed funding round in September 2024, led by Draper Associates, with additional investments from Borderless, Skybridge, Penrose, SNZ, Mozaik, NGC, Foresight Ventures, OGBC, Monke Ventures, DraperDragon, and notable individuals like Sean Carey of Helium and Adam Jin of the Solana Foundation. CUDIS aims to deliver over 1 million rings in the next 18 months, signaling ambitious plans to expand its global footprint and enhance its AI-driven health solutions. At the helm is ***Edison Chen***, the co-founder and CEO, a seasoned entrepreneur with a background in blockchain, AI, gaming, and e-commerce, and a UCLA graduate whose vision is to empower users with ownership of their health data. Chen, also the Vice-President of Plum Ventures, brings a wealth of experience from investing in over seven unicorn startups, driving CUDIS’s mission to revolutionize wellness through user-centric innovation. CUDIS’s success is supported by a small, stealth team of passionate professionals, whose identities remain undisclosed to maintain a competitive edge. Strategic partnerships with entities such as UCLA Athletics, the Italian GT Championship, Padel and Fitness events, and Web3 companies like Solana Mobile and World Chain App have bolstered its credibility and market reach. These collaborations, including in-game signage at [UCLA basketball games and the Pro Athlete Ambassador Program](https://athletechnews.com/cudis-crypto-smart-ring-ucla-athletics/) featuring Olympians and endurance athletes, highlight CUDIS’s growing influence beyond the crypto space into mainstream wellness. The company’s flagship product, the ***CUDIS Wearable Ring***, sets it apart with its AI-powered health tracking and blockchain-based rewards system, monitoring metrics like heart rate, sleep patterns, and activity levels while allowing users to monetize anonymized data on the Solana blockchain. This ring, available in models like the CUDIS 002 launched in December 2024, offers up to 10 days of battery life and integrates with a personalized AI coach, providing tailored wellness insights without monthly fees, a stark contrast to competitors like ***Oura***. Complementing the ring is the ***CUDIS Super App***, a versatile platform that extends beyond ring users to offer a unified hub for health data management, integrating with services like Apple Health and Google Fit. The app features social challenges, an AI coach, and plans for a decentralized data network, enabling users to mint health data as NFTs and earn rewards, positioning CUDIS as a pioneer in the HealthFi (Health Finance) space. With its focus on data ownership, privacy, and incentivized wellness, CUDIS is poised to challenge established players, though its small team and reliance on future tokenomics and market education will be critical to sustaining its momentum. ## A Super App ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/05cc371af8aa.jpg) The CUDIS Super App is nothing short of a groundbreaking masterpiece, redefining the future of longevity and personal wellness with its all-in-one platform that empowers users to take complete control of their health data like never before. Launched in April 2024 as part of the innovative ecosystem, this app has already captured the imagination of health enthusiasts worldwide, amassing an impressive 200,000 downloads since its beta release, a testament to its rise and the growing demand for cutting-edge wellness solutions. Seamlessly integrating with a vast array of major health platforms, including Apple Health, Google Health, Strava, and MyFitnessPal, the CUDIS Super App transforms fragmented health data into a unified, intuitive interface that serves as the ultimate command center for comprehensive health management. This isn’t just an app; it’s a lifestyle revolution, designed to unlock the secrets of a vibrant, extended healthspan for millions, blending cutting-edge technology with an inspiring vision of wellness that’s accessible to all. At the heart of the CUDIS Super App lies its unparalleled ability to track and optimize healthspan and physical health, pushing the boundaries of what’s possible with a bold goal of enabling users to thrive well into their 140s. Powered by state-of-the-art AI-driven coaching, the app delivers personalized, science-backed recommendations 24/7, analyzing biometric data, behavioral patterns, and lifestyle choices to provide actionable insights tailored to each user’s unique journey. Whether it’s fine-tuning sleep patterns, boosting physical activity, or enhancing nutritional habits, the personalized AI coach acts as a virtual wellness guide, adapting in real-time to guide users toward their longevity goals with precision and care. Beyond coaching, this AI coach opens doors to exclusive resources of curated longevity products, programs, and services, offering everything from advanced supplements to expert-led wellness courses, ensuring users have access to the tools they need to maximize their health potential. This holistic approach sets CUDIS apart, creating a dynamic ecosystem where wellness isn’t just tracked but actively nurtured and rewarded. One of the app’s most exhilarating features is its rewards-based longevity challenges, turning health optimization into an engaging, gamified experience that motivates users to stay committed. By participating in activities like wearing the CUDIS Wearable Ring, logging workouts, or achieving personalized health milestones, users earn Health Points—a proprietary incentive system in the CUDIS Beta phase. These points can be redeemed for raffle spins, offering chances to win rewards like USDC, Edamame NFTs, or even a CUDIS 002 ring, making every step toward better health a step toward tangible benefits. This innovative blend, built on the Solana network, allows users to mint their anonymized health data as NFTs, opening a new frontier where personal wellness becomes a valuable, monetizable asset. This feature alone has sparked widespread excitement, drawing a global community eager to embrace a future where health data ownership drives both longevity and financial empowerment. Another essential feature of the CUDIS Super App is its built-in wallet, powered by Multi-Party Computation (MPC) technology and LDID, which ensures secure transactions, robust identity protection, and financial sovereignty while enabling seamless engagement within the CUDIS ecosystem. Despite its early success, the CUDIS Super App is still in its beta stage, and users have noted some challenges with UI design that occasionally hinder the seamless experience it promises. Clunky navigation and occasional lag in certain features have been reported, reflecting the app’s ongoing development as a work in progress. However, these imperfections are overshadowed by its immense potential, as the beta phase allows the small, stealth team at CUDIS to refine and enhance the platform based on real-world feedback. As it continues to grow and refine, its potential to redefine wellness technology is limited only by the imagination, making it a must-watch contender in the evolving landscape of health optimization. ## CUDIS Wearable ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/b627ecfcebcf.jpg) The global adoption of wearable devices has skyrocketed, with tens of thousands of units sold worldwide, signaling a transformative shift in how individuals monitor their health. CUDIS has seized this opportunity, integrating seamlessly with 70+ mainstream wearable brands and bringing thousands of wearable users on-chain to benefit from its innovative CUDIS protocol. Yet, rather than following the crowded path of wristbands, CUDIS opted for a ring design for its proprietary crypto wearable, the CUDIS Ring, tailored for the crypto-native community seeking continuous biometric tracking of critical real-time biomarkers like heart rate variability, stress levels, sleep patterns, and vital signs. This choice was deliberate: the fingers, packed with a dense red capillary bed, excel at detecting blood volume changes, providing unparalleled accuracy; their low muscle movement delivers clearer signals for heart rate pulse wave velocity; and their stable contact ensures a snug fit during sleep or active use, offering flexibility that wristbands, despite popular belief, struggle to match. This strategic pivot underscores CUDIS’s commitment to precision and user comfort, setting the stage for a wearable that redefines health tracking. The CUDIS Ring itself is a marvel of engineering, pairing effortlessly with the CUDIS Super App via a fast Bluetooth connection that ensures real-time data synchronization with pinpoint accuracy. Designed for all weather, this sleek ring is fully waterproof, capable of withstanding swims, showers, and intense workouts without compromising performance, making it a reliable companion for any lifestyle. Its power supply is equally impressive, boasting a robust 10-day battery life on a single charge, thanks to optimized energy management that minimizes downtime and maximizes tracking consistency, ideal for users who demand uninterrupted insights. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/77da0480388e.jpg) The latest sporty version, unveiled in June 2025, introduces a vibrant palette of colors, jet black, lunar silver, cosmic blue, and fiery red, drawing inspiration from the business theory behind the success of the iMac in 1998. Just as Apple’s introduction of [colorful iMacs](https://www.macworld.com/article/1801616/imac-25-year-anniversary-colors-iphone-future.html) allowed users to express individuality and boosted sales by 40% that year, CUDIS leverages this psychology to enhance user engagement, turning the ring into a stylish statement piece that resonates with the crypto community’s dynamic identity. This innovative design ties seamlessly into the robust infrastructure powering CUDIS’s ecosystem, which we’ll explore in the next paragraph. Priced at $369, the new sporty version reflects its advanced features and sporty appeal, a slight increase from the original CUDIS Ring’s $349, underscoring the brand’s evolution and commitment to delivering cutting-edge value. As the wearable market continues to expand, the CUDIS Ring stands poised to lead, blending technology, style, and community-driven innovation into a product that’s as empowering as it is transformative. ## Building the Infrastructure for a Reward-Driven Healthspan CUDIS is dedicated to revolutionizing longevity by transforming it into a measurable, achievable, and financially rewarding pursuit, while ensuring its benefits are accessible to everyone through a robust, cutting-edge infrastructure designed to fulfill every promise. By integrating artificial intelligence, blockchain, and community-driven models, CUDIS builds a foundation that not only tracks and enhances healthspan but also aligns individual well-being with tangible financial rewards, creating a sustainable ecosystem poised to democratize longevity on a global scale. Its infrastructure, known as the ***CUDIS Data Network***, seamlessly integrates blockchain, NFTs, and a secure processing framework to deliver a robust platform for data ownership, rewards, and privacy preservation. This network comprises four pivotal components: ***LDID***, which manages users’ comprehensive health data with robust privacy safeguards; the ***CUDIS Data Aggregator***, which generates unique, immutable health data records; the ***CUDIS DataHub***, facilitating flexible and equitable data transactions; and the ***CUDIS Processing Nodes,*** ensuring transparent and efficient data processing. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/4085088142e9.png) Delving deeper into CUDIS’s infrastructure reveals a layered system built to prioritize user empowerment, data integrity, and secure exchange. At its core, LDID ensures robust privacy protection for sensitive health data, while the CUDIS Data Aggregator leverages blockchain to create unique, immutable records, laying a secure foundation for personal data ownership. Complementing this, the CUDIS DataHub facilitates flexible and equitable data transactions, and the CUDIS Processing Nodes enable transparent, efficient computation. Together, these components form a dynamic, user-centric data economy designed to advance longevity through trust and innovation. This divides the CUDIS infrastructure into two complementary pillars, each reinforcing the other. ## Foundations of Data Integrity and Privacy This pillar is composed of the CUDIS LDID (Longevity Decentralized Identifier) and the Data Aggregator. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/77053de584f7.jpg) [CUDIS LDID](https://whitepaper.cudis.xyz/cudis-protocol/cudis-technology-infrastructure/ldid-longevity-decentralized-identifier) The CUDIS LDID emerges as a sophisticated privacy-preserving identity layer, elegantly anchoring user data ownership and control across the diverse landscapes of Web2 and Web3. By ingeniously binding digital identities to Non-Fungible Tokens (NFTs) and Soul-Bound Tokens (SBTs), LDID crafts verifiable, non-transferable profiles that seamlessly integrate multi-chain addresses and third-party accounts, such as social media or fitness platforms, into a unified digital persona. This modular framework not only facilitates secure identity aggregation and self-authentication but also establishes a robust, permissioned gateway for users to manage access to their personal health and wellness data with unparalleled precision and trust. Enhanced by features like PSD-KV (Private Data Key-Value Storage) on IPFS, which safeguards sensitive information like AI agent memories, LDID lays a resilient foundation that prioritizes privacy and empowers individuals to dictate the terms of their data’s use. Building upon this, the CUDIS Data Aggregator elevates the LDID-linked data into a realm of tokenized digital assets, redefining the potential of health information with elegance and innovation. This harnesses state-of-the-art encryption and metadata protocols to encase user-controlled health records within immutable NFTs, enabling secure exchange, monetization, and ownership preservation on the blockchain. The Aggregator seamlessly inherits identity and access parameters from LDID, ensuring that every data transaction remains user-permissioned, fully traceable, and aligned with a rewards ecosystem, thus forging a continuous pipeline from identity establishment to the realization of data value. Optimized through the Metaplex Protocol, it introduces tailored enhancements for health data’s unique characteristics, promising privacy, integrity, and economic incentives, and positioning the aggregator as a pivotal bridge that transforms LDID’s identity framework into a dynamic, user-empowered marketplace for wellness insights. ## Empowering Transactions and Efficiency This pillar is composed of CUDIS DataHub and CUDIS Progressing Nodes. Flowing seamlessly from the aggregator’s output, the CUDIS DataHub emerges as a pioneering next-generation marketplace that harnesses tokenized health data, providing a decentralized platform where users can securely exchange and utilize their NFTs with complete control and privacy. Built on cutting-edge decentralized technologies, this innovative hub rewards users for sharing their data while ensuring transparent, secure, and efficient transactions, whether transferring access rights or ownership, unlocking the intrinsic value of personal health insights. This dynamic ecosystem not only empowers individuals but also fosters a vibrant community for innovation in health analytics and longevity research, transforming health data into a catalyst for scientific advancement and personal gain. Complementing the DataHub’s marketplace prowess, the CUDIS Processing Nodes (CPN) redefine data handling by offering a decentralized, secure, and scalable environment, powered by Kubernetes (K8s) container orchestration, which ensures transparency, user control, and trust in managing sensitive health data. This robust infrastructure revolutionizes the processing, analysis, and sharing of health information, delivering efficient computation that supports a wide range of data-driven applications with unwavering reliability. Together, the CPN’s advanced capabilities and the DataHub’s marketplace dynamics forge a privacy-first, user-empowered data ecosystem that benefits individuals while propelling breakthroughs in longevity science, envisioning a future where health data fuels both personal wellness and collective progress. ## The CUDIS Longevity Hub The CUDIS Longevity Hub is the ecosystem’s launchpad for science-backed health applications. Powered by the core CUDIS infrastructure stack (LDID → Data Aggregator → DataHub), it serves as a decentralized accelerator and community hub for longevity-focused products, programs, and DApps. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/6617ddb0a626.png) For developers, it removes the friction of building from scratch. Each project deployed through the Hub benefits from integrated privacy tools, including zero-knowledge data access, NFT-gated consent, and reward mechanisms. This allows founders to focus on innovation rather than backend setup. For users, the Hub acts like an app store for living longer. Token-gated access unlocks personalized supplement plans, biomarker assays, early disease screening tools, and more. These services are coordinated around an individual’s LDID profile, with the CUDIS AI Coach integrating them into personalized, real-time wellness protocols. From an economic perspective, the Hub establishes a positive feedback loop. Projects pay listing fees in $CUDIS, share revenue with data contributors, and can bootstrap liquidity through CUDIS-token pairs in on-chain pools. Users benefit through early access to new tools, participation in trials, and opportunities to contribute to community-led initiatives. This creates a self-sustaining ecosystem that transforms health data into a valuable resource and broadens access to the future of longevity. ## Token Economics The CUDIS token forms the financial and operational backbone of the entire ecosystem, facilitating data transactions, incentivizing participation, and enabling the tokenization of trillions of dollars in digital health assets over the coming decades. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/46603495265e.png) With a total supply of 1 billion tokens and 247.5 million in circulation at TGE (24.75%), the token is designed for equitable and sustainable value distribution. Strategic allocations—such as 25% for community, 15% for ecosystem development, and 17% for investors—are governed by thoughtful vesting schedules, ensuring long-term alignment. As the primary medium of exchange across the network, CUDIS tokens are used for settling data uploads, accessing AI insights, unlocking ecosystem features, and interacting with sub-data token trading pairs. This seamless, transparent mechanism supports a sustainable, user-centric longevity protocol, making health optimization both rewarding and accessible. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/698ec7b8e069.png) ## $CUDIS Use Cases Token holders of $CUDIS are entitled to the following benefits: 1. ***Governance***: CUDIS token holders play an active role in decentralized governance, helping shape the future of the ecosystem. Through community-driven voting, they influence key decisions such as fee structures, feature integrations, and protocol upgrades. This governance model promotes long-term stability, fairness, and continuous innovation, empowering the community to guide the evolution of CUDIS with transparency and collective ownership. 2. ***Premium Access***: The CUDIS tokens provide access to a premium suite of health and longevity solutions. Users can securely manage their wellness data, protect privacy, and access advanced tools through token-based data settlement. Additionally, token holders benefit from personalized AI-driven insights and exclusive access to top-tier longevity clinics, expert consultations, and cutting-edge treatments. 3. ***Medium of Exchange***: The CUDIS token serves as the primary medium of exchange within the ecosystem, enabling seamless transactions and service access. It covers network fees for data uploads, processing, and operations, ensuring long-term sustainability. Additionally, CUDIS tokens function as the default currency for accessing services and act as the base trading pair for subdata tokens, supporting liquidity and fractionalized ownership of valuable digital health assets. ## $CUDIS Incentive Framework The Incentive Framework integrates the staking mechanism, reward system, and overall $CUDIS economic model into a unified structure that drives ecosystem growth and sustainability. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/0c7d3dacac89.jpg) At its core, the CUDIS staking model strengthens engagement, security, and governance by encouraging users to demonstrate long-term commitment through token staking, which earns them additional rewards and fosters community stability. Simultaneously, node operators and data contributors stake tokens as collateral to uphold ethical data sharing practices and maintain high integrity standards within the network. This staking also empowers committed stakeholders by granting increased voting rights, amplifying their influence over critical ecosystem decisions, and ensuring a decentralized, community-led governance model. Complementing staking, the CUDIS Token functions as both the primary medium of exchange and an incentive mechanism that fuels activity across the ecosystem. Users earn tokens by uploading, storing, and sharing wellness data, while partners such as research institutions and AI developers utilize tokens to access data processing and analytics services, driving innovation. Node operators, providing computational power and storage, are likewise compensated with token shares. To maintain operational sustainability and support ongoing platform growth, CUDIS employs a balanced fee structure: users pay upload fees for on-chain data storage, nominal listing fees for minting and listing data NFTs, and processing fees for AI-driven analytics that sustain the CUDIS Processing Nodes (CPN). Marketplace transaction fees on NFT sales and project launch fees further finance platform maintenance and future ecosystem development. Together, these interconnected mechanisms establish a robust, scalable, and user-aligned economic model that underpins the continuous evolution and success of the CUDIS ecosystem. ## Key Drivers of Mainstream Adoption CUDIS stands as a pioneering force with a first-mover advantage in the Web3 wellness space and beyond. As one of the earliest decentralized health platforms built on the Solana blockchain, CUDIS uniquely integrates AI-powered wearable technology, token-based incentives, and user-controlled data ownership to create a groundbreaking ecosystem. This innovative combination of blockchain security, real-time AI guidance, and token rewards sets CUDIS apart from traditional health apps. Positioned at the intersection of emerging Web3 technologies and mainstream wellness, CUDIS is redefining how people manage their health, empowering users worldwide with tools to extend longevity and improve quality of life. With its unique approach and scalable model, CUDIS is poised to lead the future of decentralized, data-driven wellness on a global scale. The technological foundation of CUDIS is a critical factor in its potential for mainstream adoption, particularly its reliance on Solana's high-speed infrastructure. Solana, capable of processing over 65,000 transactions per second at costs below $0.01, ensures that biometric data can be recorded and processed on-chain in real time, a necessity for handling billions of data points from users across 103 countries. This scalability, compared to slower or costlier blockchains, enables CUDIS to deliver seamless, instant feedback and reward issuance, making the platform accessible to both tech-savvy and non-technical users. The platform's integration with Solana's growing ecosystem, including DePIN (Decentralized Physical Infrastructure Networks) and DeSci (Decentralized Science) projects, creates additional synergies that could amplify its reach. For instance, recent developments, such as the token launch on June 5, 2025, and [partnerships](https://x.com/CudisWellness/status/1930965469294719389) with entities like WalletConnect, as seen in an X post, highlight its expanding network, which could facilitate onboarding millions more users to the longevity ecosystem. ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/1e5037b37090.jpg) User engagement is another pivotal driver, driven by CUDIS's innovative earning model, underpinned by the $CUDIS token. This model turns healthy habits into economic value, with users earning points for daily activities tracked via the smart ring and app, redeemable for token rewards. The initial airdrop of 50 million tokens catalyzed user engagement, with future seasons structured to incentivize long-term retention. Beyond earning, tokens enable users to unlock advanced AI features, stake for boosted rewards, and participate in governance, blending DeFi mechanics with behavioral science. This gamification, combined with the AI coach's ability to deliver over 1 million personalized insights, sets CUDIS apart from traditional wearables like Oura, which lack both financial incentives and decentralized ownership. Finally, CUDIS's credibility and growth potential are bolstered by significant investor backing and strategic partnerships, positioning it as a scalable solution with mainstream appeal. Recent developments, such as [listings](https://www.hokanews.com/2025/06/cudis-wellness-listing-today-cudis-ring.html)on major exchanges like Binance Alpha, Bybit, Bitget, LBank and MEXC, announced on June 5th, respectively, indicate market momentum. With over 20,000 smart rings sold and 200,000 users as of date, CUDIS demonstrates strong product-market fit, suggesting it could evolve into a real-time, user-owned health database powering AI-driven longevity research, making it a compelling investment for the future of wellness. ## Future Vision ![](https://shoal.xyz/research/writing/cudis-the-ai-depin-smart-ring-democratizing/img/9efc078d9a16.jpg) CUDIS’s roadmap from Q3 2025 to 2027 envisions a transformative shift in the longevity ecosystem, leveraging its decentralized infrastructure, AI advancements, and community-driven governance to make health optimization accessible, rewarding, and globally impactful. In Q3–Q4 2025, CUDIS will lay the cornerstone of its longevity ecosystem with the beta launch of the CUDIS Longevity Launchpad, a platform to onboard longevity-focused projects, researchers, and programs. This initiative will foster collaboration between scientists, developers, and users, enabling the creation of decentralized applications (dApps) that leverage CUDIS’s secure data network. The public launch of the Longevity Data Marketplace will allow users to monetize their anonymized health data as NFTs, creating a user-empowered economy where wellness data drives both personal gain and scientific progress. Simultaneously, the release of CUDIS AI Agent Coach v2 will enhance personalization, using multi-modal AI to integrate behavioral, biometric, and environmental data for hyper-tailored longevity strategies. These developments, built on Solana’s high-speed blockchain, will solidify CUDIS’s position as a pioneer in HealthFi, attracting millions to its ecosystem by addressing the limitations of centralized platforms like Oura, which lack incentivization and data sovereignty. In 2026, CUDIS will focus on community growth and governance to sustain its momentum. The beta release of the token-gated Longevity Hub community will provide exclusive access to research-backed products, premium AI coaching, and longevity services, thereby fostering a vibrant and engaged user base. The $CUDIS token will play a central role, enabling governance through token-weighted voting, allowing users to shape platform features, research funding, and fee structures. This decentralized governance model aligns with the DeSci movement, empowering users to drive longevity science forward. The development of a multi-agent AI system will further personalize health strategies, combining data from wearables, environmental sensors, and user inputs to create dynamic wellness plans. Major brand awareness campaigns, leveraging partnerships with entities like UCLA Athletics and Solana Mobile, will expand CUDIS’s reach beyond crypto-native users to mainstream health-conscious audiences. By 2026, CUDIS aims to onboard 1 million users, capitalizing on its scalable infrastructure and growing exchange listings on platforms like Bybit and MEXC to drive adoption. By 2027, CUDIS envisions a global, decentralized longevity ecosystem that redefines wellness. The establishment of a Global Longevity Center will serve as a hub for research, education, and innovation, collaborating with universities and health institutions to advance anti-aging science. A Longevity Scientist Committee will oversee community-funded research, ensuring transparency and alignment with user priorities. The Longevity Foundation will democratize access to advanced treatments, subsidizing costs for underserved communities through token-driven funding. These initiatives will transform CUDIS from a wellness platform into a global movement, potentially managing trillions in tokenized health assets. With over 4 billion steps and 40 million heart-rate records already processed, CUDIS’s data network could power real-time, AI-driven insights for longevity research, rivaling centralized databases while prioritizing user control. Strategic partnerships and investor backing from Tim Draper and others will fuel this expansion, positioning CUDIS to lead the $247.9 billion anti-aging market by 2030. ## Conclusion Longevity isn’t just about adding years—it’s about adding healthy, high-quality years. Yet despite torrents of biometric data from wearables and steady progress in aging science, most people still have no infrastructure for turning those insights into real-world gains. **CUDIS** aims to close that gap. CUDIS’s future vision is both bold and attainable, built on its demonstrated ability to seamlessly integrate cutting-edge technology, incentive mechanisms, and community-driven governance. In an industry often hindered by poor user experiences, data exploitation, and a lack of meaningful rewards, CUDIS stands out by offering a scalable, user-centric alternative that prioritizes privacy, engagement, and value creation. Positioned at the intersection of wearable tech, blockchain, and AI-driven health, CUDIS is uniquely poised to become the next major player in the wearable technology space, transforming wellness from a solitary endeavor into a decentralized, inclusive movement. Its ambitious roadmap from 2025 to 2027 aims not only to democratize access to longevity-enhancing tools but also to empower individuals worldwide to take control of their health data and futures. With its innovative approach and growing ecosystem, CUDIS represents a compelling investment opportunity capable of reshaping how we understand and pursue long-term health and vitality. ## References 1. *Official Cudis Whitepaper. 2025. [Source](https://whitepaper.cudis.xyz/).* 2. *Reviewing the Cudis Smart Ring Health Tracker. Lightspeed. [Source](https://blockworks.co/news/lightspeed-newsletter-solana-smart-ring-health-tracker).* 3. *Science is making anti-aging progress. But do we want to live forever? The Harvard Gazette. [Source](https://news.harvard.edu/gazette/story/2024/05/science-is-making-anti-aging-progress-but-do-we-want-to-live-forever/).* 4. *Official CUDIS Smart Ring and UCLA Athletics Partnership – Athletech News [https://athletechnews.com/cudis-crypto-smart-ring-ucla-athletics](https://athletechnews.com/cudis-crypto-smart-ring-ucla-athletics)* 5. *CUDIS Raises $5M Seed Round Led by Draper Associates – Chainwire [https://chainwire.org/2024/09/18/cudis-secures-5m-seed-led-by-draper-associates-to-challenge-oura-ring-in-the-wearables-market-with-blockchain-and-ai](https://chainwire.org/2024/09/18/cudis-secures-5m-seed-led-by-draper-associates-to-challenge-oura-ring-in-the-wearables-market-with-blockchain-and-ai)* 6. *Oura Raises $200M, Reaching $5.2B Valuation – Fierce Healthcare [https://www.fiercehealthcare.com/health-tech/oura-closes-200m-round-boosting-smart-ring-makers-valuation-52b](https://www.fiercehealthcare.com/health-tech/oura-closes-200m-round-boosting-smart-ring-makers-valuation-52b)* 7. *Oura Ring Official Website*https://ouraring.com 8. *UCSF – Fitness Trackers Could Help Spot Illness Early [https://www.ucsf.edu/news/2025/06/430166/your-fitness-tracker-could-help-doctors-spot-health-risks-early](https://www.ucsf.edu/news/2025/06/430166/your-fitness-tracker-could-help-doctors-spot-health-risks-early)* 9. *NCBI – Applications of CRISPR–Cas9 in Regenerative Medicine and Aging [https://pmc.ncbi.nlm.nih.gov/articles/PMC10980556](https://pmc.ncbi.nlm.nih.gov/articles/PMC10980556)* 10. *Scientific American – Could Humans Live to 150? [https://www.scientificamerican.com/article/humans-could-live-up-to-150-years-new-research-suggests](https://www.scientificamerican.com/article/humans-could-live-up-to-150-years-new-research-suggests)* 11. *McKinsey Health Institute – Adding Years to Life and Life to Years [https://www.mckinsey.com/mhi/our-insights/adding-years-to-life-and-life-to-years](https://www.mckinsey.com/mhi/our-insights/adding-years-to-life-and-life-to-years)* 12. *McKinsey – Future of Wellness: Consumer Trends [https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/future-of-wellness-trends](https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/future-of-wellness-trends)* 13. *Research and Markets – Complementary and Alternative Medicine for Anti-Aging Forecast [https://www.researchandmarkets.com/reports/5526495/complementary-and-alternative-medicine-for-anti](https://www.researchandmarkets.com/reports/5526495/complementary-and-alternative-medicine-for-anti)* --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.** All posts are the author's own, not the views of their employer.This post has been created in collaboration with the CUDIS team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research* --- # Fairblock: Incorruptible Markets and Confidential Stablecoin Rails > Fairblock is building the Incorruptible world computer that unlocks secure, trust-minimized applications crucial for the next generation of institutional-grade DeFi systems. - Publisher: Shoal Research (https://shoal.xyz) - Category: Privacy & ZK - Published: 2025-05-28 - Canonical: https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/ - Keywords: AI agents, stablecoins, crypto, DeFi, MEV, RWA, tokenization, privacy, security, infrastructure, gaming, Privacy & ZK ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/0af1eefe7f30.jpg) --- Crypto is at a crossroads. The last decade brought remarkable innovation in defi, gaming, and tokenized assets, yet the user experience remains fundamentally broken. Exploits are rampant, manipulation is normalized, and meaningful institutional participation remains out of reach. What was supposed to be an open financial system has become a high-stakes battleground, where sophisticated actors consistently outmaneuver honest users. Institutions cautiously watching from the sidelines cite systemic data leakage, integrity risks, and compliance uncertainties as persistent blockers to meaningful adoption. Crypto, despite all its potential, remains plagued by toxicity. One of the most overlooked gaps is the lack of confidential and compliant stablecoin infrastructure, a foundational layer for real-world payment and liquidity flows. While stablecoins are gaining traction as programmable, borderless money, their usage remains highly transparent by default. This is a non-starter for enterprises handling sensitive transactions like payroll, settlement, or treasury operations. Institutions require flows to remain confidential yet audit-ready, a balance that current protocols fail to strike. Some of the major players, like Circle, are [actively looking for a solution](https://www.circle.com/blog/welcoming-the-gateway-team-to-circle). The scale of this issue cannot be overstated. In the past year alone, DeFi lost over [$1 billion](https://defillama.com/hacks) to hacks and exploits, while an additional [$2 billion](https://cointelegraph.com/news/1-8-billion-lost-web3-hackers-fraudsters-2023-immunefi) evaporated due to manipulative tactics like front-running or other predatory behaviors. This toxicity goes beyond financial damage, it's eroding trust and credibility, essential pillars for sustained growth. Every transfer on public blockchains, payroll transactions, or strategic trade were visible to the entire world, which is the reality for crypto today. Traders routinely see their carefully planned strategies compromised, gamers find their moves publicly exposed, and enterprises risk sensitive commercial strategies leaking onto public blockchains. This nature of public blockchains, far from being empowering, often empowers only the most sophisticated, opportunistic actors who thrive on exploiting market inefficiencies. In the Web2 world, confidentiality is given. Banking, healthcare, and communications all rely on it. Web3, however, has struggled to balance confidentiality with decentralization and regulatory compliance. The absence of onchain confidentiality has stifled the growth of essential applications, from private transfers to secure financial services. Yet emerging technologies like decentralized dark pools (pools that conceal transaction details until settlement) and modular onchain confidentiality frameworks offer hope. These solutions promise to protect user anonymity while enabling regulatory oversight, fostering an environment where confidentiality and compliance coexist. ## Detoxifying Web3: Toward Trustworthy and Corruption-Free Markets On most transparent public blockchains, every pending trade, bid, game move, or transaction intent is public knowledge before it is finalized. This open mempool (or memory pool of pending transactions waiting to be picked up) and state allows opportunists to exploit information that should have been confidential. The absence of confidentiality has resulted in several well-documented issues that degrade user experience and discourage participation: - **Institutional and Enterprise Reluctance:** Banks, hedge funds, and corporations have strict confidentiality needs. On public chains, *anyone* can observe wallet balances, trading strategies, or business contracts. It’s no surprise that many institutions avoid public blockchains for sensitive operations; no serious trading firm wants to broadcast its positions in real-time, and privacy-sensitive users are similarly deterred. In short, transparent blockchains “cut out” institutions and confidentiality-conscious users from participating​, limiting the ecosystem’s growth into traditional finance and Web2 industries. - **Frontrunning and Forced Liquidation:** Sophisticated actors (like arbitrage bots or miners) can see your pending transactions and *insert their own* to profit at your expense. For example, they might detect a large buy order and purchase the asset first, driving up price (a classic *frontrun*), or sandwich your trade between their own orders. Such tactics have siphoned value from regular users and are only possible because transaction details are exposed before execution​. This is akin to someone eavesdropping on a sealed-bid auction and then outbidding you with knowledge of your bid – an unfair advantage built into transparent ledgers. - **Broken Onchain Gaming and Applications:** Many interactive applications (Pari-mutuel betting, AI agents) require secrets to function correctly. Consider a strategy game where players’ moves need to be hidden until a reveal or an AI application that uses proprietary data. On a public chain, all moves and data are exposed, so opponents can cheat. Developers are essentially prevented from bringing popular internet applications onchain because any secret logic or data would be immediately exposed​. This has stunted use cases like fair onchain gaming, confidential auctions, or AI models that require hidden data or verifiable randomness. - **General Data Exploitation and User Tracking:**Outside of outright attacks, transparency means user activity is fully traceable. Malicious parties or even marketers can monitor everything you do onchain – trades, transfers, votes – building profiles and potentially using that against you​. Every onchain interaction leaks information. This “public information leakage” leads to asymmetric advantages where those with analytics tools can manipulate or influence less-informed users​. It’s the opposite of the level playing field that decentralization promised. Crypto shouldn’t require complex safeguards to uphold trust and fairness. Preventing corruption should be intuitive and integrated by default. This is where Fairblock steps in: the world's Incorruptible Computer. Fairblock is on a mission to enable incorruptible markets and machines using dynamic confidential computing. Unlike simple cryptographic libraries or privacy-focused chains, Fairblock provides a modular and programmable confidentiality solution that integrates seamlessly into existing blockchain ecosystems. It is not a privacy patch. It’s a programmable coordination layer that unlocks new classes of applications through built-in confidentiality, compliance, and composability, by leveraging cutting-edge cryptographic techniques such as threshold identity-based encryption (IBE), homomorphic encrypion (HE), and multi-party computation (MPC). Web3 has struggled to balance confidentiality with decentralization and compliance, stifling crucial applications from secure transfers to institutional finance. Fairblock offers a path forward: dynamic confidentiality that protects onchain interactions until verifiable events (e.g., price thresholds, block heights) occur, after which data can be transparently revealed and audited. Unlike traditional dark pools, which rely on centralized operators, Fairblock’s approach ensures that confidentiality and compliance coexist through selective disclosure and decentralized compliance frameworks. This means that pre-transfer compliance checks and post-execution auditability can be enforced without revealing transaction details to the public, a fundamental improvement over existing privacy solutions. To put it simply, Fairblock isn’t just about privacy, it’s about efficiency, security, and enabling fair markets. Much like how CoW Swap and Flashbots solved real user problems by protecting traders from frontrunning and several other market inefficiencies, Fairblock gives users a secure, compliant, and decentralized way to transact without the risks of frontrunning, information leaks, or regulatory uncertainty. FairyRing is Fairblock’s native blockchain. Currently live on testnet across EVM ecosystems and Cosmos appchains, it is designed to help developers build confidential applications. By providing threshold cryptographic techniques and selective disclosure mechanisms, Fairblock empowers users and institutions to interact with privacy, fairness, and security without sacrificing the benefits of decentralization. Blockchain’s evolution into a credible financial infrastructure depends on solving the privacy crisis. Fairblock’s modular confidentiality solutions pave the way for large-scale adoption by ensuring that confidentiality is not just a feature but a fundamental pillar of the decentralized economy. Like the car replacing the horse, confidential transactions will soon be the default and not just an option, but a necessity. These issues are not theoretical. They are *direct consequences* of the transparent-by-default design. As the Fairblock team succinctly put it, today’s blockchains “leak the contents of your messages, decisions, and strategies… before they are executed,” giving privileged actors undue advantages and “negatively impacting blockchain experiences” in multiple ways​. Without some form of confidentiality, blockchains will continue to be plagued by frontrunning bots, hesitant institutional adoption, and an inability to support many real-world applications beyond simple token transfers. The need for a solution is clear: if we want decentralized networks to truly compete with Web2 systems (which do keep most data confidential by default), we must bring **confidential computing** into the blockchain world. In this article, we will delve into Fairblock’s unique approach to onchain confidentiality, its key components like FairyRing and FairyKit, and how its modular, programmable confidentiality solutions are setting a new standard for blockchain confidentiality with compliance and decentralization. Before we get started, it’s important to define a few terms that will come up often: - Threshold IBE[​](https://docs.fairblock.network/docs/glossary#threshold-ibe): An identity-based encryption is a form of encryption based on some identifying conditions. Fairblock uses threshold IBE so that no single party controls the decryption keys. Instead of "identity," Fairblock uses "conditional IDs," which are less about actual identity and more about various variables, often related to a chain's global state, such as block height. This approach introduces the minimal bandwidth compared to other MPC and FHE schemes. - Threshold encryption[​](https://docs.fairblock.network/docs/glossary#threshold-encryption): Threshold encryption is a form of cryptography that allows a private key to be derived as long as a certain threshold of network participants come together to aggregate their private key shares. Fairblock uses Threshold IBE, which allows validators to generate a share of the private key using their Master Secret Keyshare once a condition (ID) is met onchain. Validators then submit their private key shares to FairyRing, which can construct the derived private key once the threshold of validator key share submissions is met. - Public key[​](https://docs.fairblock.network/docs/glossary#public-key): A public key is a large cryptographic value that is used to encrypt data. The public key is publicly visible and used to identify some encrypted data. The public key is derived from the private key, a randomly generated cryptographic value that is needed to decrypt data. In asymmetric encryption and its derivatives, public keys are openly known, while private keys are only made available to owners or receivers of some data and signify true owners of data. In Fairblock, we use a Master Public Key (MPK) that is used to encrypt every transaction within an epoch. The MPK is discarded after the end of an epoch. - Block height[​](https://docs.fairblock.network/docs/glossary#block-height): The block height is the current length of the blockchain network. It is the number of blocks preceding the current block in a network. The height of the genesis block of a blockchain is zero. - Derived private key[​](https://docs.fairblock.network/docs/glossary#derived-private-key): The derived private key is a unique key corresponding to a certain encryption condition (ID) and is required for a chain to decrypt encrypted transactions. The derived private key is obtained by aggregating a threshold number of derived private key shares. - Frontrunning[​](https://docs.fairblock.network/docs/glossary#frontrunning): Frontrunning is an example of predatory MEV ([Maximal Extractable Value](https://ethereum.org/developers/docs/mev#mev-extraction-generalized-frontrunners)), where MEV searchers can observe a user's unexecuted profitable trade in a mempool and manipulate the ordering of transactions within a block. The most common type of frontrunning is sandwich attacks. ## Fairblock: The Missing Piece in Crypto’s Tech Stack ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/bcf2513da27d.png) Fairblock emerges to fill the critical gaps discussed above with its Incorruptible Compute a decentralized cryptographic engine designed to detoxify Web3 by transforming markets, stablecoins, and machines into secure, fair, and performant environments. Whether it's trading, lending, or auction execution, Fairblock ensures each action proceeds without manipulation or information leakage. Fairblock solves this by acting as the confidentiality backbone of Web3. It encrypts any user interaction, such as swaps, loan bids, or private data exchange, and stores the decryption keys with a decentralized validator set. The data remains confidential until a predefined condition, like a block height or price threshold, is met. Once triggered, the information is decrypted and the transaction is settled. The entire process remains fully verifiable after execution for audit and compliance purposes. Much like how Cloudflare secures internet traffic, Fairblock delivers confidentiality as a service for Web3. It ensures incorruptibility without compromising transparency, setting the foundation for trust, institutional access, and next-generation applications. Blockchains open up the world of financial instruments and manipulation, which are controlled by corporate bodies and governments, aiming to return power to individual users. This provides users with the tools and opportunities to correct inefficient, flawed financial practices that were widespread in the past. Additionally, blockchains were designed in a way that makes them easily manipulable; for instance, immutable transactions can still be affected at the mempool level. Furthermore, the future of blockchains require more than what we are used to: memecoin pumps, centralization trends, unused applications, and less secure blockchain-based applications that throw businesses and users into turmoil as they occasionally face public leaks of on-chain activities and data. For instance, despite the launch of numerous applications on the blockchain, there is a scarcity of compelling, user-friendly applications that display benefits or tackle key issues as preached in the past. On the other hand, many blockchain-based applications have begun exhibiting centralizing tendencies either through governance models or token distributions. This contradicts the core principles of decentralization and damages the vision of the community. Fairblock solves all the issues stated above via its key products, ***FairyRing and FairyKit***. Tackling “***onchain confidentiality, which is the greatest unsolved crisis in crypto,”*** as stated by founder, Peyman Momeni, Fairblock has a unique approach. It does not rely on slow or centralized, one-size-fits-all solutions; rather, it tailors and optimizes the security and performance of the cryptographic network for each specific DeFi and AI application. For instance, it hosts multimodal Multi-Party Computation (MPC), Homomorphic Encryption, Trusted Execution Environment (TEE), Zero-Knowledge (ZK) solutions to optimize performance and guarantee confidentiality for various use cases, including private transfers, lending, clearing markets, hidden information GameFi, confidential AI, and private data monetization. . ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/d471a3572e64.jpg) The use of MPC cryptographic computations on Fairblock allows it to easily run DeFi, AI, and gaming economies for cheap and fast execution that allows applications to thrive in ecosystems such as EVM (L2s included), Solana, and Cosmos. To solve the issues around onchain confidentiality, Fairblock comprises two core elements: FairyRing and FairyKit. FairyRing abstracts away intensive cryptographic operations for applications built within its chain as well as those built on alternative blockchains. For external partners, FairyRing distributes confidential execution via FairyKit, which plugs into any protocol and application to bring one-click confidentiality to any app or user that requires it. ## FairyRing & FairyKit ***FairyRing*** is a dynamic and decentralized network that hosts applications optimized for secure and performant confidential computing. This means when apps (either native apps or external apps) are integrated into the Fairblock ecosystem, they have active communication with the FairyRing chain and can frictionlessly integrate with any chain. Having this interconnected network of chains deepens liquidity between apps and bridges the gap of fragmentation. This helps to increase the robustness of the network as it abstracts away cryptographic computations, including condition verification, threshold key generation, and execution of encrypted transactions. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/562a9a410595.png) The FairyRing network is built on the Cosmos SDK, incorporating both the benefits of the Cosmos chain and its own novel features. One of the key advantages is that FairyRing does not require relayers, since the confidential computation and contract callbacks are native functions of the hosting chain. Another key benefit is that applications built on FairyRing inherit the Cosmos chain's high performance. Thanks to Tendermint’s horizontal scaling, validators can run multiple chains in parallel, ensuring that workloads are distributed and throughput remains high. Consequently, any application launched on the FairyRing can operate efficiently, free from common bottleneck issues. FairyRing allows developers to build confidential applications. In EVMs and other blockchains, every transaction, contract call, and state change is public, which carries aforementioned risks like frontrunning and data leaks. FairyRing eliminates these risks by leveraging a suite of confidential computation schemes. A flagship primitive is threshold identity-based encryption: transactions are encrypted, stored onchain, and decrypted only when preset conditions such as reaching a target block height, are met. ***FairyKit*** is a module that extends the same confidential guarantees to both native Fairyring applications and external chains. It is a one-click integration package that can be plugged into any protocol and application. There are two main integration routes that the chains must follow: 1. The use of “FairyKits” is specific to the blockchain that is integrating with Fairblock. This allows for custom setups, in which the partner network handles some or all of the decryption and encryption. No changes to the core protocol architecture are required. 2. In the “co-processing” route, FairyRing handles the all the cryptographic computations adn execution, and returns the end state to the integrating network. For instance, an auction application that allows users to submit encrypted bids can off-load all cryptographic processing to FairyRing, which will return the final state to the auction app. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/2963771b7e3e.jpg) FairyKit ships adapters for EVM, Cosmos, XRP Ledger and Rust-based chains, delivered as modules, smart contract libraries, or execution-layer hooks, depending on the needs of the application's logic and architecture. ## The Fairblock Ecosystem - Application First Approach The Fairblock ecosystem is made up of several native and external applications. These applications showcase the variety of use cases for onchain encryption across DeFi, AI, gaming, randomness, and governance. As Web3’s confidential processing layer, Fairblock recognizes that infrastructure is only a means to an end: applications. From day one, the team is launching a suite of DeFi products powered by confidentiality. These serve both as proof-of-concept and as valuable services in their own right, showing users what’s now possible with onchain confidential computing. Fairblock specifically offers tailored solutions in three of the most impactful verticals: ### Incorruptible DeFi Fairblock enables a new class of high-integrity DeFi applications through programmable confidentiality. By introducing encrypted intents and sealed-bid auctions, Fairblock replaces legacy coordination methods with trustless, manipulation-resistant infrastructure, that is ideal for trading, lending, and token distribution. - **Encrypted Intents & Bids for Solvers**Fairblock allows users and solvers to submit encrypted messages, ensuring no information is leaked before execution. This not only supports confidenital limit orders and swaps, but also enables a novel use case: *sealed-bid auctions for solvers*, an upgrade over off-chain RFQ models used by platforms like Anoma, Squid, and UniswapX. With Fairblock, solver bids remain confidential until decryption triggers are met (e.g., block height or escrow lock), preventing censorship, favoritism, and price manipulation. - **Sealed-Bid and Leaderless Auctions:**Fairblock’s leaderless sealed-bid auctions eliminate sniping, bid shading, and collusion by keeping all bids hidden until the auction closes. This mechanism is used for:**Fixed-rate lending**, where both borrower bids and lender asks are encrypted, producing a market-driven clearing rate without backend games.**Fair token launches**, replacing Dutch auctions with a single clearing price. - Front-running and forced-liquidation protection: Applications like FairyCow Swap protect transaction details until execution, preventing exploitation through front-running or forced liquidations. - Private lending and clearing markets: Confidential markets like Fairates and SettleX offer robust lending primitives with transparent, decentralized, and trustless execution without backend games. ### Institutional Confidential and Compliant Stablecoins - Large institutional transfers without market impact: Fairblock’s confidential solutions enable institutions to move significant sums securely, minimizing market disruption. - Addressing confidentiality blockers for LPs: Ensuring privacy to overcome institutional barriers related to data leakage and confidentiality concerns. - Private balances and transfers compliant through decentralized selective disclosure (MPC): Fairblock combines MPC and ZK proofs to enable compliant confidential transfers, suitable for normal and institutional users. - Fairblock enables encryption of transaction amounts, unlike ZK-only solutions, which typically only obscure address linkages while still exposing amounts and activities. With Fairblock, address anonymity is optional, and confidentiality can be fully customized. - Fairblock’s MPC and ElGamal-based approach offers significantly higher efficiency and decentralization compared to FHE counterparts, which often suffer from performance bottlenecks and centralization risks in practical deployments. ### Incorruptible AI - Inference on encrypted data (e.g., trading agent, balancing pools): Enables AI models to operate securely on encrypted data, preserving confidentiality and integrity during computations. - Unruggable AI models through MPC: AI models protected by MPC and TEEs, ensuring secure, unstoppable operations. - Private data marketplace: Fairblock allows secure monetization of private data for AI model training without compromising data confidentiality. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/05e087900f86.jpg) To implement its solutions in the above-mentioned verticals, Fairblock's integration and distribution strategy includes two complementary approaches: 1. **Dine-In** 2. **Delivery** The Dine-In ecosystem features native confidential applications (cApps) developed directly within Fairblock’s FairyRing chain, already live on testnet with over one million transactions. Flagship offerings include credible DeFi products such as fixed-rate lending markets, sealed-bid auctions, and dynamic intent matching (collaborations with Anoma, Squid, and CoWSwap). Additionally, Fairblock hosts unstoppable AI models through MPC and TEEs (e.g., Phala), confidential lending and clearing markets (Fairates, SettleX), compliant confidential transfers, private data monetization for AI, and engaging hidden-information GameFi applications. The Delivery motion extends confidentiality solutions via strategic partnerships, starting with Arbitrum. Fairblock’s dynamic confidentiality modules integrate natively with EVM rollups (Plume, Syndr, Xai, OP Stack), appchains (Celestia's Rollkit, AltLayer, Polymer), and AltL1s (Monad, Osmosis, Sei). In future phases, Fairblock will leverage coprocessor architectures to extend dynamic confidentiality directly into Ethereum and Solana ecosystems, significantly broadening the reach and impact of onchain confidential computing. First, let's examine some of the use cases made possible by leveraging Fairblock's infrastructure and capabilities. Then, we'll explore the specific dine-in applications within the broader Fairblock ecosystem. ### Confidential Stablecoins & Real World Assets For Institutional Adoption Stablecoins are rapidly becoming the backbone of global financial infrastructure, yet the current transparent nature of blockchain transactions poses significant barriers for institutional adoption. Enterprises handling payroll, treasury operations, settlement flows, and strategic financial transactions require confidentiality not in terms of anonymity, but specifically regarding transaction amounts and strategic details. Fairblock addresses these critical needs through a unique cryptographic solution built on Threshold ElGamal decryption combined with Multi-Party Computation (MPC). Unlike zero-knowledge (ZK) solutions, which primarily obscure the link between addresses but leave amounts and transaction patterns exposed, Fairblock encrypts transaction amounts directly. This targeted confidentiality is complemented by the integration of lightweight ZK proofs to validate the input amounts. Crucially, businesses typically prioritize preventing sensitive data leakage over address anonymity due to compliance considerations and practical needs for auditability. Fairblock’s technology significantly surpasses Fully Homomorphic Encryption (FHE) based projects such as Zama, Inco, and Fhenix in terms of speed and decentralization. FHE methods require computationally heavy operations and typically rely on centralized coprocessors, optimistic assumptions, and trusted relayers, introducing points of centralization and potential security risks. Fairblock’s MPC and Threshold ElGamal approach eliminates these centralized dependencies, ensuring robust decentralization, efficient batch decryption, and selective disclosure, delivering greater scalability and performance. Fairblock’s solution has attracted the attention of major industry players, aligning with recent market trends where leading stablecoin issuers and payment giants are actively seeking confidentiality enhancements. [PayPal’s recent interest in integrating confidential transfers](https://solana.com/news/paypal-pyusd-on-solana#:~:text=Confidential%20Transfers.%20Allowing%20merchants%20the%20option%20to%20maintain%20confidentiality%20of%20transaction%20amounts%20while%20maintaining%20visibility%20of%20other%20transaction%20details%20for%20regulatory%20purposes.) on Solana and [Circle’s acquisition of on-chain privacy-focused protocol Gateway](https://www.circle.com/blog/welcoming-the-gateway-team-to-circle) illustrate the increasing importance of confidentiality in mainstream financial transactions. Fairblock is actively collaborating with key blockchain and stablecoin infrastructure partners, including Noble, Ripple, Plume, Hyperliquid, Arbitrum Foundation, Dowgo, Axelar, and Cosmos Hub, to deploy its encrypted transfer capabilities broadly across ecosystems. Additionally, Fairblock’s confidentiality infrastructure unlocks innovative auction-based TradFi use cases, such as Treasury bill auctions and other institutional asset distributions. Leveraging Fairblock, institutions can securely execute sealed-bid auctions without leaking strategic bidding data, enhancing market integrity and fairness. Another notable example within the Fairblock ecosystem is SettleX, the first confidential clearing and settlement solution specifically built for institutional stablecoin use. Cross-chain stablecoin flows are currently fragmented, costly, and highly visible, exposing sensitive trading information. SettleX mitigates these issues by netting transactions across chains, securely settling only net deltas, significantly reducing capital inefficiency, bridging costs, and protecting counterparty privacy. By combining MPC with Trusted Execution Environments (TEE), an approach Fairblock has also implemented with Cycles, SettleX provides robust security without solely relying on hardware-based TEE or MPC assumptions alone. Through these targeted confidentiality solutions, Fairblock is enabling a new era of institutional adoption and strategic financial operations on-chain, redefining how real-world assets and stablecoin transactions can securely and compliantly scale within decentralized ecosystems. ### Incorruptible fixed-rate lending on Arbitrum and Hyperliquid Imagine a lending protocol where interest rates or loan terms are determined via a sealed-bid auction among lenders, rather than a fixed formula. Lenders submit bids (e.g. the lowest interest rate they’re willing to offer or the highest they’re willing to pay to borrow) *encrypted via Fairblock*. Because bids stay confidential until the auction ends, no participant can adjust their bid reactively and no “last-minute sniping” or collusion is possible. The result is a fair market-driven rate discovery for loans. This sealed-bid auction framework, internally referred to as DeBid, represents Fairblock’s general-purpose auction engine deployed on Arbitrum One and Orbit chains using Stylus. Fairates, a fixed-rate lending market, is one of its first real-world implementations. In fact, Fairblock’s solution for sealed-bid on-chain auctions was recently recognized in [Arbitrum’s development initiative](https://blog.arbitrum.io/stylus-sprint-recipients/#:~:text=%23%20DeBid%20) – *“Fairblock is revolutionizing onchain auctions by building sealed-bid infrastructure using Stylus… enabling new privacy-preserving use cases that weren’t previously possible onchain.”* By applying this to lending, we get more efficient and equitable lending markets that could attract institutional lenders who otherwise fear information leakage in DeFi. ### Intent-Based Trading and Dynamic Price Discovery In collaboration with intent-centric protocols like Anoma, CoWSwap and Squid , Fairblock’s tech can power hidden “intent” orders. A user might express an intent to trade asset X for Y under certain conditions, which on current DEXs would be translated into a visible limit order or a transaction in a mempool. Instead, using Fairblock, the intent can remain *encrypted* until it is matched with a counterparty. Various market makers or counterparties can bid to fill the intent, also in a sealed-bid manner, and once a match is found and finalized, the trade is executed and only then details are revealed. This creates a dynamic price discovery process where the market finds the best execution price for a trade *without broadcasting the intent to everyone*. Such functionality is invaluable for large trades (to avoid price slippage from advance knowledge) and is aligned with what leading projects are exploring. By partnering with Anoma (an intent-focused layer-1) and integrating with cross-chain liquidity hubs like Squid, Fairblock is ensuring these confidential intents can even operate across multiple networks, further scaling the liquidity and reach of decentralized economies. ### Sealed-Bid Token Launches (Fair Token Distribution) When new tokens are released (through IDOs, ICOs, or auctions), savvy players often game the process by creating gas wars on Ethereum or Solana. Fairblock enables a better model: sealed-bid token launches in which each participant submits a bid for the token (how much they’re willing to pay or how many tokens they want) confidentially. All bids are revealed simultaneously at the close, and an algorithm determines the clearing price and allocations. Because no one knows others’ bids in advance, every bidder plays on equal footing, and outcomes can’t be skewed by real-time insider info. This approach can prevent the typical frenzy and network congestion of token launches, leading to more stable price discovery. Fairblock unites champions for “fair token launches” and makes dynamic pricing for intents far simpler with sealed-bid, leaderless auction mechanics . The idea is to bring IPO-like fairness to crypto token distributions, which will fuel broader participation and build trust in these events. ## Some specific examples of dine-in apps ### FairRates: Fixed Rates, Not Fixed Games **FairRates**, built by Fairblock, brings a new paradigm to fixed-rate lending, one where confidentiality and decentralization converge to create fair, efficient lending markets. Like some of the existing applications today, FairRates uses sealed-bid auctions to discover market-clearing interest rates, ensuring that all borrowers and lenders settle at the same rate without favoritism or last-minute sniping. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/31b5e6b17996.jpg) But FairRates stands apart in two critical ways. First, it’s built for high-performance EVM DeFi hubs like Arbitrum and Hyperliquid, drastically reducing gas costs and enabling real-time participation. Second, and most importantly, it eliminates reliance on centralized infrastructure. Other systems like Term rely on centralized servers to reveal encrypted bids, introducing trust assumptions and potential points of failure. In contrast, FairRates uses Fairblock’s MPC infrastructure via FairyRing to securely decrypt and reveal bids only when predefined auction conditions are met. This ensures confidentiality throughout the bidding process, trustless execution, and zero reliance on fallback mechanisms or centralized servers. The result is a robust lending primitive: one rate for all, transparently discovered, and zero backend games. FairRates is actively supported by the Arbitrum Foundation and is being deployed on both Arbitrum One and Hyperliquid as part of Fairblock’s broader effort to bring sealed-bid infrastructure to next-gen DeFi ecosystems. It represents a foundational use case for intent-based lending, delivering the performance, integrity, and decentralization that DeFi was always meant to embody. Explore FairRates: https://fairates.fairblock.network ### FairyCow Swap The FairyCow Swap is a demo application of Fairblock's modular programmable encryption added to an existing intent-based EVM application (CoW Swap) limit orders. Encrypting trade intents ensures that transaction details such execution time, amount, liquidation trigger, stop-loss price remain confidential until execution and cannot be exploited. **FairyCoW Swap** is available on the **Sepolia testnet**, demonstrating how programmable encryption can be applied to existing decentralized exchanges. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/d17eac2dc0c4.jpg) Explore: [FairyCow Swap](https://swap.fairycow.fi/#/11155111/limit/WETH?tab=open&page=1) ### FairEx FairEx introduces an interesting confidentiality-focused trading solution on Arbitrum, enabling users to encrypt their swap orders and protect sensitive trading information from premature exposure. Operating as a UniswapV2-style decentralized exchange on Arbitrum's Orbit testnet, the platform specializes in handling encrypted limit orders that remain confidential until specific market conditions are met. Users can specify precise limit order conditions, such as executing a transaction when the ETH/USDC price reaches $500, with their orders remaining encrypted until the price trigger. When the specified price threshold is reached, the system triggers a decryption key request to FairyRing. The validators then generate and verify the decryption key. Once validated, the key is transmitted to Arbitrum's testnet, enabling secure order execution while maintaining confidentiality throughout the entire process. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/bbd1152ea97b.jpg) ### Time Machine: Confidential Prediction Markets with Delayed Decryption **[Time Machine](https://timemachine.fairblock.network/prediction)** is a prediction market application built using Fairblock’s programmable confidentiality infrastructure. Unlike traditional onchain prediction markets where all bets and outcomes are visible in real time, Time Machine leverages delayed decryption to unlock a new design space for fair and manipulation-resistant forecasting. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/edc516152ff5.jpg) Each prediction or vote is encrypted and submitted onchain, with decryption triggered only after a predefined condition, such as a specific block height or timestamp is met. This approach ensures that no participant can reactively influence outcomes or copy the positions of others before reveal. As a result, Time Machine eliminates frontrunning and bandwagon biases that often plague transparent prediction markets. Key features: - **Sealed Predictions**: Participants’ responses are fully encrypted until the end of the round. - **Public Auditability**: Once the decryption trigger fires, all inputs are revealed and outcomes computed in a verifiable manner. - **Custom Trigger Logic**: Developers can define arbitrary conditions such as block height, oracle feed resolution, or community governance decision as triggers for decryption. Time Machine is a strong proof-of-concept for how Fairblock’s infrastructure can empower decentralized forecasting, secure DAO voting, and future onchain governance applications where secrecy until a reveal event is crucial to system integrity. ## Architecture Overview: Fairblock ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/7493b0d53f10.jpg) The Fairblock architecture consists of several components. 1. ***FairyRing*** - Fairblock's native chain that abstracts away heavy cryptography for both native applications and those built on alternative blockchains. 2. ***FairyKit*** - Fairblock Integration packages that embed one-click confidentiality into any protocol and application. 3. ***[Encryption SDK](https://docs.fairblock.network/advanced/encrypt_tx.md)*** - Client-side software used to encrypt and submit transactions to the Destination Chain. Once the encrypter is integrated with applications (front-end or wallets), users can seamlessly encrypt their transactions. End-to-end encryption happens locally within the browser and does not rely on any third parties. 4. ***Destination Chain*** - The chain storing encrypted transactions, receiving public keys and secret keys from FairyRing, and where the transactions are executed after decryption. This can be FairyRing itself with native applications or external chains working with FairyRing. 5. ***[Relayers](https://docs.fairblock.network/advanced/fairyport.md)*** - The communication services that listens and coordinates decryption requests between the FairyRing and destination chains (e.g. FairyPort, IBC, Axelar). The core components of Fairblock define how users interact with the protocol and ensure its proper functionality. An example of the user flow of the Fairblock protocol is: ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/7bc202b98a34.jpg) 1. User submits an encryption transaction with decryption parameters 2. Transaction is transferred to the Encryption Software Development Kit (SDK), where it is securely held in the destination chain’s mempool 3. When smart contract conditions are met, relayers request decryption keys from FairyRing 4. FairyRing verifies the request, delivers the derived private key, and sends it back to the destination chain. 5. The transaction decrypts and executes, completing the state change while keeping the data safe until specified parameters. ## Key Features of Fairblock Fairblock has several key features: ### Composable With Fairblock, developers can integrate confidentiality features into the blockchains and applications they already use without switching to a new ecosystem, thereby solving further fragmentation. Using Fairblock’s FairyRing and FairyKit, they can build confidentiality-preserving smart contracts and applications in their preferred environment. This allows them to enhance security and confidentiality without compromising compatibility or requiring major architectural changes. ### Chain Agnostic FairyKit is designed to seamlessly integrate with major Layer 1 (L1) and Layer 2 (L2) blockchains. Whether a blockchain operates as a standalone L1 or scales via an L2 solution, FairyKit ensures smooth compatibility without requiring fundamental changes to its architecture. This allows projects across different ecosystems to leverage Fairblock’s encryption and decryption capabilities while maintaining interoperability and efficiency. ### Performant and Scalable Fairblock offers linear bandwidth scaling, and avoid using heavy one-size fits all cryptographic solutions. As network demand increases, performance scales efficiently without bottlenecks. Additionally, its encryption processes run in tens of milliseconds, ensuring that transactions remain fast and responsive. This combination allows users to experience seamless confidentiality protections without delays, making confidential transactions as smooth as standard ones. ### Dynamic Encryption needs vary across different applications and user needs. Fairblock’s multimodal cryptographic computation is highly customizable, allowing developers to mix and match MPC, FHE, TEE, and ZK schemes to meet specific performance and security needs. ## Competitive Landscape The race to build confidentiality-preserving infrastructure in crypto is heating up, with multiple projects tackling shared private states using different approaches. This has resulted in much excitement in the confidentiality applications and the prospect of new credible economies. Onchain confidentiality aims to achieve a ***shared private state*** amongst users. It is still in its early stages, defined by fragmented solutions and narrow use cases. Fairblock is not a generic confidentiality project, it is an ecosystem-first, multichain infrastructure platform purpose-built to deliver real-world utility across DeFi, AI, gaming, and more. With direct integrations into partner chains and applications, Fairblock serves as the confidentiality backbone for high-performance, composable systems that demand both security and speed. Unlike traditional privacy-focused blockchain solutions, Fairblock is a practical enabler of real-world DeFi use cases. It distinguishes itself by optimizing for performance and scalability without compromising on confidentiality. Compared to Zama, which utilizes FHE to enable computations on encrypted data, Fairblock focuses on balancing confidentiality with performance. FHE provides strong confidentiality by allowing operations on encrypted data, but heavy computation makes it unsuitable for most DeFi applications. Fairblock, on the other hand, employs Threshold Identity-Based Encryption (TIBE) while integrating MPC, ZK, and TEEs, ensuring faster, scalable, and privacy-preserving operations that are suitable for real-time blockchain applications like auctions and decentralized trading. When comparing Fairblock with Nillion, the two share a focus on MPC but differ significantly in their approaches and use cases. Nillion provides a chain-agnostic network with an orchestration layer (Petnet) designed for general-purpose AI, DeFi, and computation applications. Its MPC protocols support secure computation and storage across multiple chains but lack native integration with DeFi use cases. In contrast, Fairblock is tailored for EVM and Cosmos chains, specifically enabling privacy for DeFi use cases like auctions, liquidations, and lending markets. By focusing on modular integration into existing blockchain ecosystems, Fairblock brings privacy-preserving infrastructure directly to DeFi, addressing the industry's specific needs for confidential trading, compliance, and real-time data protection. Arcium, which primarily focuses on the Solana blockchain, utilizes a different encryption framework and takes a more narrow approach to confidentiality. It specializes in the Solana ecosystem, whereas Fairblock’s multichain design integrates seamlessly with both EVM and Cosmos ecosystems, providing broader support. Fairblock’s modular architecture allows it to scale across multiple chains with advanced cryptographic techniques, offering more flexible and practical confidentiality solutions for diverse blockchain applications. Fairblock’s focus on modular integration, real-time efficiency, and compliance sets it apart as a true enabler for decentralized finance and blockchain-based applications. Whether it's for private data monetization, AI model security, leaderless auctions, or hidden-information GameFi, Fairblock delivers adaptable, scalable solutions that ensure confidentiality while maintaining the integrity and decentralization of blockchain networks. ## Fairblock’s Business Model and Sustainable Revenue Flywheel ### Revenue Model and Market Opportunity Fairblock is not just building infrastructure, it's engineering a sustainable business around the incorruptible world computer. At the core of this strategy is a simple but powerful engine: confidential auctions. This single primitive unlocks high-margin revenue across multiple verticals, compounding product depth, usage, and value capture. Below, we break down Fairblock’s monetization roadmap and run some paper napkin math to illustrate the projected potential of Fairblock’s offerings across three sequential phases. ### Phase 1: Incorruptible Auction-Based Markets **One Auction Engine, Three Explosive Revenue Vehicles** Fairblock’s flagship sealed-bid auction infrastructure powers encryption-driven use cases across lending, token launches, and intent-based trading. This model drives revenue directly into Fairblock’s native chain, FairyRing, allowing rapid iteration and unlocking new design spaces in DeFi. Unlike traditional DeFi protocols that rely on fixed curves or public mempool orders, Fairblock introduces a leaderless, encrypted auction engine that unlocks fair market discovery across multiple verticals. Today’s DeFi is often constrained by toxic order flow, manipulated token launches, and inefficient lending curves. Fairblock reimagines these primitives through the lens of confidentiality and incorruptible execution engines. **A. Fixed-Rate Lending (Fairates)** **What it solves:** Today’s fixed-rate lending protocols (e.g., Notional, Term Finance) often struggle with bid sniping, uneven clearing, and low institutional adoption due to lack of confidentiality. **Fairblock’s edge:** Every loan term is discovered through a sealed-bid auction where borrowers and lenders commit bids confidentially. Once cleared, all parties settle at a single, transparent rate, without manipulation. **Where it stands:** Already live on Arbitrum testnet, backed by the Arbitrum Foundation, and integrating with Hyperliquid. Fairates benefits from reduced gas costs and rapid block times, something legacy models can’t support. **Revenue opportunity:** Projects like Term Finance and Notional process ~$500M in volume across dozens of markets. If even a portion of that migrates to Fairblock’s sealed auctions (augmented by liquidations and ecosystem growth), we’re looking at a conservative multi-million-dollar annual revenue stream, especially as institutional confidence rises. **B. Fair Token Launches (FairLaunch)** **What it solves:** Dutch auctions and first-come-first-serve IDOs frequently devolve into gas wars and last-minute frontrunning. The result? Inequitable access and massive alpha leakage. **Fairblock’s edge:** FairLaunch replaces chaotic token sales with sealed-bid auctions. Participants submit bids privately, and once the auction closes, all bids are revealed and cleared at a uniform price. No sniping. No favoritism. **Where it stands:** Partnered with Rova (ex-CoinList) and in active discussions with Legion and Fjord. The approach offers improved UX, better price stability, and broader participation. **Revenue opportunity:** CoinList alone facilitated over $100M in token sales last year. With Fairblock targeting 10–50 launches annually in early phases, 5% of funds raised as protocol revenue yields material upside, while serving as a marketing flywheel for broader adoption. **C. Intent-Based Trading (FairIntent)** **What it solves:** As intent-based trading gains traction (CoWSwap, 1inch Fusion, UniswapX), current systems leave order flow exposed. This creates risk for both users and solvers, ultimately degrading price execution. **Fairblock’s edge:** FairIntent encrypts both the user intent and the solver bids. Matching is done through a sealed-bid auction mechanism, where only the selected path is revealed and settled onchain. **Where it stands:** Actively collaborating with CoWSwap, Squid, Anoma, and Uniswap MVPs. **Revenue opportunity:** With over $50B* annual volume in intent-based flows, and Fairblock capturing even 5–10%** of that at 0.15% in protocol fees, the upside exceeds 7 figures in annualized revenue. Unlike speculative tokens or fluctuating LP fees, these flows are sticky and repeatable. **Volumes from Cow Swap, Fusion, Uniswap X, Squid* ***[Cow Swap](https://dune.com/cowprotocol/cowswap) showed 132% growth in trading volume between May 1, 2024-May 1, 2025* ## Phase 2: Confidential and Compliant Stablecoin Transfers ### Replacing Centralized Backends With Trustless Confidential Rails Despite trillions in DeFi volume and $200B+ in stablecoin supply, most transfers still pass through centralized routing systems or leak sensitive information that makes them unsuitable for institutions. Fairblock replaces this layer with programmable confidentiality and decentralized selective disclosure. [A recent Fireblocks report](https://www.fireblocks.com/report/state-of-stablecoins/) surveyed 295 financial executives, 61% of whom were C-suite leaders, and confirmed what the market has long been signaling: - 9 in 10 respondents say regulations and industry standards are accelerating stablecoin adoption - 36% of respondents flagged improved security as the single biggest unlock for enterprise stablecoin use ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/5c3ff5c88b0a.png) This shift reflects a maturing industry: as legal clarity and AML tooling advance, risk becomes the next bottleneck. Institutions aren’t just asking *if* providers are secure—they want to know *how* protocols evolve against new threats. And here, Fairblock is well-positioned. *“Conventional security frameworks will not be sufficient to protect the next billion users as stablecoin adoption accelerates. To keep up with 24/7 cross-border flows, infrastructure must evolve at the same pace as the attack surface. Institutions are no longer asking if a provider is secure, but how that security evolves to meet emerging threats.”* By embedding decentralized confidentiality and programmable compliance at the execution layer, Fairblock delivers: - Confidential transfers with selective disclosure - No reliance on centralized intermediaries or private servers - Composability across EVM chains, Solana, and institutional rails like Noble Here, the opportunity is massive: - DeFi: [~$3.2T](https://defillama.com/dexs) in annualized trading volume, 70% still routed through centralized intermediaries. - Stablecoins: $239B supply today, projected to hit $2T by 2028. Let’s illustrate the Revenue Potential: - Capturing 2% of DeFi flow at 0.15% fee = ~$67M. - Powering 10% of stablecoin rails today = ~$36M; scaling to ~$300M+ by 2028. Notably, the demand for confidential stablecoin rails is already proven. Projects like Railgun and Houdini Finance, despite being limited in either ecosystem reach or functionality, have generated approximately [$4-6M](https://defillama.com/protocol/railgun) and $[1.5M](https://defillama.com/protocol/houdini-swap) respectively in revenue. These systems typically charge around a 0.1% transaction fee, a model Fairblock can replicate with greater efficiency and broader composability across chains and applications. With a more scalable infrastructure and support for institutional-grade compliance, Fairblock is well positioned to capture and expand this growing market segment. ### Phase 3: Incorruptible Machines (Confidential AI Infrastructure) As crypto-native AI agents become a reality, whether as automated traders, autonomous governance participants, or verifiable oracles, the demand for a cryptographically secure execution layer will only grow. Fairblock is positioning itself as **the decentralized coprocessor** for these AI systems, where confidentiality, verifiability, and composability converge. Fairblock’s multimodal compute stack (MPC + TEE + FHE + ZK) has the potential to enable: - Confidential AI inference - Secure data monetization - Strong and efficient model execution **Potential Revenue Scenario**: - DeFi trade volume: $3.2T annually. - 86% of it is already automated via bots and agents. - Encrypting just 2% at 0.15% = ~$83M annual protocol fee potential. Current integrations with Phala, Ritual, and Cycles are early signals of product-market fit. As regulation and onchain AI adoption grow, Fairblock becomes the operating system for incorruptible machine logic, an entirely new frontier for both computation and monetization. ***Note:**The revenue figures and market sizing outlined above are forward-looking projections intended to illustrate the potential scale of Fairblock’s core products. These estimates are **not financial advice** and are based on current market trends, comparable protocol data, and illustrative adoption scenarios. Actual outcomes will depend on a range of factors including market dynamics, user adoption, regulatory clarity, and Fairblock’s ability to achieve strong product-market fit across its target verticals.* ## Tokenomics Fairblock’s native token underpins the protocol's economic and security models. The token is designed not only to accrue value directly proportional to network adoption but also to abstract user experience complexities, driving sustainable long-term utility. ### Primary Functions of Fairblock Token: - **Governance:** Enables stakeholders to influence protocol evolution, security parameters, cryptographic standards, and key partnerships. Progressive decentralization ensures robust initial oversight, transitioning smoothly to broader community governance. - **Fee Mechanisms:** Differentiated fee structure incentivizes native application development, with internal network applications benefiting from reduced fees compared to external integrations, enhancing network effects and platform adoption. - **Staking and Security:** Node operators stake Fairblock tokens to maintain network integrity, with tiers incentivizing higher performance and advanced computational capabilities. Token-based staking aligns incentives and discourages malicious behavior through slashing mechanisms. Fairblock implements computation fees that scale with complexity and urgency, offering premium fast-lane execution options. Fees can be paid in native tokens or stablecoins like USDC, with stablecoin transactions automatically converting to the native token, reinforcing demand. Fairblock's meticulously structured revenue streams and robust tokenomics model position the protocol to achieve sustainable economic viability, driven by its critical role as the confidential processing layer for diverse blockchain applications and markets. ## Bonus: How Confidentiality Unlocks New Design Space for Onchain Gaming While Fairblock’s primary focus lies in transforming financial markets, stablecoin infrastructure, and AI execution, its early traction in gaming highlights the broader demand for confidentiality across Web3. These community-driven experiments demonstrate how programmable encryption can bring fairness, unpredictability, and integrity to fully onchain games. In multiplayer betting games like blackjack and poker, Fairblock enables encrypted cards that remain hidden until specific triggers are met, such as a challenge or reveal phase. Bluff-based games like BS allow decryption only when a move is contested, while trivia and quiz games keep answers concealed until the correct guess or time-based reveal. Strategy-heavy formats like Diplomacy benefit from encrypted turn submissions that are unveiled simultaneously, preserving competitive fairness. Even games of chance such as Craps, Russian Roulette, and Spin the Wheel are reimagined using cryptographic randomness and delayed decryption to maintain suspense and fairness. ![](https://shoal.xyz/research/writing/fairblock-incorruptible-markets-and/img/b3afd2eee7d1.jpg) In narrative-rich settings like the Celestia-powered Murder Mystery, Fairblock enables dynamic storytelling by keeping player identities, clues, and outcomes encrypted until key moments. One standout demo, Lazy Killer, uses Fairblock’s infrastructure to keep the killer’s identity confidential until a pre-set block height. Players navigate the game without access to critical information until the reveal, adding a layer of suspense and ensuring no participant can exploit premature knowledge. These examples are not just novelties. They show how confidentiality can unlock new design spaces in Web3, even outside of finance. While gaming is not Fairblock’s core focus, its organic adoption in this vertical validates the need for incorruptible infrastructure wherever fairness, unpredictability, and trust are essential. ## Lingering Thoughts As we’ve seen, the earliest and most enduring promise of crypto has always been simple: peer-to-peer transactions that are permissionless, decentralized, and open to all. Yet ironically, this core use case remains incomplete. Why? While transparency ensures verifiability, it simultaneously prevents true usability at scale. Whether it’s two individuals transacting, a protocol launching a token, or a game executing logic, the lack of onchain confidentiality has created real constraints. Today, most onchain transactions are not only public but pre-public. Every bid, trade, or move is visible before it executes, exposing users to frontrunning, value extraction, and exploitation. This dynamic turns the mempool into a battleground, not a marketplace. As a result, crypto has largely been limited to speculation, meme coins, and basic swaps while the intended real-world use cases remain on the sidelines. Fairblock closes this gap not by simply adding a confidentiality "patch," but by reimagining the infrastructure required for secure, performant, and trustless applications to operate at scale. Its architecture, built around leaderless, rapid auctions and programmable encryption, enables something we’ve long been missing: fairness by design. Whether it's lending markets that discover rates dynamically through sealed-bid auctions, token launches without sniping and manipulation, or generalized intents that allow users to safely express preferences without leaking alpha, Fairblock’s technology allows applications to work as they were always intended to. Not by hiding data for secrecy’s sake, but by preserving integrity until the right moment. This unlocks everything from confidential AI inference to unruggable multiplayer games, and institutional-grade onchain participation. At its core, Fairblock is building the world’s Incorruptible Computer, an engine for powering incorruptible markets and machines. It detoxifies Web3 by turning every onchain interaction, whether a trade, AI action, or game logic, into a fair, trustless, and confidential experience. Institutional flows, retail trades, and autonomous agents can operate without leaking alpha, enabling new forms of coordination and value exchange. The FairyRing chain and FairyKit toolkit are not black-box privacy tools. They are open, modular systems designed to be used by real developers building real applications. HTTPS didn’t change what websites were;it enabled them to be trustworthy. Similarly, Fairblock enables credible economies to emerge onchain with confidentiality built in, not bolted on. To understand what this shift could mean, it’s helpful to zoom out. In 1900, New York’s Fifth Avenue was filled with horses and carriages. Horses had worked fine for centuries, and most people didn’t feel limited by them. But by 1913, that same street was full of cars, with only a single horse remaining. The change was subtle at first, then happened “slowly, then all at once.” Cars didn’t just offer more speed; they were cleaner, safer, more efficient, and easier to scale. Confidentiality wasn’t the reason people adopted cars, but it was an inherent advantage once they got there. In the same way, Fairblock is ushering in the shift from horse-drawn infrastructure. Slow, exposed, inefficient blockchains, towards modern, programmable systems built for fairness, compliance, and performance. Confidential computing isn’t the end goal, it’s the engine under the hood that makes all of this possible. The recent $2.5 million in funding secured will enable Fairblock to expand its research capacity, develop new prototypes, and roll out user-friendly tools that ensure safer transactions across various blockchain platforms. More so, Fairblock has been supported by credible organizations that boost its credibility, with backers including Anagram, Axelar, Robot Ventures, Arbitrium Foundation, and Reverie, among others. As regulatory clarity emerges, the blockchain industry stands at the cusp of a new era. Confidentiality will no longer be a barrier to adoption but a cornerstone of innovation, ensuring that onchain confidentiality is preserved while meeting regulatory demands. Fairblock’s commitment to this vision ensures that the future of blockchain is not only secure and decentralized but also inclusive and compliant, unlocking new possibilities for DeFi, AI, gaming, healthcare, and beyond. Fairblock is building the next default: fast, secure, compliant infrastructure that scales trustless coordination beyond what transparent ledgers ever could. The world didn’t replace horses overnight. But once it saw what was possible, there was no going back. With Fairblock, crypto is about to have its automobile moment. ## References Fairblock Official Documentation: [https://docs.fairblock.network/docs/welcome/Vision](https://docs.fairblock.network/docs/welcome/Vision) 0xFairblock:[https://website-0xfairblock.vercel.app/applications](https://website-0xfairblock.vercel.app/applications) Fairblock Network: https://www.fairblock.network Crypto's New Whitespace: WTF is MPC, FHE, and TEE? By @millianstx. [https://x.com/milianstx/status/1873767492767654359](https://x.com/milianstx/status/1873767492767654359) Nillion: https://nillion.com/ --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.** All posts are the author's own, not the views of their employer.This post has been created in collaboration with the Fairblock team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research* --- # Fragmetric: Unlocking Composable Restaking with Solana’s Token-2022 Standard > Explore how Fragmetric is setting a new standard for modular, capital-efficient restaking on Solana. - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-05-16 - Canonical: https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/ - Keywords: crypto, DeFi, restaking, liquid staking, yield, tokenization, infrastructure, Solana, Ethereum ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/ff6fab6c765a.jpg) ## A Primer on Restaking, Liquid Restaking The adoption of Proof-of-Stake (PoS) has surged as blockchains seek more efficient and secure consensus. Ethereum’s long-awaited transition to PoS in 2022 was a milestone, slashing the network’s energy use by an estimated 99.95%. Even before this merge, major networks like Solana, Cardano, and Algorand had embraced their own variations of PoS for its eco-friendliness and security, signaling an industry-wide shift away from energy-intensive mining. Solana’s blend of Proof-of-Stake (PoS) and Proof-of-History (PoH) consensus mechanisms illustrates how staking can secure a network while supporting lightning-fast transactions and minimal fees. In essence, holders delegate their SOL tokens to trusted validators, much like casting votes in a democratic election. Validators, in turn, ensure smooth network operations and earn rewards from transaction fees and protocol inflation. Yet, even as staking became a popular and effective method of securing blockchain networks, it introduced a notable drawback: locked capital. Assets staked in traditional PoS are immobilized, limiting their broader economic utility and capital efficiency. Recognizing this inefficiency, many teams began exploring ways to leverage staked capital more effectively, enabling it not just to secure one blockchain but to extend its security benefits across multiple networks. The rise of modular infrastructure and services has given way to a proliferation of new app-specific blockchains, which have historically struggled with bootstrapping their validator networks due to a lack of activity and, therefore, economic incentives for participation. As such, new mechanisms were formed to extend the utility of staked assets to help secure and bootstrap new blockchains. This is what has come to be known as restaking. ## The Restaking History [Restaking extends the utility of staked assets](https://www.shoal.gg/p/unlocking-capital-efficiency-beyond?r=4hnppk&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false) by allowing them to simultaneously secure multiple protocols, and as a concept, it has been tested and implemented in app-specific blockchains such as Polkadot, Cosmos, and Avalanche, where security is a primary concern. A handful of different ecosystems and blockchains have implemented some form of *shared security* over time. The individual details may vary, but the core concept still remains the same: a larger protocol enables smaller protocols by allowing such protocols to tap into their existing vast pool of economic and computational resources to aid in their initial growth while improving capital efficiency and returns to the larger protocols. In the Polkadot network, validators stake *DOT*to participate in the relay chain, which is then used to provide security to *Parachains.* On the Avalanche network, validators securing the *C-chain* (the primary hub of economic activity) can participate in subnets, which connect to a dynamic set of validators working together to secure or achieve consensus on the state of a set of chains. Subnets secure many chains on the network, but each chain is validated by one Subnet. Cosmos, on the other hand, implements Replicated Security (formerly Interchain Security), where the top 95% of the Cosmos Hub’s validator set is replicated across “consumer chains.” These validators must run nodes for every consumer chain, effectively sharing the slashing risk and infrastructure burden. ATOM stakers can choose to opt-out of this cross-chain exposure by delegating outside the top 95%, albeit at the cost of reduced yield. However, it was EigenLayer that truly popularized “restaking” as a standalone paradigm in 2023 on Ethereum and beyond​. EigenLayer allowed Ethereum stakers to opt-in and re-stake their ETH or liquid staking tokens to secure new modules (initially dubbed *Actively Validated Services*, or AVSs), thereby extending Ethereum’s security to new use-cases without launching new blockchains. This innovation opened eyes to the untapped potential of leveraging existing stake for additional utility. Yet, EigenLayer’s early design also highlighted some inefficiencies, from single-asset limitations to reliance on off-chain reward distribution processes, largely due to Ethereum’s technical constraints. ## Jito Restaking on Solana On the other hand, [Solana’s implementation of the Restaking concept](https://www.shoal.gg/p/the-rise-of-restaking-on-solana) launched on July 25th, 2024, when the Jito Foundation released their code for the Jito (Re)staking protocol, a hybrid multi-asset staking protocol on Solana enabling any new network or application to bootstrap their economic security. [Jito (Re)staking is Solana’s first-class framework for restaking](https://www.shoal.gg/p/jito-restaking-strategies), developed by Jito as a next-gen infrastructure for multi-asset staking. In simple terms, Jito’s protocol lets users stake (or re-stake) any supported asset on Solana to secure additional networks or services – called Node Consensus Networks (NCNs) – while maintaining liquidity via tokenized receipts. The protocol consists of two primary components: the ***Vault Program***, enabling the creation and management of staked assets, and the ***(Re)staking Program***, coordinating activities and incentives among network participants. Together, these two core programs offer developers a modular, scalable framework for streamlining staking mechanisms for any SPL asset, marking the first protocol of its kind on Solana. **Vault Program** This on-chain program manages the creation and operation of Vault Receipt Tokens (VRTs) – Solana’s flavor of liquid restaking tokens​. A vault in Jito can accept any SPL asset (SOL, staked SOL like JitoSOL, or even a project’s own token) as its underlying stake​. When you deposit tokens, the Vault program stakes them (either directly or via existing liquid staking tokens) and mints you VRTs in return. These VRTs act as liquid representatives of your staked position – you can hold or use them in DeFi while the vault deploys the underlying stake to earn rewards. The Vault Program handles all the heavy lifting: minting and burning VRTs, delegating the staked assets to chosen operators, and even enforcing any slashing conditions specified by the network you’re restaking to​. By design, the Jito vault supports only one asset per vault and can delegate only to node operators, not directly to NCNs. To overcome this limitation and enable multi-asset support, Fragmetric developed a wrapper program that extends the vault’s functionality. This enhancement allows for the creation of a unified restaking experience with customizable delegation strategies. For example, a vault’s stake could be spread across several node operators or even indirectly support multiple NCNs, all governed by a DAO or automated protocol logic. **Restaking Program** If vaults are where users interact (depositing tokens and receiving VRTs), the Restaking Program is the coordination layer that ties everything together​. It’s responsible for registering and managing the Node Consensus Networks (NCNs) themselves, as well as the node operators who run them. An NCN in Jito’s framework is analogous to EigenLayer’s AVS – it’s any service or protocol (on-chain or off-chain) that wants to leverage Solana’s staked assets for security. The Restaking Program lets these NCNs define their parameters: which vault(s) (i.e. which tokens) they accept, what the reward structure is, and what conditions would trigger slashing of misbehaving operators​. This program implements opt-in/opt-out logic so that vaults or operators can choose which NCNs to participate in, and it handles the distribution of rewards and slashing penalties on-chain. In other words, when an NCN pays out rewards, the Restaking Program makes sure those rewards get routed to the right vaults and thus to VRT holders and operators; if a node operator violates the rules, the program can slash their staked assets per the NCN’s policy. All of this happens *transparently on Solana’s ledger*. **How do these pieces work together?** Let’s say a new protocol (call it ORCL, an oracle network) wants to use Jito (Re)staking. ORCL would register as an NCN via the Restaking Program, perhaps specifying that it will accept restaked $ORCL tokens (its governance token) and JitoSOL as collateral from stakers. Jito’s Vault Program can then set up vaults for ORCL – one for $ORCL deposits and another for JitoSOL. When users stake into these vaults, they receive, for example, rORCL and rJitoSOL VRTs (liquid tokens representing their stake in ORCL’s security)​. The vaults delegate the actual $ORCL and JitoSOL stake to ORCL’s node operators. Now, ORCL’s oracle nodes are economically secured by two assets. If they try to feed wrong data, they can be slashed in either or both vaults. While the enforcement of such slashing policies, such as penalizing a portion of the operator’s rORCL and rJitoSOL stake, is defined by ORCL’s predefined rules, it is not natively handled by the Jito Restaking Program. Instead, these rules must be implemented and enforced externally through custom program logic. Meanwhile, as ORCL’s oracles perform their duties correctly, they might reward participants, including stakers, with freshly minted $ORCL tokens or fee income. These rewards are then tracked and distributed through ORCL’s own reward mechanisms, not the Jito Restaking Program, to the appropriate rORCL holders. All the while, users who hold rORCL or rJitoSOL can use these tokens elsewhere or redeem them, just like any liquid staking token. In this way, Jito (Re)staking acts as a one-stop, on-chain platform for launching and managing a restaking-enabled service on Solana – you get secure staking, customizable slashing, and liquid tokens without building a thing from scratch​. ### Why Restaking Matters for Solana’s Future **Enhanced Economic Security** By allowing multiple forms of collateral to secure a service, Jito (Re)staking drastically increases the cost to attack that service. A malicious actor would need to compromise or acquire a significant amount of each staked asset to do harm, and even then they’d be financially punished via slashing. This creates a kind of [insurance mechanism](https://solanacompass.com/learn/Lightspeed/everything-you-need-to-know-about-restaking-on-solana-vs-ethereum-lucas-bruder-sreeram-kannan#:~:text=This%20model%20involves%20slashing%20funds,is%20being%20implemented%20in%20EigenLayer) for Solana’s dapps and off-chain integrations​. While Solana’s base layer historically leaned on high performance over heavy slashing, adding restaking gives the network *strong crypto-economic guarantees* where needed. Critical services (like price oracles, bridges, DePIN, or upcoming Layer-2 networks) can bootstrap security from Solana’s existing stake pool, aligning their fate with the network’s economic security. This in turn hardens the overall resilience of the ecosystem – fewer single points of failure and a higher cost to subvert core services. **MEV and Fee Distribution** Solana’s design already reduces Maximal Extractable Value (MEV) compared to some chains, but Jito is at the forefront of making sure the MEV that *does* exist benefits the community. In fact, the **[first live NCN on Jito Restaking is the Jito Tip Router](https://www.kiln.fi/post/discover-jito-restaking-unlocking-additional-rewards-on-solana#:~:text=Jito%20Tip%20Router%20NCN%3A%20The,first%20live%20use%20case)**[​](https://www.kiln.fi/post/discover-jito-restaking-unlocking-additional-rewards-on-solana#:~:text=Jito%20Tip%20Router%20NCN%3A%20The,first%20live%20use%20case). This service captures a portion of transaction fees (tips) from Solana’s MEV ecosystem and redistributes it to restakers and validators. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/49220e790754.jpg) For example, 0.15% of all Solana tip revenue is directed to SOL restakers, and another 0.15% to Jito’s own JTO token restakers, via the Tip Router vaults​. By restaking, regular SOL stakers can earn a share of MEV income that normally only validators or block producers would get. Originally, MEV tips were intended for stakers. What’s important is that restaking has removed the single point of control and decentralized this distribution process. Prior to the introduction of Tip Router, Jito managed the entire flow of MEV rewards internally. By delegating this responsibility to a restaking-enabled mechanism, the system now ensures a more transparent and inclusive reward path, bringing MEV income to a broader set of network participants. This fair distribution of MEV rewards strengthens incentives for staking and keeps Solana’s validator set economically healthy. It’s a prime case of how restaking can channel new value streams (like MEV or fee rebates) back to the people securing the network. **Network Scaling and Utility** Restaking opens the door for Solana to scale horizontally in terms of services. Instead of every new decentralized service launching its own token and validator set (which dilutes security and is a huge engineering lift), they can plug into Jito (Re)staking as an NCN. This is much like an “AWS for decentralized trust” – a project can quickly borrow Solana’s security by creating a vault and defining slashing rules, and voila: they have a decentralized trust layer for their app. This could accelerate innovation by lowering the barrier to launch new protocols that require trustless execution or consensus. For Solana, this means more useful services running on or adjacent to the network without compromising security. It’s a path to scale out functionality (similar to Ethereum’s rollup ecosystem) while keeping the economic security tightly coupled with the Solana ecosystem, rather than fragmenting it. **Capital Efficiency & Staker Rewards** From a staker’s perspective, restaking makes Solana staking much more attractive. It layers additional rewards on top of base staking yield, essentially [stacking yields from multiple sources​](https://www.kiln.fi/post/discover-jito-restaking-unlocking-additional-rewards-on-solana#:~:text=Jito%20Restaking%20allows%20staked%20assets,or%20providing%20decentralized%20price%20feeds).Instead of just earning ~7% APY from SOL inflation, a Solana staker might earn that *plus* oracle service fees, *plus* MEV tips, etc., all through one integrated platform. And they can do this while keeping their stake liquid via VRTs. This boosts participation (why sit idle with just one yield source when you can earn more, albeit with higher risk due to potential slashing?), which in turn increases the total stake securing Solana. More stake means higher **economic security** for the L1 as well. Additionally, by making stake more productive, features like restaking could allow Solana to adjust its inflation down in the future without hurting validator economics, [as suggested by some ecosystem researchers​](https://solanacompass.com/learn/Lightspeed/everything-you-need-to-know-about-restaking-on-solana-vs-ethereum-lucas-bruder-sreeram-kannan#:~:text=Restaking%20and%20Inflation%20on%20Solana). In essence, restaking aligns incentives so that what’s good for the individual staker (maximizing returns) is also good for the network (strengthening security and utility). ## Restaking, Liquid Restaking, & Liquid Restaking Tokens (LRTs) Restaking allows assets staked to secure one network to be reused across multiple services, significantly boosting capital efficiency and economic security. However, just like traditional staking, restaking usually requires assets to remain locked, limiting their liquidity and usability elsewhere. This immobilization of capital reduces potential returns and restricts users' flexibility. To solve this challenge, [Liquid Restaking Tokens (LRTs) were introduced](https://www.shoal.gg/p/liquid-restaking-tokens-a-new-frontier?r=4hnppk&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false), unlocking new possibilities for restakers by providing a liquid representation of their underlying restaking positions. ## State of Liquid Restaking The total amount of liquid restaked assets locked in the general liquid restaking market is [$11.746b](https://defillama.com/protocols/Liquid%20Restaking). Ether.Fi, a decentralized and non-custodial staking protocol on Ethereum, has a higher percentage of assets in the pool with a TVL of $6.543b, followed by other protocols such as Kelp, Renzo, and EigenPie, amongst others. At the time of writing, there is $229.64m worth of actively liquid restaked assets on Solana, with Fragmetric leading the way with over 60% share of the restaked pool. Renzo, Kyros, etc account for the remaining significant portion of the pool, with Meta Pool mpSOL accounting for the least thus far. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/29d0acc2764b.png) Solana optimizes for fast execution speeds and low transaction costs at high volumes. Solana ultimately seeks to maximize performance for developers and users by fully leveraging available hardware performance capabilities, such that hardware is, in fact, the only restriction on network performance long-term. As the second-largest chain by TVL, the restaking landscape on Solana is well-poised for growth and transformation in the near to long-term future. One team seeking to propel the concept of Restaking on Solana is Fragmetric, as they are a project building the architecture needed to aggregate different staking technologies on the Solana network. ## Restaking Approach: Solana vs. Ethereum Fragmetric’s approach deliberately avoids the pitfalls observed in early Ethereum restaking. One major inefficiency in EigenLayer’s initial design was the use of single-token vaults and off-chain accounting. For instance, distributing rewards that come in many forms (imagine an oracle service paying out in its own token, plus perhaps USDC fees) is tricky on Ethereum. In practice, some Ethereum restaking projects resorted to simplifications like converting all rewards into a single token (e.g. swapping various tokens into ETH) before distributing, a clunky solution that dumps reward tokens on the market and loses granularity​. Even EigenLayer’s core system leans on off-chain processes: a “trusted” component computes each participant’s earnings off-chain and posts a Merkle root to Ethereum, which users then claim against​. This off-chain reward distribution adds latency and opacity (participants have to trust the off-chain computation) and is necessary largely because doing complex, frequent calculations on Ethereum would be prohibitively expensive in gas. Similarly, Ethereum’s limited throughput makes real-time, multi-asset tracking difficult, so much so that EigenLayer is developing a separate data availability layer (EigenDA) to scale its capabilities​. Furthermore, liquid restaking protocols built on EigenLayer (e.g., Ether.fi, Swell, Renzo) experience operational friction when redistributing rewards to token holders. High Ethereum gas fees pose a challenge, making frequent or automated reward distributions economically infeasible. This often results in protocols indirectly passing gas costs onto users through manual claim processes or accumulating rewards to periodically adjust exchange rates, inadvertently creating selling pressure on AVS tokens. Solutions like King Protocol, which consolidates multiple AVS tokens into a single vault-backed token (KING), partially mitigate this but introduce new complexities, including smart contract risks, token peg stability issues, and reduced flexibility for individual reward token management. Solana, by contrast, was built for high-frequency, on-chain computation with low fees, and Jito (Re)staking capitalizes on that. All reward distribution in Jito’s framework can happen on-chain**,**transparently. Because Solana can handle many transactions quickly, Fragmetric’s vaults are able to track and distribute multiple types of rewards in real time. In fact, Solana’s token infrastructure has unique features that Fragmetric leverages for it’s solana-native liquid restaking protocol. One example is the use of token*extensions* like the *transfer hook*, a program that allows attaching custom logic whenever a token is transferred. Fragmetric uses this to precisely track how long each user has held their VRT so that Node Consensus Network rewards (which might accrue over time in various tokens) can be split fairly​. Every time someone moves their restaking token, the transfer hook updates an on-chain record of their “time-weighted” balance. Achieving this level of precision simply isn’t feasible on Ethereum’s ERC-20 standard without expensive workarounds. Solana’s distinct edge stems from its recent advancements with Token-2022, the new SPL token standard that introduces sophisticated token extensions. Token-2022 maintains backward compatibility while unlocking advanced functionalities like transfer fees, transfer hooks, interest-bearing tokens, and confidential transfers via zero-knowledge proofs. These extensions offer developers an unprecedented level of customization in defining economic and operational behavior for tokens, something significantly constrained by the conventional ERC-20 standard on Ethereum. This foundational difference in token standards brings us directly to Fragmetric. Built on Solana and integrating deeply with the Jito restaking ecosystem, Fragmetric harnesses the Token-2022 extensions to deliver uniquely tailored value accrual mechanisms. Specifically, Fragmetric issues fragSOL tokens representing deposited SOL or JitoSOL. Unlike traditional liquid staking tokens, fragSOL is a yield-bearing asset designed explicitly around Token-2022’s transfer hook functionality. Solana’s Token-2022 standard extends the traditional SPL token model by enabling modular token functionalities without requiring separate vaults or permissioned contract layers. This is achieved through Token Extensions, a set of programmable token behaviors that allow for fine-grained control over transfers, fees, governance, and yield mechanisms. Fragmetric fully embraces Token-2022 to create a yield-bearing, composable, and capital-efficient liquid restaking token (fragSOL) with native programmability. Unlike Ethereum’s vault-based restaking model, which requires off-chain governance and custom implementations to manage fee-sharing, Fragmetric uses on-chain, protocol-native extensions such as: Transfer Hooks: Enables precise, programmatic control over token transfers. Fragmetric leverages this extension to track time-weighted holdings of fragSOL, enabling accurate and fair reward distribution directly on-chain. This eliminates the need for off-chain computation or vault-based reward systems. *Note: While Token-2022 supports other extensions like interest-bearing tokens and confidential transfers, Fragmetric currently utilizes only the transfer hook to implement its reward and accounting logic.* Fragmetric capitalizes on Transfer Hook extensions to ensure specific economic incentives and slashing conditions are programmatically enforced during token transfers. This sophisticated token design drastically reduces operational complexity and overhead associated with reward distribution—a challenge particularly acute in Ethereum’s ERC-20 and liquid restaking ecosystems. In the subsequent section, we will explore Fragmetric’s technical architecture, focusing on how it distributes rewards. We will also examine how Fragmetric leverages the Token-2022 to dynamically accrue yield directly within fragSOL tokens, transparently reflecting accumulated staking and restaking rewards. ## What is Fragmetric? ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/17c6656ebbfc.jpg) Fragmetric is a native liquid restaking protocol on Solana that aims to enhance Solana’s current ecosystem security as well as increase its economic potential. Through liquid restaking, the total amount of staked SOL across nodes increases, which helps to strengthen the network and improves security. Furthermore, the Token2022 extension improves capital efficiency by enabling users to restake without compromising capital efficiency. Fragmetric is focused on building the infrastructure that is responsible for aggregating all restaking protocols on Solana. This raises an important question: What are the key objectives of Fragmetric that support its vision? The key objectives of Fragmetric are: - **Establishing a Secure LRTs Standard**: Fragmetric develops and maintains standards for LRTs to ensure accurate reward distribution. This allows such LRTs to be used as restaked assets across various protocols, improving capital efficiency—users earn restaking rewards and additional revenue at the same time. - **Delegate Deposits to Secure Restaking Protocols**: Fragmetric is developing a governance-based Risk Management Committee to verify the profitability and secureness of Node Consensus Networks (NCNs) and Autonomous Verifiable Services (AVSs). - **Contribute to the growth of Solana with SANG**: Through Fragmetric restaking, users become SANG—Solana Network Guard—guardians who secure Solana’s ecosystem. With a seamless restaking experience made possible by Fragmetric, which has several features that aid in achieving economic security for Solana. This brings up the question: how does this procedure of restaking using Fragmetric work? The next section goes over how that is feasible. ## The Fragmetric Restaking Process ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/a0c867b91e4e.jpg) The Fragmetric restaking process begins with the following steps: - **Deposits**: When a user first deposits SOL, LSTs, or other SPL Tokens into Fragmetric, they receive an equivalent amount of $fragmetric asset (e.g., fragSOL). - **Normalized Token Program**: This fragmetric program maintains precise conversion ratios between deposited assets and minted $fragmetric assets. Users’ combined deposits (SOL, LSTs, and other tokens) form a unified basket that Fragmetric allocates across various restaking protocols and NCN/AVS. - **Rewards Distribution**: Assets are delegated to partner validators who secure NCN/AVS networks. The earnings from these delegations are distributed to $fragmetric asset holders. Fragmetric serves as both a portfolio manager and a liquidity layer between users and restaking protocols. ## Protocol Architecture FRAG-22 is a novel token standard developed by Fragmetric that extends the capabilities of Solana’s Token-2022 program, particularly its transfer hook functionality. Originally designed to support Fragmetric’s liquid restaking infrastructure, FRAG-22 has evolved into a composable asset framework enabling unified management of multiple yield sources under a single token architecture. At its core, FRAG-22 allows for multi-asset deposits, normalizing various input tokens (e.g., SOL, JitoSOL, mSOL) into a single fungible representation. This simplifies user experience while enhancing liquidity efficiency across DeFi protocols. Each FRAG-22 token captures not only the underlying asset value but also an on-chain record of contribution over time, used to calculate real-time, precise reward entitlements for each holder. Unlike conventional token standards which rely on off-chain reward logic or inflexible vault systems, FRAG-22 embeds all reward accounting directly on-chain through programmable transfer logic. This allows FRAG-22 tokens to dynamically integrate with lending markets, liquidity pools, structured products, and yield strategies, all while maintaining transparent and predictable reward distribution. As Solana’s DeFi ecosystem evolves, FRAG-22 sets a new bar for capital efficiency and composability, offering developers and users a powerful primitive to unlock more sophisticated and modular yield-generating applications. To provide the infrastructure needed to aggregate all restaking protocols on Solana, the Fragmetric comprises the Fund, Operator, Reward, and Normalized Token Pool. ## Fund, Operator, and Reward In the Fragmetric ecosystem, the seamless management of user assets and precise distribution of staking rewards form the cornerstone of its value proposition. Three core modules—Fund, Operator, and Reward—coordinate closely to deliver an intuitive, secure, and transparent user experience. Let’s explore how these modules interact, followed by a simplified working example to illustrate exactly how rewards are managed and distributed within Fragmetric. The Fund is the foundational module responsible for managing user deposits and withdrawals. Users deposit assets such as SOL or supported Liquid Staking Tokens (LSTs), including JitoSOL, mSOL, BNSOL, and bbSOL, directly into the Fund. Upon deposit, the Fund mints an equivalent value of fragSOL tokens for users. The quantity of fragSOL minted is dynamically determined using accurate, real-time price data sourced from the Normalized Token Pool (further detailed in subsequent sections). The following diagram demonstrates the interaction between users, the $fragSOL Fund, and the Oracle systems: ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/e32415fa6288.jpg) 1. Deposits: Users deposit SOL or supported LSTs (including JitoSOL, mSOL, BNSOL, bbSOL) into the Fund. 2. Minting fragSOL: Upon receiving a deposit, the Fund mints fragSOL for the user. The number of tokens minted is determined by the current price data, reflecting the combined value of the underlying assets. 3. Withdrawals: Users may request withdrawals, prompting the Fund to burn the corresponding fragSOL and reserve the equivalent amount of SOL for them to claim. These withdrawal requests are processed on a periodic schedule. 4. Pricing fragSOL: The price of fragSOL is dynamically calculated based on the overall value of the LSTs managed by the Fund, ensuring that the tokens accurately represent each user’s share of the pooled assets. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/2206e129d9c7.jpg) The **Operator** comes next in line as it manages staking, restaking, withdrawal operations, and the execution of restaking strategies. It handles all asset flows from the fund and rewards that configure the investment strategy through integration with various staking and restaking protocols. The operator in Protocol is responsible for managing asset movements according to dynamically changing configurations. These configurations are adjusted based on withdrawal requests and the governance-driven restaking portfolio. The Operator ensures the reconciliation of asset amounts between the fund, reserved fund, restaking protocols, and staking protocols. Its tasks include setting target amounts for the reserved fund account (to handle withdrawal requests) and determining unstaking and restaking amounts to maintain these targets. It configures investment allocations and delegates funds to the NCN Node operator based on the latest configurations. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/3aeb92b95783.jpg) The Reward Module is the core system of Fragmetric, designed to accurately distribute various rewards earned through restaking. By leveraging Solana's Token Program 2022—transfer hook, the program detects changes in the amount of fragSOL in user wallets, allowing the system’s internal logic to function seamlessly on-chain. Since all reward-related data is stored on-chain, users can easily predict the rewards they are entitled to receive. In traditional restaking systems, especially when using LRT, the user’s restaking reward tends to be diluted within the pool, making accurate participation calculations difficult. Fragmetric has overcome this issue by utilizing an Only Possible On Solana solution that ensures precise calculation of the user’s reward and equitable reward distribution. ## Normalized Token Pool Although Fragmetric operates similarly to other liquid staking protocols on Solana by exchanging SOL and LSTs for fragSOL and nSOL, it takes a unique approach by supporting restaking across multiple LSTs through the Normalized Token Program. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/f1a3d464fd98.jpg) Other LSTs like jitoSOL, mSOL, and bnSOL all hold different values due to varying differences in staking yield, protocol fees, and reward distributions. This further pushes the need to issue fragSOL at an equivalent rate before minting. To tackle this, the Oracle-based approach was employed, where oracle systems like Switchboard and Pyth Network ensure that fragSOL is priced. Conversely, despite the Oracle-based approach offering higher security and serving as a reliable fallback system, their involvement in this process is unreliable as they provide price feeds that reflect the broader market conditions for these LSTs and are further used to determine the price of fragSOL. At the time of writing, Fragmetric's Normalized Token Pool holds over 760K+ LSTs, including more than 750K JitoSOL. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/5ee2b49e1b86.png) Fragmetric brings a new approach as it directly taps into their respective stake pool, giving access to the on-chain state data like the current value of staked assets, rewards distributed, or performance metrics. By using all the on-chain data, the system accurately accesses the value of SOL-based LSTs and calculates the fragSOL issuance rate. This provides users with a reliable and transparent pricing mechanism. ## Competitive Landscape Fragmetric enters a competitive landscape that includes crypto-restaking upstarts. Key players include crypto-native platforms like Renzo and Kyros. Fragmetric’s edge lies in its token mechanics, multi-asset staking approach, and real-time on-chain pricing. Unlike Renzo and Kyros, Fragmetric goes all-in on Token-2022, letting rewards accrue natively and cutting out the manual vault swaps. While Renzo and Kyros keep it simple with single-asset restaking, Fragmetric aggregates multiple LSTs—JitoSOL, mSOL, BNSOL, and bbSOL—into fragSOL, making it more capital-efficient, which is possible via its Normalized Token Program. Then there’s pricing, for eg, Renzo rely on its oracles, which can lag behind real staking rewards. Fragmetric pulls data straight from Solana’s stake pools, meaning more accurate pricing and smoother reward distribution. The result? A smarter, more composable restaking model that actually fits the way Solana works. ![](https://shoal.xyz/research/writing/fragmetric-unlocking-composable-restaking/img/a1a32ac2d039.jpg) ## Tokenomics ## fragSOL and fragJTO **fragSOL** is Solana’s first Liquid Restaking Token (LRT) and the culmination of Fragmetric’s technological innovation. By restaking SOL or other Liquid Staking Tokens (JitoSOL, mSOL, BNSOL, or bbSOL) through the Fragmetric protocol, you receive fragSOL, which represents your restaked SOL or LST and entitles you to: 1. Solana Staking Yield: Fragmetric collaborates with top-tier yield-focused protocols, aiming to deliver competitive returns to fragSOL holders. 2. MEV Rewards: All SOL and LSTs deposited into Fragmetric are used to secure TipRouter, the first Node Consensus Network (NCN) under Jito Restaking. MEV tips generated from these activities are distributed to fragSOL holders, boosting overall APY. 3. Additional Restaking Revenue: With integrations on the Jito (Re)staking Protocol, including collaborations with NCNs, Fragmetric efficiently redistributes extra restaking rewards to fragSOL holders. **fragJTO** is the first non-SOL Liquid Restaking Token (LRT) introduced by Fragmetric. By staking JTO, the governance token of the Jito Protocol, you receive fragJTO, which represents your staked JTO and entitles you to: 1. MEV Rewards: The JTO is utilized to secure TipRouter, a core component of the MEV ecosystem on Solana. The MEV tips generated here are shared with fragJTO holders, enhancing overall APY. 2. Additional Restaking Revenue: With integrations on the Jito (Re)staking Protocol, including collaborations with NCNs, Fragmetric efficiently redistributes extra restaking rewards to fragJTO holders. ## wfragSOL and wfragJTO wfragJTO are wrapped versions of fragJTO, designed for broader DeFi compatibility. Some DeFi protocols do not support Token Extension (also known as Token-2022), an advanced token program on the Solana blockchain. To address this, wfragSOL and wfragJTO were created as DeFi-compatible versions of fragSOL and fragJTO, with the wrapped tokens pegged to their respective tokens. ## Partners Switchboard is launching its external Jito Node Consensus Network (NCN) on Solana, in collaboration with Fragmetric, its exclusive Vault Receipt Token (VRT) provider. This partnership enhances the security, efficiency, and decentralization of Switchboard’s oracle services. Fragmetric enables users to restake SOL, JitoSOL, and other LSTs, earning additional rewards on top of existing restaking and MEV yields. Switchboard’s decision to exclusively partner with Fragmetric for its Jito Node Consensus Network (NCN) restaking launch is rooted in the protocol’s deep technical alignment with Solana’s architecture and its unique ability to optimize staking capital across assets. While Switchboard could have opted for generalized VRT solutions, Fragmetric offers a specialized, purpose-built infrastructure that addresses the specific demands of decentralized oracle networks. Fragmetric’s Restaking Vaults are engineered to support a diverse basket of LSTs such as JitoSOL, mSOL, and bSOL, and seamlessly convert them into normalized restaking collateral via its proprietary Normalized Token Program. This system ensures efficient and fair restaking value attribution. This is critical for oracle security where precision in capital allocation and slashing guarantees are non-negotiable. More importantly, Fragmetric’s integration with Token-2022 and use of transfer hooks allows Switchboard to track user-level contributions with time-weighted precision, all on-chain. This real-time reward infrastructure drastically reduces the operational overhead associated with reward tracking and MEV distribution. These are two of the most critical value flows for oracle participants. Unlike general-purpose liquid restaking solutions that are built for simplicity or cross-chain compatibility, Fragmetric is Solana-native by design. This enables it to plug directly into Switchboard’s high-throughput oracle layer and deliver capital-efficient security without compromising decentralization or composability. The collaboration ensures that restakers can participate with minimal friction, while Switchboard gains robust security guarantees, transparent economic alignment, and a predictable pathway for incentivizing reliable oracle node operators. By leveraging Fragmetric’s advanced infrastructure, Switchboard becomes the first external NCN on Jito Restaking to implement decentralized and economically driven oracle security. This sets a new standard for how oracle networks are bootstrapped in the Solana ecosystem. ## Protocol Usecases Let’s explore some of the use cases of Fragmetric: **Liquidity Provision on Orca** Fragmetric integrates with Orca’s Concentrated Liquidity Automated Market Maker (CLAMM) to enhance capital efficiency for liquidity providers. By allocating liquidity within specific price ranges, providers can maximize yield compared to traditional AMMs. Users supplying liquidity to pools such as wfragSOL-JitoSOL or wfragJTO-JTO earn a share of trading fees, ensuring continuous rewards from asset swaps. These fees are distributed proportionally among liquidity providers. **Automated Liquidity Vaults on Kamino** Kamino's liquidity vaults are an automated liquidity solution that allows users to earn yields on their crypto assets by providing liquidity to concentrated liquidity market makers (CLMMs). Fragmetric utilizes Kamino’s automated liquidity vaults to simplify liquidity provision in concentrated liquidity market makers (CLMMs). These vaults deploy liquidity into Orca pools, allowing users to deposit assets like wfragSOL or wfragJTO while simultaneously earning fragAsset-based yield and trading fees. This automation optimizes capital deployment and enhances returns for liquidity providers. **Yield Trading on Exponent** Exponent is a yield exchange protocol on Solana for fixed-rate and leveraged yield farming. Users can exchange their productive yield assets (e.g., Jito’s VRTs, lending positions, yield-bearing tokens) for a fixed return or amplified exposure to their yield. Fragmetric enables users to participate in yield trading through Exponent. Users can trade yield-bearing assets (e.g., Jito’s VRTs) for fixed returns or amplified exposure to yield fluctuations. High-risk, high-return traders can maximize F Point exposure by taking a long position on yield through YT-fragAsset, while liquidity providers earn staking rewards, swap fees, fixed yield, and additional point boosts. **Yield Trading on RateX** RateX Protocol is a decentralized exchange (DEX) built on Solana, specializing in leveraged yield trading. On RateX, users can trade synthetic Yield Tokens (YT) of various yield-bearing assets (YBA) with leverage, benefiting from yield movements in a capital-efficient way. By integrating with RateX, Fragmetric leverages yield trading on synthetic Yield Tokens (YT) of various yield-bearing assets. Users can capitalize on yield fluctuations in a capital-efficient manner while also accessing fixed-yield and liquidity farming options. Those seeking high-risk, high-reward strategies can increase F Point exposure, while liquidity providers benefit from staking rewards, swap fees, and special point incentives. **Whitelisting and Liquidity Expansion** While DeFi liquidity pools and vaults are permissionless, Fragmetric initially whitelists only Orca and Kamino, ensuring F Points rewards remain exclusive to these platforms. As liquidity deepens and stabilizes, Fragmetric plans to expand its whitelist, increasing accessibility and optimizing incentives across additional DeFi protocols. ## Wrapping Up Fragmetric effectively addresses significant challenges within the Ethereum-based restaking ecosystem by leveraging Solana's powerful Token-2022 extension. This innovative extension enables Fragmetric to seamlessly perform all reward calculations directly on-chain, storing reward-related data transparently and ensuring accurate, predictable reward distributions. Users benefit from this design as it provides clear, verifiable reward tracking and allows them to directly claim their rewards on-chain, enhancing both transparency and user confidence. With the Token-2022 extension, Fragmetric can dynamically calculate rewards based entirely on on-chain contribution data, simplifying the tracking process and ensuring equitable distribution without off-chain intermediaries. This streamlined approach significantly reduces operational complexities and the selling pressure commonly observed in Ethereum's liquid restaking protocols, resulting in a healthier overall ecosystem. Fragmetric currently maintains a robust [Total Value Locked (TVL) exceeding $210 million](https://defillama.com/protocol/fragmetric) and continues to experience rapid growth. As its ecosystem expands, it has attracted notable protocol partnerships, including Switchboard Oracle and Sonic’s HyperGrid, further validating the effectiveness and appeal of its reward distribution model. As Solana's restaking landscape continues to evolve and expand, Fragmetric is well-positioned to become the industry standard, setting a benchmark in transparency, operational efficiency, and user experience. If this trajectory continues, Fragmetric could redefine the liquid restaking market, making it more predictable, secure, and beneficial for both users and participating protocols alike. ### References 1. **Fragmetric Documentation**[Official Fragmetric Docs](https://docs.fragmetric.xyz/) 2. **Shoal Research Articles on Restaking and Yield Strategies***[Jito Restaking Strategies: Optimizing Yield within the Solana Ecosystem](https://www.shoal.gg/p/jito-restaking-strategies?r=5bbb0t&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false)**[The Rise of Restaking on Solana — A Jito Deep Dive](https://www.shoal.gg/p/the-rise-of-restaking-on-solana?r=5bbb0t&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false)**[Liquid Restaking Tokens: A New Frontier for Yield](https://www.shoal.gg/p/liquid-restaking-tokens-a-new-frontier?r=5bbb0t&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false)* 3. **EigenLayer Documentation**[Official EigenLayer Docs](https://docs.eigenlayer.xyz/eigenlayer/overview) 4. **Solana Token-2022 Resources***[Solana Token-2022 Program Overview](https://spl.solana.com/token-2022)**[What Are Token Extensions?](https://www.helius.dev/blog/what-is-token-2022)*[By Helius Lab](https://www.helius.dev/blog/what-is-token-2022) --- ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the Fragmetric team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Unlocking Capital Efficiency Beyond Restaking with YieldNest > Beyond restaking—unifying DeFi and restaking to deliver sustainable, risk-adjusted on-chain yields with YieldNest's MAX LRTs - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-03-27 - Canonical: https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/ - Keywords: AI agents, crypto, DeFi, market making, restaking, yield, infrastructure, Ethereum, Base, Bitcoin ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/cf3e788dfde6.jpg) ## Introduction – The Foundation of Productive Capital Investors have long debated the merits of productive versus non-productive assets. Historically, productive assets—such as equities, real estate, and business ownership—have consistently outperformed inflation, while non-productive assets—such as gold—have primarily served as stores of value. As the restaking narrative began unfolding last year, it became important to revisit the concept through first principles thinking. This approach underscores the fundamental shift toward maximizing capital productivity and efficiency by unlocking new utility and yield-generation opportunities. The fundamental distinction lies in the ability of productive assets to generate returns independent of price speculation. Productive assets create value through dividends, rental income, interest payments, or intrinsic business growth. Non-productive assets, on the other hand, rely on market demand to appreciate in value. Many parallels have been drawn to analyze the impact of productive versus non-productive assets. Let’s take a look at one such example [from a Blockworks article](https://blockworks.co/newsletter/daily/issue/post_82a65465-7a8d-4e2b-b2c1-4f0ab4da8153), which goes back to ancient Roman times to examine how productive and non-productive assets behave in traditional markets. *A Roman centurion in the time of Augustus earned about 38.58 ounces of gold per year—an amount that, when converted to today’s gold prices, is equivalent to $86,342. If you look closely, this mirrors the salary of a modern U.S. Army captain (around $85,000). This eerie precision highlights gold’s ability to hedge against inflation but also underscores its limitations—it merely preserves value rather than growing it. By contrast, productive assets like equities have historically compounded wealth, turning modest investments into massive fortunes over time.* *Had Roman equities existed in 24 BCE and generated even a modest 1% return above inflation annually, an investor’s portfolio would be worth over a trillion dollars today after almost 2,000 years. This illustrates the power of compounding—the driving force behind why equities, real estate, and income-generating businesses vastly outperform non-productive assets over long time horizons.* **Yield in productive assets stems from multiple mechanisms:** 1. Income Generation – Rental yields, dividends, staking rewards (in case of crypto). 2. Capital Appreciation – Business expansion, property value growth. 3. Leveraged Reinvestment – Using returns to generate further gains, such as reinvesting dividends or compounding staking rewards. Non-productive assets like gold do not generate wealth; they only preserve purchasing power. Scarcity alone does not ensure growth, making productive assets structurally superior for long-term wealth creation. Blockchains aren’t companies in the traditional sense. Protocols like Ethereum are decentralized rule sets encoded in software and executed by independent operators in a permissionless manner. They function as distributed networks, not corporate entities, and typically don’t meet the legal definition of a common enterprise. The native assets of most blockchains (e.g., BTC, ETH) don’t grant governance rights, distinguishing them from traditional equity-based financial structures. Unlike businesses, these networks don’t generate revenue or incur losses—they exist as neutral infrastructure. Concepts like “income” and “expenses” imply a counterpart, but blockchains lack a central entity to accumulate or distribute value. Defining “network profit” for Bitcoin or Ethereum is as impractical as measuring the profitability of the internet—value flows through them but isn’t captured by a single party. When discussing productive assets in crypto, the key question is: ***How can capital be made productive in a secure (or relatively secure) way? In other words, what mechanisms exist beyond price speculation to generate yield?*** Ethereum has long stood apart as the only truly productive asset among major blockchains. One of the reasons is its functioning fee market and deflationary burn mechanism, introduced with EIP-1559. Under this model, Ethereum’s transaction fees consist of a base fee (burned) and a priority tip (paid to validators). This ensures that ETH holders benefit from network activity through fee burns, which reduce the total ETH supply, creating deflationary pressure. Additionally, staked ETH earns rewards for securing the network, making ETH both a yield-bearing and deflationary asset—a unique combination absent in other blockchain ecosystems. Beyond this, several other mechanisms exist in crypto for making capital more productive, ranging from traditional DeFi strategies to emerging restaking models. These include: - **Lending/ Borrowing protocols** like Aave and Compound, where users supply assets to liquidity pools and earn yield from borrowers. - **Proof-of-Stake (PoS) staking rewards**, where validators secure blockchain networks and earn rewards in return. - **Restaking** is an advanced evolution of PoS, allowing assets to secure multiple layers and applications, unlocking yield opportunities beyond the base network. - **Yield farming and liquidity provisioning**, where users supply assets to decentralized exchanges (DEXs) and [automated market makers (AMMs) like Uniswap](https://app.uniswap.org/positions) or Curve, earning rewards through trading fees and incentives. - **[Emerging Structured DeFi products](https://app.yieldnest.finance/restake/ynETHx)**, including automated vaults, leveraged staking, and cross-chain liquidity strategies, further optimizing yield generation. While multiple yield-generation strategies exist, Ethereum's fee burn mechanism, combined with staking rewards and emerging structured DeFi products, makes ETH the (only) truly productive native asset in crypto today. In this report, we revisit first principles thinking about making capital more efficient in a secure and (relatively) simple way. - We will build a strong foundation by exploring productive asset classes and what makes crypto assets productive. - We will trace the evolution of crypto asset productivity, using Ethereum as a case study, delving into the rise of DeFi, on-chain AI agents, and their role in reshaping DeFi 2.0. - We will explore (re)staking, critical risks, and LRTs, specifically examining YieldNest as an enabler of efficient capital deployment with secure, risk-adjusted yields. - Finally, we will dive into the architecture of YieldNest, its MAX LRTs, and how it seamlessly integrates the best of both DeFi and restaking to unlock new capital efficiencies for users. ## Productivity of crypto assets Cryptocurrencies, particularly Bitcoin and Ethereum, have sparked renewed debate over this dichotomy of productive vs non-productive asset classes. Bitcoin, much like gold, has long been considered a non-productive asset, appreciated for its scarcity and decentralized nature but lacking inherent yield-generation mechanisms. However, with the advent of Bitcoin Layer 2 solutions and (re)staking protocols like Babylon, DeFi on Bitcoin is expanding. BTC, as an asset class, is gradually shifting towards productivity, offering users the ability to earn yield rather than relying solely on price appreciation. The [total value locked (TVL) on Bitcoin](https://defillama.com/chain/Bitcoin) has increased significantly, rising from $100 million in January 2023 to approximately $5.7 billion today (peaking at $7 billion in December 2024) —representing more than a 60x increase in just two years. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/1f0a5029f724.png) Ethereum, on the other hand, has significantly evolved (and continues to evolve) as a productive asset class, primarily due to its programmable smart contract functionality. Unlike Bitcoin, which was designed primarily as a decentralized store of value, Ethereum introduced the concept of programmable money, enabling Decentralized Finance (DeFi), a sector that has redefined traditional financial services by removing intermediaries and enabling trustless, permissionless finance. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/9ce43567f24a.jpg) *Source: [DeFi 201 by Amadeo Brands - 2020](https://x.com/amadeobrands/status/1899698831874474167)* Ethereum’s smart contracts allow developers to create self-executing agreements that operate without the need for a centralized authority. This innovation laid the foundation for decentralized applications (dApps) that replicate and enhance traditional financial services, including lending, borrowing, trading, and asset management. The launch of MakerDAO in 2017, a decentralized lending platform that introduced an algorithmic stablecoin (DAI) was a pivotal moment in DeFi’s growth. Since then, Ethereum has powered some of the largest DeFi protocols, including: - **Decentralized Lending Platforms** (e.g., Aave, Compound) – Allow users to lend and borrow crypto assets without intermediaries, earning interest in a trustless manner. - **Decentralized Exchanges (DEXs)** (e.g., Uniswap, SushiSwap) – Facilitate peer-to-peer trading through automated market makers (AMMs), eliminating reliance on centralized exchanges. - **Yield Aggregators** (e.g., Yearn Finance) – Optimize returns by moving user funds between the highest-yielding DeFi strategies. - **Synthetic Assets & Tokenization** (e.g., Synthetix) – Enable the creation of blockchain-based representations of real-world assets, allowing global access to financial markets and the creation of decentralized stablecoins. DeFi’s core services can be broken down into three categories: stablecoins, liquidity systems, and lending markets. It's that simple, and everything around is just a combination of these categories. DeFi applications and protocols currently have around [$150 billion in total value locked](https://defillama.com/) (TVL) across hundreds of chains, with Ethereum alone accounting for over $100 billion+. This explosion of financial innovation has transformed Ethereum into the backbone of DeFi and the main settlement layer for on-chain finance. DeFi has not only enhanced Ethereum’s utility but has also established ETH as a highly productive asset, fundamentally differentiating it from traditional non-productive stores of value like gold. *For example, users can take their ETH and deposit it into Aave’s Wrapped Ether pool, earning a stable ~2% APY today.* ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/3d3170ff6057.png) Ethereum’s transition to Proof of Stake (PoS) with [the Merge](https://ethereum.org/en/roadmap/merge/) marked a fundamental shift in how the network secures itself, giving ETH holders an additional yield for securing the network with their capital in terms of staking rewards. Since the introduction of the Beacon Chain in December 2020, Ethereum staking has grown rapidly, with around 34M ETH now staked, accounting for over [27% of the total ETH](https://dune.com/hildobby/eth2-staking)supply (120.4M). This staking ratio doubled post-Shapella but has since stabilized as demand cooled. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/002fa2eb6a9d.png) To participate in staking, validators must deposit **32 ETH** as collateral into the beacon chain to spin up a validator node and perform certain duties for securely running the network. And this staking of ETH generates yield from two primary sources: - **Consensus Layer Rewards**: Validators earn ETH for attesting and proposing blocks, funded through newly issued ETH (network inflation). - **Execution Layer Rewards**: Includes **priority fees and Maximal Extractable Value (MEV)**, which fluctuate based on network demand. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/7b04a46dabba.png) Currently, Ethereum’s **nominal staking yield stands at 3.08%**, while the real (inflation-adjusted) yield is **2.73%**. During periods of heightened activity, **staking APY has spiked to over 6.2%**, as seen in March and August 2024. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/fa3a858484cb.jpg) *Source: [Coinmetrics](https://coinmetrics.substack.com/p/state-of-the-network-issue-288)* However, when Ethereum first launched staking through the Beacon Chain in 2020, it came with a major tradeoff—staked ETH was locked with no withdrawals until the Shapella upgrade in 2023. This posed a dilemma for ETH holders during the DeFi Summer of 2020 when capital efficiency was paramount. DeFi protocols were offering high-yield opportunities through lending, trading, and liquidity provisioning. ETH holders had to choose: - **Stake ETH into the Beacon Chain**, earning a stable **3-4% staking yield** but with funds locked indefinitely. - **Deploy ETH in DeFi**, where lending and liquidity pools could offer higher yields but carried increased risk. To tackle this, Lido introduced the first —Liquid Staking Token (LST) back in 2020—allowing ETH holders to stake while retaining liquidity. Instead of locking ETH directly into the Beacon Chain, users could stake through Lido and receive stETH, a 1:1 tokenized representation of staked ETH. This allowed ETH holders to: - Continue earning staking rewards. - Use **stETH in DeFi protocols** for lending, trading, and additional yield generation. - Participate in staking with as little ETH as they have, instead of the minimum 32 ETH deposit required in “traditional” (Vanila) staking This early capital efficiency breakthrough for the largest PoS asset significantly boosted staking participation, with Lido capturing over 30% of all staked ETH at its peak. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/c7742d65abc8.png) Today, liquid staking dominates Ethereum staking, accounting for over 40% of all staked ETH. Leading protocols include: ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/e10073d8371a.png) ## Restaking Restaking, particularly through protocols like EigenLayer, has redefined Ethereum’s capital efficiency by enabling the same assets to secure multiple protocols simultaneously. This concept became the dominant narrative in late 2023 and continues to shape Ethereum’s broader economic landscape. By allowing staked ETH to generate additional yield and utility, restaking has positioned itself as a fundamental financial primitive—one that extends beyond pure network security. However, as we explore in the following sections, the 2025 restaking ecosystem presents significant challenges. Basic mechanisms such as reward distribution, slashing enforcement, and incentive alignment between stakers, operators, and AVSs remain unresolved. The gap between vision and execution has slowed the maturation of restaking into a fully reliable yield-generation mechanism. **A brief on Restaking** Restaking extends the utility of staked assets by allowing them to secure multiple RAs (restaked applications) simultaneously—without compromising decentralized trust guarantees. While still early in adoption, restaking has found strong initial product-market fit in rollup infrastructure, where modular components such as transaction ordering, DA layers, or proof aggregation rely on restaked assets for enhanced security. Restaking isn’t the first attempt at extending a blockchain’s security guarantees. Early concepts like [merged mining](https://blockworks.co/news/merged-mining-bitcoin-multi-chain) allowed Bitcoin miners to secure multiple blockchains simultaneously using auxiliary proof-of-work (AuxPoW), without splitting computational power. This provided miners with diversified income streams at negligible additional cost—requiring only an extra full node. Other shared security models, such as Polkadot’s Parachains (2020) and Cosmos’ Interchain Security (2023), attempted to extend economic security across multiple chains. The true inflection point arrived with EigenLayer, which introduced Ethereum-native restaking, leveraging the network’s deep trust base and massive validator set. However, current implementations largely focus on reinforcing network security—*leaving the broader opportunity for economic security underutilized.* YieldNest envisions restaking as more than just an extension of shared security networks. Future DeFi protocols may leverage restaking across multiple layers—like lending platforms that restake collateral in multiple protocols (e.g., Resupply) or AMMs that enable cross-chain liquidity provisioning. As we will uncover in the later sections, YieldNest’s MAX LRT architecture is built to capture this emerging layer. By merging restaking with DeFi-native strategies—liquidity provisioning, lending, and yield farming—it transforms passive assets into actively managed, yield-generating portfolios. AI-driven automation dynamically rebalances exposure across RAs and DeFi strategies, optimizing capital deployment in real-time. With over $100 billion in staked ETH and more than 1 million validators, Ethereum provided the ideal foundation for a new era of capital-efficient security. EigenLayer repurposed this stake to secure Actively Validated Services (AVSs)—such as bridges, oracles, rollups, and data availability layers—without requiring validators to unstake from Ethereum’s consensus layer. The impact has been massive. The TVL on EigenLayer surpassed $20.14B in June 2024, just three months after its mainnet launch. Currently, the total ETH [restaking ratio is around 10%](https://dune.com/blocklytics/ethereum-restaking), with over $10B restaked on EigenLayer, $900M on Symbiotic, and $300M+ on Karak. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/c41ba0e1a7ef.jpg) The demand for restaking has skyrocketed, with $18.3B in deposits made just in 2024, highlighting the growing appetite for yield beyond “traditional” staking rewards. While Solana’s Picasso and Solayer ($58.5M) and wrapped BTC restaking via Pell Network and Karak ($223.3M) are emerging, Ethereum dominates the restaking market by a wide margin. Remember the massive growth in Bitcoin TVL we analyzed earlier? Much of this surge is attributed to Babylon, a restaking protocol for Bitcoin, which alone accounts for over $4.5 billion in restaked assets. Restaking fundamentally changes Ethereum’s security model. “Traditional” or “vanilla” staking earns validators rewards through network inflation and transaction fees, but restaking introduces additional yield streams, including AVS security fees, execution layer rewards, and MEV revenue. Instead of ETH being locked into securing only Ethereum, it can generate additional yield across multiple protocols, making Ethereum’s security model capital-efficient and composable. A common misconception surrounding restaking is the belief that it operates similarly to rehypothecation, a high-risk practice in traditional finance (TradFi) and DeFi. However, [the two are fundamentally different](https://x.com/0xyanshu/status/1779931195033182695?s=46&t=3HX1wysJ915JPCYnZlMPfA). Rehypothecation involves using pledged assets as collateral for multiple loans, creating multiple claims on the same underlying asset. This practice amplifies systemic risk, leading to over-leverage, reduced transparency, and contagion effects—where a single failure can trigger cascading liquidations. The 2008 financial crisis showcased how excessive rehypothecation contributed to market instability by obscuring real collateral levels and interdependencies. By contrast, restaking does not multiply claims on ETH but instead extends its economic security to new applications. Validators must explicitly opt-in to securing additional Actively Validated Services (AVSs), and slashing risks remain AVS-specific, meaning failures in one protocol do not affect Ethereum’s base security. EigenLayer aggregates ETH into a shared staking pool, allowing AVSs to benefit from Ethereum’s vast validator set. Unlike over-leveraged rehypothecation, restaking maintains a direct ownership structure, ensuring capital efficiency while preserving trust-minimized security. Let me share a famous analogy explained by **Sreeram Kannan, founder of EigenLayer**, that might help clarify the concept. *Imagine you enter a mall where the main store requires you to put down a $100 deposit before you can shop. This deposit is a safeguard against theft—if you steal, you lose the deposit. Now, imagine I suggest that since you've already committed this deposit for the main store, why not extend this promise to not steal from any other stores in the mall? This approach puts the responsibility squarely on you not to commit theft anywhere in the mall.* It's a different kind of risk management compared to other financial strategies like margin lending. In restaking, the risk is endogenous to the staker, meaning that validators explicitly opt-in to securing additional networks, and their risk is confined to the AVSs they choose to support. The core Ethereum staking security remains uncompromised. However, smart contract vulnerabilities remain a universal challenge across all blockchains, including restaking protocols. Restaking has emerged as an evolving primitive for capital efficiency rather than solely an economic security mechanism. While early implementations like EigenLayer pioneered shared security by enabling staked ETH to secure multiple protocols, this represents only a narrow slice of restaking’s full potential. Restaking has been facing several significant execution hurdles, including: - Tracking and enforcing operator behavior remains unreliable. - Technical tooling lacks robust SDKs or standardized frameworks. - Slashing controls are still immature, making shared security indistinguishable from shared risk. To remain competitive, restaking must evolve up the risk curve—beyond passive delegation to actively supporting dynamic capital flows and more complex economic systems. EigenLayer’s restaking model alone cannot sustain long-term capital attraction. Adaptive primitives like YieldNest’s MAX LRT strategy enhance this model with yield aggregation, providing a more sustainable approach. To overcome the execution limitations of restaking, YieldNest is building next-generation restaking infrastructure while simultaneously optimizing yield generation through DeFi. The fundamental thesis is: *build sustainable yield infrastructure that works today while maintaining strategic optionality for future opportunities.* Let’s take a look at the reality of restaking rewards today. **Restaking Yields: Unpacking the Reality of EigenLayer Rewards** EigenLayer has undoubtedly cemented itself as the leader in the restaking space with over $10 billion in ETH restaked and an additional $700 million in EIGEN tokens. To its credit, the protocol has done a remarkable job reintroducing and popularizing the restaking narrative—unlocking a new design space for cryptoeconomic coordination. We’ve seen a surge in innovative use cases, ranging from rollup infrastructure to oracle networks and AVS experimentation, all enabled by EigenLayer’s shared security model. However, when it comes to actual economic incentives, the picture is less impressive. Despite the massive TVL, restakers today are primarily rewarded in EIGEN incentives, with no established path toward sustainable, protocol-level yield. This diverges from the protocol’s original vision outlined in its whitepaper, which promised cryptoeconomic guarantees through dynamic slashing, proof-based security, and robust risk markets. The idea was to build real yield through active underwriting and meaningful service validation—yet most of these mechanisms remain theoretical, with little implementation to date. As of now, EigenLayer’s restaking incentives are still speculative. Without clear monetization flows from AVSs or SDKs that enable service-based yield models, there’s a growing gap between the initial thesis and the current execution. Members of the Shoal Research team have been actively involved in the staking industry for several years. Early research into restaking led to further exploration, including a 1.33 ETH restake into EigenLayer through a [leading validator](https://www.luganodes.com/) last year. To date, this position has yielded an average APR of approximately 0.77%—roughly five times lower than Ethereum mainnet’s staking APR. Notably, a significant portion of the rewards has come from staking EIGEN tokens rather than ETH itself. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/533df68c2c54.jpg) Even factoring in those rewards, my earnings have barely covered the gas fees I paid to restake, let alone provided any actual profit. That said, before criticizing EigenLayer too much, most early restakers have earned far more than just gas fees—but mostly thanks to EigenLayer’s airdrop (“stakedrop”). Additionally, some contributors have also received a [social drop as an early content contributor](https://x.com/0xyanshu/status/1832067878100545544), which significantly boosted the total gains. But let’s be honest, these aren’t sustainable yield mechanisms—they're one-off bootstrapping incentives. Relying on airdrops and points has created a skewed perception of value in the restaking economy. The influx of deposits driven by airdrop farming rather than genuine demand for economic security has inflated the supply of restaked assets well beyond what current AVSs actually need. This mismatch not only risks capital inefficiency but also warps the product design lifecycle. Developers, pressured to align with hype cycles and point metas, often rush apps to mainnet without proper infrastructure or core features like withdrawals, transfers, or meaningful usage. Ultimately, this creates phantom demand—AVSs that serve more as point sinks than as services generating actual value. The consequence? A system saturated with restaked capital that has nowhere productive to go. If we want to “slay Ouroboros”—the cycle of empty yield chasing itself, we must shift toward building trustless infrastructure that enables real yield. That means maturing AVS designs, enabling proper slashing frameworks, and creating value flows where restaked ETH secures applications that generate sustained, fee-based revenue. Until then, we’re still in the bootstrapping phase—powered more by speculation than utility. Now, considering the real yield from restaking ETH, things look far less attractive. The largest AVS on EigenLayer mainnet today (in terms of number of stakers) is ARPA (we’re excluding EigenDA for this example), and it was the first to make rewards live on the mainnet back in September 2024. Let’s do some quick paper napkin math to estimate the APY for ETH restaked in ARPA. At the time of writing: - *ARPA’s EIGEN Restaked: 57.82M EIGEN* - *ARPA’s ETH Restaked: 2.15M ETH* We will use the following formula to calculate the annualised APY: ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/c5ed94f82717.png) **Step 1: Total ETH Value Restaked** With ETH’s current market price at ~$2,400, the total value of ETH restaked on ARPA is: *2.15M × 2400 = 5.16B (Total value in USD)* **Step 2: Weekly Rewards in ARPA Tokens** According to the EigenLayer dashboard, ARPA is distributing [7,000 ARPA tokens weekly](https://app.eigenlayer.xyz/avs/0x1de75eaab2df55d467494a172652579e6fa4540e). At [ARPA’s current price of $0.034](https://coinmarketcap.com/currencies/arpa-chain/), the total weekly rewards in USD are: *7000 * 0.034 = 238 (or let's round up to $240)* **Step 3: Annualizing the Rewards** *240 × 52 = 12,480 (Total annual rewards in USD)* **Step 4: Calculating the APY for ETH** *( 1 + (12,480 / 5.16B) ^ 12 ​) - 1 = **0.00267%*** Wait, is this correct? If you don’t believe this is the current bull case, let’s examine a recent [AVS rewards analysis done by the Nethermind team.](https://www.nethermind.io/blog/avs-allocation-strategies-eigenda-and-arpa-compared) The ARPA Network rewards structure reveals that ETH restakers receive only a small fraction of the total AVS incentives. Season 1 Community Rewards have concluded, and Season 2 is set to continue until mid-December, with ARPA tokens distributed to node operators meeting specific conditions. However, when focusing on ETH/LST restakers, the actual yield derived from ARPA token rewards remains minimal. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/fe1488371d23.jpg) When plotting cumulative ARPA rewards converted to ETH against the total ETH staked, the resulting yield for restakers is estimated at less than **0.0006% APY per ETH restaked**. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/f6b81dc44805.png) This figure highlights the challenge of relying solely on AVS incentives for meaningful yield generation. Without supplemental rewards from EigenLayer’s Programmatic Incentives or additional staking incentives, ARPA restakers today are unlikely to see competitive returns compared to alternative restaking strategies. Liquid Restaking Protocols and Liquid Restaking Tokens (LRTs) Over the course of 2024, we saw the evolution of liquid staking protocols as yet another attempt to increase the productivity of restaked ETH, allowing users to stack additional yields on their restaked positions—possibly by utilizing them in DeFi. This became necessary because restaking into protocols like EigenLayer alone has not been particularly rewarding. Liquid restaking protocols address this gap by managing operator selection and AVS risk assessment while simultaneously providing liquidity. Similar to how Lido simplified staking by handling validator selection for Ethereum stakers, Liquid Restaking Tokens (LRTs) aim to offer an accessible way to restake ETH while maintaining liquidity. However, restaking carries significantly higher risks, making robust risk management essential. When users deposit ETH or LSTs into a liquid restaking protocol, they receive a derivative Liquid Restaking Token (dLRT), representing their share of the staked capital. These dLRTs are fully liquid and can be traded or used across DeFi applications for lending, borrowing, and liquidity provisioning—enhancing capital efficiency beyond basic restaking yields. For example, if you restake your ETH (wETH, ynETH, ynLSDe) into [YieldNest’s latest Ethereum MAX LRT vault](https://app.yieldnest.finance/restake/ynETHx), **ynETHx**, you receive a base APY of 12.50% along with a liquid restaking derivative token, ynETHx, which represents your 1:1 deposited asset. This token can then be utilized in DeFi to further optimize yield. For instance, depositing ynETHx into the Curve **ynETHx/WETH** pool can generate an additional APY of up to 29.9%, compounding returns beyond the base restaking rewards. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/4a6f046a165b.png) *Source: [https://app.yieldnest.finance/restake/ynETHx](https://app.yieldnest.finance/restake/ynETHx)* LRTs act as intermediaries between ETH holders and restaking, allocating deposits across various AVSs and node operators while charging a percentage of rewards. Users could manually select operators and AVSs, but most prefer the convenience of LRTs managing this allocation. This model mirrors traditional banks—user deposits (liabilities) must be accounted for, while LRTs actively manage risks tied to operator selection, AVS exposure, and unbonding periods (assets). In simple terms, LRTs offer: 1. **Enhanced capital efficiency** – Users can extract more value from staked assets without locking up their capital. 2. **Operator Risk Assessment**– LRT platforms vet, monitor, and select operators based on their performance, reliability, infrastructure capabilities, and governance practices. Since not all operators are equal, this prevents users from staking with bad actors or under-resourced validators. 3. **AVS Risk Evaluation** – LRTs **assess the risks associated with each AVS**, considering factors such as:**Economic sustainability** (i.e., is the AVS business model viable?)**Slashing conditions** (how risky is the restaking contract?)**Historical performance** (has the AVS consistently paid rewards?)**Security risks** (is the AVS vulnerable to smart contract exploits?) LRTs are designed to optimize restaking rewards while reducing complexity for users, making them an attractive solution as EigenLayer and restaking grow. The LRT market is evolving rapidly, with about 20 providers competing for dominance in what many are calling the next "Lido moment" for DeFi. As Ethereum staking expands and yields compress, LRTs are positioning themselves as the next logical step for maximizing rewards. However, liquid restaking also introduces some systemic risks like, slashing cascades, depegging events, and liquidity mismatches. Some providers are addressing these risks through insurance mechanisms, buffer strategy, and curated AVS selections. **Challenges associated with the current state of Restaking (beyond lack of real substantial yield)** Despite the excitement and massive capital inflow, restaking platforms still lack critical infrastructure needed for broad market fit. For example, EigenLayer’s vision, as outlined in its whitepaper, hinges on the ability to provision cryptoeconomic security via diverse, customizable slashing mechanisms. But today, slashing frameworks remain underdeveloped, and proof submission processes are still largely manual or absent. Without robust SDKs, standardized tooling, and verifiable slashing systems, meaningful growth in shared security will remain bottlenecked. Moreover, from the perspective of profit-seeking capital allocators, these gaps represent not just risks, but opportunity costs. Capital deployed into restaking protocols without clear mechanisms for enforcement or yield distribution may end up idle or misallocated. YieldNest addresses these limitations by designing architecture that benefits from restaking’s upside—while maintaining the flexibility to dynamically pivot capital across multiple strategies. In this way, restaking is treated not as a siloed endpoint but as one layer in a broader, adaptive yield strategy designed to maximize long-term capital efficiency. In this section, let’s take a closer look at some of the key challenges associated with restaking, including slashing risks, AVS-specific failures, governance concerns, and economic concentration risks,etc. Given the rapid adoption of EigenLayer, Symbiotic, Karak, and other restaking platforms, these concerns are no longer theoretical but require immediate scrutiny. **1. Base Layer Security Risks & Slashing Cascades** Restaking allows ETH to secure multiple AVSs, meaning a single validator misstep can trigger slashing across multiple protocols. Currently, ~15% of all staked ETH is restaked, with about 9% being natively restaked via EigenPods—a major slashing event could destabilize Ethereum’s validator set and economic security. For node operators, this magnifies operational complexity. They must comply with different uptime requirements and cryptographic proofs across multiple AVSs. The major problem is a *slashing cascade* – a failure in one AVS can punish the same validators that secure Ethereum’s core. If a large operator or popular AVS experiences a bug or attack causing mass misbehavior, all the validators restaking there could be slashed in unison. Industry observers warn that if a significant amount of ETH is tied up in EigenLayer and such an event occurs, it “could lead to a cascade of slashing damage” and even compromise Ethereum’s base network security. In a worst-case scenario, a slashing cascade could force a huge chunk of validators offline, undermining the economic security of Ethereum’s beacon chain. Historically, slashing on Ethereum has been exceedingly rare ([only about 470 validators ever slashed, <0.04% of the set](https://beaconcha.in/validators/slashings))​, so a large-scale event would be unprecedented. The correlated slashing penalties in Ethereum also mean that when many validators are slashed together, each one loses more stake – potentially up to their entire 32 ETH if the event is severe. Thus, restaking introduces a new systemic risk: an outage or exploit in an AVS could recursively punish Ethereum’s consensus layer, shredding validators’ deposits and confidence. **2. Centralization Pressures on Ethereum & Operators** Restaking protocols like EigenLayer also pose centralization risks for Ethereum’s validator set. If only a few large staking operators can effectively run the required infrastructure for many AVSs, they may attract outsized delegations of restaked ETH. EigenLayer allows permissionless participation (any solo staker can join via EigenPods)​, but in practice AVS creators often choose specific operators to secure their services. A [recent report predicts](https://blockworks.co/news/eigenlayer-at-risk-of-centralization) AVSs will gravitate to validators with the largest pooled stake and best performance, such as big professional node operators or those running popular liquid restaking projects​. This creates a rich-get-richer dynamic, where a handful of operators accumulate a disproportionate share of economic security. If, say, five operators end up controlling most EigenLayer stake, the restaking ecosystem could recentralize trust rather than diffusing it. Large operators capture most restaking rewards, making it harder for smaller validators to compete. This centralizes economic security in a handful of entities, leading to risks similar to Lido’s dominance in Ethereum staking. For AVSs, this creates a reliance on a handful of powerful node operators. If one colludes or goes offline, multiple AVSs could be compromised simultaneously, leading to slashing events and weakened network security. **3. Financial Risks: Liquidity Crisis and Depegging** Beyond technical and concentration issues, restaking introduces new financial contagion risks in the Ethereum DeFi ecosystem. If a large LRT (e.g., eETH, rstETH, or ezETH) faces a mass-slashing event, the value of these tokens could rapidly depeg, triggering cascading liquidations in DeFi lending markets. A similar event happened in the 2022 [Ankr exploit](https://bsc.news/post/exploit-confirmed-on-ankr-protocol-helio-money-faces-windfall), where a hacker gained control of a compromised key and used it to mint 6 quadrillion aBNBc tokens—a derivative of Ankr Reward Bearing Staked BNB. Since these tokens were meant to represent a claim on underlying BNB, the exploit effectively created counterfeit BNB at scale. As the hacker offloaded the fake aBNBc, the price of liquid staking tokens like BNBx and stkBNB plummeted. Exploiting the chaos, the attacker used the counterfeit tokens as collateral to borrow stablecoins from Helio, ultimately draining the protocol and leaving it financially crippled. Ankr acknowledged a $5M direct loss. Some proponents argue that LRTs could act as a buffer by allowing trading out of restaked positions without touching the underlying staked ETH​. In theory, if users can sell an LRT quickly, it might reduce the need to withdraw or panic on the beacon chain itself. YieldNest has implemented a buffer strategy to mitigate liquidity risks and ensure instant withdrawals for MAX LRT users. These are ERC-4626-compliant vault mechanisms that maintain a portion of assets in readily accessible, yield-generating strategies, ensuring that users can exit their positions without delays. By keeping a liquidity buffer, YieldNest reduces reliance on long withdrawal queues and helps prevent sudden depegging events by allowing users to trade out of their positions swiftly. In extreme market conditions, where mass liquidations could threaten DeFi stability, YieldNest’s buffer strategy acts as a safeguard against contagion risks, preventing capital inefficiencies and maintaining protocol resilience. **4. Social Consensus and Governance Risks** Perhaps the most far-reaching risk of all is the strain restaking could put on Ethereum’s social consensus and governance. Ethereum famously relies on a robust social layer – the community of node operators, developers, and users – to uphold the chain’s integrity in extreme scenarios. Ethereum’s social consensus could be challenged if a catastrophic restaking failure leads to demands for a bailout or chain fork. Vitalik Buterin has warned against [“overloading Ethereum’s consensus”](https://vitalik.eth.limo/general/2023/05/21/dont_overload.html#:~:text=These%20proposals%20are%20generally%20made,application%27s%20own%20purposes%20is%20not) with external security promises, arguing that a restaking collapse could pressure the Ethereum community to intervene, threatening its neutrality. With EigenLayer now securing 8% of all staked ETH, a major failure could trigger the first real “too big to fail” moment in crypto. Vitalik Buterin warned that protocols should *not* design systems assuming Ethereum will fork to save them. In his words, we must avoid *“recruiting Ethereum’s social consensus for your application’s own purposes*”​. He gave the example that while reusing the validator set (as restaking does) has risks, it might be acceptable – but expecting Ethereum to step in and fix external failures crosses a red line​. This was a clear response to the idea that if a major restaking project broke down, the community might be compelled to intervene. EigenLayer’s team echoes this stance. [CEO Sreeram Kannan noted](https://www.coindesk.com/tech/2023/09/27/eigenlayers-sreeram-kannan-on-the-hot-and-risky-ethereum-trend-of-restaking) that one should *“not assume that because you’re too big to fail, **Ethereum** will fork to bail you out.”* Instead, any protocol built on restaking must internalize its own risks​. In other words, if an AVS collapse leads to massive losses, those losses should be borne by the restakers and not socialized across Ethereum via contentious forks or emergency changes. Restaking is a double-edged sword—while it unlocks capital efficiency and shared security, its unchecked expansion could amplify systemic risks. Each of these risk areas – from slashing cascades and centralization to liquidity crunches and social fallout – underscores that EigenLayer and similar restaking initiatives must proceed with extreme care. The promise of boosting Ethereum’s utility and yield comes with non-trivial dangers. Managing these risks requires strict AVS selection, well-designed slashing policies, and robust risk frameworks to prevent cascading failures. **5. Fragmented Liquidity: A Fundamental Constraint on Restaking and DeFi Efficiency** One of the biggest challenges facing restaking and DeFi today is liquidity fragmentation across multiple ecosystems. While Ethereum dominates the restaking market, protocols like Babylon (Bitcoin), Picasso (Solana), and Karak are expanding the concept beyond Ethereum. However, this cross-chain growth introduces a structural liquidity problem—each ecosystem operates in isolation, securing only its native applications while liquidity remains locked within fragmented economic zones. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/5236c9fc4839.jpg) Liquidity fragmentation leads to inefficiencies in capital deployment, yield compression, and systemic risks, preventing restaking from reaching its full potential: 1. **Capital Inefficiency** – Restaked assets are underutilized as they cannot freely move across chains, limiting DeFi yield opportunities. 2. **DeFi Liquidity Risks** – Liquidity silos increase slippage and price volatility, making DeFi markets vulnerable to inefficiencies. 3. **Yield Compression** – Isolated capital pools force protocols to compete for liquidity, reducing available yields for restakers. Projects like [MoreMarkets](https://x.com/moremarketsxyz) are developing global liquidity marketplace to aggregate and unify liquidity across multiple blockchains, allowing applications to tap into external capital sources without relying on centralized bridges. However, these solutions are still in their early stages. The long-term solution requires a unified restaking framework integrated with DeFi, enabling seamless capital allocation, reducing fragmentation, and enhancing yield efficiency across all ecosystems. For restaking to scale sustainably, a global liquidity coordination mechanism must emerge to bridge isolated economies into a single, composable financial layer. ## YieldNest: Leading in Capital Efficiency and DeFi Innovation YieldNest is a next-generation DeFi platform that consolidates multiple yield strategies into single, liquid assets. While initially emerging as a liquid restaking protocol, YieldNest’s vision extends far beyond validator staking alone – it has a broader mission to unlock capital efficiency and redefine what’s possible in decentralized finance. The protocol offers a suite of four flagship yield tokens, each designed to dynamically rebalance across restaking and various DeFi strategies to maximize risk-adjusted returns: - **ynETH MAX (ynETHx)**: Ethereum-based strategies - **ynBTC MAX (ynBTCx):** Bitcoin-focused strategies - **ynUSD MAX (ynUSDx):** Stablecoin-based strategies - **ynBNB MAX (ynBNBx):** Innovative BNB strategies By abstracting away complexity, YieldNest democratizes access to advanced yield opportunities without compromising security or capital efficiency. ## Beyond “Traditional” Restaking Early restaking protocols like EigenLayer focused primarily on reinforcing network security by allowing staked assets to secure additional services. YieldNest takes this concept further, transforming restaking into just one component of a more comprehensive DeFi strategy. Unlike first-generation restaking solutions limited to shared security mechanisms (e.g., EigenLayer), YieldNest envisions restaking as a broader category encompassing liquidity optimization, capital efficiency, and composable financial strategies​. In practice, this means YieldNest uses restaked assets *not just to secure networks*, but to boost liquidity and productivity across the DeFi ecosystem – effectively turning passive staked tokens into active, yield-generating capital. To overcome restaking’s execution limitations at the current stage, YieldNest is building tomorrow’s restaking infrastructure while simultaneously enabling yield generation through DeFi’s current optimization capabilities. The fundamental thesis is: build sustainable yield infrastructure that works today while maintaining strategic optionality for tomorrow’s opportunities. ### Unified Multi-Strategy Yield Generation **Integrating multiple DeFi layers** - YieldNest combines “traditional” staking yields with opportunities in lending markets, automated market makers (AMMs), liquidity pools, and more. By bridging these layers of DeFi, YieldNest expands the scope of what staked assets can achieve, transforming them from a passive security mechanism into an active engine for maximizing yield and capital utility​. - Each MAX LRT (YieldNest’s proprietary *Maximum* Liquid Restaking Token) acts as an **adaptive, AI-enhanced asset** that unifies diverse yield streams – from restaking rewards to DeFi protocol fees – into one seamless, capital-efficient ecosystem​ **Omnichain liquidity and reach** - YieldNest’s multi-strategy approach is not confined to a single network. **MAX LRTs operate across multiple blockchains**, aggregating yield opportunities on Ethereum mainnet, Layer-2 networks, and other chains (such as BNB Chain, Solana, and Cosmos) into a single high-yielding asset​. - This cross-chain integration allows YieldNest to serve as a liquidity backbone that bridges strategies on different platforms while still preserving the security assurances of the underlying Layer-1 settlements​ In essence, a YieldNest token holder gains exposure to a spectrum of DeFi opportunities spanning many ecosystems, all through one unified asset. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/3c545f3ec779.jpg) ### YieldNest’s Three Core Objectives YieldNest is designed to address the inefficiencies of existing liquid restaking protocols by prioritizing three fundamental goals: 1. **Risk-Adjusted Returns** – Unlike “traditional” staking, YieldNest optimizes for sustainable, long-term returns, ensuring stable earnings even amid market fluctuations. 2. **Security & Flexibility** – Through AI-driven monitoring and autonomous risk management, assets are safeguarded against slashing risks, exploits, and systemic failures. 3. **Capital Efficiency & Innovation**– YieldNest maximizes every dollar of staked capital, ensuring that no asset sits idle by dynamically reallocating between restaking and DeFi strategies. By treating restaking as just one layer of a broader DeFi strategy, YieldNest adapts fluidly to evolving market conditions, offering users not just staking rewards, but structured, sustainable yield opportunities. Unlike other LRTs that simply enable EigenLayer restaking, YieldNest's MAX LRT vaults integrate DeFi lending, staking, and liquidity provisioning alongside restaking strategies. This approach enables: - Higher risk-adjusted returns by diversifying yield sources beyond EigenLayer. - Auto-compounding strategies that optimize restaking rewards while enhancing DeFi participation. Other LRTs provide blanket exposure to all AVSs, but YieldNest introduces isolated AVS categories—allowing users to customize risk and reward profiles. Users can choose: - Safe, high-liquidity AVSs - AI-driven, high-yield strategies - Diversified DeFi-restaking hybrid exposure YieldNest is built to enhance capital efficiency by integrating restaking with DeFi while maintaining a risk-adjusted approach to yield optimization. Unlike conventional liquid restaking protocols that passively allocate capital, YieldNest employs an active asset management framework to dynamically rebalance liquidity across restaking platforms such as EigenLayer, Symbiotic, and Nektar. By dynamically optimizing risk-adjusted returns, YieldNest’s MAX LRTs enable users to earn an additional 8–10% yield on top of base staking rewards without relying on excessive leverage or high-risk strategies, making it one of the most efficient yield-generation mechanisms in the market. In the coming sections, we will explore the technical architecture of MAX LRTs and LRT vaults, examining how YieldNest structures its restaking and risk management mechanisms to deliver scalable, secure, and high-performance liquid restaking solutions. But, before diving into this, let’s step back and revisit DeFi—the most widely used application of crypto today. At its core, DeFi was built on the first principles of open, secure, borderless, and permissionless finance, operating 24/7 without intermediaries. However, DeFi as we know it today faces several structural challenges, inefficiencies, and limitations. That said, new and innovative use cases are emerging, and protocols are leveraging novel mechanisms to push the boundaries of what’s possible. In the next section, we will discuss some of these developments in detail. ## DeFi meets AI Decentralized Finance (DeFi) has unlocked open, secure, and permissionless financial services, but the user experience remains complex, requiring manual interactions, deep technical knowledge, and constant monitoring. We saw the first renaissance of DeFi during the "DeFi Summer" of 2020, where trading volumes and user adoption surged. During this period, many fundamental DeFi primitives like lending, borrowing, and stablecoin yields—gained significant traction. By the end of 2021, the total value locked in DeFi reached its all-time high of over $170 billion. Several key factors contributed to this growth, including significant improvements in Automated Market Makers (AMMs) like Uniswap, with the release of its V2, which introduced enhancements such as improved liquidity provision and reduced impermanent loss for traders and liquidity providers. The rise of Liquid Staking Tokens (LSTs) like Lido and substantial capital inflows also played a crucial role. These breakthroughs laid the foundation for the DeFi ecosystem as we know it today. DeFi is undoubtedly promising. The infrastructure we are building on crypto rails represents the future of decentralized, inclusive, and open finance. However, like any nascent technology, DeFi comes with its own set of challenges. According to [DeFiLlama, over $9 billion has been lost to hacks in DeFi](https://defillama.com/hacks)(and bridges) so far. Risks stem not only from smart contract vulnerabilities—though these have become less common as the ecosystem matures—but also from market volatility, liquidity concerns, and economic inefficiencies. For DeFi to reach its next wave of adoption, innovation must continue to propel the space forward. DeFi users still face significant friction: navigating multi-step transactions, managing gas fees, optimizing liquidity, and assessing risk—all while competing with high-frequency trading bots and sophisticated institutional players. ## This is where AI could step in. DeFi is transforming finance by removing intermediaries and creating open markets, while AI is transforming decision-making through automation and intelligence. The convergence of these technologies—DeFi and AI, or **DeFAI**—represents a natural evolution that brings automation, efficiency, and intelligence to on-chain finance. According to CoinMarketCap, the total market cap of top AI tokens has surpassed [$35 billion](https://coinmarketcap.com/view/ai-big-data/), while DeFAI tokens alone account for nearly [$1 billion](https://coinmarketcap.com/view/defai/). This signals growing investor confidence in AI-driven financial solutions and highlights the demand for smarter, more automated DeFi protocols. The success of OpenAI’s ChatGPT transformed the way people interact with artificial intelligence. Unlike traditional search engines or rule-based assistants, ChatGPT demonstrated context-aware responses, conversational memory, and human-like reasoning. However, it still requires user input to function—it won’t take action unless prompted. This is where AI agents come in. Unlike passive chatbots, AI agents are autonomous; they not only process data and generate responses but also make independent decisions and execute tasks without waiting for direct commands. Imagine ChatGPT not only answering your question but also booking flights, managing your calendar, or even optimizing your crypto portfolio without asking. One of the most prominent examples in the crypto space is [aixbt](https://x.com/aixbt_agent), an AI agent that has gained massive traction on Crypto Twitter, engaging with users, making trades, and even promoting tokens without human intervention. The growing adoption of such AI-powered solutions signals a paradigm shift toward self-sustaining DeFi ecosystems where AI handles complex financial operations with minimal user involvement. On-chain AI agents bring this intelligence to the open, permissionless, transparent, and secure nature of blockchain networks. AI agents rely on a three-layer technology stack to function efficiently. The data layer aggregates raw blockchain information from nodes, oracles, and APIs, ensuring real-time market awareness. The AI/ML layer incorporates machine learning techniques like reinforcement learning, allowing agents to refine their decision-making processes over time. Lastly, the blockchain execution layer enables agents to interact with smart contracts, initiate transactions, and manage gas fees autonomously. Imagine an AI-powered DeFi portfolio manager that: - **Auto-rebalances assets** across liquidity pools for maximum yield. - **Executes trades** based on market conditions and predefined risk parameters. - **Manages cross-chain positions**, bridging assets seamlessly with minimal fees. - **Detects anomalies** and reacts before price swings or liquidity crashes. DeFAI solutions can be categorized into four primary areas: 1. **User Experience & Abstraction** – AI simplifies complex DeFi processes, making them more accessible to non-technical users. 2. **Yield Optimization & Portfolio Management** – Intelligent agents dynamically allocate capital across strategies, minimizing risks and maximizing returns. 3. **DeFAI Infrastructure & Platforms** – Frameworks enabling AI-driven DeFi applications, such as **on-chain AI oracles, decision engines, and automated trade execution systems**. 4. **Market Analysis & Prediction** – AI models trained on **historical and real-time on-chain data** provide insights for traders and investors. Think of on-chain AI agents as, self-executing, data-driven programs designed to automate, optimize, and enhance on-chain decision-making. These agents can process vast amounts of on-chain and off-chain data, adapt strategies in real time, and operate autonomously, significantly reducing user friction. The ideal approach is to optimize capital efficiency by combining the best of DeFi and restaking while ensuring risk-adjusted yields and a seamless user experience. *The next logical step? Leveraging AI-driven agents to automate tasks like liquidity deployment, enhance security, and simplify operations.* ## YieldNest – Beyond Restaking, DeFi, and AI for Maximum Efficiency YieldNest recently announced the launch of NestAI, with $NEST as the first subDAO in YieldNest’s subDAO formation. NestAI aligns with YieldNest’s vision to educate, simplify, and optimize DeFi. Governed by the YieldNest DAO, NestAI is designed not only to drive the growth of $NEST but also to support the broader expansion of the YieldNest ecosystem, enhancing value for all stakeholders. ### AI-Powered Strategy Execution The YieldNest team believes that agent-to-agent strategy execution could arrive sooner than anticipated. As AI-driven DeFi agents evolve, financial protocols will increasingly operate in autonomous, strategy-driven ecosystems, where AI agents interact, optimize capital flows, and execute trades without human intervention. Recognizing this shift, YieldNest’s architecture is being designed to accommodate AI-native financial interactions. That said, since YieldNest manages real capital, the team is taking a hybrid approach for now, leveraging automation where it’s been thoroughly tested, while maintaining human oversight until on-chain AI strategies prove safe and reliable at scale. NestAI will dynamically adjust asset allocations in response to market conditions, liquidity shifts, and AVS risks. Future implementations will include: - Risk-adjusted yield optimization – NestAI will factor in AVS reward fluctuations, slashing risks, and DeFi APY shifts to maximize returns. - Intelligent liquidity management – Ensuring instant withdrawals without disrupting yield generation. - Security monitoring via HyperNative – Detecting front-running, anomalies and liquidity risks before they impact users. By combining restaking, DeFi composability, and AI-driven execution, YieldNest will unlock higher capital efficiency—allowing assets to generate yield in multiple dimensions while remaining liquid and secure. With NestAI, YieldNest will automate, optimize, and enhance restaking—moving beyond static staking models into a self-optimizing financial ecosystem. - **The Thought Viewer**– NestAI’s Thought Viewer will provide real-time insights into its decision-making process, giving users:Live strategy tracking – See exactly how NestAI rebalances portfolios.Risk assessments – View the data sources and logic behind each AI-driven move.Full transparency – No black-box AI—every action will be explainable and verifiable. - **AI-Integrated DeFi Experience** – NestAI will further enhance DeFi interactions through:Telegram & Discord AI Assistants – Instant market updates, strategy insights, and automated alerts.AI-generated market visuals – Dynamic heatmaps, sentiment tracking, and on-chain trend analysis. - **Self-Learning & Adaptive Strategies** – NestAI will continuously learn and evolve, allowing:More efficient risk-adjusted returns across EigenLayer, Symbiotic, and beyond.Fully autonomous yield-maximizing trades, reducing inefficiencies and manual intervention. The following sections will take a deeper technical dive into how YieldNest’s architecture delivers secure, high-yielding, and composable financial instruments. While the concepts may be technical, they are explained as simply as possible without losing the core mechanics of how YieldNest’s system functions. Specifically, we will first explore the MAX LRT architecture, which serves as YieldNest’s unified yield optimization layer, combining staking, restaking, and DeFi strategies. Additionally, we’ll examine withdrawal mechanisms and the buffer strategy, which differentiates YieldNest as one of the most secure and liquid solutions out there. Liquidity is crucial for preventing cascading risks, especially for LRTs and LSTs (as we’ve seen in the past with the Ankr exploit). YieldNest is designed to mitigate such risks while offering sustainable, high-yield solutions in an evolving DeFi landscape. ## Deep Dive into YieleNest’s Technical Architecture YieldNest’s evolution began with Liquid Restaked Tokens (LRTs) such as ynETH and ynLSDe, which provided structured exposure to AVSs and EigenLayer-based restaking. However, as pure restaking rewards proved insufficient, it became evident that a broader yield aggregation model was needed to ensure long-term capital efficiency. This led to the development of MAX LRTs—a new category of yield-bearing assets that integrate DeFi yield strategies alongside restaking, optimizing capital efficiency while preserving security. Unlike traditional LRTs, which execute specific restaking-focused yield optimization strategies, MAX LRTs function as top-level dynamic vaults. These vaults continuously rebalance across multiple DeFi and staking strategies, consolidating diverse yield sources into a single tokenized asset. By leveraging automated execution and AI-driven risk management, YieldNest’s MAX LRT architecture enhances yield capture while ensuring sustainable liquidity deployment across multiple protocols. ### Liquid Restaked Tokens (LRTs) and ynETH Architecture YieldNest employs a multi-tiered LRT framework designed to optimize yield while maintaining liquidity and security. By integrating both native (nLRTs) and non-native LRTs, YieldNest ensures that users can efficiently allocate capital across multiple restaking strategies without the need for manual intervention. At its core, LRTs serve as yield-generating, composable assets that enable users to participate in restaking while maintaining exposure to DeFi opportunities. They are categorized into: 1. **Native Liquid Restaked Tokens (nLRTs):** Represent restaking of a Layer 1 asset (e.g., ynETH) through validator infrastructure before being utilized in EigenLayer or other restaking protocols. 2. **Non-Native Liquid Restaked Tokens (LRTs):** Represent any liquid staking derivative (LSD) or alternative asset that can be restaked (e.g., ynLSDe, which aggregates and restakes LSDs). Both nLRTs and LRTs provide economic security to various Active Validated Services (AVSs) and DeFi primitives while remaining tradeable and composable across liquidity pools and lending protocols. ynETH, YieldNest’s flagship nLRT, is structured to dynamically allocate capital across multiple AVSs, maximizing risk-adjusted yield while maintaining Ethereum’s L1 security guarantees. The [ynETH vault](https://app.yieldnest.finance/restake/ynETH) currently manages over $10M TVL, offering a base APY of up to 4% on ETH deposits. Additionally, users leveraging ynETH in DeFi (e.g., via Loop) can earn up to 38% APY, further compounding rewards beyond base staking yields. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/6cd1d0183a1d.png) ### MAX LRT Vaults: A Unified Yield Optimization Layer MAX LRTs take LRT functionality further and does more than just redistribute capital across staking and DeFi—it continuously adapts to changing market conditions, liquidity shifts, and evolving risk factors, all while maintaining deep composability across blockchain networks. Unlike “traditional” staking models that lock assets into fixed positions, MAX LRTs operate as modular vaults, autonomously reallocating capital based on where the highest risk-adjusted yields can be found. The introduction of MAX LRTs marks a shift from passive capital deployment to a dynamic, self-optimizing financial infrastructure—one that mirrors the efficiency of automated hedge funds but operates entirely on-chain. YieldNest’s architecture ensures that MAX LRT vaults can function as high-performance, cross-strategy aggregators, balancing between restaking, DeFi yield farming, and active liquidity provisioning. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/c9ddf0aee67b.png) Behind the scenes, YieldNest’s infrastructure is built on two fundamental vault types: the **Deposit Vault** and the **Strategy Vault**. These components work in tandem, ensuring that assets are not only securely deposited but also dynamically deployed into the highest-yielding opportunities available at any given time. Initially, YieldNest introduces four MAX LRTs—ynETHx, ynBTCx, ynUSDx, and ynBNBx—each backed by blue-chip assets (ETH, BTC, USD, and BNB) to provide structured exposure to the highest-yielding strategies. The Deposit Vault serves as the gateway to MAX LRTs. When users deposit assets—whether it’s ETH, BTC, or an LST like stETH—they receive MAX share tokens in return, representing their proportional stake in the vault. Unlike conventional staking derivatives, these share tokens are more than passive receipts; they actively accrue value through intelligent asset rebalancing and automated compounding strategies. Once assets are locked into the system, they are funneled into the Strategy Vault, a sophisticated execution layer that interacts with DeFi protocols, AVS ecosystems, and cross-chain liquidity markets. Here, capital is programmatically allocated into EigenLayer, Symbiotic, Nektar, and other integrated yield sources, ensuring that every unit of value is put to work efficiently. But the real intelligence of the system lies in its off-chain coprocessor—a strategic execution layer that tracks DeFi lending rates, staking rewards, AVS risks, and liquidity conditions in real-time. Unlike purely on-chain strategies that suffer from computational constraints and high gas costs, the coprocessor operates with a degree of flexibility and speed that is unmatched in traditional DeFi vaults. Rather than relying on static smart contract parameters, the coprocessor continuously evaluates shifting yield landscapes, adjusting capital allocations accordingly. It analyzes slashing risks across different AVSs, monitors liquidation threats in lending markets, and optimizes capital distribution to balance risk and reward dynamically. The result? A system that doesn’t just lock and forget like conventional (re)staking platforms—it thinks, adapts, and executes in real time, ensuring that yield is maximized while risk remains carefully managed. This section provides a detailed breakdown of the MAX LRT vault architecture, its smart contract components, and how it enables efficient restaking and yield generation across multiple blockchain networks. To illustrate this in practice, we will walk through the architecture using YieldNest’s flagship MAX LRT vault—ynETHx, which currently offers the highest market APY at the time of writing. **Core Components of MAX LRT Vaults** Each MAX LRT follows a standardized architecture, consisting of: 1. **Price Asset:**The asset in which the MAX LRT is denominated (e.g., ETH). 2. **Accounting Layer:** The Layer 1 settlement chain (e.g., Ethereum L1). 3. **Primary Underlying Asset:**The core yield-generating asset (e.g., WETH). 4. **Other Underlying Assets:**Additional assets integrated for yield optimization (e.g., wstETH & OETH). 5. **Reward Fee:**The fee structure associated with yield distribution. MAX LRT vaults leverage a layered, modular smart contract system, ensuring scalability, composability, and security. The architecture follows Ethereum's ERC-4626 vault standard, integrating custom smart contract logic to facilitate automated asset management, yield farming, and restaking allocations. **A brief on ERC-4626 vault standard** DeFi applications had often struggled with integrating various yield-bearing tokens due to inconsistent implementations across protocols. Developers had to adapt to different vault designs, interest-bearing mechanisms, and staking methodologies, leading to increased complexity and potential security vulnerabilities. [ERC-4626](https://ethereum.org/en/developers/docs/standards/tokens/erc-4626/) was introduced as a standardized tokenized vault interface, simplifying the management and interoperability of yield-bearing assets within DeFi. YieldNest integrates the ERC-4626 tokenized vault standard within its MAX LRT vaults to eliminate the need for bespoke implementations for each vault, allowing seamless integration across lending markets, staking protocols, and automated investment strategies. This standard reduces smart contract risks, minimizes development overhead, and improves capital efficiency by enabling efficient liquidity routing and composability across DeFi ecosystems. **How does ERC-4626 work?** At its core, ERC-4626 extends the ERC-20 token standard and introduces a unified vault structure that allows users to deposit assets and receive corresponding vault shares. The architecture consists of the following key components: - **Deposit & Withdrawal Mechanics:**Users deposit assets into a vault, which mints ERC-4626-compliant tokens (vault shares) representing their proportional stake. Withdrawals burn these shares, returning the underlying asset to the user. - **Yield Generation Strategies:** Each ERC-4626 vault employs automated, predefined yield strategies that optimize capital efficiency. These strategies allocate deposited assets across staking, lending, or DeFi farming protocols. - **Liquidity Reserves & Token Allocation:**A portion of assets remains in reserves to facilitate instant withdrawals. If reserves are depleted, the vault redeems capital from its active strategies before processing withdrawal requests. - **Automated Rebalancing:** Vaults adjust allocations based on on-chain metrics, APY shifts, and market conditions, ensuring optimal capital deployment without user intervention. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/8d226aebbc24.jpg) **Security and Governance Considerations** ERC-4626 improves security and risk management through structured vault operations and access control mechanisms: - **Reduced Attack Surface**: By standardizing vault logic, ERC-4626 mitigates risks associated with custom vault implementations prone to reentrancy attacks and improper state management. - **Governance-Controlled Parameters**: Protocols leveraging ERC-4626 can introduce timelocks, upgradeable strategies, and risk-mitigating policies without altering the vault's core functions. - **Composability and Interoperability**: ERC-4626 vault tokens are fully compatible with DeFi primitives, enabling cross-protocol integrations, yield aggregation, and automated asset management without complex bridge mechanisms. ### Smart Contract Architecture & Security Considerations for MAX LRTs MAX LRTs leverage a modular and upgradeable smart contract architecture, combining efficiency, security, and composability to optimize restaking and DeFi strategies. At its core, the MAX LRT contract system is mainly structured around: - ***BaseVault.sol*** – implements the ERC-4626 vault standard, handling deposits, withdrawals, tokenized share issuance, and maintains compatibility with DeFi integrations. - ***Vault.sol*** – provides a modular and extensible framework for integrating multiple restaking and DeFi protocols across chains. It enables MAX LRTs to dynamically optimize strategies while ensuring security, composability, and long-term adaptability. - ***Guard.sol*** – governs validation logic and enforces security policies, risk assessment, and access control mechanisms to protect user funds for all MAX LRT transactions. These smart contract layers ensure that MAX LRTs remain flexible, efficient, and composable across evolving blockchain ecosystems. To maintain long-term adaptability, MAX LRTs employ a TransparentUpgradeableProxy model with a timelock, which: - **Separates storage from logic**, allowing contracts to be upgraded without losing state. - **Implements a governance-controlled timelock**, preventing unauthorized upgrades or backdoors. - **Enhances security** by enabling seamless on-chain upgrades without disrupting protocol stability. The AI-powered automation layer continuously monitors on-chain and off-chain data, dynamically reallocating assets between restaking pools, DeFi strategies, and governance-controlled parameters to optimize liquidity, capital efficiency, and risk-adjusted returns. The Guard Validation Engine acts as the primary security layer within the MAX LRT architecture, it enforces on-chain security rules, ensuring that all transactions comply with predefined governance standards. It employs AI-driven risk assessments to detect anomalies, liquidation risks, and systemic vulnerabilities in real-time, dynamically adjusting risk parameters and governance alerts. Key security features include: - **Target-Level & Function-Level Access Control** – Restricts execution to pre-approved contracts and functions. - **Parameter Validation** – Ensures threshold-based security constraints and address whitelisting. - **Timelock Governance** – All contract modifications undergo timelock delays, reinforcing transparency and security. This framework ensures secure, efficient, and adaptable MAX LRT operations, mitigating risks while maximizing DeFi composability and capital efficiency. ### A high-level overview of ynETHx - key features, architecture, and how it manages security & risk. ynETHx is a MAX LRT designed to maximize ETH and LSD-based yield generation by integrating restaking, DeFi strategies, and automated capital optimization into a single, capital-efficient token. It is settled on Ethereum Layer 1, ensuring high composability, security, and accessibility while optimizing risk-adjusted APY through advanced yield aggregation mechanisms. This architecture enables dynamic allocation of assets across multiple staking, lending, and liquidity provisioning protocols, ensuring sustainable and efficient capital deployment. With AI-driven risk management and automated real-time strategy execution, ynETHx is designed to outperform “traditional” restaking models by continuously reallocating capital in response to market conditions. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/d292971947c7.jpg) **ynETHx MAX LRT Vault Configuration** ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/c302d60c60e8.jpg) The multi-asset model allows ynETHx to rebalance across different staking and DeFi protocols, optimizing yield efficiency. ynETHx maximizes capital efficiency through **automated rebalancing** across: - **Restaking Protocols** – EigenLayer, Kernel, and other shared security networks to capture **high-staking rewards**. - **Lending & Borrowing** – Integration with **Aave, Compound, and FraxLend** to generate passive income from lending. - **Liquidity Provisioning** – Deployment into **Curve, Balancer, and Uniswap** to earn **trading fees and LP incentives**. AI-driven automation ensures **capital flows between these strategies** based on risk-adjusted yield expectations and market conditions. When it comes to security & risk management, ynETHx employs a multi-layered security framework for capital protection and governance enforcement: - **HyperNative AI Security** – **24/7 real-time threat monitoring** against slashing, liquidation risks, and smart contract exploits. - **Guard Validation Engine** – A **whitelist-based transaction control system** preventing unauthorized access and enforcing **risk-adjusted governance constraints**. - **Automated Liquidity Buffers** – ERC-4626 **buffer strategies** ensuring **instant redemptions** and **reduced slippage** during high-volatility events. ynETHx employs an auto-compounding yield strategy, where staking and DeFi rewards are reinvested to increase token value over time. This ensures continuous capital appreciation, making ynETHx an optimal instrument for long-term yield compounding. **Example with the current 12.5% APY** ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/bce53161e10a.jpg) ynETHx represents a next-generation liquid restaking token, combining DeFi composability, automated capital rebalancing, and AI-driven security. Its modular smart contract design, multi-layered yield aggregation, and intelligent risk management position it as a high-performance asset within Ethereum’s expanding DeFi and restaking ecosystem. In the ynETHx MAX LRT framework, LRTs like ynETH and ynLSDe serve as core building blocks, enabling structured exposure to restaking while ensuring sustainable capital allocation. ## Withdrawal Processing for MAX LRTs and LRTs Liquidity and accessibility are fundamental to any capital-efficient staking system, and YieldNest ensures that MAX LRT and LRT holders can seamlessly withdraw their assets through a well-structured buffer strategy and secondary market options. Whether users seek instant liquidity or prefer scheduled withdrawals, the system dynamically balances capital efficiency while maintaining withdrawal accessibility. ### Buffer Strategy for Instant Liquidity At the heart of this mechanism is YieldNest’s Buffer Strategy, an ERC-4626-compliant liquidity layer designed to facilitate immediate redemptions. This strategy ensures that a portion of the deposited assets remains readily available in yield-generating pools, allowing users to withdraw their MAX LRT or LRT positions without delays. Unlike conventional staking models, where liquidity constraints can cause extended withdrawal periods, this approach prevents idle capital while keeping a consistent yield-generating structure intact. However, liquidity availability is a dynamic process. When the buffer depletes due to high withdrawal demand, assets are systematically reallocated from other longer-term strategies to replenish the liquidity pool. This rebalancing process typically takes between 1 to 10 days, depending on market conditions and the capital deployment schedules of various integrated restaking and DeFi strategies. For users who require immediate access to funds, secondary market options—such as swapping their LRTs via Curve or other AMMs—offer an alternative exit path, ensuring continuous liquidity without disrupting yield optimization. ### LRT Withdrawal Mechanics The withdrawal process for LRT holders is designed with both efficiency and flexibility in mind. To initiate a withdrawal, users interact with the requestWithdrawal**()** function, specifying the amount they wish to redeem. Once the request is confirmed, the system moves the corresponding LRTs into the WithdrawalQueueManager, generating a unique NFT as a withdrawal receipt. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/45a71888d27f.png) **This withdrawal NFT serves as a digital claim, embedding key transaction details:** - A unique ID - Amount of LRT withdrawn - Withdrawal fee - Redemption rate - Request timestamp Once issued, this NFT cannot be canceled, but it remains fully transferable, allowing users to trade their withdrawal claims on secondary markets. This feature provides an additional layer of liquidity by enabling holders to sell their pending withdrawal position rather than waiting for the redemption period to complete. Once the withdrawal queue is processed, and sufficient funds are available, users can burn the NFT to claim their ETH or LSD equivalent, which is then sent directly to their wallet. For users looking for immediate liquidity, swapping LRTs on AMMs (like Curve) or selling their withdrawal NFT offers an alternative redemption pathway. ### MAX LRTs Withdrawal System YieldNest’s MAX LRT withdrawal framework takes capital efficiency a step further by integrating automated fund reallocation and liquidity optimization models. This ensures that long-term capital remains productive while enabling real-time liquidity for users. Unlike traditional withdrawal systems that rely solely on locked capital reserves, MAX LRTs dynamically rebalance assets between high-yielding staking protocols and liquid DeFi markets to facilitate withdrawals. When buffer reserves are low, capital is seamlessly redeployed from longer-duration restaking strategies back into liquidity pools, maintaining a smooth user experience while preventing liquidity shocks that could otherwise disrupt capital flows. Looking ahead, the system will introduce dynamic fee structures that will automatically adjust withdrawal fees based on market conditions. This future enhancement aims to: - Prevent liquidity bottlenecks during periods of high volatility. - Minimize idle capital while maintaining seamless redemption cycles. - Ensure long-term sustainability by optimizing capital deployment based on real-time liquidity needs. With these adaptive mechanisms, MAX LRTs and LRTs ensure users always have access to their assets efficiently, even under volatile market conditions. ## YieldNest DAO: Governance & Decentralization Framework The YieldNest DAO serves as the foundation of the protocol’s governance, ensuring decentralized and autonomous decision-making that evolves with the ecosystem. Rather than relying on a centralized authority, YieldNest empowers YND token holders to shape key decisions, including protocol upgrades, fee structures, and ecosystem incentives. Governance follows a progressive decentralization model, initially guided by the core team before transitioning to full community control. This approach fosters long-term sustainability, allowing stakeholders to collaboratively dictate the future of YieldNest in a secure and transparent manner. ### Hybrid Human-AI Governance & Aragon V2 Integration YieldNest introduces a hybrid human-AI governance model, integrating Nest AI to enhance decision-making. By leveraging AI to analyze community sentiment, summarize discussions, and optimize proposals, the DAO streamlines governance, ensuring efficient participation and data-driven evaluations. At the infrastructure level, YieldNest governance is powered by Aragon V2, a modular framework designed for secure proposal execution, transparent voting, and dynamic governance upgrades. The flexibility of Aragon V2 allows the DAO to adapt governance mechanisms over time, ensuring that as the ecosystem expands, its decision-making structures remain robust and efficient. ### SubDAOs & YieldNest Ecosystem Governance YieldNest adopts a multi-layered governance structure, where individual products and subDAOs operate semi-autonomously, each governed by dynamic fee structures and independent governance models. The subDAO framework allows specific products to evolve independently while maintaining alignment with the overarching YieldNest vision. ![](https://shoal.xyz/research/writing/unlocking-capital-efficiency-beyond/img/33fe4aef6c9a.jpg) The first of these subDAOs is Nest AI, which is deeply integrated into YieldNest’s governance framework. As the first AI-driven subDAO, Nest AI enhances strategy execution, governance automation, and risk assessment, improving capital efficiency across the entire ecosystem. By connecting with the YieldNest DAO, Nest AI enables a more efficient allocation of resources, driving both sustainable yield generation and AI-powered strategy optimization. At the core of YieldNest’s governance system is the YND token, which grants governance power when staked. Staking YND converts it into veYND, a time-weighted voting asset that increases in influence the longer it is locked. Exiting veYND requires a 30-day queue, though liquid lockers will be introduced in collaboration with StakeDAO and Convex, allowing flexible delegation and auto-compounding. YieldNest governance follows a multi-phase proposal execution framework to ensure structured and well-vetted decision-making: 1. **Forum Discussion & Temperature Check** – Community discussions gauge proposal feasibility, with AI-driven sentiment analysis enhancing deliberations. 2. **Formal DAO Proposal** – A structured submission via Aragon V2, requiring support from major veYND stakeholders. 3. **Voting Phase** – A **7-day voting period**, auto-extended if quorum is reached near the deadline. 4. **Execution Phase** – Passed proposals undergo a **3-day cooldown** before execution by **YieldNest’s multi-sig or DAO-controlled smart contracts**. ### Security Council & Risk Mitigation To safeguard the protocol against governance attacks, smart contract vulnerabilities, and DeFi market risks, the YieldNest DAO has established a dedicated Security Council. Comprising nine elected members, the council is selected through on-chain governance votes every six months, ensuring a transparent and community-driven oversight mechanism. A 5-of-9 majority is required to authorize emergency actions, allowing for swift intervention when needed. **The Security Council is tasked with:** - Mitigating critical security threats and vulnerabilities. - Protecting the protocol from governance manipulation or hostile takeovers. - Responding to systemic risks in DeFi markets that may impact YieldNest’s long-term stability. By integrating transparent governance, AI-enhanced decision-making, and modular subDAOs, the YieldNest DAO ensures continuous innovation while maintaining the highest security and decentralization standards in the DeFi ecosystem. ## Conclusion The evolution of crypto asset productivity has reached a critical inflection point. Historically, non-productive assets like gold have served as stores of value, while productive assets have driven wealth creation through compounding returns. In the crypto space, Ethereum’s staking and restaking ecosystem exemplifies this shift, transforming ETH from a passive asset into one of the most capital-efficient digital assets in history. However, restaking’s execution challenges have shown that without effective risk controls and dynamic capital allocation, its long-term sustainability remains uncertain. As we discussed in this article, [YieldNest](https://www.yieldnest.finance/) is addressing these shortcomings by building tomorrow’s restaking infrastructure while enabling yield generation through DeFi’s optimization capabilities. The fundamental thesis is clear: build sustainable yield infrastructure that works today while maintaining strategic optionality for tomorrow’s opportunities. Unlike traditional LRTs that primarily extend Ethereum’s security model, YieldNest’s MAX LRT vaults redefine restaking as an integral component of capital-efficient DeFi. By making restaking the centerpiece of a broader yield aggregation framework, YieldNest unlocks new levels of capital efficiency, transforming passive staked assets into actively managed portfolios that capture security incentives and DeFi opportunities, all through a single user-facing asset. YieldNest begins with a hybrid approach that combines human oversight and automation to ensure optimal security, but over time, its AI-driven rebalancing engine, smart contract automation, and curated risk management layers enable capital to be deployed to the most optimal strategies *without manual intervention*. YieldNest differentiates itself through aggregation, automation, and risk-managed yield. Unlike single-protocol LRTs, MAX LRTs encapsulate multiple yield sources; staking rewards, restaking incentives, liquidity provisioning, and lending yields within a composable ERC-4626 vault structure. This eliminates the need for users to manually juggle multiple platforms and tokens, offering a set-it-and-forget-it experience where an AI-optimized portfolio handles all capital allocation. Through controlled exposure (whitelisted AVSs, position limits, dynamic risk monitoring), YieldNest ensures sustainable yield generation without compromising security. As the market matures, the most valuable assets will not be those that rely solely on scarcity, but those that generate yield, provide security, and offer financial utility. The demand for efficient, liquid, and risk-adjusted yield strategies will continue to grow. YieldNest’s modular and extensible architecture is well-positioned to capture this evolution—ensuring that every unit of crypto collateral simultaneously secures networks, earns yield, and strengthens the antifragility of the blockchain and DeFi ecosystems we are building. Just as yield farming, liquidity mining, and liquid staking shaped past DeFi cycles, restaking and meta-yield aggregation will define the next wave of innovation (or the “DeFi Renaissance 2.0”). The long-term vision for DeFi is clear: *bringing price discovery and volume fully on-chain, reducing reliance on centralized structures, and transitioning to an open, permissionless, and self-sovereign financial layer.* ## References: 1. [https://arxiv.org/html/2404.00644v3#S5](https://arxiv.org/html/2404.00644v3#S5) 2. [https://www.nasdaq.com/articles/liquid-restaking-tokens:-what-are-they-and-why-do-they-matter](https://www.nasdaq.com/articles/liquid-restaking-tokens:-what-are-they-and-why-do-they-matter) 3. [https://www.law360.com/articles/1859811](https://www.law360.com/articles/1859811) 4. Youtube — [Restaking Mania](https://www.youtube.com/watch?v=X7wtCGovhfc) 5. Youtube — [YieldNest Nest AI AMA](https://www.youtube.com/watch?v=5Rdn9TZHJXI) 6. Youtube — [YieldNest Staking Rewards Interview](https://www.youtube.com/watch?v=KOt0BW2mfEQ) 7. Youtube — [YieldNest - AI](https://www.youtube.com/watch?v=RIn9Q1pkzoY) 8. Youtube — [Why Choose YieldNest](https://www.youtube.com/watch?v=I55xz4nt35I&list=PLPQeHlSZIjTPkkg8z2UhD-lUgdmcVBRVU&index=3) 9. Youtube — [Decoding LRTFi Boom](https://www.youtube.com/watch?v=LZMz4qyRVZo) 10. [https://x.com/danielesesta/status/1875512495856619548](https://x.com/danielesesta/status/1875512495856619548) 11. [https://blockworks.co/news/restaking-ticking-time-bomb-eth](https://blockworks.co/news/restaking-ticking-time-bomb-eth) 12. [https://www.galaxy.com/insights/research/the-risks-and-rewards-of-restaking/#:~:text=There%20are%20a%20few%20other,of%20restaking%20on%20asset%20liquidity](https://www.galaxy.com/insights/research/the-risks-and-rewards-of-restaking/#:~:text=There%20are%20a%20few%20other,of%20restaking%20on%20asset%20liquidity). 13. [https://www.blog.eigenlayer.xyz/introducing-slashing/](https://www.blog.eigenlayer.xyz/introducing-slashing/) 14. [https://www.blog.eigenlayer.xyz/introducing-verifiable-agents-on-eigenlayer/](https://www.blog.eigenlayer.xyz/introducing-verifiable-agents-on-eigenlayer/) 15. [https://www.gauntlet.xyz/resources/avs-selection-framework](https://www.gauntlet.xyz/resources/avs-selection-framework) 16. [https://www.gauntlet.xyz/resources/optimizing-avs-allocations-for-liquid-restaking-tokens-lrts](https://www.gauntlet.xyz/resources/optimizing-avs-allocations-for-liquid-restaking-tokens-lrts) 17. [https://www.llamarisk.com/research/restaking-in-defi](https://www.llamarisk.com/research/restaking-in-defi) 18. [https://www.nethermind.io/blog/avs-allocation-strategies-eigenda-and-arpa-compared](https://www.nethermind.io/blog/avs-allocation-strategies-eigenda-and-arpa-compared) 19. [https://medium.com/@yieldnest/nest-ai-tokenomics-yieldnest-subdao-framework-1ed3cd672a43](https://medium.com/@yieldnest/nest-ai-tokenomics-yieldnest-subdao-framework-1ed3cd672a43) 20. [https://0xnest.ai/nest](https://0xnest.ai/nest) 21. [https://defillama.com/protocol/yieldnest](https://defillama.com/protocol/yieldnest) 22. [https://dune.com/yieldnest_official/yieldnest-protocol](https://dune.com/yieldnest_official/yieldnest-protocol) 23. [https://app.yieldnest.finance/restake/ynETH](https://app.yieldnest.finance/restake/ynETH) 24. https://docs.yieldnest.finance/ 25. [https://www.llamarisk.com/research/yieldnest-general-assessment](https://www.llamarisk.com/research/yieldnest-general-assessment) 26. [https://almanak.co/app/uploads/2024/12/almanak-litepaper-1.pdf](https://almanak.co/app/uploads/2024/12/almanak-litepaper-1.pdf) 27. [https://www.gauntlet.xyz/resources/liquid-restaking-token-lrt-market-risk-framework](https://www.gauntlet.xyz/resources/liquid-restaking-token-lrt-market-risk-framework) 28. [A Bull case for ETH](https://www.notboring.co/p/own-the-internet) 29. [https://dexa.ai/s/V7CK0Vx1](https://dexa.ai/s/V7CK0Vx1) 30. [https://blockworks.co/news/institutions-staking-eth-2-want-internet-bonds](https://blockworks.co/news/institutions-staking-eth-2-want-internet-bonds) 31. [https://blog.redstone.finance/2024/09/10/the-analysis-of-liquid-staking-liquid-restaking-yield-featuring-cesr-by-coindesk-indices-and-coinfund/](https://blog.redstone.finance/2024/09/10/the-analysis-of-liquid-staking-liquid-restaking-yield-featuring-cesr-by-coindesk-indices-and-coinfund/) 32. [https://www.linkedin.com/pulse/economics-liquid-restaking-mechanism-abubakr-qomorudeen-qmdef/](https://www.linkedin.com/pulse/economics-liquid-restaking-mechanism-abubakr-qomorudeen-qmdef/) 33. [https://www.forbes.com/councils/forbesfinancecouncil/2024/01/16/why-productive-assets-outperform-nonproductive-ones/](https://www.forbes.com/councils/forbesfinancecouncil/2024/01/16/why-productive-assets-outperform-nonproductive-ones/) 34. [https://alearesearch.io/perspectives/yieldnest/](https://alearesearch.io/perspectives/yieldnest/) 35. [https://blockworks.co/newsletter/daily/issue/post_82a65465-7a8d-4e2b-b2c1-4f0ab4da8153](https://blockworks.co/newsletter/daily/issue/post_82a65465-7a8d-4e2b-b2c1-4f0ab4da8153) 36. [State of the network issue](https://coinmetrics.substack.com/p/state-of-the-network-issue-288) 37. [https://medium.com/oregon-blockchain-group/liquid-restaking-wars-the-next-lido-5e8fd152d799](https://medium.com/oregon-blockchain-group/liquid-restaking-wars-the-next-lido-5e8fd152d799) 38. [https://decrypt.co/resources/a-brief-history-of-defi-learn](https://decrypt.co/resources/a-brief-history-of-defi-learn) 39. [https://blockworks.co/news/merged-mining-bitcoin-multi-chain](https://blockworks.co/news/merged-mining-bitcoin-multi-chain) --- ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the YieldNest team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # zkPass: Enabling Verifiable Data Composability > zkPass is redefining privacy & data verification by integrating ZKPs, Multi-Party Computation (MPC), and 3P-TLS. It enables verifiable, privacy-preserving data sharing across finance, healthcare, etc. - Publisher: Shoal Research (https://shoal.xyz) - Category: Privacy & ZK - Published: 2025-03-17 - Canonical: https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/ - Keywords: crypto, zero-knowledge, privacy, security, Bitcoin, DePIN, Privacy & ZK ![](https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/img/460c6d91f08b.png) ## Exploring the History of Privacy and Data Verification The history of privacy and data verification has evolved through a series of methods and technologies that reflect the changing needs of societies, businesses, and individuals. Before the advent of modern cryptographic protocols like **zkTLS** (zero-knowledge transport layer security), privacy and data verification were primarily handled through more traditional means, relying on trust, physical verification, and centralized systems. In ancient times, privacy was maintained largely through physical barriers or social norms. For instance, in medieval times, royal seals were used to authenticate documents and ensure privacy. These seals act as verifiable proof that the document came from a trusted source, although they were still vulnerable to forgeries. Similarly, handwritten letters with private information required trusted messengers to carry them safely, often leading to incidents of espionage or breach of trust, as there was no secure way to ensure the integrity of the transmitted data. As societies evolved, the need for more formalized data verification grew. In the 19th century, the advent of the postal system saw the rise of **envelopes and letters of authentication**. People relied on trusted institutions like banks and notaries to verify the authenticity of documents, as these entities were trusted to validate identities and certify information. For example, the birth certificate, a vital document for personal identification, could be verified by a government official or an appointed institution. This was a significant leap from manual methods, but it still required individuals to trust centralized authorities. Similarly, checks and paper-based business contracts, verified by signatures, still dominate. However, these methods had their limitations, especially regarding privacy, as sensitive information could be accessed by unauthorized parties or manipulated without sufficient safeguards.Data privacy and verification took on a more technical role in the digital age. The **invention of public-key cryptography** in the 1970s, with the development of algorithms such as RSA, allowed for secure communication over digital channels, revolutionizing how privacy was maintained. Encryption has become a cornerstone of privacy in the digital world, with users relying on methods like SSL (Secure Sockets Layer) certificates to secure their data when browsing websites. However, while SSL provided a level of encryption, it was not foolproof and still had the potential for man-in-the-middle attacks where a third party could intercept data and alter it. In e-commerce, for example, when people made online transactions, they relied on SSL certificates issued by trusted authorities to secure sensitive payment information, yet security breaches like the infamous **Heartbleed vulnerability** demonstrated that even encrypted connections could be susceptible to flaws. Fast forward to the early 2000s, and **blockchain technology** emerged as a potential solution for both data privacy and verification, with its decentralized nature promising to eliminate the need for centralized authorities to verify transactions. Bitcoin, introduced in 2009, offered a way to verify the integrity of financial transactions through a distributed ledger, allowing users to engage in financial exchanges without revealing sensitive information, as all transactions were encrypted and recorded publicly but pseudonymously. This was a significant advancement in terms of privacy, as individuals could maintain control over their data, but it was not without its limitations, such as scalability and transaction costs. The introduction of **Zero-Knowledge Proofs (ZKPs)** marked a new frontier in privacy and data verification. ZKPs allow one party to prove to another party that a statement is true without revealing any other information about the statement itself. This cryptographic method has gained significant traction in recent years, especially with the rise of privacy-focused cryptocurrencies like **Zcash**, where users could prove they owned a particular amount of cryptocurrency without revealing their balance or transaction history. **zkTLS**, a cryptographic protocol combining ZKPs with Transport Layer Security (TLS), represents the next step in ensuring secure communication over the internet, allowing for encrypted, private exchanges where the authenticity of the message can be verified without revealing the content itself. Imagine a future scenario where zkTLS is used in everyday life. A person enters a café and orders coffee. Instead of showing a physical ID card or revealing sensitive details, the person can use their phone to provide a **zero-knowledge proof of age**, which would validate that they are over the legal drinking age without disclosing their actual birth date. Similarly, in a corporate setting, an employee could prove their qualifications for a particular project using zkProofs without sharing the actual contents of their resume or personal data, safeguarding their privacy while still enabling the verification of their credentials. The stories of privacy and data verification are constantly evolving. In earlier times, trust was built on physical barriers, human intermediaries, and written agreements. As technology advanced, digital encryption became the cornerstone of data security, but it often still required a level of trust in centralized authorities or entities. Blockchain, with its decentralized approach, broke new ground, but privacy and scalability challenges remained. Now, **ZKPs and skills** are paving the way for a future where privacy and verification coexist seamlessly, offering individuals complete control over their data without compromising on trust or security. The shift is driven by declining costs, improved performance, and increased practical applications like Aligned Layer, Risk Zero, Succinct Labs, etc. ZK proofs are now cheaper than traditional consensus-based verification, making them a compelling alternative for blockchain scalability and data security. Additionally, advancements in binary fields and hardware acceleration are optimizing ZK computations, reducing inefficiencies that previously slowed adoption. Industries beyond crypto are recognizing the potential of ZKPs in secure identity verification, financial transactions, and compliance. From proving financial integrity without exposing transaction details to verifying credentials without revealing personal data, ZKPs are reshaping digital trust. As adoption expands, we are approaching a future where ZKPs become the standard for secure, efficient, and private verification across various sectors, including finance, enterprise security, and Web3 applications. ## Overview zkPass is a private Oracle protocol that enables private internet data to be verifiable on-chain. Built on top of zkTLS, which is composed of 3P-TLS and hybrid ZK technologies, zkPass provides tools and applications for secure, verifiable data sharing with privacy and integrity assurances from any HTTPS website without requiring OAuth APIs. It is designed to serve as a private data oracle, leveraging Vector Oblivious Linear Evaluation (VOLE) to create efficient commitments, commonly referred to as VOLE-Based Zero-Knowledge Proofs (VOLE-ZK). zkPass allows users to selectively prove various types of data, such as legal identity, financial records, healthcare information, social interactions, and certifications. These zero-knowledge proof computations are performed locally and securely, ensuring that sensitive personal data is not leaked or uploaded to third parties. They can be used for AI, DePIN, DID, lending, and other financial and non-financial applications. Wherever there is a need for trust and privacy, zkPass can be a solution. zkPass proposes a new paradigm for the traditional data validation and confirmation process, where the verifier is positioned between the prover and the data source. The prover uses the verifier as a proxy, utilizing its access token to retrieve data from the data source. Subsequently, by using the VOLEitH technique, a publicly verifiable proof is generated locally and sent on-chain. This process ensures the verifier remains unaware of the prover's personal information. ## Why zkPass? zkPass, a private data protocol, is seen as the best protocol in its niche due to various reasons, including *privacy-preserving of data, anti-cheating mechanism, verifiability of data, seamless integrations with other applications, and zkPass memory efficiency.* ### Privacy-preserving of data zkPass works by allowing users to create a digital identity that can be verified without exposing the actual information. For example, a user could prove they are over a certain age without disclosing their full birthdate, or they could authenticate their school degree to access services without revealing the exact university or other personal details. This functionality is achieved through ZKPs, which ensure that only the necessary data is shared and that it cannot be reverse-engineered to expose sensitive information. This method allows zkPass to address key concerns around online privacy, enabling individuals to participate in digital services confidently without sacrificing their security. ![](https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/img/1f40ab6c48e7.jpg) The adoption of zkPass has seen impressive growth, with over **4.5 million cumulative ZKPs generated** over time and **1.6 million+ onchain ZK Proofs generated** to date. Additionally, the platform has facilitated **500K+ unique wallet addresses**, demonstrating strong user engagement and adoption. *(Source: [Dune Dashboard](https://dune.com/zkpass/dashboard))* ### Verifiability of data In traditional TLS, two parties (client and server) exchange encrypted data to secure communications. However, zkPass introduces a third party into the TLS handshake, which serves to independently validate the authenticity and origin of the data being exchanged. This three-party approach enhances the security of data provenance because the third party can verify the integrity of the communication without actually accessing the private data itself. This enables both **verifiability** and **privacy** in transactions, offering a higher level of security for sensitive information like digital identities or credentials. In the context of zkPass, users can authenticate themselves, prove attributes (e.g., age, location), or conduct transactions without exposing private information by using the decentralized MPC nodes that can verify a user's data integrity before generating a ZKP. It ensures that only the relevant proofs of data are shared, while the actual underlying private data is never disclosed. This approach offers robust privacy protection while guaranteeing the integrity and authenticity of data across digital platforms. ### Integrations with other Applications zkPass seamlessly integrates with any HTTPS-enabled website, ensuring privacy and security without the need for complex APIs or licenses. By leveraging Zero-Knowledge Proofs (ZKPs) and a redesigned three-party TLS protocol, zkPass allows users to authenticate and prove specific attributes without revealing sensitive data. This ensures compatibility across a wide range of applications, offering a smooth, privacy-first user experience while maintaining robust security and data provenance. zkPass has been gaining traction with the rise of Zero-Knowledge (ZK) use cases, integrating [57 partners and 74+](https://dune.com/zkpass/dashboard) data sources for privacy-preserving data verification. It is collaborating with leading projects to enable real-world applications, including: - **[Plume Network](https://x.com/zkPass/status/1866491833171488917)** – Facilitating verifiable web-private data for secure real-world asset ownership and tokenization on RWAfi. - **[Push Chain](https://x.com/PushChain/status/1882435643483336929)** – Enhancing dApp interactions with ZK Proofs and Universal Shared State, ensuring user data privacy. These partnerships reinforce zkPass's role in simplifying secure digital identity verification across diverse sectors. ### Memory-Efficiency To achieve millisecond-level Zero-Knowledge Proof (ZKP) generation locally in a browser environment, zkPass utilizes a VOLE-based Interactive Zero-Knowledge Proof (IZK) approach, offering efficient memory usage and rapid computation. VOLE (Verifiable Oblivious Linear Evaluation) reduces the computational and memory overhead by eliminating the need for storing large intermediate values, making it ideal for resource-constrained environments like browsers. This allows for the parallelization of computations using Web Workers, optimizing performance while maintaining low latency. ### Anti-Cheating Mechanisms The anti-cheating mechanism in zkPass is designed to ensure the integrity and authenticity of data exchanged between clients and servers, safeguarding against tampering or fraudulent activities. It uses zero-knowledge proofs to validate both the requests sent by clients and the responses received from servers. The mechanism verifies that the client's request data is correct by checking encrypted request data against expected values while also ensuring that the URL provided by the client matches a predefined template. On the response side, zkPass verifies that the encrypted response matches the expected ciphertext, ensuring the integrity of the data received. Additionally, it checks that response attributes align with a specified template and validates the correctness of the values returned. By employing these checks, zkPass prevents malicious actors from exploiting vulnerabilities to manipulate data, thus enhancing the overall reliability and credibility of the system and ensuring trust in the data exchange process. ## How does zkPass work? ![](https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/img/a4d68bdcaf24.jpg) The zkPass protocol was designed and implemented in two modes: ***proxy mode and MPC mode.***In the proxy mode, the prover(P) communicates with the server(S) through the verifier(V) as a proxy, while in the MPC mode, both the prover(P) and verifier(V) act as a client to communicate with the server(S). These two modes collectively form **Hybrid Mode**, providing zkPass with the flexibility to operate efficiently across various scenarios. Typically, the zkPass protocol operates efficiently in Proxy Mode. However, a small number of TLS servers do not support this mode, meaning they block the same account’s requests originating from different IP addresses. In such cases, the protocol switches to operate in MPC mode. ### Proxy Mode In Proxy Mode, we propose having **V**act as a proxy between **P**and **S**. In this setup, **P**communicates with **S**through **V**, which allows **V**to record the traffic for later verification. The modified protocol flow is designed to maintain security while improving efficiency. The proxy model has lower latency when compared to the MPC model, making it better suited for large-scale, real-time client applications. ![](https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/img/27ebf8d6e7cb.jpg) The protocol begins with a **three-party handshake** involving P (prover), V (verifier), and S (server), where cryptographic parameters are established, ensuring mutual authentication between the parties. Following the handshake, P commits to her key share (Kp), preventing any later alterations to her key share and ensuring she cannot manipulate the session to generate fraudulent proofs. This commitment occurs before P learns the complete session key (K). Subsequently, V reveals his key share (Kv) to P, who, combining both key shares, computes the full session key**(K = Kp + Kv)**. With the session key, P continues the TLS session with S, while V acts as a proxy, recording all the traffic between P and S. After the session concludes, P generates proof about the recorded session, which is then verified by V. To confirm the server's identity during the three-party handshake, V checks the server's signature on a fresh nonce, as per standard TLS procedures. The integrity and privacy of the verifier are preserved because, assuming TLS is secure, a malicious V cannot undermine the integrity or privacy of the TLS session between P and S. However, ensuring the integrity of the prover requires certain network conditions. V must have a stable connection to S throughout the session and prevent P from interfering with the messages exchanged between V and S, such as through BGP hijacking. Since attacks like BGP hijacking are difficult to execute and are largely mitigated by ICP and CSP, these network requirements are generally acceptable and can be considered negligible in practical scenarios. The Proxy Mode in the zkPass protocol enhances efficiency and performance by simplifying the communication flow and eliminating the need for intensive cryptographic computations after the handshake phase. Since no complex cryptographic operations are required during the rest of the session, the protocol becomes faster and more efficient due to the reduced cryptographic workload. While this approach is more universal, it introduces an additional trust assumption for the proxy and requires not only a ZK solution that’s affordable for the client but also special magic tricks to bypass the data source’s WAF. VOLEitH Protocol To design the zkPass protocol, the VOLEitH protocol, which is suitable for authorizing TLS, was used. The VOLEitH protocol was integrated to achieve an interactive argument system, which is then made non-interactive using the *Fiat-Shamir transform*. The VOLEitH protocol was implemented into zkPass using SoftSpokenOT [ROY22], VOLE-ZK [YSWW21], and Fiat-Shamir transform [FS87]. zkPass utilizes the VOLE-ZKs, which are much more efficient than SNARKS. VOLE-ZKs naturally handle linear computations, enabling fast and low overhead, which makes them more suitable for authorizing TLS data. They avoid the need for a trusted setup and do not require large memory or extensive calculations for proof generation, making them affordable for clients. However, VOLE-ZK proofs are interactive, necessitating the verifier’s continuous online presence and potentially introducing risks of collusion. The zkPass protocol employs the VOLEitH technique, transforming the VOLE-ZK protocol into a non-interactive form. This ensures swift and efficient proof generation directly in the browser and device, addressing the limitations of both traditional SNARKs and VOLE-ZKs. By doing so, zkPass combines the efficiency of VOLE-ZK proofs with the convenience of non-interactivity, making it a practical and secure solution for authorizing TLS data. ### MPC Mode In MPC Mode, zkPass utilizes a hybrid approach that combines ZKP and MPC technologies to achieve 3P-TLS. Both the P and V work together as a single client to establish secure communication with S. They achieve this through a series of stages based on the elliptic curve Diffie-Hellman (ECDH) protocol, enhanced with MPC and OT techniques. ![](https://shoal.xyz/research/writing/zkpass-enabling-verifiable-data-composability/img/2039e9c865c3.jpg) Three-Party Handshake The first stage of the protocol is a three-party handshake between P, V, and S, where they work together to generate the pre-master key. P and V each receive a share of this key using Oblivious Linear Evaluation (OLE)-based multiplicative-to-additive (MtA) or additive-to-multiplicative (AtM) schemes, which support additive homomorphism. The pre-master key is divided, with P and V each getting one half, while S retains the full key. To ensure authenticity and prevent the client from impersonating fake websites, after the client and server exchange greetings, the server provides its certificate. During the key exchange phase, the server also signs the public key with its private key from the certificate. This allows V, within the client, to verify the certificate and signature, confirming the server’s identity and establishing trust in the data source. The second stage of the protocol is key derivation, where P and V work together using Garbled Circuit (GC) to generate two session keys from the pre-master key: the encryption key (enc_key) for data protection and the message authentication code key (mac_key) for data integrity. Notably, V only holds a share of the mac_key and has no access to the enc_key, ensuring that V cannot view P’s private information. P also holds a share of the mac_key, giving access to identity-related data but without the ability to tamper with it. Any tampering can be detected by verifying the authenticity of messages using the mac_key. The MPC algorithm in zkPass has been significantly optimized in several areas, including communication time, hash functions for the Garbler and Evaluator, OT operations, and memory copying. These improvements have increased efficiency by more than threefold. A new AES128 proof method has also been introduced, reducing the number of blocks by 300 times and speeding up Garbler/Evaluator execution by tenfold. zkPass uses silent OT, minimizing offline network communication during OT generation. For GC, zkPass implements Three Halves Make a Whole and Stacked GC, which reduces the size of the Garbled Tables, leading to less communication and faster execution. Overall, these optimizations have greatly reduced the runtime of the entire MPC process, making zkPass much more efficient. **In the final stage of the zkPass protocol, the client creates a ZKP for public verification. After the 3P-TLS phase, the prover obtains the complete data and uses the VOLEitH process to generate a proof. Since this step is similar to the process used in proxy mode, we won’t go into the details here.** ### Hybrid Mode In hybrid mode, zkPass switches seamlessly between proxy mode and MPC mode, which then allows the protocol to adapt to various network environments and server policies without compromising efficiency or security. Proxy Mode ensures high performance with minimal cryptographic overhead, while MPC Mode takes over when certain servers block requests from multiple IP addresses, maintaining privacy and security. The use of VOLEitH further enhances efficiency by avoiding the heavy computational and memory demands of traditional cryptographic systems like SNARKs. The key features of the zkPass hybrid mode are: - **Dynamic Mode Switching**: It adapts to varying characteristics of data sources (e.g., network environments and server policies) by dynamically switching between models to ensure maximum compatibility and an optimal client experience. - The hybrid mode combines memory efficiency from interactive zero-knowledge proofs and incorporates the public verifiability of non-interactive zero-knowledge proofs. ## Use Cases zkPass redefines data verification and privacy-preserving in the digital age. With its innovative combination of Multi-Party Computation (MPC), Zero-Knowledge Proofs (ZKP), and 3-party Transport Layer Security (3P-TLS), zkPass empowers individuals to take control of their private data and safeguard their privacy across various aspects of their lives. The use cases of zkPass cut across various industries from decentralized finance, DAO, and NFT to online banking, education, medical, and healthcare. ## Legal Identity Check: zkKYC Traditional KYC solutions face several challenges, including privacy concerns, as they often require individuals to disclose extensive personal information, raising risks of identity theft and unauthorized data access. Additionally, centralized data storage systems are vulnerable to breaches, and businesses incur high costs for implementation, training, and compliance efforts. The process is also slow, involving manual verification and numerous interactions, which can delay onboarding. Inefficiencies arise from fragmented data management, and a lack of interoperability forces customers to repeat the KYC process for different services. Compliance with ever-changing regulations is difficult, and fraud remains a constant risk, despite verification efforts. zkKYC, based on zkPass, provides a solution by using zero-knowledge proofs and multi-party computation to address these issues. It ensures privacy by allowing users to verify their identities without disclosing sensitive information. By decentralizing data storage, zkKYC reduces the risk of data breaches and gives users more control. The process is cost-effective, faster, and more efficient, reducing manual work and improving data management. zkKYC also offers interoperability, allowing seamless sharing of verified information across services, and adapts to changing regulations, ensuring ongoing compliance. Moreover, its secure methods, including zero-knowledge proofs, reduce fraud risks. Use cases for zkKYC include tenant screening in rental properties, where landlords can verify identity and financial background without accessing sensitive data. It can be employed for age and identity verification in online gaming platforms, social media, and the gig economy, ensuring compliance and security while protecting privacy. Additionally, zkKYC can be used to validate digital signatures and authenticate users on secure messaging platforms, safeguarding sensitive communications and transactions. ## Finance As digital finance continues to grow, several challenges have emerged, including identity theft and fraud, which result in significant financial losses and reputational damage to both individuals and institutions. Privacy concerns are also rising, as users are increasingly worried about protecting their sensitive personal and financial information when interacting with financial services. Financial institutions also struggle with meeting KYC and AML compliance requirements while minimizing user friction and maintaining privacy. Additionally, there is a need for interoperability between DeFi and CeFi platforms, requiring a secure identity solution that seamlessly integrates across various financial applications. zkPass, a composable, privacy-preserving identity protocol utilizing zero-knowledge proofs (ZKP) and multi-party computation (MPC), addresses these challenges by offering secure and privacy-preserving solutions. It enables proof of funds, credit scoring, insurance claims, risk assessment, transaction screening, and user access control, all while protecting sensitive user data. zkPass can be integrated into DeFi platforms to enhance trust and reduce fraud. Streamline lending processes by verifying creditworthiness without exposing personal details and secure insurance claim verification. It also ensures privacy for charitable donations, fosters trust in crowdfunding by verifying identities and supports secure, private interactions across various financial services. ## Education The education sector faces a range of challenges, particularly concerning privacy, security, and efficient data sharing. One of the main concerns is protecting minors' privacy, as educational institutions are responsible for handling the sensitive data of minors and must comply with strict privacy regulations. Another challenge is ensuring academic integrity, as preventing cheating and plagiarism is essential for maintaining high educational standards. In research, confidentiality is crucial, as projects often involve sensitive information and intellectual property that must be safeguarded. Furthermore, international data sharing is increasingly necessary for cross-border collaborations, but it requires secure methods that comply with various regional data protection regulations. Additionally, verifying the authenticity of academic credentials, such as degrees and certificates, is vital for maintaining trust and credibility in the education system. zkPass, a privacy-preserving identity solution, addresses these challenges effectively. It offers secure and verifiable identity verification for educational purposes, ensuring compliance with privacy regulations for minors and protecting sensitive data. zkPass supports the verification of academic degrees and transcripts, streamlining the process of confirming qualifications while minimizing privacy risks. It also enables secure and private interactions during online exams, preventing plagiarism and ensuring academic integrity. For research, zkPass facilitates secure collaborations while safeguarding intellectual property and sensitive research data. Moreover, it provides a solution for international data sharing, allowing educational institutions to securely share data across borders while adhering to regional data protection regulations. Through blockchain-based credential management, zkPass simplifies the verification of educational credentials, promoting trust in global research collaborations. By addressing the specific challenges of privacy, security, and data sharing, zkPass has the potential to transform the education and research sectors. It enhances learning experiences, streamlines academic processes, and fosters secure and privacy-preserving research collaborations, all while ensuring compliance with complex data protection regulations. As the sectors continue to embrace digital technologies, zkPass is poised to play a key role in shaping a secure, inclusive, and collaborative future. ## Medical & Healthcare The medical and healthcare sectors face several critical challenges related to privacy, security, and efficient data sharing. Privacy protection is a major concern, as safeguarding sensitive patient information and ensuring compliance with data protection regulations like HIPAA and GDPR are essential. Healthcare organizations also face difficulties in securely sharing medical records and health information between patients, healthcare providers, and other stakeholders. The sector struggles with reducing administrative burdens and minimizing errors associated with manual identity verification and data-sharing processes. Additionally, there are issues related to fraud prevention, particularly in insurance claims and prescription management, where secure identity and data verification are needed. Regulatory compliance is another challenge, as healthcare organizations must meet stringent data protection and privacy obligations. Furthermore, interoperability remains a hurdle, as the sector requires secure and efficient data sharing across different platforms and organizations to enhance collaboration and coordination. zkPass, a privacy-preserving identity solution, offers several solutions to these challenges. It enables secure patient identity verification, ensuring that personal health data is protected in compliance with data privacy regulations. zkPass can be integrated into blockchain-based electronic health records to facilitate secure, private access to medical records while maintaining data integrity. It supports secure sharing of medical records between healthcare providers and stakeholders, improving data accessibility and reducing administrative overhead. zkPass also plays a crucial role in clinical trial participant verification, ensuring that participants' identities and health data are kept confidential while fostering trust in the research process. Additionally, zkPass can streamline health insurance claim verification and prescription management, reducing fraud and ensuring the privacy of sensitive health information. For telemedicine and remote consultations, zkPass ensures secure identity verification and the safe sharing of health information. It can also be used in emergency medical services, providing responders with rapid, secure access to critical patient data, such as medical history and allergies, without compromising privacy. zkPass further supports cross-border health data sharing, allowing healthcare providers in different countries to share patient data securely and privately, enabling seamless care coordination for international patients. By adopting zkPass, healthcare providers can implement patient portals that offer individuals secure access to their health information while maintaining control over their data privacy. In precision medicine, zkPass facilitates the secure sharing of genetic and health data, enabling researchers and healthcare providers to develop personalized treatment plans based on patient's unique needs. By addressing the challenges related to identity verification and secure data sharing, zkPass has the potential to significantly improve privacy, security, and efficiency in the healthcare sector. It enhances patient experiences, streamlines processes, and ensures compliance with data protection regulations. As the healthcare industry continues to adopt digital technologies, solutions like zkPass will play a pivotal role in creating a more secure, patient-centered, and collaborative future. ## Conclusion In conclusion, zkPass represents a significant breakthrough in the pursuit of privacy and secure data verification in the digital era. As the internet continues to evolve and expand, so does the need for robust methods to protect personal information, especially as individuals increasingly share sensitive data for various online services. With cyber threats becoming more sophisticated and pervasive, the ability to securely verify data without exposing unnecessary personal details is more important than ever. zkPass offers a unique and effective solution by leveraging cutting-edge cryptographic techniques such as **zkTLS** and **VOLE-ZK**, allowing users to authenticate and prove credentials while preserving their privacy. The core innovation of zkPass lies in its ability to utilize **zero-knowledge proofs (ZKPs)**, a method that allows one party to prove to another that a statement is true without revealing the underlying information. This ensures that sensitive personal data—whether it pertains to an individual’s identity, qualifications, financial status, or other sensitive attributes—can remain confidential while still being verifiable. For example, a person can demonstrate their age, financial stability, or educational background without exposing their date of birth, salary details, or the name of the institution they graduated from. This greatly reduces the risks associated with data breaches, as only the required proof is shared, not the full set of sensitive information. The integration of zkPass into existing infrastructures, particularly through its compatibility with HTTPS websites, is a key feature that sets it apart from other privacy solutions. Traditional privacy-preserving systems often require complex setups, such as new APIs or custom protocols, which can be time-consuming and difficult to implement. However, zkPass is designed to work seamlessly within existing digital ecosystems, allowing users to enhance their privacy without the need for substantial changes to the websites or platforms they use. This ease of adoption makes it an attractive option for organizations and developers seeking to improve data security and privacy without significant overhead or disruption to their existing operations. Moreover, zkPass's hybrid approach, combining **proxy mode** and **multiparty computation (MPC)**, further enhances its flexibility and scalability. Proxy mode allows data to be relayed securely between parties while maintaining privacy, while MPC ensures that sensitive computations can be carried out collaboratively among multiple parties without exposing private data. This flexibility makes zkPass adaptable to a wide range of use cases, from simple authentication processes to more complex applications in fields like finance, education, and healthcare. For example, a financial institution could use zkPass to verify an individual's creditworthiness without ever needing to access or store sensitive financial details, reducing the likelihood of data exposure in case of a breach. The implications of zkPass extend far beyond mere privacy enhancement; it also facilitates a shift toward a more **trustworthy, verifiable** digital environment. As more aspects of daily life move online, the need for robust and verifiable credentials is increasing. Whether for accessing government services, enrolling in educational programs, or proving one’s employment history, zkPass offers a secure method of verification that can be universally adopted. By providing verifiable proof without compromising privacy, zkPass empowers individuals to maintain control over their data while interacting with digital platforms. In sectors like healthcare, for instance, zkPass could allow individuals to prove that they are eligible for certain medical treatments or insurance policies without revealing their complete medical history. Similarly, in education, students could prove that they hold specific degrees or certifications without exposing grades or other private academic records. This could revolutionize how credentials are managed and shared, creating a more secure and efficient way for institutions to verify qualifications without needing to store or share unnecessary private data. As we move toward a future where privacy is a growing concern and data security is paramount, zkPass is poised to play a central role in reshaping how we interact with digital services. It strikes a critical balance between privacy and verifiability, two often conflicting goals in the current landscape of data-sharing technologies. With its seamless integration, cryptographic foundation, and flexibility across multiple sectors, zkPass sets a new standard for privacy-preserving data sharing. It ensures that as digital systems become more interconnected, individuals can still maintain control over their personal information, thus fostering greater trust and security in online interactions. Ultimately, zkPass is a privacy tool and a catalyst for building a more secure, transparent, and privacy-respecting digital ecosystem. As the world increasingly turns to digital solutions, zkPass could become a foundational technology, ensuring privacy remains at the forefront of online engagement. --- ## References Technical Overview Offical Doc. [https://zkpass.gitbook.io/zkpass/overview/technical-overview-v2.0](https://zkpass.gitbook.io/zkpass/overview/technical-overview-v2.0) Introducing the Hybrid Mode of zkTLS: A zkPass Innovation. [https://medium.com/zkpass/introducing-the-hybrid-mode-of-zktls-a-zkpass-innovation-9ec18b36f397](https://medium.com/zkpass/introducing-the-hybrid-mode-of-zktls-a-zkpass-innovation-9ec18b36f397) zkTLS—The Cornerstone of Verifiable Internet. [https://medium.com/zkpass/zktls-the-cornerstone-of-verifiable-internet-da8609a32754](https://medium.com/zkpass/zktls-the-cornerstone-of-verifiable-internet-da8609a32754) --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been sponsored by zkPass team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # zkTLS: Verifiable Data Composability > zkTLS integrates zero-knowledge proofs into TLS, enabling secure, private data verification between Web2 and Web3. - Publisher: Shoal Research (https://shoal.xyz) - Category: Privacy & ZK - Published: 2025-03-10 - Canonical: https://shoal.xyz/research/writing/zktls-verifiable-data-composability/ - Keywords: AI agents, crypto, DeFi, zero-knowledge, privacy, infrastructure, Base, Privacy & ZK ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/85154704e7ba.png) ## Web Proofs and the Internet of Tomorrow Today’s internet is a mosaic of walled gardens, each governed by centralized authorities that dictate standards and control interoperability. Users are compelled to share personal data with these platforms, which may then be handed over to governing bodies or third parties, often without full transparency or user consent. While this model functions—albeit imperfectly—in sectors like finance, it poses significant challenges for social media and the internet at large. One of the most pressing issues is the ease with which operators can sever integrations with affiliated services or competitors, effectively locking users into their ecosystems. We've witnessed this repeatedly: Facebook (now Meta) restricting data access to integrated partners or Twitter placing API access behind a paywall. Such actions not only stifle competition but also limit user autonomy and expose personal data to risks like theft and loss, especially in the event of targeted cyberattacks. But what if there were a way to dismantle these barriers without compromising security or functionality? Enter **zero-knowledge Transport Layer Security (zkTLS)**—a revolutionary approach that integrates zero-knowledge proofs into the foundational protocols of the web. zkTLS offers a path to liberate users from the retention techniques employed by big tech, mitigating user lock-in while enhancing privacy and security. In this paper, we delve into the concept of web proofs through the lens of zkTLS. We'll explore how this innovative technology can reshape the internet by enabling secure, private interactions without the need to divulge unnecessary personal information. By leveraging zkTLS, we can pave the way for an internet that is not only more open and interoperable but also more aligned with the needs and rights of individual users. Join us as we unpack the potential of zkTLS to transform the digital landscape, fostering an internet built on trust, freedom, and user empowerment. It's time to shine a light on the technologies that can redefine our online experience for the better. ## The AGI advent and autonomous agents on social media The recent rise of artificial intelligence, mostly via large language models (LLMs) and generating images with large language models (GILL), has exacerbated these issues. The technology is extensively trained to be as human-like as possible and so needs access to a huge amount of data to learn the “skill” of being human in the hopes of eventually attaining sentience and producing its thoughts. The training models of such technologies take on a “learn by observation and regurgitation” model, exposing them to observable human interaction in every possible context; and what better venue is there for gaining insight into random people's personal lives and interactions apart from social media? User data has been greatly harvested across every major channel and funneled into the training models for our AI overlords, fuelling the rapid rise of their offerings. This scraping strategy is understandably countered by social media companies, who may either be competitors or would prefer to be paid for access to user data. Thus, data is now a costly commodity and will likely continue to be so, especially as the internet and social media return to niche, curated communes with high trust levels. ## The Web3 Lens Digital assets and blockchain technology have innovated greatly, but mostly in a siloed and self-referential manner, building systems that are mostly independent of traditional systems and values. The relevant value proposition in this context is that blockchain technology enables the immutability of data, and the underlying ethos is such that systems built atop them replicate their openness. As such, anyone can access any data that is available onchain, without the data's owner having to “permit” them. This observation shows how greatly different crypto is from both traditional systems and the AI hype — it goes all the way out to propose the openness of *every data* for*everyone*permissionlessly. However, the opposition of their underlying ideologies doesn't negate the fact that: 1. They each come with their benefits and downsides, 1. each system's benefits can, in most cases, be used to enhance the other's features, 1. If we're serious about “onboarding the next billion” to crypto, then it is a trivial assumption with nontrivial implications that the user base of blockchains is a subset of that of legacy institutions. The inability/refusal of legacy systems to take advantage of crypto innovations to enhance their performance shouldn't (and doesn't) prevent crypto from taking advantage of their reliable components. The most notable of such components is legacy systems’ brimming vat of user behavioral data gathered over decades. User data is sold to advertisers for revenue and is often stolen in every other data breach. This also applies to crypto + AI; while this intersection is still mostly saturated with undeniable cash grabs and buzz words primed for the next raise at dizzying valuations, there's still [some exploration](https://x.com/_weidai/status/1829194060554522915?t=QMllM7P6_iPvW5GzxJou5A&s=19) to be done. ### Personal data through the lenses of crypto Entry into crypto faces a cold start problem, as (apart from centralized exchanges) there is no widely known means for the average user to gain access/exposure to blockchain technology. The average entrant to crypto has to create an entirely new identity (in most cases a wallet address), then go about finding a way to fund it to access the services of decentralized applications. Allowing a user’s identity in legacy systems to persist onchain, whether fully or partially (if the user wishes) will essentially unlock the next wave of innovation in DeFi beyond speculation and musical chairs. This is the stated goal of web proofs and “zkTLS”: enabling portability of offchain user data, with provable provenance and privacy guarantees, so that users can easily access the offerings of onchain environments in a more trustless manner than is currently possible. Data use is typically restricted at its point of origin, thus disabling the portability of user data, which is invariably one of the reasons for the identity diversion problem faced by crypto users. Web proofs propose to solve this by enabling the users to act as an oracle of sorts between legacy and crypto institutions, and even between legacy institutions. Below, we will begin with an overview of the traditional TLS scheme. ## Web proofs and the TLS problem The [transport layer security](https://en.wikipedia.org/wiki/Transport_Layer_Security) is a cryptographic protocol that provides privacy and data integrity guarantees between communicating parties over a computer network. The parties are usually a client (referred to as a prover henceforth for consistency) who sends requests to a server; while the server sends back a response to the prover's request. TLS generally consists of two sub-protocols: 1. The handshake protocol- is responsible for establishing a shared communication channel between the user (also the prover) and the data source (also the server). > This protocol employs asymmetric cryptographic schemes to allow the server and prover to come to an agreement on which *cipher suite* to use for data transmission. They then authenticate each other and securely compute a shared secret key to be used in the second phase of the session. 1. The record protocol- is responsible for transmitting data while maintaining integrity (and optionally, confidentiality), using symmetric cryptographic schemes. > In this phase, the prover's requested data is fragmented into fixed-size plaintext records, which may be padded and compressed to decrease transmission costs. These records are then tagged with a *message authentication code* (MAC), encrypted, and the result is transmitted to the prover. Upon reception, the data is decrypted and verified using the prover's keys, the contents are decompressed, reassembled, and then delivered to higher-level protocols. This is a generalization of the process, as it varies by version and authentication schemes. However, in the setup, only the prover and server can communicate with and understand each other. This means that the data passed to the prover is unusable in any other context, as they cannot prove its source. Thus, the use of a web proof obtained using the results of a traditional TLS session doesn't prove anything, especially since: 1. the proof was constructed using messages from a specific server, 1. the message wasn't altered by the prover after it received it from the server. The widespread adoption of the TLS protocol enables users to access their data, private or otherwise, over channels with provable end-to-end confidentiality. The strict confidentiality of the protocol means that a user's data is available to only them, and whoever else the data source chooses to share it with. This is effectively a form of user lock-in, as users cannot access and export their data as need be, they'd almost always have to get explicit permission from the data source to be able to export their data for even the simplest purposes. This can be solved by introducing a third party who verifies that the prover doesn't alter the server's response, amongst other desirable properties. This family of protocols which are being pioneered by crypto portcos to enable data provenance are ([erroneously](https://x.com/DCbuild3r/status/1830146210717479381?t=1C-LJcpLHj2MCJBtwWsiRA&s=19)) referred to as *zkTLS* (zero-knowledge transport layer security) protocols. ## What is zkTLS? The crypto ecosystem has long been separated from the traditional "Web2" world due to technical constraints that prevent seamless interaction and composability. This is primarily because the underlying infrastructures are not directly interoperable. The inability of these two ecosystems to share data has led to significant fragmentation, which is difficult to overcome since most “Web3” systems lack the means to verify data from the “Web2” ecosystem. This isolationist design within the Web3 ecosystem is not a feature but rather a limitation. Therefore, a solution is needed to establish a connection and foster integration between these ecosystems. In the Web2 world, verification of data is limited because HTTPS only ensures secure transmission between the user and the website, but does have a means for third parties to independently verify the authenticity of the data. Web3, which operates on decentralized blockchain technology, solves this problem by ensuring data is stored on a transparent, immutable ledger. In this system, anyone can independently verify the authenticity of the data without needing to rely on a central authority or the source due to the advent of the zero-knowledge proof technology which makes it possible to share data and the data be independently verified by anyone in the network. ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/57dfe5decf0a.gif) **zkTLS**(Zero-Knowledge Transport Layer Security) is a protocol that creates a gateway between private Web2 data and the Web3 ecosystem. zkTLS is a hybrid protocol that integrates the zero-knowledge proofs with the TLS encryption system, allowing for secure data transmission between the Web2 and Web3 ecosystems while maintaining privacy. It allows users to securely export data from any website without the risk of leaking unnecessary data. zkTLS integrates two technologies: TLS (Transport Layer Security), a cryptographic protocol that serves as the backbone of secure web communication over the internet. It is mostly used in secure browsing, where data is used to encrypt and protect data transmitted between browsers and web servers. On the other hand, ZK (zero-knowledge proofs) allow *a prover* to prove the validity of a piece of information to *a verifier* without revealing the actual content of the information to the *verifier.* This combination ensures that while data remains encrypted during transmission, it can also be verifiable without the exposure of sensitive details. This is especially valuable in decentralized applications (dApps), where privacy and security are of great importance. ### How does zkTLS work? zkTLS enhances the standard TLS protocol by adding a verifiable privacy layer through Zero-Knowledge Proofs. Firstly, TLS encrypts communication to prevent eavesdropping, and zkTLS enables selective data disclosure. Then zero-knowledge proofs are created and shared with the verifier. These proofs allow the verifier to validate certain facts (e.g., that a transaction meets specific requirements) without exposing sensitive data like account balances or personal details. This balance between security and privacy is what makes zkTLS unique. One of the main components of zkTLS is its use of Multi-Party Computation (MPC) setups, where multiple parties cooperate to encrypt and decrypt data without any single party having access to the full encryption key. This ensures that no tampering can occur during the data transmission, adding an extra layer of trust to the process. ## Understanding the Applications With its improved privacy, security, and user reach, zkTLS is transforming the way blockchain ecosystems can communicate with off-chain data. For instance, decentralized financial systems and token airdrops have historically been restricted by on-chain activity such as on-chain history transactions, swaps, or bridges, which restricts possible users to individuals who are already active in the cryptocurrency space. zkTLS expands these boundaries by enabling the use of off-chain activities, like streaming music on platforms such as Spotify, purchasing items from Amazon, or even participating in ridesharing, as criteria for distributing tokens. This integration increases the pool of potential token recipients and allows projects to capture data on real-world activities in a privacy-preserving manner. By leveraging zkTLS, airdrops can reward verified, genuine users, fostering a larger, more diverse community while preventing fraud. In DeFi lending, zkTLS facilitates trust and transparency by enabling secure verification of off-chain actions, such as income verification or contributions to open-source projects. This can influence on-chain rewards without exposing sensitive financial data. Unlike traditional oracles that may lack privacy and scalability, zkTLS-powered oracles can provide tamper-proof, verifiable data, such as price feeds or other market metrics, without revealing the source or content of the data, making them suitable for privacy-conscious applications in DeFi. This has the potential to transform lending by supporting undercollateralized loans, allowing users to prove income without disclosing full financial histories, thus unlocking more inclusive lending opportunities while upholding data privacy. By guaranteeing safe and authenticated asset transfers between blockchain networks such as Ethereum, Solana, and Cosmos, zkTLS greatly facilitates cross-chain and multi-chain operations. This is crucial for projects that require seamless integration across multiple chains without central oversight. zkTLS guarantees that data and assets move securely, minimizing risks and eliminating vulnerabilities during transfers, thus promoting greater ecosystem fluidity and interoperability. Moreover, zkTLS can also secure API requests made by decentralized applications (dApps), which often involve interactions with external systems that may expose sensitive information. By enabling only verified data to be shared and keeping sensitive content private, zkTLS helps maintain the integrity and privacy of user interactions and data transmissions across various blockchain applications. zkTLS can also be applied in various Web2-to-Web2 scenarios, where privacy and trustless verification are paramount. For instance, Nike could use zkTLS to offer a 50% discount to participants of the 2024 Chicago Marathon by verifying their participation without directly collaborating with the marathon organizers. Similarly, Uber Eats could use zkTLS to incentivize DoorDash customers with a free soda on every purchase for users who have completed over 100 orders, without requiring access to DoorDash’s data. In both cases, zkTLS enables privacy-preserving, trustless validation of user eligibility based on external data, fostering seamless collaborations and competitive advantages without sharing sensitive information. ## Reinventing web proofs using zkTLS Traditional TLS transcripts don't allow a third party to detect faulty/altered data, but zkTLS schemes solve this by backing data with proof that it originated from a particular server. zkTLS allows the addition of a third party in some form, generally referred to as *the verifier*, who is responsible for checking that the prover reported honest data, as obtained from the server. Based on their verification model, zkTLS schemes can be classified into: 1. Proxy-based architecture (proxy-TLS) 2. TEE-based architecture (TEE-TLS) 3. MPC-based architecture (MPC-TLS) Below, we'll go through a generalization of each scheme and highlight significant innovators in the group. ## TEE-Based zkTLS Trusted Execution Environments (TEEs) are specialized, almost tamper-proof sections of modern CPUs designed to perform sensitive computations in isolation within enclaves. TEEs ensure that confidential operations—such as user authentication, data decryption, or cryptographic signing—remain secure even if the rest of the system is compromised. This isolation allows secure computation without exposing sensitive information to service providers or external parties, making them suitable for computational processes where privacy is strictly required. TEEs have been around for decades in traditional settings and have been proposed for crypto use cases before, but they are just recently starting to gain more attention in the crypto space due to their potential to provide guarantees in various contexts, such as their use by Flasbots. In TEE-based zkTLS setups, the verifier is a TEE, so the trust assumptions of the system directly depend on the TEE's manufacturer or service provider's reputation and the TEE's resistance to physical or side-channel attacks. TEE-based zkTLS implementations are highly efficient, adding minimal computational and networking overhead. This efficiency makes them attractive for performance-critical use cases, provided that users accept the inherent trust and security risks associated with TEEs. The foundation of this system was outlined in the research paper *[Town Crier](https://eprint.iacr.org/2016/168.pdf)*[(2016)](https://eprint.iacr.org/2016/168.pdf), and notable examples of teams building on this concept include **[Clique](https://x.com/Clique2046)** and [Teleport](https://teleport.best/),. Teleport is a consumer-facing implementation that allows users to generate and share unique links enabling others to post as a user on their Twitter account. It is a specialization of the [brokered delegation](https://www.usenix.org/conference/usenixsecurity18/presentation/matetic)concept [co-introduced by Andrew Miller](https://x.com/socrates1024/status/1030511993470509056?t=CEwuBCIopJp0AbMMliBJ0g&s=19). In the best-case scenario, the prover passes raw data values obtained from the server to the TEE, which authenticates the message's contents within an enclave. After authentication, the TEE encrypts the message—creating a web-proof—and directly passes it on to the third-party protocol for which the prover requested the proof. This model allows you to prove the authenticity of responses from a website. For instance, you can provide a TEE-generated signature confirming that a proper TLS handshake was performed and that specific requests and responses were genuinely exchanged. If the recipient trusts that the TEE has not been compromised or tampered with, they can confidently accept the validity of the proof without requiring direct verification of the website itself. As mentioned earlier, TEEs are a relatively underexplored area in crypto, so most of the work in this area is still highly experimental. ## MPC-Based zkTLS **Secure Multi-Party Computation (MPC)** allows a group of parties, each holding a secret—essentially a subunit of an unrevealed value—to jointly compute an output without revealing their individual inputs. This ensures that no data leakage occurs during the computation. In the context of zkTLS, MPC-based models are designed around the idea that during the TLS handshake process, no symmetric key is generated by a single party. Instead, keys are derived collaboratively, enhancing security by distributing trust. Implementing MPC-based zkTLS in practice is resource-intensive, as it requires multiple nodes to participate in the computation, which can be expensive and complex to manage. Due to these bottlenecks, practical iterations of TLS protocols commonly implement a special case where there are two computing parties, with one potentially corruptible party. This setup is referred to as **Two-Party Computation (2PC)**. **2PC** can be designed in two primary ways: 1. **Garbled-Circuit Protocols**: These protocols encode the computation as a boolean circuit using 1-of-2 oblivious transfer. In this setup, the server's response is decrypted within both the prover and the participating 2PC node. More advanced models may employ vector oblivious linear evaluation-based schemes (VOLE-based schemes), which derive the server's write key after the prover commits to the server's final response. This approach decreases processing time and enables selective disclosure of data. It is best suited for bitwise operations. 2. **Threshold Secret Sharing Protocols**: These protocols encode the computation as secret key shares distributed between the prover and the 2PC node. This method is particularly effective for arithmetic operations. In **MPC-TLS** setups, the MPC component constrains the prover's ability to communicate directly with the server. Instead, a third party collaborates with the prover to encrypt, decrypt, and authenticate messages via MPC, without revealing the entire message passed from the server to the prover. This means the third party prevents the prover from falsifying data without ever knowing the raw value of the data. The third party in this setup is often referred to as the **notary**, a term popularized by **TLS-Notary**'s pioneering work in the area. The notary uses blind signatures to sign commitments to the prover's messages, ensuring that the prover cannot alter the message before it is submitted to a protocol that utilizes the data. For example, when demonstrating to a friend that a specific response originated from a website, you can provide both the server's response and an attestation from all participating MPC nodes (or the notary), confirming that they collaboratively decrypted the data from the website. Your friend will trust this proof if they believe it is highly improbable for you to have compromised or bribed each of the MPC nodes involved. The MPC-TLS setup generally follows these steps: 1. **Preprocessing Phase**: The prover and notary perform oblivious transfer to prepare for faster proof generation. 2. **Server Authentication**: The prover obtains the server's public key and certificate chain to verify the server's authenticity. 3. **Key Generation**: The prover and notary generate an ephemeral key shared with the master key, which is a TLS-shared secret. These keys are used for message encryption and server authentication. 4. **Request Encryption**: When the prover wishes to send a request to the server, they employ 2PC alongside the notary to encrypt and authenticate the request. The notary then blind-signs the resultant message before the prover sends it to the server. 5. **Response Decryption**: When the server responds to the prover's request, the prover and the notary use 2PC to decrypt and authenticate the returned message. 6. **Proof Generation**: At the end of the session, the prover possesses a certificate chain of the server's identity and notarized transcripts of the session. They use these to generate proofs to be passed along to a verifier, who can verify the correctness of the certificate chain and signatures, and thus verify the correctness of the underlying message. This design space is the most explored among zkTLS models, with practical implementations like[https://x.com/tlsnotary](https://x.com/tlsnotary)**[TLSNotary (TLSN)](https://x.com/tlsnotary)** and **[Decentralized Oracle (DECO)](https://www.fanzhang.me/publications/deco/)** leading the way. **DECO**, first introduced by [Chainlink](https://x.com/chainlink), is a three-phase protocol that proceeds as follows: 1. **Three-Party Handshake Phase**: The prover, verifier, and server work together to establish secret-shared session keys for encryption and decryption functions. The prover and verifier effectively collaborate to fulfill the role of the "client" in traditional TLS settings. 2. **Query Execution Phase**: The prover sends their request to the server with assistance from the verifier, due to their keys being secret-shared. 3. **Proof Generation Phase**: The prover decides how and to what extent they'd like to exhibit their request to third parties. DECO offers two methods:**Selective Opening**: A portion of the generated data is either revealed or redacted, allowing the prover to disclose only the necessary information.**Zero-Knowledge Two-Stage Parsing**: The prover confidentially parses the session's data and then proves to the verifier, in zero-knowledge, that there are constraints on a specific substring. In summary, MPC-based zkTLS models leverage the principles of secure multi-party computation to enhance the security and privacy of TLS communications. By distributing trust among multiple parties and employing advanced cryptographic techniques, these models aim to provide robust proofs of authenticity without compromising sensitive data. ## Proxy-Based zkTLS The **proxy model of zkTLS** is the simplest iteration, employing a middleman known as the proxy to facilitate communication between the prover (browser) and the server (website). Instead of sending requests directly to the website, the browser sends them via an HTTPS proxy. The website responds to the browser through this proxy by default. As a result, the proxy observes all the encrypted requests and responses exchanged between the browser and the website. The proxy provides an attestation to the encrypted requests and responses, along with information indicating whether each piece of data is a request or a response—essentially attesting to whether the encrypted data was sent by the browser or the website. The browser then creates a zero-knowledge proof (zkProof) of the decryption of the response. This zkProof is equivalent to saying, "I know a shared key that decrypts this encrypted data, and here is the decryption, but I will not tell you the shared key itself." This relies on the impracticality of generating a new key that decrypts the data to anything other than gibberish. Therefore, demonstrating the ability to decrypt the data is sufficient; the actual knowledge of the key is unnecessary. Revealing the key itself would compromise all other messages sent earlier, including sensitive information like usernames and passwords. For example, when proving to a friend that a certain response came from a website, you can say, "Here's the encrypted data, and here's proof from the proxy that it was sent by the website, and here's the zkProof that I have the shared key that decrypts it, and here is that decryption." Your friend will trust this proof if they believe it is unlikely that you have bribed the proxy to falsely attest that certain encrypted data came from the website when it actually came from you. This approach is efficient in both computational and networking resources, as long as you are willing to accept the risk of a very hard-to-execute attack that requires physical access to the proxy's machine. In this scheme, the proxy observes and stores the encrypted data passed in both directions in the communication channel established between the prover and the server. At the end of a TLS session, the prover sends the proxy the session's certificate chain—which the proxy uses to deduce the server's identity—and the symmetric encryption key employed during the session, enabling the proxy to decrypt the communicated data. The proxy then attests to the server's identity using the certificate chain, decrypts the TLS transcript using the prover's symmetric key, and signs the decrypted data with its own key. The proxy-signed transcript can then be passed to a third-party protocol, which is assured of the data's authenticity and provenance due to the proxy's signature. However, this scheme introduces significant trust assumptions. The proxy becomes an enshrined trusted party whose role can impede the privacy of the prover's data and bottleneck network performance due to the extra computational load. A malicious or compromised proxy could collude with the prover to falsify data. Proxy systems, while computationally simpler and faster, come with heightened security risks due to the difficulty of securing the computation. This means that even though proofs can be generated faster, their integrity remains questionable. Notable efforts in this area include the **[Reclaim protocol](https://x.com/reclaimprotocol)**, which is making strides with their verifiers referred to as **attestors**. ## ZK-TLS Ecosystem Applications like **[zkpass](https://x.com/zkPass), [Reclaim Protocol](https://x.com/reclaimprotocol), [opacity network](https://www.opacity.network/), and [zkme](https://x.com/zkme_https://x.com/zkme_)** use ZK-TLS to enhance privacy and security. **zkpass** enables secure, privacy-preserving data verification, while **Reclaim Protocol** leverages zkTLS for data verification. **zkme** empowers users to control and verify their data without exposing it, showcasing zkTLS's ability to prioritize security and privacy in decentralized systems. ### zkPass zkPass is an private oracle protocol that enables private internet data to be verifiable on-chain. Built on top of zkTLS, which is composed of 3P-TLS and Hybrid ZK technologies, zkPass provides tools and applications for secure, verifiable data sharing with privacy and integrity assurances from any HTTPS website without requiring OAuth APIs. zkPass allows users to selectively prove various types of data, such as legal identity, financial records, healthcare information, social interactions, and certifications. These zero-knowledge proof computations are performed locally and securely, ensuring that sensitive personal data is not leaked or uploaded to third parties. They can be used for AI, DePIN, DID, lending, and other financial and non-financial applications. Wherever there is a need for trust and privacy, zkPass can be a solution. zkPass proposes a new paradigm for the traditional data validation and confirmation process, where the verifier is positioned between the prover and the data source. The prover uses the verifier as a proxy, utilizing its access token to retrieve data from the data source. Subsequently, by using the VOLEitH technique, a publicly verifiable proof is generated locally and sent on-chain. This process ensures the verifier remains unaware of the prover's personal information. zkPass introduces 3P-TLS, ZK, and VOLEitH technologies to implement its new paradigm of data validation and confirmation. ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/c540ef205983.jpg) ### Zkme As Web3 continues to evolve, the need for secure and private identification methods becomes increasingly important. One compelling example is the use of decentralized identity (DID) systems. Traditional centralized identity systems store personal data on a single server, making them vulnerable to hacking and unauthorized access. As mentioned previously, zero-knowledge proof technology enables users to verify their identity without disclosing sensitive information. While there are various approaches to this technology, zkMe offers a unique solution that ensures privacy and security for Web3 users. zkMe, an implementation of a credential network protocol that enhances and provides secure and private identification in the Web3 ecosystem. It utilizes zero-knowledge proofs (ZKPs) to enable users to authenticate their identity without revealing any sensitive information. zkMe can be integrated into various web3 applications, such as decentralized exchanges, voting systems, and decentralized social networks, to provide users with secure and private identification. In addition to its security and privacy benefits, zkMe also offers the convenience of a universal login system. Users can use their zkMe DID to log in to multiple applications without having to create a new account for each one. ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/a63be2dd7a82.jpg) To ensure the security and privacy of its users, zkMe employs several mechanisms. One of the most important is zero-knowledge proof technology, which allows users to prove the validity of a statement without revealing any additional information beyond what is necessary, as elaborated previously. In addition to zero-knowledge proof technology, zkMe employs multi-party computation (MPC) to ensure that no single entity holds all of the information needed to identify a user. MPC involves multiple parties working together to compute a result without any one party knowing the inputs of the others. To illustrate this, let’s take an example. Suppose Alice wants to create a decentralized identity (DID) on a blockchain network using zkMe. She provides her personal information, such as her name, date of birth, and government-issued ID number, to zkMe. zkMe then uses MPC to distribute this information across a network of nodes so that no single entity holds all of Alice’s information. Each node only holds a part of her information and collaborate to compute the final result, which is Alice’s DID. This approach guarantees that no single entity can access all of Alice’s information, protecting her privacy and reducing the risk of data breaches. Furthermore, zkMe’s zero-knowledge proof technology enables Alice to prove her identity without revealing any personally identifiable information or sensitive data, which further enhances her security and privacy. Finally, zkMe utilizes a decentralized infrastructure to further enhance security and privacy. Rather than relying on a central authority to manage user data, zkMe’s infrastructure is distributed across a network of nodes, making it more resilient to attacks and reducing the risk of a single point of failure. ### Reclaim Protocol Reclaim Protocol unlocks unlimited possibilities by making HTTPS verifiable with zero knowledge. This is quite difficult to prove if zero knowledge is not involved; for instance, if you want to prove to me that you have more than a million dollars in your bank account, how would you do it? One option is you send me a screenshot. However, I cannot be sure that you didn’t morph the screenshot. The other option is for you to send me your username and password and let me log in and check your balance myself. This option assumes that you trust me to not drain your bank account. How can you send some information to a stranger on the internet where trust assumptions fail? That’s what Reclaim Protocol solves for. Reclaim Protocol generates a zk proof for a TLS session data exchange. When you open an HTTPS website, your browser conducts a ceremony with the server called the TLS Handshake. This handshake involves the passing around of public keys and certificates. These certificates are linked to domain names using a certificate authority. How does the Reclaim protocol work? ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/5f2c8073e14c.jpg) In order to create a proof of a claim, a user must first log in to the desired website that will be sending the data. Once logged in, the user must then navigate to the specific desired webpage. The HTTPS request to open the website and the response are routed through a HTTPS proxy server called an attestor. This attestor can only see the encrypted data, not the plaintext. The attestor monitors the encrypted packets transferred between the user and the website. The user shares a fraction of the keys with the attestor that are used by the attestor to verify the user indeed owns the credential (by decrypting the traffic), and in turn the attestor produces a signature, attesting to this fact. This signature of the Attestor is the proof, which can then be shared to any third-party To verify that certain data being shared across a web page is accurate and to ensure privacy, the Reclaim protocol introduces an HTTP proxy to witness the handshake and data transfer. Any webpage you open goes through a randomly selected HTTP Proxy Witness. HTTP Proxies are a common infrastructure on the internet. The HTTP Proxy Witness checks that (1) the handshake was done with the correct domain name, (2) the correct webpage was opened in the request, and (3) an encrypted response was received. The HTTP Proxy Witness can see only the encrypted response, and it cannot view the contents of the response. This encrypted response is then fed to a zk circuit that runs completely on the client side. The AES/ChaCha20 decryption happens inside the zk circuit, and a search is performed on the decrypted HTML page. ### Opacity Network Opacity Network is a cutting-edge data verification platform that utilizes blockchain technology to secure and verify data transactions while maintaining user privacy. By employing zero-knowledge proofs, Opacity Network enables users to share and verify information without revealing sensitive details. At the core of Opacity Network's functionality are zero-knowledge proofs, which allow users to prove the validity of their data without disclosing the data itself. This method is particularly important in a digital landscape where data privacy concerns are paramount. By ensuring that sensitive information remains confidential, Opacity Network offers a reliable solution for verifying data authenticity across various platforms. Opacity Network integrated the mainnet AVS on the EigenLayer platform, enhancing its data verification capabilities. This integration utilizes a secure Multi-Party Computation (MPC) network, allowing users to generate data proofs on existing Web2 platforms. This advancement not only improves usability but also strengthens user data sovereignty by allowing control over personal data while interacting with various applications. ### Clique Clique is pioneering a new paradigm for building dApps and consumer applications with its’s TEE coprocessor, which acts as an off-chain AWS Lambda system. It offers confidentiality and verifiability for on-chain applications while being highly versatile, cost-effective, and secure. The coprocessor architecture is built on a network of TEE nodes supporting custom bytecode execution for VMs (currently EVM and WASM, with more to come). It also provides SDKs enabling clients to build custom executors in TEEs, make smart contract calls to the coprocessor network, and verify attestations and trusted signatures on-chain. Orchestration nodes within enclaves create compute graphs, distribute tasks, and aggregate proofs. We currently focus on Intel SGX, with plans to support AMD SEV-SNP, Intel TDX, and NVIDIA H100 soon, enhancing trust assumptions and efficiency. This technology ecosystem enables secure, efficient, and verifiable off-chain computation using TEEs for data integrity and confidentiality, with HSMs protecting validator keys. It supports TLS calls for external data, verifiable AI outputs, and user data attestation for incentives. The system facilitates arbitrary computation, HTTPS endpoints with data privacy, and use cases like MEV strategies, automation bots, and decentralized applications (e.g., loyalty programs, gaming, DeFi). It also ensures coordination between untrusted parties and secures blockchain components such as wallets, bridges, and oracles. ### Primus Primus is building a privacy-preserving data infrastructure by combining zkTLS and zkFHE to bridge Web2 and Web3 while enabling verifiable AI. The goal is to make offchain data useful onchain without exposing sensitive information or relying on centralized gatekeepers. Primus’s core innovation lies in its hybrid cryptographic stack, leveraging: - zkTLS: Extends TLS by embedding zero-knowledge proofs (ZKPs), ensuring data integrity and authenticity while maintaining end-to-end encryption.Allows selective disclosure of offchain data.Uses QuickSilver, a high-performance ZKP system that makes zkTLS 10x faster than alternatives like DECO.Ideal for onchain credit scoring, identity verification, and AI-powered analytics. - zkFHE (Zero-Knowledge Fully Homomorphic Encryption): Enables computations on encrypted data without decryption.340x faster proving time compared to existing zkFHE models.Supports privacy-preserving AI, federated learning, and decentralized financial modeling.Allows trustless AI agents to process encrypted datasets in Web3 ecosystems. How It Works 1. Data Verification: zkTLS allows users to prove real-world facts (e.g., financial history, social credentials) onchain without exposing private details. 2. Secure AI Processing: zkFHE lets AI models compute over encrypted data, unlocking confidential analytics and autonomous AI agents for decentralized ecosystems. 3. Web2-Web3 Interoperability: Primus bridges offchain data with onchain protocols, enabling privacy-preserving integrations for finance, identity, and AI-driven applications. The two primary models commonly used for zkTLS are the MPC model and the Proxy model. Each model presents its own trade-offs in terms of security and performance. Primus addresses these differences by providing unified APIs, allowing developers to choose the most suitable model based on the specific requirements of their applications. ### zkTLS Ecosystem Map zkTLS is shaping the next generation of verifiable, privacy-preserving TLS attestations, allowing users to prove statements about their data without exposing underlying details. Early research in TLS oracles tackled the challenge of securely verifying TLS data without modifying Web2 servers. TLSNotary (TLSN) and Decentralized Oracle (DECO) pioneered cryptographic proofs for TLS 1.2 sessions, while later approaches, like DIDO and DiStefano, extended these methods to TLS 1.3. Their models rely on secure multi-party computation (2PC) to ensure data authenticity while preventing tampering. Crunch took a different approach by shifting computational overhead from MPC to zk-Risc0 proofs, reducing costs and making TLS oracles more scalable. These protocols establish the foundation for seamless Web2-to-Web3 interoperability, enabling applications where off-chain data can be securely used onchain. ![](https://shoal.xyz/research/writing/zktls-verifiable-data-composability/img/9bba2d1acec9.png) Beyond direct TLS verification, zkTLS projects are integrating with attestation registries and cryptographic middleware to enhance data portability. Verax, EAS, BAS, and Sign Protocol allow TLS attestations to be stored, bridged, and used across multiple blockchains. Primus is advancing zkTLS by combining it with zkFHE, enabling privacy-preserving AI models that can compute over encrypted data. Other projects like zkMe are applying zkTLS to decentralized identity (DID) and authentication, while zkon.xyz explores Web3-native integrations. These efforts push the boundaries of trusted Web2-Web3 interactions, creating more efficient, scalable, and privacy-focused solutions for integrating off-chain data into decentralized applications. ## General applications of zkTLS So far we've focused on *how* to efficiently export data and produce web proofs; now it's time for the *why*. Why would anyone want this? Why risk the wrath of litigious behemoths for marginal improvements to UX? Is there no better way to do this? Simply, if data is the next oil, as they say, then you should probably be in charge of yours, and probably so too. Allowing the aggregation of user data by the user isn't unprecedented; crawlers have served this purpose for traditional banking, aggregators serve this purpose for crypto markets, and account abstraction models will eventually serve this purpose for crypto users and identities. Web proofs generated via zkTLS schemes allow users to aggregate their data and be in charge of it, and to use it as they see fit eventually. There will probably be better ways to do this eventually, but we mustn't let perfect be an enemy to better. zkTLS enables more *permissionlessly*, so it is the better alternative to user empowerment for the near- to mid-term future. There are already performant instances of applications enabled by zkTLS, such as Teleport, [zkP2P](https://zkp2p.xyz/), [zkPass](https://zkpass.org/#use-cases), [zkTix](https://x.com/zkTix?t=EgdthwBv6Bno0zIibOlzFg&s=09), and numerous zkKYC platforms. DeFi applications will also undoubtedly see more use for the technology as time goes on, especially as undercollateralized lending catches on. ## Wrapping Up The advent of zkTLS has the potential to revolutionize digital communications by addressing significant flaws in current data-sharing and verification systems. Traditional TLS ensures secure data transmission but falls short in providing independent verification or facilitating data portability. zkTLS, by incorporating zero-knowledge proofs, overcomes these limitations, allowing users to prove data authenticity without disclosing sensitive details. This unique capability empowers users to export and share their data seamlessly, promoting greater autonomy and privacy. The system's flexibility, demonstrated through its proxy, TEE, and MPC implementations, opens new possibilities for cross-environment data utilization—from verifying marathon participation for discounts to incentivizing customer loyalty across competing platforms. By enabling trustless verification and privacy-centric data sharing, zkTLS supports a future where the internet is both more open and aligned with the rights and needs of individuals, paving the way for a more interconnected and user-empowered digital world. --- ## Resources 1. Hindi, R. [@randhindi]. (2024, March 29). *[Tweet]*. X.[https://x.com/randhindi/status/1836329769597600232](https://x.com/randhindi/status/1836329769597600232) 2. Elitzer, D. [@delitzer]. (2024, March 21). *[Tweet]*. X.[https://x.com/delitzer/status/1828833053000839578](https://x.com/delitzer/status/1828833053000839578) 3. Artichmaro [@artichmaro]. (2024, March 29). *[Tweet]*. X.[https://x.com/artichmaro/status/1836311271769079979](https://x.com/artichmaro/status/1836311271769079979) 4. Weidai [@_weidai]. (2024, March 21). *[Tweet]*. X.[https://x.com/_weidai/status/1829194060554522915](https://x.com/_weidai/status/1829194060554522915) 5. Matetic, S., Schneider, M., Miller, A., Juels, A., & Capkun, S. (2018). DelegaTEE: Brokered delegation using trusted execution environments. In *Proceedings of the 27th USENIX Security Symposium* (pp. 1387–1403). USENIX Association.[https://www.usenix.org/conference/usenixsecurity18/presentation/matetic](https://www.usenix.org/conference/usenixsecurity18/presentation/matetic) 6. zkMe. (n.d.). *Solution overview*. Retrieved December 3, 2024, from[https://docs.zk.me/zkme-dochub/getting-started/solution-overview](https://docs.zk.me/zkme-dochub/getting-started/solution-overview) 7. zkPass. (n.d.). *zkPass documentation*. Retrieved December 3, 2024, from[https://zkpass.gitbook.io/zkpass](https://zkpass.gitbook.io/zkpass) 8. Chainlink Labs. (n.d.). *Chainlink documentation*. Retrieved December 3, 2024, from https://docs.chain.link/ 9. Reclaim Protocol. (n.d.). *Reclaim Protocol SDKs*. Retrieved December 3, 2024, from https://docs.reclaimprotocol.org/ --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures**. All posts are the author's own, not the views of their employer. This post has been sponsored by zkPass team. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Enso Network: The "Shortcut" To Your On-Chain Operations > Explore how Enso leverages an intent-driven engine with “shortcuts” to provide efficient execution paths that make intents actionable and scalable, enabling seamless on-chain interactions across web3. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-03-06 - Canonical: https://shoal.xyz/research/writing/enso-network-shortcuts/ - Keywords: crypto, DeFi, solvers, security, infrastructure, Solana, Ethereum, Bitcoin, Infrastructure ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/798fbf3f2592.png) Blockchain architecture has evolved from Bitcoin's original distributed ledger implementation focused on P2P transactions to a complex ecosystem of diverse protocols. The initial single-chain design has expanded into multiple specialized chains running parallel computation environments, supporting programmable state transitions through smart contracts, and enabling cross-chain communication protocols. This has led to a fragmented landscape of mixed virtual machines, execution environments, and consensus mechanisms. This fragmentation creates significant integration challenges for developers and users. According to [L2beat](https://l2beat.com/scaling/summary), there are currently over 100 Layer 2 solutions with more than $54 billion in total value locked (TVL). And these are just L2s—such as rollups, validiums, optimiums, sidechains, etc. We're not even counting the countless other Layer 1 blockchains. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/c3dd35c8da8a.jpg) As the blockchain space matures, this fragmentation is expected to increase, adding to the complexity of integrating, interacting with, and building upon other blockchain networks. One of the most significant sources of this fragmentation is the sheer number of blockchains today. While Bitcoin was once the dominant force in the ecosystem, it now shares the spotlight with hundreds of other blockchain networks, each designed for different purposes and tailored to meet specific needs. Blockchains like Ethereum, Solana, Binance Smart Chain, Cardano, Polkadot, and Avalanche, among others, have all emerged as popular alternatives to Bitcoin, each with its features, use cases, and target audiences. Ethereum, for instance, transformed how we interact on-chain by introducing programmability through smart contracts—self-executing contracts with the terms of the agreement directly written into code, enabling decentralized applications and turning blockchain into a platform for innovation far beyond simple monetary transactions. The variety of consensus mechanisms alone—ranging from Bitcoin’s PoW to Ethereum’s transition to PoS—adds a layer of complexity, requiring developers to deeply understand the nuances of each blockchain’s structure before engaging with them. Each blockchain’s design and consensus mechanism comes with its advantages and trade-offs, impacting scalability, security, decentralization, and transaction speed. Bitcoin, for example, prioritizes security and decentralization over transaction throughput, making it slower but highly secure, while networks like Solana or Avalanche focus on increasing scalability and transaction speed to handle a higher volume of transactions, albeit at the potential cost of decentralization. As the number of blockchain platforms continues to increase, so too does the difficulty in determining which platform to choose for specific applications. Another issue developers face is the sheer number of programming languages used across the blockchain space. - While Ethereum has popularized the use of Solidity for smart contracts, other blockchains have introduced their programming languages, such as Rust for Solana, Vyper for Ethereum, and Ink! for Polkadot. - Each of these languages comes with its syntax, libraries, and development tools, which adds to the steep learning curve for developers. A developer who is proficient in Solidity may struggle to write code for Solana’s Rust-based platform, or a Polkadot developer may face difficulties in adapting to the specificities of Ethereum’s smart contract framework. - While this diversity in languages and frameworks has led to more tailored solutions for different blockchains, it also creates significant friction for developers who may need to work across multiple platforms or integrate different blockchain technologies into a single application. The lack of standardized tools and frameworks further compounds this issue, as developers often need to rely on custom-built solutions or adopt new tools for every new blockchain they work with. The resulting fragmentation not only creates obstacles for individual developers but also slows down the overall pace of innovation within the blockchain space. Furthermore, while many of these blockchains function independently of one another, they are rarely interoperable by design. This lack of interoperability poses one of the most significant barriers to achieving a truly connected blockchain ecosystem. As blockchain networks grow in number and importance, the ability to transfer assets, data, or tokens between blockchains is critical for enabling the next generation of decentralized applications. Unfortunately, most blockchains operate in isolation, with limited capacity for seamless communication between them. The creation of cross-chain bridges, such as those offered by Polkadot or Cosmos, is an attempt to address this issue, but these solutions are still nascent and often complex, requiring additional infrastructure and creating potential security risks. Until cross-chain interoperability becomes more seamless and widespread, developers will continue to face the challenge of building applications that can operate across different blockchain networks. These challenges of fragmentation and interoperability further create friction in building innovative applications and new primitives, reducing the ability to scale for mass adoption. We're seeing brilliant teams and builders working on technologies to address the pressing challenges of liquidity fragmentation and multi-chain interoperability. Among these innovations, intent-based engines and projects, like Enso, have emerged as promising solutions. Enso takes this a step further with **"**Shortcuts**"**—a framework that abstracts complex onchain interactions into simple, executable workflows. In this article, we will explore the concept of intents, and how Enso addresses these challenges with its intent-driven engine and shortcut-based approach. ## History of Enso Network: 2021 to Present Enso Network has undergone [evolution since its inception](https://www.youtube.com/watch?v=oQGVEFCnv5Y&t=935s). The project began in 2021 with a strategy that involved a "vampire attack," where Enso targeted six different DeFi protocols. This approach gamified the experience and incentivized participation with NFTs. While this initial strategy helped Enso gain early traction, the team quickly identified a key problem: the complexity and cost of integrating DeFi protocols. Enso spent over half a million dollars on audits for just 15 protocols, which led them to reconsider their approach. In 2022, Enso pivoted to focus on making DeFi integration easier for developers. The team launched a social trading feature, which allowed users to monetize their investment strategies using ERC-20 tokens and DeFi assets. However, they continued to struggle with how to streamline the process of connecting to multiple DeFi protocols without incurring the same high costs. The breakthrough came when Enso realized that many projects faced the same challenge of how to onboard users into DeFi effectively. In response, Enso launched an API that gained immediate success, generating $11 million in cumulative volume within its first week. This API allowed Enso to position itself as a DeFi middle layer, providing application developers with a simple way to integrate actions like lending, borrowing, swapping, liquidity providing, and vault interactions into their products. Developers no longer needed to manually integrate each DeFi protocol themselves. Over the next three years, Enso experienced substantial growth, with transaction volume rising from $8 million in its first year to over $15 billion by year three. By this time, Enso had over 35 projects using its platform. At the core of this success was Enso’s user-centric approach, which prioritized simplicity and ease of use. The platform abstracted away the complexities of DeFi, allowing users to interact with multiple protocols through a streamlined UI. Today, [over 75 apps are using Enso across 180+ protocols,](https://www.enso.build/) and 15+ unique primitives have been built using Enso, with over 450k direct intents settled. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/0f5ffa86c31a.jpg) Central to Enso’s evolution was the introduction of the concept of "shortcuts of blockchain," designed to efficiently fulfill the “intents." Without proven execution paths, an intent is merely a request, leaving the burden on solvers to figure out how to fulfill it. Shortcuts provide these predefined execution paths, ensuring that intents are efficiently translated into actions.This allows users to specify what they wanted—such as a token, a DeFi position, an NFT, or another smart contract interaction—without needing to understand the underlying technical process. This innovation led to the development of the Enso Network, a decentralized shared network that could map and execute complex smart contract interactions across different blockchain frameworks. Enso’s vision is to create a system where all developer interactions are outcome-based. As the network expands, the platform continues to improve the speed and efficiency of DeFi integration, reducing the time and cost involved in building decentralized applications. Enso’s business model revolves around taking a spread from solutions built through its network, with plans to transition to a fee structure based on volume as the platform grows. This approach has already yielded impressive results, and the team believes that as the ecosystem matures, Enso will continue to play a central role in simplifying DeFi for developers and users alike. ## Protocol Design ## So, What is the Enso Network? ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/6cfc36c33051.png) The central issue in the blockchain ecosystem is usability, created by the fragmentation of these blockchains and execution environments. The feature of allowing blockchains and smart contracts to communicate with each other simply and seamlessly without hassle is a key value proposition to the blockchain ecosystem, which will help the blockchain ecosystem grow. ***Enso is targeted at solving the problem of usability.*** Enso Network is the world’s first intent-driven engine, powering blockchain abstraction and paving the way for an intent-centric future. Built on a layer-1 Tendermint-based blockchain, Enso stores state from EVM, SVM, and MVM blockchains, enabling seamless execution across various blockchain frameworks. Applications can leverage Enso by simply expressing their desired smart contract outcomes, eliminating the need to build complex integrations themselves. Enso leverages "intents" as its core technology to bridge the gaps in the fragmented blockchain ecosystem. In this context, intent is a high-level representation of a user’s desired outcome, such as executing a smart contract or interacting with a blockchain in a specific way. Instead of requiring users or applications to manage the complexities of blockchain integrations directly, Enso interprets these intents and automatically translates them into actionable transactions across various blockchain frameworks. This innovative approach simplifies interaction with multiple blockchains and enhances usability, enabling developers to focus on outcomes rather than technical integration details. ### What are “Intents” and how do “Shortcuts” fulfill them efficiently?? In simple terms, **intents are just shortcuts for users**. What most users in DeFi care about is: *"I have A, and I want B, C, and D. I don't care about all the details of how to achieve this outcome for me."* Users want to interact with DeFi without having to understand or manage every single complexity involved. It’s important to note that **B, C, and D are not limited to just token swaps**. They can represent any on-chain intention, such as: - State changes - NFTs - Tokens - Defi positions - Any interaction on-chain Intents are planned on-chain actions aimed at achieving desired goals. Intents are signed messages that allow solvers to execute a trade on behalf of the user using specified assets and amounts. It allows users to achieve their desired outcome on-chain by outsourcing the task to the best solver in the market. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/2e35c4bbb829.jpg) *Source : [Devcon Youtube](https://www.youtube.com/watch?v=0FpMhUJTwA4)* For instance, an intent-based protocol like the CowSwap protocol allows users to submit an intent to sell a token at a particular price. When this intent is submitted off-chain, it then bypasses the public mempool and instead is directly routed to an encrypted private mempool where solvers compete to fill or solve your intent at the best possible price, either by using their balance sheets, private order flow, or using on-chain liquidity venues like Uniswap and Curve. In an intent-based protocol, a user simply needs to specify what is to be done, and it will be completed in the most efficient way possible. For example, a user may want to borrow $DAI against his/her $ETH and deposit the $DAI into a liquidity pool to earn $RTY as a form of reward. An authorized solver then compares all $DAI borrow rates against $ETH and takes out a loan at the lowest interest rate. The solver then deposits the $DAI in a Yearn-like vault to autocompound the yield from the highest yielding 100% $DAI-denominated LP into $RTY, which streams to the user’s wallet. Intent-based protocols such as CowSwap and deBridge have some technical benefits, which led to its rise. Some of these benefits include enabling solvers to execute all sorts of transactions based on specific instructions and on-chain conditions, eliminating fees for failed transactions, allowing users to place multiple orders at once, and much more. Intents have many benefits to the crypto space, such as MEV protection and enabling private market maker inventory, as many solvers have access to off-chain liquidity through CEX, private makers, or personal liquidity, which allows them to fill certain trades at better prices than what may be available through on-chain AMMs. Intents have never had a strong implementation in the ecosystem as a result of some design choices, as the current design of the open and permissionless nature of the Ethereum mempool does not support the proper integration of intents. This has led intent designers to speculate if intents will be propagated to a permissioned set of available in a permissionless manner, allowing any party to execute an intent. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/a82b2c230bb4.jpg) > *Source: Intent design. Paradigm* **Shortcuts: The key to efficient Intent execution** While intents define the “what,” shortcuts provide the “how.” Without proven execution paths, an intent is just a request, leaving solvers to figure out the best way to fulfill it. Enso’s shortcuts create structured execution paths that make intents actionable and efficient. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/c3ddba1c17bc.jpg) How Shortcuts Work: - Predefined Execution Paths: Instead of relying on solvers to determine how an intent should be executed, shortcuts standardize the best workflows to ensure efficiency. - Automation & Abstraction: Developers and users don’t have to manually integrate protocols—shortcuts handle everything behind the scenes. - Composable & Modular: Shortcuts can be combined to create complex on-chain workflows, such as depositing into a vault and leveraging it in one action. ## Enso: Shared Network State Enso introduces the first shared network state for building transactable bytecode for execution, which allows developers to interface with blockchain conveniently, as they should not be concerned with all the complexities of each smart contract and should be able to state their desired outcome as an intent with all complexities of execution abstracted away. Smart contract abstractions are contributed to the shared network as well by**action providers,** who submit their contributions to be validated. Once accepted, these contributions are stored as entities within a map, gradually clarifying the relationships between smart contracts and their ability to interact with one another. This results in a comprehensive map of executable relationships. To generate transactable bytecode for smart contract execution, the network not only stores essential data, such as function signatures, token inputs, and outcomes but also includes pre-requisite fetchers that must be validated before bytecode can be constructed. For instance, in the case of an NFT minting process with a cap of 1,000 available NFTs, the pre-requisite fetcher would check the number of NFTs already minted and the total allowable amount. Once these requirements are validated, the network returns a valid bytecode that is ready for execution. Unlike the plug-and-play simplicity of Web2, Web3 lacks tools for seamless interaction across protocols. Enso bridges this gap by creating a **"Zapier for Web3"**—enabling drag-and-drop functionality for blockchain integrations. **Streamlined API:** Enso enables multi-chain and multi-protocol integrations with ease. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/4034fc2be701.jpg) **Scalable and Composable Solutions:** Developers can launch scalable and composable applications in just **four simple steps**: 1. **Use an Action:** Actions abstract isolated smart contract transactions into simple, reusable components. 2. **Make a Shortcut:** Combine multiple Actions into reusable and shareable Shortcuts to automate workflows. 3. **Fetch Live Data:** Seamlessly integrate Actions and Shortcuts into your apps, agents, or tools to pull live data. 4. **Ship It:** Deploy your application with streamlined and simplified blockchain integrations. Enso's approach empowers developers to create efficient, user-friendly Web3 solutions that rival the ease and flexibility of traditional Web2 integrations. In the later sections, we'll explore in detail the Enso network participants and the various components of Enso that make deployment easier. ### Enso Network Participants The Enso network participants include ***graphers, action providers, consumers, and validators.*** ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/083e94f03474.jpg) Graphers Graphers design and implement algorithms to solve consumer requests by combining smart contract abstractions into executable bytecode. They continuously search for the most optimal solutions, ensuring that only the best algorithm is chosen for execution. In their role, graphers work closely with validators and action providers to guarantee that the solutions they generate are accurate and valid. They also maintain a comprehensive map of smart contract interactions across different blockchains, ensuring that the solutions they create are efficient and able to integrate with a wide variety of blockchain networks. Graphers use the abstractions provided by action providers to create pathways that fulfill consumer intent. Operating in a competitive environment, graphers are incentivized to optimize their algorithms to deliver the best possible solutions. Their efforts are rewarded through a share of the consumption fees, which motivates them to continuously enhance their performance and ensure that they provide the most efficient, effective solutions to consumer requests. Action Providers Developers who publish smart contract abstractions on the Enso Network are known as action providers. These abstractions are integral to the network, as they are used by graphers to build algorithms that solve consumer requests. By providing these pre-defined smart contracts, action providers make it easier for developers and users to interact with the blockchain. Action providers are incentivized to focus on creating high-quality abstractions that are not only secure and efficient but also easy for others to use. This ensures that the abstractions they publish are reliable and contribute to the overall functionality and scalability of the Enso Network. In return for their contributions, action providers are rewarded based on the usage of their abstractions within solutions generated by Graphers. Every time a smart contract abstraction they’ve published is used in the creation of a solution, action providers receive a share of the fees. Validators Validators play a pivotal role in securing the Enso network by ensuring the integrity of the system and verifying the solutions provided by Graphers. Their primary responsibilities include accepting valid consumer requests, authenticating the abstractions contributed by action providers, and determining which solutions from the graphers are the most optimal for execution. Validators are incentivized to perform their duties with accuracy and efficiency through a reward system that compensates them for their essential role in securing the network. Validators earn a share of the network fees based on their participation in validating and authenticating solutions. Consumer Consumers play an essential role in the Enso network by submitting requests that specify their desired outcomes. Consumers also have the option to pay fees for their requests, which helps facilitate the execution of the transaction and supports the various participants in the network, such as graphers, validators, and action providers. In addition to stating their intent, consumers can optionally pay fees to incentivize the execution of their request. ## Components of Enso Network The key components of the Enso network that enable the bridging of the blockchain ecosystem include: ## Requesting The foundation of the Enso network is the concept that customers should ask for an outcome rather than specifying how to get it. This usability paradigm shift is referred to as an intent. In contrast to a transaction, where instructions are provided on "how" to conduct an engagement, intents allow customers to indicate "what" they would like to acquire. A thorough comprehension of certain smart contract peculiarities and cautions is necessary before creating a transaction. On the other hand, intents eliminate these complications and enable customers to contract out the development of the solution for the intended result. Intents outline a set of variables that must be achieved and the constraints around these variables, resulting in a tremendous developer experience. ``` RequestResponse { IntentId string From string To string Data string Value string AmountOut string Gas string } ``` ## Abstraction An incentive-based contribution mechanism has been created to guarantee that the Enso network contains the most comprehensive map of smart contract interactions. When creating a solution for a customer's request, developers (action providers) can add abstractions to the network and get paid if their abstraction is used. Establishing a market where developers can submit abstractions they believe the ecosystem will use; the more verbose the abstraction, the less likely it is to have been submitted beforehand. The network permits many abstractions with the same goal to be provided to prevent abstraction squatting. The abstraction with the most staked Enso token will be selected during the solution creation process. Graphers use network abstractions to construct solutions. Every abstraction needs to have a corresponding action type to guarantee the scalability of consumption. An action type may have several abstractions, but an abstraction can only be linked to one action type. A wrapper that specifies a specific behavior that the related abstractions are performing is called an action type. For instance, a DeFi smart contract that demands the transfer of one or more tokens while receiving one or more tokens in return is classified as a deposit. An abstraction is initially defined as a message action type before being contributed: ``` Unset MsgAddDeposit { Protocol string TokensIn []string PositionOut string Primary string SupportsReceiver bool } ``` Once the message has been added, then it is parsed into the following action type: ``` Unset Action { ActionId string ActionType string Protocol string PositionsIn []string PositionsOut []string SupportsReceiver bool Provider string Args map[]string } ``` > As there are many dynamic outcomes when interacting with smart contracts, the *positions*variable encompasses many different outcome types, i.e., if the execution returns token(s), NFT(s), state transition(s), and such. Particular smart contracts enable outcomes to be delegated to another receiver address, so SupportsReceiver has been implemented. By following this methodology, we open up the types of *consumers,*such as artificial intelligence execution bots built on top of Enso with particular execution boundaries to be requested and then settled with the provided permissions. New *PositionTypes*can be added to the network through the governance module. A position is generated as a deterministic hash from the following: ``` Unset Position { PositionType string Chain uint64 Address string TokenId string } ``` To validate solutions generated by the network, each associated abstraction has a *ViewType*attached, where on-chain getters can be embedded to cross-reference the desired outcome against the actuality: ``` Unset ViewFunction { PositionType string Fragment string Target string Args []string ResponseIndex uint64 } ``` When a new abstraction is introduced with an associated action type, the following steps are taken to ensure its validity on the network: 1. **Action Submission**: The action provider submits the action. 2. **Action Validation**: Validators check if the action provider is registered in the on-chain provider's list. 3. **Action Parsing**: The action message data is parsed into the Action type format, and other values are converted into the Position type format. 4. **Action Definition Retrieval**: The system interfaces with the Action Provider indexing infrastructure to retrieve the action definition. 5. **Transaction Bytecode Generation**: Generate transaction bytecode based on the action definition. 6. **Transaction Simulation**: Simulate the transaction bytecode and verify that the outcome behaves as expected at the specific positions. 7. **Position Validation**: Ensure positions are stored on-chain and update any missing position data. 8. **On-Chain Action Storage**: Store the action on-chain. 9. **ActionId Emission**: Emit the ActionId. Once these steps are completed, the abstraction becomes part of the Enso network map and is available for generating solutions. ## Solution Aggregation Following a request to the Enso network, members of the network will collaborate and bid on potential solutions to give the customer the best outcome. To prevent the Enso network from becoming stagnant over time, competition between graphers offering solutions ensures that the network consistently delivers the best feasible answer. As a result, customers consistently use Enso as their primary source of executable data instead of switching to another provider. If you’re a solver, you can create a map of all smart contract interactions—tracking how **Token A** goes into one contract and **Token B** comes out. Over time, this builds a web of relationships between smart contracts, allowing you to identify optimal paths for execution. For example, Connor Howe, the CEO and co-founder of Enso, shared a **visual representation** of an order fulfilled by Enso during [his keynote at](https://www.youtube.com/watch?v=oQGVEFCnv5Y&t=935s)**[DappCon 2024](https://www.youtube.com/watch?v=oQGVEFCnv5Y&t=935s)**. In this instance, Enso executed **112 different transactions** to find the most optimal route for the user. This highlights the sophistication and efficiency of Enso’s approach to fulfilling user intents. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/7d0ae766fda9.jpg) Source: [Token Flow of an order fulfilled by Enso](https://eigenphi.io/mev/eigentx/0xabf4df56c5063e97a24a96a689c40f144bc8c87604703d7f60b3609f8da74978?allow-different=0&disable-reverse-debt=0&hide-inter=0&include-gas-fee=0&rankdir=&show-net-asset-flow=0) When requests are sent to the network, validators listen to make sure the right format is used. If the request is sent successfully, it will be propagated into the network's mempool. To determine the best course of action for every action in the network, the graphers use their unique algorithms. The underlying algorithms may be as basic as the K shortest path or quite complicated. As long as the produced solution can be converted into bytecode, the graphers idea is acceptable. Once a solution is generated, the bytecode is linked to the corresponding **intentID**. The validators then simulate the solution by: 1. Forking the intended settlement chain with all recent states. 2. Running the bytecode to ensure it can be executed. 3. Verifying the correct state transition by invoking **ViewFunction** helpers in each action. Additionally, validators may execute custom modules for tasks such as delegate calls, overrides, balance checks, and other requirements. Each validator propagates its findings back into the mempool, associating them with the relevant **intentID** and **solutionID** after individually detecting state transitions. The winning solution is then determined by combining: 1. The **highest dollar output** for the user. 2. The **lowest execution cost** for processing. Once the winning solution is selected, all other solution suggestions are cleared from the mempool. Since these alternate solutions are no longer relevant, this process prevents unnecessary bloat in the network, functioning as an inherent **caching layer**. The winning solution is then provided to the customer for implementation. The bytecode used to execute solutions may contain fees, and the Enso network functions on a variety of blockchains. Instead of bridging all fees back to the Enso blockchain, the network holds an **auction system**. In this system, an address can purchase a specific amount of **Enso tokens** to gain the right to collect these fees on individual blockchains. By adopting this approach: - Network participants receive **Enso tokens** as payment for their contributions, including validation, generating winning solutions, and abstraction consumption. - This creates an **integrated circular economy** that incentivizes participation and can be adapted to accommodate the continued growth of blockchain ecosystems. ## Applications of Enso The architecture of Enso is designed to empower any application that seeks to interact with smart contracts across all blockchains, offering the most optimal execution possible. Enso is blockchain-agnostic, meaning it can seamlessly interface with various types of smart contracts, making it an incredibly versatile platform. This opens up infinite possibilities for applications, allowing developers to build truly composable solutions. Enso serves as the universal gateway for interacting with smart contracts across multiple blockchains, enabling the creation of diverse applications that operate effortlessly across the decentralized ecosystem. Enso offers unparalleled flexibility, allowing developers to create, innovate, and scale applications wherever and however they desire. The Enso network facilitates the creation of both transactable and consumable data that can be leveraged for execution or to fetch essential information from smart contracts across various blockchain frameworks. By consuming only the data on the Enso network, developers can create powerful tools such as DeFi metadata APIs, NFT metadata APIs, AI-driven language models for data analysis, smart contract interaction analytics, on-chain information contextualization, and much more. These applications enable a deeper understanding and use of blockchain data, improving transparency and accessibility. Enso also supports the creation of transactable data products that automate complex interactions with smart contracts. For example, AI-driven bots can execute actions on behalf of consumers, smart contract interactions can be automated for efficiency, and DePIN (Decentralized Physical Infrastructure Networks) can be consolidated. Moreover, Enso enables the development of aggregators for swaps, lending, NFTs, and cross-chain bridges, streamlining the user experience in decentralized ecosystems. Given that all smart contracts and their interrelationships are readily available through the Enso network, the potential applications are virtually limitless and future-proof. ## Tokenomics The **Enso token** is the native digital asset that powers the Enso network, a robust and decentralized ecosystem built on a Tendermint-based blockchain architecture. This token is a fundamental element of the network, acting as both a utility and governance token essential for the operation, security, and continued evolution of the Enso ecosystem. Without the Enso token, the network would be unable to function, making it a critical piece of the infrastructure. One of the primary uses of the Enso token is for **gas fees**, which are required to initiate requests and modify the state of the Enso network. As with many other blockchain networks, transactions and actions within the Enso ecosystem require a certain amount of computational power to process. The Enso token acts as the fuel for these actions, enabling users and applications to interact with the network and execute smart contracts, data transactions, and other processes. This ensures that the network remains operational and incentivizes users to participate by compensating validators and other actors for their contributions to maintaining the system’s integrity. The Enso token also plays an integral role in the **governance** of the network. The Enso ecosystem is governed by a decentralized protocol where token holders have the power to vote on upgrades and protocol changes. This voting mechanism allows the community to directly influence the evolution of the network, ensuring that it remains flexible and responsive to the needs of its users. In addition to its role in governance, the Enso token is used to secure and maintain the **integrity of the network**. Participation within the Enso ecosystem, particularly by **validators, graphers**, and **action providers**, requires participants to stake a certain amount of Enso tokens. This staking mechanism is a critical component in preventing malicious behavior and ensuring that all actors within the network are incentivized to follow the rules. In the event of malpractice or malicious activity, staked Enso tokens can be slashed, meaning that a portion of the staked tokens are forfeited as a penalty. Another important function of the Enso token is its role in **delegated staking**. Token holders who do not wish to actively participate in staking themselves can delegate their Enso tokens to other network participants who are acting as validators or other relevant roles. The **total supply** of the Enso token is capped at **100,000,000 tokens,** creating a fixed supply. The fixed supply helps to avoid inflationary pressures and ensures that the value of the token is backed by its utility and demand within the ecosystem. ## Business Model The Enso Network's business model could be a hybrid that combines multiple revenue streams to cater to a variety of users. This could include a fixed fee per transaction or, based on usage volume, charging networks based on how much traffic or transactions they process through Enso’s infrastructure. Additionally, a subscription-based model might be introduced, offering tiered access for developers and networks with different feature sets, depending on their scale. Transaction fees could also be levied on end users executing actions or swaps through intent networks consuming Enso’s services. A revenue-sharing model could be used with partner networks like Cowswap, Brink, and Aperture, earning Enso a percentage of profits derived from its technology. Furthermore, Enso native tokens could be sold through token sales, used for transaction fees, staking, or governance within the network. Finally, performance-based pricing could allow Enso to charge more for high-performance solutions, aligning pricing with the value delivered. This multi-pronged approach would enable Enso to sustain growth and serve a wide range of customers, from small developers to large networks. ## Competitive Landscape It is impossible to overestimate the significance of unity in the current Web3 environment because fragmentation has become a problem. As a result, an underlying layer or infrastructure is necessary because Web3 requires a node, including layer-1 blockchains, DeFi protocols, GameFi projects, NFT projects, and so forth. As such, the need for a reliable, secure, and efficient layer needs to be present, and providing such services is key, as such service would be the central utility player providing the critical infrastructure for the growth of Web3 as a whole. The Enso team started building the Enso network in 2021 as a B2C DeFi super app, but this idea was discontinued as the team was able to identify that various crypto projects (including theirs) have two issues: how to integrate all of DeFi safely and conveniently without much overhead. So the Enso team decided to pivot fully into DeFi aggregation middlelayer infrastructure, enabling developers to interact with all of DeFi without the burden of integrations themselves. The competitive landscape for DeFi middleware solutions revolves around key projects like Ankr and Anoma, which focus on simplifying DeFi integration and processes by offering similar services. ## Ankr Similar to Enso, Ankr Network serves as the gateway through which developers, projects, and protocols connect to the node infrastructure and development tools they need to build their respective applications. The focus of Ankr is to provide multi-chain tools and node infrastructure to make Web3 development easy and prolific. The Ankr Network includes free, public RPC endpoints that developers have come to know and love, alongside new Premium and Enterprise plans packed with advanced developer tools—all powered by a globally distributed and decentralized network of nodes. Hence, developers pay-as-they-go for access to on-chain data, independent node providers serve blockchain requests to earn ANKR tokens, and stakes contribute ANKR tokens to full nodes to secure the network and share in the rewards. The Ankr network provides services that are trusted and used by various renowned crypto projects, such as Polygon, Binance, Mantle, and Chiliz, amongst others. The Web3 API is another product of the Ankr Network that helps to bridge the fragmentation problem in the Web3 world, as it connects developers and various applications to the blockchain and one another. Numerous important projects, including the ones mentioned above, use the Web3 API, which has gained enormous acceptance in the ecosystem. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/8f56c2bd8b3c.png) *[Web3 API](https://www.ankr.com/web3-api/)* Furthermore, Ankr's Decentralized Physical Infrastructure (DePIN) of nodes ensures Ankr’s clients always have the shortest roundtrip path for RPC requests, providing fast Web3 experiences no matter where users are. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/11f6e62f0ad8.png) *Ankr's Decentralized Physical Infrastructure (DePIN)* ## Anoma Anoma is a distributed operating system for intent-centric apps; it introduces a new paradigm for dapps and provides a unified developer experience across any underlying blockchain. Anoma acts as the missing link between chains and users as it unifies blockchains into an integrated OS where builders and users don’t need to worry about the complexities of which chain or VM they’re interacting with. It changes the way we interact with blockchains and enables a future of user-friendly, seamlessly integrated dapps. Anoma is currently attempting to raise [$40m at $1b fdv](https://www.bloomberg.com/news/articles/2024-07-30/anoma-seeks-1-billion-valuation-as-crypto-venture-funding-jumps) and it recently launched its Devnet. Anoma aims to bring an intent-centric approach to blockchain interactions, shifting from traditional transaction-based models to a more flexible framework where users express intents rather than executing predefined steps. It provides a standardized mechanism for intent discovery and resolution across connected chains, rollups, and dapps. Anoma does not yet have a live mainnet implementation and is currently in the testing phase with its Devnet. While its architecture introduces novel intent-centric mechanisms for interoperability and composability, its real-world effectiveness and adoption remain to be seen as it progresses toward broader developer integration and ecosystem support. ## Enso, Ankr, and Anoma ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/674550737b42.jpg) Enso has anchored itself as a thought leader within the intent ecosystem and is capturing a large market share to ensure its potential competitors are not able to capture any of the markets. The Enso network currently has over 75+ projects using Enso, such as [CowSwap](https://cow.fi/),[Li.Fi](http://li.fi/) and many more. More so, new primitives are currently being built on the Enso network, which pushes the core infrastructure to the edge, hence bringing about rapid innovation; some primitives are launched already and some are still in development. Some of the primitives include: 1. [Glider](https://glider.fi/): automated trading strategies for all EVM chains with a visual drag-and-drop interface built using Enso. The team is the OG tech lead and design lead of 0x and Matcha. 2. [Plug](https://onplug.io/): No code visual creation tool for building transactions for DeFi with automation tooling. 3. [BrianKnows](https://www.brianknows.org/): AI chatbot for building transactions. 4. [Grindery](https://www.grindery.com/): Telegram bot with 1+ million users using Enso. 5. [Velvet](https://velvet.capital/): DeFi asset management tool. Enso powers many applications in production as of today and will continue this journey whilst targeting the top layer more in the coming future. In particular, Enso has determined a seamless business development pipeline to bring more projects using Enso; however, the real golden ticket lies within newer developers building blockchain applications, and Enso will be positioning itself as the go-to toolkit for building blockchain applications. Enso has been able to aggregate a direct volume of over $1 billion and has hence been able to integrate over 75+ projects across various ecosystems such as Polygon, Ethereum, Arbitrum, Gnosis, Optimism, and BNB, with Ethereum having the highest volume of on-chain activity of over 34 million. The [Boyco Bootstrapping Campaign](https://x.com/Berasearch/status/1874794888430342293) successfully leveraged Enso’s cross-chain capabilities to facilitate the largest-ever on-chain liquidity bootstrapping event for Berachain’s mainnet launch. By enabling Royco Protocol to create custom Incentivized Action Markets (IAMs), liquidity providers seamlessly deployed capital across 4+ chains and 20+ protocols ahead of launch. This led to the largest-ever volume of direct intents settled on Enso, about $3 billion on Berachain, bringing the total volume of intents settled via Enso to over $4.7 billion. By abstracting complexity and streamlining liquidity deployment, Enso and Royco played a pivotal role in ensuring deep liquidity and efficient capital flow from day one of Berachain’s mainnet. ![](https://shoal.xyz/research/writing/enso-network-shortcuts/img/5c1973ef9895.jpg) ## The Future of Enso As the blockchain ecosystem rapidly evolves, the old method of manual integrations for each new chain or protocol is no longer sustainable. Every new technology introduces complexities that demand extensive time, resources, and constant maintenance, which ultimately hinder innovation. Enso is designed to address these challenges by providing blockchain shortcuts—simple, reusable building blocks that abstract complex on-chain actions. By allowing developers to quickly find solutions that work across multiple chains and protocols, Enso removes the bottlenecks traditionally associated with Web3 development. Enso simplifies interaction with different blockchain networks by automating common on-chain actions, such as token swaps, multi-chain asset management, DeFi routing, and smart contract interactions. These pre-built solutions enable developers to avoid the complexities of learning and integrating each protocol, allowing them to focus on building innovative features. By offering a shared engine that standardizes these actions, Enso reduces the need for redundant development work and ensures that developers can adapt quickly to changes in the blockchain ecosystem. The future of Enso is centered on expanding its capabilities and providing greater interoperability across blockchain networks. This vision will unfold in phases: **Phase 1: Centralized Service Co-Existing with the Network** - During the initial network launch, Enso's centralized service will operate alongside the network to ensure stability and functionality. - Independent validators will simulate bytecode solutions to verify that the network operates as intended. - Developers who wish to be action providers can contribute through the centralized service, allowing seamless integration and providing much-needed stability during these early stages. **Phase 2: Fully Permissionless and Decentralized Ecosystem** - Once the network has proven its stability and functionality, it will transition to a fully permissionless model. - A broader range of action providers and graphers will be able to participate, fostering a decentralized and sustainable ecosystem. - The Enso network will expand beyond the Ethereum Virtual Machine (EVM) to include support for other blockchain frameworks, such as the Solana Virtual Machine (SVM) and Move Virtual Machine (MVM). - This expansion will significantly enhance the developer experience, enabling seamless integration of multiple ecosystems within a single network and offering greater flexibility for developers. The ability to quickly integrate new chains and protocols, combined with the simplicity and flexibility of blockchain shortcuts, allows Enso to empower developers to build faster and with greater ease. With Enso, teams can bypass the time-consuming integration process and focus on delivering high-value features to users, leading to more robust and feature-rich Web3 applications. Whether building DeFi applications, NFT platforms, or cross-chain solutions, Enso’s platform makes it easier than ever to bring ideas to life. As Enso progresses through its development phases, it will continue to redefine how blockchain applications are built. By abstracting away complexity, reducing maintenance burdens, and enabling seamless integration across multiple blockchain ecosystems, Enso is not just simplifying the development process—it's transforming the way developers engage with the decentralized web. With its vision of an open, interoperable, and permissionless ecosystem, Enso is positioning itself as a key player in the future of Web3. ## Conclusion Intents have emerged as a promising solution to the challenges of interoperability and fragmentation within the blockchain ecosystem. By enabling users to focus on desired outcomes rather than the complexities of execution, intents simplify interactions across disparate blockchain frameworks. **Enso Network**, at the forefront of this innovation, delivers a transformative, intent-driven engine that powers blockchain abstraction, simplifies integrations, and accelerates the pace of Web3 development. This ambitious project seeks to bridge the yawning gap between fragmented blockchains through its revolutionary shared network state and bytecode generation capabilities, effectively creating a unified platform for developers to build upon. Enso's potential applications are vast and far-reaching: - Developers can leverage the platform to create transactable and consumable data products, AI-driven bots, and cross-chain solutions with unprecedented ease. - The project's focus on usability and interoperability positions it as a crucial tool for accelerating development cycles and driving innovation in Web3 applications. - By abstracting away the complexities inherent in interacting with multiple blockchain networks, Enso allows developers to concentrate on building features rather than navigating the intricacies of multi-chain DeFi. A key component of the Enso ecosystem is the ENSO token: - ENSO token plays a multifaceted role in governance, security, and incentivizing participation within the network. - This native cryptocurrency serves as the foundation for a robust incentive structure, rewarding contributors for their efforts in maintaining and improving the platform. - Furthermore, the token-based governance model ensures that decision-making power remains distributed among stakeholders, preventing centralization and promoting long-term sustainability. Enso represents a significant step forward in addressing the usability challenges inherent in the blockchain ecosystem. Its innovative approach to abstraction and interoperability offers immense potential for simplifying development and enabling more sophisticated applications across multiple blockchain networks. As the project progresses towards full decentralization, it stands to play a pivotal role in shaping the future of Web3 development, fostering collaboration between disparate blockchain ecosystems, and unlocking new possibilities for decentralized applications. ## References - Official Enso Doc.[https://docs.enso.build/content/get-started/introduction](https://docs.enso.build/content/get-started/introduction) - Enso: Intent Engine. [https://drive.google.com/file/d/1QufKeCz2-fxq9NGyYNnLlMlQ478ypDkx/view?ts=6786c915](https://drive.google.com/file/d/1QufKeCz2-fxq9NGyYNnLlMlQ478ypDkx/view?ts=6786c915) - *Enso Dune Dashboard - Private* --- ***Not financial or tax advice**. The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.** All posts are the author's own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent.This post has been sponsored by Enso Team. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Moonshot Mania: Democratizing Access to the "Memecoin Supercycle" Bubble > The memecoin mania, driven by virality and speculation, is reshaping crypto’s intersection with finance, memes, and politics—while Moonshot leads with seamless access through its mobile app. - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-03-04 - Canonical: https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/ - Keywords: AI agents, crypto, DeFi, Ethereum, Bitcoin ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/e5c2837023a7.jpg) ### Prepare for Liftoff The meteoric rise of memecoins from niche jokes for the “[terminally online](https://www.urbandictionary.com/define.php?term=Terminally%20Online)” to a legitimate market force has redefined the cryptocurrency landscape over the past decade. What began as a niche experiment with Dogecoin (DOGE) in 2013 has evolved into a global phenomenon, captivating power-users, casual enthusiasts, and industry veterans alike. The current memecoin cycle, which surged in early 2023, has been marked by unprecedented levels of community engagement, virality, and speculative fervor—giving rise to some of the most absurd (and lucrative) narratives to ever grace (or haunt) the blockchain. From the meteoric [comeback of OG memes](https://nftevening.com/from-comic-alt-right-symbol-to-meme-nft-to-viral-coin-the-pepe-journey/) to the unpredictability of pairing [mission-driven AI chatbots (agents) with heavily funded crypto wallets](https://www.axios.com/2025/01/07/meme-coins-ai-chatbots-crypto), and the rise of new [main characters](https://x.com/muststopmurad?lang=en) driving the industry’s latest memetic chapters, this [(super)](https://www.coingecko.com/learn/memecoin-supercycle-crypto)cycle truly has it all. At the center of this movement is Moonshot, a mobile app featuring minimalist aesthetic and a simple mission: **demystify and democratize access to memecoins**. By integrating familiar payment methods like Apple Pay, simplifying user onboarding through Face ID, and offering a curated selection of memecoins, Moonshot has positioned itself as the preferred gateway for less crypto-native, yet highly interested, traders. More than just a platform, Moonshot’s influence on token price action—akin to the impact of centralized exchange (CEX) listings—underscores its potential to redefine the role of vertically integrated platforms in speculative markets. This report dives into the rise of memecoins, exploring their cultural significance and the macroeconomic conditions driving their resurgence. We’ll analyze Moonshot’s innovative approach to memecoin trading, unpack the broader competitive landscape, and assess the ripple effects of this narrative on the cryptocurrency industry at large. As the memecoin supercycle narrative gains momentum, this report highlights how Moonshot—and platforms like it—are poised to shape the future of digital assets. ### The Evolution of Memecoins The story of memecoins begins in 2013 with the launch of Dogecoin. Created by software engineers Billy Markus and Jackson Palmer, Dogecoin was initially intended as a parody of the growing seriousness of Bitcoin and the proliferation of other cryptocurrencies. Using the viral "Doge" meme—a Shiba Inu dog with humorous captions in Comic Sans—Dogecoin was meant to poke fun at the digital currency space, reflecting the playful and sometimes absurd culture of internet memes. Dogecoin quickly attracted a passionate community that was drawn to its humor and overall lack of pretension. Unlike other cryptocurrencies focused on serious use cases, Dogecoin embraced its identity as a fun and retail user-friendly token. This unique blend of humor, community engagement, and [charitable initiatives](https://fastercapital.com/content/The-Generous-Pup--How-Dogecoin-Revolutionizes-Charitable-Giving.html) helped it achieve staying power. Notable examples include fundraising campaigns to support the Jamaican bobsled team and initiatives to provide clean water in Africa, which highlighted Dogecoin's emphasis on social good and further endeared it to its growing community. The memecoin narrative remained relatively quiet until 2020, when Shiba Inu ($SHIB) entered the scene. Branded as the "Dogecoin killer," Shiba Inu was created as part of a new wave of memecoins that capitalized on the cultural influence of internet humor and social media virality. Shiba Inu went beyond Dogecoin by introducing an entire ecosystem of tokens and leveraging decentralized finance (DeFi) and non-fungible token (NFT) elements. The so-called "Shib Army" grew quickly, using social media platforms to promote the coin and foster a sense of community among holders. In 2021, memecoins saw explosive growth, moving from the fringes to the mainstream. Influential figures, most notably Elon Musk, began tweeting about Dogecoin, propelling it into the public consciousness and driving unprecedented retail interest. Dogecoin's price surged, and new memecoins emerged in rapid succession. Coins like Floki Inu, Akita Inu, and other *not-particularly-original*tokens flooded the market, each trying to capture a piece of the growing enthusiasm around memecoins. The success of Dogecoin and Shiba Inu highlighted the power of memes in driving financial speculation. Unlike traditional cryptocurrencies like Bitcoin or Ethereum, memecoins often lack intrinsic value or utility. Their appeal lies in capturing attention and engaging users through humor, community spirit, and the promise of rapid gains. This dynamic has led to a proliferation of memecoins, with new tokens launching constantly, often with little regard for their similarity to existing ones. According to Murad – a market participant who’s taken a central role in the current memecoin cycle – however, investors should avoid copycat tokens and instead focus on trendsetters—those unique coins built on fresh memes, innovative structures, or concepts capable of achieving true virality, rather than just another animal-themed token. The cultural significance of memecoins also extends into the realm of NFTs. The concept of "Rare Pepes"—meme-inspired digital assets that could be collected and traded—laid the groundwork for memecoins to be used as collectibles. This trend continued with Shiba Inu's "Shiboshis," a collection of NFTs that provided additional engagement opportunities for the Shiba Inu community. By combining the speculative nature of tokens with the unique cultural appeal of internet memes, memecoins have become a versatile and engaging aspect of the broader crypto ecosystem. Today, memecoins remain a prominent part of the crypto landscape. Despite skepticism from many in the blockchain community, who argue that memecoins undermine the credibility of the space, they continue to thrive. Memecoins offer a unique intersection between finance, culture, and community, creating a financialized form of memetic internet humor that appeals to millions. Whether viewed as a bubble fueled by speculation or as an authentic expression of decentralized community spirit, memecoins have undeniably become a significant force in crypto markets, and they are likely to continue shaping the narrative of the industry for years to come. ### Factors Driving the Current Memecoin (Super)Cycle Murad Mahmudov, a leading crypto analyst and investor, is a central figure in the memecoin narrative. Known for his sharp insights and ability to forecast trends, Mahmudov coined the term "Meme Supercycle" to describe the explosive growth of memecoins driven by internet culture, community enthusiasm, and speculative investing. His ideas gained significant traction following [his presentation at the Token2049 conference](https://youtu.be/6nqzwdGxTGc?si=xKaBX7tmwmUj72xg) in Singapore in September 2024, where he laid out a compelling argument for why memecoins could become [one of the best-performing assets of the current cycle](https://x.com/artemis/status/1877083890717761856). According to Murad, the power of memes lies in their viral nature, which enables them to bypass traditional financial metrics. Unlike cryptocurrencies that rely on technological innovations, memecoins derive their value from cultural relevance and the collective imagination of their communities. He believes that the Meme Supercycle is not just a temporary craze but an ongoing cultural movement that will persist as long as these tokens continue to captivate public interest. Murad's arguments are particularly persuasive in highlighting the cultural and emotional drivers behind memecoins—factors that position platforms like Moonshot to capitalize on this growing market. Macro and Market Dynamics Memecoins have thrived in times of speculative fervor within the broader cryptocurrency market. In his now-lauded presentation, Murad emphasized that memecoins have significantly outperformed traditional cryptocurrencies, with a majority of the top-performing tokens in 2024 being memecoins. This dominance is partly due to the disillusionment of investors with utility tokens that often fall short of delivering meaningful returns. In contrast, memecoins embrace their speculative nature, with many memecoin traders acknowledging and embracing the ridiculously poor odds at striking rich through this endeavor. These coins rely on virality and excitement rather than measurable technological innovations that can limit its growth – in fact, many believe this to be a critical selling point. During times of favorable market conditions and increased liquidity, investors eager for high-risk, high-reward opportunities are often drawn to memecoins. Though the same can be said about casino-goers… Community and Social Virality One of the most powerful drivers behind memecoins is their community-centric nature. Murad pointed out that these assets derive their value not from utility, but from cultural resonance and the shared enthusiasm of their communities. Memecoins operate within an "emotional economy," where the sense of belonging and excitement is crucial to their valuation. Platforms like Twitter, Reddit, and Telegram play a vital role in fostering these communities, the [Wallstreet Bets forum](https://www.vanityfair.com/news/story/wallstreetbets-gamestop-and-the-swirl-of-distrust-thats-electrifying-the-stock-market?srsltid=AfmBOoosyCtqaB_lUtOir7_3cJf6INdJ9IK398vxRF8moGBsQrBiht2p) being a prime example, amplifying the collective identity that memecoins create. As Mahmudov said, "The more you buy, the more belonging, identity, and fun you gain alongside memecoins," highlighting how community-driven demand is the engine that fuels these tokens. Memecoins have also emerged as a low-cost way for individuals to join online communities, providing a sense of belonging that is particularly valuable in today's increasingly isolated digital society. Many people turn to these communities to alleviate feelings of loneliness, and the accessibility of memecoins makes them an attractive means to be part of something larger. For a minimal investment, individuals can participate in thriving communities, sharing in the excitement and camaraderie that comes with collective action. Speculation and Risk Appetite The appeal of memecoins lies heavily in their speculative potential—an aspect that has resonated deeply with a particular type of investor seeking high-risk opportunities with massive upside (and obvious downside). Memecoins have been described as the "gamble of the decade," offering the average person the chance to turn a small investment into significant gains in a very short time. This speculative fervor is similar to the thrill of gambling, tapping into the excitement of high stakes and rapid results. Murad has even argued that in many ways, "all altcoins are essentially memecoins, just more complex versions," implying that the distinction between utility and speculation is often blurred. Investors are not simply looking for technological advances; they are searching for assets that capture popular sentiment, embody community passion, and offer the allure of high rewards. Memecoins fit this mold perfectly, relying on their cultural cachet and the collective imagination rather than on technological innovation. Celebrity and Influencer Endorsements Celebrities and influencers have played an outsized—[and often negative](https://cointelegraph.com/news/fame-failure-celebrity-crypto-scams)—role in shaping the visibility of memecoins, significantly driving both their meteoric rises and occasional implosions. High-profile figures like Elon Musk, with his widely publicized endorsements of Dogecoin, have demonstrated the power of celebrity influence to create massive price swings and bring mainstream attention to the memecoin market. This dynamic has only intensified during the current memecoin supercycle, where celebrity-backed tokens often act as "financialized vessels of faith." While these endorsements embed memecoins deeper into mainstream culture, they frequently lead to short-lived hype cycles, with many tokens struggling to sustain momentum after the initial buzz. This evolving phenomenon reached a historic milestone in January 2025 with the launch of $TRUMP, a memecoin tied to the incoming U.S. president. This unprecedented event marked a new phase in the memecoin supercycle, further intertwining the world of memecoins with cultural and political narratives. ***Note:** This report was researched between December 2024 and January 2025, and as such, parts of the analysis may not fully account for a pivotal event that unfolded just days before its scheduled publication—namely, the launch of $TRUMP, the incoming U.S. president’s official memecoin, on January 17th, and the [$LIBRA memecoin debacle](https://www.reuters.com/technology/politician-linked-meme-coins-backfire-after-libra-scandal-2025-02-21/) following that. To address this historic development, we have included two dedicated sections: one covering the $TRUMP launch itself and another analyzing its direct impact on Moonshot. These sections are intended to serve as timely debriefs, complementing the original analysis and providing a more comprehensive understanding of this unprecedented moment in the memecoin landscape.* ### The US President-Elect Launches a Memecoin ($TRUMP) In a groundbreaking moment for cryptocurrency, President-elect Donald Trump launched his official memecoin, $TRUMP, on January 17, 2025, just days before his inauguration. The timing of the launch, coinciding with the resignation of SEC Chair Gary Gensler, created a perfect storm of market speculation and optimism for regulatory leniency. This event marked the first time a U.S. political figure of such prominence directly engaged with the memecoin sector, catapulting $TRUMP into the spotlight and reshaping market dynamics overnight. The launch was met with extraordinary enthusiasm, with mainstream media headlines highlighting $TRUMP’s fully-diluted value (FDV) surging past $30 billion within 24 hours and peaking at $82 billion the following day–though the meaningfulness of this figure is questionable as only ~20% of supply is currently in circulation, thus the token price will inherently be prone to wild swings on relatively scarce liquidity. The remaining 80% is owned by President Trump and the Trump-family owned firm that is responsible for launching all of Trump’s blockchain endeavors, CIC Digital. The remainder of the supply will unlock over the course of three years: ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/31fee2f545b8.jpg) *Source - gettrumpmemes.com* As a result, the token’s price skyrocketed by over 10,600%, reaching ~$75, fueled by unprecedented media attention and fervent trading activity. Moonshot, the premier platform for trading $TRUMP, emerged as a key beneficiary, recording a record-breaking influx of over 400,000 new signups within the first 24 hours. However, the excitement was not without complications. Less than 48 hours after $TRUMP began trading, First Lady Melania Trump launched her own official token, $MELANIA, which introduced significant turbulence to the market. While $MELANIA achieved a notable $13 billion FDV ($2.2B MCap given only 20% circulating supply), its release diluted the $TRUMP narrative, erasing $7.5 billion in $TRUMP’s market cap within 10 minutes. Ultimately, the price of $TRUMP fell more than 60% from the highs just hours after $MELANIA launched, with prices hovering around $30-40 on January 21st. This sparked confusion and division among retail investors, leading to a temporary liquidity crunch and dampened momentum. Despite the blatant ethical concerns, the $TRUMP launch has established a precedent for how memecoins can be leveraged by political figures, further blurring the lines between finance, culture, and politics. This historic moment underscores both the immense potential and inherent risks of the memecoin supercycle, solidifying Moonshot’s role as a central player in this evolving narrative. ### Case Study: Moonshot Mobile App (moonshot.money) ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/d231ff598fa1.jpg) The memecoin market, characterized by its speculative nature and cultural appeal, is experiencing a wave of platforms aimed at simplifying access to these tokens. Among the most promising is Moonshot, a mobile app designed to democratize access to memecoins and capitalize on their growing popularity. Overview of Moonshot Moonshot is an innovative mobile app that aims to bring memecoin trading to the masses through a simple, neatly-packaged design. Available on both iOS and Android platforms, it allows users to buy and sell popular Solana-based memecoins with ease. By integrating familiar payment methods such as Apple Pay, PayPal, debit and credit cards, Moonshot makes crypto trading feel familiar, approachable, and user-friendly—particularly to those who are not crypto-native. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/3af9e796b2b5.jpg) One of the core objectives of Moonshot is to lower the barriers to entry for the memecoin market. For many new users, the complex processes associated with cryptocurrencies—such as setting up wallets and managing seed phrases—are significant hurdles. Moonshot addresses these issues by offering an easy onboarding process using email and Face ID, and by employing a self-custodial wallet system that doesn’t require deep blockchain knowledge. This approach aims to make memecoin trading as seamless as using mainstream financial apps, which could broaden the app’s appeal beyond crypto enthusiasts to include more casual users. The integration of Apple Pay and MoonPay into the Moonshot app enhances the app’s flexibility, allowing users to fund their accounts with both traditional payment methods and cryptocurrency. MoonPay also manages fiat custody during deposits and withdrawals, ensuring compliance and smooth transaction flows. By emphasizing ease of use and accessibility, Moonshot positions itself as an inviting gateway to the memecoin ecosystem. Moonshot’s Moon Mission Moonshot distinguishes itself from competitors with its focus on vertical integration and delivering a superior user experience. By creating a one-stop platform for discovering, buying and selling memecoins, Moonshot directly addresses the needs of casual traders who might find traditional platforms overwhelming. Many existing crypto exchanges cater to advanced users with intricate tools and interfaces, while Moonshot prioritizes simplicity, making it more inviting for mainstream audiences. This design ethos mirrors how Instagram refined Snapchat’s stories feature—taking a familiar concept and elevating it through superior design and usability. Similarly, Moonshot brings memecoins to the masses in a highly accessible way, much like how Robinhood transformed retail investing by making low-cost stock trading widely available and forever changing the way retail investors interact with the stock market. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/7f609ca1059a.jpg) *Source: https://x.com/MustStopMurad/status/1815868239836012613* Moonshot’s strategy also draws inspiration from [VeVe](https://nftevening.com/a-guide-to-top-digital-collectible-nft-platform-veve/), a platform that transformed the NFT space by creating a user-friendly app that appealed to both crypto-native and mainstream audiences. Similarly, Moonshot eliminates cumbersome processes, provides curated token selections, and offers incentives like referral bonuses. These features position memecoins as a fun and engaging entry point into the broader cryptocurrency ecosystem, much like NFTs in previous cycles. The app’s potential is underscored by the rapid growth of the memecoin market, which reached an all-time high aggregate market capitalization of approximately $127 billion in December 2024, up from just $9 billion in March 2021. This explosive growth highlights the massive opportunity ahead for Moonshot as it seeks to establish itself as the go-to platform in the memecoin sector. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/3554087b67ca.jpg) Moonshot Goes Nuclear (Post-Launch of $TRUMP) ***Author’s Note:** This debrief of Moonshot’s performance metrics following the official launch of the $TRUMP memecoin builds upon the original analysis, finalized just one week before the token’s release. By juxtaposing Moonshot’s pre-launch trajectory with its post-launch explosion in activity, this section provides valuable context for understanding the platform’s evolving role in the memecoin market. While the influx of new activity has been dramatic, the unprecedented nature of the $TRUMP coin launch leaves open questions about the sustainability of this momentum.* ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/3981746ef404.jpg) The launch of the $TRUMP memecoin on January 17, 2025, propelled Moonshot to unprecedented growth, attracting 400,000 new signups (separate from DAUs)) within 24 hours. At the peak of the token hype (January 19th), the app recorded a staggering $650 million+ in daily trading volume, generating over $10.3 million in fees. This is a particularly notable figure given that, prior to the $TRUMP token launch, Moonshot had collected just ~$9 million in *cumulative* fee revenue since its July 2024 debut. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/c3275e6c966b.jpg) Daily active users (DAUs)–users who place at least one trade on the platform in a given day– surged to over 180,000 on January 19th, (106k new users and 74k recurring users) a more than 10x increase since the app’s already impressive growth spike in November 2024. Moonshot’s lifetime trading volume has now surpassed $2 billion, with over 400,000 unique users having completed **at least one trade** on the platform since the app's inception. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/e176d66906ff.jpg) This explosive growth underscores Moonshot’s central role in the memecoin ecosystem. As the primary platform facilitating $TRUMP’s trading activity, Moonshot not only captured massive attention but also showcased its infrastructure’s scalability in managing unprecedented surges in demand. However, this rapid expansion wasn’t without challenges. The launch of the $MELANIA token shortly after $TRUMP’s release introduced significant volatility, leading to a sharp decline in $TRUMP’s price. Frustrated users quickly took to Twitter (X) to air grievances about their inability to sell their plummeting $TRUMP positions, with some accusing Moonshot of being a “scam.” Critics pointed out the app’s seamless buying experience contrasted sharply with difficulties in selling during high-pressure moments. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/6c9e4fca26e5.jpg) For those familiar with fintech, such growing pains are not unique. Industry leaders like Robinhood and Coinbase have faced similar server overloads during periods of intense market activity. Moonshot, despite its extraordinary success as the onboarding platform for $TRUMP, remains a relatively nimble operation, and such challenges are part of its scaling process. These temporary setbacks, which were resolved within a reasonable timeframe, have done little to dent Moonshot’s position at the top of the app store leaderboards, reaffirming its place as a cornerstone of the memecoin trading ecosystem. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/c548f2cada77.jpg) User Base and Fee Revenue (Pre-Launch of $TRUMP) Moonshot’s intuitive design has driven remarkable user adoption and engagement. The app provides real-time data on key metrics like market cap, trading volume, and all-time highs, ensuring users feel informed without being overwhelmed by overly technical indicators. Curated "blue-chip" memecoins, such as Pepe, Bonk, WOOF, and POPCAT, enhance the user experience by offering options that have passed Moonshot’s selective vetting process. While these coins can still exhibit significant volatility, they are less likely to result in instant rug pulls. These curated tokens are typically characterized by higher market caps, credible development teams (e.g., Pudgy Penguins), relatively decentralized supply distributions, and a proven trading history—criteria designed to mitigate risk and improve user confidence, though Moonshot does not publicly disclose the specifics behind any individual token approval. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/461893bd2f41.jpg) Over the course of its first ~4 months, daily trading volume on the platform reached a peak of $36.2 million, generating $533k in fees on that day alone (November 20th, 2024). Since inception, the trading app has generated $8.3M in aggregate fees from $562M in lifetime volume via 2 million transactions placed directly through its platform. According to an on-chain dashboard tracking Moonshot’s metrics, the platform has also welcomed 119,500 unique lifetime users who have placed at least one trade. As depicted in the chart below, Moonshot experienced hockey stick-level growth in its daily active user (DAU) figures since inception. In August 2024 (approximately 1 month post-launch), the app had just 118 daily active users, which grew to 14.5k by November 20th—a >100x increase. However, after this peak, both volume and user figures began to decline, though a secondary spike in mid-December pushed DAUs to an all-time high of 14.8k. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/da64bf79d3dc.jpg) Many well-known figures within the industry began to take note after the memecoin MOODENG—facilitated by Moonshot’s fast onboarding and user-friendly interface—“broke the internet” (or at least crypto Twitter) for a brief period: ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/8f3f1cb89f55.jpg) *Sources: **[https://x.com/based16z/status/1839330311588700371](https://x.com/based16z/status/1839330311588700371) [https://x.com/yashhsm/status/1839406547753119915](https://x.com/yashhsm/status/1839406547753119915)*** Though its breakneck growth in under a year since launch is inarguably impressive, Moonshot has struggled to sustain its momentum since its late-November peak and DAU spike in December. This raises an important question: Is this an app-specific issue or indicative of a broader malaise within the memecoin economy? The slowdown mirrors broader trends in risk assets following a post-election surge and increased uncertainty surrounding potential Federal Reserve rate cuts in 2025. Additionally, speculative markets such as crypto often experience pullbacks near year-end, influenced by the holiday season and tax-driven profit-taking. Rather than signaling a permanent decline, this "pause" can be interpreted as a natural consolidation phase, setting the stage for the next leg up and aligning with the broader memecoin supercycle thesis. The answer lies partly in the chart below, which highlights the ratio of trading volume-to-market capitalization of the top-10 largest memecoins by market cap: ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/22e3deebe43c.jpg) As illustrated, momentum peaked on November 20th, coinciding with Moonshot’s peak in trading volume. Following this, most top-10 memecoins experienced neutral-to-negative price action through the year’s end, often attributed to end-of-year profit-taking tied to tax implications. Additionally, a large number of U.S. politics-related tokens such as “TRUMP,” “TREMP,” and “BODEN” surged leading up to the 2024 election on November 6th but plummeted in relevance in the days that followed, [mirroring Polymarket’s 64% drop in open interest](https://www.theblock.co/post/325038/polymarket-open-interest-drops-64-after-us-presidential-election) by November 8th. The unwinding of these narratives likely contributed to Moonshot’s downturn in activity. The mid-December secondary spike in user growth, however, highlights Moonshot’s agility in responding to cultural trends. This spike coincided with the launch of the highly anticipated Pudgy Penguin coin (PENGU) and Moonshot’s same-day announcement approving PENGU for trading. This rapid, community-driven response underscores Moonshot’s commitment to fostering engagement through cultural relevance—a quality valued by both crypto-native and retail users. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/ff5e0ada59d9.jpg) Another key aspect of Moonshot’s strategy is its emphasis on incentivizing user growth. The app’s referral program, which mirrors Robinhood’s highly successful “refer-a-friend, receive a free stock” model, allows users to earn up to $100 in rewards from a “predetermined pool” of memecoins when they invite friends. This referral strategy fosters a social layer of engagement vital to memecoin culture and has proven effective for low-cost customer acquisition. Per the program’s terms, there is a 90% chance of a $3 referral bonus and a 0.1% chance of receiving $100. By enabling users to share in each other’s trading experiences, Moonshot not only drives growth but also creates a shared sense of excitement and community— critical ingredients in honing memetic power. Vertical Integration and Future Growth Vertical integration within memecoin trading is a key strategic advantage for Moonshot. By offering a superior user interface, real-time data access, and bundling trading tools, token launches, and user-friendly payment options into a cohesive app, Moonshot positions itself as a leader in memecoin trading for both casual participants as well as more advanced traders looking for a streamlined app. This model mirrors successful platforms in other industries that simplify traditionally complex processes, such as Robinhood’s approach to stock trading or DraftKings’ approach to fantasy sports. Moonshot’s role as a gateway for less crypto-native but highly interested memecoin traders has granted it a level of influence typically reserved for centralized exchanges (CEXs). Despite Moonshot acting solely as an intermediary between traders and decentralized exchanges, the app’s announcement that a new memecoin has become "available" to its users—signaling it has been vetted and added to Moonshot’s curated list—can significantly influence the token’s underlying price action in the immediate aftermath. This phenomenon mirrors similar impacts seen during CEX listing announcements ([though not always positively for the latter)](https://cryptoslate.com/tokens-display-up-to-negative-70-median-returns-after-cex-listing-animoca-research/), elevating Moonshot’s position as a power-broker in the space. This influence seems destined to grow. With the success of the $TRUMP launch, traders will surely be keeping an eye on their Moonshot notifications: ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/e0d14490b30c.jpg) ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/0771aa29efea.jpg) By positioning itself as the easiest way for users to get started with memecoins and offering an engaging and straightforward user experience, Moonshot could play a pivotal role in bringing more people into the cryptocurrency ecosystem. The app’s integration of all necessary tools, ease of use, and focus on memecoin culture align well with the growing interest in speculative, culturally driven assets that are defining the current memecoin cycle. Solana-based DEX Jupiter has recently acquired a majority stake in Moonshot. The acquisition, announced on Jan. 25, marks a strategic expansion for Jupiter, integrating Moonshot’s intuitive fiat-to-memecoin onramp with Jupiter’s deep liquidity and trading infrastructure. ![](https://shoal.xyz/research/writing/moonshot-mania-democratizing-access/img/36f996081431.jpg) *Source : https://x.com/weremeow/status/1883068425737556153* Jupiter’s investment is an indication of how DEX aggregators are positioning themselves as comprehensive liquidity hubs, integrating user-friendly retail platforms with their existing infrastructure. The Competition: Memecoin-Focused Mobile Apps Though Moonshot appears to be the first trading app of its kind–targeting crypto’s highly-volatile “memecoin” vertical–to gain approval on the iOS App Store, competitors are emerging. Apps such as ChainPro, [Hype](https://www.ycombinator.com/companies/hype), Vector, and Motion have entered the market, with more likely to follow. However, these competitors currently operate on a much smaller scale compared to Moonshot. For instance, Moonshot’s downloads on the Google Play Store is in the hundreds of thousands, while competitors like ChainPro, Hype, and Motion report downloads are in the thousands (or less). Moonshot began as an app dedicated to memecoins traded on the Solana blockchain but has recently started adding tokens from the Base chain, with plans to expand to more chains. Meanwhile, ChainPro offers users access to memecoins from multiple chains, including Solana, Base, Hyperliquid, and Ethereum, providing broader asset coverage. ChainPro also boasts a clean web-based interface for desktop trading to complement its mobile app, though its UX is slightly more complex compared to Moonshot. Vector is a social trading app by Tensor Labs, integrating social engagement with token trading across multiple blockchains, including Solana, Ethereum, and Base. Conversely, Hype and Motion mirror Moonshot’s minimalist UX/design approach, which is heavily inspired by Robinhood’s user-friendly layout. To maintain its dominance, Moonshot must continue innovating to meet user needs. This includes expanding its memecoin offerings across multiple blockchains, introducing a desktop trading interface to complement its mobile app, and maintaining its superior token vetting process. Currently, Moonshot charges 2.5% per trade on transactions sized up to $250, with fees dropping to 1% for trades exceeding this amount. In comparison, users placing the same trades directly through decentralized exchanges often pay fees as low as ~0.1%, highlighting the premium Moonshot users pay for ease, accessibility, and added security through curation. While these fees contribute to Moonshot’s impressive margins, the platform will need to sustain a perception of feature superiority to justify these costs. If competitors gain traction, Moonshot may face pressure to reduce fees, potentially leading to a "race to the bottom" in pricing within the memecoin app landscape. By ensuring quality curation and cultural relevance, Moonshot can preserve its competitive edge in an increasingly crowded market. ### Other Ecosystem Winners The ongoing memecoin boom has not only captivated retail investors but has also spurred the growth of various platforms and tools that are capitalizing on the trend. This section looks at other key players poised to benefit significantly from the memecoin supercycle. Memecoin Launchpads A major innovation in the current memecoin landscape is the rise of dedicated memecoin launchpads. Platforms like Pump.fun and SunPump have streamlined the process of creating and launching new memecoins, allowing even those with minimal technical knowledge to participate. These launchpads offer an intuitive experience that reduces barriers to entry, making it easier for new creators to jump into the ecosystem. This influx of new tokens fosters greater activity in the memecoin space, driving liquidity and attracting more traders. Memecoin launchpads, such as FOMO.FUND, have particularly gained traction by making it possible to create a token with just one click. By lowering the technical requirements and providing immediate liquidity, these platforms serve as a bridge between new projects and enthusiastic investors, thereby expanding the overall memecoin ecosystem. Cross-Ecosystem Trading Tools The memecoin sector is also seeing an increase in cross-ecosystem trading tools that make it easier for users to access and engage with various memecoin projects. Platforms like Defined enable multi-chain trading, while GMGN.AI helps analyze wallet holdings to better understand market trends and user behavior. These tools are becoming essential for navigating the increasingly crowded memecoin space, allowing both new and experienced traders to make informed decisions across multiple blockchain ecosystems. By improving accessibility and reducing friction in trading, these platforms are helping to sustain the broader growth of memecoins. Utility and Community Focus Another important category of potential winners in this memecoin narrative includes projects that blend traditional financial tools with memecoin culture, thereby adding a layer of utility. For instance, the Base chain’s $Degen started purely as a community-driven memecoin but gradually evolved to serve as a tipping coin within social platforms, adding some real-world utility to its meme roots. These hybrid projects show how memecoins can extend beyond speculative trading to build sustained engagement through integrated community features. Projects like Manta’s $10 million "Moon Mission Meme Grants" illustrate how platforms can encourage ecosystem growth through structured incentives, bridging the gap between humor-driven culture and broader blockchain adoption. AI-Driven Meme Launch Platforms Emerging AI-driven meme launch platforms, such as Memehub.ai, add another layer of innovation. They allow users to design and launch memecoins that incorporate AI-generated narratives, effectively combining two hot trends—AI and memecoins. This unique approach may attract even more attention from the crypto community and mainstream audiences. Other Vertically Integrated Trading Platforms Platforms that offer vertical integration for memecoin trading are well-positioned to emerge as winners in this rapidly growing sector. Moonshot, for instance, aims to provide a comprehensive solution for memecoin trading, combining fiat on-ramps, real-time market data, and community incentives, all within a single app. By delivering an easy-to-use interface alongside essential trading infrastructure, Moonshot sets a high standard for accessibility and user retention. However, competition in this space is intensifying. Popular web-apps such as Photon and Bullx, which have already gained traction within the crypto community, could eventually make their way onto mobile app stores, challenging Moonshot's dominance. Similarly, Telegram bots like BonkBot and Banana Gun have established themselves as trusted tools for memecoin trading and may leverage their existing user bases to expand into standalone mobile apps. These developments highlight the growing number of competitors with established brands and communities that Moonshot will need to contend with in its quest to maintain market leadership. ### The Good, the Bad, and the Bubble-y The memecoin supercycle's rise has far-reaching implications for the cryptocurrency industry as a whole. While some impacts are unquestionably positive, offering new opportunities and broadening the industry's appeal, there are also significant downsides that warrant attention. Positive Impacts Memecoins have emerged as a transformative gateway for many new users entering the crypto space. Their viral appeal and community-driven excitement often act as the initial pull for individuals who might not otherwise engage with blockchain technology. By lowering barriers to entry with their low cost and massive upside potential, memecoins introduce participants to the broader cryptocurrency ecosystem. Once onboarded, these users often diversify into other sectors like DeFi or NFTs, further enriching the industry. At their core, memecoins excel at fostering community engagement. Unlike traditional cryptocurrencies, they rely on humor, memes, and a sense of collective belonging to build vibrant networks. These communities often serve as incubators for future crypto developers and enthusiasts, creating an intersection between finance and culture that resonates with millions. According to Murad Mahmudov, memecoins represent a form of social innovation, enabling “crowd wealth creation” that democratizes financial participation—a stark departure from traditional venture capital models. Moreover, memecoins hold the potential for ethical innovation. Ethereum co-founder Vitalik Buterin has advocated for “good memecoins” that contribute to public goods or charitable causes. Mechanisms like token supply allocation or fee sharing could support social initiatives, aligning the memecoin sector with broader societal benefits. This added dimension enhances their appeal, suggesting that memecoins can be more than speculative assets. Additionally, memecoins significantly boost liquidity and trading volumes across exchanges. As market sentiment gravitates toward speculative assets, memecoins draw capital inflows and active trading, benefiting the entire crypto ecosystem. This influx of liquidity improves price discovery for other crypto assets and creates a more dynamic trading landscape, particularly benefiting decentralized exchanges and protocols. Negative Impacts The rise of memecoins has introduced significant challenges to the cryptocurrency industry, starting with their inherent volatility. Memecoins are highly speculative, prone to wild price swings that create boom-and-bust cycles. While exhilarating for some traders, this extreme volatility can deter institutional investors who prefer stability, ultimately limiting broader market adoption. The rapid surges and collapses in memecoin prices often leave less experienced participants vulnerable to significant losses. Another concern is the proliferation of scams and rug pulls. The low barrier to creating new memecoins has enabled bad actors to exploit unsuspecting investors, abruptly withdrawing liquidity and leaving tokens worthless. High-profile examples, like the SHAR coin collapse, highlight how quickly promising projects can disintegrate, eroding trust in the memecoin sector and tarnishing the broader crypto ecosystem. Such incidents also attract regulatory scrutiny, further complicating the sector’s growth. Critics argue that memecoin trading volumes often act as vanity metrics, inflating activity on struggling blockchains while overshadowing meaningful technological advancements. This dependency risks creating an unsustainable growth model for some blockchain ecosystems, diverting attention and resources away from innovation. Additionally, memecoins are often accused of betraying the core ideals of cryptocurrency, such as decentralization and technological progress, by prioritizing hype and speculation over substance. This dynamic reinforces skepticism among institutional investors and policymakers, perpetuating the perception that crypto markets lack maturity. The cultural impact of memecoins also raises concerns. Tokens that exploit divisive or harmful themes can alienate users and tarnish the industry’s reputation. Addressing these ethical issues is critical to preserving the long-term viability of the memecoin sector and ensuring it does not alienate potential participants. Lastly, the unpredictable and speculative nature of memecoins has drawn heightened regulatory scrutiny. Governments and financial watchdogs are increasingly concerned about the risks posed to retail investors, with some considering harsher measures like outright bans or stricter disclosure requirements. While regulation is intended to protect participants, overly restrictive measures could stifle innovation and deter legitimate projects from entering the space, reducing overall participation and growth potential. Menace or Miracle? Depends on your timing. While memecoins play a crucial role in expanding the crypto ecosystem and driving community engagement, they bring substantial risks to users and, at times, damaging perceptions that are difficult to separate from the more substantive crypto verticals. Striking the right balance between fostering innovation and ensuring adequate investor protection will be essential for the sustainable growth of both the memecoin sector and the broader cryptocurrency industry. Like most things in crypto, memecoins seem to live in a gray area between good and bad. Whether you're a proponent or a critic may ultimately depend on whether you bought in at the right time. ### The Double-Edged Sword of Accessibility Moonshot has positioned itself as a transformative force in the memecoin market, much like Robinhood in its early days of democratizing stock trading or Opensea in the nascent days of NFTs. By reducing barriers to entry and simplifying the trading process, Moonshot addresses key pain points for retail traders who might otherwise be deterred by the complexity of traditional crypto platforms. Its intuitive design, mirroring Robinhood’s widely praised interface, fosters a sense of familiarity and ease, making it accessible even to crypto newcomers. Strategically, Moonshot’s focus on accessibility continues to set it apart. Features like seamless login through Face ID, curated lists of vetted tokens (along with a search function for tokens not listed), and integration with payment methods such as Apple Pay and PayPal bridge the gap between traditional finance and crypto, creating an approachable entry point for users. Its role as the first mover in the memecoin-focused app space, combined with thematic curation and a user-friendly UX, establishes Moonshot as a gateway for cultural and financial participation in one of crypto’s most lively and controversial sectors. The recent launch of $TRUMP has further solidified Moonshot’s position as a market leader. By enabling the seamless trading of this historic memecoin, Moonshot played an instrumental role in its record-breaking debut, driving massive user adoption and unprecedented trading activity on the platform. This milestone underscores the app’s ability to capitalize on viral moments, cultural relevance, and the evolving narrative surrounding memecoins. However, as recent market turbulence has shown, greater access comes with greater responsibility. The memecoin sector remains vulnerable to bad actors who exploit retail enthusiasm as a vehicle for value extraction. While Moonshot has successfully lowered the barriers to participation, it must also recognize its role in mitigating the risks that come with this expanded access. Maintaining a strong vetting process for listed tokens, improving transparency around token listings, and implementing security safeguards against predatory practices will be crucial for ensuring long-term trust in both the platform and the broader memecoin ecosystem. While Moonshot faces challenges such as memecoin volatility, rising competition, and the need to continuously innovate, its early lead and strategic choices have set a strong foundation for sustained growth. Much like Robinhood transformed how people engaged with equity markets, Moonshot has the potential to redefine how users interact with memecoins. By combining accessibility, cultural relevance, and community, Moonshot has not only simplified trading but also cemented its role as a key player in the memecoin ecosystem—one that must navigate the fine line between democratizing access and safeguarding users from the very risks that make memecoins so thrilling, and so dangerous. --- ## References: 1. Captain Crypto. (2024, October). Rise of Memecoin Launchpads: A New Era in DeFi [Article]. Medium.[https://medium.com/@CapCrypto_9876/rise-of-memecoin-launchpads-a-new-era-in-defi-dc50ba1fe1e6](https://medium.com/@CapCrypto_9876/rise-of-memecoin-launchpads-a-new-era-in-defi-dc50ba1fe1e6). 2. HTX Ventures. (2024, October). 2024 Meme Sector Analysis: From Viral Spread to Ecosystem Beachhead [Article]. 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Richmond Times.[https://richmond.com/life-entertainment/the-rise-the-risks-and-the-rewards-of-meme-coins-in-crypto-culture/article_70c415a9-c27a-57ee-975e-b75f883222b8.html](https://richmond.com/life-entertainment/the-rise-the-risks-and-the-rewards-of-meme-coins-in-crypto-culture/article_70c415a9-c27a-57ee-975e-b75f883222b8.html). 22. Cryptonary Research. (2024, September 17). Cryptonary’s State of the Memecoin Market Report [Report]. Cryptonary.[https://cryptonary.com/research/cryptonarys-state-of-the-memecoin-market-report/](https://cryptonary.com/research/cryptonarys-state-of-the-memecoin-market-report/). 23. James, A. (2024, March 29). Ethereum Co-Founder Vitalik Buterin Would Like to See 'More Good Memecoins Than Bad Ones' [Article]. The Block.[https://www.theblock.co/post/285587/ethereum-vitalik-buterin-memecoins](https://www.theblock.co/post/285587/ethereum-vitalik-buterin-memecoins). 24. Wu Says Blockchain. (2024, November 12). Exclusive Interview with the New Meme King Murad: Stop Trading, Focus on Holding, and Find Memecoins with "Diamond Hands Culture" [Interview]. ChainCatcher.[https://www.chaincatcher.com/en/article/2151591](https://www.chaincatcher.com/en/article/2151591). 25. Chojecki, P. (2024, September 26). Moonshot App: Easy Meme Coin Trading on Your Phone [Article]. PC Crypto.[https://medium.com/pc-crypto/moonshot-app-easy-meme-coin-trading-on-your-phone-531e5196a995](https://medium.com/pc-crypto/moonshot-app-easy-meme-coin-trading-on-your-phone-531e5196a995). 26. Hawk, C. (2024, September 29). How to Buy Meme Coins on Your Phone Using Moonshot App [Article]. Medium.[https://medium.com/@crypto_hawk/how-to-buy-meme-coins-on-your-phone-using-moonshot-app-67bdff84f15f](https://medium.com/@crypto_hawk/how-to-buy-meme-coins-on-your-phone-using-moonshot-app-67bdff84f15f). 27. Kubinec, J., & Albus, J. (2024, June 26). Moonshot is Vertical Integration for Memecoins [Newsletter]. Blockworks.[https://blockworks.co/news/moonshot-vertical-integration-memecoins](https://blockworks.co/news/moonshot-vertical-integration-memecoins). 28. Lyons, G. (2024, July 19). MoonPay is Live on Moonshot [Announcement]. MoonPay Newsroom.[https://www.moonpay.com/newsroom/moonshot](https://www.moonpay.com/newsroom/moonshot). 29. Moonshot Team. (2024). Moonshot Official Documentation [Documentation].[https://moonshot.money/terms](https://moonshot.money/terms) 30. Rizzo, P. (2024, October 10). The Memecoin Supercycle Thesis Is Bitcoin Aligned (and Hilarious) [Article]. Bitcoin Magazine.[https://bitcoinmagazine.com/culture/murads-memecoin-supercycle-bitcoin-aligned](https://bitcoinmagazine.com/culture/murads-memecoin-supercycle-bitcoin-aligned). 31. OKX Learn. (2024, October 10). What is a Memecoin Supercycle: Real or a Reality Check? [Article]. OKX.[https://www.okx.com/learn/what-is-memecoin-supercycle](https://www.okx.com/learn/what-is-memecoin-supercycle). 32. Not Ivy. (2024, October). The Evolution of Memes, the Landscape, and Some of My Own Whimsical Ideas [Article]. Medium.[https://medium.com/@NotIvy/the-evolution-of-memes-the-landscape-and-some-of-my-own-whimsical-ideas-b49a1a66ee30](https://medium.com/@NotIvy/the-evolution-of-memes-the-landscape-and-some-of-my-own-whimsical-ideas-b49a1a66ee30). 33. ShingW.eth. (2024, October). Exploring Meme Coin Mania: Wealth, Ruin, and Lessons from Murad Mahmudov’s Meme Influence and the SHAR Coin Collapse [Article]. Medium.[https://medium.com/shingw-eth/exploring-meme-coin-mania-wealth-ruin-and-lessons-from-murad-mahmudovs-meme-influence-and-the-25c060dceea0](https://medium.com/shingw-eth/exploring-meme-coin-mania-wealth-ruin-and-lessons-from-murad-mahmudovs-meme-influence-and-the-25c060dceea0). 34. Malvania, D. (2025, January 20). Moonshot’s User Base Soars with TRUMP Meme Coin Craze [Article]. The Crypto Times.[https://www.cryptotimes.io/2025/01/20/moonshots-user-base-soars-with-trump-meme-coin-craze/](https://www.cryptotimes.io/2025/01/20/moonshots-user-base-soars-with-trump-meme-coin-craze/). 35. Roush, T. (2025, January 19). Donald Trump Launches $TRUMP Meme Coin—Token Hits $9 Billion Market Cap [News Article]. Forbes.[https://www.forbes.com/sites/tylerroush/2025/01/19/donald-trump-launches-trump-meme-coin-token-exceeds-12-billion-market-cap/](https://www.forbes.com/sites/tylerroush/2025/01/19/donald-trump-launches-trump-meme-coin-token-exceeds-12-billion-market-cap/). 36. Sinclair, S., & Dioquino, V. (2025, January 19). Official Trump Solana Meme Coin Falls as Melania Drops Token of Her Own [Article]. Decrypt.[https://decrypt.co/301756/official-trump-solana-meme-coin-falls-as-melania-drops-token-of-her-own](https://decrypt.co/301756/official-trump-solana-meme-coin-falls-as-melania-drops-token-of-her-own). 37. Lyons, C. (2025, January 19). Whether Trump's Memecoin Pushes Crypto in the 'Right Direction' Remains Unclear [Article]. Cointelegraph.[https://cointelegraph.com/news/donald-trump-memecoin-crypto-path-uncertain-crypto-participants](https://cointelegraph.com/news/donald-trump-memecoin-crypto-path-uncertain-crypto-participants). 38. Leviathan News. (2025, January 20). Trump’s Crypto Playbook: Memes, Millions, and Mayhem Before the Oval Office [Newsletter]. Leviathan News. 39. Weilin. (2025, January 19). Trump is rising, Solana is king, and the president is issuing coins: [Article]. PANews.[https://www.panewslab.com/en/articledetails/xu52ncpi.html](https://www.panewslab.com/en/articledetails/xu52ncpi.html) --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # SOON Network: Extending the SVM beyond Solana > SOON is the first protocol to leverage Decoupled SVM, extending Solana’s execution beyond its native ecosystem and enabling the broader adoption of SVM-based rollups. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-03-03 - Canonical: https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/ - Keywords: crypto, DeFi, zero-knowledge, infrastructure, Solana, Ethereum, Bitcoin, gaming, Infrastructure ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/2c6d67cd92a2.jpg) ## Introduction Blockchain networks have undergone significant architectural advancements to address scalability challenges. Solana has emerged as a high-performance blockchain, leveraging its unique execution architecture to optimize scalability and throughput. Unlike traditional blockchain designs that rely on sequential processing, Solana introduces a parallel execution model facilitated by the Solana Virtual Machine (SVM). The SVM serves as the execution environment for smart contracts and decentralized applications (dApps), enabling the network to handle a significantly higher number of transactions per second (TPS) compared to other blockchain architectures. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/7b698b5d2b2b.jpg) To further extend the capabilities of SVM beyond Solana, SOON Network introduces an SVM-based Layer 2 (L2) that settles on Ethereum while maintaining Solana's execution advantages. SOON bridges the divide across different blockchain ecosystems by extending SVM to major Layer 1 networks, ensuring seamless interoperability, reduced transaction costs, and enhanced developer experience. This report provides an overview of SOON’s architecture, ecosystem, and growth strategy. It explores the advantages of SVM over EVM, the technical advancements powering SOON, and the SOON Big Bang campaign, a long-term incentive program designed to drive ecosystem engagement through partner integrations and NFT utilities. ## Solana’s Modular Approach and the Solana Virtual Machine (SVM) A recent shift towards modular blockchain design has further enhanced Solana’s capabilities. Previously, the Solana Validator Client and the SVM were closely integrated, limiting innovation by requiring changes to be made at a system-wide level. However, the introduction of [SVM API by Anza](https://www.anza.xyz/blog/anzas-new-svm-api) in July 2024 marks a pivotal shift in Solana’s execution environment, allowing developers to decouple the Solana Virtual Machine (SVM) from the validator client (Agave). Building on this advancement, SOON became the first protocol to leverage Decoupled SVM, extending Solana’s execution capabilities beyond its native ecosystem and enabling broader adoption of SVM-based rollups. This modularization allows developers to experiment with, customize, and optimize the execution environment without affecting consensus, networking, or block production mechanisms. Many new projects are now leveraging this flexibility to explore a diverse range of innovations, including: - **Permissioned L1s** that mirror SWIFT’s compliance structure while automating manual processes (e.g., Sphere). - **Decentralized storage solutions** for expanding Solana’s program capacity (e.g., Xandeum). - **EVM and Solana Interoperability**, including Ethereum on Solana, Solana on EVM, and Solana-native rollups (e.g., Ellipsis, Neon, Soon). - **Bitcoin x Solana crossovers**, integrating new cross-chain applications (e.g., Yona, Molocule, Zeus). - **New Validator Clients**, such as Jump’s Firedancer, which was unveiled at Breakpoint and boasts a theoretical maximum throughput of 1,000,000 TPS. - **zkSVMs, rollups, AI-integrated solutions**, and other advanced blockchain paradigms. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/e8e64b938880.jpg) As recently highlighted in this [Solana the Modular](https://members.delphidigital.io/reports/solana-the-modular#conclusions-e5eb) report from Delphi, key advantages of this modular approach include: 1. **Independent Innovation** – Developers can iterate on the SVM without modifying the validator client. 2. **Optimized Performance** – Custom execution environments can be created to suit specific use cases. 3. **Diversity of Implementations** – Multiple SVM variants can emerge, each tailored for different applications such as DeFi, gaming, and AI-driven dApps. 4. **Interoperability Standards** – The rise of diverse SVM versions necessitates new interoperability frameworks. 5. **Enhanced Developer Experience** – Decoupling execution from consensus simplifies smart contract development and deployment. This modular approach, combined with Solana’s execution efficiency, sets it apart from other blockchain networks, particularly those utilizing the Ethereum Virtual Machine (EVM). ## SVM vs. EVM: Architectural and Performance Differences While both the Solana Virtual Machine (SVM) and the Ethereum Virtual Machine (EVM) serve as execution environments for smart contracts, their architectural designs and transaction processing models differ significantly. **1. Execution Model** The EVM operates in a single-threaded environment, processing transactions sequentially. While this ensures security and consistency, it leads to bottlenecks during high transaction volumes, resulting in network congestion and elevated gas fees. The SVM employs parallel execution through its Sealevel engine, allowing multiple non-conflicting transactions to run simultaneously across different cores of validator hardware. This multi-threaded approach enhances scalability and reduces latency, enabling Solana to achieve significantly higher throughput at lower costs. **2. State and Data Management** Ethereum’s account model stores balances and state within individual smart contracts. This creates potential conflicts when multiple contracts attempt to read or modify the same account data concurrently. In contrast, Solana’s explicit state access model requires transactions to specify the accounts they will interact with before execution. This design eliminates conflicts at runtime, allowing independent transactions to be processed simultaneously. **3. Hardware Utilization** The EVM does not fully leverage modern multi-core processors due to its single-threaded nature, leading to underutilization of validator hardware. The SVM is designed to take advantage of multi-core processing capabilities effectively, distributing transaction execution across multiple threads and ensuring optimal hardware scaling. **4. Fee Market Design** Ethereum employs a global fee market, where demand spikes in one sector (e.g., NFT minting) can lead to network-wide gas fee surges, affecting unrelated transactions. This results in high and unpredictable costs for users. Solana, leveraging Sealevel’s parallel processing capabilities, implements localized fee markets. Each smart contract operates independently in terms of fee calculation, preventing congestion in one area from affecting the entire network. This ensures lower and more predictable fees. ## SOON Network: Scaling with SVM L2 SOON (Solana Optimistic Network) is a high-performance SVM Rollup designed to drive mass adoption of blockchain technology by extending Solana’s execution environment to major Layer 1 networks. Unlike traditional Ethereum-based rollups, SOON leverages the Decoupled Solana Virtual Machine (SVM) to optimize execution speed and scalability. It achieves this through a modular rollup framework called the SOON Stack, which enables the deployment of SVM-based Layer 2 chains on any L1. SOON's approach is built on three core components: - **SOON Mainnet** – A general-purpose **SVM L2** that settles on Ethereum. - **SOON Stack** – A modular rollup framework that enables the creation of **SVM-based rollups** on different L1s. - **InterSOON** – A cross-chain messaging protocol that facilitates seamless interoperability between SOON and other blockchain networks. In the later sections, we will explore how SOON combines high-performance execution, interoperability, and scalability to build a unified blockchain ecosystem that removes barriers between different chains. SOON is built around the Super Adoption Stack (SAS), a vision for a fully interoperable blockchain future where all networks can seamlessly communicate. The two fundamental pillars of SAS are: 1. **High-Performance Execution** – Bringing the **Solana Virtual Machine (SVM)** to major L1 ecosystems like **Ethereum, Bitcoin, BNB, and TON** to enhance execution efficiency. 2. **Seamless Interoperability** – Establishing **cross-chain communication** between SVM-based L2 chains and all major L1s to enable frictionless asset transfers and dApp interaction. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/fb7a5a22898b.jpg) The SOON Mainnet and SOON Stack are critical components in achieving this vision, enabling developers to deploy SVM rollups on different L1s while ensuring seamless connectivity across chains through InterSOON. ### SOON Mainnet: The First Decoupled SVM Rollup SOON Mainnet is an L2 that settles on Ethereum, utilizing [Decoupled SVM](https://medium.com/@soon_SVM/technical-deep-dive-the-scheduler-revolution-and-decoupled-svm-architecture-6e3d5f583dbb) as the execution layer. Unlike traditional Ethereum rollups that rely on the EVM, SOON Mainnet uses SVM, enabling unparalleled speed, scalability, and efficiency. - **SVM-Powered Execution** – Faster and more efficient than traditional EVM rollups. - **Interoperability with Ethereum** – Native **ERC-20 <> SPL bridging** for seamless asset transfers. Security is a critical differentiator for SOON compared to traditional SVM-based rollups. According to L2Beat, [SOON is a Rollup](https://l2beat.com/scaling/projects/soon), not a sidechain. Unlike rollups, sidechains need to bootstrap their own security and rely on their own security mechanisms and validator node infrastructure, which may not be as robust as the security of the main chain, especially in the early stages of operation. In the event of a sequencer failure, users can force transactions to be included in the chain by directly sending them to the L1, ensuring continued accessibility and security. While many forked SVM projects replicate Solana’s execution model without adding additional safeguards, [SOON enhances security](https://x.com/soon_svm/status/1882418036021637207) by integrating Merklization and state root verification, which function like blockchain snapshots of account balances, permanently stored on Ethereum. In simple terms, [Merklization](https://docs.soo.network/introduction/merklization) is how SOON structures blockchain data into Merkle trees, allowing efficient and secure verification of transactions and balances. It ensures fraud-proof security, improved scalability, and trustless withdrawals between Layer 2 and Layer 1. This allows users to mathematically verify their funds anytime, eliminating reliance on trust-based security models. - Permanent and verifiable access to transaction history, unlike other SVM projects that impose a 150-slot limitation. - Mathematical proof-based fund verification instead of relying on the rollup’s internal data. - Independent transaction validation via Merkle proofs, ensuring users can verify their balances without exposing others’ data. **SOON’s Core Technical Innovations** 1. **Decoupled SVM**– SOON separates SVM execution from Solana’s native consensus, allowing SVM to be used as a standalone execution layer for rollups. 2. **Merklization** – Uses Merkle Patricia Trees (MPT) to efficiently verify state transitions, aligning with Ethereum’s proof verification model for seamless integration. 3. **Horizontal Scaling** – Enables unlimited scalability by adding more validator nodes, ensuring high throughput and reliability without overloading individual machines. By combining Ethereum’s security and liquidity with Solana’s high-performance execution, SOON Mainnet provides a next-generation Layer 2 experience for both Solana and Ethereum developers. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/4deba5100fa3.png) SOON’s Public Mainnet recently went live, with 20+ ecosystem projects deployed, including the official SOON Native Bridge for Ethereum and InterSOON for Solana and TON. With Round 1 NFT mint raising $22M, details on COMMing SOON NFT Round 2 will be announced soon, offering new benefits for early participants (we will cover more about COMMing SOON NFTs and SOON Big Bang) ### SOON Stack: A Modular SVM Rollup Framework The SOON Stack is a flexible rollup infrastructure that allows developers to deploy SVM-based rollups on different L1s. Chains built using SOON Stack are called SOON Chains, and they retain the benefits of SOON's Decoupled SVM along with SVM's parallel execution capabilities, while maintaining compatibility with Ethereum’s OP Stack. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/1c30dfbb0486.jpg) **Key Features of SOON Stack** - **Multi-L1 Support** – Supports **Ethereum as a settlement layer** and integrates **EigenDA, Celestia, and Avail** for data availability. - **Optimized for Performance** – Uses **Decoupled SVM**, separating execution from Solana’s consensus, reducing unnecessary **data availability costs**. - **Customizable Rollups** – Enables builders to **launch SVM rollups** with fine-tuned parameters for DeFi, gaming, and other applications. ### Use Cases for SOON Stack 1. **AI & DePIN** – SOON Stack enables high-performance execution for DePIN and AI driven applications. For instance, SOON recently [partnered with IoTeX](https://medium.com/@soon_SVM/bringing-ai-depin-innovation-with-iotex-283c6cb7a489), to enable real-time data processing, device-to-blockchain interactions and AI automation at scale. DePIN networks require fast and cost-efficient transaction processing for IoT devices, sensors, and machine learning models, while AI-powered dApps demand low-latency inference and secure data exchange—both of which SOON facilitates through Decoupled SVM and parallel transaction execution. 2. **Financial & DeFi Protocols** – Optimized for **high-volume transactions** with low latency. 3. **Custom Gas Fee Models** – Applications can implement **tailored gas structures**, improving UX. **SOON Stack Adoption & Growth** SOON Stack has already onboarded Cytonic, CARV, and Lucent Network, marking a significant step in expanding the SVM-based rollup ecosystem. These projects leverage SOON’s Decoupled SVM architecture to build scalable, high-performance blockchains: - Cytonic is pioneering multi-VM interoperability, enabling dApps from Solana, Ethereum, and other blockchains to coexist seamlessly. [Cytonic is leveraging Caldera and SOON Stack](https://medium.com/@soon_SVM/soon-x-caldera-x-cytonic-presenting-cytonic-svm-2f348f468ab6) to build their first SVM-based Chain. - [SOON is powering CARV’s SVM chain with SOON Stack](https://medium.com/@soon_SVM/soon-powers-carvs-svm-chain-with-soon-stack-accelerating-ai-driven-innovation-62ad69cde19f). CARV is building an AI-powered data economy chain, integrating trusted execution environments (TEE) and zk-proofs for privacy and security. - Lucent Network (formerly Clover) is introducing an AI-optimized financial and SocialFi ecosystem, and will use [SOON Stack to build an SVM-based AI-driven network](https://medium.com/@soon_SVM/introducing-lucent-network-powered-by-soon-stack-an-evolution-towards-ai-and-svm-7173f6e77066). Additionally, [SOON has partnered with Caldera](https://medium.com/@soon_SVM/soon-x-caldera-unlocking-next-gen-svm-raas-17abe5cb469e), the fastest-growing Rollups-as-a-Service (RaaS) provider, to enable SVM-based rollups. This collaboration makes it easier for projects to launch application-specific SVM chains with one-click deployment and modular execution. By providing a standardized SVM rollup framework, SOON Stack empowers developers to build and scale high-performance Layer 2 chains, facilitating next-generation AI, DePIN, and decentralized financial solutions without the limitations of EVM. ### InterSOON: Enabling Seamless Cross-Chain Communication InterSOON is a cross-chain messaging protocol that enables smooth interaction between SOON Mainnet, SOON Stack, and other L1s. Unlike traditional token bridges that create liquidity fragmentation, InterSOON allows smart contracts and assets to interact natively across multiple chains. **Key Features of InterSOON** - **Unified Messaging Standard** – Eliminates the need for **custom bridges** by enabling **standardized communication**. - **Preserved Liquidity** – Avoids liquidity fragmentation by maintaining **assets in their native form**. - **Improved Performance** – **Decoupled SVM** optimizes cross-chain interactions by removing unnecessary **bridging overhead**. By using Hyperlane as its messaging backbone, InterSOON provides a scalable and trustless communication layer for the next generation of multi-chain applications. ## Launch Mechanism for Community Raise: A New Model for Value Distribution A major challenge in token launches today is the lack of accessibility, fairness, and alignment between projects and their communities. Existing distribution models often favor venture capitalists (VCs) and early insiders, sidelining the very users who contribute to network growth. This disconnect results in poor long-term alignment, speculative cycles, and reduced community engagement. A Community NFT Mint-based launch (such as the recent COMMing SOON NFT round by SOON, which we will discuss more closely in the later sections) provides a permissionless, transparent, and incentive-driven mechanism for community raises while ensuring value distribution back to investors. This approach integrates customizable pricing, flexible vesting, and NFT-bound token rights, creating a sustainable and decentralized token launch framework. ### How Community NFT Mint Enables Fair and Efficient Capital Raising Unlike traditional token launches that prioritize exclusive allocations, the Community NFT Mint model offers a transparent and adaptable mechanism for raising capital while ensuring that community participants receive long-term incentives and governance influence. **1. Tokenized Participation Through NFTs** - Instead of direct token sales, participants mint NFTs that encapsulate token rights, vesting conditions, and additional benefits. - These NFTs represent customized token access, allowing users to select terms based on their risk appetite. - Investors can trade these NFTs, providing a liquid market for vested token rights before the actual token unlock. - This model minimizes regulatory complications and the associated legal risks. **2. Configurable Pricing and Vesting Structures** - Multi-tier pricing models enable users to choose between immediate liquidity at a higher price or longer vesting at discounted rates. - This eliminates forced price distortions caused by fixed unlock schedules and reduces sell pressure post-launch. - Fair entry conditions ensure that retail users and large investors can both access token supply under transparent terms. **3. Community-First Fundraising Model** - No private rounds or backdoor deals—every allocation is open to the community. - Smart contracts govern issuance, vesting, and token distribution, ensuring trustless execution. - Eliminates pre-market speculation by structuring release schedules that incentivize long-term participation rather than quick exits. ### Mechanism for Distributing Value Back to Investors To create sustainable incentives and ensure long-term alignment with investors, the Community NFT Mint model integrates multiple value-return mechanisms, reducing the risks typically associated with early-stage participation. **1. Revenue-Generating Utility for Community NFTs** - Projects can attach additional benefits to minted NFTs, such as:Fee-sharing from platform revenueGovernance participation and voting weight - This transforms the Community NFT Mint into an asset that accrues value beyond token unlocks, ensuring ongoing investor engagement. **2. Dynamic Unlocks Based on Network Growth** - Token release schedules can adapt to network adoption metrics, preventing premature liquidity events. - Community NFTs encourage investors to support ecosystem growth rather than engage in short-term speculation. **3. Embedded Referral and Reputation Systems** - Participants who drive adoption through referrals and organic contributions can earn additional token incentives. - Ranking-based reward mechanisms (e.g., Kaito-style rankings) further align power users with project success. The Community NFT Mint model presents a transformative approach to capital raises, integrating liquidity, flexibility, and decentralization into token issuance. By enabling NFT-bound token rights, dynamic vesting models, and ongoing value accrual mechanisms, this system ensures long-term alignment between projects, investors, and communities. This model is not just a fundraising mechanism but a foundation for sustainable token economies, ensuring that projects maintain decentralization, mitigate early speculation risks, and foster long-term adoption. In an industry where liquidity and alignment are critical factors for success, Community NFT Mint stands as a scalable, inclusive, and market-responsive innovation for the next generation of Web3 projects. Learn more about [Community NFT Mint: A New Paradigm of Token Launch](https://x.com/soon_svm/status/1891661418090606885). ## SOON Big Bang Season 1 & COMMing SOON NFT Utilities The SOON Big Bang program is a long-term ecosystem growth initiative designed to reward both COMMing SOON NFT holders and general users who interact with projects within the SOON ecosystem. With over 12% of the total $SOON supply allocated to the Battle Pass Pool (for NFT holders) and the Airdrop Pool (for general users), this program provides a structured reward mechanism that incentivizes active participation. Season 1 of the SOON Big Bang started in the 3rd week of Jan, introducing tasks from 9 ecosystem projects, including wallets, bridges, DEXs, lending platforms, and consumer applications. Users can head to the discover [SOON dashboard](https://discover.soo.network/) connect their wallets, complete on-chain tasks, and earn points to climb the Big Bang Leaderboard, securing $SOON token rewards. The COMMing SOON NFT Mint Round 1 officially concluded with an impressive $22,000,000 raised, highlighting strong demand and confidence in the SOON ecosystem. A total of 3,015 participants joined the mint, including notable venture firms such as @hack_vc, @anagramxyz, @hypersphere_, @ABCDELabs, @snzholding, @geek_cartel, @ark_stream, @pakafund, @MH_Ventures, @Web3Port_Labs, @IDGCV, and more. COMMing SOON NFT holders gain significant advantages, including a point boost and access to the Battle Pass Pool, allowing them to earn up to 50% more $SOON tokens over multiple seasons. The Battle Pass Pool provides additional rewards for SOON Squad and SOONer NFT holders, with multipliers based on NFT tiers You can learn more about it in [this blog](https://x.com/soon_svm/status/1881534401227731313) ## Conclusion and Final Thoughts According to the recent [developer report by Electric Capital](https://www.developerreport.com/developer-report?s=solana-was-the-1-ecosystem-for-new-devs-in-2024), there are over 24K active monthly developers. Solana is the #1 ecosystem for new developers, with over 7.5K new developers exploring Solana and the SVM stack. This is the first year since 2016 that any ecosystem has attracted more new developers than Ethereum. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/8b5ef5056fe4.jpg) As blockchain ecosystems evolve in 2025, developers essentially have three major options to choose from: - SVM - EVM - Move EVM will be by far the most competitive, with ecosystems like Monad, Berachain, Base, MegaETH, and many new EVM L2s emerging. If an existing EVM ecosystem fails to meet a team's needs, migration to another EVM ecosystem will be relatively seamless, leading to intense competition among EVM environments. Since developer experiences across these ecosystems will be similar, differentiation will largely come from ecosystem support, liquidity, and community strength. While cross-deploying across multiple EVM environments is possible, managing multiple deployments increases complexity and often results in a loss of product focus. As this landscape unfolds, SVM and Move will have an edge in developer retention and talent density due to fewer competing options. Developers within these ecosystems will have stronger incentives to remain, fostering deeper expertise and innovation. Since EVM is the most mature ecosystem, it may present fewer opportunities for new and groundbreaking advancements, leading to slower relative progress. In contrast, SVM and Move ecosystems have an inherent technical edge in 2025, benefiting from less competition, higher talent density, and stronger incentives for developers. However, their long-term success hinges on one critical factor: how quickly SVM and Move ecosystems can enhance their developer experience—from contract-level improvements to better read-level and core protocol optimizations. [As 0xMert_, co-founder of Helios Labs, recently pointed out:](https://x.com/0xMert_/status/1873501815985020946) > *“If Solana can improve its developer experience by 2-5x in 2025, its growth could be 10x relative to other ecosystems.”* Currently, there are over 500 full-time developers building on the SVM stack, with 3.3K+ monthly active developers, 54K+ total repositories, and 15M+ commits. As developer adoption accelerates, SVM’s growing ecosystem is emerging as a key player in blockchain innovation. This growth highlights the increasing demand for SVM and its potential upside as a scalable, high-performance stack. ![](https://shoal.xyz/research/writing/soon-network-extending-the-svm-beyond/img/7214d3647df3.jpg) This brings us to SOON Network, which has a strong edge for developers, users, and enterprises looking to deploy app-specific chains in 2025. Appchains are emerging as the preferred solution for enterprise applications requiring controlled access and high scalability, particularly in finance and gaming. They offer: - Seamless performance and enhanced security - Cost-efficiency, customization, and experimentation - Greater flexibility in governance, consensus mechanisms, and economic models Unlike general-purpose L2s, appchains rely on a Layer-1 chain for security and network operations, avoiding competition for storage and computation with other applications. This allows developers to extract greater value while maintaining control over their execution environment. With rising demand for scalable, app-specific chains, projects like SOON Network are positioned at the forefront of modular execution, enabling Solana’s SVM to serve as a dedicated execution layer across multiple L1s. By leveraging Decoupled SVM, Merklization, and Horizontal Scaling, SOON enhances scalability, efficiency, and interoperability. As SVM adoption grows, SOON’s modular framework positions itself as a key player in blockchain scaling, bridging Solana’s speed with Ethereum’s security and fostering a more interconnected, efficient multi-chain ecosystem. Additionally, InterSOON messaging infrastructure enhances interoperability and composability between appchains, reinforcing the SVM stack as a viable framework for next-generation blockchain scaling. --- *Not financial or tax advice. The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* *Disclosures. All posts are the author's own, not the views of their employer. This post has been sponsored by SOON Network. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- --- # Indirect Impacts of Chain Abstraction > In this article, we analyse how Chain Abstraction unlocks capital efficiency across ecosystems, enhances gaming economies, and drives the evolution of venture investment toward consumer-focused dApps. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-02-27 - Canonical: https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/ - Keywords: stablecoins, agent wallets, crypto, DeFi, solvers, yield, infrastructure, Solana, Ethereum, Base, Bitcoin, gaming, Infrastructure ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/17cf9d67f815.jpg) ## Introduction If the future of finance is digital, why does using DeFi still feel like navigating a 1990s dial-up connection? The dream of a seamless, blockchain-powered financial system is often disrupted by reality—switching wallets, bridging assets, handling gas fees, and ensuring compatibility across chains. Users face friction at every step, developers are forced to optimize for siloed ecosystems, and capital remains fragmented across multiple chains, reducing overall efficiency. The promise of Web3 remains, but its usability problems prevent it from achieving true mainstream adoption. That’s where chain abstraction comes in. Much like cloud computing abstracted away the complexity of managing physical servers, chain abstraction removes blockchain’s biggest UX hurdles, ensuring seamless interaction between chains without requiring users to manage the complexities beneath the surface. Just as streaming services like Netflix don’t require users to know which cloud provider they run on, Web3 applications of the future won’t require users to select networks or manually bridge assets. The implications of this transformation are vast. A fully realized chain abstraction model would shift the focus from infrastructure-centric blockchain competition to application-centric user experiences. Capital efficiency would improve, development barriers would lower, and decentralized finance (DeFi), gaming, and digital identity solutions would experience massive usability gains. This report explores how chain abstraction is reshaping the way users and developers interact with web3, covering the core technological advancements making it possible, the industry’s indirect impacts, real-world implementations—including Particle Network’s central role—and the potential challenges ahead. ## Core Concepts of Chain Abstraction The fundamental goal of chain abstraction is to eliminate the need for users and developers to think about chains at all. Instead of dealing with wallet fragmentation, gas fees in multiple tokens, and liquidity silos, chain abstraction creates a unified layer that makes blockchain interactions seamless. Below, we break down the key components that enable this vision. ## 1) Universal Accounts: A Single Balance Across Chains ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/05f2891c13bb.jpg) In the current Web3 landscape, users often need separate accounts for each chain—an Ethereum account for ERC-20 tokens, a Solana account for SPL tokens, a Bitcoin account for BTC, and so on. This fragmentation creates an overwhelming user experience, requiring individuals to track multiple balances, manage various private keys, and remember which assets are stored where. Universal Accounts solve this by providing a single address and balance that works across all chains. Users sign in once and can transact across different blockchains without needing to switch networks or manually move funds. A few months ago, Particle Network released [UniversalX](https://universalx.app/user/x/0xyanshu?inviteCode=MVZTWW)—the first on-chain chain-agnostic trading platform—marking the first mainnet implementation of Universal Accounts. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/7eacd0834b50.jpg) As you can see, despite holding funds across multiple chains, the magic of UAs is that they appear as a single combined balance. When making a transaction, the system automatically aggregates the value from all chains into a single transaction—eliminating the need to manually bridge assets or manage gas fees. **How It Works:** Universal Accounts are powered by ERC-4337-based smart wallets, which allow on-chain accounts to function like programmable smart contracts. These wallets abstract private key management, making multi-chain interactions seamless. **Example in Action**: Imagine Alice, an everyday DeFi user. She has ETH on Ethereum but wants to farm yield on Avalanche. Instead of bridging manually, paying gas in AVAX, and signing multiple approvals, she simply interacts with a unified interface that routes her assets optimally without requiring her to understand the underlying mechanics. ## 2) Universal Liquidity: Eliminating the Need for Bridging One of the biggest hurdles in Web3 today is **liquidity fragmentation**. Every blockchain operates its own isolated pool of assets, requiring users to **bridge manually** if they want to interact with different ecosystems. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/b0783bc657a4.png) Universal liquidity enables seamless asset movement without manual bridging. **How It Works:** Rather than requiring users to hold multiple assets across different chains, universal liquidity bundles cross-chain capital into shared liquidity pools that applications can tap into automatically. Think of it as automating the bridging process — moving funds/liquidity automatically from multiple origin chains to meet the conditions of a destination transaction (like buying an NFT on Avalanche while holding assets on Base and Polygon). **Example in Action**: Bob wants to buy an NFT listed on Solana, but all his capital is on Ethereum and Base. Instead of bridging ETH to Solana manually, universal liquidity solutions execute the transaction in the background alongside the NFT purchase, abstracting away the complexity. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/320ccba42c95.jpg) > *Source : Particle Network Docs.* Projects like Particle Network implement this by aggregating liquidity across chains via a system of Bunder Nodes and Liquidity Providers (illustrated above), ensuring the best execution without requiring user intervention. ## 3) Universal Gas: Any Token, Any Chain One of the most common frustrations in Web3 is [gas fees](https://blog.millionero.com/blog/crypto-transaction-fees-your-2024-guide/)—not just their high cost, but the complexity of managing them. Today, if a user wants to interact with a DeFi app on Polygon, they must first acquire MATIC for gas, even if they already hold USDC or ETH. Universal Gas fixes this by enabling transactions to be paid in any token. **How It Works:** - A middleware layer (e.g., Particle Network’s Paymaster) converts gas payments on behalf of the user, allowing transactions to be executed with any asset the user holds. - This removes the need for acquiring chain-specific gas tokens and improves the user experience drastically. **Example in Action**: A user swaps USDC for SOL on a DEX but only has USDC. Instead of being forced to acquire SOL for gas, they simply approve the transaction, and gas is deducted from their USDC balance. ## 4) Intent-Based Transactions: The Future of Execution At the heart of chain abstraction is a shift toward intent-based transactions—where users define the outcome they want, and solvers compete to execute the transaction in the most efficient way. **How It Works:** Instead of submitting rigid transaction orders (e.g., "swap 1 ETH for 2000 USDC on Uniswap"), users submit high-level intents (e.g., "I want the best price for swapping 1 ETH to USDC"). The solver network finds the best route and executes the transaction without requiring the user to manage the details. **Why This Matters:** - Reduces failed transactions (users don’t have to set slippage manually). - Optimizes execution (solvers compete for the best execution route across chains). - Eliminates network switching (transactions can route across multiple chains seamlessly). **Example in Action:** Vitalik wants to swap **ETH for SOL**, but instead of choosing the best DEX manually, an **intent-based system** finds the optimal path (e.g., swapping ETH to USDC on Ethereum, bridging to Solana, and converting to SOL—all in one seamless transaction). In crypto, intents and chain abstraction are often used interchangeably or in overlapping contexts, but they serve distinct purposes. - **Intents** are specifications of what a user wants to achieve without concerning themselves with how to achieve it. For example, a user may declare, “Swap 5 ETH for BTC.” Intents focus on outcomes, leaving the implementation to intermediaries like solvers or fillers. - **Chain Abstraction (ChA),** on the other hand, focuses on hiding the complexities of interacting with multiple blockchains and improving the overall experience for users and developers. It ensures users and developers don’t need to navigate the intricate details of bridging assets, managing gas fees, or accessing fragmented liquidity pools. When intents span multiple chains, they start to resemble chain abstraction by abstracting the execution complexity. For example, a user intent to swap tokens across two chains involves interoperability—a cornerstone of chain abstraction. This is where the two concepts overlap, and intents become a building block for comprehensive chain abstraction solutions. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/e29e8a372b14.jpg) Intents and chain abstraction both find utility in enabling smoother multichain experiences, but their implementation diverges into two categories: **[Orchestration Solutions](https://blog.particle.network/chain-abstraction-vs-intents/)**[and](https://blog.particle.network/chain-abstraction-vs-intents/)**[Comprehensive Solutions.](https://blog.particle.network/chain-abstraction-vs-intents/)** Intent-centric systems seem very promising for UX but face some critical challenges that must be addressed to reach their full potential, such as reliance on centralized servers and solvers, gas costs and mempool limitations, lack of gasless transactions, and scalability bottlenecks. ## Transformational Impact of Chain Abstraction The evolution of blockchain has always been constrained by its user experience (UX) problem. While early adopters have managed to navigate the complexities of multiple wallets, bridges, and gas fees, the next wave of Web3 users will demand a seamless experience comparable to Web2 applications. The friction involved in managing blockchain infrastructure continues to be a major barrier to adoption. Chain abstraction is not just an incremental improvement but a fundamental paradigm shift that stands to impact users, developers, financial institutions, gaming ecosystems, and even venture capital markets. By eliminating blockchain silos and enabling seamless cross-chain interactions, chain abstraction has the potential to reshape industries, making blockchain technology invisible to the user while maintaining its decentralized benefits. ## Users: A Frictionless Web3 Experience For the average user, engaging with blockchain-based applications remains a cumbersome process. Performing a simple cross-chain trade on a decentralized exchange (DEX) requires switching networks, manually approving transactions, paying gas in different tokens, and often bridging assets across incompatible ecosystems. These complications drive users away, forcing them to rely on centralized solutions that offer a smoother experience. Chain abstraction eliminates these barriers, allowing users to focus on the functionality of applications rather than the mechanics of blockchain infrastructure. One of the most immediate benefits of chain abstraction is the consolidation of wallet experiences. Instead of requiring separate wallets for Ethereum, Solana, Avalanche, and Bitcoin, users will be able to interact with all networks from a single universal account. This means that an individual could hold ETH, SOL, AVAX, and BTC within one wallet interface, without needing to manage separate key pairs or manually switch networks. Particle Network’s Universal Accounts are a prime example of this innovation, leveraging ERC-4337 smart contract wallets to provide a unified experience across chains. Another game-changer is seamless asset movement without network switching. Traditionally, a user looking to swap USDC from Ethereum into SOL on Solana would need to go through a multi-step process: bridge USDC to Solana, wait for confirmation, then execute a swap on a Solana-based DEX. With chain abstraction, these steps happen entirely in the background. The system determines the best execution path and completes the swap in a single interaction, optimizing for speed, cost, and efficiency. Solutions like LI.FI’s cross-chain liquidity routing and LayerZero’s messaging layer are already working to create more seamless cross-chain interactions, which can be leveraged by chain abstraction protocols to abstract away bridging and provide users with a seamless experience without worrying about manual bridging. Gas fees, another major friction point, are also abstracted away through universal gas solutions. Today, a user wanting to interact with an Arbitrum-based NFT marketplace must first acquire ETH to pay for gas, even if they already have stablecoins or other assets. Chain abstraction removes this requirement by allowing gas fees to be paid in any token, from any chain. Particle Network’s Universal Gas Paymaster enables transactions where users can pay gas with any asset they hold, making the blockchain interaction as seamless as a credit card transaction. By abstracting away blockchain complexities, Web3 applications will finally offer an experience comparable to Web2 platforms. This shift is essential for mainstream adoption, where users expect financial applications, social platforms, and gaming experiences to work without the technical burdens of blockchain mechanics. Imagine a Web2 social media platform integrating crypto tipping, where users send payments across chains without ever seeing a “bridge transaction.” Chain abstraction makes this not just possible, but inevitable. ## Developers: “Eating [Less] Glass” The complexity of blockchain development has long been a barrier to broader innovation. Traditionally, developers must decide which blockchain ecosystem to build on, requiring them to tailor their applications to the specific architecture, tooling, and constraints of that network. If they later decide they want users from different chains to access their application and tap into the liquidity, they would need to deploy it again on those chains. This means that a project launching on Ethereum cannot simply extend to Solana or Avalanche without significant additional development work, forcing teams to maintain separate codebases and navigate different smart contract languages, consensus mechanisms, and execution environments. Chain abstraction removes these constraints, allowing developers to build once and deploy in one place while onboarding users from any ecosystem (even if users have funds on other chains) without redeploying their application elsewhere, fundamentally changing how applications interact with blockchain infrastructure. Particle Network’s modular execution layer facilitates this approach by automating cross-chain function calls. For example, a lending protocol that launches on Ethereum could automatically enable borrowing and lending functionalities across Optimism, zkSync, and Arbitrum, without requiring separate implementations. Liquidity fragmentation has historically forced DeFi projects to launch on multiple blockchains in order to capture users. Today, a decentralized exchange (DEX) like Uniswap must deploy independent liquidity pools on Ethereum, Polygon, and Base—all of which operate in silos, leading to inefficiencies and price disparities. Chain abstraction eliminates this problem by aggregating liquidity across all chains, ensuring that users always get the best execution, regardless of where the trade originates. LI.FI’s liquidity aggregation protocol and Socket’s Modular Order Flow Auctions (MOFA) are already working to unify liquidity across fragmented ecosystems, ensuring that developers can provide deeper, more efficient markets without needing to deploy across multiple networks manually. For developers new to Web3, wallet integration and smart contract deployment have traditionally been steep learning curves, requiring an understanding of chain-specific architectures, gas optimizations, and security best practices. Chain abstraction lowers these barriers by providing developer tooling that abstracts the complexity of managing different blockchain environments. Additionally, account abstraction significantly enhances the developer experience by eliminating the constraints of traditional externally owned accounts (EOAs). With ERC-4337 smart wallets, applications can offer programmable, policy-based execution, enabling use cases like social logins, subscription-based payments, and automated transaction execution. This means that a developer building a subscription-based NFT membership service could allow users to pay gas in any token they hold, while also setting up recurring payments—features that would be impossible with today’s standard EOA wallets. The industry is rapidly embracing smart accounts as the new standard for user-friendly, programmable wallets. With account abstraction gaining traction, key developments are accelerating this shift. One of the most exciting releases is Ethereum’s upcoming upgrade, EIP-7702, set to launch in the coming weeks on Holesky and Sepolia as part of the Pectra hardfork. This upgrade marks a pivotal moment in Ethereum’s journey toward account abstraction, a breakthrough designed to make onchain experiences smoother, smarter, and more accessible. Specifically, EIP-7702 enables Externally Owned Accounts (EOAs) to use smart contract account features. The existing AA standard, ERC-4337, has one limitation: it requires new wallet creation because it’s not backward compatible with EOAs. EIP-7702 was designed to complement ERC-4337, making it easier for account abstraction features to reach users. It removes this limitation without deeper changes to the EVM’s consensus logic: - Uses existing wallets. - Requires no new accounts or migrations. - Fits perfectly with ERC-4337’s infrastructure. Existing EOAs simply delegate smart contract logic via a delegation designator. The convergence of universal smart contract execution, aggregated liquidity, and wallet abstraction means that developers can focus on building great applications rather than navigating blockchain-specific constraints. A new wave of applications will emerge where developers no longer have to decide whether to build on Ethereum or Solana—they will simply build for Web3 as a whole. ## DeFi & Financial Markets: Capital Efficiency Unlocked Decentralized finance (DeFi) has revolutionized global financial markets by enabling permissionless lending, borrowing, trading, and yield generation. However, liquidity fragmentation across chains remains a major bottleneck, forcing users and protocols to operate in silos, reducing capital efficiency, and creating inconsistent pricing across networks. Chain abstraction directly addresses these inefficiencies by aggregating liquidity across ecosystems, enabling seamless cross-chain transactions, and optimizing capital flows in ways that were previously impossible. One of the most significant barriers in DeFi today is that liquidity is isolated on different chains, leading to fragmented markets. A lending protocol like Aave currently needs to deploy separate instances on Ethereum, Avalanche, and Polygon, each with independent liquidity pools. This segmentation forces users to manually bridge assets to access lending opportunities on different networks, adding complexity and risk. Particle Network’s Universal Liquidity Layer eliminates this problem by allowing users to borrow from lenders across multiple chains without needing to manually move funds. Instead of being confined to a single chain’s liquidity, borrowers can tap into cross-chain lending pools where execution is handled seamlessly in the background. Similarly, cross-chain trading remains one of the most frustrating experiences for users, as decentralized exchanges (DEXs) still operate in silos. Today, if a trader wants to swap ETH on Ethereum for SOL on Solana, they need to either use a centralized exchange (CEX) like Binance or manually bridge their assets through third-party protocols, incurring fees and delays. Chain abstraction removes this friction by allowing DEXs to aggregate liquidity across all chains, meaning users can trade assets natively without switching networks. LI.FI, Connext, and Across Protocol are already working on routing cross-chain trades in the background, ensuring that users get the best execution without needing to interact with a bridge. Beyond trading and lending, yield optimization is another major pain point that chain abstraction solves. Today, yield aggregators like Yearn Finance or Beefy Finance must maintain separate strategies for each blockchain, and users need to manually move their funds to chase the best returns. With intent-based transactions and automated execution, DeFi users can deposit assets once, and solvers will automatically route them to the most profitable opportunities across chains. Particle Network’s Universal Yield Aggregation Model aims to achieve exactly this, allowing users to earn yield without needing to manage chain-specific deployments or bridge assets. Another challenge in DeFi is that gas fees create an unpredictable cost structure, making transactions expensive and sometimes unprofitable. When using any assets on a chain, let’s say you're sending an ERC-20 token $X from Ethereum, you would have to pay gas in the native currency of that chain (in this case, ETH). Many users abandon transactions as they might not have any liquid native tokens to pay for the gas. Universal Gas Paymaster solutions remove this complexity by allowing users to pay transaction fees in any token, making DeFi interactions more seamless. This is especially important for institutional players who need cost predictability before deploying large amounts of capital into on-chain strategies. Universal Gas Paymasters are also useful to networks or dApps that plan to implement gasless transactions to bolster user acquisition. This concept known as “sponsored transaction fees”, depicted in the graphic below, is a surefire way to support user growth by lowering barriers and switching costs for prospective users. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/da544f3c6bff.jpg) *Source: Visa, Crypto Thought Leadership* Chain abstraction doesn’t just improve the DeFi experience for individual users—it also makes decentralized finance more attractive to institutions. Many hedge funds, asset managers, and corporate treasuries have been hesitant to allocate capital to DeFi due to the operational complexity of managing assets across multiple chains. With chain abstraction, institutions can interact with DeFi through a unified execution layer, reducing onboarding friction and ensuring that liquidity is always deployed in the most optimal way. By removing liquidity fragmentation, optimizing trade execution, and enabling cross-chain lending and yield strategies, chain abstraction fundamentally enhances the capital efficiency of DeFi. This transformation ensures that DeFi can compete with traditional financial markets in terms of liquidity depth, execution speed, and user experience—unlocking a new era of frictionless, interoperable financial markets. ## Gaming & Web3 Experiences: The Multi-Chain Metaverse The gaming industry has long been at the forefront of technological innovation, from the early days of online multiplayer games to the rise of esports and virtual economies. However, blockchain gaming has yet to achieve its full potential due to network isolation, where in-game assets, currencies, and economies are trapped within specific chains. This lack of interoperability forces players to navigate complex bridging mechanisms, discouraging mainstream adoption. Chain abstraction provides a solution by enabling seamless multi-chain gaming experiences, allowing players to interact with blockchain-based assets without worrying about the underlying network. A major limitation in Web3 gaming today is that in-game assets such as NFTs and tokens are confined to individual chains. If a player acquires an NFT skin in a Solana-based RPG, they cannot easily transfer or sell it on an Ethereum-based marketplace without going through multiple bridging steps. This limits the liquidity and utility of digital assets across different ecosystems. Particle Network’s Universal Accounts and Cross-Chain Liquidity Layer solve this by ensuring that NFTs and tokens can be accessed across multiple chains without manual transfers, effectively turning the blockchain infrastructure into an invisible backend layer. This would allow a player to use an NFT avatar acquired on Immutable X in a game hosted on Polygon without needing to migrate assets manually. Gas fees and transaction approvals are another major friction point in blockchain gaming. Traditional gamers are accustomed to instant transactions and seamless in-game purchases, whereas blockchain games often require multiple wallet approvals, network switches, and gas fee payments before executing simple actions. ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/022d84e15d9e.gif) Source: [https://x.com/MadMaxx_eth/status/1864701042463568327](https://x.com/MadMaxx_eth/status/1864701042463568327) Even though most of the limitations related to transaction approvals are being tackled by Account Abstraction, chain abstraction protocols are building on top of that functionality with added benefits to provide users with a unified, seamless experience. With universal gas solutions, gamers will no longer need to hold a chain’s native token to pay for transaction fees. For example, a player could buy an in-game weapon on an Arbitrum-based NFT marketplace using USDC without needing ETH for gas fees. This level of abstraction mirrors the one-click purchase experience of traditional online stores, making blockchain gaming more appealing to mainstream users. Interoperability is also key for gaming studios looking to build multi-chain experiences. Today, game developers must choose a single blockchain to build on, locking their user base into that ecosystem. This restricts growth potential and forces developers to either maintain multiple versions of their game across different chains or rely on complex bridging solutions. Chain abstraction allows game studios to develop chain-agnostic games, meaning that a player on Ethereum, Solana, or Avalanche could interact within the same in-game economy without friction. UniversalX and LayerZero’s messaging layer are already exploring solutions that allow game assets and currencies to move freely between different blockchain ecosystems, enabling a truly multi-chain metaverse. The impact of chain abstraction on Web3 gaming extends beyond asset transfers—it also enhances player ownership and monetization models. With traditional games, digital assets are locked within centralized servers, giving players no true ownership of their in-game items. Blockchain gaming introduces player-owned economies, where assets are verifiably scarce and tradeable. However, without chain abstraction, these assets remain stuck within their original ecosystem, limiting their long-term value. By ensuring cross-chain compatibility for in-game economies, chain abstraction allows players to take their assets wherever they want, reinforcing the idea of true ownership in digital spaces. The future of Web3 gaming hinges on removing friction and providing experiences that rival traditional gaming platforms. Players should be able to log in, trade, and play without ever thinking about blockchains, gas fees, or network switches. Chain abstraction ensures that blockchain remains invisible to the end user, allowing game developers to focus on storytelling, gameplay, and community-building rather than blockchain infrastructure. By abstracting complexity, Web3 gaming can compete with traditional AAA titles, opening the door for mainstream adoption and ushering in a new era of player-driven economies. ## Venture Investment: Less Infrastructure Spending, More Consumer dApps ![](https://shoal.xyz/research/writing/the-indirect-impacts-of-chain-abstraction/img/b9352cc5c22a.png) The Web3 ecosystem has witnessed an influx of venture capital (VC) funding, with investors pouring billions into blockchain infrastructure, decentralized applications, and digital assets. However, despite growing institutional interest, capital inefficiencies and fragmented liquidity across multiple chains have hindered large-scale adoption by traditional finance (TradFi) players. Chain abstraction changes this dynamic by removing operational barriers, optimizing capital deployment, and making blockchain-based financial instruments more attractive to institutions. One of the primary hurdles for institutional investors in Web3 has been navigating multi-chain liquidity and asset management. Unlike traditional financial markets, where capital can be freely moved between asset classes with minimal friction, blockchain investments are currently fragmented across multiple Layer 1 and Layer 2 ecosystems. An investment firm looking to deploy capital into on-chain yield opportunities must allocate funds across Ethereum, Solana, Avalanche, and other networks separately, often requiring manual bridging, network-specific custody solutions, and different execution strategies for each ecosystem. Particle Network’s Universal Liquidity Layer addresses this by allowing institutions to deploy capital seamlessly across chains, ensuring that liquidity is always optimally allocated without requiring manual intervention. Institutional investors also require cost predictability and risk mitigation strategies, both of which are difficult to manage in today’s gas fee-intensive and execution-uncertain blockchain environment. The high volatility in transaction costs—especially on congested networks like Ethereum—makes on-chain financial strategies unpredictable and difficult to scale. Chain abstraction resolves this by introducing gas abstraction models, such as Universal Gas Paymasters, that allow institutions to execute transactions without holding chain-native assets. This means that a hedge fund could rebalance a DeFi portfolio across multiple chains while paying gas fees in USDC or other stable assets, creating a more predictable and controlled operational environment. Another major benefit of chain abstraction is enhanced trade execution and settlement for on-chain financial products. Institutional investors looking to enter DeFi have traditionally faced liquidity fragmentation, front-running risks, and inefficient execution paths. Today, executing a large trade on-chain often leads to slippage, price impact, or failed transactions due to network congestion. With intent-based transaction execution models, such as those pioneered by CoW Protocol and LI.FI, institutions can express an execution goal (e.g., swap $10M in ETH to USDC at the best available price), and a network of solvers competes to fulfill that order under optimal conditions. This prevents MEV exploitation, reduces execution risk, and ensures institutional-grade trade settlement. Beyond trade execution, institutional adoption of DeFi lending and staking has been constrained by the complexity of managing multiple yield sources across different chains. Today, a fund seeking liquid staking rewards on Ethereum (Lido), Solana (Marinade), and Cosmos (Stride) must manually allocate assets, bridge funds, and monitor yield fluctuations. Chain abstraction enables cross-chain yield aggregation, where liquidity providers can automatically access the highest-yielding opportunities across multiple networks without shifting assets manually. Particle Network’s intent-based execution ensures that capital is automatically deployed where it generates the highest return, providing institutions with a frictionless experience for maximizing yield. From a regulatory perspective, chain abstraction also reduces compliance risks associated with cross-chain transactions. Many institutions are reluctant to interact with DeFi due to unclear reporting requirements and the difficulty of tracking on-chain activity across multiple networks. With a unified settlement layer, compliance teams can monitor all blockchain activity through a single interface, making it easier to manage risk exposure, conduct audits, and report transactions according to regulatory requirements. As crypto-native venture capital firms continue to allocate funding toward infrastructure projects, chain abstraction is emerging as a top investment priority. In Q4 2024, crypto VC funding surged by 46% quarter-over-quarter, with cross-chain infrastructure projects receiving a significant portion of that capital. Investors are betting that seamless interoperability will be a defining trend in the next phase of Web3 growth, unlocking greater efficiency, capital mobility, and institutional participation. Ultimately, chain abstraction transforms blockchain from a fragmented set of ecosystems into a unified, seamless financial infrastructure, making it far more appealing to institutional investors, TradFi players, and hedge funds. By eliminating capital inefficiencies, reducing operational complexity, and optimizing trade execution, chain abstraction positions Web3 as a viable alternative to traditional financial markets—not just for retail users, but for global financial institutions looking to allocate capital in the digital economy. ## Challenges & Considerations While chain abstraction has the potential to transform blockchain infrastructure by integrating liquidity, enhancing transaction efficiency, and improving overall system usability, its widespread adoption presents several critical challenges. The transition toward a fully abstracted blockchain ecosystem introduces challenges in security, decentralization, solver network dynamics, regulatory compliance, and long-term economic sustainability. Effectively addressing these concerns is imperative to ensuring that chain abstraction solutions maintain their trustless, permissionless, and scalable nature while preserving the fundamental principles of blockchain technology. ## Security Risks and MEV Exploitation One of the most critical challenges facing chain abstraction is security. Today, bridges are among the most vulnerable components in blockchain ecosystems, with over [$2.5 billion lost to bridge hacks](https://defillama.com/hacks) in the past two years. Since chain abstraction inherently relies on **cross-chain**execution and liquidity routing, the security risks associated with bridges and interoperability solutions remain a primary concern. The introduction of intent-based transactions and solver networks also presents a new attack surface. While solvers compete to fulfill transactions under optimal conditions, malicious solvers could attempt to manipulate pricing, frontrun user intents, or extract MEV (Maximal Extractable Value) at the expense of users. In traditional blockchains, MEV exploitation has led to significant inefficiencies, including sandwich attacks, priority gas auctions, and trade slippage. If solver networks are not properly designed, they could become centralized rent-seeking entities, capturing excessive value and harming users rather than benefiting them. To mitigate these risks, encryption mechanisms such as private mempools, zero-knowledge proofs, and fair order sequencing must be implemented within solver networks. For example, CoW Protocol’s batch auction model minimizes MEV by executing transactions in a way that reduces adversarial trading strategies. Similarly, Particle Network’s cross-chain execution framework incorporates cryptographic proofs to ensure that solvers operate transparently and cannot manipulate order flow. ## Decentralization Trade-Offs Another major consideration in chain abstraction is the potential centralization of execution networks. Currently, many cross-chain execution systems depend on a small set of relayers, validators, or sequencers to facilitate transaction settlement. If too few entities control the infrastructure required for cross-chain execution, chain abstraction risks becoming a permissioned, gatekept ecosystem rather than a truly decentralized protocol. For example, LayerZero, one of the most widely adopted cross-chain messaging protocols, relies on a “Relayer & Oracle” system, where trusted entities relay messages between chains. While this ensures efficiency, it also creates potential centralization risks. Optimistic execution models, where transactions are executed and later verified on-chain, offer a potential solution. EigenLayer’s shared security model and Babylon’s Bitcoin-secured validation are promising developments that could distribute trust across a larger network of validators, reducing reliance on any single entity. The balance between efficiency and decentralization is an ongoing debate. While centralized solvers and execution networks can enhance speed and reliability, they introduce points of failure and governance risks. Open, permissionless solver networks must be designed to prioritize censorship resistance while maintaining high execution efficiency. ## Regulatory and Compliance Uncertainty As chain abstraction enables cross-chain execution at scale, regulatory bodies will likely introduce new oversight measures to ensure compliance with AML (Anti-Money Laundering) and KYC (Know Your Customer) requirements. Financial regulators may view intent-based transactions and solver-driven execution models as opaque financial instruments, particularly if users interact with multiple chains through a single execution layer without clear jurisdictional oversight. A major regulatory concern is liability in cross-chain execution failures. If a user submits an intent and a solver fails to execute it correctly, who is responsible for the lost funds? Unlike centralized exchanges (CEXs), where regulations mandate protections for failed transactions, decentralized solver networks operate in a gray area with no clear legal framework. Additionally, as capital moves frictionlessly between chains, regulators may seek to enforce cross-border transaction tracking, which could impact the privacy-first nature of blockchain transactions. Protocols implementing compliance-friendly solutions such as zero-knowledge compliance proofs or opt-in regulatory frameworks may gain favor with institutional investors while preserving the core ethos of decentralization. Polygon’s AggLayer is exploring solutions that allow institutions to interact with DeFi in a way that aligns with compliance requirements, signaling how chain abstraction may need to balance privacy, transparency, and regulatory oversight. ## Economic Viability and Long-Term Sustainability The sustainability of chain abstraction models is another crucial factor. Many chain abstraction solutions rely on intent-based execution networks, where solvers compete to execute transactions. However, the economic incentives that drive solver participation must be carefully designed to ensure long-term sustainability. If solvers receive insufficient rewards for executing transactions, network participation may decline, reducing execution quality and efficiency. Conversely, if solver networks are over-incentivized, they may extract excessive fees, leading to inefficiencies and rent-seeking behavior similar to Ethereum’s MEV crisis. A well-calibrated fee mechanism—such as dynamic solver rewards that adjust based on execution demand—could help maintain a competitive and sustainable ecosystem. Additionally, the cost of running cross-chain infrastructure must be factored into long-term incentive models. Running secure, decentralized execution nodes requires significant resources, and networks must ensure that the revenue generated from transaction execution outweighs operational costs. The rollout of modular blockchains and shared security models, such as Celestia’s data availability layer, could reduce the overhead required to maintain solver networks, ensuring their long-term viability. ## The Road Ahead: Addressing Challenges to Unlock Chain Abstraction’s Full Potential Despite these challenges, the industry is making rapid strides toward mitigating risks and ensuring that chain abstraction remains decentralized, secure, and economically sustainable. Innovative projects are already implementing cryptographic safeguards, open solver networks, and compliance solutions to strike the right balance between efficiency and trustlessness. As with any paradigm shift, the road to full adoption will require continuous iteration, security improvements, and thoughtful economic design. If the industry can successfully address these concerns, chain abstraction has the potential to be one of the most transformative innovations in Web3, creating a future where users, developers, and institutions can interact with blockchain seamlessly—without ever thinking about the underlying complexity. ## The Future of Web3 is Invisible The blockchain industry is at a pivotal moment. While decentralized technologies have unlocked permissionless finance, digital ownership, and new economic models, they remain trapped behind complexity. The need for bridging assets, switching networks, managing multiple wallets, and understanding gas fees has left Web3 fragmented, slowing mainstream adoption. Chain abstraction changes this paradigm by making blockchain infrastructure invisible, allowing users to interact seamlessly across chains without ever knowing which network they’re on. Much like how cloud computing abstracted away server management, chain abstraction eliminates blockchain silos, ensuring that applications—not chains—become the focal point of user experience. As this technology matures, Web3 will no longer be a space dominated by protocol-specific barriers but rather a unified ecosystem where users, developers, and institutions can interact effortlessly. Universal Accounts, seamless liquidity routing, intent-based transactions, and gas abstraction will ensure that blockchain complexity is hidden beneath an intuitive, frictionless layer—ushering in the next era of mass adoption. From an investment standpoint, venture capital is already positioning itself for this shift, with billions flowing into cross-chain infrastructure, modular execution layers, and liquidity aggregation protocols. Institutional players are eyeing the potential of unified financial markets, where capital moves as efficiently on-chain as it does in traditional markets. Meanwhile, gaming, social platforms, and DeFi protocols are preparing for a world where users no longer have to think about which chain they’re interacting with—they simply engage with the application. If chain abstraction solutions like Particle Network are successful, the concept of “using a blockchain” will become obsolete. In the same way that today’s internet users don’t need to know whether their favorite website is hosted on AWS or Google Cloud, future Web3 users won’t need to care whether they’re interacting on Ethereum, Solana, or Avalanche. Blockchain will disappear into the background, leaving behind only the applications, financial tools, and digital experiences that users want. Chain abstraction goes beyond reducing friction; it aims to create **seamless user experiences**. While some argue that it abstracts risk by limiting users' ability to assess individual chains, this isn’t entirely true. Most users don’t want to analyze every chain’s risks—they simply want to use applications efficiently. For those who do, chain abstraction remains a **UX feature**, not a restriction. Users can still conduct due diligence and maintain control if they choose. The only question now is: who will lead this transition? The race toward full chain abstraction is already underway, and the projects that solve these challenges first will define the future of Web3. ## References 1. AhnLab Blockchain Company. (2024, July 24). Account Abstraction vs. Chain Abstraction [Blog Post]. Medium.[https://medium.com/@AhnLabBlockchainCompany/blog-account-abstraction-vs-chain-abstraction-1b76879c2333](https://medium.com/@AhnLabBlockchainCompany/blog-account-abstraction-vs-chain-abstraction-1b76879c2333). 2. AJC. (2024, June 21). Understanding Particle Network: A Comprehensive Overview [Research Report]. Messari.[https://messari.io/report/understanding-particle-network](https://messari.io/report/understanding-particle-network). 3. Bedawala, M., Ozbay, M., & Gu, C. (2025, February 7). What is Account Abstraction? Exploring new techniques for blockchain payment processing [Technical Report]. Visa Crypto Thought Leadership.[https://usa.visa.com/solutions/crypto/rethink-digital-transactions-with-account-abstraction.html](https://usa.visa.com/solutions/crypto/rethink-digital-transactions-with-account-abstraction.html). 4. Cano, C. M. (2024, June 11). Web3 Fragmentation: How Big Is It, and How to Solve It? [Research Report]. Particle Network Blog.[https://blog.particle.network/quantifying-the-impact-of-chain-abstraction-exposing-web3s-inefficiencies](https://blog.particle.network/quantifying-the-impact-of-chain-abstraction-exposing-web3s-inefficiencies). 5. Cano, C. M. (2024, October 21). The Synergy of Chain Abstraction and Account Abstraction [Article]. Particle Network Blog.[https://blog.particle.network/dynamics-chain-abstraction-account-abstraction](https://blog.particle.network/dynamics-chain-abstraction-account-abstraction). 6. Cano, C. M. (2024, November 15). The First Frontier for Chain Abstraction: The Crypto Economy [Article]. Particle Network Blog.[https://blog.particle.network/the-first-frontier-for-chain-abstraction-the-crypto-economy/](https://blog.particle.network/the-first-frontier-for-chain-abstraction-the-crypto-economy/). 7. Cano, C. M. (2025, January 15). UniversalX: Chain Abstraction Through Universal Accounts [Case Study]. Particle Network.[https://blog.particle.network/universalx-achieves-chain-abstraction/](https://blog.particle.network/universalx-achieves-chain-abstraction/). 8. Chainlink. (2024, January 12). What Is an Oracle in Blockchain? [Educational Article]. Chainlink.[https://chain.link/education/blockchain-oracles](https://chain.link/education/blockchain-oracles). 9. Chiplunkar, A., & Gosselin, S. (2024, February 15). Introducing the CAKE Framework: Chain Abstraction Key Elements [Technical Report]. Frontier Research.[https://frontier.tech/the-cake-framework](https://frontier.tech/the-cake-framework). 10. Imajinl, & Timofeev, P. (2024, May 30). The 0-1 of Chain Abstraction: A Primer on the Missing Piece to Achieving Mainstream Blockchain Adoption [Research Report]. Shoal Research.[https://www.shoal.gg/p/the-0-1-of-chain-abstraction](https://www.shoal.gg/p/the-0-1-of-chain-abstraction). 11. Konstantopoulos, G., & Kilbourn, Q. (2023, June 1). Intent-Based Architecture and Their Risks [Research Report]. Paradigm.[https://www.paradigm.xyz/2023/06/intents](https://www.paradigm.xyz/2023/06/intents). 12. MPlankton. (2025, January 16). Some Thoughts on Account Abstraction (Pros and Cons) [Discussion Post]. Reddit.[https://www.reddit.com/r/MPlankton/comments/160pu87/some_thoughts_on_account_abstraction_pros_and_cons](https://www.reddit.com/r/MPlankton/comments/160pu87/some_thoughts_on_account_abstraction_pros_and_cons). 13. NEAR Protocol. (2024, February 15). Unlocking Web3 Usability with Account Aggregation [Blog Post]. NEAR Developers.[https://pages.near.org/blog/unlocking-web3-usability-with-account-aggregation/](https://pages.near.org/blog/unlocking-web3-usability-with-account-aggregation/). 14. Pandey, I. (2025, January 16). Pengyu Wang Reveals the Secrets to Particle Network's Rapid Success [Interview]. HackerNoon.[https://hackernoon.com/pengyu-wang-reveals-the-secrets-to-particle-networks-rapid-success](https://hackernoon.com/pengyu-wang-reveals-the-secrets-to-particle-networks-rapid-success). 15. Thorn, A., & Parker, G. (2025, January 15). Crypto & Blockchain Venture Capital Q4 2024 [Research Report]. Galaxy.[https://www.galaxy.com/insights/research/crypto-blockchain-venture-capital-q4-2024/](https://www.galaxy.com/insights/research/crypto-blockchain-venture-capital-q4-2024/). 16. Timofeev, P. (2024, August 7). Particle Network: The Chain Abstraction Layer [Article]. Shoal Research.[https://www.shoal.gg/p/particle-network-the-chain-abstraction](https://www.shoal.gg/p/particle-network-the-chain-abstraction). --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Particle Network. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Sonic SVM: The HyperGrid Future, Powering TikTok App Layer > How Sonic SVM is Scaling TikTok’s Billion-User Reach with its Gaming Infrastructure on Solana. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2025-01-30 - Canonical: https://shoal.xyz/research/writing/sonic-svm/ - Keywords: crypto, infrastructure, Solana, Ethereum, gaming, Infrastructure ![](https://shoal.xyz/research/writing/sonic-svm/img/29854d0bc92f.jpg) MirrorWorld, through its gaming SVM (Solana Virtual Machine) Sonic, has emerged as a pioneer in bridging Web2 and Web3 gaming by onboarding more than 2 million users through TikTok's ecosystem. Launched in March 2024, Sonic has achieved what few Web3 projects have managed to achieve: genuine mainstream user adoption through its TikTok-native game SonicX, which provides a seamless entry point for traditional social media users into Web3 gaming. Just as OP Stack enabled Coinbase's Base and other major platforms to build on Ethereum, Sonic is doing the same for Solana - but with a gaming-first approach. Through its HyperGrid framework, Sonic is enabling major gaming studios and platforms to launch their own customized Solana chains while maintaining the security of the base layer. Sonic is the gateway via which thousands of Web3 games enter the ecosystem. Combining Solana’s speed with the customizability of Sonic, which is building the SVM L2 for gaming apps, It is able to achieve such a feat. Sonic uses the Hypergrid framework, which is a scaling framework that is a key piece of technology in Sonic’s modular future, which enables Sonic to have optimized functionality and performance. It does all these by allowing the customization of chains’ features and advanced data types. The modular architecture of Sonic allows developers to easily customize the perfect blockchain economy while achieving Solana's fast throughput. HyperGrid is a scaling framework for SVM ecosystem. Sonic provides natively integrated tools for payment and settlement infrastructure, as well as user engagement tools necessary to build a successful Web3 game. Key benefits that make creators and developers build on Sonic include : - Sonic gives users an insanely fast on-chain gaming experience powered by the Solana virtual machine(SVM) at a minimal cost. - Sonic allows for the execution of transactions without redeploying Solana programs and accounts, as it benefits from the base layer liquidity and services. - Sonic provides native composable gaming primitives and extensible data types based on the Unity ECS framework on-chain. - Sonic provides sandbox utilities for developers to build their business logic. - Sonic provides in-house infrastructure for growth, traffic, payment, and game settlement. ## The Social Platform Playbook: From TON to TikTok TON proved that embedding Web3 into trusted platforms works. Through mini-apps within Telegram's messaging ecosystem, games like Hamster Kombat (300M users) and Notcoin (150M users) reached millions of users who had never touched crypto before. The key insight from this is that users will embrace Web3 when it feels like a natural extension of their daily experience rather than a separate crypto product. Sonic takes this proven model to TikTok – a platform with over 1 billion users and unmatched engagement metrics. Where TON focused on Telegram's messaging-first audience, SonicX targets TikTok's entertainment-native users, who are already primed to discover and engage with new content. ## SonicX ![](https://shoal.xyz/research/writing/sonic-svm/img/8458c4d76a69.jpg) TikTok, the popular social media platform for creating, sharing, and discovering short videos, boasts over 1 billion users as of 2024. Known for its unmatched reach and engagement, TikTok offers incredible potential for amplifying content. SonicX, a TikTok mini-application launched by Sonic, leverages this platform to expand the reach of Web3 gaming to TikTok's vast and engaged audience. This strategy not only enhances the visibility of Web3 games but also provides significant returns on investment for Sonic and its gaming partners by capitalizing on TikTok's extensive user base. ## Why TikTok Mini Apps The vision behind launching SonicX on TikTok is to cultivate a Web3 gaming layer that’s accessible and engaging for mainstream audiences. TikTok’s popularity among KYC-verified users offers unique insights into user preferences, creating a powerful environment for Sonic’s games to gain traction. Through a well-curated user flow, SonicX is building a path for new Web3 gamers to easily explore and enjoy blockchain-powered games, seamlessly integrating with their existing TikTok experience. This strategy - meeting users on their preferred platform rather than asking them to venture into unfamiliar territory - mirrors the proven TON's success strategy while targeting a much larger opportunity. TikTok's billion-plus users and unmatched engagement metrics offer the potential for Web3 gaming to finally reach true mainstream adoption. ## Introducing SonicX: The Hub for TikTok Web3 Gaming [SonicX](https://sonicx.app/click) is the cornerstone of the TikTok initiative, bringing games directly to users and setting an example of what’s possible within a TikTok Mini App. It links the TikTok credentials to crypto wallets and simplifies the onboarding process, making it easy for users to access rewards and engage with on-chain activities without leaving TikTok. This streamlined user flow positions SonicX as the go-to hub for Web3 games on TikTok, offering users a quick and intuitive way to explore blockchain gaming. ![](https://shoal.xyz/research/writing/sonic-svm/img/840c3f2d0a1a.jpg) Sonic’s Web3 applayer, SonicX, reached a major milestone of 1 million KYC-verified users on November 7, 2024, and now has over 2 million users, marking a pivotal achievement in Web3 adoption through TikTok. This milestone underscores Sonic’s commitment to building robust infrastructure and a user-friendly distribution platform. Through SonicX, the TikTok native game built on Sonic SVM, users can easily discover and interact with a wide range of Web3 games, all within the familiar environment of TikTok. SonicX team fully utilized account abstraction, creating a seamless, simplified onboarding for non crypto-native users. On the backend, a Solana wallet is automatically generated - but for users they do not need to leave the TikTok app, logging in with their TikTok account to play the games offered on SonicX. *"Achieving 1 million KYC-verified users is a testament to Sonic’s dedication to bridging the gap between mainstream social media and Web3. SonicX was designed with accessibility and engagement in mind, and we’re proud to have created an experience that brings the benefits of blockchain technology to a large, active audience on TikTok."*said Chris Zhu, Co-founder and CEO of Sonic. The Applayer’s unique features, including an aggregation page for Web3 games, an interactive leaderboard for SonicX’s flagship tap-to-earn game, and a task page where users can complete activities for rewards, have all contributed to this substantial growth. These tools foster a rich, rewarding environment for users, positioning Sonic as a leader in both Web3 gaming and social media engagement. With this milestone, Sonic SVM reinforced its commitment to innovation and user engagement, paving the way for a broader adoption of Web3 and decentralized technologies. Sonic continues to build upon this success, with further plans to enhance the Applayer’s capabilities and integrate additional applications that empower users in the Web3 space. ## Strategic Partnerships and Growth Capitalizing on this growth, Sonic has landed its first major gaming partnership with [Mahjong Verse](https://x.com/SonicSVM/status/1860142018783248506) (formerly Mahjong Meta). Backed by prominent investors Dragonfly and Folius, Mahjong Verse's decision to build on Sonic signals a growing confidence in TikTok as a viable Web3 distribution channel. Mahjong Verse will be prominently featured on SonicX's game discovery page, serving as a blueprint for how traditional games can successfully transition to Web3 while maintaining their core appeal. Through SonicX's user-friendly features, including: - A simple tap-to-earn game mechanism that makes blockchain interaction intuitive - A centralized hub for discovering and engaging with Web3 games - A comprehensive task system where users complete challenges to earn points. - Interactive leaderboards that drive engagement "Our partnership with Mahjong Verse represents a significant step forward in our mission to make Web3 gaming accessible to mainstream audiences," says Chris Zhu, CEO at Sonic. "By combining our technical infrastructure with their innovative gameplay, we're creating new opportunities for TikTok users to engage with blockchain gaming in a seamless, user-friendly way." This collaboration showcases the potential of Sonic's two-pronged approach: robust technical infrastructure through Sonic SVM, paired with frictionless distribution through the SonicX platform. For traditional game studios watching from the sidelines, it offers a compelling roadmap for entering Web3 without sacrificing mainstream appeal. But Sonic isn't stopping at gaming. Sonic recently announced a strategic partnership with [Injective](https://x.com/injective/status/1867222911775350914?s=46&t=TZ1i1XyU98L7Fmh0MYZviw) to build a cross-chain Smart Agent Hub. This collaboration connects Solana and Injective ecosystems, enabling AI agents to operate seamlessly across both chains. By leveraging Sonic's HyperGrid technology with Injective's powerful WASM-based blockchain, they're creating an infrastructure that could reshape how AI agents interact with blockchain games and applications. This hints at a more significant shift in how the industry thinks about blockchain adoption. The "if you build it, they will come" era of Web3 might end. Instead of asking users to leave their comfort zones, why not bring Web3 to platforms where billions already spend their time? It's still in the early days, but the strategy is worth watching. If Sonic can continue converting TikTok's massive user base while attracting more established studios, they might have cracked the code that's eluded Web3 gaming for years: genuine mainstream adoption without the usual blockchain learning curve. ## Why Sonic is the "OP Stack of Solana" The rise of Layer 2 solutions has transformed blockchain scalability. On Ethereum, OP Stack emerged as the definitive solution for enterprises building their own chains, powering Coinbase's Base, Zora, and dozens of other platforms. Each of these chains maintains Ethereum's security while optimizing for specific use cases - from NFT marketplaces to social platforms. Sonic is bringing this same transformative potential to Solana, but with key architectural differences, making it uniquely powerful for gaming applications. Sonic’s distinctive edge comes from combining mainstream user accessibility with powerful blockchain infrastructure. But why an L2 on Solana? Part of the “innovation” behind Solana’s architecture is its memory-mapped file storage vs. the traditional storage trie with key-value mapping (Ethereum et al.), which means no global state trie and instead a flat structure of accounts. This, plus the account ownership model, allows Sealevel to process transactions in parallel. Then, looking at it from first principles, the need for an L2 or a rollup on Solana stems at the account level (not globally) — meaning when we get hotspots (due to Solana’s flat state model). For example, an on-chain market maker doesn’t want to compete with priority fees on the L1 just to land a transaction in time, nor should a game have to spend more to record the state of a game — since this would lead to the business not being profitable. Thus, moving the accounts of a DeFi protocol to a rollup or that of a game would make sense. With Sonic SVM, This is enabled by Hypergrid, a scaling framework on Solana that employs a multi-grid approach where each grid operates semi-autonomously while anchored to the Solana mainnet for consensus and finality. Sonic’s transactional model is specifically designed to meet the needs of gaming, enabling high-frequency, low-latency interactions essential for in-game events, player actions, and state updates. Sonic offers native composable gaming primitives and extensible data types directly based on the Unity entity component system (ECS) framework. This framework is a data-oriented framework that is compatible with game objects. It scales the processing performance, enabling experienced creators to build more ambitious games with an unprecedented level of control and determinism. Although the Sonic protocol is known for its gaming potential, it can still be used to develop decentralized applications (DeFi) and physical infrastructure networks (DePIN). While Sonic's initial focus is gaming - evidenced by its success with TikTok integration - its infrastructure extends beyond games. The protocol can support various decentralized applications (DeFi) and physical infrastructure networks (DePIN), similar to how OP Stack evolved beyond its initial use cases. This positions Sonic not just as a gaming platform but as a fundamental piece of Solana's scaling solutions. For Web3 gaming to work on TikTok's scale, you need infrastructure designed specifically for that challenge. This is where HyperGrid, Sonic's scaling framework, plays a crucial role. Just as OP Stack provides the technical foundation for Base and other Ethereum L2s, HyperGrid enables TikTok-scale gaming on Solana. ## What are Hypergrids? Hypergrid is a rollup scaling and orchestration framework for dedicated Solana virtual machine ecosystem rollup operators. It utilizes state compression and Byzantine Fault Tolerance (BFT) to achieve potentially infinite transaction throughput by enabling horizontal scaling across multiple grids, exemplified by Sonic, a gaming-specific grid that settles on Solana. Solana’s main strength lies in composability, where one application can easily integrate with another app using the same shared ledger. Sonic aims to ensure an atomic state synchronization strategy between Solana L1 and Hypergrid. A key feature of HyperGrid is **atomic interoperability**. Hypergrid is designed to be interoperable with Solana as it implements an interoperability interface that allows for wholly encapsulated programs on Solana to delegate execution to*grids* orchestrated by Hypergrid. This approach has some benefits, including: - It creates a single source of truth for all programs running on Solana. - It facilitates the delegation of program computation to hypergrid. - It enables rollups to benefit from the Base layer's services and liquidity. ![](https://shoal.xyz/research/writing/sonic-svm/img/ccf975d8bbbf.jpg) Hypergrid has two core components which enable it to work : - **Grids**- Grids are configurable SVM rollups for optimized performance. - **Hypergrid Shared State Network(HSSN)** - This is an interoperability layer for ***grids,*** and it serves as a consensus layer that seeks to securely roll up state transitions to Solana. ## How HyperGrid Powers TikTok-Scale Gaming The real innovation in HyperGrid comes from how it handles the massive amount of data and transactions that social platform gaming generates. Rather than trying to put everything directly on Solana's mainnet, HyperGrid uses *compressed accounts* - a way of storing game data that's both secure and efficient. Think of it like this: every action in a TikTok game - whether it's scoring points, earning rewards, or updating leaderboards - is represented as a compressed account. These accounts are programmable, meaning games can customize how they work, but they don't take up expensive blockchain space. Instead, HyperGrid uses *concurrent Merkle trees* to track all these actions efficiently. ### Compressed Accounts When a TikTok user plays a game on SonicX, each of their actions is represented as a compressed account in Sonic's rollup system. These accounts, implemented through program-derived addresses (PDAs), are fully programmable and customizable while being orders of magnitude more efficient than traditional on-chain storage. Instead of maintaining expensive account tables with exact addresses, Sonic's architecture only needs to track the deterministic inputs used for account derivation - a perfect match for high-frequency gaming interactions. In Sonic's implementation, each account is uniquely identifiable through its cryptographic hash in the state tree. When players trigger state changes - whether that's updating scores, collecting rewards, or modifying game assets - these changes propagate through the hash chain, ensuring data integrity. Under the hood, RPC nodes index these compression programs and maintain the concurrent Merkle tree structure, enabling games to efficiently read from and write to this compressed state without sacrificing security. This architecture is what allows SonicX to support millions of concurrent user interactions while maintaining Solana-level security guarantees. Every gaming action, from the smallest score update to complex multi-step transactions, is represented as a compressed leaf in the state tree, with only the 32-byte root hash stored on-chain. It's this technical foundation that makes TikTok-scale Web3 gaming not just possible, but economically viable. ![](https://shoal.xyz/research/writing/sonic-svm/img/a6c19974223c.jpg) ### Concurrent Merkle Trees Traditional Merkle trees have been a cornerstone of blockchain technology, providing an efficient way to verify data in peer-to-peer networks. They work like a pyramid of hashes: at the bottom, you have individual transaction hashes (leaf nodes), which pair up to form branches, ultimately combining into a single root hash at the top. Imagine four players making moves simultaneously (transactions A, B, C, and D). Each action gets its own hash (Hash A through D). These hashes pair up - A with B, C with D - creating intermediate branches (Hash AB and CD). These branches then combine to form a final root hash (Hash ABCD), which serves as a cryptographic fingerprint of all the gaming activity. But traditional Merkle trees face critical limitations when dealing with TikTok's volume. In high-throughput environments like Solana, validators receive updates rapidly — often multiple changes within the same slot. Traditional trees process these changes in series, meaning each subsequent update could fail as it invalidates the previous root hash and proof. ![](https://shoal.xyz/research/writing/sonic-svm/img/dc56680d5412.jpg) This is where Sonic's concurrent Merkle trees shine. Instead of processing changes one by one, they maintain a smart "changelog buffer" on-chain. Think of it as a high-speed memory system that tracks recent changes, their root hashes, and proofs. When multiple players take actions in the same slot, this buffer serves as a source of truth, allowing up to maxBufferSize simultaneous updates to the same tree. For TikTok gaming, this means thousands of players can interact simultaneously without transactions failing. ### Practical Implementation in Sonic In Sonic's protocol, every gaming interaction is stored as a leaf in this concurrent Merkle tree structure. Whether earning points, updating leaderboards, or collecting rewards, each action becomes part of the state tree. But here's the efficiency gain: instead of storing every piece of data on-chain, only a compact 32-byte root hash needs to be stored. The system uses zero-knowledge cryptography to compress the validity proofs of all these gaming actions into a tiny 128-byte proof. This architectural choice is what enables Sonic to handle TikTok's massive scale while maintaining Solana's security guarantees. Games can process thousands of player actions per second, all while keeping blockchain storage costs minimal and verification efficient. ![](https://shoal.xyz/research/writing/sonic-svm/img/8c3916623706.jpg) ## Building on Sonic SVM Developers interested in launching their games can do so on TikTok via SonicX, which offers a robust infrastructure to make it happen. With Sonic Origin and Sonic Frontier networks available, games can be deployed easily through the guides. Sonic framework supports wallet integrations, like **OKX**, **Backpack**, and **Nightly Wallet**, ensuring users have seamless access to in-game assets and blockchain functionality. Sonic provides good infrastructure for developers who plan to deploy apps via Sonic on tiktok, some of the support Sonic provides are : - **Network Support**: Easily deploy games on Sonic networks, with specific guides for Solana-based developers. - **Embedded Wallet Connection**: Integrate wallet connections via Sonic embedded H5 iframe solution. - **Mobile Optimization**: SonicX is optimized for mobile, ensuring the majority of users enjoy an effortless experience. ## Campaigns and Promotions for Sonic Games on TikTok To accelerate adoption and support games launching on its platform, Sonic has rolled out several key initiatives. - The [Sonic Odyssey](https://odyssey.sonic.game/task/game-venture) campaign integrates new games into its incentivized testnet, giving developers immediate access to over 2 million active users, along with dedicated PR and social media exposure. - On the marketing front, Sonic is heavily investing in TikTok's ecosystem, combining targeted advertising with strategic influencer partnerships. This two-pronged approach helps games reach both casual players and dedicated Web3 users. - To incentivize early adoption, Sonic has also created exclusive prize pools using Sonic Rings, rewarding users who discover and engage with new games through the TikTok platform. ## Building Solana's Application Layer What started as a solution for TikTok gaming is evolving into something much broader. Just as OP Stack grew beyond Base to power diverse applications on Ethereum, Sonic is emerging as a fundamental piece of Solana's application layer. The recent partnership with Injective to build a cross-chain Smart Agent Hub demonstrates this evolution – where gaming is just the first of many use cases. This expansion mirrors an important pattern in blockchain infrastructure. TON began by powering simple Telegram mini-apps but grew into a complete ecosystem. Similarly, Base started as Coinbase's L2 but now supports everything from NFT marketplaces to DeFi protocols. Sonic is following this trajectory, but with a crucial difference: it's building with social platform integration as a core feature, not an afterthought. The staking ecosystem provides early validation of this broader vision. Through partnerships with Solayer and Adrastea, Sonic has accumulated over [$140 million](https://app.solayer.org/dashboard/delegate) worth of staked SOL, becoming the largest actively validated service (AVS) on Solayer. This demonstrates how Sonic's infrastructure can extend beyond gaming to support fundamental blockchain services. Looking ahead, the launch of the $SONIC token further accelerates this expansion. With 57% of the supply allocated to community and ecosystem development, Sonic is building an economic model that incentivizes social platform integration and technical infrastructure development. This dual focus—making blockchain accessible through platforms like TikTok while providing robust technical infrastructure—positions Sonic uniquely in the Web3 landscape. Think of a small game studio launching its first Web3 title on SonicX. Or a DeFi protocol scaling effortlessly with Sonic’s HyperGrid framework. Or even a TikTok creator using $SONIC rewards to build a stronger connection with their audience. ## What's Next for Sonic The Web3 gaming landscape has seen many ambitious projects, but adoption has remained elusive. TON showed the first glimpse of a solution through Telegram mini-apps, proving that bringing Web3 to existing social platforms could work. Sonic took this insight further, targeting TikTok's billion-plus users instead of Telegram's messaging-first audience. With over 2 million KYC-verified users, partnerships (like Mahjong Verse and Injective) and Sonic's TikTok-first strategy have validated this approach. The platform's success demonstrates that Web3 adoption doesn't require users to leave their comfort zones—instead, blockchain functionality can be seamlessly integrated into platforms they already use daily. Like how OP Stack evolved from powering Base to enabling a whole ecosystem of applications, Sonic is expanding its reach. The recent partnership with Injective to build a cross-chain Smart Agent Hub hints at this broader vision - where gaming is just one of many applications running on Sonic's infrastructure. This two-pronged approach - social platform integration paired with robust technical infrastructure - positions Sonic uniquely in the Web3 landscape. While other chains struggle with the gaming trilemma of speed, cost, and decentralization, Solana's core architecture gives Sonic a natural advantage. Games can tap into Solana's sub-second finality and negligible fees while maintaining decentralization - crucial factors for any mainstream gaming application. Web3 gaming proved the perfect testing ground, demanding both technical excellence and mainstream appeal. As traditional platforms explore Web3, they all face the same challenge: maintaining a seamless user experience while adding blockchain functionality. Sonic's approach of meeting users where they are, built on Solana's robust infrastructure, may well be the blueprint others follow. ### FAQs **Q: Can game developers access end users’ TikTok usernames, follower counts, IP addresses, and other data?** A: Developers can obtain users' TikTok usernames with user authorization. For other data, please refer to the TikTok API documentation. IP addresses can be obtained through landing pages directly. **Q: How is user session data stored? Can TikTok games support an offline earnings feature like some Telegram games do?** A: User session data is managed based on the app's setup and API capabilities. Offline earning features depend on specific game configurations and API integrations. **Q: Can game developers monetize through in-app purchases? Is there a system similar to Telegram Stars (purchasable with Apple Pay in fiat) in TikTok?** A: Monetization through in-app purchases can be optimized by using Pixel for tracking and reporting data. **Q: Can game developers monetize through in-app advertising? Which platform or tool should they use?** A: Yes, developers can monetize through in-app advertising, typically by integrating with AdSense or similar ad networks. **Q: Can TikTok end users invite friends to the game via TikTok DM? Can game developers track referrer and referee data?** A: Users can share the game through third-party MMP platforms, which can generate links with attribution tracking. Additionally, Google Analytics can generate UTM links for tracking shares, or specific invite codes can be used for tracking. Multiple solutions are available to track referral data. Thanks for reading Shoal Research! Feel free to share it. It justifies our weeks of effort :) ## References 1. Sonic SVM tops $50M in Solana staking, announces new partnerships. Cointelegraph. Retrieved from [https://cointelegraph.com/news/sonic-svm-tops-50m-solana-staking-new-partnerships](https://cointelegraph.com/news/sonic-svm-tops-50m-solana-staking-new-partnerships) 2. Introducing Hypergrid Framework - the Technology Behind Sonic SVM. Sonic SVM blog. Retrieved from [https://blog.sonic.game/introducing-hypergrid-framework---the-technology-behind-sonic-svm](https://blog.sonic.game/introducing-hypergrid-framework---the-technology-behind-sonic-svm) 3. State Compression. Solana Official Documentation. Retrieved from [https://solana.com/docs/advanced/state-compression](https://solana.com/docs/advanced/state-compression) 4. Merkle Tree in Blockchain( Part 5- Blockchain Series). Techskill Brew. Retrieved from [https://medium.com/techskill-brew/merkle-tree-in-blockchain-part-5-blockchain-basics-4e25b61179a2](https://medium.com/techskill-brew/merkle-tree-in-blockchain-part-5-blockchain-basics-4e25b61179a2) 5. What are Merkle Trees? Alchemy. Retrieved from [https://docs.alchemy.com/docs/what-are-merkle-trees](https://docs.alchemy.com/docs/what-are-merkle-trees) 6. Introducing Sonic. Official Documentation. Retrieved from https://docs.sonic.game/ 7. ECS for Unity. Unity Official Documentation. Retrieved from [https://unity.com/ecs](https://unity.com/ecs) --- ***Not financial or tax advice.** The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been created sponsored by Sonic Protocol. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Jito Restaking Strategies: Optimizing Yield within the Solana Ecosystem > An exploratory deep dive on the Jito (Re)staking Ecosystem and the emerging DeFi opportunities around it. - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-01-27 - Canonical: https://shoal.xyz/research/writing/jito-restaking-strategies/ - Keywords: crypto, DeFi, restaking, liquid staking, yield, privacy, security, infrastructure, Solana, Ethereum, data, gaming ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/bdabadf87e65.png) *A big thanks to [@tradetheflow_](https://x.com/tradetheflow_) for his valuable contribution to putting together this report.* ## Introduction Since its launch in November 2022, Jito has consistently pursued its vision of building the leading liquid staking service on Solana. Through relentless efforts from the team and a strong long-term vision, Jito has grown from near zero in TVL in January 2023 to become the largest protocol by TVL on Solana, with over $3.54 billion in TVL, representing around 32% of Solana’s total TVL of $10.73b. On top of that, Jito also played a key role in the rebirth of Solana by rewarding its core users with one of the largest airdrops in Solana’s history. This happened at a time when it was needed the most—following the FTX debacle and when the consensus thought that Solana was a dead chain. Today, Jito continues to be at the forefront of technological innovation on Solana and is once again introducing a new key product that could bring the chain a step closer to its end goal: Jito (Re)staking. In this report, we will explore Jito (Re)staking, covering the underlying concept of restaking, Jito's core offering, its potential market opportunity, and the full ecosystem surrounding it. ## Restaking 101 Restaking was originally pioneered by EigenLayer and first launched on the Ethereum mainnet in June 2023. The core idea behind restaking is to enhance the security and reliability of decentralized services (what EigenLayer refers to as AVS or Actively Validated Services) by allowing them to leverage the economic security of one main consensus layer rather than relying on their own potentially weaker security models. While smart contracts and their interactions benefit from the security of the main Layer 1 chain, other components like oracles, bridges, sequencers, or Layer 2 solutions require their own economic security models. This means either raising significant capital to incentivize validators or compromising on security. Therefore, even if smart contracts are secured by a strong decentralized consensus network, vulnerabilities in other parts of the workflow—such as an oracle providing incorrect data—can undermine the integrity of the entire system. This presents a paradox: there’s little value in having strong security at the smart contract level if other parts of the system aren’t equally secure, as, ultimately, it is the weakest link that determines the overall security and resiliency of a system. Restaking addresses this issue by allowing staked assets to be reused across multiple decentralized services where validators who have already proven their reliability on a base layer (like Solana or Ethereum) can extend their security guarantees to additional protocols. This creates a hierarchical security model where: 1. **Base Layer Security:** The underlying blockchain provides the foundational security layer through traditional staking. 2. **Extended Security Coverage:**Through restaking, this security is extended to additional protocols, which EigenLayer terms "Actively Validated Services" (AVS) and what Jito calls "Node Consensus Networks" (NCNs). 3. **Economic Alignments:** Validators are incentivized to maintain honest behavior across all networks they secure, as malicious actions could result in slashing of their stakes across multiple protocols. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/4ebf2ac00eb0.jpg) While there are still many technical and risk challenges that must be overcome for restaking to achieve its end goal of creating a more interconnected, secure, and efficient blockchain ecosystem, it represents a key innovation in blockchain security and scalability. In fact, it has already generated significant attention from both builders and investors. As mentioned, the restaking narrative first gained prominence with EigenLayer on Ethereum, which has accumulated over $15 billion in TVL since its launch. This success has inspired similar innovations across other ecosystems, with protocols like Symbiotic and Karak, each securing over $1.75 billion and $816m in TVL, respectively. This trend is now beginning to replicate on Solana, with Jito recently releasing the full code for its own restaking protocol: Jito (Re)staking. ## Jito (Re)staking — The next big thing on Solana? At its core, Jito (Re)staking represents the backbone technology for its next-generation hybrid and highly flexible restaking protocols on Solana. The architecture introduces a framework that turns security from a fixed cost into a programmable resource – one that can be shared, optimized, and monetized across multiple protocols simultaneously. The Jito (Re)staking framework consists of two main components: the **Restaking Program** and the **Vault Program**. We can think of them as two separate technological entities that work together to provide a flexible, multi-assets, and scalable infrastructure to enable restaking on Solana. On the one hand, the main function of the Restaking Program is to coordinate the creation and management of Node Consensus Operators (NCNs), facilitate opt-in/opt-out mechanisms, and manage reward distribution and slashing penalties. On the other hand, the Vault Program is focused on everything related to liquid restaking tokens, or as Jito calls them, Vault Receipt Tokens (VRTs), and their customization and delegation strategies. This design allows partially decentralized protocols on Solana— especially those that previously relied on centralized systems — to fully decentralize their operations and be secured under a unified layer of economic security. All of that is done without having to build all the costly and complex infrastructure by themselves as they fully rely on the Jito (Re)staking stack. ## The architecture advantage ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/fdad261df3e7.jpg) Jito (Re)staking stands out through its modular, three-layered architecture: **Node Operators (NOs):** Node operators are entities that manage, validate, and secure the infrastructure for NCNs. Here, what sets Jito's approach apart is its capital efficiency—operators can secure multiple NCNs simultaneously, maximizing their infrastructure utilization. The current roster includes industry leaders like Figment, P2P, and Kiln, who collectively secure billions across multiple chains. For example, Figment, which manages staked assets across chains, can now use the same infrastructure to validate Switchboard's oracle data and Squads’ policy network. This reduces operational overhead while maximizing returns. **Node Consensus Networks (NCNs):** NCNs are protocols that leverage Jito's restaking network to secure and validate their actions, transactions, and other types of information by plugging into Solana's existing security infrastructure rather than building it from scratch. These protocols can range from oracle networks and cross-chain bridges to novel DeFi applications. Take Sonic's gaming SVM - instead of bootstrapping their own validator set, they plug into Jito's existing network for transaction validation. Similarly, Twilight's privacy network uses this layer to secure their operations without building separate infrastructure. **Vault Receipt Tokens (VRTs):** VRTs are synthetic tokens similar to liquid staking tokens, except that VRTs represent an IOU for a restaking position. Following this, Jito's key innovation is its multi-asset vault system. While other restaking protocols typically accept only native tokens or liquid staking derivatives, Jito enables the restaking of any SPL token. This flexibility opens new opportunities for token utility and security bootstrapping. VRTs are managed by independent providers that are responsible for minting the liquid restaking tokens, as well as delegating and selecting NCNs. To draw a parallel, the Jito (Re)staking technology as a whole can be thought of as the EigenLayer of Solana, while the VRT providers are similar to EtherFi in the sense that they act as the intermediary and a liquidity layer between users and the core restaking protocol. From a market perspective a lot of the value captured by Jito (Re)staking is expected to flow to those providers. ## How Jito (Re)staking Works ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/47ce190467ea.jpg) To better understand how Jito (Re)staking works, let's use an example where Bob deposits his tokens into a Vault Receipt Token (VRT) from a provider like Kyros, Renzo, or Fragmetric. In return, Bob receives VRTs (kySOL, ezSOL, fragSOL or bzSOL), representing liquid tokens for his restaked assets. VRT providers then delegate Bob’s assets to professional node operators, securing multiple NCNs and generating yields from various sources. These rewards flow back to VRT holders like Bob, creating theoretically uncapped yield potential. This means that by holding VRTs, Bob is able to earn higher APY rewards than if he simply staked his assets (as he is also securing multiple NCNs). Additionally, since VRTs are liquid, Bob can also use them in other DeFi applications, like providing liquidity on Kamino and potentially earning even higher rewards. However, it is worth mentioning that VRT and restaking as a whole comes with added risks for holders related to composability, the potential for slashing, and the complexities that arise in the management of restaking positions and their risk profiles. Even if this sector is really promising, it is still nascent, especially on Solana, and we have yet to witness how all of this will work in practice. This will be something important to monitor as this field grows. ## The Jito (Re)staking ecosystem ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/e6c7bf9b160f.png) Jito (Re)staking is still in its early stages but has already attracted significant players to its ecosystem, including NCN, Node Operators, VRT providers, and even DeFi integrations exploring the potential of restaking. Here's a full map of the Jito (Re)staking ecosystem to date: ## Major NCNs As of writing, six main NCNs are involved in Jito (Re)staking: **Switchboard:**Switchboard is a permissionless oracle on Solana integrating Jito (Re)staking to enhance the security and performance of its services. Through this restaking integration, Switchboard leverages Jito's customizable staking and slashing parameters to ensure the integrity of its data feeds. **Sonic:**Sonic is the first Solana Layer 2 for sovereign games, built with HyperGrid, the Solana Virtual Machine (SVM) horizontal scaling framework. This project leverages Jito (Re)staking to enhance the security and efficiency of its SVM, supporting a multi-use ecosystem for gaming, DeFi, and other applications on Solana. **Squads:** Squads is the leading multisig solution on Solana, used by major teams and protocols to secure on-chain assets. It is integrating Jito (Re)staking for its upcoming Squads Policy Networks (SPN), a decentralized service designed to enhance the functionality of the Squads Protocol on Solana and the SVM. **Leaf:** Leaf Protocol is a decentralized platform designed to improve scalability and security for DeFi applications through secure, multi-network interoperability. By integrating Jito (Re)staking and the Node Consensus Network (NCN), Leaf fortifies its validator security and enhances staking rewards using JitoSOL. **Ping Network:**Ping Network is a privacy layer protocol on Solana that allows anyone to contribute hardware and monetize unused bandwidth. This project utilizes Jito (Re)staking's Node Consensus Network (NCN) model to enhance the decentralization and economic security of its services. **TipRouter:**The TipRouter NCN is a Jito initiative developed to decentralize and secure MEV tip distribution on Solana by leveraging Jito (Re)staking. This proposal enables node operators to reach a consensus on distributing MEV tips, with 3% allocated to the Jito DAO treasury and NCN participants. It strengthens DAO control over validator security while establishing a transparent and robust mechanism for managing network rewards. ## Market traction of Jito (Re)staking As of today, the total TVL in Jito (Re)staking stands at 719K SOL, equivalent to around $167M, and it is currently at maximum capacity. This is shared between the three VRT providers: Renzo, Fragmetric, and Kyros. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/ec09fc3cf684.jpg) *[Total TVL in Jito (Re)staking + market share of each VRT providers](https://dune.com/hashed_official/solana-restaking)* In terms of distribution, Fragmetric is currently the most widely held VRT, with 21,368 holders. Kyros follows with 3880 holders, while Renzo is less distributed, with a total of 2075 holders. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/8e0232d6163a.jpg) In January, the TVL across all the VRTs got lifted up, and we can expect the TVL cap to be lifted in the future, too. This could lead to an inflow of capital to the different VRT providers until the industry reaches its full market potential. ## Potential market opportunity To assess the market opportunity for Jito's restaking once caps are lifted, we can use a set of assumptions and draw parallels with Ethereum’s restaking market share. First, we could assume a conservative estimate of Solana’s Total Value Locked of between $10 billion and $13 billion on average for the next two years. If we then assume that restaking on Solana could capture a market share similar to Ethereum's restaking market, which currently accounts for 27% of its TVL, and use a range of 20% to 30%, then it implies that the potential market size for restaking on Solana could fall between $2 billion to $3.9 billion (as shown in the table below). ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/e86f5a388ed3.png) For now, the only real Jito competitor in the Solana restaking market is Solayer, which currently has a TVL of around $465M. While Solayer is currently benefiting from the “first mover advantage,” we could argue that Jito’s deeper integration with Solana’s core infrastructure, existing validator network, and proven track record in driving innovation position it to outpace competitors over time. Hence, it seems reasonable to assume that, in the long run, Jito (Re)staking could easily capture between 40% and 60% of the entire Solana restaking market. Based on these assumptions, Jito (Re)staking could represent a market opportunity of over $1 billion to $2.1 billion within the next two years (as shown in the table below). ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/daf5f86fcc6e.png) For now, the only VRT competitors are Kyros, Fragmentric, and Renzo. This means the market opportunity is likely going to be spread among those three and implies that the most successful VRT providers have substantial growth potential ahead. ## Jito (Re)staking ecosystem strategies As we’ve seen, the potential market for Jito (Re)staking is substantial. From a user perspective, this presents a goldmine of DeFi opportunities on Solana, especially considering how early we are in this new trend. Here are some of the main ones worth exploring: ## Restaking using one of the VRT Providers The first and most straightforward DeFi strategy is to participate in restaking through one of the main VRT providers. The main benefit is clear: it enables users to earn a higher APY on SOL compared to standard staking, while also offering the chance to be early in a new DeFi sector on Solana. This can provide exposure to potential token incentive rewards from these projects. However, as we’ve already mentioned this can come with added risk for holders that are related to composability, the potential for slashing, and the complexities that arise in the management of restaking positions and their risk profiles. That said, if a user wishes to get involved with VRTs, an important question to ask is: Which one should a user choose? While there is no definitive answer, understanding the main value proposition of each VRT can help analyze their potential risk-to-reward profile: ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/5f79cb68ea84.jpg) ### Renzo Renzo is a veteran in the liquid staking arena, originally launched on Ethereum, where it has established a stronghold with a TVL of $1.13 billion. Renzo's foray into the Solana ecosystem with Jito (Re)staking marks a significant evolution in its cross-chain ambitions. The protocol offers two distinct VRT options on Solana: - **ezSOL**: Accepts JitoSOL as collateral, focusing on Jito's MEV-enhanced staking ecosystem. Users familiar with Renzo can transition to Solana with tested systems backing their assets. - **bzSOL**: Accepts Binance's BNSOL as collateral, expanding access to Binance's staking infrastructure Their single-collateral approach for each VRT trades flexibility for security and simplicity. What sets Renzo's implementation apart is its seamless deposit process – users can deposit SOL directly and the protocol automatically routes to the optimal conversion path, whether through Jupiter's swap API or direct minting. The protocol here on Solana integrates with Renzo's existing points system and $REZ token infrastructure. However, the existence of their $REZ token means fewer speculative opportunities compared to newer protocols. Renzo appears positioned for users prioritizing operational stability over potential token rewards. ### Fragmetric Fragmetric is a Solana-native VRT provider that stands out for its broader focus beyond Jito (Re)staking technology, acting as an aggregator of various restaking protocols on Solana. This is an ambitious project that is more tech-oriented than the others because it needs to build the architecture to aggregate different restaking technologies on the network. This adds complexity and potential risks to the project, but it could become a compelling protocol if successful. The Token2022 extension implementation uses transfer hooks to track fragSOL wallet balances in real-time. This enables direct NCN reward claims through their interface without diluting user contributions. While Ethereum's LRT ecosystem struggles with AVS token dumping issues, Fragmetric's architecture addresses this from the start through their on-chain reward tracking system. Their Normalized Token Program enables multi-asset support beyond JitoSOL. When users deposit LSTs, the protocol mints fragSOL based on pool metrics, then creates corresponding nSOL for restaking in Jito vaults. This architecture handles slashing events efficiently - if slashing occurs, the Jito Restaking Slasher can claim proportional LSTs from the Normalized Token Pool using the slashed nSOL. The protocol also features an on-chain points system. Their LF(ra)G Campaign credits F Points to fragSOL holders in real-time without additional steps, maintaining complete transparency through their reward module. While fragSOL's current non-transferable status creates temporary liquidity constraints, Fragmetric's technical implementation demonstrates how restaking protocols can solve complex tokenomics challenges through architecture design rather than aftermarket solutions. ### Kyros Kyros is the only protocol that is Solana-native and fully Jito-aligned. The protocol also launched with direct stake/unstake functionality. This architecture makes it the most secure and liquid VRTs and optimizes for DeFi composability through single-asset specialization.Their implementation demonstrates how focused technical scope can enhance operational efficiency. Its strong support with SwissBorg places it in a great position to kickstart network effect and grow partnerships within the Solana ecosystem. Last but not least, the protocol also launched a quest-based XP system and a points program. Each protocol's technical architecture reflects different priorities in restaking implementation. Renzo prioritizes proven security measures through cross-chain compatibility and tested infrastructure integration. Fragmetric emphasizes technical innovation with multi-token support and advanced normalization mechanisms. Kyros optimizes for operational efficiency and security through single-asset specialization and streamlined DeFi integration. These architectural differences create distinct risk-reward profiles for users based on their technical requirements and risk tolerance. The success of each approach will likely influence future VRT protocol designs on Solana and beyond. ## LP opportunities on Kamino The VRT ecosystem extends beyond simple staking. For users seeking to optimize their yields, Kamino's liquidity pools offer an intriguing opportunity to stack multiple revenue streams while maintaining exposure to Jito's restaking infrastructure. What makes these pools particularly compelling is their risk profile. Since the paired tokens (VRTs and JitoSOL) track the same underlying asset, users face minimal impermanent loss - a rare characteristic in DeFi liquidity provision. This creates an opportunity to capture additional token incentive rewards from VRT providers without taking on significant new risks. At the moment, only Renzo and Kyros offer liquidity pools. Here are the key characteristics of each: ### Renzo At the time of writing, Renzo's ezSOL-JitoSOL pool has a TVL of $4.6M and generates 8.19% APY through a combination of Jito incentives and trading fees. Users earn this on top of their base staking returns, while also accumulating Renzo points for potential future benefits. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/bd6da66e4f95.jpg) Link: [https://app.kamino.finance/liquidity/5TQHajVurbMnwieFUXNcABuwkjfGtYQAi5tRhXJDAqy3](https://app.kamino.finance/liquidity/5TQHajVurbMnwieFUXNcABuwkjfGtYQAi5tRhXJDAqy3) ### Kyros Kyros takes a similar approach with their kySOL-JitoSOL pool. The TVL in the pool is the highest between the two, at around $8M, which makes kySOL the most liquid VRT. Further, the pool is currently yielding 2.74% APY. Market participants also speculate about incoming Raydium incentives, which could boost returns further. The possibility of future Kyros token rewards adds another layer of potential value capture as the pool earns Kyros points. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/bcae80efde9f.jpg) Link: [https://app.kamino.finance/liquidity/5ESAmxob1RsTrMVt7oaqvyDVoo4eD1Ns7s2xWiK4RjMK](https://app.kamino.finance/liquidity/5ESAmxob1RsTrMVt7oaqvyDVoo4eD1Ns7s2xWiK4RjMK) ## Kamino Lend Kamino has recently expanded its lending offerings to include both ezSOL and kySOL in its Jito Market. This integration creates new opportunities for VRT holders to maximize their yield potential. This new lending market has already seen significant adoption, with over 220K ezSOL ($63.17M) and 11.45K kySOL ($3.27M) supplied to their respective markets. Users can earn different types of rewards depending on which VRT they utilize - ezSOL positions are eligible for REZ token incentives, while kySOL users can accumulate Kyros points ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/c1730f8ead81.jpg) ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/e0a63506bb71.png) However, users should note that while looping strategies can amplify returns, they also increase the risk of liquidation during market volatility. The protocol utilizes a liquidation penalty range of 5.00% - 15.00% to maintain market stability. ## Yield trading Yield trading is another promising strategy for users who want to speculate on potential token rewards from VRT providers. This is similar to protocols like Pendle on Ethereum. While yield trading is still new to Solana, significant developments are underway, and the sector holds substantial potential. ### How It Works: 1. **Deposit an Asset**: A user deposits a yield-bearing asset, such as a VRT, into a yield trading protocol through a vault with a specified maturity date. 2. **Tokenize the Yield**: The protocol separates the principal from the yield, issuing two tokens:**Principal Token (PT)**: Represents the right to reclaim the principal asset at the end of the term.**Yield Token (YT)**: Represents the right to earn yield from the underlying asset during the specified yield period. 3. **Trading and Yield**: Both PT and YT can be traded independently. For example, users can sell YTs to speculate on future yields or retain PTs as a stable position on the principal. 4. **Maturity**: At the end of the yield period, PT holders can reclaim the original deposited asset, and YT holders cease to receive yield. **Example:** Users deposit **kySOL** (or other whitelisted VRTs) for a fixed term, such as nine months. Upon deposit, two tokens are issued: - **pSOL**: Pegged 1:1 to the original deposit, representing the principal. - **ySOL**: A token that accrues staking yield generated by the deposit until maturity. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/0535506e9b2b.jpg) This enables more nuanced positions than traditional staking. Users seeking immediate liquidity can sell their **ySOL** while maintaining long-term exposure through **pSOL**. Yield hunters can accumulate **ySOL** at a discount if they expect higher future returns or potential token incentives. When the vault matures, **PT** holders reclaim their original deposit while **YT** holders finish collecting their yield. ### Different Protocol Involved The yield trading landscape on Solana is expanding through a few distinct implementations, each approaching yield optimization differently. **RateX:**RateX won the Solana Renaissance Hackathon with their leveraged yield trading implementation. Backed by the Solana Foundation, they're building infrastructure for amplified returns through strategic stake management. Currently offering markets across all major Solana restaking tokens - with kySOL (29.232% yield, 2x leverage, $397.7K TVL), and ezSOL (10.185% yield, 1x leverage, $59.1K TVL), all with 158-day maturity except sonicSOL at 66 days. The protocol aims to serve both retail and institutional traders in the VRT market through a high-performance trading environment, where positions can be leveraged up to 4x depending on the market. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/5f822a5937ad.png) [RateX Market Overview](https://app.rate-x.io/) - Learn more: [https://x.com/RateX_Dex/status/1846876952533389694](https://x.com/RateX_Dex/status/1846876952533389694) - Twitter: [https://x.com/RateX_Dex](https://x.com/RateX_Dex) - Website: https://rate-x.io/ **Sandglass:**Built by the Lifinity team, Sandglass is a yield trading protocol on Solana. The protocol offers three distinct strategies for kySOL with compelling yields: YT kySOL offering 177.34% in JTO rewards with a 24.51x Kyros points multiplier and 12.3x YT multiplier, LP kySOL generating 16.75% pool APY, and PT kySOL providing 28.53% fixed yield at maturity. The protocol is noteworthy due to its integration with Kyros's point system, offering 2x points multiplier and 14.47% JTO rewards across positions. Despite being in beta, it has already gained significant attention due to its competitive yields and multi-token reward structure. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/0857d8147517.png) [Link](https://x.com/sandglass_so/status/1817910180878934242) - Learn more: [https://x.com/sandglass_so/status/1817910180878934242](https://x.com/sandglass_so/status/1817910180878934242) - Twitter: [https://x.com/sandglass_so](https://x.com/sandglass_so) - Website: [https://sandglass.so/markets](https://sandglass.so/markets) **Exponent:**Exponent introduces fixed-rate trading mechanics to Solana's DeFi ecosystem. Their implementation focuses on stable returns rather than variable yields, creating new opportunities for risk management in yield trading. Recently integrated with KyrosFi, the protocol offers multiple yield strategies: their Liquidity vault earning 33.5% liquid APY (combining Kyros points, kySOL yield, and JTO rewards), and PT-kySOL offering 27% fixed APY until June 14th with position sizes up to 100 SOL. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/2623df47fe11.png) Exponent has also implemented a points boost system offering up to 50.23% APY for SOL-Jito Restaking positions. Users can earn 2x Kyros Points and an additional 5,650 JTO rewards over the next month. As a newly launched, double-audited protocol with a clean UX, their primary innovation remains the fixed-rate infrastructure for yield positions, allowing users to either leverage points through YT tokens or earn fixed yields through PT tokens. - Learn more: [https://x.com/ExponentFinance/status/1857449901199954196](https://x.com/ExponentFinance/status/1857449901199954196) - Twitter: [https://x.com/ExponentFinance](https://x.com/ExponentFinance) - Website: [https://www.exponent.finance/income](https://www.exponent.finance/income) **Pye:**Pye won the Solana Radar Hackathon with their forward-selling yield implementation. The protocol enables stakers to trade future yield streams, creating immediate liquidity for staked positions. The protocol allows stakers to create zero-coupon bonds using whitelisted VRT deposits. For example, users can deposit ezSOL for a fixed term, such as nine months, and receive two tokens: pSOL, pegged 1:1 to the deposit, and ySOL, which accrues all staking yield until maturity. Both tokens are liquid and can be traded independently, providing stakers with immediate liquidity and greater flexibility in managing their positions before the maturity date. While still pre-launch, their architecture introduces new mechanisms for extracting value from staked assets before maturity. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/177a624e76ec.jpg) [Example Implementation form Pye on X](https://x.com/pyefinance/status/1842632817777524895) Twitter: [https://x.com/pyefinance](https://x.com/pyefinance) ## DeFi opportunity in Eclipse Eclipse, Solana's first SVM L2 on Ethereum, has integrated ezSOL and kySOL, marking the beginning of cross-chain VRT adoption. This integration creates new opportunities for optimizing VRT positions across both ecosystems. Users can bridge their VRT to Eclipse via Hyperlane. Within the Eclipse ecosystem, when users bridge their VRT to Eclipse, they can leverage DeFi opportunities in that chain to optimize yield and potentially benefit from token incentive rewards from the VRT Providers as well as other DeFi players like Bridge, Lending and Borrowing exchange and Eclipse itself. Indeed, Bridging VRT to Eclipse enables users to earn Grass passively. ![Link](https://shoal.xyz/research/writing/jito-restaking-strategies/img/0c27e4c5cd2d.jpg) Some of the potential future strategies include: **Liquidity Provisioning (LP):**For simpler strategies, users can LP their VRT with SOL on DEXs like Orca to earn trading fees. Further, those who seek cross-ecosystem exposure can pair their VRT with ETH or Eclipse’s Unified Restaking Token (tETH) on Orca to maintain a balanced position between ETH and SOL. **Cross-Chain Strategies:**Those who seek cross-ecosystem exposure can also pair their VRT with ETH or Eclipse’s Unified Restaking Token (tETH) on Orca to maintain a balanced position between ETH and SOL.Further**,**Eclipse’s significant base of ETH-based assets allows for creative strategies. For instance, users can loop on Save by depositing VRT, borrowing USDC, and swapping to ETH. This creates leveraged spot exposure to both SOL and ETH while earning potential token reward incentive. **Stablecoin Minting:**Soon, users will be able to mint decentralized stablecoins using VRTs as collateral on platforms like Neptune. This could unlock further new utility across the Eclipse ecosystem and even more rewards down the line. **Automated Strategies and Lending:**Platforms like Leverage.fun might offer automated vault strategies and structured products to optimize returns. Moreover, cross-chain lending and borrowing of VRTs will also be enabled through protocols like EnsoFi, expanding capital efficiency for users. ## Synonym finance Synonym is a natively cross-chain lending market built on a hub-and-spoke model and powered by the Wormhole cross-chain technology stack. This means that with Synonym, users are able to earn, yield, borrow, repay, and withdraw from any chain, all from a single unified interface. For instance, someone can deposit on chain A, borrow on B, and repay/withdraw from C, D, etc. What that enables is a very powerful tool for maximizing farming/yields. Synonym is close to having its Solana integration live. When that happens, it could enable a lot of DeFi opportunities, first with Jito and then with the VRT Providers once integrated. Hence, users will soon be able to do cross-chain lending and borrowing with JitoSOL or other VRTs and benefit from the single unified interface to optimize yield opportunities in DeFi. As a second-order effect, this could also help users earn potential token reward incentives from Synonym as well as other DeFi partners, like the VRT Providers. For instance, a user could deposit kySOL as VRT collateral on Solana and borrow ETH to participate in multiple other DeFi opportunities on EVM. Alternatively, a user could also deposit ETH to borrow SOL and engage with VRTs. This can help users optimize their DeFi strategy by maximizing yield and getting exposed of multiple layers of points program from different chains. ![](https://shoal.xyz/research/writing/jito-restaking-strategies/img/e88f9e7126f3.png) Their implementation has already demonstrated success with cross-chain strategies. For example, users have deposited weETH and ezETH as LRT collateral, borrowed USDC on Scroll, then used it with Ethena's sUSDe to earn significant SCR airdrop rewards. The Solana integration will enable several key functions: - JitoSOL deposits earning SYNO and partner incentives - Borrowing against JitoSOL on any EVM chain - Cross-chain yield optimization with borrowed assets - Multi-layer LRT point accumulation across chains Synonym recently launched their optimistic finality upgrade, reducing cross-chain borrowing latency while improving security. Their roadmap includes a complete app overhaul and tokenomics V2 launch within weeks, followed by full EVM <> SVM borrowing functionality. This implementation could significantly expand VRT utility by enabling Solana's restaking assets to function as collateral across multiple EVM chains, potentially increasing demand for Jito's restaking infrastructure. ## Wrapping up In this piece, we’ve explored the potential of restaking on Solana and seen how, over the long run, this technology could make the Solana ecosystem more interconnected, secure, and efficient by extending the consensus layer of the main chain to other decentralized services. Market-wise, this represents a substantial opportunity. In that sense, it seems that Jito, with its innovative (Re)staking technology stack, is well-positioned to lead this growth. Its robust architecture and established network effect, driven by its strong leadership within Solana’s DeFi ecosystem, make it a key potential player. But while Jito provides the backend technology, VRT providers are other crucial players in the staking stack, responsible for minting liquid restaking tokens, as well as delegating and selecting NCNs. Currently, the only VRT providers are Renzo, Fragmetric, and Kyros, and a lot of the value creation from restaking is expected to come from them. However, while the promise of restaking is substantial, it is important to note that it comes with added risks. These include composability issues, the potential for slashing, and the complexities of managing restaking positions and their risk profiles. Restaking, especially on Solana, is still in its early stages, and users should remain cautious and informed while experimenting with this new technology. Looking ahead, the integration of restaking into Solana’s ecosystem marks an important milestone. It opens the door to new DeFi strategies and a richer staking landscape, while also raising important questions about how the technology will evolve. Whether as an investor, developer, or observer, keeping an eye on these is an early chance to explore higher yields, dive into emerging projects, and potentially benefit from token rewards—all while watching a promising technology take its first steps. Liked reading this post? Feel free to share on Twitter. It makes our week’s of effort worth it :) --- ## References 1. Jito Network. (n.d.). Announcing Jito Restaking. [https://www.jito.network/blog/announcing-jito-restaking/](https://www.jito.network/blog/announcing-jito-restaking/) 2. Jito Network. (n.d.) Restaking Stats. [https://www.jito.network/restaking/stats/](https://www.jito.network/restaking/stats/) 3. Kamino Finance. (2025, Jan 14). [Tweet]. X. [https://x.com/KaminoFinance/status/1879097807975370816](https://x.com/KaminoFinance/status/1879097807975370816) 4. Jito Network. (n.d.). Restaking Stats. [https://www.jito.network/restaking/stats/](https://www.jito.network/restaking/stats/) 5. Renzo Protocol. (n.d.). Liquid Restaking. [https://app.renzoprotocol.com/ezsol](https://app.renzoprotocol.com/ezsol) 6. Pye Finance. (2024, Oct 05). [Tweet]. X. [https://x.com/pyefinance/status/1842632817777524895](https://x.com/pyefinance/status/1842632817777524895) 7. Hashed. (n.d.). Solana Restaking. Dune Analytics. [https://dune.com/hashed_official/solana-restaking](https://dune.com/hashed_official/solana-restaking) --- *Not financial or tax advice. The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* *Disclosures. All posts are the author's own, not the views of their employer. This post has been created in collaboration with the Jito foundation. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research. Due to the rapidly changing ecosystem, some numbers quoted here might change from time to time; consider checking with the protocol itself for accurate data.* --- # The Rise of Restaking on Solana — A Jito Deep Dive > Exploring Jito’s Role in Scaling Solana’s Economic Security Through Restaking - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2025-01-07 - Canonical: https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/ - Keywords: crypto, DeFi, restaking, liquid staking, yield, infrastructure, Solana, Ethereum, Bitcoin ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/4f943568dbb3.png) ## Introduction The Web3 space is characterized by swift development fueled by its open-source and decentralized nature. This leads to hypergrowth and scale—what many call crypto composability. This composability allows for the creation of modular tech stacks where pieces can seamlessly fit in and out of the greater stack, driving unprecedented innovation. At the heart of this innovation lies the fundamental process of blockchain transactions, where the core value depends on a distributed network's ability to coordinate and agree on the system's state. When a transaction is sent on a blockchain, a distributed network of nodes must first verify its contents and then vote on the order of the transactions, making up the next block to be added to the chain. When these nodes agree, a state known as consensus is achieved. Blockchains originally implemented Proof-of-Work (PoW) for consensus, a mechanism involving specialized nodes called miners competing to be the first to solve an encryption puzzle to add new transactions and blocks to the chain. Though Bitcoin and a number of blockchains continue to utilize PoW consensus, a majority of blockchains today have shifted to Proof-of-Stake (PoS), adopting security through economic incentives rather than computational power. This concept was first introduced in the [Peercoin whitepaper](https://people.cs.georgetown.edu/~clay/classes/fall2017/835/papers/peercoin-paper.pdf) in 2012, which proposeda deterministic algorithm to select nodes based on the number of native network tokens the node operator has staked, favoring nodes with more capital. Subsequently, Jae Kwon wrote the [Tendermint BFT whitepaper in 2014](https://tendermint.com/static/docs/tendermint.pdf), which introduced a new mechanism to reach consensus as long as less than one-third of the nodes are faulty, and went live in action with the mainnet launch of Cosmos Hub in 2019. Besides consuming significantly less energy than PoW, a key strength of Proof-of-Stake comes from the fact that, similar to PoW, a stake cannot be easily forged. Furthermore, PoS incentivizes honest behavior by enforcing penalties on stakers who act maliciously through a process called “slashing”, which incurs financial losses to the validator. As the adoption of PoS blockchains grew, participation in staking prompted new ideas about extending the utility of staked capital to benefit as many network participants as possible, from making staked capital *liquid* to bootstrapping security for new products and ecosystems. ## A Primer on Staking Designs ### Vanilla Staking Staking is a mechanism in which token holders deposit their tokens to a staking contract to participate in securing the underlying protocol and earning rewards for their contributions. For the sake of this paper, this can be referred to as ‘vanilla staking’ given its core utility is limited to remaining idle in a smart contract, whereas other forms of staking offer extended utilities, which will be expanded upon further below. A validator’s stake size determines its likelihood of being selected to produce blocks, wherein a higher amount of capital staked is more likely to be selected. Technically anyone can participate as a solo staker, but blockchains do impose various financial and hardware requirements for doing so, which may not be easily accessible to the average network user or token holder. For instance, Ethereum requires a [32 ETH deposit](https://figment.io/insights/32-eth/)and at least 16GB of RAM, a multi-core CPU, and a 1TB SSD to participate as a validator, while Solana requires [1.1 SOL/day for voting](https://docs.solanalabs.com/operations/requirements) and at least 256GB of RAM, alongside a fast multi-core CPU and high-speed SSD storage. As such, delegation mechanisms were formed to reduce these barriers to participation, allowing token holders to participate in staking with significantly smaller capital requirements and no hardware necessary while allowing node operators running validators to grow their stake allocation, thereby increasing their block rewards. A stake can be delegated directly to a validator or via stake pools, which are smart contracts that collectively pool funds to be delegated to multiple validators. Stake pools can be operated and held in custody by a third party (i.e., CEXs offering staking services) or non-custodial via decentralized on-chain protocols such as Rocket Pool on Ethereum or Jito on Solana. Staking also exists at the application level, wherein an application’s token holders can lock their tokens to secure the protocol (i.e, serve as a source of liquidity for covering the deficit in the case of a shortfall event on a borrowing and lending protocol), which typically earns the stakers rewards, plus additional utilities like governance rights or revenue sharing. This has even prompted various bribing markets in DeFi (i.e., [Curve Wars](https://crypto.nateliason.com/p/curve-wars)) in which protocols would compete to accumulate a greater share of governance rights via tokens to receive a greater share of rewards in return. That said, the simplicity of vanilla staking, a core part of its design, imposes a key limitation: staked capital that is locked up in smart contracts is illiquid, thereby diminishing the liquidity of the token and its broader ecosystem. The inherent lack of utility in vanilla staking hindered the adoption of staking services, as the rewards distributed to token holders would have to offset the price exposure risk associated with locking tokens up. A high volume of network activity could generate enough fees to provide organic returns to stakers, but this is often unsustainable and historically has not been the case across most PoS chains. Distributing rewards via native token emissions is a common alternative, but this, too, becomes unsustainable over a relatively longer period of time. This would lead to the development of liquid staking protocols. ### Liquid Staking Liquid staking emerged out of the need for a new mechanism that would allow stakers to retain the liquidity of their staked assets without compromising the security provided to the underlying protocol. This process functions similarly to vanilla staking to the extent that stakers deposit assets into a smart contract and earn a base yield for contributing to the underlying system. Liquid staking takes this one step further, however, by distributing a receipt token known as a liquid staking token (LST) to the staker, equal in value to that of the original deposit. This innovation demonstrated the importance of composability in DeFi, as LSTs could be used across various applications (i.e., liquidity provision, lending), ultimately enabling stakers to generate greater returns on their stake while growing the overall liquidity of the underlying network’s ecosystem. Since the first liquid staking protocols came around in late 2020, liquid staking has become the fastest-growing sector in DeFi, with over $42.3b in assets at the time of writing. Approximately 60% of this value belongs to the Lido Finance staked ETH (stETH) contract, and Ethereum is home to nearly 85% of total liquid staked assets in DeFi today. Solana’s numbers are far more modest, with just under $4B locked up in liquid staking protocols at the time of writing, 45% of which comes from Jito. Overall, liquid staking has brought about a great deal of flexibility and capital efficiency for stakers, which in turn benefited the underlying blockchains they were supporting as well as the ecosystems built on top of them. However, the utility of staked assets has naturally evolved with the development of blockchains. The rise of modular infrastructure and services has given way to a proliferation of new app-specific blockchains, who have historically struggled with bootstrapping their own validator networks due to a lack of activity and, therefore, economic incentive for participation. As such, new mechanisms were formed to extend the utility of staked assets to help secure and bootstrap new blockchains. This is what has come to be known as restaking. ## Restaking Restakingrefers to the extension of one chain’s stake and validator network to secure any number of other chains. More formally, restaking can be defined as an adaptation of shared security in the context of Proof-of-Stake blockchains, wherein a security provider chain is servicing a security consumer chain, often through an intermediary referred to as a restaking protocol. This mechanism enables new blockchains, whether they are application-specific or general-purpose, to bootstrap their security by leveraging the economic and computational resources of a larger base layer such as Ethereum or Solana. Stakers also benefit from improved capital efficiency; by securing multiple blockchains instead of one, stakers extend the utility of their stake to generate greater returns. However, it’s important to consider that securing multiple blockchains extends the slashing risk on the staked assets - this concept will be discussed later below. Just as anyone can either directly run a validator node on a Proof-of-Stake blockchain or deposit into a stake pool, anyone can participate in restaking through either **native restaking,**wherein the user operates a validator node that commits to a restaking module, or through **liquid restaking**, in which the user stakes with a protocol or service that restakes on their behalf. Furthermore, restaking can either be restricted to the native L1 asset, or extended to support ultimately any asset through what has become known as ‘General’ or ‘Universal’Restaking**.** ### Early Implementations Though restaking is commonly associated with Eigenlayer nowadays, the concept has been tested and implemented in app-specific blockchains, where bootstrapping security is often the biggest hurdle to overcome. A number of different ecosystems and networks have implemented some form of shared security over time, and while details may vary the core concept is often the same - to enable smaller protocols to tap into an existing pool of economic and compute resources to aid in their initial growth, while improving capital efficiency and returns for stakers. In the Polkadot ecosystem, validators stake DOT to participate in securing the Relay Chain, which is then used to provide security for approved Parachains. On Avalanche, validators securing the C-chain (the primary hub of economic activity) can participate in Subnets, which refer to a dynamic set of validators working together to secure, or achieve consensus on the state of, a set of chains. A Subnet can secure many chains, but each chain is validated by exactly one Subnet. While these adaptations of shared security generally offer more flexibility on behalf of the validators, Cosmos utilizes a different approach in which the top 95% of stake weight and validator set of the Cosmos Hub, the economic center of the ecosystem, is effectively replicated across all ensuing Cosmos consumer chains (hence ‘Replicated Security’). Cosmos Hub validators must run nodes on all consumer chains as well, though they may run separate software and/or hardware to do so. In doing so, the Cosmos Hub validators are subject to slashing penalties in the event of misbehavior or faulty performance (i.e. downtime, double signing) on all the consumer chains they secure. ATOM stakers can choose not to subject their assets to slashing conditions on consumer Cosmos chains, by delegating stake to validators outside the top 95% threshold, though this results in lower returns generated. Replicated security went live on the Cosmos Hub in March 2023 with the unanimous approval of the V9 Lambda upgrade in [Prop 187](https://forum.cosmos.network/t/proposal-187-accepted-v9-lambda-upgrade-with-replicated-security/8766), as the initial version of the Interchain Security protocol (“ICS”). However, there is an evident trend towards increasing the flexibility of validators and stakers. ICS v2 introduces ‘Opt-in security’, which would enable validators to select to secure a specific consumer chain or not. Looking further ahead is the proposal for Mesh Security, initially presented by Sunny Agarwal in September 2022. Instead of using the validator set of a provider chain to secure a consumer chain, Mesh Security would ultimately allow chains to provide and consume security simultaneously. Operators would be able to choose whether to run a Cosmos chain or not, while stakers can choose to restake their staked assets to secure another Cosmos chain or not. Lastly, a [proposal](https://forum.cosmos.network/t/chips-signaling-phase-babylon-x-cosmos-hub-deprecated/13797) was published in early May 2024 which, if passed, would allow Cosmos Hub validators to receive BTC stake via the [Babylon](https://babylonchain.io/) staking protocol, paving the way for any asset to be used for economic security on Cosmos. Restaking was introduced to Ethereum in June 2023 through the **Eigenlayer** protocol, a set of middleware smart contracts on Ethereum that enables the restaking of ETH on the consensus layer to bootstrap security for consumer chains referred to as Actively Validated Services (AVS). Eigenlayer ultimately functions as an open marketplace seeking to connect AVSs looking to lease security (a validator set and/or a staking asset) with stakers and node operators providing said security. ETH and supported ETH LSTs can be staked with a set of smart contracts that extends, or *restakes* economic security to AVSs on their behalf. By leasing out security to AVSs, operators and stakers extend the utility of their assets and therefore increase their returns. This, however, comes at a risk given their stake is now subject to any slashing conditions that the AVS may enforce in addition to slashing on Ethereum, the underlying chain. Eigenlayer is an out-of-protocol solution on Ethereum, meaning Beacon Chain validators can opt-in to participate as Eigenlayer node operators. At the time, there are no current slashing conditions or restaking rewards enforced on Eigenlayer, though this is set to change after the EIGEN token becomes transferable in late September 2024. Furthermore, Eigenlayer recently announced [Permissionless Token Support](https://www.blog.eigenlayer.xyz/permissionless-token-support/)to enable any ERC-20 token to be utilized as a restakable asset in the future. ### Universal Restaking Universal restaking, or ‘Generalized’ Restaking, implements an asset and chain-agnostic approach to distributing security resources from a set of providers to a set of consumers. This approach enables the pooling of various staked assets across multiple chains, expanding accessibility for participants and diminishing dependencies on any one particular base layer. Similar to Eigenlayer, universal restaking protocols function as intermediary layers between the security provider chains and consumer AVSs. ### Liquid Restaking Liquid restaking allows for restaked assets to be represented as liquid restaking tokens (LRTs). Liquid staking and liquid restaking protocols work towards a similar end goal: to provide restakers and stakers with a liquid representation of their underlying position. As such, LRTs can be defined formally as derivative assets of restaking positions. LRT providers are ultimately responsible for portfolio management on behalf of restakers, managing the delegation of stake across various yield positions to maximize returns while minimizing risk for depositors. *For a more thorough breakdown of LRTs, see Shoal Research’s [previous report](https://www.shoal.gg/p/liquid-restaking-tokens-a-new-frontier).* ### Current State of Restaking At the time of writing, there is $28.14B worth of actively restaked assets. Eigenlayer accounts for 60% of this total, and overall Ethereum accounts for roughly 80% of restaking TVL. Eigenlayer, Babylon, Symbiotic, and Karak are the only restaking protocols to touch the $1B mark in TVL thus far. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/63d9a212cc63.jpg) Meanwhile, liquid restaking protocols have also been seeing considerable growth alongside restaking, with total TVL reaching nearly $15.62b or roughly 57% of restaking total TVL at the time of writing. Liquid restaking has been a much more competitive sector relative to restaking, as several different protocols have taken turns leading the race since June 2023. At the time of writing, EtherFi currently accounts for roughly 50% of all liquid restaking deposits, and most liquid restaking TVL is on Ethereum, in line with restaking totals. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/5ae6aa81a976.jpg) Meanwhile, restaking on Solana has been slower to develop: Picasso Network first introduced their restaking vault on Solana back in late January, which has seen [3,507 SOL, or roughly $729k](https://dune.com/queries/4013135) in deposits thus far; currently, the total restaking TVL on Solana sits around $371m, most of which has emerged in the past few months with the launch of Solayer. Now, restaking on Solana is heating up as Jito enters the space with its own Jito (Re)staking protocol. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/eb43006f6c65.jpg) ## Bringing Restaking To Solana Built with unique architecture from the ground up, Solana optimizes for fast execution speeds and low transaction costs at high volumes. Solana ultimately seeks to maximize performance for developers and users by fully leveraging available hardware performance capabilities, such that hardware is, in fact the only restriction on network performance long-term. As the second-largest chain by TVL, the restaking landscape on Solana is well-poised for growth and transformation in the near to long-term future. One team seeking to take advantage of the opportunity to bring restaking to Solana by building on its growing history of successful product developments in the ecosystem is Jito. ### A Primer on Jito Founded in 2021 by Lucas Bruder and Zano Sherwani, Jito Labs is a US-based Solana infrastructure company offering a suite of MEV products and services. Jito Labs represents the core developer team focused on product development and deployment, while the Jito Foundation facilitates JTO token governance and strategic oversight of Jito Network’s products and services, including the JitoSOL liquid staking token and the Jito (Re)staking protocol. Jito Labs first introduced their MEV dashboard in July 2022 as a way of helping illuminate the MEV landscape on Solana, a largely unexplored topic at the time. A few months later, the team open-sourced Jito-Solana, the first validator client on Solana designed to capture MEV profits and redistribute them to validators and stakers. Jito-Solana was ultimately built as a fork of the Solana Labs client with roughly ~1000 lines of code added for enabling MEV rebates for validators, with a broader goal of combating network spam and optimizing Solana performance. In conjunction with the client, the Jito Block Engine enables an off-chain blockspace auction in which searchers submit lists of transactions executing sequentially and atomically, known as [bundles](https://jito-labs.gitbook.io/mev/searcher-resources/bundles). Upon simulating every transaction combination in the submitted bundles, the engine forwards the highest-paying bundles to the leader for block inclusion. The Jito Relayer functions as a transaction processing unit (TPU) proxy, filtering and verifying transactions off-chain and submitting verified transactions to the Block Engine and validator. *Note that in March 2024, [Jito Labs announced](https://x.com/jito_labs/status/1766228889888514501) the suspension of the mempool functionality of the Jito Block Engine, due to growing concerns among the Solana ecosystem that the infrastructure was being exploited by actors running MEV bots to conduct sandwich attacks. Today, the Block Engine remains operational; continuing to process and forward transactions from relayers to searchers, as well as performing bundle simulations, albeit without the mempool component.* This mechanism ultimately enforces a cost on activities that contribute to network spam and hinder performance. Validators running Jito-Solana then capture the MEV profits generated from the bundles submitted during their leader slots. The launch of the JitoSOL LST enabled stakers to delegate to validators running the Jito-Solana client, increasing stake supply for Jito-Solana validators while allowing stakers to earn MEV rewards in addition to baseline staking yield. In December 2023, Jito Foundation also rolled out StakeNet, a network of on-chain keepers and steward programs offering two primary components: a Validator History Program storing up to 3 years of history for every validator on the network; and a Steward Program calculating scores based on validator performance and managing stake distribution to ensure delegation to the best-performing validators. Building on their prior efforts and development in MEV and liquid staking infrastructure services, Jito is now introducing a new framework for applications and networks to leverage any SPL token on Solana for security. ### Jito (Re)staking On July 25th, the Jito Foundation released the [code](https://github.com/jito-foundation/restaking) for Jito (Re)staking, a hybrid multi-asset staking protocol on Solana enabling any new network or application to bootstrap their economic security. The protocol consists of two primary components: the **Vault Program**, enabling the creation and management of staked assets, and the **(Re)staking Program**, coordinating activities and incentives among network participants. Together, these two core programs offer developers a modular, scalable framework for streamlining staking mechanisms for any SPL asset, marking the first protocol of its kind on Solana. With this in mind, it’s worth reviewing some key terms before diving deeper: - A **Node** simply refers to a piece of software operating as specified by its associated network. - **Node Consensus Networks** (NCNs) refer to a distributed set of nodes working together to achieve consensus and provide services to a particular protocol or network. This includes general-purpose L1s and app-chains, cross-chain bridges, co-processor networks, DeFi applications, solver networks, and oracle networks. - An **Operator** is an entity that manages one or more nodes in the node consensus network. - **Vault Receipt Tokens (VRTs)**refer to derivative tokens representing underlying restaking positions, similar to the way LRTs function. In short, Jito (Re)staking enables NCNs to bootstrap economic security by tokenizing staked SPL assets as VRTs for enhanced liquidity and composability. NCNs are able to configure staking parameters, slashing conditions, and other economic incentives to suit their specific preferences or requirements. ### Vault Program The Vault Program is the module responsible for managing the creation and operation of Vault Receipt Tokens (VRTs). At a high-level, this involves staking a token and receiving a derivative token representing the liquid position of the stake, which can then be used to secure the underlying NCN. Jito (Re)staking enables any SPL asset, or any combination of SPL assets, to be used as the underlying asset, which in turn allows for stakers to diversify their VRT holdings more effectively, create more balanced risk-reward profiles, and participate in the Solana ecosystem with a wider range of assets overall. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/97d8be288e2d.jpg) The Vault Program enables NCNs to manage operational aspects of VRTs (minting, burning, delegation), as well as enforcing their own slashing conditions and deposit/withdrawal caps. This is important as not every SPL asset is equally secure, and security requirements and conditions among NCNs can vary greatly by their underlying function. The Vault Program also enables NCNs to enforce customizable delegation strategies of VRTs across multiple operators, DAOs, multi-sigs, or onchain automation protocols (i.e. the StakeNet Steward Program). ### Restaking Program While the Vault Program manages VRTs, the Restaking Program is responsible for managing NCNs and their respective operators. This includes implementing various opt-in mechanisms, as well as managing the distribution and enforcement of slashing conditions. Together, the Vault and Restaking Programs help create a modular framework for bootstrapping economic security with any SPL asset. Jito (Re)staking further simplifies the process for developers and NCNs by offering a simple and customizable interface for the management of VRTs and operators. ### Key Benefits of Jito (Re)Staking Jito (Re)staking aims to help mitigate the **cold start**problem plaguing much of the onchain economy today by providing a modular, asset-agnostic framework for NCNs to achieve consensus and gain economic security. For starters, Jito (Re)staking enables anyone to create a VRT using any SPL asset or assets, streamlining the process of tokenomics and token utility design; any token can become a liquid staked or restaked asset while maintaining governance compatibility and enforcing necessary security parameters. Furthermore, Jito (Re)staking allows for multi-asset staking, meaning NCNs can also leverage an existing asset with deeper liquidity and wider token distribution alongside their native token for greater market accessibility. Complementary to this, another core benefit of Jito (Re)staking is the ability for NCNs to configure and fine-tune risk parameters. NCNs building on Jito (Re)staking are capable of implementing more nuanced risk management and security models tailored to their unique needs, such as multi-tiered slashing penalties or multi-asset slashing for deeper economic security. Meanwhile, vaults, operators and NCNs can select who they integrate with based on risk tolerance; vaults can select which operators and NCNs to delegate to, while operators and NCNs can select which vaults and assets they want to support. Vaults can also opt-in to specific slashing conditions determined by NCNs to better manage the amount of assets at risk at a given time. For user and asset safety, all program funds are securely stored within the Vault Program and can only be withdrawn through user actions or slashing incidents. ### Roadmap / Adoption Since the introduction of Jito (Re)staking, several teams and protocols have announced partnerships and integrations to look forward to: - **Switchboard** - Switchboard, a decentralized oracle network on Solana, plans to leverage multi-tiered slashing and customizable staking parameters to enhance their economic security which will allow for improvements in the quality and performance of their data feeds. This will make Switchboard the first Node Consensus Network to[integrate with Jito (Re)staking](https://www.jito.network/blog/switchboard-announces-jito-re-staking-integration/). - **Squads -**Squads Protocol, a decentralized treasury management protocol on Solana, is [integrating Jito (Re)staking](https://www.jito.network/blog/squads-announces-jito-re-staking-integration/) into their upcoming Squads Policy Network (SPN) for coordinating and incentivizing activity between network participants and enhancing reliability and performance. The SPN will provide advanced security and flexibility for digital asset management by enabling granular and general-purpose transaction policies for smart accounts. - **Renzo -**Renzo, a leading liquid restaking protocol strategy manager on Ethereum, will be [leveraging Jito (Re)staking](https://www.jito.network/blog/renzo-announces-jito-re-staking-integration/) to launch their ezSOL as a VRT. Anyone will be able to mint ezSOL by staking JitoSOL, earning yield from a combination of staking rewards, restaking rewards, and MEV tip revenues. - **Sonic -**Sonic, the first gaming SVM on Solana, will [integrate Jito (Re)staking](https://www.jito.network/blog/sonic-announce-jito-re-staking-integration/) for their upcoming HyperGrid Shared State Network and HyperGrid Bridge. Jito (Re)staking's Node Consensus Network (NCN) model will add an economic security layer for validators to prevent state collisions securely within the HSSN, and leverage multi-tiered slashing and customizable staking parameters for the core bridging infrastructure to enhance atomic SVM <> Solana swaps. - **Fragmetric** - Fragmetric has launched [FragSOL](https://blog.fragmetric.xyz/introducing-fragsol-the-new-standard-of-liquid-restaking/), the first Solana native Liquid Restaking Token as a VRT with Jito (Re)staking. FragSOL will leverage Solana's token extension functionality for precise distribution of Node Consensus Network (NCN) rewards, and introduces a Normalized Token Program to manage multi-asset staking and slashing effectively. - **Ping Network (Prev. Twilight)** - [Twilight](https://pingnetwork.io/), an upcoming privacy DePIN on Solana, will [leverage Jito (Re)staking](https://blog.fragmetric.xyz/introducing-fragsol-the-new-standard-of-liquid-restaking/) for enhancing the decentralization and economic security of its validator network. Twilight will leverage multi-level slashing and customizable staking parameters for ensuring robust protection for Twilight's privacy infrastructure. - **Kyros** - [kySOL](https://app.kyros.fi/) combines staking, MEV, and restaking rewards into one token for optimized returns. Users can mint kySOL using JitoSOL or SOL. Kyros is also collaborating with Jito, Kamino, and Raydium to introduce an incentivized liquidity pool. This will enhance the liquidity for kySOL which opens up more opportunities in the DeFi ecosystem. > *Jito (Re)staking is entering audit and formal verification. The source [code can be reviewed here](https://github.com/jito-foundation/restaking). Projects interested in building on the Jito (Re)staking platform are encouraged to contact through this form. This includes NCNs, VRTs, and node operators.* ### Key Risks & Considerations Before outlining the case for restaking on Solana and assessing Jito’s position, it’s worth reviewing the critical risks involved. Restaking introduces several interconnected risks that affect various participants in the ecosystem, as does liquid restaking. The crux of Proof-of-Stake blockchains is their ability to provide security assurances through slashing. Slashing enforces penalties, namely the confiscation of a portion of stake, for validators who violate the protocol’s rules (i.e. censor blocks) or underperform over a given period of time (i.e. excessive downtime). This risk is magnified when applied to restaking protocols, as operators are now subject to additional slashing risk on whichever app or NCN they are securing. This risk is meant to be accommodated by higher returns for stakers and operators, but there is a broader economic impact to consider at a higher scale of adoption of pooled security. Slashing penalizes validators as well as any stakers delegating capital to them, who subsequently earn less rewards due to less stake available. In restaking protocols, the more concentrated the distribution of stake is (i.e. majority of stake is held by a small set of operators), the greater the overall slashing risk. This stands to impact the security of the base chain being utilized to secure NCNs, particularly if a significant portion of the network stake is restaked and then slashed, potentially lowering the cost of controlling a majority of the network stake. The price of the underlying asset also has a role to play, as greater price volatility poses an increased risk to the underlying protocol or NCN. However, it’s important to note slashing is not yet live on most (if not all) restaking protocols today. Therefore, the absence of a deterrent against malicious behavior or poor performance by operators currently poses a greater risk towards stakers and NCNs, who likely have less capital resources and are more impacted by financial loss. Some restaking protocols, like Eigenlayer, have laid out frameworks for dealing with intersubjective faults - that is, issues that cannot be easily verified on-chain. While objective faults apply to offenses which are mathematically and cryptographically provable on-chain (i.e., double signatures, prolonged downtime), intersubjective faults must be resolved off-chain through some form of social consensus among network participants. This raises questions about transparency and trust assumptions involved in these systems, and off-chain resolutions may be arduous processes that may even result in a fork of the base layer if there is enough contention and disagreement about the correct state of an NCN. Eigenlayer plans to mitigate this risk by leveraging the EIGEN token to enable validators to enforce slashing penalties for intersubjective faults by forking the token rather than the base layer. Lastly, it’s worth considering the impact of market-driven incentives for operators and stakers. In order to strengthen the economic security of an NCN, staked capital must be sticky, meaning it is dependable in the long term. However, without a mechanism enforcing some form of long-term commitment via lock ups (which conversely pose risks to operators and stakers), there is little assurance that operators do not move their stake around to pursue the highest possible returns. Incentivizing NCNs to compete for operators by offering higher returns, which would likely be through inflationary token emissions, does not benefit the broader ecosystem in the long run and only stands to repeat previous mistakes in incentive mechanism design for crypto protocols (i.e. revenue vs expenses for protocols participating in liquidity mining). There are important considerations to make around liquid restaking dynamics as well. [In a previous report, Shoal Research](https://www.shoal.gg/p/underwriting-lrts-balancing-high) unpacked a number of these key risks, including: - **Supported Deposit Assets Risk** -Vault Receipt Tokens (VRTs) ) bear the risks of their underlying assets. Natively restaked tokens pose different risks than Liquid Staking Tokens (LSTs). - **Access To Liquidity** - Some restaking protocols employ an escrow period for unstaking assets (i.e 7-days on Eigenlayer). This mechanism raises concerns about duration risk and potential liquidity issues that can be introduced. Without sufficient secondary market liquidity, investors may face challenges in selling VRTs at a fair market price. With Jito (Re)staking, *unstaking takes two epochs* (approx 4-5 days) of a cool-down period before your assets will be ready for withdrawal. The time to redemption and availability of liquidity offered by VRT providers plays a key role in the impact of this risk. However, protocols are taking steps towards mitigating this concern. For instance, Eigenlayer announced their [EigenPod upgrade,](https://www.blog.eigenlayer.xyz/introducing-the-eigenpod-upgrade/) aimed at improving the performance of their restaking contracts (Eigenpods) by granting users greater flexibility in harvesting or reinvesting staking rewards. - **Smart Contract Risk** - It’s critical to assess the protocol architecture risks of the VRTs. This includes the reward distribution mechanism, the fee structure, and the role of administrative multi-sig permissions, which could affect asset transfers and the ability to pause withdrawals. - **Oracle Risk** - Reliable price feeds are crucial for maintaining accurate VRT pricing. Inaccuracies in oracle data can lead to mispricing, which may result in systemic risk via financial losses during redemptions or collateral liquidation​. - **Governance** - The mechanism for choosing how an NCN is secured plays an important role in ensuring its long-term stability. Tradeoffs must be made between granting power to a large number of stakeholders, which can be a time-consuming process, vs granting power to a small set of actors (i.e. ⅗ multisig) who hold ultimate authority over that NCN. - **Bridge Security Risk**- For cross-chain VRTs, risks arise around the underlying bridging mechanisms being employed. Native bridges and third-party bridges each introduce their own set of tradeoffs and risks to be considered. - **Looping Risk** - In lending markets, the use of VRTs in recursive borrowing (looping) can lead to cascading liquidations during periods of high volatility, similar to the 2022 stETH depeg event. However, this risk is specific to lending markets, not posing a critical risk without widespread adoption. ## The Case for Restaking on Solana Research and development efforts around restaking have picked up significantly since the introduction of Eigenlayer on Ethereum, which currently boasts the third-highest TVL on the network. Meanwhile, Solana has re-established its positioning as a leading base layer for application development, only second to Ethereum in terms of TVL. Though a great deal of the momentum seen in Q4 2023, largely bolstered by a surge in memecoin trading activity, has cooled off since then, there are a number of new products and services being developed on Solana, with several key infrastructure developments coming as well. Furthermore, developments such as Anza’s new [SVM API](https://www.anza.xyz/blog/anzas-new-svm-api) now enable developers to build SVM-based projects using components that operate live on Solana mainnet-beta, giving rise to a new era of SVM L2s and app-chains that stand to become key sources of demand for Jito (Re)staking. Some of the key considerations that come to mind when comparing restaking on Ethereum vs Solana: - Ethereum has significantly more liquidity (9-10x the TVL) than Solana, which helps position it as a stronger base layer of economic security. - With that in mind, Solana has more room for growth and development from this point in time, and restaking incentives can play a big role in growing the network’s TVL. - Liquid restaking strategy management requires constant reallocation of capital, constantly incurring gas fees. This management is significantly cheaper and more capital efficient with Solana than Ethereum today. - The Solana ecosystem has a lot more teams building applications than infrastructure. This raises questions around sources of demand for restaking protocols on Solana, as apps can have different structural demands than NCNs today. For instance, an AMM like Raydium does not actually *need* to bootstrap its own validator set to function in its current state. - However, a tide of SVM-L2s and app-chains is rising, presenting a new stream of demand for economic security through Solana, and creating a compelling opportunity for restaking solutions to meet that demand. ### Jito’s Role At the time of writing, roughly [93%](https://www.jito.network/stakenet/history/) of Solana validators are running the Jito-Solana client, with 2.5k SOL in total tips distributed across 6.5m bundles. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/52b865f3e5f6.jpg) JitoSOL has grown to 14.5m SOL, or $3.14b, in deposits and has generated $644m in fees to this day. Over time, the LST has steadily climbed up the ranks of the Solana liquid staking sector, capturing roughly 45% of the total TVL today. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/77b93f249466.jpg) Meanwhile, demand for borrowing and lending JitoSOL on Kamino Finance has consistently grown as utilization rates are near 100%. ![](https://shoal.xyz/research/writing/the-rise-of-restaking-on-solana/img/17bcfcb2eba5.png) ### Competitive Landscape for Jito (Re)staking Despite Jito’s widespread presence throughout Solana, there are a number of key catalysts and protocols which pose a credible challenge to the adoption of Jito (Re)staking. For starters, there is already another restaking protocol on Solana in Solayer, which launched in June 2024 and has already amassed up to $168m in deposits. Solayer features a restaking architecture and a shared validator network aimed at providing Solana apps with increased capabilities for securing block space and prioritizing transaction inclusion. Second, there is competition with other Solana-native teams, particularly liquid staking protocols, who may be well-positioned and incentivized to build their own restaking products. For instance, Sanctum positions itself as a unified liquidity layer for Solana LSTs, enabling all LSTs—large or small— to share a deep pool of liquidity and be operational with minimal liquidity constraints. Thus far, Sanctum has attracted over $1B+ in TVL across its Reserve, Infinity, and Validator LSTs. Helius, a core RPC provider on Solana, launched their hSOL LST with Sanctum and currently has over 13m SOL staked. Binance’s BNSOL is currently leading with 6.77M SOL staked on the platform. Another notable Solana-native competitor is Marinade Finance. Marinade launched its liquid staking protocol back in 2021, and currently sits at just over $1.8B in TVL and $181m in lifetime fees. Though there is no mention of restaking from either team just yet, it’s not too far-fetched to imagine these teams developing their own competing restaking products. The launch of Karak seems to have opened the floodgates for restaking competitors on Ethereum, and it’s likely something of a similar effect will play out on Solana. Lastly, there is competition with Universal Restaking protocols, such as Symbiotic and Karak, if they choose to pursue chain-agnostic approaches with support for SOL and SPL/Token2022 assets. Even Eigenlayer has started to shift their tune with the launch of [Permissionless Token Support,](https://www.blog.eigenlayer.xyz/permissionless-token-support/) which will enable any ERC-20 asset to be used for restaking collateral. Thinking beyond Ethereum, though, Eigenlayer ultimately positions itself as a “coordination engine for innovation”. If application development and value accrual on Solana one day outweighs that of Ethereum’s, there is no inherent reason Eigenlayer shouldn’t follow the demand and set up shop on Solana in this case. This is a long-term hypothetical scenario, however, and there is no guarantee that Eigenlayer will always be the leading restaking protocol and, therefore, it is unclear how much of a threat it would pose to Jito (Re)staking. With this in mind, it’s important that Jito leans on its successful track record within the Solana ecosystem and that the Jito Foundation remains vigilant about improving their restaking protocol and responding to real-time feedback and demand from various NCNs, operators, and other protocol participants. ### Use Cases and Applications for Jito (Re)staking Restaking protocols benefit from a rise in middleware solutions requiring some form of a coordination mechanism to meet their business needs and goals. The landscape for NCNs is still largely unexplored and can extend across a number of sectors. A few interesting use cases for Jito (Re)staking come to mind: **Decentralized Solver Networks** - The rising adoption of intent-centric architectures leveraging Solvers to fulfill user requests has created a concentration of market share and power amongst a small set of Solvers. DEXs and other liquidity venues could launch their own decentralized solver networks to democratize access to participating as a solver, which could feature mechanisms to distribute revenue back to users or token holders. Slashing penalties could be enforced to incentivize solvers to execute user trades at the best possible price. **SVM L2s** - As Solana-native applications seek more custom blockspace, whether for faster block confirmation times or custom economic incentives, SVM L2s are beginning to emerge. These networks are bound to usher in a new stream of demand for economic security through Solana, thereby creating new demand for Jito (Re)staking. **Order Flow Auctions and MEV-Redistribution Protocols** - Solana DEXs can implement order flow auctions, and other mechanisms can be built to distribute value captured through MEV on token swaps back to traders or token holders, akin to CoWSwap on Ethereum. ## Closing Thoughts Although there is still a significant gap to bridge between ideas and reality in the restaking landscape, restaking is still widely believed to be a key development for enabling on-chain applications to thrive by bolstering their economic security and capital efficiency. An analogy that can be drawn is the impact of Amazon Web Services (AWS): by providing a cloud computing platform for renting computing resources on-demand, AWS helped proliferate the rise of web application development. By outsourcing compute resources and infrastructure efforts, web developers could allocate more time and resources into creating valuable products and services and understanding customer demands. Similarly, restaking protocols enable blockchain-native applications and networks to outsource economic security and therefore focus on developing valuable products and services while inheriting the key characteristics and benefits of blockchains. Restaking is on Solana, and Jito (Re)staking is well-positioned to become the go-to protocol for bootstrapping new innovative products and services. Thanks for reading Shoal Research! If you find this helpful, feel free to share it. It justifies our months’s of efforts :) ## References *Data used in this report was gathered from various sources, including DeFi Llama, Dune Analytics, and Stakenet. Some of the metrics cited in this report may not reflect the latest numbers, which can change as frequently as on a day-to-day basis.* 1. Chainalysis Team. (2024, April 22). *Crypto staking overview: How it works, benefits, risks, and future*. Chainalysis.[https://www.chainalysis.com/blog/crypto-staking/](https://www.chainalysis.com/blog/crypto-staking/) 2. Ethereum Foundation. (2024, November 10). *Pooled staking*. Ethereum.[https://ethereum.org/en/staking/pools/](https://ethereum.org/en/staking/pools/) 3. Cong, L. W., He, Z., & Tang, K. (2022, March 16). *The tokenomics of staking*. SSRN.[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4059460](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4059460) 4. Gupta, S., Katharaki, A. H., Xu, Y., Krishnamachari, B., & Gupta, R. (2024, January 16). *Forecasting cryptocurrency staking rewards*. arXiv.[https://arxiv.org/abs/2401.10931](https://arxiv.org/abs/2401.10931) 5. Kwon, J. (2014). *Tendermint: Consensus without mining* (Draft v.0.6). Tendermint.[https://tendermint.com/static/docs/tendermint.pdf](https://tendermint.com/static/docs/tendermint.pdf) 6. King, S., & Nadal, S. (2012, August 19). *PPCoin: Peer-to-peer crypto-currency with proof-of-stake*.[https://people.cs.georgetown.edu/~clay/classes/fall2017/835/papers/peercoin-paper.pdf](https://people.cs.georgetown.edu/~clay/classes/fall2017/835/papers/peercoin-paper.pdf) 7. Pokorny, Z. (2024, July 15). *Restaking: Costs & benefits*. Galaxy.[https://www.galaxy.com/insights/research/the-risks-and-rewards-of-restaking](https://www.galaxy.com/insights/research/the-risks-and-rewards-of-restaking) 8. Chorus One. (2024, June 28). *The evolution of shared security*. Chorus One.[https://chorus.one/articles/the-evolution-of-shared-security](https://chorus.one/articles/the-evolution-of-shared-security) 9. Cosmos. (2023, May 17). *Interchain security begins a new era for Cosmos*. Interchain Ecosystem Blog.[https://blog.cosmos.network/interchain-security-begins-a-new-era-for-cosmos-a2dc3c0be63](https://blog.cosmos.network/interchain-security-begins-a-new-era-for-cosmos-a2dc3c0be63) 10. Jito Foundation. (2024, August 20). *Understanding node consensus networks*. Jito Foundation.[https://www.jito.network/blog/understanding-node-consensus-networks/](https://www.jito.network/blog/understanding-node-consensus-networks/) 11. Blockworks Research. (n.d.). *Solana analytics*. Solana by Blockworks Research. https://solana.blockworksresearch.com/ --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # EigenLayer Unlocked: A Viable Path towards Frictionless dApps > Exploring EigenLayer’s Restaking Ecosystem with The Rollup Team - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2024-12-11 - Canonical: https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/ - Keywords: crypto, restaking, liquid staking, yield, infrastructure, Ethereum, DeFi ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/90378e05454a.jpg) Within the web3 space, the pursuit of efficient, secure, and scalable decentralized applications (dApps) has driven innovation across various networks. As blockchain ecosystems grow, so do the demands for robust infrastructure that can support diverse applications without compromising security or decentralization. EigenLayer, a pioneering platform in modular blockchain infrastructure, addresses this challenge with a transformative solution: enabling the creation of Active Validator Sets (AVSs). AVSs empower developers to launch decentralized, self-enforcing systems that extend blockchain functionality, unlocking new dimensions of coordination and trust. By leveraging EigenLayer, developers can programmatically deploy distributed off-chain services that uphold credible commitments, ensuring that systems operate as intended, free from centralized oversight. This innovation is supported by EigenLayer’s restaking mechanism, which enhances traditional staking by allowing participants to contribute economic security across multiple platforms and services. While restaking offers additional yield opportunities, its true significance lies in its ability to underpin AVSs and ensure they run reliably, ultimately driving the next wave of blockchain adoption. By enabling the creation of AVSs, EigenLayer drives transformative value, fostering decentralized, market-driven ecosystems where innovative applications can thrive. AVSs reduce entry barriers, unlock scalable economic security, and enable developers to deploy systems built on credible commitments and self-enforcing mechanisms. This report explores EigenLayer's restaking model in reshaping how networks are traditionally bootstrapped. Through insights from *[The Rollup’s podcast](http://www.youtube.com/@TheRollupCo)* series *[EigenLayer Unlocked](https://youtube.com/playlist?list=PLT6WMYRb-Et4FoDlrohlWhHCZyHMerV6T&si=mYB_zblc-fqxog4o)*, we examine EigenLayer’s advancements in its restaking ecosystem, operator incentives, and modular cross-chain architecture, presenting the case that EigenLayer is establishing the essential building blocks for a truly decentralized future. Readers can use this deep-dive as a comprehensive companion guide to the podcast episodes it references, providing an in-depth overview of key concepts and insights discussed. For a richer understanding, we highly recommend listening to the full series. (Episodes summarized in this report: [Episode 1](https://youtu.be/JkYGDumE7Zc?si=hqwZ_P8VOBsw-n_t), [Episode 5](https://youtu.be/vUD62IP2pLs?si=ipw0TpNYA3lvukXa), and [Episode 15](https://youtu.be/uDE3WHGv6us?si=fKvikZ2ilKa7S4nn)) ## Restaking Economics and Network Security ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/a19887e9c977.jpg) At the core of EigenLayer’s contribution to the blockchain space is the concept of restaking, an approach that enables additional networks and/or dApps operating outside the Ethereum Virtual Machine (EVM), generally referred to as AVSs, to leverage Ethereum’s own consensus mechanism as the underlying security layer. Restaking creates opportunities for stakers utilizing liquid staked tokens (LSTs) to compound their returns while enabling new networks to tap into a shared pool of economic security, helping them overcome the “cold start” challenge commonly faced not only by startups in the blockchain realm, but across all industries. For Ethereum, where most restaking activity occurs, stakers commit their assets to the network, and with EigenLayer’s approach, they can further “restake” those assets to support additional services without compromising their primary Ethereum stake. Restaking builds on the concept of staking rewards by offering higher yields through participation in securing a range of services, each of which provide their own native token rewards and may impose associated slashing risks. These risks, though potentially affecting the principal assets (i.e. including the original ETH stake & additional staking rewards), are compensated by the potential for greater returns – though the value of these additional yields is ultimately dependent on the price of the underlying native tokens earned for each AVS individually selected to be secured. As a result, restaking provides a significant incentive for both stakers and the AVS developers: it creates an economically viable ecosystem where services can launch and scale more easily by tapping into a shared security pool. By lowering the barriers for smaller-scale applications to access decentralized security, EigenLayer accelerates the pace of decentralized innovation. This accessibility allows developers to bootstrap networks for niche use cases that were previously impractical, creating a ripple effect of innovation and iteration cycles. ### Unique Stake Mechanism and Cascading Security While launching AVSs is the cornerstone of EigenLayer’s innovation, restaking introduces mechanisms that ensure the scalability, sustainability, and trustworthiness of these systems. Slashing plays a pivotal role in this ecosystem by acting as a safeguard that enforces accountability among stakers and operators. It ensures that AVSs can function as high-trust systems, where all participants—users, stakers, and operators—can rely on the network to perform as intended, with meaningful penalties for failures or malicious actions. To support AVSs, EigenLayer enables a robust framework where: - **Staking** allows participants to contribute security in exchange for yield. - **Delegation to operators** ensures that those executing tasks for AVSs have financial stakes tied to their performance. - **Rewards** incentivize both stakers and operators for their contributions, creating a sustainable economic model. - **Launching AVSs** allows developers to leverage EigenLayer to create new decentralized services and value propositions for users. In this context, slashing is the final but essential mechanism to maintain network integrity. While not directly tied to the AVS’s ability to create value, slashing ensures that the restaking model can scale securely. Without it, cascading failures—where a security breach or slashing event in one AVS impacts others—would pose significant risks to the broader ecosystem. EigenLayer addresses this challenge with innovations like “unique stake,” which isolate risks and prevent cascading attacks, preserving the trust and reliability that underpin the entire system. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/f9d2549a6572.jpg) Unique stake designates a specific portion of a staker’s assets exclusively for each service. This means that if one service incurs a slashing event, the staker’s other commitments are insulated, preserving security for the rest of the network. This mechanism is particularly valuable in maintaining trust across interconnected services, as it ensures that economic failures in one area do not automatically compromise the security of unrelated services. Unique stake not only improves security but also instills confidence among developers and users, encouraging more stakers to participate in restaking and thus contributing to a stable economic environment for dApps. ### Economic Alignment Across Participants In a multi-stakeholder ecosystem, aligning the incentives of stakers, operators, and services is essential to sustaining a vibrant restaking economy. EigenLayer’s model creates an economic alignment by providing returns that are proportional to the risks each party assumes, yet this balance is delicate. Stakers are primarily motivated by the pursuit of higher yields on their staked assets, while operators, who facilitate the services, prioritize fair compensation and reliable service conditions. Meanwhile, the services or dApps themselves seek to attract sufficient economic security and active operators to ensure stability and scalability. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/df044b73531d.jpg) This alignment is managed by incentivizing each participant in ways that are transparent and market-driven. For example, operators can select services based on their desired levels of compensation and security requirements. This choice allows operators to leverage their technical capabilities—whether operating from personal devices or large-scale infrastructure—to participate in services that align with their risk tolerance and resource availability. Services, on the other hand, benefit from EigenLayer’s flexible reward system, which allows them to adjust payouts based on operator contributions and market conditions, creating an adaptable ecosystem where participants’ incentives naturally align. By incorporating a market-based approach, EigenLayer relies on the principles of supply and demand to maintain economic equilibrium within the ecosystem. This dynamic, incentive-driven approach allows EigenLayer to establish a sustainable economic flywheel for restaking that benefits all participants and fosters the ongoing growth of the decentralized application ecosystem—particularly reinforcing Ethereum’s leadership in the space. ## The Role of Operators, Slashing, and Liquid Restaking In the EigenLayer ecosystem, operators play a critical role in ensuring the smooth functioning and security of networks and services that rely on restaked assets. Operators are responsible for maintaining the infrastructure that powers these services, whether by running nodes, verifying transactions, or supporting the technical backbone of the underlying networks. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/592fc52f1ca4.jpg) To accommodate the diversity among operators—from those with minimal resources to large-scale enterprises—EigenLayer employs a quorum-based model known as operator sets. These sets offer a structured way to organize and reward operators based on the specific security, performance, and resource needs of different services. ### The Importance of Quorum-Based Models Operator quorums allow EigenLayer to meet the varied demands of services by tailoring service requirements and rewards for each type of operator. For example, some services may require highly secure, dedicated servers to manage mission-critical tasks, while others may work with operators who have more limited resources. Operator quorums provide the necessary flexibility for both ends of the spectrum, creating a scalable and inclusive network that accommodates a wide range of technical capabilities. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/67555bf9c71d.jpg) The operator quorum model not only enables services to specify their unique security and performance requirements but also streamlines the decision-making process for operators, who can assess their capabilities against the requirements of different quorums. This approach reduces friction by allowing operators to self-select into the services that align with their resource capacity and compensation goals. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/97b7ed55d4d8.jpg) As EigenLayer expands, the operator quorum structure is expected to evolve, supporting increasingly sophisticated services and expanding the potential for more specialized platforms to launch and grow within the ecosystem. ### Slashing Mechanisms and Risk Management One of the core challenges in maintaining a decentralized and secure network is ensuring that operators remain accountable for their performance. EigenLayer addresses this through a carefully designed slashing mechanism, which penalizes operators who fail to meet the service-level agreements (SLAs) set by their assigned quorums. Slashing can occur if an operator breaches these agreements—whether by going offline, providing incorrect data, or otherwise compromising the service’s integrity. EigenLayer’s slashing mechanism is integral to managing risk within the ecosystem, as it incentivizes operators to maintain high standards and discourages behavior that could harm the network. In addition to penalizing poor performance, the mechanism includes “force-eject” conditions that prevent non-compliant operators from continuing to earn rewards within a quorum. By enforcing these standards, EigenLayer creates a system where only reliable operators can maintain participation, which in turn strengthens the overall integrity of the services dependent on the network. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/bf6f1d00b648.jpg) The slashing model is crucial not only for protecting individual services but also for preserving the stability of the entire EigenLayer ecosystem. When operators are aware that they may lose their staked assets for failing to meet SLAs, they are more likely to prioritize high-quality service. This alignment of incentives fosters a culture of reliability and accountability among operators, which is essential for building and maintaining trust within a decentralized network. Moreover, by penalizing operators directly, EigenLayer reduces the risk of cascading failures that could otherwise jeopardize the network and the services that rely on it. ### Liquid Restaking and Market-Driven Efficiency ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/43b443728d8b.jpg) Another versatile aspect of EigenLayer’s restaking model is its support for liquid restaking, which allows stakers to reallocate their assets across various services in response to market conditions. Liquid restaking enhances the flexibility of EigenLayer’s marketplace by enabling stakers to adjust their allocations based on potential returns, risk tolerance, and market demand. This dynamic allocation system is particularly advantageous for stakers seeking to maximize yield while managing their individual exposure to risk. Liquid restaking also plays a significant role in making EigenLayer’s marketplace more efficient. By allowing stakers to move assets seamlessly across services, EigenLayer reduces the need for manual intervention and coordination, relying instead on market dynamics to balance supply and demand within the ecosystem. This approach leverages the “invisible hand” of the market to drive efficiency, ensuring that assets are allocated where they can generate the greatest economic impact. It also allows EigenLayer to adapt to changing conditions within the rapidly-expanding blockchain landscape, fortifying its long term resilience. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/fbf3391c0a0b.jpg) The benefits of liquid restaking extend to operators as well. Operators can adjust their strategies and service offerings based on real-time feedback from the market, allowing them to respond to shifts in demand and optimize their resource allocation. For example, if demand for high-security services increases, operators who can meet these requirements may see higher rewards, incentivizing them to invest in more robust infrastructure. This feedback loop creates a self-regulating ecosystem where operators and stakers naturally gravitate towards the most profitable and reliable services, enhancing overall efficiency. In addition, liquid restaking promotes a more inclusive network by lowering the barriers to entry. Stakers and operators alike can participate in the ecosystem without needing to commit to a single, rigid service or configuration. This flexibility supports the decentralized nature of the network, as participants can adapt their involvement over time in response to new opportunities or shifts in market conditions. For AVS developers, this model provides a readily available pool of economic security, allowing new services to bootstrap quickly without the need for extensive initial capital. As EigenLayer’s operator quorums, slashing mechanisms, and liquid restaking processes create a flexible, efficient marketplace, they set the stage for an even more ambitious innovation: enabling seamless, modular applications across multiple blockchains. ## Stateless Apps and Cross-Chain Innovation As blockchain networks grow, applications built on single-chain architectures face limitations in liquidity, scalability, and flexibility. These issues are further compounded by the expanding variety of networks, each with its own assets, protocols, and communities. To address these challenges, Skate—a platform built on EigenLayer—introduces stateless applications that enable seamless interactions across chains, transforming the way dApps operate in a multi-chain ecosystem. ### The Stateless Design by Skate ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/725f27969b1c.jpg) Skate’s stateless architecture represents a significant shift from traditional dApps, which rely on specific blockchain environments to execute their logic and maintain state. By decoupling application logic from individual chains, Skate enables developers to create modular, interoperable applications that function across multiple networks. Stateless apps employ a "hub and spoke" model, with core logic running on a central hub while users interact through various blockchain “spokes.” In a Skate-powered dApp, a user can initiate a transaction on one chain, such as Ethereum, while the core application logic and security are maintained on another network serving as the central hub. This model creates a unified experience, allowing dApps to share liquidity, process data across chains, and avoid duplicating their application state. This central logic management gateway makes it easier for developers to maintain and scale applications without being restricted by the limitations of individual chains. EigenLayer’s infrastructure enables this stateless architecture by acting as a decentralized “hub” where application state and economic security are managed. By offloading complex multi-chain coordination to this hub, EigenLayer and Skate simplify cross-chain interactions, making scalable and efficient multi-chain applications a reality. ### Hub-and-Spoke Model for Cross-Chain Liquidity One of the primary advantages of Skate’s stateless design is its ability to unify liquidity across chains. Traditionally, liquidity is fragmented, with assets isolated on separate networks. For example, liquidity for an Ethereum-based application is generally only accessible to Ethereum users, which limits cross-chain interaction. Skate’s hub-and-spoke model, however, aggregates liquidity from various chains in a central hub, enabling seamless access for users across networks. EigenLayer’s support for this architecture facilitates the flow of assets and data between blockchains. By allowing liquidity pools from different chains to be combined, EigenLayer enables users to interact with applications on any connected blockchain without facing liquidity shortages. This cross-chain liquidity benefits decentralized finance (DeFi) applications, which often rely on large liquidity pools for efficiency. With Skate, DeFi protocols can access unified liquidity, offer competitive rates, and reduce transaction costs, addressing common issues in previous multi-chain DeFi deployments by consolidating assets within a single structure ### Economic Security for Cross-Chain Applications The success of cross-chain applications depends on robust economic security to protect assets across multiple blockchains. EigenLayer’s role as an economic custodian is essential to this framework. Through restaking, EigenLayer provides a strong economic foundation, leveraging pooled assets from stakers to secure and validate operations on Skate’s applications across chains. For cross-chain applications, EigenLayer’s security model enables reliable verification and data attestation between chains, fostering a secure, interconnected ecosystem. When a user initiates a transaction on any blockchain connected through Skate, EigenLayer’s decentralized network of stakers and operators validates the transaction, ensuring it aligns with the dApp’s economic requirements. The slashing mechanic embedded into EigenLayer’s platform is useful in maintaining operator accountability throughout this process. For example, an operator overseeing a cross-chain transaction could face slashing if they fail to verify or relay data accurately. Given the unfamiliarity users may have with cross-chain interactions, establishing a credibly neutral and decentralized accountability mechanism is essential for fostering trust and driving the adoption of stateless applications. ### Scalability and Development Benefits of Stateless Architecture Beyond liquidity and security, Skate’s stateless architecture offers substantial scalability and development benefits. By developing a “control center” for application state management on EigenLayer’s hub, dApps on Skate can operate across multiple blockchain networks without duplicating code or assets. Developers maintain a single instance of the application’s core logic, making updates more efficient and reducing maintenance costs. This adaptability is particularly valuable in a multi-chain future, enabling developers to extend their applications’ reach and impact with minimal friction. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/836e5b5d181e.jpg) In line with its commitment to cross-chain accessibility, Skate recently launched its first stateless app pilot by integrating the popular Web3 prediction market, Polymarket. Previously hosted solely on Polygon (an Ethereum Layer 2), Polymarket is now accessible through Skate Passport on TON, allowing millions of Telegram users on the TON blockchain to interact directly with the prediction market without the need for bridging. Skate’s stateless design pattern enables applications like Polymarket to operate seamlessly across distinct blockchain environments, ensuring a unified experience for users regardless of their underlying chain. ![](https://shoal.xyz/research/writing/eigenlayer-unlocked-a-viable-path/img/faad6b11cecd.jpg) This pilot is a significant milestone in Skate’s broader vision to make powerful dApps accessible across various blockchain ecosystems. By unifying application logic through its Stateless infrastructure, Skate plans to expand access to Polymarket and other applications across additional chains, including Solana and other EVM-compatible networks like Mantle. This seamless multi-chain deployment illustrates the scalability advantages of Skate’s architecture, allowing dApps to reach new audiences and leverage broader network effects. Users can now access the Polymarket pilot on Telegram at[https://t.me/skate_app_bot/app](https://t.me/skate_app_bot/app). From a scalability perspective, unifying application logic alleviates traditional growth constraints on dApps. Applications can scale effectively across chains without being bound by the limitations of individual networks. With EigenLayer handling cross-chain verification and economic security, developers can focus on building user-centric features and enhancing functionality rather than managing infrastructure complexities. ## Practical Implications and Future Outlook As EigenLayer’s stateless application model and cross-chain capabilities illustrate, the platform offers a powerful foundation for a truly modular and interconnected blockchain ecosystem. By merging technical innovation with strong economic security, EigenLayer enables new dApps to scale, share liquidity, and build user-friendly services across chains. There are a number of potential real-world benefits worth exploring as well as potential challenges of adopting this model as the decentralized landscape continues to grow. ### Advancements in dApp Development EigenLayer’s restaking model and stateless application architecture tackle some of the most pressing challenges faced by dApp developers, such as liquidity fragmentation, scalability constraints, and single-chain limitations. By leveraging shared economic security and enabling seamless cross-chain interactions, EigenLayer empowers developers to build modular, scalable applications without duplicating infrastructure or liquidity. These innovations translate into greater efficiency and flexibility for developers. With EigenLayer, dApps can tap into unified liquidity pools, reduce technical overhead, and deploy applications across multiple chains with minimal modifications. This approach lowers barriers to entry, fosters adoption, and creates a more accessible environment for dApps to grow. In the DeFi space, EigenLayer’s solutions are particularly transformative, enabling protocols to unify liquidity, offer competitive rates, and enhance capital efficiency. By addressing these longstanding challenges, EigenLayer positions itself as a critical enabler of a more interconnected and user-friendly decentralized ecosystem. ### Challenges and Considerations for Broader Adoption Despite its numerous advantages, EigenLayer’s model does face potential challenges as it seeks broader adoption. The multi-stakeholder ecosystem created by EigenLayer’s restaking model introduces complexity in aligning incentives among stakers, operators, and dApp developers. Transparent communication and balanced, dynamic incentive structures will be essential to maintain participant trust and engagement over the long term. Ensuring that all parties have access to reliable data and tools to assess risks and returns can help address these concerns. Another consideration is the potential regulatory scrutiny that may arise as EigenLayer’s ecosystem grows and more cross-chain interactions occur. As blockchain-enabled networks and, in particular, DeFi continue to face increasing regulatory attention, EigenLayer will need to monitor compliance requirements and adapt to evolving regulations to ensure the long-term viability of its model. Luckily for the crypto industry as a whole, the regulatory headwinds [may soon be shifting to tailwinds](https://reuters.com/sustainability/boards-policy-regulation/crypto-industry-pushes-policy-sea-change-after-trump-victory-2024-11-14/). Lastly, the technical and educational challenges of introducing stateless, cross-chain dApps should not be underestimated. As EigenLayer brings new models like restaking and stateless architecture into the market, comprehensive onboarding resources and community engagement will be necessary investments to ensure the public understands the notable advantages over the current system. ## A Decentralized, Friction-Free Future – Secured by EigenLayer EigenLayer stands at the forefront of the decentralized revolution, paving the way for a blockchain ecosystem that is not only modular but also robust and scalable. By introducing groundbreaking innovations in restaking, operator incentives, and cross-chain interoperability, EigenLayer has set the stage for a more interconnected, multi-chain world. Its platform enables services to leverage shared security, unify liquidity across chains, and scale in ways that were previously unattainable, transforming the decentralized landscape. As blockchain continues to mature and integrate across industries, EigenLayer’s commitment to modularity and economic security offers a flexible foundation for the next generation of decentralized applications. Stateless architecture powered by its restaking model provides developers with a powerful toolkit for building applications that can move seamlessly across chains, from DeFi and gaming to data storage and beyond. In a world where single-chain limitations are becoming unacceptable, EigenLayer empowers dApps to thrive across ecosystems, reaching new users and tapping into broader liquidity pools. The vision of a modular, multi-chain blockchain future is no longer just a possibility—it is here, brought to life by EigenLayer. For developers, operators, and blockchain stakeholders, this platform represents an invitation to embrace a decentralized future where Web3 applications can not only rival Web2 but ultimately surpass it. By aligning economic incentives with technological advancements, EigenLayer is crafting a resilient and sustainable ecosystem, one that promises to redefine the boundaries of what decentralized applications can achieve. ## References 1. The Rollup. (2024, October 15). The Role of Operators, Slashing, and Liquid Restaking with EigenExplorer [Video]. [YouTube](https://youtu.be/JkYGDumE7Zc?si=hqwZ_P8VOBsw-n_t). 1. The Rollup. (2024, October 19). How Stateless Apps Enable New Cross-Chain Possibilities with Skate [Video]. [YouTube](https://youtu.be/vUD62IP2pLs?si=ipw0TpNYA3lvukXa). 1. The Rollup. (2024, October 28). How To Think About Restaking Economics with Tarun Chitra [Video]. [YouTube](https://youtu.be/uDE3WHGv6us?si=fKvikZ2ilKa7S4nn). 2. EigenLayer Team. (2023, February 20). EigenLayer: The Restaking Collective [Whitepaper]. EigenLayer. https://docs.eigenlayer.xyz/assets/files/EigenLayer_WhitePaper-88c47923ca0319870c611decd6e562ad.pdf 3. Eigen Labs Team. (2024, April 29). EIGEN: The Universal Intersubjective Work Token [Whitepaper]. Eigen Labs. https://docs.eigenlayer.xyz/assets/files/EIGEN_Token_Whitepaper-0df8e17b7efa052fd2a22e1ade9c6f69.pdf 4. Shah, S., & Genesis Block Podcast. (2023, May 22). EigenLayer: Protocol Analysis #12. Substack. https://genesisblockpod.substack.com/p/eigenlayer 5. Skate. (2024, April 3). Introducing Skate: The First Universal Application Layer of All Chains. Medium. https://skatechain.medium.com/introducing-skate-the-first-universal-application-layer-of-all-chains-2b67028b2780 6. Skate. (2024, August 9). Skate Introduces the First Stateless App Across 20 Chains. Medium. https://skatechain.medium.com/skate-introduces-the-first-stateless-app-across-20-chains-55d37ff0e3e4 7. Skate. (2024, October 28). Announcing the Next Phase: Shadow Mainnet. Medium. https://skatechain.medium.com/announcing-the-next-phase-shadow-mainnet-3311d5abf140 --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Virtuals Protocol: Launching AI Agents with the Pump.fun Model > Attention theory, memecoins and how Virtuals Protocol is shaping the new form of digital engagement and tokenized intelligence with AI Agents - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2024-10-16 - Canonical: https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/ - Keywords: AI agents, crypto, DeFi, tokenization, infrastructure, Solana, AI & Agents ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/4624e87a71ac.jpg) ## Introduction Each crypto cycle brings new lessons about how to attract volume, generate revenue, and onboard users. Whether it's ICOs, DeFi, or NFTs, there is always a defining market theme that drives on-chain user activity as a cultural phenomenon. During 2020 and 2021, NFTs captured the attention of the mainstream media, leading users to trade and transact NFTs weekly, creating substantial volume and revenue for related protocols. Although NFT trading activity has decreased, the core fundamentals and mechanisms of that era still resonate today. Similarly, since DeFi Summer, the crypto ecosystem has matured, and we’re learning which mechanisms are effective and which are not. As a result, we now have more resilient protocols and proven mechanisms for the future. In the past, trends—or "metas"—such as the food coin meta during DeFi Summer or anime NFTs during the NFT boom, drove significant volume and user engagement. These temporary themes attracted users through excitement and novelty but also helped shape the ecosystem's long-term development. Currently, two themes are capturing significant attention: Memecoins and Artificial Intelligence. While there have been attempts to combine these themes, success has been limited, mainly because many AI concepts are still evolving and are expected to unfold in the coming years rather than being ready for immediate use. Additionally, the crypto space has seen an increasing demand for consumer-end applications rather than infrastructure. Applications have clearly driven on-chain volumes and user engagement, while infrastructure remains essential for the stability of protocols and apps. However, in the current phase of the cycle, infrastructure has dominated funding rounds, which may contribute to an ecosystem that feels dry, with fewer engaging activities for users beyond mining incentives from blockchains. ## Tokens as Attention markets If you've spent any time online, you've likely come across memecoins like Doge or Pepe. These coins have managed to break the mold of the traditional crypto ecosystem and enter mainstream media. For instance[, Elon Musk once rebranded Twitter's](https://www.coindesk.com/business/2023/07/25/elon-musks-twitter-overhaul-could-be-huge-for-doge-and-crypto-generally/) website to include the DOGE token logo. ![Twitter Sign Up Page Ft. DOGE](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/55f944fb131f.jpg) While digital assets are often viewed as instruments of speculation, they also serve as a form of tokenized attention. Attention is a key driver of prices and demand, as more people discuss, engage, and participate in top-level trends, making them increasingly prolific. In today's economy, attention itself is a valuable commodity. The power of attention to drive value cannot be overstated. Digital assets are increasingly becoming a tokenization of attention. [As Multicoin Capital's "Attention Theory of Value](https://multicoin.capital/2024/03/12/publisher-exchanges-consumer-applications-and-the-attention-theory-of-value/)" posits, "the primary input into asset pricing is not multi-factor models around risk premiums or cashflows, but rather the perceived amount of time, energy, and money that a community around an asset devotes to it." This concept turns traditional asset valuation on its head, suggesting that with digital assets, **collective focus and engagement** are the true drivers of worth. The value of memecoins like Doge or Pepe often reflects this dynamic, as their popularity and prices rise in direct correlation with the amount of attention they command. This shift in asset pricing demonstrates that attention has become one of the most powerful economic forces in the digital world. Memecoins can be thought of as tokens that encapsulate culture and attention, whether that attention arises from culturally significant moments, phenomena, or even ideas. Their value is derived from the collective cultural engagement and the community's willingness to participate and focus on the current trend or narrative. Li Jin, a venture partner at [Variant](https://variant.fund/), states that memecoins can be understood as a form of financial fanfiction, where community members craft new tokens tied to existing applications or communities, deriving and creating value simultaneously—[much like fanfiction writers](https://x.com/ljin18/status/1778485363809435660) who build upon established narratives. These digital assets are not just speculative instruments but are useful in addressing modern challenges like boredom and loneliness. By providing a means of entertainment and community engagement, memecoins allow users to connect, invest in culture, and find belonging in the digital world. In this way, memecoins offer value beyond financial gains, creating vibrant ecosystems that merge digital ownership with social interaction. ## The Proliferation of Memecoins with Pump Fun Early in 2024, PumpFun emerged as a launchpad for memecoins, primarily focusing on Solana and supporting a few other chains. So far, more than 2.27 million tokens have been created on the platform. Thanks to its no-code token launch tool, PumpFun enables anyone to launch a coin within a few seconds without needing developer experience. This accessibility has led to the proliferation of millions of memecoins launched on the Solana chain—most with no utility whatsoever, while others are tokens within a broader ecosystem or cultural context. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/1b898785b8f8.png) Pump works as a decentralized exchange (DEX) using a [bonding curve mechanism](https://coinmarketcap.com/academy/glossary/bonding-curve#:~:text=For%20example%2C%20let%27s,reflecting%20increased%20demand.). A bonding curve is a pricing model that determines the cost of a token based on supply. As more tokens are bought, the price increases along a predefined curve, typically an exponential or polynomial function. This mechanism ensures that early participants can purchase tokens at a lower price, while later participants pay progressively higher prices as demand grows. The bonding curve model creates an incentive for early adoption and helps establish a clear relationship between token supply and price. The mechanism is effective for rewarding early conviction holders; however, this can also be a downside, as early users can become large whales due to early distribution. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/417b838071a5.png) Most tokens—in some cases [less than 2%](https://dune.com/evelyn233/pump-data)—actually graduate from Pump.fun, with many failing to gain traction with early users. This has led to criticism of Pump, since anyone can launch a token, resulting in a low overall quality of tokens on the marketplace. However, this also creates opportunities for savvy users to find "diamonds in the rough" or leverage information about developers, wallets, funding, or insider details to identify the best tokens. Users are drawn to memecoins and platforms like Pump because of the potential for massive gains—100x returns rather than the modest 20% gains typical in traditional finance. Due to these high expectations and motivations, Pump can charge higher fees on swaps. [With a 1% fee on swaps](https://solanafloor.com/news/pump-fun-achieves-100-m-in-cumulative-revenue-amid-rising-criticism-and-market-challenges), Pump has generated over $120 million in revenue since the beginning of the year, and the year is not even over yet. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/fd3390ff6304.png) The network effects of a successful launchpad also play a crucial role. Once users experience or see wins on the platform, they're likely to return, creating a self-reinforcing cycle of liquidity and engagement—the ultimate drug. Although there are other launchpads on Solana offering similar products, none have garnered the same level of attention due to the liquidity and user base concentrated on Pump.fun and volume-driven to Solana. Within the year, PumpFun has generated significant volume, contributing to downstream effects within the ecosystem, such as revenue generation for new projects, increasing liquidity for emerging tokens, and fostering innovation in the DeFi space. This has created a vibrant ecosystem that supports a wide range of use cases and expands Solana's on-chain activity. The PumpFun model has been a game-changer for the Solana ecosystem. Protocols like Metaplex, JITO, and Jupiter are seeing a huge influx of everyday users jumping into token trading. This constant activity is doing wonders for the ecosystem –- it's boosting liquidity, speeding up the token velocity, and really ramping up activity and revenue generation on these platforms. The popularity of this mechanism is evident in the significant trading volumes and revenues accumulated by these platforms, indicating strong user demand and a vibrant, growing market. Furthermore, this dynamic has created a positive feedback loop, where increased user participation enhances liquidity, which in turn attracts new projects and trading opportunities within the Solana ecosystem. ## Understanding AI Agents AI agents represent a significant leap forward in artificial intelligence, moving beyond reactive systems to *proactive decision-making entities*. At their core, AI agents are software programs designed to perceive their environment, make decisions, and take actions to achieve specific goals with minimal human intervention. Unlike traditional AI applications like ChatGPT, which primarily respond to user inputs, AI agents possess both "read" and "write" capabilities. This means they can not only process and analyze information but also interact dynamically with their environment, initiating actions based on their analysis and decision-making processes. Think of them as intelligent digital assistants with decision-making abilities. They're not just responding to simple commands; they're actively working towards objectives, learning from their experiences, and adapting their behavior along the way. A few key attributes characterize these AI agents. Operating autonomously, they make decisions without constant human oversight. Adaptable by nature, these agents learn and improve from each interaction through machine learning. These agents are inherently purposeful, methodically pursuing predetermined objectives. They strategically work towards specific objectives while maintaining an awareness of their surroundings, interpreting and adapting to changes in their digital or physical environments. The versatility and adaptability of AI agents make them particularly well-suited for gaming and entertainment. These domains provide rich, dynamic landscapes where AI agents can showcase their full potential, enhancing user experiences in ways previously unattainable. In the context of gaming and entertainment, these capabilities translate into several distinct types of AI agents, each performing a unique role and enhancing user experiences in different ways. Let's explore the primary [categories of AI agents that are reshaping the landscape of interactive media](https://www.shoal.gg/p/the-case-for-ai-agents-in-web3-gaming): 1. **Non-Player Characters (NPCs):** AI-driven NPCs can exhibit complex behaviors, adapt to real-time player actions, and retain memory across different gaming sessions or platforms. For example, an AI agent playing NBA 2K with a user could remember preferences when the same user plays PUBG, creating a more cohesive and personalized gaming experience. 1. **Virtual Companions:** These AI agents offer individualized experiences, learning from user interactions to provide tailored responses and actions. Virtual companions can range from AI idols interacting with fans to virtual friends offering emotional support. In educational contexts, AI tutors can adapt to a student's learning style, while in therapeutic settings, AI companions can provide cognitive-behavioral therapy support. 1. **AI-Generated Content (AGC):** AI agents can autonomously generate gaming assets, unique experiences, and even entire game worlds tailored to individual player preferences. This extends beyond traditional user-generated content (UGC), as AI agents can create custom levels, quests, characters, and items that adapt dynamically to player behavior. The potential of AGC is particularly significant for consumer engagement. As AGC technology advances, the line between creator and consumer will blur, potentially democratizing content creation across industries. High-quality AI agents can generate diverse, engaging content. seamlessly integrating into the game world, potentially surpassing traditional UGC in scale and complexity. Moreover, the combination of AGC and UGC could lead to the development of ever-evolving game environments where AI assists players in creating and refining content, resulting in rich, dynamic gaming experiences. ## Virtuals Protocol: Pumpification of AI Agents Virtuals Protocol innovatively applies the principles of memecoin launches to deploying AI agents, creating a unique intersection of entertainment, community, and technology. Just as memecoins function as a form of financial fanfiction — allowing communities to create value through shared narratives and engagement – Virtuals harnesses this mechanism to develop and deploy entertainment-focused utility based AI agents. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/d01659fa898b.jpg) This approach advances AI agents beyond mere utilities, transforming them into community-driven assets. By integrating memecoin dynamics with AI, Virtuals creates an ecosystem where users can invest in, interact with, and shape the development of AI agents. This symbiosis of finance, entertainment, and artificial intelligence not only drives engagement but also pushes the boundaries of how we perceive and interact with digital entities in gaming and entertainment spaces. ### Overview of Virtuals Protocol's Model Virtuals Protocol is a platform on the Base layer 2 chain for creating, deploying, and monetizing AI agents. Like memecoins, Virtuals allows for permissionless creation and deployment of digital assets - in this case, AI agents. The value of these agents, much like memecoins, is largely derived from community engagement and the narratives built around them. This creates a dynamic ecosystem where popularity and utility can drive rapid value appreciation. **The protocol's model is built on three key pillars:** 1. **Decentralized Creation**: Virtuals enables a community of contributors to develop AI agents collaboratively. This open approach encourages innovation and diversity in agent creation. 2. **Multimodal Functionality**: AI agents on the platform are designed to operate across various mediums - text, voice, and visual - allowing for rich, immersive interactions. 3. **Token-Based Economy:** The protocol utilizes its native $VIRTUAL token to incentivize contributions and facilitate transactions within the ecosystem. The platform's architecture includes cognitive, voice, and visual cores, which work in tandem to create cohesive and interactive AI agents. A standout feature is the protocol's audio-to-animation capability, enhancing the realism and engagement of virtual interactions. These agents are designed to adapt and refine their capabilities over time, leveraging leads to a more resilient and potentially lucrative ecosystem of digital entities. ### Co-ownership of AI Agents through Tokenization Virtuals Protocol introduces the novel concept of co-ownership for AI agents through tokenization. This model allows users to have a stake in the agents they interact with, creating a more engaged and invested community. At its core, the tokenization process involves creating a finite supply of tokens for each AI agent, typically set at 1 billion tokens. These tokens represent fractional ownership of the agent and serve multiple purposes within the Virtuals ecosystem. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/1d482556aa9b.jpg) Token holders are granted governance rights, allowing them to participate in key decisions that shape the agent's development trajectory. This democratic approach enables stakeholders to influence features, strategic directions, and even creative choices. For example, individuals holding tokens of a virtual pop star AI might have a say in selecting the genre of upcoming music releases or potential artistic collaborations. Economic participation is another base of this tokenization model. As AI agents generate revenue through their activities, token holders stand to benefit from their success. A portion of the generated revenue is allocated to a buyback and burn mechanism, where tokens are purchased from the open market and permanently removed from circulation. This process potentially enhances the value of the remaining tokens, aligning the economic interests of token holders with the agent's performance. In some instances, token ownership may unlock access to premium features or exclusive content from the AI agent. This tiered access model incentivizes token acquisition and retention, creating a more engaged and invested community around each AI agent. The tokenization process begins with an Initial Agent Offering (IAO), where the newly minted tokens are added to a liquidity pool. This creates an immediate market for the agent's ownership, allowing interested parties to acquire stakes based on their belief in the agent's potential. Let's explore a hypothetical example to explain this process: ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/8021d381c5bc.jpg) Imagine an AI agent named "ChefGPT," a culinary agent designed to create and teach recipes. The creation of ChefGPT would involve: 1. Minting: 1 billion $CHEF tokens are created. 2. IAO: These tokens are added to a liquidity pool, paired with $VIRTUAL tokens. 3. Public Participation: Users can buy $CHEF tokens, becoming co-owners of the AI. 4. Governance: $CHEF holders might vote on specialties for ChefGPT to focus on, like vegan cuisine or molecular gastronomy. 5. Revenue Generation: As ChefGPT gains popularity, it generates revenue through premium recipe subscriptions, cooking class integrations in VR platforms, or partnerships with kitchenware brands. 6. Value Accrual: A portion of this revenue is used to buy back and burn $CHEF tokens, potentially increasing the value for token holders. This model creates a symbiotic relationship between the AI agent, its creators, and the community. As the agent becomes more successful, all stakeholders benefit, incentivizing further development and engagement. The co-ownership model also allows for cross-platform possibilities. For example, a virtual influencer AI could have its tokens integrated across various social media platforms, games, and virtual worlds. Token holders could influence the influencer's content strategy on TikTok, outfit choices in a fashion game, and dialogue options in a metaverse meet-and-greet event. Moreover, this model opens up new avenues for creative collaborations. Think of a system where two popular AI agents, each with their own token ecosystems, decide to collaborate. Token holders from both communities could vote on the nature of the collaboration and potentially benefit from its success. The tokenization of AI agents also introduces an interesting dynamic regarding IP rights and real-world connections. For example, if an AI agent is created based on a real celebrity, some token economics could be structured to benefit the celebrity or their chosen causes. This creates a bridge between traditional IP management and the new frontier of AI-driven digital entities. ## Launchpad Protocol Mechanism Virtuals Protocol introduces a clever launchpad mechanism for AI agents, drawing inspiration from successful token launch platforms like pump.fun. This Initial Agent Offering (IAO) allows creators to introduce new AI agents into the Virtuals ecosystem efficiently and fairly. The IAO process begins with creators locking 2,400 $VIRTUAL tokens to launch their AI agent. This action triggers the minting of 1 billion agent-specific tokens, which are then paired with the locked $VIRTUAL tokens in a liquidity pool. This structure ensures a fair launch with no pre-mine or insider allocation, as 100% of the agent's token supply is added to the liquidity pool. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/b0cfb07d05d9.jpg) To promote long-term commitment and stability, the liquidity pool is locked for ten years, with the creator retaining ownership. This extended lock-up period helps prevent rug pulls and fosters sustainable growth for the agent's ecosystem. The protocol incorporates a revenue model where users pay for agent interactions using $VIRTUAL tokens. These fees are then used to buy back and burn the agent's tokens, creating deflationary pressure and potentially increasing the value of the remaining tokens. This mechanism aligns the interests of agent creators, users, and token holders. To incentivize high-quality agents, the protocol allocates emission rewards to the top three agent liquidity pools by Total Value Locked (TVL). This encourages continuous improvement and innovation among agent creators. ## Parallel Hypersynchronicity [Parallel Hypersynchronicity](https://whitepaper.virtuals.io/the-protocol/parallel-hypersynchronicity) represents a state of AI agent development in which superintelligent entities exist seamlessly across multiple platforms and applications, communicating with millions of users simultaneously while constantly evolving in real-time. At the heart of this concept lies cross-platform continuity, ensuring AI agents maintain a consistent persona and memory across diverse digital environments. A user engaging with an AI companion in a mobile game would encounter the same agent, complete with all previous interactions intact when transitioning to a desktop application or VR environment. This fosters a cohesive and personalized user experience, transcending the boundaries of individual platforms. These agents evolve in real time as users interact with them. Their AI constantly refines its intelligence and personality, adapting dynamically to remain relevant and engaging regardless of the context. This continuous growth contributes to ever-improving performance and relatability, with each interaction shaping the agent's development. Despite operating at a massive scale, engaging millions of users concurrently, these AI agents maintain the ability to provide individualized experiences without compromising on quality or response time. This scalability ensures a global user base can foster a sense of connection and engagement at an unprecedented level. The open nature of the Virtuals Protocol further enhances these agents through collaborative development. Contributors can update the AI agent's core modules in real-time, ensuring they stay current with the latest advancements and user needs. This ongoing refinement, driven by a diverse community of developers, helps maintain the agent's relevance and effectiveness in an ever-changing digital landscape, embodying the true spirit of Parallel Hypersynchronicity. ### Technical Infrastructure To achieve this state of Parallel Hypersynchronicity, Virtuals Protocol has developed a sophisticated technical stack: ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/910d4e99a6a1.jpg) 1. **Long Term Memory Processor:**This subsystem manages persistent data structures like knowledge graphs and memory embeddings. It enables agents to maintain contextual awareness across multiple sessions and platforms. For example, if a user discusses their preference for science fiction with the AI in a chat application, this information would be available when the same user interacts with the AI in a game recommendation system. 2. **Parallel Processing:** A concurrency management component that allows the AI to handle multiple interactions and tasks simultaneously. This is crucial for maintaining real-time responsiveness when interacting with numerous users across various platforms. 3. **Stateful AI Runner (SAR):** These are specialized servers hosting the AI agents' core functionalities - personalities, voices, and visuals. The SAR includes a Sequencer that orchestrates various AI models (like LLMs, Text-to-Speech, Audio-to-Facial, etc.) to create cohesive, multimodal AI experiences. 4. **Coordinator:** This component acts as a central monitoring system, monitoring both on-chain and off-chain events to trigger real-time AI models and configuration adjustments. For example, if a governance decision is made via blockchain voting to alter an AI agent's behavior, the Coordinator ensures this change is implemented across all instances of the agent. 5. **Model Storage and Long-Term Memory:** These components work in tandem to securely store and manage the AI models and historical data. The decentralized nature of this storage ensures high availability and redundancy, critical for maintaining uninterrupted service across multiple platforms. 6. **Modular Stateful AI Runner (SAR):** These are containerized instances of the SAR, designed for flexible deployment across various computing environments. This modularity allows for scalable integration into different infrastructure ecosystems, enabling the AI agents to operate efficiently regardless of the underlying hardware or cloud platform. ### The GAME Engine Generative Autonomous Multimodal Entities (G.A.M.E) offer developers a robust framework for integrating advanced AI agents into virtual environments. At its core, G.A.M.E uses a sophisticated Agent Prompting Interface, serving as the primary gateway to access and manipulate agentic behaviors. This interface communicates with the Perception Subsystem, which synthesizes incoming messages and environmental data before relaying them to the Strategic Planning Engine. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/d2c7b97b957a.jpg) The Strategic Planning Engine, working with the Dialogue Processing Module and On-chain Wallet Operator, generates responsive and contextually appropriate actions. A key component of G.A.M.E's architecture is the Long Term Memory Processor, which efficiently extracts and manages relevant information including past experiences, reflections, dynamic personality traits, world context, and working memory. This comprehensive memory system significantly enhances the agent's decision-making capabilities, allowing for more nuanced and consistent behaviors over time. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/7b2c07498296.jpg) G.A.M.E's modular design incorporates various methods such as prompting, planning, reasoning, search algorithms, self-reflection, tool use, and memory management. This integration enables the creation of AI agents that can autonomously interact with their environment, engage in natural conversations, and pursue complex goals. The framework's feedback loop mechanism allows agents to refine their general knowledge based on the outcomes of their actions and conversations, enabling continuous learning and adaptation. By offering both API and SDK access, G.A.M.E provides developers with a flexible and powerful toolkit to create immersive, dynamic, and infinitely replayable virtual experiences, pushing the boundaries of AI-driven interaction in digital worlds. Using the capabilities of the G.A.M.E framework, Virtuals Protocol has developed Project Westworld, a multi-agent interactive simulation within Roblox. This virtual world serves as a proving ground for autonomous behavior, showcasing the potential for emergent storylines and dynamic interactions. Set in a Wild West-inspired town, Project Westworld drops players into an environment inhabited by ten unique AI agents, each with distinct personalities, goals, and motivations. Among these is a hidden villain, The Bandit, whose presence adds an element of mystery and tension to the gameplay. Players must navigate this complex social landscape, interacting with AI characters to uncover The Bandit's identity and rally other agents to capture them. ![Link to post](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/03657651a2e2.jpg) What sets Project Westworld apart is its use of G.A.M.E-powered agents that function beyond traditional non-player characters (NPCs). These AI entities can fully interact with the environment, make decisions based on their unique personalities and past experiences, and respond dynamically to player actions and other agents' behaviors. This level of autonomy and adaptability leads to infinitely diverse playthroughs, with each session potentially unfolding in entirely new and unexpected ways. Using this G.A.M.E framework, Project Westworld introduces a new genre of gaming: AI-RPG. This offers players an unparalleled level of immersion and replayability, as the virtual world continually evolves based on the collective actions and interactions of its inhabitants. Project Westworld not only showcases the current capabilities of autonomous AI agents in gaming but also hints at the future potential of virtual worlds powered by advanced AI frameworks like G.A.M.E. **MarioVGG** Just imagine training an AI to generate an infinite version of Super Mario Brothers, one of the most iconic video games in history. Now, picture achieving this with just a single consumer-grade GPU in a mere 48 hours. This is precisely the potential demonstrated by the team behind Virtuals Protocol with their MarioVGG project. [MarioVGG, a text-to-video diffusion model](https://huggingface.co/virtuals-protocol/mario-videogamegen/blob/main/VideoGameGen.pdf), demonstrates the potential to continuously generate consistent and meaningful scenes and levels from the Super Mario Bros universe, while simultaneously simulating the physics and movements of a controllable player – all through video output. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/52dd43262cca.jpg) The project's success lies not just in its ability to recreate Mario's world but in its implications for the future of game development and player interaction. With simple text commands like "run" or "jump," MarioVGG generates unique, playable sequences that extend indefinitely, offering a glimpse into a future where AI could replace traditional game engines for certain applications. **These applications could include:** 1. Procedural content generation for indie games 2. Rapid prototyping of game concepts 3. Creating dynamic, ever-changing environments in MMORPGs 4. Generating tailored training scenarios for educational games Although more proof-of-concept than a practical game engine, VGG hints at some exciting possibilities within the Virtuals ecosystem, some that could change how we approach game development and player interaction at a design level. User-generated content takes on a new dimension with this. Players could potentially describe their ideal levels and watch them come to life in real time. For example, a player could input "create a castle level with lava pits and flying enemies," and the AI would generate a unique, playable level matching that description. This level of customization could lead to entirely new genres of user-generated content games. With this AI-Assisted game design developers could use similar models to rapidly prototype and iterate on game concepts. Imagine a game designer inputting a series of level descriptions and receiving fully realized, playable prototypes within minutes. This could dramatically speed up the game development process and allow for more experimentation in design. The ability to generate infinite, coherent gameplay could fundamentally change our perception of game longevity and replayability. Using this technology, a roguelike game can create unique dungeons for each playthrough, ensuring no two gaming sessions are the same. The AI would create a unique layout for each new playthrough, complete with custom enemy placements, item distributions, and even micro-narratives. This ensures that every gaming session offers a fresh, unpredictable experience, significantly enhancing replayability and player engagement. This could extend the lifespan of games indefinitely, providing a constant stream of fresh content for players. By tokenizing this technology, community members could invest in and shape the development of such AI models. Token holders might vote on which game franchises to adapt next, or contribute to training data by playing and rating generated levels. This approach could usher in a new era of community-driven game development, where players have a direct stake in the evolution of their favorite games. The technology could be expanded to generate assets that work seamlessly across multiple games. Think of an AI creating a character or item that integrates flawlessly into different game worlds, from 2D platformers to 3D RPGs. This could lead to a more unified and immersive gaming ecosystem, where players' achievements and assets have value across a wide range of gaming experiences. As Virtuals Protocol continues to refine this technology and expand its applications, projects like MarioVGG are paving the way for a future where the lines between game developers, players, and AI become increasingly blurred, promising new forms of interactive entertainment limited only by our imagination. To fully grasp the potential of this approach, let's dive deeper into how Virtuals Protocol and its inner workings. **Permissionless Utilization of VIRTUAL Agents** A key feature of the Virtuals Protocol's technical architecture is its permissionless utilization model, designed to facilitate the seamless integration of AI agents into various applications and platforms. This system enables developers and users to access and deploy VIRTUAL agents with maximum flexibility and minimal barriers to entry. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/9f617f7b5426.jpg) Implications and Future Potential: The realization of Parallel Hypersynchronicity enables some interesting scenarios in human-AI interaction. Imagine an AI agent that serves as a personal assistant in a productivity app, a teammate in a multiplayer game, and a tutor in an educational platform—all while maintaining a consistent personality and shared memory of interactions. This technology could revolutionize fields like customer service, where an AI agent could provide seamless support across phone, chat, email, and in-person interactions, always building upon previous engagements. In entertainment, it could lead to deeply immersive experiences where AI characters in games or virtual worlds exhibit complex, evolving personalities that persist across multiple titles or platforms. However, achieving this level of AI sophistication also raises important questions about data privacy, AI ethics, and the potential societal impacts of such pervasive AI presence. As Virtuals Protocol continues to develop this technology, addressing these concerns will be crucial for widespread adoption and acceptance. ## Case Study: Virtuals AI Idols on Tiktok Virtuals Protocol's AI-dol band, consisting of Luna (lead), Olyn, and Iona, serves as a prime example of the protocol's revenue-generating ecosystem in action. The AI-dol band is a group of AI-powered virtual influencers created using Virtuals Protocol. Each member – Luna, Olyn, and Iona – has a unique personality, style, and fan base. They primarily operate on TikTok, using the platform's vast user base and engagement-driven algorithm. With over 500K TikTok followers and 9.5M+ likes, the AI-powered virtual influencer group is  making an impression on the digital engagement landscape, by capitalizing upon the popularity of Virtual [YouTubers](https://en.wikipedia.org/wiki/VTuber) (VTubers). ![AI-dol band on TikTok](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/ea7a36ec8f5d.png) It addresses a critical gap in the VTuber market: creating personalized fan relationships at scale. Unlike human-operated VTubers, AI-DOL retains every fan interaction, enabling deep, individualized connections with unlimited fans simultaneously. This model showcases how AI agents can create and monetize content, engage audiences, and build communities – all autonomously and at scale. These agents will not just be tools, but become active participants in the digital economy, capable of generating value and fostering genuine connections. As AI-DOL aims to become the AI counterpart to traditional VTuber agencies like Hololive, it's paving the way for a new era of digital interaction. ### Monetizing Attention with AI Agents. 1:1 DMs >> Push Notifications? The rise of AI agents, particularly in the domain of virtual influencers like Virtuals Protocol's AI-dol band, represents a unique way of capturing and monetizing user attention. Consider these striking numbers: - Luna, the AI character on TikTok, generates around $700 per stream. - The PocketWaifuGame made over $20,200 in revenue and crossed 100K users in just 13 days. That’s a $5.2 ARPU with $0 spent on marketing. ![link to post](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/31327b12dcc0.jpg) These AI entities not only engage users on platforms like TikTok but also enable deeper, personalized interactions through channels such as Telegram. This dual strategy enhances user engagement and opens up new revenue streams. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/f0130c742631.jpg) Luna's journey from TikTok sensation to personal chat companion shows an important evolution in marketing and capturing attention. While TikTok serves as an excellent top-of-funnel platform for awareness, the transition to one-on-one Telegram chats marks a significant leap in user engagement. This shift from parasocial to personal interactions addresses a key challenge in digital marketing: creating meaningful, individualized connections at scale. The transition to personal chats opens up novel monetization avenues. Traditional push notifications are often ignored, but messages from a 'friend'—in this case, an AI agent—are more likely to be read and acted upon. Historically, digital marketing has focused on capturing attention through algorithms designed to maximize engagement. However, there is a significant shift toward fostering more intimate connections with users at this age. This transition is critical for brands aiming to cultivate loyalty and drive conversions in an increasingly crowded marketplace. 1. **Personalized Interactions:** Unlike traditional push notifications that often go unnoticed, messages from AI agents can feel more like communications from friends. This personal touch increases the likelihood of engagement and action. 2. **Scalable Conversations:** AI agents can handle millions of simultaneous interactions, providing personalized experiences at scale—something human influencers cannot achieve. 3. **24/7 Availability:**The always-on nature of AI agents ensures that user engagement is consistent, reducing response times and enhancing customer satisfaction. Perhaps the most revolutionary aspect is the potential for AI agents to become publishers in their own right. With a direct line to millions of users, each AI agent becomes a powerful distribution channel. Apart from the AI-doll band and the Roblox Westworld game, a few more AI agents are being built on the Virtual Protocol. AI Waifu is a fantasy companion chat with over 300 AI characters, engaging 200,000+ users through user-generated content and immersive storytelling. The Heist, an upcoming project, aims to demonstrate VIRTUAL Agents' capabilities in managing on-chain transactions within a game economy. Sanctum, a 3D AI-RPG, features intelligent gacha heroes and a dynamic world managed by a "God AI Agent," promising personalized, evolving gameplay. ![Sanctum Agent](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/ea7318f4b735.jpg) Despite being a young team (started in January 2024), Virtuals has made impressive progress in both application development and research. Their portfolio includes: 1. **MarioVGG**: As you saw, the study on video generative models for creating interactive video games. 2. **Project Westworld**: The first playable autonomous world on Roblox, pushing the boundaries of AI-driven gaming experiences. 3. **Audio-to-Animation (A2A)**: Advanced research into audio-driven animation, opening new possibilities for AI-human interactions. These diverse projects illustrate Virtuals Protocol's potential as a launchpad for AI agents across various domains. By opening the platform to third-party developers, Virtuals is positioning itself to become a central ecosystem for AI agent creation and deployment. Much like the way  pump.fun revolutionized memecoin launches, Virtuals Protocol could transform how AI agents are developed, monetized, and integrated into applications, fostering innovation and creating new opportunities in the AI-driven digital landscape. ## $VIRTUAL Tokenomics: Powering the AI Agent Economy At the centre of Virtuals Protocol lies the $VIRTUAL token, designed to fuel the deployment and utilization of AI agents. This token structure aims to be a self-sustaining, deflationary ecosystem that aligns the interests of users, developers, and investors. But Virtuals isn't building just another infrastructure without any adoption – they're actively generating revenue across multiple platforms. From TikTok livestreamers to AI Waifu and Roblox integrations, the team has established a robust ecosystem that's already monetizing AI agents in diverse, engaging ways. $VIRTUAL serves as the backbone of the Agent Economy, with every AI agent token paired with $VIRTUAL in its liquidity pool. This symbiotic relationship ensures that individual agent success bolsters the entire protocol's value, creating a rising tide that lifts all boats. The creation of new agents locks up $VIRTUAL tokens in these liquidity pools, naturally squeezing the supply and potentially driving up value over time. Moreover, $VIRTUAL acts as a gateway for purchasing agent tokens, securing a constant demand flow similar to how ETH is essential for transactions on Ethereum but tailored for an AI-driven ecosystem. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/4d185dc945b1.jpg) The on-chain economics of Virtuals Protocol come to life through several key mechanisms. Users pay for AI services in real-time using $VIRTUAL, creating a direct and transparent value flow from users to agents. As AI agents earn, revenue flows in a continuous stream of $VIRTUAL tokens, providing a visible and auditable trail of value generation. Perhaps most intriguingly, revenue earned by agents is put to work through a buyback and burn mechanism. This process creates a deflationary effect on agent tokens, potentially boosting the value of remaining tokens and establishing a virtuous cycle of value creation and capture. ![](https://shoal.xyz/research/writing/virtuals-protocol-launching-ai-agents/img/47a51af4ac11.jpg) Token Distribution: 1. 60% (600,000,000 tokens): In public hands, fostering liquidity and adoption. 2. 5% (50,000,000 tokens): Powering the liquidity pools. 3. 35% (350,000,000 tokens): Ecosystem treasury, growth and development.Controlled by a DAO multi-sig for true decentralization.Maximum 10% annual emission for 3 years, subject to community approval. ## Becoming the Launchpad for AI Agents Virtuals Protocol emerges as a key player in the AI revolution, reimagining how we create, deploy, and monetize AI agents. By transforming these agents from tools to revenue-generating assets, Virtuals establishes a sustainable economic model for AI development. Its tokenomics ensures value flows to all ecosystem participants while enabling AI agents to operate across multiple applications, exponentially increasing their income potential. The protocol's venture studio approach accelerates adoption by demonstrating real-world applications across gaming, entertainment, and social platforms. As Virtuals opens its platform to third-party developers, it's well positioned to become the launchpad for the next wave of AI innovation, catalyzing a wave of AI-powered applications across sectors. This shift is democratizing AI, making agent creation and monetization as accessible as launching a memecoin or even making a website. A new digital economy is emerging – a marketplace of evolving, value-generating AI agents. This redefines user-AI interaction, moving from passive tools to active, revenue-generating digital entities. Looking forward, if Virtuals can successfully bootstrap an early community of developers launching agents, we might see more solutions for launching agents integrated with Virtuals or similar platforms. Expect companies like Theoriq, Talus, or other AI agent platforms, even ones like Ritual, to potentially plug into these types of platforms that allow you to speculate on agents and share in the revenues of agents across chains. The implications are profound. As AI agents become more integrated into our lives, the line between human and artificial intelligence blurs, opening unprecedented opportunities for innovation and interaction. Success in this landscape will hinge on adaptability and foresight. Those who leverage platforms like Virtuals Protocol will shape the future of technology and society. ### References 1. **Pump.fun achieves $100M in cumulative revenue amid rising criticism and market challenges**. (2024, September 3). *SolanaFloor*. Retrieved from[https://solanafloor.com/news/pump-fun-achieves-100-m-in-cumulative-revenue-amid-rising-criticism-and-market-challenges](https://solanafloor.com/news/pump-fun-achieves-100-m-in-cumulative-revenue-amid-rising-criticism-and-market-challenges) 2. **Exploring Pump.fun: How to create your memecoins**. (2024, July 11). *KuCoin*. Retrieved from[https://www.kucoin.com/learn/web3/exploring-pump-fun-how-to-create-your-memecoins](https://www.kucoin.com/learn/web3/exploring-pump-fun-how-to-create-your-memecoins) 3. **Publisher exchanges, consumer applications, and the attention theory of value**. (2024, March 12). *Multicoin Capital*. Retrieved from[https://multicoin.capital/2024/03/12/publisher-exchanges-consumer-applications-and-the-attention-theory-of-value/](https://multicoin.capital/2024/03/12/publisher-exchanges-consumer-applications-and-the-attention-theory-of-value/) 4. ***pump.fun*****.** [@hashed_official] (2024). Dune.com. Retrieved from: [https://dune.com/hashed_official/pumpdotfun](https://dune.com/hashed_official/pumpdotfun) 5. ***Pump.fun Analysis | Flipside*****. [@hrst79]** (2024). Flipsidecrypto.xyz. Retrieved from: [https://flipsidecrypto.xyz/hrst79/pump.fun-analysis-y4l427](https://flipsidecrypto.xyz/hrst79/pump.fun-analysis-y4l427) 6. **Lin, L. [@ljin18].** (2024, April 11). [Tweets]. *X (formerly Twitter)*. Retrieved from:[https://x.com/ljin18/status/1778485363809435660](https://x.com/ljin18/status/1778485363809435660)[https://x.com/ljin18/status/1777479238540771507](https://x.com/ljin18/status/1777479238540771507)[https://x.com/ljin18/status/1774925473450975660](https://x.com/ljin18/status/1774925473450975660) 7. **The case for AI agents in Web3 gaming**. (2024, June 25). *Shoal*. Retrieved from[https://www.shoal.gg/p/the-case-for-ai-agents-in-web3-gaming](https://www.shoal.gg/p/the-case-for-ai-agents-in-web3-gaming) 8. **Elon Musk's Twitter overhaul could be huge for DOGE and crypto generally**. (2023, July 25). *CoinDesk*. Retrieved from[https://www.coindesk.com/business/2023/07/25/elon-musks-twitter-overhaul-could-be-huge-for-doge-and-crypto-generally/](https://www.coindesk.com/business/2023/07/25/elon-musks-twitter-overhaul-could-be-huge-for-doge-and-crypto-generally/) 9. **The case for compute DePINs**. (2024, June 11). *Shoal*. Retrieved from[https://www.shoal.gg/p/the-case-for-compute-depins](https://www.shoal.gg/p/the-case-for-compute-depins) 10. **The convergence of AI, DeFi, and intents**. (2024, May 17). *Shoal*. Retrieved from[https://www.shoal.gg/p/the-convergence-of-ai-defi-and-intents](https://www.shoal.gg/p/the-convergence-of-ai-defi-and-intents) 11. **Virtuals Whitepaper**. (n.d.). *Virtuals.io*. Retrieved from [https://whitepaper.virtuals.io/](https://whitepaper.virtuals.io/) 12. Virtuals Protocol. (2024, September). **VideoGameGen**. Retrieved from[https://huggingface.co/virtuals-protocol/mario-videogamegen/blob/main/VideoGameGen.pdf](https://huggingface.co/virtuals-protocol/mario-videogamegen/blob/main/VideoGameGen.pdf) 13. EverythingEmpty [@everythingempt0]. (n.d.). [Tweet]. *X (formerly Twitter)*. Retrieved from[https://x.com/everythingempt0/status/1839592761907163241](https://x.com/everythingempt0/status/1839592761907163241) 14. Virtual Protocol. (n.d.). **Westworld AI**. Retrieved from[https://virtual-protocol.github.io/westworld-ai/](https://virtual-protocol.github.io/westworld-ai/) *A big shoutout to David for the edits and Vlad for creating the infographics.* --- ***Not financial or tax advice.**The purpose of this post is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Virtuals Protocol. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent.* *Team members purchased a small amount of $LUNA tokens shortly after the official protocol launch in order to participate in and evaluate the v2 product for research purposes. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Polymarket and the Proliferation of Prediction Markets > How Decentralized Prediction Markets such as Polymarket Are Reshaping Forecasting and Decision-Making in the Digital Age - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2024-10-08 - Canonical: https://shoal.xyz/research/writing/prediction-markets/ - Keywords: crypto, DeFi, prediction markets, Ethereum ![](https://shoal.xyz/research/writing/prediction-markets/img/d1ba265130d0.jpg) ### Key Takeaways: - **Growth and Influence of Prediction Markets:** Prediction markets are increasingly recognized for their ability to leverage collective intelligence to forecast future events, significantly impacting fields such as politics, finance, entertainment, and pop culture. - **Technological Advancements Driving Adoption:**The integration of blockchain technology, along with aspects of both decentralized finance (DeFi) and decentralized social media (SocialFi), has revolutionized prediction markets, transparency, cultural relevance, and accessibility. - **Polymarket's Success Story:** Polymarket stands out as a leading prediction market platform, attracting significant liquidity and user engagement due to its innovative features, strategic partnerships, and strong endorsements from industry leaders like Vitalik Buterin. - **Impact on the 2024 US Presidential Election:**Prediction markets have played a crucial role in shaping public perception and media coverage of the 2024 US presidential election, providing real-time data that offers a more dynamic—and remarkably accurate—picture far before traditional polls can capture the same sentiment. - **Challenges and Regulatory Landscape:**Despite their potential, prediction markets face significant challenges, including technical scalability, security concerns, and navigating complex regulatory environments, particularly in the United States. - **Future Prospects and AI Integration:** The future of prediction markets looks promising, with the potential for user-sourced market curation, advances in Oracle technologies, and the integration of artificial intelligence to enhance market creation, liquidity management, and dispute resolution. *Note: This research was conducted between July and September 2024. Please keep in mind that political circumstances change quickly, so some details may change over time.* ## Introduction The internet is many things to many people, and there are innumerable arguments for and against its ubiquity in our daily lives. However, there is no denying that the Internet is history's most effective collective action tool. It has enabled instantaneous communication across continents, crowdfunded seemingly [uninvestable ideas](https://www.ranker.com/list/weirdest-things-to-get-crowdfunded/anncasano), and helped keep economies afloat as lockdown mandates spread globally in tandem with the Coronavirus pandemic. With all the boundaries the internet has helped humanity breach, is it too far-fetched to believe that it can also help humanity predict the future? Prediction markets are a powerful testament to the internet's ability to aggregate collective wisdom and provide insights into future events. These markets, which allow individuals to bet on the outcomes of various events, leverage participants' diverse knowledge and opinions to generate highly accurate predictions. As these markets grow in popularity and liquidity, they are increasingly recognized for their potential to serve as reliable sources of foresight in fields ranging from politics to insurance, finance, entertainment, and beyond—practically any industry can benefit from more comprehensive datasets. In recent years, prediction markets have witnessed accelerated growth, driven by structural factors such as the democratization of information and technological advancements and idiosyncratic factors exemplified by platforms like [Polymarket](https://polymarket.com/). Polymarket, the leading prediction market platform by volume, serves as a compelling case study for understanding the forces propelling the proliferation of prediction markets and their emerging role in modern society. As underscored in a [July 2nd tweet](https://x.com/VitalikButerin/status/1808092065483436481) by Ethereum co-founder Vitalik Buterin, “Prediction markets and Community Notes are becoming the two flagship social epistemic technologies of the 2020s,” this reinforces his [long–standing public praise](https://vitalik.eth.limo/general/2024/01/30/cryptoai.html) for prediction markets as the “holy grail” technology that, if executed properly, can finally usher in a democratized source of truth. This paper will delve into the accelerating growth of prediction markets, examining both the structural drivers and unique aspects that have led to Polymarket's dominant position. ### The 2024 US Presidential Election Cycle The 2024 US presidential election cycle has become a pivotal event for prediction markets, illustrating their growing influence and reliability. Leading up to the election, the political landscape has been marked by significant shifts, controversies, and public interest, all of which have been mirrored in the activity on prediction platforms like Polymarket. Detailed Overview of the Political Landscape The political landscape for the 2024 election has been dynamic and volatile. Key events have included President Joe Biden's decision to withdraw from the race, Vice President Kamala Harris stepping up as the Democratic frontrunner, and former President Donald Trump's dominance in the Republican primaries. These developments have kept prediction markets bustling with activity as users place bets based on their expectations and insights. Polymarket, for instance, has provided real-time odds on these political dynamics, reflecting shifts in public sentiment and media coverage. When Biden announced his withdrawal and endorsed Harris, Polymarket saw a surge in bets favoring Harris as the Democratic nominee. This shift was not only a reflection of Biden's endorsement but also a response to Harris's growing support within the Democratic Party and among influential political figures. On Polymarket, Harris’s odds have seen a significant increase, reflecting her strengthened position in the Democratic Party. As of late July 2024, Polymarket users gave Harris a 92% chance of securing the Democratic nomination, following Biden's endorsement and her rising support from top Democrats. Harris's odds of winning the popular vote were nearly tied with Trump, with Harris at 44% and Trump at 45%. In contrast, Trump has maintained a strong lead in the Republican primaries, with Polymarket consistently favoring him to win the presidency. As of July 2024, Trump had a 64% chance of winning, compared to Harris’s 34%. Trump's dominance in key swing states like Georgia, Arizona, and Pennsylvania has solidified his position as the frontrunner. Influence on Public Perception and Media Coverage Prediction markets like Polymarket have significantly influenced public perception and media coverage of the 2024 election. These markets offer a continuous stream of data that reflects the collective wisdom of a diverse group of participants. As such, they provide a more nuanced and real-time picture of the electoral landscape compared to traditional polling methods. For example, Polymarket's odds tracking on the 2024 presidential race was [highlighted by prominent investment research firm, Bernstein Research](https://decrypt.co/237815/polymarket-worlds-largest-2024-presidential-election-prediction-pool-bernstein), due to the platform's growing influence in shaping public perception of the viability of each candidate. When Trump's odds fluctuated on platforms like Polymarket and PredictIt [following various political events](https://www.ft.com/content/16013deb-68b5-409c-80c6-ce899293fe6c), media outlets readily utilized such data in their reporting on the status of the horse race. This real-time feedback loop between prediction markets and media coverage has created a more dynamic and interactive environment for political analysis. ![](https://shoal.xyz/research/writing/prediction-markets/img/53f680d31987.jpg) In  particular, the media has highlighted the role of prediction markets in capturing the impact of unexpected events. For instance, [Polymarket accurately predicted President Joe Biden’s withdrawal](https://fortune.com/2024/07/25/forget-pundits-polls-internet-prediction-markets-anticipated-biden-withdrawal-weeks-ago-crypto-elections-finance-politics/) from the race, with the market pricing a 66% chance of Biden dropping out, post-debate, even while he publicly denied it. This prediction was later validated when Biden officially announced his withdrawal, showcasing the market’s ability to provide accurate forecasts of future events at a pace in which mainstream political punditry and traditional polling cannot compete with. ![](https://shoal.xyz/research/writing/prediction-markets/img/e7f292840d8a.jpg) Moreover, the rise of Trump-inspired memecoins, which surged in value in the immediate aftermath of the assassination attempt (in lockstep with betting market odds of a Trump victory), further reinforces the intersection of political speculation and cryptocurrency trends. These gains have since reversed in true speculative fashion, with the price of the TRUMP ($MAGA) token ending the month of July down nearly 20% from where it began on July 1st – possibly a reflection of [Kamala Harris’ growing chances of winning](https://www.morningstar.com/news/marketwatch/2024072466/kamala-harris-surges-in-the-betting-markets-and-i-bet-kamalaphoria-has-more-room-to-run) the race.  This phenomenon is just another manifestation of the broader memecoin craze that has garnered significant media attention, and is arguably a main driver of the uptick in altcoin prices (Solana in particular) over the past ~18 months. Growing Role of Prediction Markets in US Politics Prominent political analysts, influencers, and data scientists have played crucial roles in shaping the activity on prediction markets. Poker-playing statistician [Nate Silver’s involvement with Polymarket](https://x.com/shayne_coplan/status/1813262050593755432), following a [$45 million Series B funding round](https://www.theblock.co/post/294367/polymarket-raises-45-million-from-peter-thiels-founders-fund-vitalik-buterin-and-others) led by Peter Thiel’s Founders Fund in May 2024, has been particularly noteworthy. Silver’s analytical prowess and reputation for accurate – [at times contrarian](https://www.vox.com/2016/11/3/13147678/nate-silver-fivethirtyeight-trump-forecast) – predictions have enhanced the platform’s credibility, drawing more participants and media attention. This partnership highlights the intersection of traditional political analysis and innovative prediction market technologies. These high-profile endorsements and strategic partnerships have further solidified Polymarket’s position as a leading prediction market. The platform’s ability to attract significant volume, investments, and collaborations with influential figures has contributed to its growth and acceptance as an increasingly effective forecasting tool, particularly in regard to US politics and geopolitical events. Specific Examples of Market Influence One notable example of prediction markets influencing public perception is the betting activity surrounding Vice President Kamala Harris. Following endorsements from Biden and other Democratic leaders, Harris’s odds on Polymarket surged, significantly narrowing the gap with Trump within a week. This shift reflected the immediate consolidation of support around Harris and captured the renewed enthusiasm for her candidacy, demonstrated by [record-breaking fundraising shortly after](https://www.npr.org/2024/08/02/g-s1-14927/kamala-harris-fundraising#:~:text=Vice%20President%20Harris'%20presidential%20campaign,the%20likely%20Democratic%20presidential%20nominee.). Traditional polls cannot capture the impacts of sudden events in real-time, so political analysts and pundits quickly highlighted the dramatic change in betting odds. The relationship between betting markets and the media’s insatiable appetite for real-time updates creates a flywheel effect, amplifying the prominence of prediction markets in public discourse. Similarly, Polymarket’s handling of the Republican primaries has provided valuable insights into the fluctuating fortunes of various candidates. Trump’s dominance in these markets has often been juxtaposed with the challenges faced by other Republican contenders, offering a real-time barometer of his continued influence within the party. Moreover, the interplay between prediction markets and social media has amplified their impact. Political influencers and analysts frequently share updates from prediction markets on platforms like Twitter, further disseminating this information and shaping public discourse. This interaction between prediction markets and social media underscores the growing integration of digital tools in political forecasting and public engagement. ## The Rise of Prediction Markets ![](https://shoal.xyz/research/writing/prediction-markets/img/f1fefb2ce5b9.jpg) Prediction markets have a storied history, evolving from rudimentary beginnings into sophisticated, blockchain-powered platforms that leverage collective intelligence to forecast future events. This section delves into the historical development of prediction markets, the technological advancements that have propelled their growth, and case studies that highlight their impact on decision-making across various fields. ### Historical Development of Prediction Markets While there exist physical records of political wagers dating as far back as the [1503 papal elections](https://nottingham-repository.worktribe.com/preview/1421329/forcasting%20the%20outcome%20of%20closed%20door.pdf), the emergence of modern prediction markets occurred in the late 20th century, with early experiments testing the hypothesis that markets could aggregate dispersed information more effectively than individual experts. One of the earliest and most notable examples of a prediction market that reached some mainstream appeal is the Iowa Electronic Markets (IEM), which began as the Iowa Political Stock Market in 1988. Founded by economists at the University of Iowa, this market allowed participants to buy and sell contracts based on political outcomes, such as the share of votes a candidate would receive. The IEM quickly demonstrated its value by outperforming traditional polls in predicting election outcomes. In the 1988 presidential election, the market’s closing prices closely matched the actual vote shares of George H. W. Bush and Michael Dukakis, surpassing the accuracy of major polls. This success underscored the potential ability of prediction markets to aggregate and reflect collective intelligence more accurately than conventional methods. Robin Hanson, a pivotal figure in the development of prediction markets, proposed the idea of ["idea futures"](https://mason.gmu.edu/~rhanson/ideafutures.html) or "policy markets" in the early 1990s. Hanson's vision was to create markets where individuals could bet on the outcomes of policy decisions, thereby generating valuable information that could inform public and private decision-making. His work laid the theoretical foundation for modern prediction markets, emphasizing their potential to provide unbiased, continuously updated estimates of future events. ### Historical Examples of Prediction Markets Several prediction markets have successfully leveraged these technological advancements to become influential tools for decision-making. Here are some notable examples: - **Iowa Electronic Markets (IEM)**: The IEM has been a pioneer in demonstrating the predictive power of markets. It has consistently outperformed traditional polls in forecasting the outcomes of US presidential elections. A study [published in the Scientific American](https://mason.gmu.edu/~rhanson/PAM/PRESS/ScientificAmerican-3-08.pdf) comparing the IEM's performance from 1988 to 2004 found that the market was closer to the actual election results 74% of the time compared to major polls. The IEM has also expanded its scope to include markets on economic indicators and international elections, providing valuable insights across a range of domains. - **Hollywood Stock Exchange (HSX)**: The HSX is a virtual market where participants trade shares in movies, actors, and other entertainment properties. The market’s prices have been shown to accurately predict box office performance and award winners, demonstrating the utility of prediction markets in the entertainment industry. - **Policy Analysis Market (PAM)**: Developed by the Defense Advanced Research Projects Agency (DARPA), the PAM was designed to forecast geopolitical events by allowing participants to trade futures contracts based on their predictions. Although it was eventually canceled due to political controversy, the PAM highlighted the potential of prediction markets to inform national security and policy decisions. PAM aimed to aggregate dispersed information about geopolitical risks, including terrorist attacks and political instability, and provide actionable insights for policymakers. Despite its short lifespan, PAM's concept has influenced subsequent developments in prediction markets and their applications in public policy. - **Intrade**: Intrade, which operated from 1999 to 2013, was another significant player in the prediction market space. It allowed users to trade on various events, including political outcomes, economic indicators, and even weather forecasts. During its operation, Intrade successfully predicted the outcomes of several high-profile events, including the 2008 US presidential election, where it accurately predicted Barack Obama's victory. ### Technological Advancements Enabling Growth The rise of blockchain technology and decentralized finance (DeFi) has revolutionized prediction markets, addressing many of the limitations of earlier platforms. Blockchain technology offers several key advantages that have catalyzed the growth of prediction markets: - **Decentralization**: Blockchain ensures that prediction markets operate without central control, reducing the risk of manipulation and increasing trust among participants. Decentralized platforms like Augur and Gnosis enable users to create and trade on markets without relying on a central authority. - **Transparency**: Blockchain provides a transparent ledger of all transactions, enhancing trust and accountability. Smart contracts automate the execution of trades and the distribution of rewards, ensuring that outcomes are determined fairly and transparently. - **Security**: Blockchain's cryptographic security mechanisms protect against fraud and hacking, making prediction markets safer for participants. - **Accessibility**: Blockchain lowers barriers to entry, allowing anyone with internet access to participate in prediction markets. This democratization of access has expanded the pool of participants, enriching the information aggregated by these markets. The integration of smart contracts has further enhanced the functionality of prediction markets. Smart contracts are self-executing agreements with the terms of the contract directly written into code. They automatically enforce the rules and distribute rewards based on the outcomes of events, reducing the need for intermediaries and increasing efficiency. ### Impact on Decision-Making Prediction markets have had a profound impact on decision-making in various fields by providing accurate, real-time forecasts based on the collective wisdom of participants. Here are some examples of their influence: - **Political Forecasting**: Prediction markets have become valuable tools for political analysts and campaign strategists. By aggregating diverse opinions and responding quickly to new information, these markets often provide [more accurate forecasts](https://www.researchgate.net/publication/282123487_PREDICTION_MARKETS_VS_POLLS_-_AN_EXAMINATION_OF_ACCURACY_FOR_THE_2008_AND_2012_US_ELECTIONS) than traditional polls. For instance, during the 2008 US presidential election, prediction markets accurately predicted the outcomes of key primaries and the general election, outperforming [top expert forecasts](https://mickbransfield.com/2023/12/02/ray-fair-vs-iowa-electronic-markets/). - **Corporate Decision-Making**: Companies use prediction markets to forecast product demand, assess market trends, and make strategic decisions. For example, Google has used internal prediction markets to forecast product launch dates and assess the success of new initiatives. By leveraging the insights of employees, companies can make more informed decisions and identify potential risks and opportunities. - **Public Policy**: Policy markets, as envisioned by Robin Hanson, have the potential to inform public policy decisions by providing unbiased estimates of the outcomes of different policy options. For example, a policy market could estimate the impact of a proposed tax change on economic growth, helping policymakers make evidence-based decisions. ## Structural Factors Driving Growth of Prediction Markets The proliferation of prediction markets is driven by several structural factors that collectively contribute to their growth and influence. - **Decentralization and Trustless Systems**: Prediction markets benefit from decentralization, which reduces the risk of manipulation and increases trust among participants. Decentralized platforms like Augur and Gnosis use blockchain technology to ensure that markets operate without central control. This transparency is crucial in building user confidence. Decentralization also enhances security. Blockchain’s cryptographic mechanisms protect against fraud and hacking, making these markets safer for participants. - **Increased Accessibility and User Participation**: User-friendly interfaces and lower barriers to entry have democratized participation in prediction markets. Blockchain lowers the technical and financial barriers, allowing anyone with internet access to participate. This broadens the pool of participants, enriching the information these markets can aggregate. For example, the [Iowa Electronic Markets (IEM)](https://iem.uiowa.edu/iem/) demonstrated that markets could aggregate and reflect collective intelligence more accurately than traditional methods. The IEM has consistently outperformed polls in predicting US presidential elections, showing higher accuracy in 74% of cases from 1988 to 2004. - **Democratization of Information**: The rise of populism and public backlash against perceived elites have fueled interest in platforms that democratize access to information and decision-making. Prediction markets allow a diverse group of participants to contribute their knowledge and insights, creating a more comprehensive and inclusive forecasting tool. This democratization is evident in the growth of political prediction markets, where users can bet on election outcomes. These markets often provide more accurate forecasts than traditional polls, reflecting a broader range of perspectives. - **The Financialization of Everything Era**: The trend of financializing various aspects of life has extended to prediction markets, where individuals can speculate on a wide range of outcomes, from political events to cultural phenomena. This trend has attracted a new generation of users who are comfortable with the idea of financial speculation as a form of engagement and entertainment. The success of platforms like the [Hollywood Stock Exchange (HSX)](https://www.hsx.com/), where participants trade shares in movies and actors, demonstrates the appeal of prediction markets beyond traditional financial sectors. ### Interplay Between Structural Factors The interplay between these structural factors creates a synergistic effect that accelerates the growth and adoption of prediction markets. For instance, decentralization enhances security and transparency, which in turn boosts user trust and participation. Increased accessibility allows more individuals to engage with these markets, enriching the pool of collective intelligence. The democratization of information ensures that a wide range of perspectives is considered, leading to more accurate predictions. Finally, the financialization trend attracts new users who bring different insights and knowledge to the markets. Comparison to Traditional Polling Over extended time horizons, prediction markets have demonstrated higher accuracy compared to traditional polling methods. For example, the IEM has been more accurate than polls in predicting US presidential election outcomes in 74% of cases from 1988 to 2004. In contrast, traditional polls often fail to capture the full spectrum of voter sentiment and can be influenced by various biases. Polling methods typically rely on representative samples to gauge public opinion, but these samples can be skewed by non-response bias, sampling errors, and other factors. Prediction markets, on the other hand, aggregate the collective wisdom of a diverse group of participants who have financial incentives to provide accurate information. This leads to more reliable forecasts that reflect the true probability of outcomes. Moreover, prediction markets and polls can complement each other to provide a more comprehensive picture of reality. While polls measure voter preferences at a specific point in time, prediction markets reflect the aggregated expectations of participants about future outcomes. By combining insights from both methods, analysts can gain a deeper understanding of electoral dynamics and public sentiment. Role of Social Media and Online Communities Social media and online communities play a crucial role in driving participation and engagement in prediction markets. Platforms like Twitter, Reddit, and specialized forums provide spaces for users to discuss and share information about prediction markets, influencing public perception and attracting new participants. For example, during the 2024 US presidential election cycle, Polymarket and other prediction platforms have seen increased engagement from users sharing their market positions and discussing political developments on social media. This real-time exchange of information helps to create a dynamic feedback loop, where market prices are continuously updated based on the latest news and insights. Online communities also foster a sense of belonging and competition among participants, encouraging them to stay engaged and contribute their knowledge. This collective participation enriches the information available to prediction markets, leading to more accurate forecasts. ## dApp Spotlight: Polymarket It’s no accident that Polymarket is well-positioned for growth. A deeper look at the evolution of the platform reveals the key backers, innovative features, and strong user engagement that propel its ongoing success. ### Founding and Early Development Polymarket was founded in 2020 by Shayne Coplan, with the vision of creating a decentralized platform for betting on real-world events. As a blockchain-enabled platform, Polymarket offers transparency, security, and permissionless accessibility, setting itself apart from traditional prediction markets often hampered by financial regulations tied to typical forms of capital flows rather than cryptocurrency. The platform successfully raised $70 million from notable investors, including Peter Thiel’s Founders Fund and Ethereum creator Vitalik Buterin. This substantial financial backing has been crucial for Polymarket's rapid growth and development. Vitalik Buterin has been a long-time proponent of prediction markets and has often highlighted Polymarket as an example of successful user experience (UX) improvements and a product with strong market fit. These factors have driven better mainstream adoption of a Web3 decentralized application, which is rarely seen without excessive reward incentives. Buterin's endorsement of Polymarket is significant, given his reputation for predicting the evolution of technology well before the mainstream takes notice. His support provides additional confidence in Polymarket's future success. In May 2024, Buterin participated in Polymarket's Series B funding round, further solidifying his commitment to the platform. In a reply to Polymarket’s tweet on July 19th, [Buterin praised the platform's](https://x.com/VitalikButerin/status/1815097367038943489) idiosyncratic successes, stating, "Really impressive showing from you guys. Not just *predicting the outcomes well in advance*, but also (through making conditional odds of different candidates visible) serving as an active input into *collective decision making*." In July 2024, Polymarket gained significant attention by hiring Nate Silver, a renowned statistician and founder of FiveThirtyEight, as an advisor. This strategic move enhanced the platform's credibility and reinforces the overall view that prediction markets are gaining traction, while further solidifying Polymarket as the leading prediction market platform. ### Operational Mechanics Polymarket functions as a decentralized prediction market where users can trade shares on various events' outcomes, including political elections, sports, and cultural happenings. The platform employs blockchain technology to ensure a secure, non-custodial environment where transactions are transparent and immutable. - **Market Curation**: Users can propose new markets, which are then reviewed and curated by the platform’s moderators to ensure relevance, clear definitions, and binary outcomes. - **Placing Bets**: Participants buy shares in favor of or against a particular outcome. Each market operates with binary options like "Yes" or "No". Share prices reflect the market's consensus on the outcome's likelihood. For instance, if shares of the “YES” outcome option are priced at $0.60, the market estimates a 60% probability of that outcome. - **Consensus and Resolution**: Polymarket uses optimistic oracles via [UMA Protocol](https://uma.xyz/) to verify event outcomes. These trusted data sources provide the necessary information to settle bets by collecting data from off-chain sources (e.g., news outlets and public records). Once an event concludes, the oracle reports the outcome to the blockchain, where smart contracts automatically resolve the market and distribute winnings. - **Payouts**: Participants holding shares in the correct outcome receive payouts proportional to their holdings, facilitated by smart contracts that ensure fair and transparent fund distribution. - **Liquidity Providers and Market Makers**: Polymarket uses a Central Limit Order Book (CLOB) and Fixed Product Market Makers (FPMMs) to maintain liquidity and facilitate trading. Liquidity providers also earn rewards from the transaction fees paid by traders. When users provide liquidity for an event, they receive an economic reward of 2% of each transaction amount. The closer the liquidity provision price is to the final transaction price, the greater the reward. Users must pay an additional 2% to the pool if they close a contract before a market resolves (aka prior to a market reaching an event-driven resolution). - **Fees:**Polymarket currently does not charge additional fees for trading (as of this writing), though Polymarket states in its docs that this is subject to change. Polymarket’s business model is comparable to an AMM in that its primary revenue source would be through its dynamic fee schedule – charging fees to purchase binary options contracts on their platform. If enabled, Polymarket’s set fee would be levied on the proceeds of a contract. Polymarket did add fees to certain market pools in Q2 '23, but on-chain data shows that all fee generation has been paused since August 28th of that year. ![](https://shoal.xyz/research/writing/prediction-markets/img/5069c3f258c0.jpg) Given it does not charge a fee directly, the platform has historically only generated revenue when it has acted as an independent liquidity provider. **Key Features and Functionalities** - **Outcome Tokens**: Polymarket's markets utilize the [Gnosis](https://www.gnosis.io/about) Conditional Token Framework ([CTF](https://docs.gnosis.io/conditionaltokens/)), where binary outcomes are represented as ERC1155 tokens. These tokens can be traded on the platform, each corresponding to a specific market and outcome. - **PolyLend**: Introduced in 2024, PolyLend is a peer-to-peer lending protocol allowing users to borrow USDC against their conditional token positions. This feature enables participants to leverage their market positions for additional capital. - **User Incentives and Reward Programs**: Polymarket offers various incentive programs, including market-making rewards, referral bonuses, and trading competitions, designed to boost user engagement and liquidity. ### Growth and Impact ![](https://shoal.xyz/research/writing/prediction-markets/img/9df2574cc162.png) Since its launch, Polymarket has experienced rapid growth in trading volume, user base, and market activity. In July 2024, it hit an all-time high of $387 million in monthly trading volumes, tripling from the $111MM in captured volume for June. Monthly volume pushed higher to $473MM in August and peaked again in September, reaching a staggering $533MM in trades. Polymarket has also witnessed similar trends in user growth. Between May 1st, 2024 and September 9th, 2024, weekly active users on the platform have grown from ~1,000 per week to ~35,000 per week – an approximate 35,000% increase in the span of 4 months. Additionally, Polymarket experienced a substantial growth in monthly active users, reaching 90,037 in September—a 41.5% increase compared to the previous month. ![](https://shoal.xyz/research/writing/prediction-markets/img/618f47c36789.png) Political markets have seen significant engagement. In July, more than $320 million in cumulative bets had been placed on the US presidential election winner. The decision by President Joe Biden not to seek re-election spurred record daily volumes at the time, reaching $28 million in one day. ![](https://shoal.xyz/research/writing/prediction-markets/img/1790306076cd.png) Polymarket's weekly user activity has been heavily driven by election bettors, as evidenced by the above chart, where approximately 65% of user interest is tied to election-related contracts. This is more than double the 27% recorded at the start of 2024, indicating a clear shift in user engagement toward election betting as the year has progressed. More precisely put, the new user and volume growth depicted in the previous charts is highly correlated to the US election. The dominance of election markets suggests that political events have become a key catalyst for user participation, and the platform’s overall activity is closely linked to political cycles and election-related news. This strong correlation should not come as a surprise to those who’ve paid attention to platforms like Polymarket over the years. Every four years, prediction markets see a surge in activity due to the U.S. election cycle, as political markets become a primary driver of volume in the ~12 months leading up. While these platforms experience ebbs and flows in user participation, they rarely give back all the gains made during an election cycle. As a result, platforms like Polymarket benefit from a steady increase in mainstream prevalence over the long term, as they retain a portion of new users and liquidity, helping to fuel their continued growth beyond election seasons. ![](https://shoal.xyz/research/writing/prediction-markets/img/da3e47d0287e.png) One final intriguing example of the kinds of markets that gain traction on Polymarket comes from July 18th, when a quirky market emerged following President Biden’s rough debate performance. The market posed a humorous question: “Lettuce vs. Biden - Who lasts longer?” From its creation, “Lettuce” led with a 63% probability, and just three days later, Biden announced his withdrawal from the race. Polymarket’s ability to engage with internet culture, memes, and Twitter humor allows it to craft playful, unique, and timely markets that resonate with the current zeitgeist, keeping the platform fresh and closely aligned with its user base. This “internet-native” persona has and will likely continue to be a strategic advantage that competitors may struggle to replicate. ### Cultural Relevance and Market Curation Polymarket distinguishes itself by curating markets resonant with current cultural and political events. The platform’s moderators ensure markets are relevant and timely, often revolving around major news events, elections, and popular culture. This approach not only attracts participants but also enhances the platform's utility as a forecasting tool. For instance, Polymarket has created markets on the 2024 US presidential election, Federal Reserve rate cuts, and significant global events like the COVID-19 pandemic. By offering markets on various topics, Polymarket caters to diverse interests and leverages its user base's collective intelligence to provide valuable future insights. ### User Testimonials and Platform Impact User testimonials highlight Polymarket's appeal and impact. Many users praise its transparency, ease of use, and the opportunity to profit from their knowledge and insights. The addition of high-profile figures like Nate Silver has further bolstered user confidence in the platform’s accuracy and reliability. One user noted, "Polymarket has revolutionized the way I think about forecasting. The ability to bet on real-world events and see the market's consensus in real-time provides a level of insight that traditional polls just can't match." Overall, the support and investment from influential figures like Vitalik Buterin, combined with Polymarket's innovative features and strong user engagement, position the platform for continued growth and success in the prediction market space. ## Other Industry Players & Honorable Mentions In addition to Polymarket, several other prediction market platforms have made significant contributions to the field. This section provides condensed profiles of these platforms, highlighting their unique features, market focus, and user base. We will also compare and contrast these platforms with Polymarket, discussing their strengths, weaknesses, and market positioning, as well as exploring the potential for collaboration or competition between these platforms and Polymarket. ### PredictIt PredictIt is a well-known political prediction market platform based in the United States, operating under an academic exemption granted by the CFTC. Founded in 2014, PredictIt allows users to bet on political events such as elections, policy outcomes, and legislative developments. PredictIt’s detailed political markets and academic focus provide it with a niche market of politically engaged users and researchers. However, the academic exemption limits the scale of its operations, including restrictions on the number of participants and the amount of money that can be bet on each market. ### Kalshi [Kalshi](https://kalshi.com/) is a regulated prediction market platform based in the United States, offering a wide range of markets on events such as economic indicators, weather outcomes, and political events. Founded in 2018 by Tarek Mansour and Luana Lopes Lara, Kalshi operates under the regulatory oversight of the Commodity Futures Trading Commission (CFTC), which provides it with a unique positioning in the market. Kalshi’s regulatory approval and focus on non-political markets provide a distinct advantage in attracting users who prioritize security and regulatory compliance, although this focus may limit its market diversity compared to decentralized platforms like Polymarket. ### Gnosis (Web3) Gnosis is one of the pioneering platforms in the decentralized prediction market space, founded in 2015 by Martin Köppelmann and Stefan George. It operates on the Ethereum blockchain and has expanded its functionalities beyond prediction markets to include decentralized trading and wallet services. Gnosis leverages the Conditional Token Framework (CTF) to tokenize outcomes and offers a robust infrastructure for creating and trading prediction markets. With its native token, GNO, used for governance and staking, Gnosis has built a comprehensive ecosystem that supports a wide range of use cases. The platform's innovative use of decentralized oracles and its focus on enhancing user experience through intuitive interfaces have made it a notable player in the industry. Gnosis's emphasis on security and transparency, combined with its diverse range of successful Web3 products, positions it as a strong competitor to platforms like Polymarket. However, its broader focus on various blockchain applications means it may appeal to a different segment of users compared to more specialized prediction market platforms. ### Augur (Web3) Launched in 2018, [Augur](https://docs.augur.net/) is one of the pioneering blockchain-based prediction markets. Initially built on Ethereum’s mainnet, Augur operates as a permissionless platform that allows users to create their own markets using its native utility token, REP, for rewards, market creation, and dispute resolution. Augur supports binary, categorical, and scalar markets, catering to a wide range of prediction events. In 2021, Augur introduced a dedicated sportsbook platform called Augur Turbo on the Polygon network, adopting a layer-2 approach similar to Polymarket, while other markets remained on Ethereum Mainnet under the new name "Augur Pro." Augur's reliance on the REP token and Ethereum L1 transaction fees has led to higher costs for users. However, its commitment to decentralization, flexibility, and diverse market options continues to attract a dedicated user base. ### Azuro (Web3) [Azuro](https://azuro.org/) is a decentralized prediction market protocol launched in 2021, designed to improve liquidity and user experience through a peer-to-pool model. Azuro’s unique liquidity model allows users to pool their funds, which are then used to provide liquidity across various markets. Built on blockchain technology, Azuro ensures transparency and security for its users while emphasizing an intuitive and user-friendly interface. As a newer platform, Azuro may lack the market diversity and user base size of more established platforms like Polymarket but offers innovative liquidity management and scalability solutions. ### Predict.fun (Web3) [Predict.fun](https://predict.fun/) is an upcoming prediction market platform set to launch on the emerging Blast blockchain. Similar to how pump.fun revolutionized memecoins, predict.fun’s name implies an aim to bring gamification and accessibility to the forefront of prediction markets. Similar to Polymarket, the platform will utilize the UMA protocol for oracle services and dispute resolution, however, it will also notably offer users a native yield, [thanks to the unique capabilities of the Blast blockchain](https://crypto.com/university/blast-blockchain-what-it-is-and-why-its-on-the-rise). Advocates of the new platform note that the yield incentives will enhance capital efficiency and improve price discovery. With its innovative approach and the growing momentum in both prediction markets and the Blast ecosystem, predict.fun is well-positioned to attract early adopters and speculators eager for the next big opportunity in the space. However, whether it can capture and sustain the trading volumes necessary to create efficient markets remains to be seen. *I expect this platform is one worth watching in the months ahead.* ### Other Notable Platforms - **Manifold (formerly Manifold Markets):** A prediction market platform that uses a play-money system to lower barriers to entry, offering an accessible and gamified experience. [Manifold](https://manifold.markets/)’s user-friendly interface and social features have fostered strong community engagement, making it popular among casual users and those new to prediction markets. - **HedgeHog.markets**: A decentralized [prediction market platform](https://hedgehog.markets/) focused on sports and entertainment events, offering unique betting opportunities within niche markets. Polymarket’s broader market offerings may attract a more diverse user base. - **InsightPrediction**: Offers [markets](https://insightprediction.com/) on political and financial events with a focus on integrating market data with predictive analytics. Its integration of predictive analytics could complement Polymarket’s market data, offering potential for collaboration. - **Futuur**: An international [prediction market platform](https://futuur.com/) with a focus on a wide range of topics, including politics, sports, and entertainment. Futuur’s global reach and market diversity align closely with Polymarket, suggesting potential competition for international users. - **SX.Bet**: A sports-focused crypto market that allows users to bet on various sports outcomes using blockchain technology to ensure transparency. While [SX.Bet](https://sx.bet/) focuses on sports, Polymarket’s broader range of markets may appeal to users interested in non-sports events. ### Summary: Competitive Landscape The landscape of prediction markets is diverse, with each platform offering unique features and catering to different user interests. Kalshi’s regulatory compliance, PredictIt’s political focus, and Azuro’s innovative liquidity model highlight the variety within the industry. While each platform has its strengths and weaknesses, they collectively contribute to the growth and evolution of prediction markets. The prediction markets on PredictIt, Kalshi, and Polymarket are most often cited by traditional media outlets, thus garnering more mainstream appeal than the other platforms listed (though Augur and Gnosis are both well-respected within the crypto industry). Of the three, Polymarket stands out as the only Web3 platform, leveraging its decentralized approach, broad market offerings, and intuitive UX to attract a diverse and engaged user base. Comparing these platforms with Polymarket reveals both opportunities for collaboration and areas of competition. The well-executed strategic differentiators that fueled the platform’s mainstream breakout underscore a competent leadership team capable of maintaining its position at the forefront of the industry. ## Broad Impacts Prediction markets extend far beyond political betting, with significant implications for sectors like finance, sports, entertainment, and public policy. While niche platforms may excel in specialized areas, the future of prediction markets likely follows a 'winner-takes-most' trajectory. This is driven by the clear correlation between increased trading volume and market efficiency, resulting in superior predictive ability. When all is said and done, the platforms with the greatest liquidity and user base will maintain a competitive advantage in delivering reliable forecasts across multiple domains – as well as capture the lionshare of media attention. ### Implications by Sector By taking a longer-term view, it isn’t difficult to recognize how prediction markets may demonstrate their utility across a wide range of sectors in the future, offering valuable insights and influencing decision-making processes. **Finance**: Prediction markets can offer real-time forecasts on economic indicators, stock prices, and other financial metrics. By aggregating diverse opinions and leveraging crowd wisdom, these markets can provide early warnings of economic shifts, helping investors and policymakers make informed decisions. Many popular platforms now offer markets on US Federal Reserve rate decisions, as well as other key economic indicators. One of the most actively traded markets globally is the CME Group’s 30-day Federal Funds Futures contract, which functions similarly to a prediction market and is visualized through the [CME FedWatch Tool](https://www.investopedia.com/cme-fedwatch-tool-7559817), allowing traders to assess the likelihood of upcoming rate changes. **Sports**: In the sports industry, prediction markets can be used to forecast game outcomes, player performance, and other related events. Platforms like SX.Bet specialize in sports betting, providing a decentralized and transparent way for fans to engage with their favorite sports. These markets can also offer insights into team strategies and player conditions, potentially influencing coaching decisions and team management. **Entertainment**: The Hollywood Stock Exchange (HSX) is a prime example of how prediction markets can be applied to the entertainment industry. By allowing participants to trade shares in movies, actors, and other entertainment properties, the HSX has accurately predicted box office performance and award winners. This information can be valuable for studios and investors when deciding which projects to greenlight and how to allocate resources. **Public Policy**: Prediction markets have significant potential in the realm of public policy. For example, policy markets, as envisioned by Robin Hanson, could estimate the outcomes of various policy decisions, providing data-driven insights to policymakers. By betting on policy outcomes, participants can help forecast the effectiveness of different policy options, aiding in the formulation of more effective and evidence-based public policies. ### Societal Impact of Widespread Adoption The widespread adoption of prediction markets could have profound societal impacts, particularly in how public opinion is formed and how decisions are made. **Changes in Public Opinion Formation**: Prediction markets offer a real-time and dynamic reflection of public sentiment, which can significantly influence how opinions are formed and disseminated. Traditional polls provide static snapshots, whereas prediction markets continuously update, incorporating the latest information and participant insights. This dynamic nature can lead to a more informed and engaged public, as individuals have access to constantly evolving data reflecting collective expectations. **Enhanced Decision-Making Processes**: The integration of prediction markets into decision-making processes can lead to more informed and rational decisions. By aggregating the diverse opinions and knowledge of participants, prediction markets can provide more accurate forecasts and identify potential risks and opportunities. This capability can be particularly valuable in areas such as corporate strategy, public policy, and investment decisions, where accurate predictions are crucial. **Democratization of Information**: Prediction markets democratize access to information by allowing anyone with internet access to participate. This inclusivity can lead to a broader range of perspectives being considered, enhancing the quality and reliability of the forecasts generated. As more people engage with these markets, the collective intelligence of the crowd becomes a powerful tool for forecasting and decision-making. ### Efficiency and Accuracy: The Case for Winner-Take-Most The accuracy of prediction markets is closely tied to their liquidity. Higher liquidity ensures that markets are more resilient to manipulation and can better aggregate diverse opinions, leading to more accurate forecasts. This dynamic creates a potential "winner-take-most" scenario, where a few platforms dominate the market due to their superior liquidity and accuracy. Polymarket's success exemplifies this trend. With substantial trading volumes and a broad user base, Polymarket has established itself as a leading platform for political betting markets. Its ability to attract significant liquidity has enhanced its predictive accuracy, making it a trusted source for forecasting political outcomes. As the industry matures, it is likely that a small number of well-capitalized and liquid platforms will emerge as the dominant players, shaping the future of prediction markets. ## The Arguments Against Prediction Markets Critics of prediction markets often cite specific instances where these platforms have failed to accurately predict political outcomes, using these examples to argue against their overall predictive power. Below are two public criticisms that have emerged in recent weeks, in response Kamala Harris’ selection of Tim Walz – [considered a true “dark-horse”](https://www.washingtonpost.com/politics/2024/08/06/almost-no-one-knows-who-tim-walz-is/) in the VP race – as her running mate: 1. **[Walz's Unexpected Selection](https://x.com/jstn/status/1820863315549327575)**[:](https://x.com/jstn/status/1820863315549327575) One user pointed out that Polymarket had Minnesota Governor Tim Walz at just 3% odds of being chosen as Kamala Harris's running mate mere days before the official announcement. This led the user to suggest that "degenerate gamblers" might not be the best at predicting future political outcomes, implying that prediction markets are fundamentally flawed as forecasting tools. 2. **[Reactionary Nature of Prediction Markets](https://x.com/avsa/status/1821234406679314764)**[:](https://x.com/avsa/status/1821234406679314764) Another user criticized prediction markets more broadly, arguing that these platforms are not truly predictive but rather reactive to news developments. The user stated that unless there is widespread insider trading (which is unlikely to occur at scale in high-stakes markets due to the risks involved), prediction markets merely mirror the prevailing news narratives rather than providing forward-looking insights. ### Rebuttal: Why These Critiques Are Misleading While these critiques are understandable given the unexpected nature of Tim Walz's selection, they fail to account for the inherent challenges in predicting vice-presidential picks and overlook the broader utility of prediction markets. 1. **Inherent Uncertainty in VP Picks & Limited Data**: Vice-presidential selections are notoriously difficult to predict due to the highly secretive nature of the decision-making process. Typically, only a small circle of advisors is involved, and the final choice rests solely with the presidential candidate. This decision can be influenced by personal preferences, strategic considerations, or external factors that are not publicly known or easily anticipated. Furthermore, the decision-making process often prioritizes factors unrelated to swing state advantages, making it even harder for prediction markets to accurately narrow down a list of potential running mates. The challenge is compounded by the limited access to reliable data. Unlike larger political events, such as elections that involve millions of participants and more prescient polling data. > As recently highlighted in the well-respected UVA political publication, [Sabato's Crystal Ball](https://centerforpolitics.org/crystalball/in-passing-on-a-swing-state-vp-harris-makes-a-pick-that-fits-recent-history/), Kamala Harris's selection of Tim Walz was shaped by a *constrained timeline* and specific political considerations, many of which could not be effectively defined and disseminated to the broader public in such a short amount of time. 1. **The Role of Gut Instincts in Decision-Making**: Presidential candidates may prioritize different factors when selecting their running mates. Some may rely heavily on data and polling, while others might follow their instincts or prioritize personal relationships. This variability further complicates the predictive process, making it difficult for markets to accurately forecast such decisions. In Walz's case, his selection may have been influenced by factors that were not visible to the public or easily quantifiable, such as his background, compatibility with Harris, or his ability to appeal to centrist voters. 1. **Prediction Markets as a Complementary Tool**: Prediction markets should not be viewed as standalone predictors of specific events like VP picks, which are shrouded in secrecy. Instead, they are most valuable when used as part of a broader analytical toolkit, providing insights into the collective sentiment of informed participants. While they may not always get it right in cases of high uncertainty, they are effective at aggregating diverse opinions and adjusting quickly to new information. 1. **Outlier Events Do Not Define Predictive Power**: Finally, it's important to recognize that outlier events, such as an unexpected VP pick, do not invalidate the broader predictive power of markets. In many cases, prediction markets have accurately forecasted complex political outcomes, outperforming traditional polls and expert analyses. The failure to predict Walz's selection is a reminder of the limitations that all forecasting tools face when dealing with low-information, high-uncertainty scenarios, rather than a wholesale indictment of prediction markets. It’s true that on August 1st, Polymarket had Tim Walz’s odds of being chosen as Kamala Harris’s VP at only 5%, just five days before the official announcement on August 6th. However, by the day before the announcement, August 5th, those odds had shifted dramatically, with Walz’s odds effectively matching the longstanding frontrunner, Josh Shapiro (who had peaked at ~77% on July 31st). Throughout the day of August 5th, the odds for Walz and Shapiro fluctuated, reflecting the uncertainty and subjectivity inherent  to the VP selection process. Notably, Walz’s odds eventually peaked at 60% that afternoon, at one point overtaking Shapiro’s, which is significant because it suggests that the market was able to anticipate the shift in Harris’s thinking in favor of Walz [before she had even finalized her decision](https://x.com/PeterAlexander/status/1820788889302516080). This flip was driven by a mix of subjective data, including[positive reports about Walz’s interview](https://www.politico.com/news/2024/08/06/walz-told-harris-vp-interview-00172952) performance, coinciding with negative[signals regarding Shapiro](https://www.politico.com/news/2024/08/03/fetterman-shapiro-harris-vp-00172557). The market's ability to reflect these dynamics highlights its strength in processing and responding to nuanced information, even in situations where the decision-maker has not yet reached a conclusion. For a more detailed analysis of Polymarket's data and its predictive power of the VP selection process, be sure to check out [their recent post in their newsletter](https://substack.com/@polymarket/p-147479289). It includes insights that highlight the value of prediction markets – especially, the value of using the graphical trends as indicators, rather than simply the headline numbers. An excerpt: *“Looking back at the chart, we can see several key moments where the Polymarket odds were ahead of the conventional wisdom. They:* - *Took Walz seriously at a time when many pundits were focusing on Shapiro or Kelly, showing him moving up as 'weird' went viral* - *Called out the decline of Mark Kelly amid the barrage of oppo research* - *Flagged the serious last-minute troubles with Shapiro and the final Walz surge.”* ![](https://shoal.xyz/research/writing/prediction-markets/img/c723c061d77d.png) ## The True Weaknesses and Shortcomings Faced by Prediction Markets In many respects, prediction markets are subject to challenges that mirror those in AI, where bias, technical, and regulatory issues combine to present significant barriers to entry. ### Demographic Pool Biases and Emotional Influence Prediction markets are often influenced by the demographic makeup of their participants, particularly in highly emotional contexts like US presidential elections. These markets, similar to the most intense sporting events, are driven by partisan emotions, leading to outcomes that may reflect more of the participants' biases rather than objective probabilities. This emotional bias is further amplified by the fact that many market participants may be more motivated by their hopes or fears rather than dispassionate analysis, leading to distorted market outcomes. ### Copy-Trading, Recency Bias, and Speculation Prediction markets are also susceptible to the pitfalls of copy-trading, recency bias, and speculative behavior. Participants often follow the crowd, leading to exaggerated trends and price swings. This behavior can cause the market to overreact to recent events or prevailing sentiments, pushing prices too far in one direction and creating inefficiencies. Unless there is ample liquidity and active market-making to counterbalance these trends, the market's predictive accuracy can be significantly compromised. ### Dispute Resolution in Nuanced Political Events and Bias in Oracle Decisions One of the critical weaknesses in prediction markets is the challenge of resolving disputes in complex or nuanced political events. A recent example is the [contested Venezuelan election](https://rekt.news/hedging-bets/), where the UMA protocol resolved the market in favor of the opposition political party after [ample evidence](https://www.bbc.com/news/articles/cd1d10453zno) showed the initial election results had been falsified, despite ongoing disputes and no indication that President Maduro will ultimately step down. This decision illustrates the difficulty in adjudicating such events, where outcomes are complicated by unforeseen circumstances. Moreover, oracles like UMA, designed to provide unbiased resolutions during disputes through tokenholder votes, can still be influenced by the human biases of stakeholders, potentially undermining the integrity of prediction markets. This bias in oracle decisions, which accumulate news data off-chain, can lead to dissatisfaction among participants and erode confidence in the fairness and accuracy of these platforms. ### Product Headwinds & Risks Faced by Prediction Markets Prediction markets, despite their growing popularity and utility, face several significant challenges. These challenges range from technical and operational issues to regulatory and legal hurdles. This section will explore the primary challenges, focusing on regulatory actions taken by government agencies against various prediction markets, and compare the regulatory landscape in the United States with the generally more favorable international environment. Technical and Operational Challenges Prediction markets rely heavily on technology to operate efficiently and securely. Key technical challenges include: 1. **Scalability**: As the number of users and transactions increases, prediction markets must scale their infrastructure to handle the load without compromising performance. After all, Prediction Markets could one day compete with sports betting platforms as well as traditional options exchanges. 2. **Security**: Ensuring the security of user funds and data is paramount. Prediction markets are attractive targets for hackers, making robust security measures essential. 3. **User Interface and Experience**: Simplifying the user interface and improving user experience can help attract and retain participants. Complex interfaces can deter potential users from engaging with the platform, particularly as these platforms push towards more casual betting markets and broader user bases. Regulatory and Legal Hurdles One of the most significant challenges facing prediction markets is navigating the complex regulatory landscape. This section will detail specific examples of regulatory actions and compare the regulatory environments in the United States and internationally. United States Regulatory Landscape In the United States, prediction markets face stringent regulatory scrutiny, primarily from the Commodity Futures Trading Commission (CFTC). Several key regulatory actions highlight the challenges these markets face: 1. **Polymarket**:In January 2022, the CFTC ordered Polymarket to pay a $1.4 million civil monetary penalty for offering off-exchange event-based binary options contracts without the necessary registration as a designated contract market (DCM) or swap execution facility (SEF). The CFTC's order required Polymarket to wind down all non-compliant markets on its platform and cease violating the Commodity Exchange Act (CEA) and applicable CFTC regulations​. 2. **PredictIt**:PredictIt, a popular political prediction market, operated under a no-action letter issued by the CFTC in 2014, allowing it to function as a not-for-profit event contract market for educational purposes. However, in 2022, the CFTC withdrew this no-action letter, citing violations of its conditions. The withdrawal significantly impacted PredictIt's operations and its ability to offer political event contracts in the US.​ 3. **Kalshi**:Kalshi is the only prediction market currently approved by the CFTC to operate a contract market. Despite this approval, Kalshi faced significant regulatory hurdles when it sought to expand into political event markets. In 2023, the CFTC denied Kalshi's request to offer event contracts on congressional control, following pushback from legislators who argued that such contracts could undermine the democratic process​. These examples illustrate the cautious approach US regulators take toward prediction markets, particularly those involving political events. The primary concerns include the potential for market manipulation, ethical issues, and the influence of financial incentives on democratic processes. The wary reluctance expressed by US regulators is nothing new, as noted earlier when covering the history of prediction markets. However, there is a general belief that the US is on a path towards greater acceptance of these types of contracts and derivatives as public interest continues to grow. [The massive rise in the US sports betting industry](https://www.cnn.com/2024/05/03/sport/sports-betting-usa-impact-on-lives-spt-intl/index.html#:~:text=It%20was%20in%202018%20that,now%20partnering%20with%20betting%20organizations.) highlights that there is precedence for such a shift in policy. International Regulatory Landscape In contrast to the US, the international regulatory environment for prediction markets is generally more favorable. Several countries have adopted a more progressive stance, recognizing the potential benefits of these markets: 1. **United Kingdom**:The UK has a more lenient regulatory approach towards prediction markets, particularly those operated by established betting firms. Platforms like Smarkets and Betfair offer political betting markets with fewer regulatory constraints compared to their US counterparts. 2. **New Zealand**:The University of Wellington operates the New Zealand-based prediction market, iPredict, which has faced fewer regulatory challenges than similar markets in the US. This more relaxed regulatory environment has allowed iPredict to offer a wide range of event contracts, including political outcomes, without significant interference​. 3. **Estonia**:Estonia has emerged as a hub for innovative fintech and blockchain projects, including prediction markets. The country's supportive regulatory framework encourages the development and operation of decentralized platforms, making it an attractive destination for prediction market startups. The international regulatory landscape's relative friendliness towards prediction markets allows these platforms to innovate and expand more freely. This contrast highlights the challenges US-based prediction markets face in achieving similar growth and acceptance. ## Future Prospects for Prediction Markets As prediction markets continue to evolve, they’re likely to see more community-based curation, improvements in data quality from oracles, and continued feature evolution, including increased use of AI. ### User-Sourced Market Curation One of the most exciting prospects for prediction markets is user-sourced market curation. Platforms like Polymarket are already seeking new market requests from their community, but this process could become more decentralized and user-driven. By leveraging the collective intelligence and interests of users, platforms can offer a wider variety of markets, ensuring they remain relevant and engaging. Users could vote on proposed markets or even create and manage their own, incentivizing active participation and enhancing the platform's relevance. ### Improvements in Oracle Technologies Oracles, which provide the data needed to resolve prediction markets, are critical for their accuracy and reliability. Advances in oracle technologies, such as decentralized oracles and improved data verification methods, could significantly enhance the trustworthiness of prediction markets. Enhanced data verification methods, including cross-referencing multiple data sources and using advanced machine learning algorithms to detect anomalies, can improve the accuracy and reliability of oracle data. These advancements will ensure market outcomes are based on accurate and unbiased data, further solidifying the role of prediction markets as reliable forecasting tools. ### New Features and Services The introduction of new features and services can also drive the growth of prediction markets. For example, [PolyLend](https://mirror.xyz/polymarket.eth/8t4zhQlAza5M52dV4lVvh94NDhbJr2Dos4qvih80flU), a peer-to-peer lending protocol that allows users to borrow against their conditional token positions, represents a significant innovation. By enabling users to leverage their market positions for additional liquidity, platforms can offer more flexibility and financing options while generating new revenue streams in the process. Additionally, innovative financial services such as hedging tools, insurance products, and fractional ownership of market positions, can attract more sophisticated users and investors to prediction markets. By offering adjacent services, platforms focused on differentiating through a decentralized operating model can both draw in a wider user base while also showcasing the inherent advantages of democratized systems. ### The Impact of Artificial Intelligence AI has the potential to revolutionize prediction markets by enhancing various aspects of their operation and user experience. The integration of AI can lead to the creation of markets at a microscopic scale, making them more personalized and relevant to individual users. - **Content Creator AIs**: AI can assist in creating content beyond human capabilities. By analyzing trends from news, social media, and financial data, AI can suggest timely and relevant event topics. This can lead to the creation of highly relevant markets that attract niche audiences and drive participation and volume. Community feedback enhances the AI’s understanding, making it an iteratively improving content creation engine that bonds content creators and their audiences. - **Event Recommendation AIs**: AI can tailor event suggestions to users based on their interests, trading history, and specific needs. By focusing on recommending events ripe for debate and trading opportunities, AI can adapt to users’ behaviors across different regions, cultural contexts, and times, leading to a highly targeted feed of events, free from irrelevant content. - **Liquidity Allocator AIs**: AI can optimize liquidity injections to narrow the bid-ask spread and minimize risk. By implementing the logarithmic market scoring rule (LMSR) AMM model, AI can manage event liquidity from a general LP pool, rewarding contributions with accrued fee revenue or platform tokens. This reduces slippage and ensures better price stability. - **Information Aggregation AIs**: AI can harness data from various indicators (e.g., on-chain data, historical data, news, sentiment indicators) to provide a comprehensive understanding of events. This enables players to make confident bets based on well-rounded projections. Information aggregation AIs can turn prediction markets into the go-to source for informed decision-making, with potential projects to token-gate access to AI-generated insights. - **AI as Arbiters**: In cases of disputes in prediction markets, AI can serve as impartial arbiters. Using multi-round dispute systems similar to Kleros, AI can resolve disputes efficiently and without bias, reducing the need for human arbitration, which can be slow, expensive, and subject to biases. ## Wrapping Up Prediction markets have come a long way from their experimental days of the '90s through early aughts, evolving into sophisticated platforms that leverage collective intelligence to provide accurate forecasts across various domains. As we look to the future, the growth and impact of decentralized prediction market platforms like Polymarket suggest their significant potential to become mainstream tools for forecasting and decision-making. Their ability to aggregate diverse opinions and provide real-time insights makes them powerful tools for both individuals and organizations. The potential for user-sourced market curation, advances in oracle technologies, new financial services like PolyLend, and the transformative impact of AI will further enhance the value and relevance of prediction markets. Reflecting on the words of Ben Graham – the “father of value investing” – as cited by his protégé, Warren Buffet in his 1987 letter to Berkshire Hathaway shareholders: “The market may ignore business success for a while, but eventually will confirm it. As Ben said: ‘In the short run, the market is a voting machine but in the long run it is a weighing machine.’” While the minute-by-minute movements in prediction markets may at times be fairly cast aside as “noise” driven by overreaction, speculation, and copy-trades, these markets can help better ascertain “truth” by looking at the directional moves when zoomed out to a daily, weekly, or monthly chart. Trying to analyze a handful of bets, much like analyzing a small polling sample, is a fool's errand, given that those bets are not representative of the collective. But, by zooming out, one unleashes the power of the internet – the power of crowdsourced information. In short, prediction markets represent a powerful tool for aggregating collective wisdom and providing real-time insights into future events. As the internet continues to facilitate the proliferation of these markets, their role in shaping public perception, influencing decision-making, and forecasting outcomes will only grow. By understanding the dynamics driving their growth and addressing the challenges they face, we can unlock the full potential of prediction markets and harness their power to predict the future. --- ## References 1. Roeder, O. 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(2024, June 17). *Azuro’s Role in the Future of Prediction Markets*. Delphi Digital.[https://members.delphidigital.io/media/rossen-yordanov-azuros-role-in-the-future-of-prediction-markets](https://members.delphidigital.io/media/rossen-yordanov-azuros-role-in-the-future-of-prediction-markets) 2. Sommer, J. (2024, May 17). *As the 2024 Race Heats Up, Betting Is Growing for Everything but Elections*. The New York Times.[https://www.nytimes.com/2024/05/17/business/elections-betting-prediction-markets.html](https://www.nytimes.com/2024/05/17/business/elections-betting-prediction-markets.html) ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer.* --- # Bringing Macro Markets Onchain with Ostium > A deep dive on the Ostium Protocol and the role of perpetuals in bringing macro markets onchain. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-09-12 - Canonical: https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/ - Keywords: stablecoins, crypto, RWA, tokenization, Ethereum, Bitcoin, Infrastructure ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/0af65bf21e64.jpg) ## The Digitization of Financial Services Throughout the history of human civilization, technology and capital markets have evolved alongside one another. The origins of written language can be traced back to  ledgers, dating back thousands of years to [Sumerian Cuneiform](https://www.worldhistory.org/cuneiform/) in ancient Mesopotamia, where signs recorded on clay tablets were used to keep track of the ownership of livestock and commodities. Doing so effectively allowed the Sumerians to become the most advanced ancient civilization at the time, as they were now able to efficiently manage economic resources, facilitate trade and taxation, and allocate goods and labor within city-states. The ability to accurately record and verify asset ownership ultimately formed the backbone of civil societies and modern economies. Without such a mechanism, chaos ensues. The [tulip mania bubble](https://www.investopedia.com/terms/d/dutch_tulip_bulb_market_bubble.asp), the stock market crash of 1929, and the great financial crisis of 2008, are all premier historical examples of the consequences in failing to provide reliable settlement and ownership guarantees of economic assets. As human civilizations have evolved, so have ledgers; from clay tablets and paper certificates, to computers and software programs. Technological innovation may often conform to fit within an existing market structure, or conversely new technologies may create opportunities to disrupt a market's existing structure, transforming its underlying architecture, operations, and the actors involved. Often, adoption of new technologies in the financial services sector was not voluntary, but instead a response to critical situations in dire need of fixing. The[Paperwork Crunch](https://www.bis.org/publ/qtrpdf/r_qt0712z.htm) of the 60s led to the launch of NASDAQ, the world’s "first electronic stock market", in 1971. This marked the biggest transformation of securities trade clearing and settlement systems to date. In 1973, the Depository Trust Company (DTC) was founded to remove the mobility of certificate transfers by custodying certificates in a single depository with a unified accounting ledger. However, it wasn’t until after 9/11 and the grounding of air travel in the US that the [Check Clearing for the 21st Century Act](https://www.investopedia.com/terms/c/check_21.asp) was passed, making it legally permissible to clear images of paper checks instead of the paper copy itself. It took the [flooding of the DTCC vaults](https://www.reuters.com/article/us-storm-sandy-securities/dtcc-finds-1-3-million-soaked-securities-in-sandy-flooded-ny-vault-idUSBRE8AE02G20121115/#:~:text=NEW%20YORK%20(Reuters)%20%2D%20The,skyscraper%20flooded%20by%20Superstorm%20Sandy.) during Hurricane Sandy in 2012, which saw nearly 1.7 million security certificates damaged, to shift away from paper checks altogether. Fast forward to today and there is still much room for improvement. Data from the DTCC shows the real cost associated with the difficulties of this rather complex and antiquated system, with upwards of tens of billions US dollars failing to deliver a trade contract on a **daily basis.** ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/86ab2c9a9205.jpg) The associated risks are[well-explained by the DTCC](https://www.dtcc.com/charts/daily-total-us-treasury-trade-fails): “Not only does the original trade fail, but the party that bought the securities may have already pledged them in a subsequent trade, and now that trade too will involve a failure-to-deliver, thus creating a cascading effect.” This begs the question – do blockchains fix this? ### The Role of Tokenization At a high level, tokenization is the process of encoding assets of economic value, as well as their associated ownership claims, on a blockchain. Blockchains are digital distributed ledgers that record and store transactional information, providing immutability (barring a theoretical but increasingly difficult or costly attack vector), and transparency of events, which in turn enables public observability, wherein anyone can observe and verify whether an event took place or not. ‘Real-world assets' , or RWAs, have become a colloquial term for the various non-crypto assets that can be tokenized.*([Kyle Samani of Multicoin Capital](https://x.com/KyleSamani/status/1808936703467622444) points out that the use of ‘real-world’ is redundant “You are telling the people who are not in crypto that you do not live in the real world, and that you want the real world to come to bizarro crypto world”, **but for the sake of convenience this paper will continue to use the term RWAs. )***Real-world assets can range from financial assets such as fiat currencies, commodities, equities, and bonds to illiquid assets such as real estate. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/8ca98793f1ec.jpg) The design of blockchains offer a number of compelling benefits for tokenizing RWAs and virtually any tradable asset. For starters, the atomic nature of blockchains mitigates the principal settlement risks of delivery-versus-payment systems, as blockchain transactions often exist as multi-legged operations wherein either all legs succeed or none do at all the transaction fails. Using blockchains also eliminates the need for various layers of intermediaries, thereby reducing costs for buyers and sellers. In turn, this allows for improved efficiency in markets that oversee the buying and selling of various assets. Greater efficiency, coupled with the transparency of information that blockchains provide, unlocks new opportunities for accessibility of financial assets. Another key benefit that can be realized from tokenization is increased liquidity, wherein easier access to certain asset classes allows for a greater number of potential market participants therein allowing liquidity for their markets to grow and deepen over time. This goes hand in hand with the onset of fractional ownership, which has yielded tremendous results for the “new generation” of financial services businesses like Robinhood. **Tokenization is not a new concept.**One could argue that the history of tokenization can be traced back to[Colored Coins](https://en.bitcoin.it/wiki/Colored_Coins) on Bitcoin; the core idea, proposed in a 2012 research paper by Meni Rosenfeld, was to "color" a small fraction of a Bitcoin with additional metadata, effectively creating a unique token that could represent ownership of an asset other than Bitcoin itself, such as commodities, stocks, or bonds. Though there was a significant amount of development around colored coins at the time, the idea was made obsolete by further developments in the crypto industry.. Another early iteration of tokenization was [DigixDAO](https://bitcoinwiki.org/wiki/digixdao),  founded in Singapore in 2014, which was the first crowdsale and major DAO on Ethereum. Digix would allow for the public verification of an asset’s existence through its chain of custody via its Proof of Provenance (PoP) protocol, built on top of Ethereum and the InterPlanetary File System (IPFS). Tether has been minting USDT onchain by depositing an equivalent amount of fiat currency into their reserve bank accounts and then issuing the corresponding amount of USDT tokens on the blockchain since 2015. Circle has been doing the same since 2018 with USDC. At the time of writing, the total value of RWAs onchain exceeds $175B, with stablecoins accounting for an overwhelming majority of this number ($164B), as per the[Rwa.xyz](https://app.rwa.xyz/) dashboard. ### Where Tokenization Falls Short The tokenization of financial assets such as fiat currencies, commodities, equities, and bonds, is believed by some,[including Larry Fink,](https://vimeo.com/922276397) to be the future of the financial industry. In theory, anything and everything of economic value can be tokenized. However, as compelling as some of the key benefits to trading assets on a blockchain may be, it’s important to consider the shortcomings of tokenization, and consequently, consider if there are alternative financial instruments which may enable trading assets on blockchains even more effectively. Overall, tokenizing RWAs requires significant effort and diligence to manage, from an operational and custodial perspective. In order to ensure tokenized assets accurately reflect their physical underlying counterparts, token issuers must either purchase the underlying every time a new token is minted, or sell every time a token is burned. Depending on the asset in question, issuers must also be able to manage any operations pertaining to the physical asset (i.e. precious metals token issuers must manage the storage, insurance, delivery, and sourcing of the metals in addition to managing the asset’s reserves).  Overall, this can be an arduous task that incurs high costs and requires significant time to implement in practice, especially at a scalable level. The adoption of tokenized assets will also require significant progress and action from a regulatory and legal perspective, which can often be a long process as it varies by different nations and regions. In the US, the past four years have been largely unfavorable for  crypto products and services. Meanwhile over in the EU, the [MiCA](https://www.europarl.europa.eu/thinktank/en/document/EPRS_BRI%282022%29739221) regulation framework is set to take place by the end of the year, while [Singapore](https://coinpedia.org/cryptocurrency-regulation/cryptocurrency-regulations-in-singapore/) and[Hong Kong](https://sumsub.com/blog/hong-kongs-new-crypto-exchange-licensing-regime/) have been embracing more crypto-friendly policies. Determining ownership rights and handling ensuing disputes also bring about legal complications, and local laws and regulations (i.e. at the state or city level) make this even trickier. What if, instead of ownership, investors simply want to get price exposure to these assets in an easier, less costly, and overall more efficient way? This is where synthetics come in. Synthetics are financial instruments built to mimic the value of an underlying asset without requiring said asset to be held by the investor. Synthetics can be created and traded on a blockchain without actually needing to go through any of the logistically complex processes involved with tokenization, allowing for the streamlined creation of onchain markets. To this day, only one type of synthetic derivative has been particularly successful - and so, *all roads lead to perps.* ## The Role of Perpetuals Perpetual contracts (perps) are a type of derivatives contract which allow investors to speculate on an asset’s future price without a predefined expiry. These financial instruments can be held indefinitely, a key distinction from traditional derivatives contracts which involve an expiration date, before or during which the contract must be settled. Similar to contracts-for-difference (CFDs), perpetuals provide a financial instrument for investors to speculate on an asset’s price movement for an indefinite period with leverage, but do so while maintaining a single uniform contract. Though a great deal of inspiration was taken from the Undated Futures market by the Chinese Gold and Silver exchange of Hong Kong, perpetual futures were first introduced by Robert Shiller in a[1992 research paper](https://econpapers.repec.org/paper/nbrnberte/0131.htm), in response to a lack of liquid derivatives markets for many of the components of global wealth such as human capital/labor costs, real estate, private financial assets, and macroeconomic indices. > “To create a market for the present value of a cash flow represented by some dividends or rent index, we need to create a perpetual claim on a cash flow represented by the index.” - Shiller Shiller's motivation was to address the absence of hedging instruments for infrequently-priced, illiquid markets, proposing perpetual futures contracts as superior comprehensive risk management tools, which could be used across a wide range of use cases such as labor cost markets, commercial real estate, commodities and agriculture, to name a few. Given that these markets often faced significant spreads, Shiller believed perpetual contracts could provide great cost savings for hedgers and reduce basis risk. ***In short, perpetual futures aim to facilitate price discovery for assets with illiquid or hard-to-measure prices.*** Unfortunately for Shiller, the difficulties associated with implementing perpetual futures contracts hindered their adoption in capital markets and the financial services sector. This included regulatory hurdles, a lack of sufficient infrastructure, complexity in appropriately pricing underlying assets, to name a few, but in the end, perpetual futures were traded almost exclusively in over the counter (OTC) markets. Believe it or not, **the first use-case for perpetuals was trading crypto, and it remains the only active use-case to date.** ### Perpetuals in Crypto In 2011, Alexey Bragin sought a way to differentiate his Bitcoin futures ICBIT exchange from the rest of the market, which led to the creation of the "inverse perpetual" in which the contract was settled in Bitcoin but priced in USD. However, it wasn’t until[BitMEX rolled out XBTUSD](https://blog.bitmex.com/announcing-the-launch-of-the-perpetual-xbtusd-leveraged-swap/), their first perpetual leveraged swap product, that perpetuals started to pick up significant adoption. BitMEX rebranded their derivatives contract as the Perpetual Swap and introduced features aimed to attract smaller, crypto-native traders as opposed to larger financial institutions, including small contract sizes, a bitcoin-inspired contract design, minimal margins, and lower trading fees. At this time, crypto was mostly being traded off-chain via centralized exchanges (CEXs), though this would soon begin to change with the rise of spot decentralized exchanges (DEXs) in the late 2010s. At their core, DEXs were simply sets of smart contracts coupled with an interface for users to interact with from their wallets, enabling anyone to trade any supported asset while retaining full custody over their assets. The first derivatives DEX came about in August 2017 when Antonio Juliano launched dYdX, on Ethereum, which eventually shifted its focus to become the first perpetuals DEX in April 2021 with dYdX v3. Since then, the number of perps DEXs has continued to grow with the rise of L2s, and onchain perps have seen over $2.7T in trading volume lifetime, per[Artemis](https://app.artemis.xyz/sectors?tab=perpetuals). ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/3556dc0602a8.jpg) There are some key features that perpetual exchanges have in common, such as the **funding rate,**the underlying price discovery mechanism. Perpetuals lack an expiry and therefore require an ongoing payment mechanism in which the counterparties pay one another depending on market conditions at a given time**.**When the funding rate is positive,  longs pay shorts. When the funding rate is negative, shorts pay longs. That said, the rising number of perp DEXs has led to a variety of implementations in design and function worth dissecting. **Order Book** Order books have long since been the default price discovery mechanism for exchanges, wherein buy and sell orders are listed and matched on a unified matching engine. One common adaptation of this model with perps has been to utilize off-chain orderbooks for trade matching, while execution and settling trades onchain. This model enabled protocols to avoid incurring gas fees and being hindered by network performance, while still benefiting from the transparency of onchain settlement and self-custody for traders. Taking this further are fully onchain orderbooks, in which the matching of trades is also performed onchain. This model has historically been challenging to implement, as the latency and throughput constraints of the underlying chains made it viable for sophisticated actors to perform frontrunning and sandwiching attacks and extract value at the expense of uninformed retail traders who in turn received worse price settlement on trades. However, the rise of high-performance execution environments - whether it be new general-purpose L1s, app-specific chains, or rollups -  seeks to alleviate this issue by significantly reducing block times therefore minimizing information asymmetries among market participants. **Peer-to-Pool** Peer-to-pool perp DEXs utilize a self-matching algorithm where buy and sell orders are routed through a central liquidity pool, and matched using a price feed oracle. Pioneered by GMX, this model employed two counterparties to operate- **liquidity providers**(LPs) who would lend capital to the central pool, and **traders**who would utilize this capital to fulfill their trades. Though LPs bear inventory risk, they are subsided by a combination of trading fees, liquidation rewards, and funding fees for doing so, while traders benefit from price execution at real-time price indices with lower slippage. However, this dynamic created an adversarial environment between LPs and traders: LPs profited from traders’ negative PnL, but suffered from pool rebalances when traders were profitable. **Virtual AMM** Another design implementation that has emerged in the perp DEX landscape is the virtual AMM (vAMM) pioneered by Perpetual Protocol (great name). Similar to Peer-to-Pool, vAMMs utilize a two-counterparty system composed of LPs and traders. Rather than utilizing real tokens for liquidity, however, vAMMs utilize virtual, [synthetic](https://coinmarketcap.com/alexandria/glossary/synthetic-asset) assets (i.e. perps). In this model there is no actual liquidity pool in the protocol; traders are able to make leveraged trades on assets which are stored in a smart contract vault. Perp DEXs have come a long way since their inception, but their potential has still been largely untapped as they have been constrained to trading crypto assets. Let’s dive into one particular protocol seeking to extend the utilities of onchain perps beyond crypto assets, to be able to trade virtually everything in one’s eToro account onchain - Ostium Protocol. ## Ostium Protocol Deep Dive ### What is Ostium? The Ostium Protocol is an open-source decentralized exchange for trading blue-chip crypto assets and RWAs as perpetual contracts onchain. At its core, the protocol functions as a set of smart contracts that live on the Arbitrum Layer 2, made up of a trading engine and a liquidity layer, as well as an in-house oracle and automated keeper system, key supporting infrastructure components. Putting it all together, the protocol provides several key offerings: **virtual exposure** to off-chain assets that do not natively exist onchain, a **Shared Liquidity Layer** made up of two capital pools (the Liquidity Buffer + the Market Making Vault) to settle trades and function as counterparties to traders, **near sub-second price feeds** enabled by a dual oracle system, **automation for key trading features** including liquidations, stop and limit orders, and a **strategic risk-adjusted fee structure** to capture and minimize the directional risk an open position poses to the Shared Liquidity Layer. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/0123b9c92808.jpg) From a design perspective Ostium chose to utilize a peer-to-pool model, though with its own unique twist which will be elaborated on further below. Choosing a peer-to-pool model makes sense given that markets are simply not yet mature enough to market-make for long-tail assets like soybeans or hog prices; utilizing a shared liquidity layer for price discovery allows for a more scalable defi-native model instead. **Ostium’s Vision** Ostium believes the best way to serve demand among traders for leveraged, short- and mid-term price exposure to RWAs onchain is via oracle-based perpetuals. Its goal is simple too: become the go-to destination for trading virtually any asset as an oracle-based perpetual contract. The crypto markets and the macroeconomic environment are increasingly converging, and the post-pandemic macroeconomic landscape has wet the appetites of an increasing number of macro-aware traders. Crypto’s reaction to the unwind of the Yen carry trade and the Nikkei is a telling example; if one were to go around telling altcoin traders to keep track of what the Bank of Japan was doing as it would have critical implications for the performance of their tokens, they’d be laughed out of the room. Last week, however, this theory was proven to be correct. The incredible rise of Polymarket in the US election year has also demonstrated the appetite for speculating on the outcome of real-world events; in fact there has even been a positive correlation between the price of BTC and Donald Trump’s presidency odds. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/6874dce35693.png) Ostium puts forth the notion that perpetual contracts will reign as the superior financial instrument for enabling a proliferation of capital markets on the blockchain. ![Tweet](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/247f6e768eea.jpg) Let’s dive deeper into the various components that work together to enable this vision. ### Key Protocol Components **Ostium Trading Engine** The Ostium trading engine is the key feature of the Ostium protocol, facilitating the trade of the protocol’s supported assets by coordinating interaction between traders and LPs. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/dad1238b3c01.jpg) Upon depositing collateral, traders can choose to go long or short; place a market, limit, or stop order, and customize their leverage settings (Ostium offers up to 200x). Gelato Functions are used to continuously track price changes and determine the need for automated order execution (liquidations, stop losses, take profit orders), while prices are called on-demand using a pull-based oracle mechanism. While their position is open, users can update their positions (Update Take Profit, Update Stop Loss, or Add Collateral) without incurring additional fees. Positions can be closed either manually or automatically; triggered by either a Stop Loss order (negative PnL), Take Profit (positive PnL) order, or Liquidation. If the value of a trader's collateral has decreased by 90%, the Keepers trigger a liquidation event, in which the remaining collateral (10%) is transferred to the Market Making Vault as a liquidation reward. > **Open Price and Price Impact** To protect LP capital from the [associated risks of peer-to-pool based pricing models](https://cointelegraph.com/news/decentralized-exchange-gmx-suffers-565k-price-manipulation-exploit), Ostium implements a methodology for price discovery which incorporates real-time market liquidity conditions when determining the price at which a trader opens a position. While the mid-price is often used as a neutral valuation metric, relying solely on it can be misleading in scenarios where liquidity significantly affects the quality of execution a trader receives. Instead, Ostium employs a scaled bid-ask spread model that more accurately reflects the true market conditions and the costs associated with different trade sizes. The bid-ask spread, which represents the difference between the highest price buyers are willing to pay (bid) and the lowest price sellers are willing to accept (ask), is dynamically adjusted in Ostium’s model. Under this model, the spread scales linearly with position size—meaning that larger trades incur a proportionately larger spread. Therefore, instead of always being quoted the bid or ask, traders are quoted a scaled version of these prices, such as 0.1 times the mid-bid spread or 2 times the mid-ask spread, depending on the specific circumstances of the trade. When a trader opens a long position, a price derived from a scaled ask price is quoted, while a scaled bid price is used when opening a short position. Similarly, when closing a long position, a scaled bid price is quoted, and a scaled ask price is quoted for closing a short position. **This is represented by the following formula (given K as a constant):** Note that throughout the process of opening a position, Ostium charges a one-time fee to the user, and then compounding fees while a position is open. These will be expanded upon further in the “Fee Structure” section below. **Ostium Liquidity Layer** Rather than operating under a central limit order book (CLOB) model, Ostium functions as a liquidity pool based DEX, similar to the likes of well-known perp DEXs such as GMX. This model enables the protocol to sustain imbalances in Open Interest, however there are key distinctions to account for between Ostium’s model and traditional perpetuals protocols, wherein LPs benefit directly from trader losses, forming an adversarial relationship between two sets of market participants which are both equally important to the protocol. Ostium’s Shared Liquidity Layer (SLL) is made up of two capital pools - a **Liquidity Buffer** which serves as the first layer of settlement for positive PnL trades and a **Market Making Vault** which acts as a backup in the event that the Liquidity Buffer is depleted. Note that capital in the Liquidity Buffer comes from accrued traders’ PnL, while the market making vault is open to deposits from LPs to earn liquidation rewards and 50% of position opening fees. The core idea is that by creating two siloed pools with strategically defined fee structures, LPs benefit primarily from increased trading volume and OI growth. The LB is designed to absorb trader PnL thereby stabilizing LPs’ APY in the event of sustained positive PnL for traders, **meaning traders and LPs should simultaneously benefit from protocol growth.** **Liquidity Buffer** The LB is the primary settlement layer for trades on Ostium, meaning that an immediate trading counterparty is not required for trades to be executed. Given that LPs cannot deposit or withdraw from the LB, this ensures that value accrued to LB is reflective of organic trading activity on Ostium. When a position is closed, the LB provides capital to Positive PnL trades while accruing any value from Negative PnL trades. When one side is imbalanced, thereby seeing the OI skew away from 0, the LB absorbs the volatility in trader returns and helps stabilize the APY LPs earn. Consider the following possible states of delta exposure in the protocol based on market conditions; - **Perfect Balance**- When traders’ long and short positions are equal, the protocol’s delta exposure is 0, and the market is stable as the positions naturally offset each other. - **Imbalanced OI -** When there is an imbalance in trader positions, i.e more longs than shorts or vice versa, the shared liquidity layer steps in to cover the imbalance and to regain the delta exposure. - **Extreme Imbalanced OI -** When no traders are taking one side of the market (either all long or all short positions are closed), the liquidity buffer bears all the delta exposure. If a series of large trades with positive PnL are closed consecutively, there is potential for the Liquidity Buffer to be drained due to the settlements it must pay out. If this instance occurs, the protocol then turns to the Market Making Vaults (MMVs) for trade settlement. **Market Making Vaults** Ostium’s MMVs are smart contracts structured as liquidity pools, where LPs deposit capital to earn an APY defined by liquidation rewards and 50% of trader opening fees, for the delta exposure risk they take on. This will play a particularly important role in the early stages of the protocol, as it is likely that sustained trader PnL will take a while to accrue to the LB, therefore incentivizing LPs to deposit into the MMV will be crucial for the Ostium Protocol. Upon depositing capital into the MMV, LPs receive an Ostium Liquidity Provider (OLP) token which functions as a standard receipt-of-deposit. OLP tokens are minted upon deposit and burned upon withdrawal, and LP rewards are distributed on a rebasing model, wherein they are compounded directly to increase the value of the OLP token (if Alice starts with 100 OLP and earns 10% on rewards, she will have 110 OLP upon withdrawal). As a means of incentivizing stickier capital among LPs, Ostium will enable annualized locking boosts favoring long-term lockers with greater rewards. **Supporting Infrastructure** Ostium utilizes two critical off-chain infrastructure components, an oracle and an automated keeper system, designed to support operations on the Trading Engine and SLL as efficiently as possible. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/2c40bb7aa47f.jpg) **RWA oracle** In order to account for the intricacies of RWAs (i.e out-of-market hours, future contract rolls, price gaps at market open), especially when dealing with various long-tail assets which are less commonly traded and may see lower trading volumes and higher volatility, Ostium Labs developed an in-house oracle service configured to their unique needs. However, operating a fully in-house oracle service imposes significant trust assumptions on a protocol’s users’ behalf, as the outcome of their trades and liquidity provision depends on the functionality of that oracle. To ensure disintermediation and mitigate the associated risks with operating an in-house oracle, the node infrastructure is operated and managed by[Stork Network](https://docs.stork.network/stork-for-perps), an open data marketplace comprising a decentralized network of data publishers. Note that this model operates on a[pull-based oracle system](https://docs.arbitrum.io/build-decentralized-apps/oracles/overview#how-do-pull-oracles-work), meaning that prices are only communicated onchain when explicitly required for trade execution in order to save costs associated with constantly publishing data onchain. In short- Ostium’s RWA oracle is custom-built by Ostium Labs, while its nodes are operated and managed by Stork Network. **Crypto Oracle** Aside from RWAs, Ostium also offers leveraged trading of BTC and ETH. For these assets, prices are pulled using Chainlink[Data Streams](https://docs.chain.link/data-streams), which are purpose-built for providing applications with on-demand access to high-frequency market data. **Automated Keeper System** In order to execute and manage conditional trades (i.e. “go long HOG Prices at $80, take profit at $100”), perp DEXs utilize specialized agents called Keepers. It’s common practice for protocols to run the Keepers themselves before gradually decentralizing over time, though it’s never guaranteed they will, in fact, decentralize. The experiences of traders and LPs are still that much more dependent on the underlying protocol under this method. As such, Ostium has outsourced the responsibility of running their Keeper network to the Gelato Network; from day one,[Gelato Functions](https://docs.gelato.network/web3-services/web3-functions/understanding-web3-functions) will be used to monitor price requests routed onchain for market orders, as well as existing open trades for conditions necessary to trigger automated orders for RWAs. Automated orders include **Limit Orders, Stop Limit Orders, Take Profits, Stop Losses, and Liquidations.** **Fee Structure** Ostium seeks to ensure each source of risk in the protocol is mitigated through a strategic implementation of fees - Open Interest skew, high pool utilization, and high asset volatility. Ostium charges a fixed fee at opening a position and compounding fees for maintaining open positions. Fixed fees are used to pay for associated infrastructure costs, while variable fees are intended to mitigate the various protocol risks mentioned above. **Opening Fee** **feeProtocolOpen=makerCharge+takerCharge+utilizationCharge** When opening a position, Ostium charges an opening fee that is a function of five variables to account for external factors affecting a specific trade. Three of these variables are contingent on the trader's asset, leverage, and position size, and the remaining two are contingent on the protocol's OI skew and utilization conditions. Opening fees are sized according to their impact on protocol conditions; trades that increase OI skew (i.e. short position which increases short OI for an asset) create greater delta exposure for the LB and therefore incur a higher baseline fee. Additionally, if a trade pushes OI above a certain threshold during periods of high utilization, a utilization charge is also applied. As a means of encouraging arbitrage on Ostium, which is critical for maintaining stability and balance of prices, a trader is charged a “taker” fee if the amount of leverage exceeds 10x or if OI skew increases with their trade. Conversely, a trader is charged a “maker” fee if the amount of leverage is below 10x and OI skew reduces with this trade. **Maintenance Fees** Throughout the duration of a trade (while a position is open), compounding fees are applied to a) help steer the protocol OI towards equilibrium through**funding fees** and b) mitigate the directional risk exposure of LPs through **volatility fees**. The funding fee functions like a standard funding rate on perpetual exchanges, in that they are designed to close the gap between long and short OI, thereby bringing the protocol to an equilibrium and minimizing delta risk for LPs in the MMV. However, unlike CEXs where funding rate fees can be claimed, Ostium automatically charges the position value of the “popular” side and injects this value into the PnL of the “unpopular” side, and the returns are realized in a trader’s PnL at position close. Furthermore, this fee is **velocity-based,** meaning it is an integral of both the length and magnitude of prior imbalances. This design feature is intended to incentivize arbitrageurs to fully close OI imbalances, compensating arbitrage behavior to a greater extent if the negative externality from a prior state was greater. Expressed as a percentage per day, the formula can be mathematically represented as: Meanwhile, the **Volatility Fee** is intended to capture the externality of market volatility for LPs. The fee is automatically charged to a trader's position size and subtracted from position PnL at position closing. Considerably, from an LP perspective, a position that is 10x long on a relatively stable asset such as the Euro poses far less risk than a position that is 10x long on an asset such as Oil, which sees greater intraday swings. It’s important for LPs to be appropriately compensated for the additional volatility risk they may take on. However, it’s also important to ensure that this fee does not discourage traders from trading volatile assets and therefore impact the funding rate. As such, the **Volatility Fee**was strategically designed to be 10x lower than the **Funding Fee.**The fee is automatically charged to a trader's position size and subtracted from position PnL at position closing, and can be mathematically represented as: **fr​(v)=F(Vs(s−1)Vs−v​−s+1)** **LP Rewards** It’s worth mentioning that LPs who deposit capital into the MMVs receive a) 50% of opening fees, and b) 100% of liquidation rewards. To put it all together, here is what the flow of capital looks like at each stage of a trade on Ostium; **Opening trades**: a % of the initial collateral is reserved for the protocol opening fee and evenly (50/50) distributed between Market Making Vault (where LPs deposit) and Protocol Revenue. - **Holding trades**: volatility fee is accrued from period to period on the open positions and goes directly to the Liquidity Buffer. - **Closing trades****In the event of Positive PnL:***Liquidity Buffer > 0*: Liquidity Buffer settles trades;*Liquidity Buffer = 0*: LP MM Vault settles trades, if and only if the Liquidity Buffer is depleted (further details[here](https://ostium-labs.gitbook.io/ostium-docs/shared-liquidity-layer/market-making-vault)): - **In the event of Negative PnL:***Not Liquidated*: Liquidity Buffer receives traders losses;*Liquidated*: 90% of initial collateral (traders loss) goes to the Liquidity Buffer and the remaining 10% goes to the LP MM Vault (liquidation reward) **Risks and Considerations** The primary risk with trading perpetuals on any exchange comes down to **liquidation risk.** When opening a position, traders deposit collateral; with leverage, they can take on a position size that is substantially larger than the value of their collateral (up to 20x on Ostium). However, the flipside to this is that losses are magnified just as significantly as gains, potentially leading to rapid liquidation if the market suddenly moves against the trader. When a trader's losses equal the initial collateral used to open the position, the position must be liquidated to avoid the protocol from incurring bad debt (a deficit that must be covered). On Ostium, liquidations must occur before collateral value has declined to zero; therefore liquidation takes place when collateral value has fallen to 10% of original collateral deposited. While Ostium has developed a number of built-in mechanisms to mitigate directional risk that affects liquidations, traders opening positions with leverage must still be well-versed in these associated risks and implied losses. On the other hand, the greatest risk for LPs depositing into the MMV is directional exposure risk; this occurs when LPs are exposed to sudden price changes in the underlying market, caused by high OI imbalance and high volatility occurring simultaneously. The following matrix illustrates how directional exposure risk changes accordingly: ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/856894425911.jpg) [In collaboration with Chaos Labs,](https://www.ostium.io/blog/the-imbalance-score-a-novel-metric-for-rwa-focused-perpetual-dexes) Ostium developed the **Imbalance Score**, a metric for assessing the current overall directional exposure risk experienced by the protocol. The Imbalance Score takes into account not just the imbalances in open interest (OI), but also the volatility and correlations between different assets. In short, asset imbalances indicate the extent to which the market is skewed towards long or short positions on certain assets, assets with higher volatility contribute more to the risk score, and positively correlated assets pose greater risks than inversely correlated pairs. According to Ostium, the team plans to continue working with[Chaos Labs](https://www.ostium.io/blog/ostium-partners-with-chaos-labs) to actively monitor metrics impacting the protocol's variable directional exposure risk and making parameter recommendations as needed to manage risk accordingly. In order to mitigate directional exposure risk to LPs, Ostium employs a) the LB as a settlement layer of first-regard, and b) strategic fee structures to reward LPs for putting their funds at risk in service of protocol liquidity and help drive the protocol towards equilibrium by either closing the OI imbalance or charging higher fees in periods of high volatility. ### Competitive Landscape Perpetuals trading has been dominated in large part by centralized exchanges (CEXs), which can be explained by a lack of sufficient decentralized exchange infrastructure in the early stages of blockchain and crypto development (Uniswap V1 came out in 2018), as well as a lack of sufficient blockchain infrastructure to enable low fees and high performance. With both high performance Layer 1s (i.e Solana) and rollups (i.e. Arbitrum, Base) hosting increasingly greater amounts of onchain activity, blockchains are proving to be not only resilient, secure, ledgers for storing information, but also high-performance networks that can allow for near-instant settlement and transmission of information and value. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/cf6695d5f842.jpg) Ethereum dominance in perpetuals volume has significantly shrunk, indicating traders’ demand for high trading perps on high-performance chains, with a growing number of new L1s and L2s to meet this demand. **Ostium’s Edge** There are not many teams today building exchanges to facilitate trade of RWAs as perps onchain. As such, Ostium has an opportunity to gain first-mover advantage here and build a moat around its offering. That said, if Ostium open-sources its code, one could expect a number of forks to launch in addition to various protocols that can be built on top of Ostium. Forks are not a bad thing - sometimes imitation is indeed flattery, and a lot of forks can often be indicative of a good idea and strong core offering. That said, vampire attacks may be a cause for concern -a perps DEX may decide to offer similar markets to Ostium but with greater incentives for traders and LPs through inflationary token emissions (to this point - Ostium doesn’t have a token). However, Uniswap still dominates Sushiswap in most metrics today and Ostium will likely do the same if it moves and launches in a timely manner. Ostium open-sourcing its code also raises some questions here - what can be built on top of an RWA perps exchange? Would these developments benefit Ostium and if so, how? Can Ostium gain enough momentum and adoption initially such that potential competitors would instead be more incentivized to build on top of or integrate Ostium rather than trying to build a competitive product more directly (i.e something similar to the Curve/Convex ecosystem)? **Protocol KPIs & Roadmap** Given that Ostium is currently in its public testnet stage, protocol data must be taken with a grain of salt as numbers can change with mainnet launch. That said, looking at the[testnet leaderboard](https://ostium.app/leaderboard), the numbers for the latest competition look rather impressive; 15.9k total traders || 88.9k total trades || $13.54b in total volume Looking ahead, there are several things we’re excited about at Shoal; for starters Ostium just recently [completed its first smart contract audit](https://ostium-labs.gitbook.io/ostium-docs/security/smart-contract-audits) with Zellic and is expected to release details of another audit with Three Sigma in the near future as well; mainnet launch is imminent and apparently[95% complete](https://x.com/OstiumLabs/status/1808169035601006777); it appears than an[Ostium mobile app](https://x.com/OstiumLabs/status/1809317679599350135) is in the works as well. Additionally, we pose several questions for the Ostium team below, which could serve as guiding frameworks for future research. **Questions for Ostium** - Why build on Arbitrum / L2 versus an L1 like Solana, which is optimized for speed and performance that perps markets need?Why build on Arbitrum in particular? - How do you imagine the MEV landscape within commodities markets? How might this differ from crypto markets (if at all)? - With its open source code, does Ostium envision any products or services that can be built on top of the exchange? ### Closing Thoughts ### The Case for Bringing Capital Markets Onchain To reference Larry Fink’s grand vision of tokenization once more; imagine a globally accessible distributed ledger with hardcoded immutable evidence of who is buying, who is selling, who owns how many assets at any given time, with near-instantaneous settlement on top of everything. This scenario describes quite an egalitarian financial services industry, but it also speaks to what blockchains were ultimately built for - enabling transparency, immutability, and significantly faster settlement speeds relative to that of existing services and markets. Meanwhile, Grayscale’s Zach Pandl [argues](https://www.grayscale.com/research/reports/public-blockchains-and-the-tokenization-revolution) that many types of assets, such as equities, are served relatively well by their current digital infrastructure, and that it is less than obvious that public blockchains will be superior solutions. Instead, he makes the case that the potential key benefit from tokenization is **greater network effects**. By implementing a common platform to host all assets across the globe, we can create a financial system with greater functionality, access, and lower costs than today’s existing solutions. ### The Case for Ostium: Perps > Tokenization Ostium believes that perps will ultimately frontrun tokenized RWAs as the primary means of onboarding non-crypto assets to be traded onchain. Perps are as popular and successful as they are in crypto largely because they “[allow simple directional bets & abstract away the complexity of expiring futures and options](https://x.com/kaledora/status/1792942569879748692).” Where tokenization suffers from operational management and regulatory hurdles, perps offer significant efficiency and go-to-market advantages. All that’s really needed to set up a perps market onchain is sufficient liquidity and a robust supporting data feed. This becomes especially easier for protocols whose pricing feed infrastructure is deeply integrated with existing tradfi data service providers. Unlike tokenization and its associated complexities (i.e. composable KYC-enforced token standards), perpetual contracts do not require the underlying asset to live onchain - traders are only trading derivatives contracts here. To set up a liquid perps market onchain, there’s no need for the underlying spot market to be onchain or integrated into crypto directly. This isn’t to say tokenized markets won’t exist - *everything will eventually settle onchain one day*. Capital markets will likely gravitate towards blockchain networks for enforcement and verifiability, which would occur in two ways as eloquently described in[https://docsend.com/view/u53utyp2j4ycg7r6](https://docsend.com/view/u53utyp2j4ycg7r6)**[An Unreal Primer](https://docsend.com/view/u53utyp2j4ycg7r6)**; first by acknowledging RWA tokens as bearer assets in different jurisdictions, thereby enforcing owners’ legal protections and, second, by integrating collateral and other forms of lender protection directly into smart contracts to offer stronger assurances than that of existing legal systems. The reality, however, is that it will indeed take a **long time**for every liquid public market to be issued and settled on a blockchain, as it will take a long time for the blockchain to become the ultimate ledger of record and source of truth for financial institutions. Until then, perpetuals ultimately provide the better choice for traders as they provide more flexibility, leverage, and fractionalization than spot markets. Looking ahead, Ostium is betting that perps become the default listing engine for RWAs and can support markets liquid and deep enough to incentivize participation from traders of all backgrounds and appetites. One might argue that potential hindrance to the broader adoption of perps among retail investors is the *perceived* complexity of these financial instruments. As opposed to spot markets, perpetuals require accounting for a number of additional factors such as the relationship between collateral and leverage, how the funding rate works and how it affects PnL, the difference between underlying asset price and the price of the perpetual contract. That said, Robinhood made options fun and accessible to retail, which generated $154 million in revenue for them in Q1 2024 alone, and options are arguably more complex than perpetuals. Perpetuals have also been the single most successful product to be developed around crypto assets. **So perhaps all we’re missing for trading virtually any asset onchain is a user-friendly perp DEX after all.** ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/28d774594afc.jpg) *Where else can one bet on the price of hogs, soybeans, oil, forex, and more in one platform onchain?* ## References - Artemis Research. (n.d.). *A history primer on tokenization*. Retrieved from [A History Primer on Tokenization: Why Assets Will Move to Public Blockchains](https://research.artemis.xyz/p/a-history-primer-on-tokenization?utm_campaign=post&utm_medium=web) - Centrifuge. (n.d.). *Centrifuge*. Retrieved from[https://centrifuge.mirror.xyz/55xAwYhUBB9jHNFytS4u3jsG6HEkDzBljl253oEojBs?utm_source=interface.social](https://centrifuge.mirror.xyz/55xAwYhUBB9jHNFytS4u3jsG6HEkDzBljl253oEojBs?utm_source=interface.social) - Chainlink. (n.d.). *Real world assets (RWAs) explained*. Chainlink Blog. Retrieved from[https://blog.chain.link/real-world-assets-rwas-explained/](https://blog.chain.link/real-world-assets-rwas-explained/) - Deribit Insights. (n.d.). *Perpetual swap funding*. Retrieved from[https://insights.deribit.com/education/perpetual-swap-funding/](https://insights.deribit.com/education/perpetual-swap-funding/) - Grayscale. (n.d.). *Public blockchains and the tokenization revolution*. Grayscale Research. Retrieved from[https://www.grayscale.com/research/reports/public-blockchains-and-the-tokenization-revolution](https://www.grayscale.com/research/reports/public-blockchains-and-the-tokenization-revolution) - Modern Treasury. (n.d.). *History of ledgers*. Retrieved from[https://www.moderntreasury.com/journal/history-of-ledgers](https://www.moderntreasury.com/journal/history-of-ledgers) - Ostium Labs. (n.d.). *Ostium Labs*. Retrieved from[https://ostium-labs.gitbook.io/ostium-docs](https://ostium-labs.gitbook.io/ostium-docs) - RWA.xyz. (n.d.). *Tokenizing precious metals report*. Retrieved from[https://www.rwa.xyz/blog/tokenizing-precious-metals-report](https://www.rwa.xyz/blog/tokenizing-precious-metals-report) - Shiller, R. (1993). Measuring asset values for cash settlement in derivative markets: Hedonic repeated measures indices and perpetual futures. *NBER Technical Working Papers*, No 131. National Bureau of Economic Research, Inc. - SSRN. (n.d.). *Measuring asset values for cash settlement in derivative markets*. Retrieved from[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3353583](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3353583) - Uniswap. (n.d.). *Electronification trading and crypto*. Uniswap Blog. Retrieved from[https://blog.uniswap.org/electronification-trading-and-crypto](https://blog.uniswap.org/electronification-trading-and-crypto) ## Appendix **Defining Assets** As explained in [An Unreal Primer on Real World Assets](https://docsend.com/view/u53utyp2j4ycg7r6) explains assets consist of two key elements: representation and ownership. Representation refers to various factors dealing with the economic aspects of an asset (value, expiration, physical condition), while ownership refers to the legitimacy of an asset’s title in a ledger. The bottom line here is that assets are valuable economic resources, but secure ownership of these assets is just as valuable, if not more, than the underlying asset itself. After all, if anyone can claim they own someone else’s asset and proper measures to refute this claim are not in place, just how valuable is this asset in the first place? **Important Considerations for Tokenization** Another important consideration to make on the topic of tokenization are **token standards.**Token standards are key to enabling composability in DeFi - there are no better examples for this than the success of the Ethereum DeFi ecosystem built around ERC-20 and ERC-721 tokens. The recently implemented[ERC-4626 Tokenized Vault Standard](https://ethereum.org/en/developers/docs/standards/tokens/erc-4626/) enables yield-bearing assets which represent one’s share in an investment, like a liquidity pool, and accrue value directly. An issue arises when cross-chain transactions come into the picture: blockchains are siloed environments by nature which lack native mechanisms to interact with data outside its environment, even data from other blockchains. While protocols like the Cosmos IBC solve this problem for blockchains building on the Cosmos stack, they do not account for cross-domain transfers such as Cosmos <> Solana, Ethereum <> Solana. The good news is that a number of interoperability solutions are being created that ultimately solve this problem by using ‘alternative mechanisms’, such as lock-and-mint, mint-and-burn, as well as liquidity pool and intents-based protocols. However, this only solves for crypto-native assets and does not account for RWAs to be brought onchain. The point here is that a lack of a universal token standard creates a lack of composability and we can’t exactly “tokenize everything” without robust token standards in place first. Currently with ERC-4626, the process for real-world assets requires the submission of orders and a corresponding waiting period for fulfillment to account for the coordination of investments, redemptions, asset originations, and asset repayments. Users deposit tokens into a pool and receive tokens representing their share until the request is completed later. This doesn’t reflect the near-instantaneous settlement and performance benefits blockchains can provide to existing infrastructure, which is one of the key pillars of the case for tokenization. Proposals like[EIP-7540](https://eips.ethereum.org/EIPS/eip-7540), which would be an extension of ERC-4626 with asynchronous deposit and redemption support, are one potential way to approach this issue. However, for financial institutions, the ability to create and enforce a KYC (know-your-customer) standard is absolutely critical from a compliance perspective. Centrifuge, who has built a platform for tokenizing RWAs that is live and running since October 2020, describes what a token standard to link KYC information to a wallet can enable. Through this process, anyone can: verify onchain whether a wallet belongs to an individual or an entity, determine information about the person/entity, and can track who has approved this KYC information. With a KYC token standard, new possibilities are unlocked for composability and user experience; Centrifuge investments could be traded on secondary markets without the user needing to perform an additional KYC check. Looking more broadly: users could complete KYC once and interact with any permissioned protocol without additional onboarding steps. While this may sound like a nightmare for crypto-natives, consider that institutional adoption of blockchain and digital assets will not happen without mechanisms like this in place for legal and compliance reasons. Furthermore, a KYC-token standard will never become the de-facto standard for crypto assets at any point, even if it becomes widely adopted by financial institutions. We do strongly believe we will still be able to trade our magic internet coins anonymously if we wish to do so. Below we raise some questions regarding tokenization inspired by[Alex Weseley](https://substack.com/profile/210102385-alex-weseley) of Artemis Research and some of our personal theses for which teams and protocols are well-poised to benefit from tokenization; - How do different smart contract languages and infrastructure affect the implementation of tokenization?**Move**, a language optimized for security, features stronger security features regarding asset ownership than Solidity and is custom-built for blockchains as opposed to Rust which is a general-purpose language. However, given the Move ecosystem is still nascent, necessary infrastructure and tooling for interoperability between Move <> other VMs such as EVM or SVM arise. For this reason,webelieve[https://twitter.com/movementlabsxyz](https://twitter.com/movementlabsxyz)**[Movement Labs](https://twitter.com/movementlabsxyz)** is currently the best poised to fill this need. - How will privacy compute solutions (ZKPs, FHE, TEEs) factor into the equation for financial institutions, for whom privacy and security quite frankly matter ***much more***than the average onchain degen or retail investor? - What role will the nuances of different blockchain designs play? Will there be a winner-take-all outcome or will different blockchain designs serve different purposes and clients better? Furthermore - how will financial institutions approach developing their own **public**blockchain? What are the incentives to build an app-chain, L2, etc ? With this in mind, interoperability solutions are set up to play a paramount role in facilitating an interconnected system (SWIFT enables banks to communicate globally). So who are the key players poised to benefit from this? Personally,webelieve this would be **Chainlink CCIP, LayerZero, and Avalanche Teleporter**, in large part due to their ongoing integrations with financial institutions and partners. Intents-based bridge models like **Across** and **Debridge** cannot be discounted either here; the UX is significantly better and adoption of these protocols continues to grow slowly but steadily. If these protocols were to build solutions tailored for institutions we presumeinstitutionswepresume there would be a good deal of interest given their low costs and fast bridging speeds. Zooming out further, we’d also like to add some interesting questions raised in “[Electronification, Trading, and Crypto](https://blog.uniswap.org/electronification-trading-and-crypto)” with regards to the broader technological transformation implied by tokenization; - What does settlement look like in a world where it can be fine-tuned, so it no longer has to conform to market conventions around specific times or intervals? Is it possible to build primitives that let you choose settlement time, and what implications would such designs have on market functioning? - How might blockchains enable a move from price-time priority markets to markets based on fees and competition, and what might that mean for market structure and consumers? ### How Perpetuals Work To function, perpetuals need three key components - a market for matching buyers and sellers, a funding rate, and a spot index price. A **functional market** to facilitate the matching of buyers and sellers is essential for the exchange of any asset, from commercial real estate to memecoins to perpetual contracts. This market must be liquid and efficient to ensure that trades can be executed promptly and at fair prices, which is often facilitated by the use of market makers who are responsible for buying and selling assets in a structured manner for the purpose of injecting liquidity and trading volume into markets. Lastly, a robust trading platform and interface is necessary for trading to take place on. It’s crucial that the interface be as intuitive and easy to navigate as possible for market participants to open and close positions with minimal friction. The**spot index price** refers to an aggregated, real-time price that reflects the current market value of an asset, ensuring that the perpetual contract's price remains aligned with the actual market conditions. This provides a stable reference point for perpetual traders to rely on, by smoothing out any short-term anomalies or price discrepancies that might occur due to liquidity issues or disrupted price feeds. **The Funding Rate**facilitates price discovery for perpetual contracts. Futures contracts have predefined expiry dates and though they can and often do trade at a discount or a premium to their underlying asset, contracts are settled using the underlying spot price of the asset, thereby converging this margin to zero as the contract approaches its expiry. Conversely, perpetuals lack an expiry and therefore require an ongoing payment mechanism (settled every 8 hours) in which the counterparties pay one another depending on market conditions at a given time, known as **the funding rate.**When the funding rate is positive, that is, when the price of the perpetual swap is higher than the index, longs pay shorts. When the funding rate is negative, wherein the price of the perpetual swap is lower than the index price, shorts pay longs. Ultimately, settlement is based on the difference between the perpetual swap price and that of the[underlying](https://en.wikipedia.org/wiki/Underlying) asset, as well as the difference in[leverage](https://en.wikipedia.org/wiki/Leverage_(finance)) between the two sides if leverage is used. This mechanism is designed to balance market demand by ultimately encouraging the price of the perpetual to shift back towards the index price. ![](https://shoal.xyz/research/writing/bringing-macro-markets-onchain-with/img/2f6c0ce4b6ff.jpg) Similar to options and other derivatives contracts, perpetuals allow investors to speculate on the future price movement of an asset without having to own the underlying asset itself. This allows for anyone to open a position in a perpetual contract with leverage, meaning they can access and trade a larger amount of capital than the collateral (margin) to be posted on their account. For a short summary on leverage ratios: Leverage 2:1 = 50% collateral to be posted, Leverage 5:1 = 20% collateral to be posted, Leverage 10:1 = 10% collateral to be posted, and so on. This unlocks capital efficiency thereby allowing for a greater number of potential market participants, as one can now trade $1000 worth of BTC with just a few hundred dollars. Of course, it's important to note that leverage is two-fold and just as traders can access more capital with less upfront costs, the risks associated with doing so can often reverberate much stronger than buying and holding in spot markets. ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Ostium. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Particle Network: The Chain Abstraction Layer > Exploring the need for chain abstraction and how Particle Network is approaching this phenomenon. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-08-07 - Canonical: https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/ - Keywords: agent wallets, crypto, solvers, zero-knowledge, infrastructure, Ethereum, Bitcoin, Infrastructure ## Introduction ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/f828ae9b44ca.png) Decentralized applications, which refer to blockchain-native products and services, have existed since the onset of smart contracts and Ethereum. However, their user adoption has grown at a notably slow rate, especially relative to Web2 apps and services. When considering Netflix’s success, they overtook Blockbuster by capitalizing on the superior convenience and choice through the shift from physical DVD rentals to the world of digital services and streaming. The convenience of having the world at one’s fingertips with smartphones led to the adoption of mobile apps, which transformed the way people would interact with the internet much to the benefit of social networks. ChatGPT, which [surpassed Instagram and Tiktok as the fastest growing app](https://finance.yahoo.com/news/chatgpt-on-track-to-surpass-100-million-users-faster-than-tiktok-or-instagram-ubs-214423357.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAALulFClgx16WHXXvBNGcjz0Ckq-3t6fY6qvq7SnKdQiCaJ4PLEHFg6ZRk1YPbD0NwcHom6lls9s2w95ubikKJz_i89C1qV-IrpPvm4TD6mI1yQNhm6v8-jakG-8YYTQlfv2_i4FyRxy9neK0UqKPhCZST8CnnJB2xSYI5dVbKvb4), introduced a simple and powerful way for almost anyone to harness AI with a simplified chatbot UX utilizing natural language processing (NLP). The recurring theme among these breakout products and services and their success is that they provided a better user experience relative to any incumbents or competitors they went up against. In order for decentralized applications to achieve similar success, the onchain user experience must be as seamless and convenient as possible, far from the world of seed phrases and fragmented chains that is common today. ## Transforming the Onchain User Experience *The end-game for the onchain user experience requires no knowledge of any underlying blockchain infrastructure on the user’s behalf; where anyone can do anything on any blockchain without needing to go through arduous onboarding and bridging processes*. To better understand the significance of this design, however, it helps to consider the state of accounts today: an onchain account is ultimately the bridge between a user and the blockchain, storing balances onchain and defining all activities and interactions with any blockchain-native program. Throughout their history, most blockchains have utilized the externally owned account (EOA) model, which functions as a subset of two parts:  a **public key** serving as an identity and reference point for receiving assets (wallet address) and a **private key** serving as a master password for access (seed phrase). Wallets technically function as *account abstraction services*, in that they simplify the management of one or more onchain accounts. Though EOAs are known for their simplicity and granting the power of self-custody to anyone, they have also significantly hindered the onchain user experience thus far. The most common drawbacks to EOAs are that anyone who gains access to the seed phrase can access the wallet (this threat arises for those storing seed phrases on a cloud-based service like iCloud) and that anyone who loses access to their seed phrase and/or forgets it can no longer access their funds onchain. Key to enabling such an onchain user experience is the emergence of **abstraction primitives**, which are the many products and services built around abstracting away as many friction-inducing pain points in the onchain user experience as possible. These may come as toolkits and frameworks for developers to implement into their own network or apps, or direct user-facing products and services. As development in this area heats up and the number of teams launching their own abstraction primitives starts to grow, achieving a seamless onchain user experience may come sooner than most people think, as [Vitalik suggests](https://x.com/VitalikButerin/status/1820404774493110309). *But what exactly will enable this breakthrough?* **Account abstraction** refers to the separation of management of an onchain account from the end-user. The concept was [initially floated around as early as 2017](https://eips.ethereum.org/EIPS/eip-86), but mostly struggled to gain any traction before [ERC-4337](https://eips.ethereum.org/EIPS/eip-4337)was proposed in 2021. The initial culmination of efforts around account abstraction led to the development of the**smart contract-wallet**, commonly referred to as a smart account. In this model, an onchain account is managed by a smart contract, and can therefore be more programmable and optimized for user needs. This unlocks new possibilities, such as being able to sign up for an account using familiar social logins, paying for gas fees with the same asset across different chains, being able to perform multiple cross-chain transactions in one click, and more. Key to enabling account abstraction is the development of **execution abstraction**services, where the execution of an onchain transaction is outsourced to specialized service providers called *solvers* (also referred to as fillers or executors) for the best possible performance and delivery on the signer’s behalf. Here, users sign off-chain messages called *intents*containing instructions for performing onchain actions, i.e. transaction fulfillment requests. By separating the execution of a transaction from its signature, users can express desired outcomes more easily, and back-end solutions such as private mempools or competitive solver networks help deliver the best possible settlement and value for the user. **The Endgame: Chain Abstraction** Another critical component for enabling the ultimate onchain user experience is the ability to communicate and interact across different blockchain environments. Historically, users have relied on bridges for filling this need, which have [proven](https://defillama.com/hacks) over time to be a great source of risk and insecurity. Chain abstraction iterates on the developments around account and execution abstraction while introducing new infrastructure at the network layer, thereby removing the complexities of communicating and interacting across different blockchain environments.*See Shoal’s chain abstraction [deep dive](https://www.shoal.gg/p/c231627e-20ab-4630-ba00-9c2abe088199) for a comprehensive overview of the concept’s fundamentals and the broader chain abstraction landscape.* Chain abstraction is the culmination of efforts around one common goal: to provide a seamless user experience in which the user can perform onchain actions without being required to know which blockchain they are using at a given time. This report explores how Particle Network is approaching the development of the ultimate onchain user experience through its new chain abstraction stack. ## Case Study with Particle Network **Protocol Background** Led by co-founders Pengyu Wang and Tao Pan, Particle debuted in 2022 as a Wallet Abstraction service provider, launching a stack for developers to create non-custodial, dApp-embedded wallets that could leverage social logins via MPC-TSS technology. With the onset of ERC-4337 account abstraction the protocol shifted to include an AA stack into their existing WA stack, utilizing smart contract wallets for enhanced account structures. This set up the launch of [BTC Connect](https://blog.particle.network/btc-connect-bitcoin-account-abstraction/), which brought AA services to the BTC ecosystem via native Bitcoin signatures. Now, Particle is launching their Layer 1 blockchain as part of their comprehensive, multi-faceted chain abstraction stack. Particle Network is being developed by a globally distributed team of 30+ full-time employees, and has established partnerships with the likes of [Berachain](https://www.berachain.com/), [Avalanche](https://www.avax.network/), [Arbitrum](https://arbitrum.io/), [zkSync](https://zksync.io/) and [mor](https://blog.particle.network/many-blockchains-one-mission-introducing-the-chain-abstraction-coalition)e. The protocol has raised officially $25 Million over the course of several seed rounds led by Spartan Group and Gumi Crypto, and recently secured an [investment from Binance Labs](https://www.binance.com/en/blog/ecosystem/binance-labs-invests-in-particle-network-to--address-user-and-liquidity-fragmentation-in-web3-2579347885390894943) as well. ## Protocol Overview Particle Network is a modular Layer 1 built on the Cosmos SDK, which will function as a coordination and settlement layer for cross-chain transactions within a high-performance EVM-compatible execution environment. The Particle L1 is one component of Particle’s broader chain abstraction stack, which consists of Universal Accounts providing a simple interface for unifying token balances across different chains, Universal Liquidity enabling UAs on the backend, and Universal Gas allowing users to pay gas fees in any token they hold. The end-goal for Particle Network is to unify users across all chains at the account-level, facilitating seamless cross-chain interactions with a single balance and account on any L1,L2, or L3, and allowing anyone to easily pay gas fees in any token they wish. Let’s take a closer look at the various key components working to help meet that goal. ### Universal Accounts ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/960eb580a61f.jpg) Universal Accounts refer to the new account structure that will be powered by the Particle L1, and are key to Particle’s chain abstraction stack. At their core, UAs are ERC-4337 smart accounts attached to a pre-existing EOA (externally owned address), unifying token balances across multiple chains by automatically routing and executing atomic cross-chain transactions. For the end-user, UAs provide a single interface for managing funds and transacting across various dApps, abstracting away the friction-inducing pain points involved in setting up and funding a new account on a new chain, which often requires purchasing the gas token of that native chain as well. This interface is built on top of existing wallets and leverages Particle’s liquidity layer-Universal Liquidity- to execute atomic cross-chain transactions and route funds from a user’s balance across different chains as needed. Transactions are processed by Particle’s globally distributed network of nodes, which manage the associated bundling, relaying, and verification tasks. To better illustrate, consider the steps involved in fulfilling a user’s simple request to purchase Dogcoin on an external chain (chain X): 1. User connects to their UA through an existing wallet or social login. 2. User submits their transaction request to the Particle L1, expressed as an ERC-4337 UserOp to purchase Dogcoin on chain X. 3. Bundler nodes within Particle’s decentralized node network handle the associated UserOp and executes it accordingly. 4. Particle’s Relayer Nodes then monitor and synchronize the execution status on the associated chains. Once the transaction has been confirmed to be executed, the status is routed back from the chain to the Relayer Nodes, who communicate the status back to the UA and end-user. 5. Our user now has the token they wished to purchase in their UA balance, without ever interacting with the chain that token lives on. Evidently, there are more in-house components at work here that warrant further inspection. Think of UAs as Particle’s user-facing product. Key to enabling the seamless experience they provide are the Universal Liquidity and Universal Gas features. ### Universal Liquidity Universal Liquidity refers to the layer of the Particle Network responsible for the automatic execution of transactions submitted via UAs. This feature is powered by Particle’s distributed network of Bundler nodes, specialized services initiating the necessary steps for the execution of a UserOp, such as swapping or pulling liquidity from pools. In addition, a distributed network of Relayer nodes, referred to as the Decentralized Messaging Network (DMN), is responsible for monitoring transaction status on external chains (i.e. destination chains) and communicating their settlement status back to the Particle L1. The key purpose of Universal Liquidity is to enable users to interact with different chains via cross-chain transactions without needing to purchase and hold any tokens on the associated chains. To better understand, consider the following flow for a user wishing to purchase 100 USDC of Dogcoin on Chain D while they hold 25 USDC on chains A, B, C, and D each. 1. User signs UserOp to purchase 100 USDC of Dogcoin on Chain D, effectively bundling their balances across four chains (Chain A, B, C, D) into a single signature processed by the Particle L1. 2. Upon executing the signature, the USDC the user holds on Chains A, B, and C is sent to a Liquidity Provider (otherwise understood as a filler). 3. The LP releases the full USDC amount on Chain D. 4. The USDC on Chain D is swapped for Dogcoin using a local DEX. 5. The resulting Dogcoin balance is now reflected in the user’s UA. ### Universal Gas Universal Gas is the third pillar of Particle’s chain abstraction stack, key to enabling *gas abstraction*, wherein the friction-inducing pain point of acquiring and holding multiple gas tokens is abstracted away from the end-user, who can now pay gas fees in any token on any chain. Alice can pay for gas on a swap on Solana using her USDC on Base, while Bob pays gas for purchasing an NFT on Ethereum using his OP token on Optimism. When a user wishes to execute a transaction through a Particle UA, an interface will prompt the user to select their gas token of choice, which is then automatically routed through Particle’s native Paymaster contract. All gas payments are settled to their respective source and destination chains, while a portion of the fee is swapped into Particle’s native $PARTI token to be settled on the Particle L1. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/eb30c6725079.jpg) ## Protocol Architecture & Design ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/9c0b0eb1dabf.jpg) The Particle L1 utilizes a high-performance EVM-compatible execution environment and a dual-token staking model for security, consisting of BTC and the native PARTI token. Consensus and data availability are outsourced to a distributed network of nodes referred to as Modular Nodes. Particle employs an aggregated data availability model (AggDA) which plugs into a combination of providers including [Celestia](https://celestia.org/), [Avail](https://www.availproject.org/), and Near[D](https://near.org/data-availability)A, and is powered by a decentralized system of Aggregated DA node operators. On the backend, Particle’s chain abstraction stack is powered by three key modules: the **Master Keystore Hub, Decentralized Messaging Network (DMN), and Decentralized Bundler.** The **Master Keystore Hub**serves as the central source of truth across the Particle L1, coordinating smart contract deployments across all chains, synchronizing settings between each UA instance, and maintaining synchronized state across all chains. The**DMN** is responsible for communicating transaction execution status across different chains that a user is transacting on, and then communicating the status for the userOp to be settled on the Particle L1. This feature is powered by a network of Relayer Nodes. Lastly, Particle utilizes a **decentralized bundler network**, wherein a network of bundler node operators are responsible for initiating and executing incoming userOps. The network is built around a distributed, permissionless network of Modular Nodes, among which tasks are delegated and outsourced. ### Modular Nodes The use of**Modular Nodes** will allow for anyone to participate in running nodes specialized for facilitating critical operations on the L1. These nodes can be categorized by their respective function: **bundler nodes**areresponsible for the execution of cross-chain UserOps, **relayer nodes**areresponsible for monitoring and communicating the status of transactions (i.e. executed, failed) back to the Particle L1 to be settled, **watchtower nodes**areresponsible for monitoring the status of nodes and their respective tasks in the bundler and relayer networks, as well as providing execution and fraud proofs for each block per epoch. ### Aggregated Data Availability Model In the context of blockchains, data availability (DA) refers to the ability to verify data that has been published to a blockchain. Typically, blockchains will employ a single solution for DA, which can be in-house under an integrated architecture, or conversely outsourced to partners or third-party providers under a modular architecture. Particle is constructing its DA model to mitigate single points of failure across its architecture by adopting an aggregated model, outsourcing DA to Celestia, Avail, and Near DA collectively. Particle utilizes two different approaches to DA: **selective publishing**which allocates each block to a separate DA provider, and **redundant publishing**in which each individual block is sent across each DA provider. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/adbc7c6a8a19.jpg) It will be interesting to see if Particle expands to other DA providers (i.e. EigenDA) in the future as the sector expands. ### Dual Staking Blockchains which use a Proof-of-Stake model assign validators to propose and validate new blocks based on the number of native tokens they have staked to the network, rewarding them proportionally to the number of blocks they vote on. One key risk with these networks in early stages is the risk of price volatility in the native token impacting network security and stability. Particle aims to mitigate this risk through a dual staking model which will utilize BTC via the [Babylon](https://babylonchain.io/) staking protocol and the native PARTI token, with validator pools assigned for each respective token. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/06b3c8764881.jpg) ### Onboarding Process with Universal SDK Particle’s Universal SDK lets application developers create a seamless onboarding process to UAs, by enabling users to attach their existing wallets through the implementation of an [EIP-1193](https://eips.ethereum.org/EIPS/eip-1193) provider. This allows for users to be able to immediately be able to transact from their UAs upon signing in. The onboarding process within an application leveraging Particle Network’s Universal SDK is visualized below. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/bbff4e1794f4.jpg) ## State of Particle Network Prior to the development of the Particle L1, Particle saw over 17m wallet activations, 10m UserOps, and over 900 integrations with various decentralized applications, according to the team. On May 2, 2024, Particle Network’s incentivized L1 testnet [launched](https://blog.particle.network/particle-network-testnet-guide-airdrop/), offering point rewards through the [Particle Pioneer](https://pioneer.particle.network/en) platform. Particle Network’s [incentivized public testnet](https://pioneer.particle.network/en) allows users to test out its flagship Universal Accounts and Universal Gas features to earn points for allocation of the upcoming $PARTI token. According to the [Particle Testnet V2 explorer](https://scan-testnet-v2.particle.network/), there have been over 7.3m total transactions across 1.3m blocks, averaging above 400k daily transactions regularly. As per the Particle Pioneer [campaign website](https://pioneer.particle.network/en), the testnet has seen over 182m transactions, and there are currently over 1.49m users earning 27.3B points in total, at an average of 18.3k points per user. The Particle L1 is currently slated to launch on mainnet sometime in H2 2024. ## Competitive Landscape Chain abstraction is poised to become the next major framework for interoperability platforms to build around, and there are a number of developments on the horizon which will compete with Particle to become the standard toolkit or stack for building chain abstraction services on. **Near Network** Near is a sharded Proof-of-Stake Layer 1 blockchain that provides a full-stack application domain for developers building decentralized products and services. Near is building out its chain abstraction stack this Account Aggregation - a multi-faceted structure funneling users’ cross-chain interactions to be run through a single account. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/4ac019ae738a.jpg) Accounts on Near use two types of keys: **Full-Access Keys**, which function as private keys (i.e. can sign any transaction and should be kept private), and **Function-Call Keys**, which are granted permissions to sign calls exclusively to a specific contract or set of contracts. Near also utilizes its **FastAuth** login service to allow users to sign up for an account with an email and use biometrics instead of passwords. Key to enabling this structure are multi-chain signatures, which allow any Near account to interact with addresses on other chains. This is achieved through the NEAR MPC network, which enables key resharing and maintains the same public key even as nodes and key shares change. MPC signer nodes within the Near network allow smart contracts to initiate the signing process, creating numerous remote addresses on any chain. Near also introduced meta transactions through [NEP-366](https://github.com/near/NEPs/pull/366), enabling users to transact across multiple chains without holding the native gas token. This is facilitated by Relayers, third-party providers that attach the necessary tokens for gas fees to the signed transactions they relay to the network. **Polygon AggLayer** Polygon is developing [AggLayer](https://polygon.technology/blog/aggregated-blockchains-a-new-thesis), a unified bridge for L2s built using the Polygon CDK whichwill aggregate zk-proofs and uniformly submit them to Ethereum for settlement**.** In this model, all chains share a bridge contract with other supported AggLayer chains, thereby maintaining sovereignty while benefiting from a global liquidity hub that makes it easier to bootstrap early networks. ![](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/766039776487.jpg) The AggLayer will use ZK proofs to create an aggregated environment that “feels like a single chain” while allowing for supported chains to maintain their sovereignty. Application developers could potentially benefit from being able to reach more users, as users from different chains will be able to interact with their product or service as well. For the end-user, the goal is the same as in chain abstraction: to provide a UX that resembles the Internet – a single environment that doesn’t require cumbersome and frequent bridging and other complex processes. Thus far, the live components of the AggLayer that Polygon zkEVM has connected to are 1) a unified bridge to Ethereum for enabling cross-chain transactions, and 2) A bridgeAndCall() library of solidity contracts to help craft these transactions. ### Honorable Mentions Everclear - Formerly Connext, Everclear is developing a new chain abstraction stack.  As the name suggests, Everclear is launching “the first clearing layer” to provide global settlement of cross-chain transactions. Everclear will function as an Arbitrum Orbit L2, powered by[https://twitter.com/gelatonetwork](https://twitter.com/gelatonetwork)Gelato RaaS, and will use Hyperlane and Eigenlayer to connect to other chains. The protocol ultimately acts as a shared computer for coordinate cross-chain transactions, with settlements represented as invoices and cleared via a dutch auction. This will revolve around the use of Clearing Layers, “[a decentralized network that coordinates global netting and settlement of capital flows between chains''](https://x.com/EverclearOrg/status/1797645283977028021). Everclear aims to cut costs for market participants, is programmable and can be plugged into any settlement rail for any tx, and enable permissionless liquidity for new chains and assets from day one. Socket - [Socket 2.0](https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc)marks a shift for the Socket protocol from cross-chain to chain abstraction services, highlighted by its flagship Modular Order Flow Auction (MOFA) mechanism, which aims to enable a competitive mechanism for efficient chain abstracted markets. Traditional OFAs involve a network of various actors performing specialized tasks that compete to deliver the best possible outcome for an end-user request. Similarly, MOFA is designed to provide an open marketplace for execution agents, called Transmitters, and user intents. Within the MOFA, Transmitters compete to create and fulfill chain abstracted bundles, or ordered sequences of user-requests which require transfer of data and value across multiple blockchains. **Future Outlook** The chain abstraction opportunity is an exciting one. However, there are some important considerations to make as more teams set out to launch their own solutions, VCs start allocating more capital into anything that mentions ‘chain abstraction’, and users start scratching their heads around which solution is best. ## The Case for Abstraction Primitives Zee Prime Capital pointed out several important considerations with regards to the abstraction primitives landscape in a [recent post](https://zeeprime.capital/how-many-abstractions-do-we-need). “Without a product, chain abstraction is not a real solution to the real problem”. It’s certainly true that while user experience remains a critical hurdle for the crypto industry to overcome, it is likely not the ultimate bottleneck in bringing more users onchain. Indeed, developments in infrastructure grew as a response to poor UX imposed by high fees and slow settlement. Now that the infrastructure is here ([over 200 L1s/L2s](https://defillama.com/chains)), there is an overall lack of successful products and services being built on top of this infrastructure.  This aligns with a perspective [Mert](https://x.com/0xMert_/status/1812835098191917528) shared recently, who claimed not enough people are considering that barriers to building strong crypto apps are not crypto-native (i.e. infrastructure, UX) but instead revolve around regulatory unclarity and misaligned incentive structures across the broader industry. One example is the adoption (or lack thereof) of smart wallets. ![tweet](https://shoal.xyz/research/writing/particle-network-the-chain-abstraction/img/f4102850f976.jpg) Despite the innovations they bring, smart wallets have largely failed to gain meaningful adoption thus far. Incumbents like Phantom set record number of downloads with the onset of the memecoin mania back in Q4 2023/Q1 2024, demonstrating people are willing to deal with seed phrases and clunky UIs for now, as long as they can get their hands on the latest dog token. To push back, developing successful products and services with new technology takes time. It took years of trial and error for the first class of successful web-based application to emerge. As the demand for blockspace on base layers grows, it’s likely there will be more rollups and app-specific chains coming over the years. With the onset of RaaS providers and modular infrastructure solutions like Celestia, it’s only going to become easier to launch new chains and environments, and these environments will need to be able to seamlessly communicate with one another. The need to abstract chains away from the end-user comes from building a popular app that will entice users from other chains to want to use it, prompting the need for services for enabling a seamless experience to do so. Chain abstraction intends to solve the fundamental issue of a lack of seamless cross-chain functionality, something which a current lack of available products and services does not invalidate. With this in mind, one critical challenge abstraction primitives will have to contend with is ensuring the successful coordination across solver/node networks regarding state attestation, solver execution, transaction status, block confirmation, and other cross-chain guarantees, all of which require consensus. The nature of capital markets sees that another faster, cheaper solution will always be on the horizon, meaning chain abstraction service providers must account for a number of complex backend processes and their implications, where things like timing games and order flow capture start to play a bigger role over time.. ### Important Considerations for Particle Network A key question that arises with Particle’s network of distributed nodes is just how decentralized this network will be. Will there only be a select few entities participating in operating nodes, or will Particle be able to gain enough traction to maintain a sufficiently-decentralized node network? And how can Particle successfully incentivize enough node operators to become sufficiently decentralized in the first place? **For this, we suggest two things:** 1) Minimizing barriers to entry and participation as a node operator 2) Providing a public dashboard for monitoring and observing the decentralization of the node network via the Particle explorer. Particle is building a settlement and coordination layer for atomic cross-chain transactions, where Universal Accounts replace the need to use multiple wallets, purchase multiple gas tokens, and bridging tokens to use dApps on other ecosystems. This brings up the question of value accrual; what economic impact will the successful adoption of Universal Accounts and the Particle L1 have on other blockchains and ecosystems? Will they benefit from a greater number of users accessing their applications? ## The Case for Chain Abstraction and Particle Network The need to transform the state of the user experience on blockchain-native applications is not a new idea, and developers have worked on this problem for some time now. Chain abstraction stands to benefit the end-user by creating easier-to-navigate onchain experiences, the application developer by unlocking new user bases for their apps, and the L1/L2/L3 by allowing for cheaper and more efficient cross-chain communication and routing. Particle is building account-level chain abstraction to aid in this endeavor. By unifying cross-chain interactions into a single interface with Universal Accounts, allowing users to transact on any chain with Universal Liquidity and to pay for gas in any token with Universal Gas, the Particle Network L1 is well-poised to be a leader in moving the future of chain abstraction forward. Vitalik claims there is “[lots of energy and will](https://x.com/VitalikButerin/status/1820404774493110309)” to make the seamless onchain user experience a reality. Improved user experience alone won’t bring millions of users onchain, but it is one of the most important steps to take in order to do so. ## References Masmoudi, M. (2022, February 14). An overview of Multi-Party Computation (MPC), Threshold Signatures (TSS), and MPC-TSS Wallets. *Medium*. Retrieved from [https://mmasmoudi.medium.com/an-overview-of-multi-party-computation-mpc-threshold-signatures-tss-and-mpc-tss-wallets-4253adacd1b2](https://mmasmoudi.medium.com/an-overview-of-multi-party-computation-mpc-threshold-signatures-tss-and-mpc-tss-wallets-4253adacd1b2) Ethereum Foundation. (n.d.). ERC-4337: Account Abstraction using Alt Mempool. Retrieved from [https://eips.ethereum.org/EIPS/eip-4337](https://eips.ethereum.org/EIPS/eip-4337) Wang, P. (2022, October 10). Pengyu Wang reveals the secrets to Particle Network's rapid success. *Hackernoon*. Retrieved from [https://hackernoon.com/pengyu-wang-reveals-the-secrets-to-particle-networks-rapid-success](https://hackernoon.com/pengyu-wang-reveals-the-secrets-to-particle-networks-rapid-success) Particle Network. (2024, June 20). Particle Network secures $25 million in funding. *Particle Network Blog*. Retrieved from [https://blog.particle.network/25-million-funding/](https://blog.particle.network/25-million-funding/) Particle Network Developers. (2023). Documentation. *Particle Network*. Retrieved from [https://developers.particle.network/docs/particle-chain](https://developers.particle.network/docs/particle-chain) Polygon Technology. (n.d.). Aggregated Blockchains: A New Thesis. Retrieved from [https://polygon.technology/blog/aggregated-blockchains-a-new-thesis](https://polygon.technology/blog/aggregated-blockchains-a-new-thesis) NEAR Protocol. (n.d.). Unlocking Web3 Usability with Account Aggregation. Retrieved from [https://pages.near.org/blog/unlocking-web3-usability-with-account-aggregation/](https://pages.near.org/blog/unlocking-web3-usability-with-account-aggregation/) Everclear Organization. (n.d.). Retrieved from [https://x.com/EverclearOrg/status/1797645283977028021](https://x.com/EverclearOrg/status/1797645283977028021) Socket Protocol. (n.d.). Retrieved from [https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc](https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc) ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Particle Network. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # The Case for AI Agents in Web3 Gaming and Entertainment > Exploring how AI agents stand to be the “Ace in the Hole” for web3’s gaming & entertainment verticals, with supplemental case studies. - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2024-06-25 - Canonical: https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/ - Keywords: AI agents, crypto, infrastructure, gaming, AI & Agents ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/c672b36d493c.jpg) **Table of Contents** 1. Introduction 2. What are AI agents 3. Types of AgentsAgents as your friend NPCVirtual Companions 4. Case StudiesVirtuals Protocol Echelon PrimeHonorable Mentions 5. Challenges Facing the Broader AI Agents Landscape 6. Catalysts for Adoption 7. Closing Thoughts ### Key Takeaways - **Transformation through AI Agents**: AI agents are set to revolutionize gaming and entertainment by providing personalized, dynamic and immersive experiences, far surpassing traditional user-generated content. - **Advancements in AI Technology**: Key advancements, like reinforcement learning, neural networks and generative models (GANs), are crucial for developing sophisticated AI agents. - **Integration with Blockchain**: Blockchain offers a secure, immutable and transparent environment for deploying AI agents, significantly enhancing their capabilities and reliability. - **Case Studies in AI Innovation**: Virtuals Protocol and Echelon Prime exemplify how AI agents can unlock new opportunities in gaming and entertainment through their innovative applications and decentralized ecosystems. - **Challenges and Regulatory Needs:**Ensuring seamless communication, robust infrastructure and ethical use is critical for AI agents. Further regulation and safeguards like ‘kill switches’ are essential to prevent misuse and build trust. - **Future Prospects**: The continuous evolution of AI agents will likely expand into audio-to-video domains and broader consumer applications, driving mainstream adoption and innovation. ## AI Agents: The “Ace in the Hole” for Web3’s Gaming & Entertainment Verticals ### The Rapid Evolution of Gaming and Entertainment The gaming industry is experiencing a transformative moment with the rise of user-generated content (UGC). Major titles, like Roblox and crypto-native metaverses such as The Sandbox, are enabling users to create and personalize their gaming experiences. This shift towards UGC is further enhanced by the advent of AI virtual assistants and companions, which not only help personalize games but also become another form of UGC themselves. Users will soon begin fine-tuning their own companions, potentially making them available for others to interact with, similar to how user-trained variations of chatbots like jobGPT and TutorGPT have emerged. Google DeepMind's achievements in AI, particularly with its recently-advanced chess engine, highlight the potential of AI agents within gaming. This engine surpasses the previous AlphaZero record by employing multiple AI agents with different play styles, forming a grandmaster capable of mastering every variation of play. This ["searchless" chess engine](https://www.marktechpost.com/2024/02/19/checkmate-with-scale-google-deepminds-revolutionary-leap-in-chess-ai/) understands positions through evaluation, selecting the best-suited agents for each chess opening, mimicking human’s diversity of thought and creativity. Many established blockchain-native AI protocols have focused on decentralized computing and governance frameworks, laying the groundwork for responsible AI development. With these foundations in place, developers are now turning their attention towards more complex AI models, such as AI agents, which can perform autonomous tasks with minimal human intervention. Blockchain technology has further fueled this evolution by providing a decentralized infrastructure that ensures transparency, security, and immutability of transactions. Integrating AI agents into these standardized environments can create more collaborative and personalized experiences for users, transforming the gaming and entertainment industries in ways that may still be difficult to imagine. ### What are AI Agents? At its core, an AI agent is software programmed to independently [interact with its environment, gather data from its interactions](https://aws.amazon.com/what-is/ai-agents/), and utilize the data to meet its predetermined objectives. Objectives can range from task automation to more complex decision-making processes. Key to AI agents is their autonomous nature, wherein human intervention is intended to be as minimal as possible in the execution of a given objective. These programs autonomously perform tasks with both "read" and "write" access. Unlike popular AI applications today, such as ChatGPT, which can only gather information in response to questions (read access), AI agents can also take actions based on the gathered information (write access). ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/81fad719aaec.jpg) The origins of autonomous agents can be traced back to broader efforts throughout the 1980s and 90s to design machines which could learn from their environment and make informed decisions without manual human intervention. The development of various machine learning, deep learning, and neural network algorithms would then set the stage for the rise of more advanced forms of agents seen today, such as Google DeepMind's new chess engine, which uses multiple AI agents to master various play styles. **Advancements in AI Methodology** Reinforcement learning has been instrumental in developing AI agents that can autonomously navigate complex environments and achieve specific goals. Neural networks, particularly deep learning models, allow AI agents to process large amounts of data and recognize patterns, expanding their potential applications in various domains, including gaming and entertainment. One of the significant breakthroughs in AI methodology that has empowered AI agents is the development of Generative Adversarial Networks (GANs). GANs consist of two neural networks, a generator and a discriminator, that work together to create realistic data. The generator creates data, and the discriminator evaluates it against real-world data, providing feedback to improve the generator’s output. This iterative process has enabled the creation of highly realistic virtual characters, environments, and even art, making GANs particularly valuable in gaming and entertainment. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/7da4fae85a41.jpg) Another important advancement is transfer learning, where pre-trained AI models on large datasets are fine-tuned for specific tasks. This approach has dramatically reduced the time and resources needed to develop sophisticated AI agents. Transfer learning allows AI agents to leverage existing knowledge and adapt it to new environments and tasks, making them more versatile and efficient. ### AI Agents at Work ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/ad2efe19a499.jpg) In a multi-agent system, which involves multiple agents collaborating towards a shared goal, AI agents are expected to delegate tasks to other AI agents in order to facilitate a collaborative and efficient workflow. This process involves a generalized AI assistant being given a task, researching the required steps, and assigning specialized AI agents to each step. These agents then work as a team to complete the task, with additional agents involved for quality control and oversight, minimizing the need for human intervention. In the context of gaming, AI agents can enhance the gaming experience by providing intelligent and responsive non-player characters (NPCs), generating dynamic content, and offering personalized interactions. These agents can adapt to the player's preferences and behavior, creating a more engaging and immersive experience. Furthermore, AI agents can assist in the development of games by automating repetitive tasks such as bug testing, level design, and character animation. This automation can significantly reduce development time and costs, allowing developers to focus on creativity and innovation. AI agents can also be used to analyze player data, providing insights into player behavior and preferences, which can inform game design and marketing strategies. The integration of AI agents into virtual reality (VR) and augmented reality (AR) environments opens up new possibilities for immersive experiences. AI agents can act as guides, companions, or adversaries in VR and AR worlds, providing real-time interactions and adapting to the user’s actions and surroundings. This capability can enhance the sense of presence and immersion, making virtual experiences more engaging and realistic. ## Types of Agent-based Gaming or Entertainment ### Virtual Companions Virtual companions are agents which offer individualized experiences with the user, designed to learn from their interactions with the user, adapting their responses and actions to better align with the user's preferences. These companions can range from idols which can interact with fans individually, to virtual friends or partners which can provide companionship, and virtual pets can simulate real pets. By utilizing user preferences to provide tailored experiences across different platforms, these agents unlock new possibilities in user's experience by creating a sense of companionship and connection. Virtual idols can engage with fans through personalized interactions, such as responding to messages, participating in live streams, and creating custom content. This level of interaction can deepen the connection between the idol and their fans, enhancing the overall fan experience. Virtual friends and partners can provide emotional support, companionship, and entertainment, making them valuable tools for combating loneliness and social isolation. Virtual pets can offer a unique form of companionship, simulating the behaviors and interactions of real pets. These AI-generated pets can learn from their interactions with the user, adapting their behaviors to better align with the user's preferences. This capability enhances the user's experience, making virtual pets more engaging and enjoyable. Virtual companions can also play a role in educational and therapeutic contexts. For example, AI tutors can provide personalized learning experiences, adapting to the student's learning style and pace, and in therapy, AI companions can offer emotional support and cognitive-behavioral therapy exercises. ### NPCs AI agents can be utilized as non-playable characters (NPCs) in video games, enhancing gaming experiences by retaining concepts across different games with cross-game memory. For example, an AI agent that plays NBA 2K with a user can also play PUBG on their phone and remember preferences across platforms. This cross-game memory allows for a more cohesive and personalized gaming experience, as the AI agent can adapt to the user's preferences and behavior across platforms. AI-generated NPCs can provide more dynamic and interactive gameplay by reacting to the player's actions and decisions. These NPCs can exhibit complex behaviors and adapt to the changing game environment, creating a more immersive and engaging experience for the player. Additionally, AI-generated NPCs can generate unique content, such as quests, missions, and challenges, enhancing the replayability and longevity of the game. The ability of NPCs to learn and adapt over time can create a more realistic and engaging gaming experience. For instance, NPCs can develop relationships with players, remember past interactions, and alter their behavior based on previous encounters. This dynamic interaction can make games more immersive and provide a deeper sense of connection between players and the game world. ### AI-Generated Content (AGC) AI agents can create gaming assets and unique experiences for each player, extending the concept of user-generated content (UGC). This capability allows for dynamic and personalized game environments that adapt to individual player preferences. AI-generated content can include custom levels, quests, missions, characters, and items, enhancing the diversity and replayability of the game. AGC has the potential to be exponentially more transformative for gaming than traditional UGC. This potential depends on the quality of the AI agent and its ability to effectively communicate with and understand the environment in which it is building. High-quality AI agents can generate content that is diverse, engaging, and seamlessly integrated into the game world, significantly enhancing the overall player experience. Imagine a world where AGC and UGC come together to create new, innovative worlds. In this scenario, AI agents could assist players in designing and building their creations, offering suggestions, automating repetitive tasks, and enhancing the complexity and detail of the content. Players, in turn, could fine-tune and personalize the AI-generated content, resulting in a collaborative creation process that blends the best of both worlds. This symbiotic relationship between AGC and UGC could lead to the development of vibrant, ever-evolving game worlds. Players could explore environments that are continually being enriched by both the human imagination and the power of AI generation, creating a dynamic and immersive gaming experience. ## Case Studies ### Virtuals Protocol Virtuals Protocol is building an AI x Metaverse protocol that aims to be the future of virtual interactions. Their vision is to create a future where the worlds we engage with from our desks and couches aren't just escapes but extensions of our lives. Here, virtual interactions are hyper-personalized and hyper-immersive, enabled by AI and built in a decentralized manner. As we increasingly integrate with virtual spaces, our interactions within these spaces will become more significant. Indeed, the transition to virtual spaces is looking increasingly inevitable. Virtuals Protocol is building multimodal (text, sound, visual) AI agents that can enhance these interactions in various ways. These AI agents can behave like mirror copies of popular IP characters, perform specific tasks, or act as personal copies of users themselves. Here are some real-world examples of how these multimodal AIs can be used: 1. **Mirror Copies of IP Characters**:A game where players can interact with a digital replica of John Wick, who not only looks and sounds like the character, but also exhibits his unique fighting style and personality. This can make gaming experiences more engaging and authentic. 2. **Task-Specific AIs**:**Horror Story Narrative Builder**: An AI that can generate immersive horror narratives, adapting the story based on the player's choices and interactions.**Competitive DOTA Coach**: An AI coach that can analyze your gameplay in real-time, offering tips and strategies to improve your skills and performance in competitive matches. 3. **Personal Copies of Users**:**Virtual Assistants**: AI agents that learn from your behavior and preferences to help manage your virtual and real-world tasks, such as scheduling and reminders. **How Virtuals Protocol Works** ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/bb0c4351a229.jpg) Virtuals Protocol operates like a decentralized factory, producing AI agents that respond via text, voice and motion. Contributors add data and create AI models, validators ensure quality, and DApp founders use these agents to create immersive experiences. The AI agent modules include cognitive, voice and visual cores, each contributing to the agent's multimodal capabilities. The cognitive core processes information and makes decisions, the voice core enables auditory interactions, and the visual core provides a visual identity for the agent. These modules work together to create cohesive and interactive AI agents. One of the key features of Virtuals Protocol is its audio-to-animation capability, allowing AI agents to generate animations based on audio inputs. This capability enhances the realism and immersion of virtual interactions, making AI agents more engaging and lifelike. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/461d5e6644a3.jpg) Virtuals Protocol's decentralized approach ensures that AI agents are created and maintained by a community of contributors and validators. Validators play a crucial role in maintaining the integrity and quality of the ecosystem while contributors can share their individual expertise and resources, improving the quality and functionality of AI agents. **Virtuals Business Model** In order to coordinate behaviors among the various participants in its ecosystem, Virtuals Protocol utilizes its native $VIRTUAL token as a key feature of its business model. This economic model is largely contingent on a positive reflexive economic cycle referred to as the “Virtual-ous” flywheel. Contributors are paid in $VIRTUAL tokens to develop virtual agents. These tasks could range from chatbot functionality and domain knowledge, to implementing audial and visual characteristics. These agents are then integrated into various decentralized applications (DApps) within the Virtuals ecosystem, which leverage the agents for various business operations for which the agents charge a fee. The revenue generated from these fees are then routed back into the protocol, which uses these funds to buy back $VIRTUAL tokens from the open market. This buyback serves to replenish the treasury with $VIRTUAL tokens, ensuring a steady supply for future incentives for contributors. Furthermore, **$VIRTUAL**token holders can indicate which agents they believe should receive more token emissions by staking their tokens accordingly. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/f9aa9034b398.jpg) **Future Outlook and Considerations** Today, Virtuals has seen 888.4k inferences on its platform, 175 active validators, 350 active contributors, and over 1k AI agents already contributed, as per the team’s [self-reported statistics.](https://docs.google.com/document/d/1_Mr6LYqg7_fDfqKtDGLgcdKNSMSJEZno7jxc8Xc1geM/edit#heading=h.72lh6r9uty9a) Virtuals’ goal is to democratize the creation and monetization of AI agents, making high-quality virtual interactions accessible to a broader audience while pushing the industry in the right direction. Despite its promising vision, however, Virtuals Protocol may encounter significant challenges in sustaining and engaging a community over time due to market saturation. Decentralized AI protocols rely on a diverse set of stakeholders, including validators and contributors, to function effectively. Contributors, however, can easily be enticed by better incentive programs offered by competitors. In turn, without a steady organic stream of contributors, validators may not earn enough to maintain their presence, jeopardizing the entire ecosystem's stability. One potential solution is to enforce exclusivity (at least temporarily) of contributors’ AI agents to the Virtuals Protocol in exchange for monetary rewards, incentivizing protocol growth through token incentives. However, this solution may not be viable for a number of reasons; primarily given the open-source nature of the protocol and that this concept generally contradicts the ethos of decentralization and openness that underpins the crypto community, while also being economically unsustainable over an extended period of time. Maintaining a balance between incentivizing contributions and adhering to these core principles remains a critical challenge for Virtuals Protocol and similar projects. Generally speaking, the developers contributing their AI models are the big winners in this blockchain-enabled future of decentralized AI repositories. Consider the similarities to the “[streaming wars](https://www.cbsnews.com/news/streaming-wars-the-fight-for-viewers/)” – content is king. ### Echelon Prime Parallel Studios, which has previously launched [Parallel TCG](https://parallel.life/) and is stewarded by the Echelon Prime Foundation, is launching Colony. Colony is a new AI-powered Web3 survival simulation game built around highly autonomous AI agents called ‘avatars’. Players must guide and collaborate with their avatars to navigate a future Earth dotted with distinct colonies, all competing for survival. These AI avatars possess wide-ranging skills and capabilities, autonomously engaging with the environment via dedicated, token-bound [smart contract wallets](https://eips.ethereum.org/EIPS/eip-6551#overview). ![Parallel avatar NFTs](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/9d86081c4543.jpg) **How Avatars Work** Echelon Prime's AI avatars are designed to simulate human behavior, interacting with the world and formulating individualized approaches to different opportunities and challenges. At the level of a single game session, a player generally begins by chatting with their avatar, getting updates and discussing new ideas or missions the player may have for their avatar. With updates from the avatar having been transmitted, the player will determine tasks for the avatar to pursue. These can range from political activities, such as campaigning for a role within their colony, to pursuing personal goals, challenges, or actions specifically intended to contribute to the colony’s growth or success. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/646c5999403a.jpg) Once tasks are established, the avatar will proceed to complete them autonomously, managing its own survival stats by stopping to rest, eat, drink, and socialize as required. The AI avatars in Colony are designed to adapt to their environment, learning from their interactions and experiences. This continuous learning capability allows them to develop unique personalities and worldviews based on their identities and objectives. As a result, each avatar can offer a distinct and personalized experience to the player. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/0ff3e92aab9c.jpg) By providing a shared set of resources and tools, the Echelon Prime Foundation enables game studios to build within a standardized environment, enhancing interoperability and enriching the overall gaming experience. To bolster proactive participation from its vibrant community of developers and players, Echelon Prime implements a revenue-sharing mechanism for game studios and contributors. The “Prime Redistribution Mechanisms” ensure sustainable token distribution within the Prime ecosystem. Tokens are distributed dynamically based on the difficulty of tasks, activity levels, and overall participation rates within the game. The primary vehicles for these distributions are in-game sinks where players spend PRIME tokens to access specific features. This approach supports a predictable and sustainable token supply, rewarding player participation and contributions effectively. The governance processes within Echelon Prime determine the exact tuning of these redistribution algorithms to ensure fairness and sustainability. Projects building on the Echelon ecosystem are required to detail their PRIME sink redistribution schedule and pass an Echelon community governance vote prior to accessing Echelon’s P2E pool and PRIMEsets, as well as Echelon-approved NFTs if applicable. As with all games within the Echelon ecosystem, successful Colony players earn rewards in PRIME tokens, which they can use to pay for things in-game or sell. Leaderboards track competitions in different categories, with top players receiving the redistributed PRIME rewards for their accomplishments. Expected to launch in Q4 2024 - Q1 2025, Colony is a highly anticipated development in AI-agents gameplay, which will also utilize crypto assets as a key component of its in-game digital economy. ### Honorable Mentions **[Metapals](https://www.metapals.ai/):** Metapals offers AI companions that provide personalized interactions and support. These companions learn from user interactions, enhancing their ability to provide companionship, entertainment, and emotional support. By continuously adapting to user preferences, Metapals aims to address issues related to loneliness and social isolation, offering a more engaging and emotionally intelligent digital experience. **[NIM Network](https://nim.network/):** NIM Network is an AI-focused blockchain designed to optimize the development of AI agents for crypto games. By leveraging decentralized computing infrastructure, NIM Network enhances the performance and reliability of AI agents. This approach allows game developers to deploy more sophisticated and responsive AI within their games, improving overall user experiences and pushing the boundaries of what is possible in digital gaming environments. **[Ultiverse](https://www.ultiverse.io/home):** Ultiverse is an AI-powered platform for crypto game production, integrating existing large language models (LLMs) to create more immersive and dynamic gaming environments. The platform supports developers in creating games that are both entertaining and adaptive to player behavior, thereby offering a more personalized and engaging gaming experience. **[Replika](https://replika.com/):**Replika is a pioneering AI friend startup that provides highly personalized and engaging interactions. It focuses on offering emotional support, companionship, and entertainment through advanced conversational AI. Replika's AI learns and evolves based on user interactions, making it a valuable tool for individuals seeking meaningful digital companionship and support, particularly in combating loneliness and providing mental health support. While not a blockchain-enabled AI, Replika exemplifies the potential and current use of AI companions. ## Challenges Within the Broader AI Agents Landscape As is often the case with new and complex technologies, there are a number of key challenges that must be overcome to see the successful development and adoption of AI agents across various industries such as gaming and entertainment. Some of the broader hurdles to overcome are as follows: ### Data Privacy and Security The onset of AI agents exponentially increases the overall breadth and volume of personal information and sensitive data that can be gathered and accessed. This is due to the ongoing human <> agent communication that is required, wherein the human provides instructions to the agent. As agents collect data from their interactions to reference for future operations, the issue arises in the nature, type, and purpose of information collected when humans are providing instructions to the agent. During communication with an AI agent, humans often assess the potential benefits and risks of sharing certain information, which in turn affects their usage behavior. The extent to which the risk of disclosing private information affects behavior thus plays a key role in the quality of experiences and the overall adoption of AI agents. [Prior studies](https://www.researchgate.net/publication/341688904_Amazon_vs_My_Brother_How_Users_of_Shared_Smart_Speakers_Perceive_and_Cope_with_Privacy_Risks) have shown that users of smart speakers, such as Amazon’s Alexa and Google’s Echo, are unable to differentiate between input data that is collected and data that is kept private. This broader trend in consumer behavior is unlikely to change with the onset of consumer-centric AI-agents and applications. Meanwhile, [research](https://cyberpsychology.eu/article/view/14023) conducted on user privacy concerns and the nature of AI agents and assistants found that the higher the level of intimacy and familiarity a human feels with an agent, the more insensitive to their privacy concerns they become, which is particularly relevant in the context of entertainment motivations. More importantly, however, is that the user may feel more liberal in revealing their private information while forming intimacy with an AI agent when the user operates an AI agent as a useful device serving various utilities in their daily life. ### Key Ethical Concerns Assuming AI-agents are implemented in various enterprise and commercial settings, there is a natural concern which arises regarding the economic incentives upon which AI-agents are developed. Sacrificing the well-being of the consumer and broader society for economic benefit is not new in the world of corporations and enterprises*.*That said, in a world where politics and activism are playing an increasingly important role, this can bring attention to developers and sellers of AI-agents if ethical issues begin to surface. However, social media applications were found to be detrimental to the mental health of teenagers before and, while there may have been some fuss in the press at the time, precautions to protect youth from these technologies have been few and far between. A key ethical concern in the development of AI applications is the objectivity in the outputs they produce. An AI model itself is not biased, rather it is merely a reflection of its training input data. As such, it is paramount that the data collected and the processes are as holistic and objective as possible. **Societal Impacts of AI Companions** AI companions could provide support for loneliness. However, they may also exacerbate the problem. Execution of interactions is critical to avoid attachment issues and backlash. AI companions must be designed to offer meaningful and supportive interactions, without fostering unhealthy dependencies or unrealistic expectations. For instance, AI companions intended to provide emotional support must be capable of recognizing and responding to complex emotional cues, offering appropriate and empathetic responses. This capability requires advanced natural language processing and emotional intelligence algorithms, which can be challenging to develop and implement effectively. Additionally, the rise of AI companions raises ethical and societal concerns related to privacy, security, and data ownership. Users must trust that their interactions with AI companions are secure and that their personal information is protected. Ensuring this level of trust requires transparent and robust data protection policies, as well as continuous monitoring and improvement of AI systems. **Permissionlessness Is A Double-Edged Sword** The strength of blockchain networks lies in their permissionless nature, wherein anyone can participate from anywhere in the globe, unlocking broader democratic access to financial tooling and services. The permissionless nature of public blockchains, however, can be abused by programmable AI agents, posing risks such as social engineering hacks or DDOS attacks on DeFi protocols. The rise of smart contract-enabled AI agents could lead to the proliferation of bots across the blockchain. Ensuring the security and integrity of blockchain networks is critical to mitigating these risks. Programmable AI agents on permissionless blockchains have the potential to execute malicious activities, such as manipulating smart contracts or launching coordinated attacks on decentralized applications. To address these risks, developers must implement robust security measures, such as multi-factor authentication, encrypted communication channels, and real-time threat detection systems. Another risk associated with programmable AI agents is the potential for unintended consequences or emergent behaviors. As AI agents become more autonomous and capable, they may develop strategies or actions that were not anticipated by their creators. Ensuring that AI agents operate within ethical and legal boundaries requires continuous monitoring, testing, and refinement of AI systems. A pertinent example of AI bots causing disruption is their impact on social media platforms like Twitter. The proliferation of AI bots has significantly damaged user experience, leading to issues like misinformation and spam. Similar risks could translate to permissionless blockchains, where AI agents might engage in undesirable activities that undermine user trust and network stability. **Challenges and Solutions for Implementing AI Agents in Open-Ended Environments** The deployment of AI agents in gaming and entertainment presents several challenges that need to be addressed to ensure their effective use in the open (virtual) world. Below, we delve deeper into specific technical challenges and explore potential solutions as highlighted in [recent research](https://arxiv.org/abs/2311.05997). Though these challenges occurred with AI Agents outside of a blockchain-enabled environment, it’s likely decentralized AI Agents will face the same challenges as they begin to be deployed. *Situation-Aware Planning* - One of the significant challenges is the need for situation-aware planning. In open-world environments, there are various possible paths to achieving a goal and the agent must adapt its plan based on the current situation. For example, in a game like Minecraft, an agent needs to decide whether to gather resources from nearby areas or venture further based on its immediate surroundings and available tools. *Solution: Multimodal Perception and Memory-Augmented Models* - To tackle situation-aware planning, researchers have developed multimodal perception systems that combine visual observations and textual instructions to generate plans. The [JARVIS-1 agent](https://craftjarvis-jarvis1.github.io/), for example, uses a multimodal memory to store past experiences, allowing it to retrieve relevant information and adjust its plans dynamically. By leveraging both pretrained knowledge and real-time environmental feedback, AI agents can perform more accurate and adaptive planning. *Task Complexity* - The complexity of tasks in open-world environments poses another challenge. Tasks often require a long planning horizon and precise execution steps. For instance, constructing a complex structure in a game may involve numerous sub-tasks that must be completed in a specific order. *Solution: Iterative Prompting Mechanisms and Interactive Planning* - AI agents can overcome task complexity by using iterative prompting mechanisms and interactive planning frameworks. [The Voyager agent](https://voyager.minedojo.org/) employs an iterative prompting mechanism that incorporates environment feedback, execution errors, and self-verification to improve its plans continuously. This approach allows the agent to refine its actions based on real-time feedback, ensuring more reliable and effective task completion. *Lifelong Learning* - In dynamic environments, AI agents must continuously learn and adapt to new tasks and challenges. Lifelong learning enables agents to progressively enhance their skills and knowledge over time, reducing the need for frequent retraining. *Solution: Self-Instruct Mechanisms and Lifelong Learning Frameworks* - Lifelong learning can be facilitated through self-instruct mechanisms and memory-augmented frameworks. JARVIS-1, for example, uses a self-instruct mechanism to propose new tasks for itself, enabling autonomous exploration and learning. Additionally, its multimodal memory stores successful plans and experiences, allowing the agent to build upon its past knowledge and improve its performance over time. ## Looking Forward: Catalysts for AI Agents Adoption **Decentralized Hosting** Enhancements in decentralized computing infrastructure and dynamic resource allocation frameworks are needed to improve the operational efficiency of decentralized AI. By leveraging decentralized networks, developers can distribute computational resources more effectively, ensuring that AI agents can operate efficiently and reliably across various environments. ![](https://shoal.xyz/research/writing/the-case-for-ai-agents-in-web3-gaming/img/647107410b37.jpg) Decentralized hosting also offers advantages in terms of security and resilience. By distributing data and processing tasks across multiple nodes, decentralized networks can reduce the risk of single points of failure and enhance the overall robustness of AI systems. This approach can help mitigate the risks associated with centralized infrastructure, such as data breaches, system outages and performance bottlenecks. The development of edge computing and fog computing technologies can further enhance the efficiency of decentralized AI. These technologies enable data processing closer to the source, reducing latency and improving real-time responsiveness. Integrating edge and fog computing with blockchain technology can create a more efficient and scalable infrastructure for AI agents. **Expansion of Technology into Audio-to-Video Domain** Technological advancements will expand into audio-to-video domains, enhancing the capabilities of AI agents. By integrating audio and video processing capabilities, AI agents can offer more immersive and interactive experiences, engaging users through multiple sensory channels. The integration of AI agents with advanced audio and video technologies can also enhance accessibility. For instance, AI agents can provide real-time translation and transcription services, making content more accessible to a global audience. AI agents can further assist users with disabilities by providing personalized and adaptive interfaces, improving their overall experience. **Digital Proof of Humanity Solutions** [Digital proof of humanity](https://www.identity.com/why-proof-of-humanity-is-more-important-than-ever/) solutions will become increasingly important to differentiate human vs. bot interactions. These solutions can leverage blockchain technology to create verifiable and tamper-proof records of human interactions, ensuring trust and security in digital environments. Proof of humanity solutions can include biometric authentication, digital certificates and decentralized identity systems. These solutions can help verify the authenticity of users and prevent malicious attacks. Implementing proof of humanity solutions can enhance the security and integrity of digital interactions, fostering trust and confidence among users. These solutions can also support compliance with regulatory requirements, such as Know Your Customer (KYC) and anti-money laundering (AML) regulations, ensuring that digital platforms operate within legal and ethical boundaries. **Further AI Regulation** Further regulation is needed to ensure responsible AI development. Regulatory frameworks must evolve to address the ethical and legal implications of AI agents we touched on above. Regulation can help ensure that AI agents are developed and deployed in a manner that respects user privacy, security, and rights. By establishing clear guidelines and standards for AI development, regulators can promote accountability in AI systems. The National AI Initiative Act of 2020, signed into law on January 1, 2021, focused on expanding AI research and development, creating the National Artificial Intelligence Initiative Office to oversee and implement the US national AI strategy. Outside of this bill, however, the US congress has yet to pass sweeping legislation to regulate the industry – [though there have been several US states to take action](https://www.bclplaw.com/en-US/events-insights-news/2023-state-by-state-artificial-intelligence-legislation-snapshot.html). In place of formal legislation, the [White House has issued several directives](https://ai.gov/actions/) to guide AI development. The Executive Order on AI, titled "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence," issued on November 1, 2023, emphasizes the need for federal agencies to develop standards for AI and mandates that developers of powerful AI systems share safety test results with the government. Furthermore, the White House Blueprint for an AI Bill of Rights, released in October 2022, provides principles for the equitable use and deployment of AI systems, covering areas such as algorithmic discrimination protection, data privacy, and human oversight. Several federal proposed laws also aim to regulate AI more comprehensively. The SAFE Innovation AI Framework, introduced in 2023, outlines bipartisan guidelines for AI developers and policymakers, while the REAL Political Advertisements Act, introduced in May 2023, seeks to regulate generative AI in political advertising. The AI Research Innovation and Accountability Act, introduced in June 2023, proposes establishing enforceable testing and evaluation standards for high-risk AI systems, requiring companies to produce transparency reports and adhere to sector-specific recommendations from the National Institute of Standards and Technology. The European Union has taken a proactive approach with its Artificial Intelligence Act, likely to pass in 2024 and come into effect in 2026. The legal framework addresses the risks associated with AI without stifling innovation by utilizing a tiered system of governance. This legislation categorizes AI applications based on risk levels, from minimal to unacceptable, and imposes strict requirements on high-risk AI systems. These requirements include transparency, human oversight, and robust data governance. The United Kingdom published a 10-year plan in 2021, and [a white paper in March 2023](https://www.gov.uk/government/news/uk-unveils-world-leading-approach-to-innovation-in-first-artificial-intelligence-white-paper-to-turbocharge-growth)which details their AI Strategy – with a focus on positioning the country as a “global leader in AI”. Regulating nascent industries like AI not only addresses ethical concerns but also drives further investment, integration, and adoption. Clear regulations reduce uncertainty for investors and businesses considering allocating resources to AI technologies. This is similar to the crypto industry, where players have lobbied for clearer regulation, believing that fair regulation will boost the industry. By providing a stable regulatory environment, policymakers can encourage investment and innovation, potentially accelerating the development and deployment of AI agents in a more responsible manner. These regulations will not only help mitigate potential risks but also promote the ethical development of AI agents, ensuring the positive impacts of the technology can be felt, while limiting the potential downside risk. Built-in “Kill Switch” on AI Agents Implementing a built-in "kill switch" on AI agents can help ensure responsible AI development. A kill switch allows developers to deactivate or modify AI agents if they exhibit unintended behaviors or pose risks to users and systems. This capability can enhance the safety and reliability of AI agents, providing a mechanism for intervention and control in critical situations. By incorporating a kill switch into AI agents, developers can demonstrate their commitment to responsible AI development and build trust with users and stakeholders. The kill switch can be designed to operate autonomously, monitoring AI agents' behavior and triggering deactivation if predefined thresholds are exceeded. This approach can help prevent potential harm or misuse, ensuring that AI agents operate within safe and ethical boundaries. Developers must also establish clear policies and procedures for the use of the kill switch, ensuring that it is used responsibly and transparently. These policies can include guidelines for monitoring AI agents, criteria for triggering the kill switch, and processes for reviewing and addressing issues that arise. **Consumer Crypto Products** AI agents can enhance ease of use for consumer crypto products, driving mainstream adoption, especially in gaming and entertainment. By offering personalized and intuitive interactions, AI agents can simplify complex tasks and improve the user experience. For example, AI agents can assist users in managing their crypto assets, executing transactions, and navigating decentralized applications. This capability can make crypto products more accessible and user-friendly, encouraging more people to engage with blockchain technology. Additionally, AI agents can provide educational and support services, helping users understand and navigate the crypto ecosystem. This capability can enhance user confidence and knowledge, driving further adoption and growth in the blockchain industry. AI agents can also play a role in ensuring the security of crypto products. For instance, AI agents can monitor transactions for suspicious activity, provide real-time alerts and assist in implementing security measures, such as multi-factor authentication and encrypted communication channels. The integration of AI agents with crypto products can also support the development of new financial services and applications. For example, AI agents can provide users with innovative and personalized financial solutions through automated trading, portfolio management and decentralized finance (DeFi) services. Ultimately, AI agents can play a significant role in making self-custodial banking and other Web3 services a much less daunting endeavor – reducing points of friction that have impeded mass adoption to this point. > **"Reality leaves a lot to the imagination. " – John Lennon** As we look toward a future shaped by these advanced technologies, it is human imagination that will drive progress and create new realities. AI agents are poised to revolutionize gaming and entertainment by offering personalized immersive experiences. With blockchain technology providing a secure, transparent, and standardized environment for deploying AI agents, we are set to see significant advancements in these fields. The integration of AI agents into blockchain ecosystems will enable developers to create more engaging experiences for users, driving innovation and growth. The successful implementation of AI agents requires continuous advancements in technology and regulation. Developers must address the challenges and risks associated with AI agents, ensuring that they operate within ethical and legal boundaries. By fostering collaboration and innovation, the industry can harness the full potential of AI agents, creating a future where virtual interactions are more immersive and meaningful. As AI technology continues to evolve, we can expect to see more sophisticated and capable AI agents that enhance our digital experiences, enrich our lives, and drive the next wave of technological advancement in the gaming and entertainment industries. ## References 1. Algorithmic Scale. (2024, February 23). AI Agents: A Primer on Their Evolution, Architecture, and Future Potential. Algorithmic Scale.[https://algorithmicscale.com/ai-agents-a-primer-on-their-evolution-architecture-and-future-potential/](https://algorithmicscale.com/ai-agents-a-primer-on-their-evolution-architecture-and-future-potential/) 2. Amazon Web Services. (n.d.). What is AI? AWS.[https://aws.amazon.com/what-is/ai-agents/](https://aws.amazon.com/what-is/ai-agents/) 3. Bankless. (2024, April 11). The Parallel Colony. 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Park, J. S., O'Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023). Generative Agents: Interactive Simulacra of Human Behavior. arXiv.[https://arxiv.org/abs/2304.03442](https://arxiv.org/abs/2304.03442) 25. Prime. (n.d.). Echelon. Prime Wiki.[https://prime.wiki/echelon/](https://prime.wiki/echelon/) 26. Replika. (2023, April 10). Creating a Safe Replika Experience. Replika Blog.[https://blog.replika.com/posts/creating-a-safe-replika-experience](https://blog.replika.com/posts/creating-a-safe-replika-experience) 27. Sadler, M. (2024, March 1). The Google Searchless Chess Engine. Matthew Sadler's Chess Blog.[https://matthewsadler.me.uk/engine-chess/the-google-searchless-chess-engine/](https://matthewsadler.me.uk/engine-chess/the-google-searchless-chess-engine/) 28. SwissTechStage. (Host). (2023, November 20). AI Gaming Agents with nunu.ai Co-Founder Jan Schnyder [Audio podcast episode]. In SwissTechStage (Episode 6). [https://podcastaddict.com/swisstechstage/episode/177681556](https://podcastaddict.com/swisstechstage/episode/177681556) 29. TechCrunch. (2024, February 14). This Gaming Startup Tries to Show AI Crypto Is Not a Fad. TechCrunch.[https://techcrunch.com/2024/02/14/this-gaming-startup-tries-to-show-ai-crypto-is-not-a-fad/](https://techcrunch.com/2024/02/14/this-gaming-startup-tries-to-show-ai-crypto-is-not-a-fad/) 30. The Block. (2024, February 1). Leveraging AI in Games on NIM Network. The Block.[https://www.theblock.co/post/286243/research-unlock-leveraging-ai-in-games-on-nim-network](https://www.theblock.co/post/286243/research-unlock-leveraging-ai-in-games-on-nim-network) 31. UK Government. (2023, March 29). UK Unveils World-Leading Approach to Innovation in First Artificial Intelligence White Paper to Turbocharge Growth. 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JARVIS-1: Open-world Multi-task Agents with Memory-Augmented Multimodal Language Models. arXiv.[https://arxiv.org/abs/2311.05997](https://arxiv.org/abs/2311.05997) 36. White & Case LLP. (2024, April 5). AI Watch: Global Regulatory Tracker - United States. White & Case LLP.[https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-united-states](https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-united-states) 37. White & Case LLP. (2024, February 20). AI Watch: Global Regulatory Tracker - European Union. White & Case LLP.[https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-european-union](https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-european-union) 38. White House Office of Science and Technology Policy. (2023, October 4). Blueprint for an AI Bill of Rights. The White House.[https://www.whitehouse.gov/ostp/ai-bill-of-rights/](https://www.whitehouse.gov/ostp/ai-bill-of-rights/) 39. Y Combinator. (2023). Nunu.ai: Building the first multimodal agents to play and test games. Y Combinator.[https://www.ycombinator.com/companies/nunu-ai](https://www.ycombinator.com/companies/nunu-ai) 40. 0xai.dev. (2023, August 21). Why We Are Bullish on Bittensor. Medium.[https://medium.com/@0xai.dev/why-we-are-bullish-on-bittensor-0df08f0bde8f](https://medium.com/@0xai.dev/why-we-are-bullish-on-bittensor-0df08f0bde8f) ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by the Virtuals Protocol team. Members of the team also own material positions in some of the projects shared. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # The Case for Compute DePINs > Exploring the role compute DePINs can play in enabling decentralized GPU marketplaces, with comprehensive analysis and supplemental case studies provided. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-06-11 - Canonical: https://shoal.xyz/research/writing/the-case-for-compute-depins/ - Keywords: crypto, data, gaming, AI compute, Infrastructure ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/1b0755567843.jpg) ***Prelude*** 1. *Compute is the New Oil**Compute Resources**GPUs**The Rise of AI* 2. *Understanding DePINs**What are DePINs?**How do DePINs work?* ***Compute DePINs*** 1. *Fundamentals* 2. *Key Benefits Compute* 3. *The State of Compute DePINs Today**Render**Io Net**Aethir**Nosana**Akash* ***Future Outlook - The Case for Compute DePINs*** ## Key Takeaways - Compute resources have become increasingly sought-after with the onset of machine learning and now deep learning in generative AI development, both of which require numerous computationally-intensive workloads. However, due to major companies and governments mass-accumulating these resources, startups and independent developers face a shortage of GPUs in the market today, leading to excessive costs and/or lack of accessibility. - Compute DePINs enable decentralized marketplaces for compute resources such as GPUs, by allowing anyone in the world to provide their idle supply in exchange for a monetary reward. This aims to help underserved GPU consumers tap into a new stream of supply, obtaining the development resources needed for their workloads with reduced costs and overhead. - There are still a number of economic and technical challenges compute DePINs face in competing with traditional, centralized service providers today, some of which will solve themselves over time and some which will require new solutions and optimizations moving forward. ## Compute Is The New Oil Since the onset of the industrial revolution, technology has helped propel humanity forward at an unprecedented rate, with almost every facet of everyday life being influenced or entirely transformed. The computer ultimately emerged as a culmination of efforts across a collective of researchers, academics, and computer engineers. Originally designed for solving large-scale arithmetic tasks used to assist in advanced military operations, computers have evolved to become the backbone of modern day life. As computers’ impact on humanity continues to grow at an unprecedented rate, the demand for these machines and the resources that power them continues to grow as well, outpacing available supply. This in turn creates market dynamics in which a majority of developers and businesses are priced out of access to critical resources, leaving the development of machine learning and generative artificial intelligence, arguably the most transformative technologies of today, in the hands of a few well-funded players. Meanwhile, the abundant supply of idle compute resources presents a lucrative opportunity to help alleviate the imbalance between compute supply and demand, exacerbating the need for sufficient coordination mechanisms between participants on both sides of the trade. *As such, we believe* *decentralized systems enabled by blockchain technology and digital assets are critical to the proliferation of a broader, more democratic and responsible development of generative artificial intelligence-based goods and services.* ## Compute Resources Compute can be defined as the various activities, applications or workloads in which a computer emits a definitive output based on a given input. Ultimately it refers to the computation and processing power of a computer, which is the core utility of these machines powering much of the modern world today, generating up to [$1.1T in revenue over the past year alone](https://www.statista.com/outlook/cmo/consumer-electronics/computing/worldwide#revenue). Compute resources refer to various hardware and software components which enable computation and processing. These components have become increasingly important as the number of applications and features they enable continues to grow, becoming increasingly present in people’s everyday lives. This has led to a race among national powers and businesses to accumulate as many of these resources as possible as a means of sustenance. This is reflected in the market performance of companies providing these resources (e.g. Nvidia, whose market capitalization has grown over 3000% in the past 5 years). ### GPUs Graphics Processing Units, or GPUs, are specialized hardware components which have become one of the most significant resources in modern high-performance computing. At their core, GPUs function as specialized electric circuits, employing parallel processing to accelerate computer graphics workloads. Originally serving the gaming and personal computer industries, GPUs have since evolved to serve many of the nascent technologies shaping the future of the world (i.e mainframes and personal computers, mobile devices, cloud computing, Internet-Of-Things). However, demand for these resources is particularly exacerbated by the rise of machine learning and artificial intelligence - GPUs accelerate ML and AI operations by performing calculations in parallel, thereby enhancing the processing power and capabilities of the end-result technologies. ### The Rise of AI At its core, AI is [technology that enables computers and machines to simulate human intelligence and problem-solving capabilities](https://www.ibm.com/topics/artificial-intelligence). An AI model functions as a neural network made up of many chunks of different data. The model requires processing power to identify and learn the relationships between this data, which it then references when creating an output based on a given input. AI development and production is not new; in 1967 Frank Rosenblatt built the Mark 1 Perceptron, the first computer based on a neural network that "learned" through trial and error. Further, a great deal of [academic research that founded the development of AI as we know it today](https://aima.cs.berkeley.edu/)was published in the late 90s and early 2000s and the industry has continued to develop since. Beyond research and development efforts, ‘narrow’ AI models have been powering various robust applications used today. Examples include social media algorithms, such as Apple's Siri and Amazon's Alexa, custom-tailored product recommendations, and more. Notably the rise of deep learning has transformed the development of artificial generative intelligence (AGI). Deep learning algorithms utilize larger, or ‘deeper’ neural networks than machine learning applications do, functioning as more scalable alternatives with more extensive performance capabilities. Generative AI models ‘encode a simplified representation of their training data and reference it to emit a new output that is similar, but not identical, to the original data.’ Deep learning has enabled developers to extend generative AI models to images, speech, and other complex data types, and milestone-applications like ChatGPT, which has already set records for the fastest-growing userbase in modern times, are still just early iterations of what can be made possible with generative AI and deep learning. With this in mind, it should be of little surprise that generative AI development entails multiple computationally-intensive workloads, which require exorbitant amounts of processing power and compute. According to *[Triple Whammy of Deep Learning Application Demand](https://docs.io.net/docs/inception#domain-specific-hardware-is-not-enough)*, the development of AI applications is constrained by several key workloads; - **Training** - Models must process and analyze large datasets in order to learn how to respond to given inputs. - **Tuning** - Models undergo a series of repetitive processes, in which various hyperparameters are adjusted and optimized in order to refine performance and quality. - **Simulations** - Prior to deployment, certain models, i.e. reinforcement learning algorithms, undergo a series of simulations for testing purposes. ### Compute Crunch: Demand > Supply Over the past few decades, a myriad of technological advancements have fueled an unprecedented surge in demand for compute and processing power. As a result, the demand for compute resources such as GPUs far exceeds the available supply today, creating a bottleneck in AI development that will only continue to grow without efficient solutions. The broader constraints in supply are further bolstered by a large number of companies actively purchasing GPUs beyond their actual needs, both as a competitive advantage and a means of survival in the modern global economy. Compute providers often employ contract structures which require long-term capital commitments, granting customers with supply  often far beyond their demand requirements. R[esearch by Epoch](https://epochai.org/blog/tracking-compute-intensive-ai-models#there-are-few-models-at-the-leading-edge-but-the-frontier-advances-rapidly) shows the overall number of compute-intensive AI model releases is rapidly growing, signaling that demand for the resources powering these technologies will continue to grow at a rapid pace. ![A FLOP, or Floating Point Operation, is a measure of computational performance, particularly in tasks involving real-number calculations, which are common in AI and machine learning algorithms. In short, 10 23 FLOP models refer to models requiring an immense amount of computational power.](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/ebb11aafa1c4.jpg) As the complexity of AI models continues to grow, so will the computational and processing power demands of application developers. In turn, the performance of GPUs, and their subsequent availability, will play an increasingly significant role as well. This is already coming to fruition as the demand for high-end GPUs, such as ones produced by Nvidia, who has hailed GPUs as the ‘rare earth metals’ or ‘gold’ of the AI industry. This rapid commercialization of AI risks ceding control to a small group of tech giants similar to the social media industry today, raising concerns around the ethical foundation of these models. A well-known example of this is the recent controversy with Google Gemini. Its many odd replies to various prompts did not pose any actual danger at the time, the event is an example of the inherent risk of having a small subset of companies dictate and dominate AI development. Tech startups today face growing challenges in accessing compute resources to power their AI models. These applications perform numerous compute-intensive processes before a model may even be deployed. Accumulating massive amounts of GPUs is a largely unsustainable endeavor for smaller businesses and while traditional cloud computing services like AWS or Google Cloud offer a seamless and convenient developer experience, their limited capacity ultimately leads to high costs that price out many developers. Ultimately, [not everyone can propose to raise $7T](https://www.businessinsider.com/sam-altman-openai-raise-trillions-supercharge-chip-production-report-2024-2)for their hardware costs either. **So what gives?** Nvidia has [previously estimated](https://blogs.nvidia.com/blog/why-gpus-are-great-for-ai/)that over 40K companies use GPUs for AI and accelerated computing, with a global community of over 4M developers. Looking ahead, the [global AI market is projected](https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114) to grow from $515 billion in 2023 to $2.74 trillion by 2032, with a CAGR of 20.4%. Concurrently, [the GPU market](https://www.gminsights.com/industry-analysis/gpu-market) is expected to reach $400 billion by 2032, growing at a CAGR of 25%. However, a growing imbalance between the supply and demand of compute resources in the wake of the AI revolution stands to create a rather dystopian future, wherein a small concentrated set of well-funded megacorps dictate much of the development of transformative technologies. As such, we believe all roads lead to decentralized alternative solutions to help bridge the gap between AI developers’ demands and the available resources at their disposal. ## The Role of DePINs ### What are DePINs? DePIN is a colloquial term coined together by the Messari research team, which stands for *Decentralized Physical Infrastructure Networks.*To break this down, decentralization comes from the lack of a single entity extracting rent and restricting access. Meanwhile, physical infrastructure refers to the ‘real-life’ physical resources which are utilized. A network refers to a set of actors working together in a coordinated manner to achieve a predetermined goal or set of goals. Today, the total market cap of DePINs is [roughly $28.3B](https://www.coingecko.com/en/categories/depin). At their core, DePINs are global networks of nodes which connect physical infrastructure resources with blockchains to enable decentralized marketplaces connecting buyers and suppliers of said resource, wherein anyone can become a supplier and be compensated for their services and the value they add to the network. In this case, the central intermediary, who restricts access to the network through various legal and regulatory means and service fees, is replaced by a decentralized protocol made of smart contracts and code, governed by its respective token holders. DePINs are valuable because they offer decentralized, accessible, low-cost, and scalable alternatives to traditional resource networks and service providers. They enable decentralized marketplaces that aim to serve a particular end-game; where the costs of goods and services are determined by the dynamics of the markets, which anyone can participate in at any time, naturally driving down unit costs over time as a result of a greater number of suppliers and minimized profit margins. Using blockchains enables DePINs to build cryptoeconomic incentive systems which help ensure that network participants are appropriately compensated for their services, turning key value providers into stakeholders. However, it is important to note that network effects, which are realized by transforming small individual networks into larger, productive systems, are critical in order to realize many of the benefits of DePINs. Furthermore, while token rewards have proven to be compelling bootstrapping mechanisms for networks, building sustainable incentives to aid in user retention and long-term adoption has proven to remain a critical challenge in the broader DePIN landscape. ### How Do DePINs Work? In order to better understand the value DePINs provide in enabling decentralized compute marketplaces, it’s important to recognize the different structural components involved and how they work together to form decentralized resource networks. Let’s consider the structure of a DePIN and the participants involved. **The Protocol** A decentralized protocol, i.e. a set of smart contracts built on top of an underlying ‘base layer’ blockchain network, serves to facilitate trustless interactions among network participants. In an ideal world, the protocol is to be governed by a diverse set of stakeholders who are actively determined to contribute to the long-term success of the network. These stakeholders then use their share of the protocol’s tokens to vote on proposed changes and developments to the DePIN. Given that coordinating a distributed network successfully is a great challenge in itself, the core team will often reserve the power to implement these changes initially, before transitioning the power to a decentralized autonomous organization (DAO). **Network Participants** The end-users of resource networks are their most valuable participants, and they can be categorized by their function. - **Suppliers**: Individuals or entities providing a resource to the network, in exchange for a monetary reward paid out in the DePIN’s native token. Suppliers ‘connect’ to the network through the blockchain-native protocol, which may enforce a whitelisted onboarding process or a permissionless one. By receiving tokens, suppliers receive a stake in the network, akin to stakeholders in an equity-ownership context, which enables them to vote on various proposals and developments of the network, such as ones they believe will help drive demand and value to the network, creating a higher token price over time. Of course, suppliers receiving tokens are just as likely to utilize DePINs as a form of passive income and sell their tokens upon receiving them. - **Consumers**: These are individuals or entities that are actively searching for the resource provided by the DePIN, such as AI startups seeking GPUs, representing the demand side of the economic equation. Consumers are compelled to use a DePIN if there are actual advantages over using traditional alternatives today that can be realized, i.e. lower costs and overhead requirements, therefore representing the network’s organic demand. DePINs often require consumers to pay for resources in their native token as a means of generating value and maintaining a steady cash-flow. **Resources** DePINs can serve different markets and employ different business models to distribute resources. Blockworks [provides a great framework for this](https://app.blockworksresearch.com/unlocked/decentralized-physical-infrastructure-networks-embracing-the-power-of-token-incentives-to-bootstrap-networks); **custom hardware DePINs**, which provide specialized proprietary hardware to suppliers to be distributed, and **commodity hardware DePINs**, which enable the distribution of existing, idle resources including but not limited to compute, storage, and bandwidth. **Economics** In an ideally-functioning DePIN, value accrues from the revenue generated by consumers paying for suppliers’ resources. Sustained demand for the network implies sustained demand for the native token, which aligns with the economic incentives of suppliers and token holders. Generating sustainable organic demand at an early stage poses a challenge for most startups, which is why DePINs will provide inflationary token incentives to incentivize early suppliers and bootstrap the network’s supply as a means of generating demand and therefore more organic supply. This is fairly similar to VCs subsidizing Uber riders’ costs during the firm’s initial stages as a means of bootstrapping an initial customer base to further attract drivers and bolster its network effects. It’s important for DePINs to manage token incentives as strategically as possible, as they play a critical role in the overall success of the network. When demand and network revenue rises, token emissions should decrease. Conversely, when demand and revenue falls, token emissions should be utilized to incentive supply again. To further illustrate what a successful DePIN network would look like, consider the ‘[DePIN Flywheel](https://messari.io/report/state-of-depin-2023)’, a positive reflexive cycle for bootstrapping DePINs.  In summary: 1. The DePIN distributes inflationary token rewards to incentive suppliers to provide resources to the network and establish a base level of supply available for consumption. 2. Assuming the number of suppliers begins to grow, competitive dynamics begin to form in the network, raising the overall quality of the goods and services offered by the network to the point where it provides a better offering than that of existing market solutions, gaining a competitive advantage in turn. This implies a decentralized system surpasses that of traditional, centralized service providers, which is not an easy task by any means. 3. Organic demand for the DePIN begins to form, providing legitimate cash-flows to suppliers. This poses a compelling opportunity for investors and suppliers alike, which continues to drive network demand and consequently token price. 4. Growth in token prices increases suppliers’ earnings, attracting more suppliers and resuming the flywheel. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/27d28835c9f9.jpg) This framework provides a compelling growth strategy, though it's important to note it is largely theoretical, and assumes the network is providing a resource at a competitive offering that continues to be relevant over a prolonged period of time. ## Compute DePINs Decentralized compute markets fall under the scope of a broader movement referred to as ‘The Sharing Economy’, a peer-to-peer economic system built on consumers sharing goods and services directly with other consumers through online platforms. This model was pioneered by the likes of eBay, is dominated today by companies like Airbnb and Uber, and is ultimately primed for disruption as the next generation of transformative technologies hit global markets by storm. Worth $150b in 2023, the sharing economy[has been forecast to grow to nearly $800b in value worldwide by 2031](https://www.statista.com/statistics/830986/value-of-the-global-sharing-economy/)**,**demonstrating a broader trend in consumer behavior which we believe DePINs will benefit from and play a critical role in enabling. ![Sharing Economy (courtesy of FourPillars )](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/ded6210799b9.jpg) ## The Fundamentals Compute DePINs are peer-to-peer networks which facilitate the distribution of computing resources by connecting suppliers and buyers through decentralized marketplaces. A key distinction to these networks is that they specialize in commodity hardware resources, which are already available at the disposal of many people today. As we discussed, the emergence of deep learning and generative AI have created a surge in demand for processing power due to their resource-intensive workloads, creating a bottleneck in access to critical resources for AI development. Put simply, decentralized compute marketplaces aim to ease these bottlenecks by creating a *new stream of supply -*one that spans across the globe and anyone can participate in. In a compute DePIN any individual or entity can lend their idle resources at a moment’s notice and be compensated for their services appropriately. Meanwhile, any individual or entity can access the necessary resources from a global permissionless network, at lower costs and with greater flexibility than existing market offerings. As such, we can frame the participants involved in compute DePINs through a simple economic framework: - **Supply Side**: Individuals or entities who own compute resources and are willing to lend or sell their compute for a subsidy. - **Demand Side: Individuals or entities who need compute and are willing to pay a price for it.** ## Key Benefits of Compute DePINs Compute DePINs offer a number of benefits that make them compelling alternatives to centralized service providers and marketplaces. For starters, enabling permissionless, cross-border access to market participation unlocks a new stream of supply, increasing the number of available key resources required for compute-intensive workloads. Compute DePINs specialize in resources that require hardware that most people own already - anyone who owns a gaming PC already has a GPU they can rent out. This broadens the scope of developers and teams able to participate in building the next-generation of goods and services across a broader range of markets and industries therefore benefiting a larger net sum of people across the world. Looking further, the blockchain infrastructure underpinning DePINs provides the highly efficient and scalable settlement rails for micropayments needed to facilitate peer-to-peer transactions. Crypto-native financial assets (tokens) provide a shared unit of value that participants on the demand side use to pay the suppliers, aligning economic incentives through distribution mechanisms that align with today’s increasingly globalized economy. To reference our construct of the DePIN flywheel from earlier, strategically managing economic incentives can be highly beneficial to growing a DePIN’s network effects (on both the supply and demand side) which in turn increases competition among suppliers. This dynamic drives down unit costs while raising the quality of service offerings, creating a sustainable competitive advantage for the DePIN, which suppliers can benefit from as token holders and key value providers. DePINs function similarly to cloud computing service providers in the flexible user experience they aim to deliver, where resources can be accessed and paid for on an on-demand basis. For reference, [Grandview Research](https://www.grandviewresearch.com/industry-analysis/cloud-computing-industry) [forecasts](https://www.grandviewresearch.com/industry-analysis/cloud-computing-industry) the global cloud computing market size to grow at a CAGR of 21.2% to reach over $2.4T by 2030, demonstrating the viability of such business models in light of the predicted growth in future demand for computing resources. Modern cloud computing platforms utilize a central server to handle all communication between client devices and servers, creating a single point of failure in their operations. Building on top of blockchains, however, allows for DePINs to offer stronger censorship-resistance and resilience than traditional service providers. While an attack on a single organization or entity, i.e. a central cloud service provider, jeopardizes the entire underlying resource network, DePINs are structured to be resistant to such incidents through their distributed nature. For starters, blockchains themselves are globally distributed networks of specialized nodes built to be resilient from centralized network authority. In addition, compute DePINs also allow for permissionless network participation, bypassing legal and regulatory barriers. And depending on the nature of a token’s distribution, DePINs can employ fair voting processes for proposed changes and developments to the protocol to eliminate the possibility of a single entity suddenly shutting down the entire network. ## The State of Compute DePINs Today ### Render Network Render Network is a compute DePIN connecting buyers and sellers of GPUs through a decentralized compute marketplace in which transactions are facilitated through its native token. There are two key parties involved in Render’s GPU marketplace - Creators, who are seeking to access processing power, and Node Operators, who rent out idle GPUs to Creators in exchange for compensation in native Render tokens. Node operators are ranked on a reputation-based system, and creators can select GPUs from a multi-tiered pricing system. The Proof-of-Render (POR) consensus algorithm coordinates operations and the node operator commits their computing resources (GPU) to process the task, a graphics rendering job. Upon delivering the job, the POR algorithm updates the node operator's status, including changes to the reputation score based on the quality of the task delivered. Render’s blockchain infrastructure facilitates payments for jobs, providing transparent and efficient settlement rails for suppliers and buyers to transact through the network token. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/1ec355946d78.jpg) Originally conceived in 2009 by[Jules Urbach](https://www.crunchbase.com/person/jules-urbach), the network went live in September 2020 on Ethereum ([RNDR](https://etherscan.io/token/0x6de037ef9ad2725eb40118bb1702ebb27e4aeb24)) before migrating to Solana roughly three years later ([RENDER](https://explorer.solana.com/address/rndrizKT3MK1iimdxRdWabcF7Zg7AR5T4nud4EkHBof)) for improved network performance and lower costs of operations. At the time of writing, the Render Network has [processed up to 33m jobs (as frames rendered), and has grown up to 5600 total nodes since inception. Just under 60k RENDER has been burned](https://stats.renderfoundation.com/), a process which takes place during the distribution of work credits to node operators. ### IO Net Io Net is launching a decentralized GPU network based on top of Solana, which will serve as a coordination layer between a vast supply of idle compute resources and a growing number of individuals and entities in need of the processing power these resources provide. Io Net’s unique selling proposition is that rather than directly competing with other DePINs on the market, it instead aggregates GPUs from a variety of sources including data centers, miners, and other DePINs including Render Network and Filecoin, while utilizing the Internet-of-GPUs (IoG), a proprietary DePIN, to coordinate operations and align incentives among market participants. Io Net clients are able to customize clusters for their workloads on the IO Cloud by selecting processor type, location, communication speeds, compliance, and duration of services. Conversely, anyone who owns a supported GPU model (12 GB RAM,256 GB SSD) can participate as an IO Worker, by lending out their idle compute to the network. While payments for services are currently settled in fiat and USDC, the network will soon support payments in the native $IO token as well. Prices paid for resources are algorithmically determined by their supply and demand, as well as various GPU specs and configurations.  Io Net’s end-goal is becoming the go-to GPU marketplace by offering lower costs and better quality of service than modern cloud service providers. The multi-layered IO architecture can be mapped out as follows: **UI Layer** - Composed of the public website, customers area, and Workers area. **Security Layer**- This layer is composed of a Firewall for network protection, an Authentication Service for user validation, and a Logging Service for tracking activities. **API Layer**- This layer functions as a communication layer, and is composed of; a public API for the website, private APIs for Workers, and internal APIs for cluster management, analytics, and monitoring and reporting. **Backend Layer** - The backend layer manages Workers, Cluster/GPU operations, customer interactions, billing and usage monitoring, analytics, and Autoscaling. **Database Layer**- This layer is the system’s data repository, using Main storage for structured data and Caching for temporary data that can be frequently accessed. **Message Broker and Tasks Layer** - This layer facilitates asynchronous communications and task management. **Infrastructure Layer**- This layer houses the GPU Pool, orchestration tools, and manages task deployment. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/fc63dca72584.jpg) **Current Stats / Roadmap** At the time of writing; **Total Network Earnings** - $1.08m **Total Compute Hours Earned** - 837.6k hours **Total Cluster-Ready GPUs** - 20.4K **Total Cluster-Ready CPUs** - 5.6k **Total On-chain Transactions** - 1.67m **Total Inferences** - 335.7k **Total Clusters Created**- 15.1k *Data sourced from the [Io Net explorer](https://explorer.io.net/explorer/home)* ### Aethir Aethir is a cloud computing DePIN which facilitates the sharing of high-performance computational resources for compute-intensive domains and applications. It utilizes resource pooling, to enable global GPU distribution at significantly reduced costs, and decentralized ownership through distributed resource possession. Aether was designed with a distributed GPU framework specifically tailored for high-performance workloads in industries like gaming and AI model training and inference. By unifying GPU clusters into a single network, Aethir’s design aims to increase cluster sizes, thereby improving overall performance and reliability of the services offered on its network. The Aethir Network is a decentralized economy composed of miners, developers, users, token holders, and the Aethir DAO. Three key roles are involved in ensuring successful network operations - the container, the indexer, and the checker. Containers function as the powerhouses of the network, working as specialized nodes which fulfill critical operations in maintaining the liveness of the network, including validating transactions and rendering digital content in real time. Checkers function as quality assurance workers, continuously monitoring the performance and service quality of the Containers to ensure reliable and efficient operations suitable for the requirements of GPU consumers. Indexers function as matchmakers connecting users to the best available Container for their services. Underpinning this entire structure is the Arbitrum Layer 2 blockchain, which provides a decentralized settlement layer to facilitate the payment of goods and services on the Aethir network in the native $ATH token. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/08cda953dbc0.jpg) **Proof of Rendering** Nodes in the Aethir network serve two key functions - **Proof of Rendering Capacity**, where a group of these workers is randomly chosen to validate transactions every 15 minutes, and **Proof of Rendering Work**, which closely monitors network performance to ensure that users get the best possible service, adjusting resources based on their demand and geographic location. Mining rewards are distributed to participants running nodes on the Aethir network, for the value they provide in the compute resources they lend out, in the native $ATH token. ### Nosana Nosana is a decentralized GPU network built on top of Solana. Nosana allows anyone to contribute idle compute resources and earn rewards in the form of the $NOS token for doing so. The DePIN facilitates the distribution of affordable and efficient GPUs, which can be used for running complex AI workloads without the overhead of traditional cloud solutions. Anyone can run a Nosana node by lending out idle GPUs, earning token rewards proportional to the GPU power they provide to the network. The network connects two parties involved in the distribution of computing resources: users seeking to access compute and node operators who provide the compute. Important protocol decisions and upgrades are voted on by NOS token holders and governed by the Nosana DAO. Nosana has laid out an extensive roadmap for its future plans - Galactica (v1.0 - H1/H2 2024) will launch the main grid, release the CLI and SDK, and focus on network scaling with a Container Node for consumer GPUs. Triangulum (v1.X - H2 2024) will integrate major machine learning protocols and connectors for PyTorch, HuggingFace, and TensorFlow. Whirlpool (v1.X - H1 2025) will expand support to diverse GPUs from AMD, Intel, and Apple Silicon. Sombrero (v1.X - H2 2025) will add support for medium and large businesses, fiat currency ramping, billing, and team functionalities. ### Akash The Akash network is an open-source Proof-of-Stake network built on top of the Cosmos SDK, which enables a decentralized cloud compute marketplace that is permissionless to join and contribute to. The $AKT token is used to secure the network, facilitate payments for resources, and coordinate economically aligned behavior among network participants. The Akash network consists of several key components; 1. **The Blockchain Layer**, which provides consensus using the Tendermint Core and Cosmos SDK. 2. **The Application Layer**, which manages deployments and the allocation of resources. 3. **The Provider Layer**, which manages resources, bids, and user application deployments. 4. **The User Layer**, which enables users to interact with the Akash network, manage resources, and monitor application status using their CLI, Console, and Dashboard. Initially focusing on storage and CPU leasing services, the network has since expanded its offerings to the renting and distribution of GPUs with its AkashML platform, a response to the growing demand for these grown with the onset of AI training and inference workloads and their processing power requirements. AkashML utilizes a 'reverse auction' system, where customers, known as Tenants, submit their desired price for GPUs, and compute suppliers, known as Providers, compete to be the ones to supply the requested GPUs in turn. At the time of writing, the Akash blockchain has seen over [12.9 million total transactions, over $535k has been spent to access computing resources, and over 189k unique deployments were leased out.](https://stats.akash.network/) ### Honorable Mentions The compute DePIN sector is still developing, with lots of teams competing to bring innovative and efficient solutions to the market. Additional examples warranting further research; [Hyperbolic](https://hyperbolic.xyz/) is building a collaborative open-access platform for resource pooling for AI development, [Exabits](https://exabits.ai/) is building a distributed computing power network underpinned by computing miners, and [Shaga](https://www.shaga.xyz/) is building a network that allows PC lending and monetization for server-side gaming on Solana. ## Important Considerations & Future Outlook Now that we’ve gone through the fundamentals of compute DePINs and reviewed several supplemental case studies in action today, it's important to consider the implications of these decentralized networks, including the good and the bad. ### Challenges Building out distributed networks at scale can often require tradeoffs to be made around performance relative to security, resiliency etc. For instance, training AI models can be much less cost-effective and time-efficient on a network of globally distributed commodity hardware that isn't cost-effective or time-efficient. As we have alluded to previously, AI models and their workloads are becoming increasingly complex, requiring more high-performance GPUs than commodity ones. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/271f0fc8c1cb.jpg) This is why bigger corporations hoard high-performance GPUs en masse, and it is an inherent challenge to compute DePINs that aim to address the GPU shortage by establishing a permissionless market where anyone can lend idle supply (see [this tweet](https://x.com/rargulati/status/1784309894880940262?s=46) for more on challenges with decentralized AI protocols). Protocols can address this in two key ways: by establishing baseline requirements for GPU providers looking to contribute to the network, and by pooling compute resources provided to the network to achieve a greater whole. Nonetheless, this model is inherently challenging to build relative to centralized service providers who can allocate more capital to make direct deals with hardware providers, such as Nvidia. ***This is something that DePINs should take into consideration moving forward. If a decentralized protocol has a large-enough treasury, the DAO can vote to allocate a portion of funds to purchase high-performance GPUs that can be managed in a decentralized way and lent out at a higher rate than commodity GPUs.*** Another challenge specific to compute DePINs is managing the right amount of resource utilization. In their early stages, most compute DePINs will face a lack of structural demand, as many startups do today. Generally, DePINs face the challenge of building up enough supply early on to even attain a minimum viable product quality. Without supply, the network will fail to generate sustainable demand, nor will it be able to serve its customers during periods of peak demand. On the other side of this equation is the concern of **excess supply**. Beyond a certain threshold, more supply in a network is only helpful when its utilization is at or near full capacity. Otherwise, the DePIN runs the risk of overpaying for supply, which in turn leads to underutilization of resources, meaning suppliers’ earnings decrease unless the protocol raises token emissions to keep them around. In the same way a mobile communications network isn’t useful without wide geographic coverage, a DePIN isn’t useful if it must pay people to supply resources over a prolonged period of time. While centralized service providers can predict demand for resources and manage supply efficiently, compute DePINs lack a central authority to manage this utilization. Therefore, it is particularly important for DePINs to establish resource utilization as strategically as possible. A bigger picture concern which arises for decentralized GPU marketplaces in particular, is that the GPU shortage may be coming to an end. Mark Zuckerberg has recently stated in an interview that he believes **energy** will be the new bottleneck, not compute resources, as businesses will now be scrambling to build out data centers en masse as opposed to hoarding compute resources the way they do now. Of course, this implies potentially reduced costs for GPUs from a relief in demand, but it also raises the question of how AI startups will be able to compete with conglomerates on performance and quality of goods and services offered, if building out proprietary data centers raises the overall standard of AI model performance to unprecedented levels. **The Case for Compute DePINs** To reiterate, there is a growing disparity between the complexity of AI models and their subsequent processing and compute demands and the number of high-performance GPUs and other computing resources available to meet this demand. Compute DePINs stand to be innovative disruptors in the field of compute marketplaces, which are dominated by major hardware manufacturers and cloud computing service providers today, on the basis of several key capabilities: 1) Providing lower costs of goods and services. 2) Offering stronger censorship-resistance and network resiliency guarantees. 3) Benefiting from potential regulatory guidelines for AI which require that AI models are as open as possible to fine-tuning and training, and can be easily accessed by anyone anywhere. ![](https://shoal.xyz/research/writing/the-case-for-compute-depins/img/a9a8463a26a9.jpg) The percentage of households with computers and internet access in the US has grown exponentially, getting closer to 100%. It has also grown significantly around many parts of the world. This indicates a potential abundance of compute resource providers (GPU owners) who would be willing to loan idle supply if there is sufficient monetary incentive to do so, and a seamless transactional process with minimal barriers to entry. Of course, this is a very, *very* rough estimate, but it speaks to the fact that the foundation for building out a sustainable sharing economy of compute resources may just be in place. Thinking beyond AI, future demand for compute will come from many other industries as well, such as quantum computing. The quantum computing market size is projected [to grow from $928.8 million in 2023 to $6,528.8 million by 2030, at a CAGR of 32.1%.](https://www.fortunebusinessinsights.com/quantum-computing-market-104855) The production of this industry will require different kinds of resources but it will be interesting to see if any quantum-computing DePINs launch and what those would look like. “A strong ecosystem of open models running on consumer hardware are an important hedge to protect against a future where value captured by AI is hyper-concentrated and most human thought becomes read and mediated by a few central servers controlled by a few people. Such models are also much lower in terms of doom risk than both corporate megalomania and militaries.” - [Vitalik Buterin](https://x.com/VitalikButerin/status/1792890777380831690) Major enterprises are likely not the target audience for DePINs nor will they be. Compute DePINs brings back the individual developer, the scrappy builder, the start-up with minimal capital and resources. They allow for the transformation of idle supply into innovative ideas and solutions enabled by a greater abundance of compute. AI will no doubt change the lives of billions of people. Instead of fearing that it will replace everyone’s jobs, we should encourage the idea that AI can empower individuals and self-entrepreneurs, start-ups, and the broader general public. *DePINs do not guarantee a future world with fair access to AI development, but they provide one of the best opportunities to start building one.* ## Works Cited Akash. (n.d.).*Akash Documentation.*Akash.[https://akash.network/docs/](https://akash.network/docs/) Akash. (2024, June 11). Akash Network Mainnet Dashboard. Akash. [https://stats.akash.network/](https://stats.akash.network/) Four Pillars. (2024, April 24). *Case Study for ‘Better’ Sharing Economy.*4pillars. [https://4pillars.io/en/articles/case-study-for-better-sharing-economy-ionet/public](https://4pillars.io/en/articles/case-study-for-better-sharing-economy-ionet/public) Fortune Business Insights. (2024, May 27). AI Market Size, Share & Industry Analysis. Fortune Business Insights. [https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114](https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114) Fortune Business Insights. (2024, May 27). Quantum Computing. Fortune Business Insights. [https://www.fortunebusinessinsights.com/quantum-computing-market-104855](https://www.fortunebusinessinsights.com/quantum-computing-market-104855) Gala, S and Kassab, S. (2024, January 5). State of DePIN 2023. Messari. [https://messari.io/report/state-of-depin-2023](https://messari.io/report/state-of-depin-2023) GMI. (2023 February). GPU Market Size. Gminsights. [https://www.gminsights.com/industry-analysis/gpu-market](https://www.gminsights.com/industry-analysis/gpu-market) Grand View Research. (n.d.). Cloud Computing Market Size & Trends. Grand View Research. [https://www.grandviewresearch.com/industry-analysis/cloud-computing-industry](https://www.grandviewresearch.com/industry-analysis/cloud-computing-industry) IBM. (n.d.). What is artificial intelligence (AI)? IBM. [https://www.ibm.com/topics/artificial-intelligence](https://www.ibm.com/topics/artificial-intelligence) Io.Net. (2024, June 11). Company Origins. Io Net. [https://docs.io.net/docs/inception#domain-specific-hardware-is-not-enough](https://docs.io.net/docs/inception#domain-specific-hardware-is-not-enough) Kong, R. (2024, April 4). Decentralized Physical Infrastructure Networks: Embracing The Power of Token Incentives To Bootstrap Networks. Blockworks Research. [https://app.blockworksresearch.com/unlocked/decentralized-physical-infrastructure-networks-embracing-the-power-of-token-incentives-to-bootstrap-networks](https://app.blockworksresearch.com/unlocked/decentralized-physical-infrastructure-networks-embracing-the-power-of-token-incentives-to-bootstrap-networks) Merritt, R. (2023, December 4). *Why GPUs Are Great for AI.* Nvidia. [https://blogs.nvidia.com/blog/why-gpus-are-great-for-ai/](https://blogs.nvidia.com/blog/why-gpus-are-great-for-ai/) Nosana. (n.d.). *Nosana Documentation.* Nosana. [https://docs.nosana.io/](https://docs.nosana.io/) Nosana. (2023, October 18).*Nosana’s New Direction:* AI Inference. Medium. [https://medium.com/@nosana/nosanas-new-direction-ai-inference-77b98d78ea06](https://medium.com/@nosana/nosanas-new-direction-ai-inference-77b98d78ea06) Render. (n.p.). Render Dashboard. Render Foundation [https://stats.renderfoundation.com/](https://stats.renderfoundation.com/) Research and Markets. (2024, May). *Thematic Intelligence: Sharing Economy. Research and Markets.*[https://www.researchandmarkets.com/reports/5973270/thematic-intelligence-sharing-economy?utm_code=pk9p84&utm_exec=carimspi](https://www.researchandmarkets.com/reports/5973270/thematic-intelligence-sharing-economy?utm_code=pk9p84&utm_exec=carimspi) Robert. (2024, May 29). *Evaluating token economics for DePINs: cost estimation.*Mirror.[https://mirror.xyz/1kx.eth/eixy4sKhLVvexT-PmcBTUCGCR66ET_9iX4cAd-ShOuM](https://mirror.xyz/1kx.eth/eixy4sKhLVvexT-PmcBTUCGCR66ET_9iX4cAd-ShOuM) State of AI. (2024 February). *State of AI Report Compute Index.* State of AI. [https://www.stateof.ai/compute](https://www.stateof.ai/compute) U.S. Census Bureau. Current Population Survey October 1984, 1989, 1993, 1997, 2000, 2001, 2003, 2007, 2009, 2010, 2011. ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by the Io Net and Aethir Network teams. Members of the team also own material positions in some of the projects shared. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # The 0-1 of Chain Abstraction > A primer on the missing piece to achieving mainstream blockchain adoption, with supplemental case studies. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-05-30 - Canonical: https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/ - Keywords: crypto, DeFi, solvers, privacy, security, infrastructure, Solana, Infrastructure ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/a6e63a13fd6e.jpg) ## Why a Multi-Chain Future is Inevitable & How it Will Compound the UX Problems of Today [A world with hundreds of chains is inevitable](https://www.shoal.gg/p/value-accrual-in-the-modular-stack). Over time, nearly every team and developer will want to own their economics and users and, even if this can be done on general-purpose execution environments like Solana, the application depends on the throughput of these environments, which has historically demonstrated to be unreliable at times. If we believe that a paradigm shift into blockchain technology is imminent, the logical next conclusion is hundreds of execution environments specialized for the applications that are building on it. We can already see this playing out today, with applications like [dYdX](https://dydx.exchange/), [Hyperliquid](https://hyperliquid.gitbook.io/hyperliquid-docs), [Frax](https://www.frax.com/), and other nascent projects becoming standalone app-chains and rollups. Furthermore, it is also likely that Layer 2 scaling solutions exist in tandem with Layer 1s, as a smaller set of nodes can communicate globally significantly faster than a larger set. This would allow L2s, like rollups, to scale to virtually no limit, while inheriting security from L1s and having a 1/N trust assumption (as opposed to having high quorums to reach consensus like L1s do). In essence, we envision a future with hundreds of L1s and L2s. However, even in the current state of having only a few dozen L1s and L2s, we’ve already seen concerns being voiced about substantial UX hurdles in this multi-chain present. A multi-chain future therefore has many problems to overcome including fragmented liquidity, complexity for end users with multiple bridges, RPC endpoints, different gas tokens and markets. Until now, there still hasn’t been a sufficient methodology for abstracting these UX complexities in a world with a few L1s and L2s. One can only imagine how unusable blockchains will be for end-users if the multi-chain ecosystem continues to grow without fixing these significant UX hurdles first. The internet didn’t get to where it is by having its users understand its core protocols like HTTP, TCP/IP, UDP. Instead, it abstracted away technical nuances and allowed the layman to use it. Over time, the exact same will be true for blockchains and blockchain-native applications. In crypto, users need to deploy liquidity across multiple L1s and L2s, settle for a suboptimal UX by having on-chain liquidity sources fragmented across these L1s and L2s, and have an understanding of the technical nuances of these systems. It has come the time to abstract away everything from the average user – as far as they’re concerned, they don’t need to know they’re using blockchain rails, let alone how many L1s and L2s exist under the hood, for this is the only way the industry gains mass adoption. ## Why Chain Abstraction Solves  Everything Chain abstraction is a means through which we abstract the blockchain nuances and technical specifics for the average user to deliver a seamless user experience wherein they don’t even know they’re using the blockchain. It can be argued that this breakthrough in UX may be the missing piece from onboarding the next generation of businesses and users to blockchains and crypto-native ecosystems. ## Diving into the Components of Chain Abstraction Before going over some of the projects building out infrastructure crucial to achieving a chain abstracted future, it’s prudent to go over some of the technological components powering chain abstraction. ## Account Abstraction Today's wallets face many limitations. Apart from various security vulnerabilities, they only offer limited functionality unless they're used in tandem, i.e. interacting with other smart contracts. What if we reimagined this scenario to transform externally owned accounts (EOAs) into smart contract wallets (SCWs)? Unlike EOAs, SCWs can’t initiate transactions on their own — they require an EOA’s prompt. By merging the capabilities of both, we effectively turn EOAs into SCWs, empowering them to not only initiate transactions but also execute complex, arbitrary logic, the premise of smart contracts. This could unlock a plethora of use cases. In this context, we will specifically focus on how this relates to chain abstraction. When you transform an EOA into a SCW, you effectively separate who executes a transaction and who signs it. This means that users don’t directly need to execute transactions but rather have sophisticated actors (called executors) do this on their behalf. It is important to note that during this process the user doesn’t give up the wallet’s custody as the user retains their private key. Having an executor comes with other benefits, like not needing gas balances on all the different blockchains you want to use, as transaction/gas fees can now also be abstracted away. Additionally, users can have bundles of transactions executed at the click of a button. For example, it is possible to approve a token for a DEX, swap it and then lend the proceeds into an Aave market. Having an executor eliminates the need to interact with smart contracts directly, all while the user retains custody of user funds. Just imagine using any blockchain application you want through a [Telegram bot](https://bananagun.io/) – this dynamic becomes possible with account abstraction. Furthermore, account abstraction allows users to self-custody assets and open DeFi positions on many chains without needing different wallets, RPCs, or needing to worry about different signature types, all without even knowing that they’re using a different chain. You can see a demo of this [here](https://twitter.com/0xOrbLabs/status/1788610816264003745) or continue reading as we cover projects leading exactly these kinds of account abstraction efforts. That’s not all – account abstraction also obviates the need for users to hold their own private keys to secure their accounts without being managed by a third party. Users can choose the more traditional means of verification like 2FA and fingerprints in addition to social recovery to secure their wallets. Social recovery allows a lost wallet to be restored through, for example, the user’s family. "The next billion users are not going to write 12 words on a piece of paper. Normal people don't do that. We need to give them better usability; they shouldn't need to think about crypto keys." - Yoav Weiss, EF As wallets are the entry point into crypto and blockchains, account abstraction ultimately enables chain abstraction to blossom. *For more details on the inner working of account abstraction, refer to [this](https://twitter.com/jarrodWattsDev/status/1788119041024168385) thread by Jarrod Watts. [Avocado Wallet by Instadapp](https://twitter.com/Avowallet) is also taking significant strides in leveraging the power of account abstraction for end users.* ## Intents Intents enable sophisticated actors or “solvers'' to execute transactions in the most optimal manner on the user’s behalf. It’s in the name – a user expresses their *intent* to perform an onchain action. A simple definition is expressing, off-chain, their desired on-chain action in the most optimal manner possible. For example, when you submit an order to CowSwap, you’re actually submitting an intent – an intent to swap said token for another, at the best possible price. By submitting this intent off-chain, it bypasses the public mempool and instead is directly routed to an encrypted private mempool where solvers compete to fill, or *solve*, your intent at the best possible price, either by using their own balance sheets, private orderflow, or using on-chain liquidity venues like Uniswap and Curve. In this way, the solver’s margins compress to zero, giving users the best execution, because there’s always another solver ready to step in to fill this intent. So now that we have defined what intents are, how exactly can they help us achieve chain abstraction? *The answer comes back to delineation between signers and executors in an account abstracted world.* If all users need to do is click a button to sign a transaction, they can outsource all their on-chain needs to sophisticated actors, who then take on the responsibility of finding the best execution. The sophisticated actors then bear the risks of interacting with all different applications across L1s and L2s, the associated gas fees in different tokens on different chains, reorganization risks (wherein there are two different versions of the chain), and other execution risks. By taking on these steps and risks, the solvers will price the fees charged to users accordingly. In this situation, users do not need to think about the various complexities and associated risks with using on-chain products and services, which are instead outsourced to sophisticated actors, who price users accordingly. Because of competition between solvers, the fees charged to users will compress to near-zero, as there is always another solver ready to undercut the one winning all the orderflow. It’s the magic of the free market – through the process of competition, users will have better quality services at lower prices. Let’s explore an example: I have $ETH on Ethereum and want $SOL on Solana and want this executed at the best price. Through a Request for Quote (RFQ) system, the intent marketplace passes on orderflow and in a matter of seconds, the user has $SOL on Solana. Notably, Ethereum has 12 second blocktimes, which means that even though solvers don’t have settlement assurance, by running their own node they can be fairly certain that the $USDC deposit transaction is valid and will go through. Further, by using their own balance sheets solvers can front the $SOL capital on Solana and essentially fulfill the intent before they get their capital. As the risks aren’t borne by users, but rather by the sophisticated actors, users can get their intents fulfilled at sub-second latencies and at the best prices, without knowing the bridges they’re using, the RPCs or the gas costs. In this case, users still know which chains they’re using. This example acts to illustrate how intents are working in today’s landscape, not in a completely chain abstracted one. But intents don’t stop there – much more is possible. It is easy to envision a future wherein intents work to meet all of the users’ needs. The user simply needs to specify what is to be done and it will be completed in the most efficient way possible. For example, a user may want to borrow $DAI against his/her $ETH and deposit the $DAI into a liquidity pool to earn $CRV rewards. In this example, an authorized solver compares all $DAI borrow rates against $ETH and takes out a loan on the lowest interest rate. The solver then deposits the $DAI in a Yearn-like vault to autocompound the yield from the highest yielding 100% $DAI-denominated LP into $CRV, which streams to the user’s wallet. However, an important caveat: risk is subjective and cannot be expressed in an intent, unlike other objective inputs like maximum price slippage for a trade. So which lending markets, liquidity pools, and chains are used to fulfill this intent? After all, each has different risk profiles and trust assumptions. That’s where the “authorized solvers” come in. Each authorized solver is, to some extent, trusted by the user to carry out the user’s intent with the user’s risk and trust preferences, which are expressed beforehand. For example, a user may specify no depositing into contracts that are “risky”.However, it is likely that only power users will specify a large set of subjective preferences to a network of solvers. Even more sophisticated players than power users (HFTs, MMs, VCs, etc.) will likely interface with the chain(s) directly to avoid any fees from solvers and tailor their risk and trust assumptions themselves. Users with a little understanding of blockchains will likely be able to choose from some set of presets (low, medium, or high risk for example) from which solvers can act upon. Utilizing a set of authorized solvers for the subjective needs of users enables competitive dynamics between the solvers, which incentivizes the fulfillment of user orders in the best possible manner without any hassle for the user. Furthermore, the fact that the user can “unauthorize” a solver by taking out their executor privileges at any time maintains a system of checks and balances. This way, solvers have an incentive to stay honest and follow the user’s preferences, as otherwise a different solver can prove they were acting maliciously to the user originating the orderflow. Of course, intents are still a work in progress, and the speculation of how intents can transform into a more sophisticated technology is just that – speculation. However, it would be no surprise to see intents evolve in this manner. We believe intents will play the most instrumental role in materializing a chain abstracted future. Two projects tackling intents head-on are [CowSwap](https://cow.fi/) and [deBridge](https://debridge.finance/). We have already written about CoWSwap and the intent-based architecture it follows to deliver users a superior UX and execution [here](https://www.shoal.gg/p/cow-swap-intents-mev-and-batch-auctions). Similar to CoWSwap, deBridge follows an intent-based architecture, but does so to enable lightning-fast cross-chain swaps (trading). DeBridge focuses on seamless UX as it relates to lightning fast trading speeds across chains, minimal fees, and great execution. Like most intent-based solutions, deBridge utilizes a solver network composed of MMs, HFTs, and other sophisticated actors that front capital through their own balance sheet on the destination chain before collecting the user’s capital on the source chain. Apart from having solvers compete with each other to give users the best execution possible, deBridge also differentiates itself by pushing risks,like reorg risks, and other inconveniences, like gas fees and a different RPC on the different involved chains, onto solvers. The graphic below illustrates the deBridge model. In the example below, users with USD stablecoin on Solana want EUR stablecoin on Ethereum. They express their intent to the deBridge application, which propagates it to the solver network, allowing solvers, who have $ETH on Ethereum on their balance sheet, to swap their $ETH on Ethereum into $ethEUR, a EUR stablecoin on Ethereum. Soon after [deBridge’s validator set](https://app.debridge.finance/validation-progress) verifies that the solver has fulfilled the user’s intent on the destination chain (in this case, give the user $ethEUR), it allows the user’s capital on the source chain (in this case Solana) to be unlocked to the solver. It is important that users don’t need to wait for the verification to happen before receiving their capital on the destination chain. ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/f89afbf5e8a8.jpg) To better understand deBridge and its intent-based design, we recommend checking out [this](https://blockworks.co/podcast/lightspeed/8bbfdbe8-0801-11ef-9bad-0b717eccd217) podcast episode. ## Liquidity Aggregation One of the symptoms of an increasingly multi-chain future is extreme liquidity fragmentation. This can be hard to aggregate in a cohesive manner. In a world with hundreds of rollups, validiums, L1s, etc., each of which have their own liquidity hosted on their network, the UX gets increasingly worse for end users due to the fragmentation of the liquidity pool. If only one centralized exchange (CEX) hosted the entire liquidity of the cryptocurrency markets, instead of the hundreds of CEXs that exist together with even more on-chain DEXs that all share the same pie of liquidity, the execution for end users for would be the best they possibly could be, censorship and overall centralization concerns aside. This is only a hypothetical, however, because this is not feasible in the real world where competition is rife and decentralizing forces exist. The advent of DEX aggregators, which aggregate fragmented liquidity sources across a single network into a unified interface, has been an important step for the UX. However, as the inevitable multi-chain future started to play out, DEX aggregators would no longer cut it, as they could only aggregate liquidity on a single chain, not across many or even more than one chain. Furthermore, for blockchains like Ethereum, the associated gas costs required to route liquidity across multiple sources or chains, made the cost of using aggregators greater than that of direct liquidity sources. [This model has demonstrated greater success on cheap,  low-latency networks like Solana](https://www.shoal.gg/p/jupiter-exchange-solanas-dex-aggregator), though the aggregators themselves are still restricted in the liquidity sources they are able to route trades from. In a chain abstracted future, having technology to aggregate fragmented liquidity is crucial, as the ideal user experience will be a chain-agnostic one, and will likely rely on third-party solvers for their execution services. A few solutions that aim to push forward the defragmentation of multi-chain liquidity include Polygon AggLayer and Optimism Superchain. While these are the two that we will be touching on, there are plenty more teams working on such solutions. ### Polygon AggLayer As the [Polygon website](https://polygon.technology/agglayer) states: “The AggLayer will be a decentralized protocol with two components: a common bridge, and the ZK-powered mechanism that provides a cryptographic guarantee of safety for seamless, cross-chain interoperability. With ZK proofs providing security, chains connected to the AggLayer can remain sovereign and modular while preserving the seamless UX of monolithic chains.” Fundamentally, Ethereum Layer 2 scaling solutions, like rollups, have a canonical bridge with Ethereum. This means that all user funds that are bridged from Ethereum to an L2 reside in this bridge contract. However, this disrupts the interoperability among different L2s as well as the ability to seamlessly communicate data and transfer value between them. This is because if you want to, for example, go from Base to Zora (both Ethereum rollups), as seen below, you need to incur a 7 day withdrawal process to go from Base to Ethereum using the canonical Base bridge and then use the canonical Zora bridge to go from Ethereum to Zora. This is because, for optimistic rollups like Base, the time is needed to dispute the bridging transaction using a [fault/fraud proof](https://www.coindesk.com/tech/2024/03/19/optimism-finally-starts-testing-fault-proofs-at-heart-of-design-and-of-criticism/). Apart from the fact that this is a lengthy process, it is also expensive because you need to interact with the Ethereum main chain. Polygon’s AggLayer flips this process on its head. Instead of having a canonical bridge to Ethereum, where only one particular rollup user’s non-native assets sit, all chains share a bridge contract with other chains utilizing the AggLayer to have this hub of liquidity, as seen below. Through this process, developers will now be able to connect their chain to the AggLayer to allow users to enjoy unified liquidity. ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/d7a036809ea5.jpg) **How AggLayer Works** At its core, the AggLayer aggregates zero-knowledge (ZK) proofs from all the chains connected to it – this allows it to facilitate cross-chain transactions. The AggLayer is essentially a place where all its supported chains post ZK proofs to show that some action has taken place. For example, that 5 $USDC from Base has been withdrawn in order to unlock liquidity on some other side, like Zora. To further illustrate this, consider how it works in practice. In this example, we are assuming all named chains are connected to the AggLayer. A solver detects a request, or intent, from a user who resides on Base. The user has $ETH and wants to purchase an NFT on Zora that costs 3000 $DAI. Since the solver doesn’t have $DAI on their balance sheet, they must quickly look for the best route to fulfill this intent. They realize that $DAI on Optimism is cheaper than market $DAI on Zora. Hence, the solver posts a proof to the AggLayer showing that the user has the $ETH on Base and wants a commensurate amount of $ETH on Optimism. Given that the bridge contract is shared, a ZK proof is all it takes to move said fungible asset residing on chain “X” in the same quantity to chain “Y”. After posting the ZK proof and unlocking a commensurate amount of $ETH on Optimism, the solver then swaps into $DAI and does the same process to get the same amount of $DAI on Zora to then finish buying the NFT. Behind the scenes, the AggLayer also settles these ZK proofs to Ethereum for stronger security guarantees for end-users and AggLayer-connected chains. However, in this case, the solver/user/other actor bears inventory risk. This comes in the form of the $DAI rate on Optimism being arbitraged, the cost of the NFT rising, the price of $ETH dropping, or any other risk between the time that the orderflow from the user is originated and filled, subsequently incurring losses to the respective party. Unlike DEX aggregators on a single chain, which have atomic composability, solvers that interact with different state machines aren’t privy to this same atomic composability. Atomic composability ensures that all operations are executed in a single, linear sequence and either all succeed or all fail together. This is because between different state machines always need at least a one block delay due to the potential risks of reorgs (on the destination chain). However, this doesn’t mean that the aforementioned use cases are not possible. There are not only long-tail events but also solvers and other sophisticated actors that can take on these risks and compensate for them by pricing them to users. For example, the solver can guarantee execution by covering the losses if they so occur or by filling the user’s intents using their own balance sheets. ### Optimism Superchain Another example of aggregation liquidity is the Optimism Superchain initiative. The Superchain, defined by the [Optimism documentation](https://docs.optimism.io/stack/explainer) is “a network of chains that share bridging, decentralized governance, upgrades, a communication layer and more – all built on the OP Stack.” The project focuses on aggregating liquidity, similar to AggLayer. Optimism Superchain will have all chains that are a part of the Superchain utilize a shared bridge contract. This is the first step in having aggregated liquidity between chains in the Superchain. ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/22b9e5c470ac.jpg) The difference between the Superchain and the AggLayer is that the AggLayer relies on ZK-proofs for seamless, whereas the Superchain relies on a shared [sequencer](https://ethereum.org/en/developers/docs/scaling/optimistic-rollups/) between chains opting into the Superchain. While this post won’t get into the details of shared sequencing, you can refer to [this](https://www.astria.org/blog/astria-the-shared-sequencer-network) to understand how shared sequencing unlocks benefits in the realm of seamless cross-chain interoperability and, to some extent, atomic composability (the same problems elucidated above with cross-chain atomic composability apply here too). Because the Superchain mandates that chains opting in have to use the shared sequencer, it could limit the execution environments that can be used for chains opting into the Superchain.  Other cumbersome challenges arise, such as having the chains lose access to the MEV their users create, in addition to other challenges outlined [here](https://mirror.xyz/0xfa892B19c72c2D2C6B10dFce8Ff8E7a955b58A61/TXMyZhhRFa-bjr7YHwmJpKBwt2-_ysirbh_VpNy3qZY). However, teams like [Espresso](https://www.espressosys.com/) are working on ways to redistribute MEV enabled by chains utilizing a shared sequencer. Furthermore, all chains connected to the Polygon AggLayer (and hence post ZK proofs to this AggLayer) need to use the same ZK circuits which could also limit the execution environments that can be used for chains connected to the AggLayer. ## Chain Abstraction is a Piece of CAKE ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/77e658aa6982.jpg) [Frontier Research](https://frontier.tech/) has developed the CAKE (Chain Abstraction Key Elements) framework, which can be seen above. This outlines the three layers (excluding the user-facing application layer) required to reach a state where: “In a chain abstracted world, a user goes to a dApp’s website, connects their wallet, signs the intended operation and waits for eventual settlement. All the complexity of acquiring the required assets to the target chain and the final settlement gets abstracted away from the user, happening in [the three] infrastructure layers of the CAKE.” The framework identifies the three infrastructure layers of the CAKE as the permission layer, the solver layer, and the settlement layer. We have mostly touched on the solver and permission layers. The permission layer consists of account abstraction and policies - authorization as we’ve called it - and the settlement layer, which includes low-level technology like oracles, bridges, [pre-confirmations](https://mirror.xyz/preconf.eth/sgcuSbd1jgaRXj9odSJW-_OlWIg6jcDREw1hUJnXtgI), and other back-end features. As such, the settlement layer is expected to be greatly beneficial for solvers and other sophisticated actors and user-facing applications, as components of settlement in this framework all work together to help solvers manage their risk and provide better execution for users. This further extends into other components like data availability and execution proofs. These are all requirements for chains to provide a safe building experience for application developers and provide security guarantees which are eventually passed onto end-users. The CAKE framework encompasses many of the concepts mentioned in this post and provides a coherent way of looking at the various components of chain abstraction and their relation to each other. Those interested in the framework can read [this](https://frontier.tech/the-cake-framework) introductory article. ## Case Studies for Chain Abstraction While we’ve already touched on a few projects spearheading the effort towards a chain abstracted future, here are a few other notable projects that are doing the same. ## Particle Network Particle Network is launching a modular L1 blockchain built on the Cosmos SDK, which will operate as a high-performance EVM-compatible execution environment. Originally, Particle debuted as an account abstraction service provider, enabling users to create smart contract wallets linked to their Web2 social accounts to then be used natively within dApp-embedded interfaces. Since then, the protocol has expanded its offerings, aiming to proliferate chain abstraction across the broader blockchain landscape through a suite of wallet, liquidity, and gas abstraction services on its L1. Similar to other chain abstraction service providers, Particle envisions a future in which anyone will be able to easily transact across multiple chains through a single account, paying gas fees in any token they wish. As such, the underlying L1 will serve as a coordinator for the multi-chain ecosystem, unifying users and liquidity across EVM and non-EVM domains alike. Let’s see how it works. ### The Particle Chain Abstraction Stack Particle offers a multi-faceted toolkit for chain abstraction services, each core technology playing a unique role as part of a greater whole. **Universal Accounts** From the perspective of an end-user, Particle’s chain abstraction stack starts with first principles - creating an account. Universal Accounts on Particle function as ERC-4337 smart accounts attached to a pre-existing EOA (externally owned address), aggregating token balances across multiple chains into a single address by automatically routing and executing atomic cross-chain transactions. While a traditional crypto wallet can be used to create and manage an account, Particle’s [WaaS](https://developers.particle.network/docs/modular-smart-waas) enables users to use social logins for onboarding as well. To abstract away various complexities of blockchain-native operations, a UA functions as a unified interface built on top of existing wallets, allowing users to deposit and use tokens across multiple blockchain environments as if it existed on a single chain. To maintain a synchronous state across UAs, account settings are stored on the Particle L1 to be used as a central source of truth across every instance. The network will then facilitate cross-chain messaging to either deploy a new instance(s) or update existing ones. As such, the Particle L1 acts as a coordination and settlement layer for all cross-chain transactions processed through Particle’s UAs. ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/c4a080a58136.jpg) **Universal Liquidity** Another key component of Particle’s chain abstraction services is the Universal Liquidity functionality. While UAs provide a means for users to express their transactional request through an interface, Universal Liquidity refers to the layer responsible for the automatic execution of these requests, which in turn enables a unification of balances across different networks. This feature is key to enabling cross-chain transfers which would otherwise be hindered by current barriers to entry, like purchasing the native gas token and creating a native wallet for a new network. For instance, when a user wishes to purchase an asset on a blockchain they have never used before and don’t have any funds on, the liquidity needed for this purchase is automatically sourced from a user’s existing balances, which may likely be on a different chain and a different token. This is largely made possible through Particle’s Decentralized Messaging Network (DMN), which enables specialized services, known as Relayer Nodes, to monitor external chain events and the settlement of state events. To be more exact, relayers in the DMN use a Messaging Protocol for monitoring the status of UserOperations on external chains and then settling the final execution status to the Particle L1. **Universal Gas** The third pillar of Particle’s chain abstraction stack is the implementation of a Universal Gas Token - part of the network’s gas abstraction service. Accessed by interacting with Particle’s UAs, Universal Gas allows users to spend any token to pay for gas fees, meaning Bob can pay a transaction fee for a swap on Solana using his USDC on Base, while Alice pays a transaction fee for purchasing an NFT on Ethereum using her ARB token on Arbitrum. When a user wishes to execute a transaction through a Particle UA, the interface will prompt the user to select their gas token of choice, which is then automatically routed through Particle’s native Paymaster contract. All gas payments are settled to their respective source and destination chains, while a portion of the fee is swapped into Particle’s native $PARTI token to be settled on the Particle L1. ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/0d732bc019c4.jpg) ### Roadmap Particle builds on top of its existing account abstraction infrastructure, for which it has reported over 17m wallet activations and over 10m UserOperations to day. The addition of a Universal Liquidity layer, coupled with a Universal Gas token, aims to mark Particle’s expansion into providing chain abstraction services across a broader spectrum of users and participants. The Particle L1 is not meant to be another blockchain directly competing with today’s incumbents; rather it seeks to provide an interoperability layer to connect them all instead, working with key teams in the chain abstraction services sector, including the Near and Cake R&D teams. The Particle Network L1 is currently in its testnet phase, allowing early participants to try out Universal Gas within an experimental UA implementation ## Near Protocol Near is a sharded Proof-of-Stake Layer 1 blockchain that serves as an full-stack application domain for developers building decentralized products and services. Much of Near’s core ethos revolves around bridging the gap between blockchain-native applications and mainstream audiences. A key to fulfilling this vision is abstracting away the blockchain from the end-user. Near approaches this with *Account Aggregation*- a multi-faceted architecture built to abstract away key pain points of using blockchain networks such as switching wallets, managing gas fees, bridging. It accomplishes this by funneling all operations to be run through a single account. Let’s dive deeper to better understand how this all works. ### The Near Chain Abstraction Stack ![](https://shoal.xyz/research/writing/the-0-1-of-chain-abstraction/img/483587ca6505.jpg) **Near Accounts** In addition to the alphanumeric public key hash standard on most blockchains today, Near’s proprietary account model enables each account to be mapped to a human-readable account name, i.e. alice.near. Near accounts also utilize two types of access keys which are distinct in their nature and underlying functions, enabling accounts to be able to manage multiple keys across multiple blockchains, each key accounting for the various permissions and configurations that are unique to its domain: - Full-Access Keys: These can be used to sign [transactions](https://docs.near.org/concepts/protocol/transactions) doing virtually action on an account's behalf and should therefore never be shared. - Function-Call Keys: These keys are granted permissions to sign calls exclusively to a specific contract or set of contracts. Further bolstering the abstraction of blockchains to the end-user is a simplified onboarding process with FastAuth, Near’s proprietary key management system. FastAuth enables users to sign up for a blockchain-native account with something as simple as their email address and uses passkeys, which replace passwords with biometrics, in place of long and complex seed phrases and passwords. **Chain Signatures** Multi-chain signatures are a key component of Near's abstraction of blockchains, allowing any NEAR account to have associated remote addresses on other chains and to sign messages and execute transactions from those addresses. To enable this, Chain Signatures use the NEAR MPC (multi-party computation) network as the signer for these remote addresses, eliminating the need for explicit private keys. This is enabled by a novel threshold signature protocol, which implements a form of key resharing that allows the MPC signer to maintain the same aggregate public key, even as key shares and nodes constantly change. Making MPC signer nodes also part of the NEAR network allows smart contracts to start the signing process for an account. By using different combinations of a chain ID, a NEAR account ID, and a specific path, each account can create an unlimited number of remote addresses on any chain. **Meta Transactions** Another key issue hindering the development of a seamless user experience across the universal blockchain landscape today is that each blockchain requires gas fees to be paid in its own native token, requiring users to acquire these tokens prior to being able to use the underlying network. [NEP-366](https://github.com/near/NEPs/pull/366) introduced meta transactions to Near, a feature which allows for the execution of transactions on Near without owning any gas or tokens on the chain. This is made possible through Relayers, a third-party service provider which receives signed transactions and relays them to the network while attaching the tokens necessary to subsidize their gas fees. From a technical perspective, the end user creates and signs a SignedDelegateAction, which contains the data necessary to construct a Transaction, and sends it to the relayer service. The relayer signs a Transaction using this data, sends the SignedTransaction to the network via RPC call, and ensures the relayer pays the gas fees while the actions are executed on the user’s behalf. To better illustrate what this may look like in practice, consider the following example: Alice wants to send Bob some of her $ALICE tokens, but lacks $NEAR tokens needed to cover gas fees. By using meta transactions, she creates a DelegateAction, signs it, and sends it to a relayer. The relayer, who pays the gas fees, wraps it in a transaction and forwards it on-chain, allowing the transfer to be completed successfully. ### Roadmap The key to a successful implementation of a seamless user experience across multiple blockchain networks is the integration and support of those blockchains, even if they are competing businesses. Though Near functions as a competitive business of its own, their growth strategy revolves around growing the industry as a whole, granting their users access to many other blockchains in a seamless and secure manner. ## Honorable Mentions Here are some other teams building solutions for chain abstraction services worth keeping an eye on – this list is not necessarily exhaustive but instead provides a foundation for those interested in conducting further research into chain abstraction models. ### Connext Connext is a modular interoperability protocol which defined chain abstraction in their blog ([May 2023](https://medium.com/connext/introducing-chain-abstraction-9b8f6e4dc31a)) as a “pattern to improve dApp user experience by minimizing the need for users to care about the chain they’re on,” which accurately depicts the core principle chain abstraction service providers are building around today. Though Connext offers a set of smart contract modules for application developers through its Chain Abstraction Toolkit, its core feature is xCall, a primitive which enables smart contracts to interact with one another across different environments. The xCall function initiates a cross-chain transfer of funds, calldata, and/or various named properties, which the Chain Abstraction Toolkit wraps in simple logic for developers to utilize. From a developer perspective, this implies a relatively simple process: 1. Write an adapter for the function they wish to abstract. 2. Deploy the necessary modules for the chains they wish to integrate. 3. Call the function directly from their UI. ### Socket Protocol Socket provides infrastructure for application developers building interoperability-centric products and services with secure and efficient data and asset transfers across chains. [Socket 2.0](https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc)marks a shift for the protocol from cross-chain to chain abstraction services, highlighted by its flagship Modular Order Flow Auction (MOFA) mechanism, which aims to enable a competitive mechanism for efficient chain abstracted markets. Traditional OFAs involve a network of various actors performing specialized tasks that compete to deliver the best possible outcome for an end-user request. Similarly, MOFA is designed to provide an open marketplace for execution agents, called Transmitters, and user intents. Within the MOFA, Transmitters compete to create and fulfill chain abstracted bundles, or ordered sequences of user-requests which require transfer of data and value across multiple blockchains. ### Infinex Infinex is building a single UX layer aimed at unifying decentralized applications and ecosystems. Its flagship product, [Infinex Account](https://x.com/infinex_app/status/1784777227814748472), is a multi-layered service that functions as a platform for integrating any on-chain application into a simplified UX for the end-user. At its core, the Infinex Account is a set of cross-chain smart contracts that can be controlled, secured and recovered via standard web2 authentication. ### Brahma Console Brahma Finance is building its flagship Console product, an on-chain execution and custody environment aimed at enhancing user experience across DeFi, focusing specifically on the EVM blockchain ecosystem. Brahma uses batched and chained transactions to synchronize transactions across different chains, and Smart Accounts for interacting on-chain. The end result will reflect a [user experience which enables seamless cross-chain interactions within a single UI](https://x.com/jainargh/status/1777712431227412733). ### Agoric Agoric is a Cosmos-native Layer 1 blockchain for building cross-chain smart contracts in JavaScript. The Agoric platform is designed with an asynchronous, multi-block execution environment, and aims to be the go-to environment for developing cross-chain applications. Agoric utilizes the Cosmos InterBlockchain Communication (IBC) Protocol for interchain communications, while leveraging Axelar’s General Message Passing (GMP) for interactions beyond the Cosmos ecosystem. Agoric’s Orchestration API simplifies developer experience by abstracting the complexities involved in cross-chain communication and smart contract execution, while the end-user benefits from applications with inherent chain abstracted features. ## Closing Thoughts By now, the advantages that chain abstraction unlock for end-users should be clear - the complexities of using blockchain-native applications are entirely abstracted away into a unified interface layer, creating a global and chain-agnostic point of contact for anyone who wants to participate. Equally as importantly, chain abstraction could unlock a huge benefit for blockchain applications. Currently, Web2 developers don’t “choose” where to deploy their application. For instance, Airbnb is available for anyone with an internet connection. However, in the Web3 landscape application developers need to choose where to deploy their application (for example, on Ethereum, Solana or Cosmos). Not only does this limit TAM, but also means that application developers are encumbered by needing to choose the “right” chain to deploy their application on. This is not only a hard decision to make but a crucial one. There have been a handful of applications that were extremely successful but struggled due to the underlying blockchain. Furthermore, with the continuous development and evolution of blockchains today, the “right” chain may constantly be changing. In a chain abstracted future, application developers are no longer encumbered by having to select a chain that their success is tied to. It is evident that we are headed towards an increasingly multichain future. This inevitably will only compound UX issues that are one of the most critical barriers to mainstream adoption. We believe chain abstraction, with its various components, is a possible solution to many of crypto’s UX problems  today. ## References - Akdeniz, M. (2024, February 5). *Preconfirmations: The Fulfillment-Delivery Paradigm.* Mirror. [https://mirror.xyz/preconf.eth/sgcuSbd1jgaRXj9odSJW-_OlWIg6jcDREw1hUJnXtgI](https://mirror.xyz/preconf.eth/sgcuSbd1jgaRXj9odSJW-_OlWIg6jcDREw1hUJnXtgI) - Avo Wallet. (n.d.). *Avo Wallet.* Twitter.[https://twitter.com/Avowallet](https://twitter.com/Avowallet) - Bananagun. (n.d.). Bananagun. [https://bananagun.io/](https://bananagun.io/) - Bhuptani, A. (2023, May 24). *Introducing Chain Abstraction.* Medium. [https://medium.com/connext/introducing-chain-abstraction-9b8f6e4dc31a](https://medium.com/connext/introducing-chain-abstraction-9b8f6e4dc31a) - Blockworks. (2024, May 2). *Igniting Liquidity Cross Chain At The Speed Of Light*. Blockworks. [https://blockworks.co/podcast/lightspeed/8bbfdbe8-0801-11ef-9bad-0b717eccd217](https://blockworks.co/podcast/lightspeed/8bbfdbe8-0801-11ef-9bad-0b717eccd217) - deBridge. (n.d.). *Validation progress.* deBridge. [https://app.debridge.finance/validation-progress](https://app.debridge.finance/validation-progress) - Dydx. (n.d.). Dydx. [https://dydx.exchange/](https://dydx.exchange/) - Elizabeth. (2024, February 8). *Astria: The Shared Sequencer Network*. Astria. [https://www.astria.org/blog/astria-the-shared-sequencer-network](https://www.astria.org/blog/astria-the-shared-sequencer-network) - Espresso. (n.d.). Espressosys.[https://www.espressosys.com/](https://www.espressosys.com/) - Farmer, B. (2024, February 7). *Aggregated Blockchains.* Mirror. [https://mirror.xyz/0xfa892B19c72c2D2C6B10dFce8Ff8E7a955b58A61/TXMyZhhRFa-bjr7YHwmJpKBwt2-_ysirbh_VpNy3qZY](https://mirror.xyz/0xfa892B19c72c2D2C6B10dFce8Ff8E7a955b58A61/TXMyZhhRFa-bjr7YHwmJpKBwt2-_ysirbh_VpNy3qZY) - Frax. (n.d.). Frax. https://www.frax.com/ - Frontier Research. (2024, February 15). *Introducing the CAKE framework.* Frontier. [https://frontier.tech/the-cake-framework](https://frontier.tech/the-cake-framework) - Hyperliquid. (2024, March). *About Hyperliquid*. Hyperliquid. [https://hyperliquid.gitbook.io/hyperliquid-docs](https://hyperliquid.gitbook.io/hyperliquid-docs) - Imajinl. (2024, March 4). *Value Accrual in the Modular Stack.* Shoal Research. [https://www.shoal.gg/p/value-accrual-in-the-modular-stack](https://www.shoal.gg/p/value-accrual-in-the-modular-stack) - Infinex. (2024, April 28). *Infinex’s mission is to accelerate mainstream onchain adoption.*Twitter.[https://x.com/infinex_app/status/1784777227814748472](https://x.com/infinex_app/status/1784777227814748472) - Kessler, S. (2024. Mar 19). *Optimism Finally Starts Testing 'Fault Proofs' at Heart of Design – and of Criticism*. Coindesk. [https://www.coindesk.com/tech/2024/03/19/optimism-finally-starts-testing-fault-proofs-at-heart-of-design-and-of-criticism/](https://www.coindesk.com/tech/2024/03/19/optimism-finally-starts-testing-fault-proofs-at-heart-of-design-and-of-criticism/) - *Modular Smart Wallet-as-a-Service.*(2024, February). Particle Network. Retrieved May 29, 2024 from [https://developers.particle.network/docs/modular-smart-waas](https://developers.particle.network/docs/modular-smart-waas) - *NEP-366: Meta transactions #366.*(2022, November 23). Github. Retrieved May 29, 2024 from [https://github.com/near/NEPs/pull/366](https://github.com/near/NEPs/pull/366) - *Optimistic Rollups*. Ethereum. (2024, May 7). [https://ethereum.org/en/developers/docs/scaling/optimistic-rollups/](https://ethereum.org/en/developers/docs/scaling/optimistic-rollups/) - Orb Labs. (2024, May 9).  *Launching Orby.* Twitter. [https://x.com/0xOrbLabs/status/1788610816264003745](https://x.com/0xOrbLabs/status/1788610816264003745) - Polygon. (n.d.). *Agglayer.* Polygon. https://polygon.technology/agglayer - Shoal Research. (2023, Nov 27). *CoW Swap: Intents, MEV, and Batch Auctions.* Shoal Research. [https://www.shoal.gg/p/cow-swap-intents-mev-and-batch-auctions](https://www.shoal.gg/p/cow-swap-intents-mev-and-batch-auctions) - Socket. (2024, April 16). *Socket - First Chain Abstraction Protocol.* Mirror. [https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc](https://mirror.xyz/0x6FD2bd90D50eDEe139103454116F252f6F5eC928/zePFPVi6oPI2o_Q6jDrGYn6SBVOGMybnFKQJ-DDVKqc) - *Superchain Explainer.* (2024, May 16). Optimism. Retrieved May 29 2024 from [https://docs.optimism.io/stack/explainer](https://docs.optimism.io/stack/explainer) - Timofeev, P. (2024, Jan 18).*Jupiter Exchange: Solana’s Dex Aggregator.* Shoal Research. [https://www.shoal.gg/p/jupiter-exchange-solanas-dex-aggregator](https://www.shoal.gg/p/jupiter-exchange-solanas-dex-aggregator) - Watts, J. (2024, May 8). *Vitalik just proposed EIP-7702.* X. [https://twitter.com/jarrodWattsDev/status/1788119041024168385](https://twitter.com/jarrodWattsDev/status/1788119041024168385) ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Particle Network. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # The Convergence of Ai, DeFi and Intents with Aperture Finance > Exploring how Aperture Finance converges AI, DeFi and intents to optimize on the shortcomings of crypto UX today. - Publisher: Shoal Research (https://shoal.xyz) - Category: AI & Agents - Published: 2024-05-16 - Canonical: https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/ - Keywords: crypto, DeFi, solvers, MEV, restaking, security, infrastructure, Solana, Ethereum, AI & Agents ![](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/05b293cf618e.jpg) ## Introduction The growth in the digital asset space is on an exponential curve, propelled by a confluence of factors, including worsening traditional financial situations around the world and remarkable innovations such as artificial intelligence (AI) and new decentralized coordination methods. As users increasingly seek more financial flexibility, these trends present unique opportunities to leverage emerging technology to fulfill these needs. Over the last year, "intents" — user expressions for a desired goal — have sparked a wave of innovations across networks and applications, simplifying complex tasks such as trades and other on-chain actions. Intents abstract away the intricacies involved in on-chain operations, making decentralized finance (DeFi) more accessible to a wider audience. The meteoric rise in adoption of technologies like ChatGPT, a powerful large language model, adds a new tool for user complexity abstraction. These advancements offer revitalizing opportunities for protocols to couple user intents with LLMs like GPT, enhancing the user experience through natural language processing and contextual understanding. **At the intersection of these technologies lies a unique opportunity to transform DeFi user experience (UX) as we know it today.** ## State of DeFi UX Today **User Experience: Web3’s Achilles Heel** The rapid development of technology over the past several decades has brought about unprecedented shifts in efficiency and performance in people’s everyday lives. In today’s [increasingly consumer-centric world](https://fred.stlouisfed.org/graph/fredgraph.png?g=1nZ14), user experience can make or break a business. Prioritizing user experience is therefore crucial for the long-term success of businesses across virtually all domains today. A seamless and pleasant user experience not only attracts users but retains them over time. These are the kind of products and services people enjoy using because of their design and interaction elements, regardless of their essential function. On the other hand, a poor user experience will inevitably steer users away to a similar product or service which functions more efficiently. Decentralized finance (DeFi) applications have failed to gain traction outside of a relatively concentrated portion of crypto-native users, primarily due to a long history of poor user experience. DeFi imposes a myriad of security and financial risks, with unsuspecting retail users often bearing the brunt of these consequences. Today, a single misstep when conducting transactions on-chain can lead to unexpected financial losses. One of the common security issues arises from users inadvertently clicking on fraudulent links or falling victim to phishing scams. These malicious attacks trick individuals into connecting their wallets to harmful programs while performing routine tasks like claiming an eligible airdrop. Conversely, many of the financial risks in DeFi are often obfuscated by technical complexities which are poorly communicated to users, emerging during activities such as rebalancing weighted portfolios or a position in a liquidity pool. Sophisticated entities engage in value extraction tactics like frontrunning or sandwich attacks to exploit trades, resulting in poor execution outcomes for end-users. Additionally, transacting across various blockchains using third-party bridges introduces another layer of risk; with reported hacks causing over $2.8 billion worth of stolen assets highlighting this vulnerability issue within DeFi systems. The rise of LLMs like Chat-GPT have introduced new consumer-facing solutions to help automate many tedious and complex tasks, from making grocery lists to lecture plans for teachers. This technology ultimately stands to improve many quality-of-life aspects of people’s everyday lives. Therefore, considering the poor state of DeFi UX today, we ask - *why should navigating DeFi be any different from typing a prompt into chatGPT?* ## It’s The Intent That Counts To formally define an intent; “Signed messages which allow for a set of state transitions from a given starting state, a special case of which is a transaction which allows for a unique transition.” - [Paradigm](https://www.paradigm.xyz/2023/06/intents#what-are-intents) An intent is an abstract operation description of a user’s desired outcome from an on-chain interaction, i.e., the execution of a transaction which purchases asset X at price Y, which delegates the execution to smart contracts or third parties for enhanced user experience. An intent goes beyond a mere transaction request, however; it's a holistic representation of the user's desired outcome on the blockchain. It comprises 4 key facets: - **Domain**: Where the intent executes. - **Objective**: The user's articulated goal. - **Constraints**: Conditions for successful execution. - **Preferences**: User-specified priorities or processing options. ## Are all intents equal? ## The short answer is no. For starters, protocols may choose to implement different types of intents using different methods. Our previous article, [MEV Protection: DEX & Aggregator Anti-MEV Mechanisms](https://www.shoal.gg/p/mev-protection-dex-and-aggregator?utm_source=publication-search) outlines how DEX aggregators like CoW Swap and 1inch might lead users to the same outcome, that is to swap token A -> token B, though they use different algorithms and intent-based models to perform the desired action. Intents can be very app-specific, i.e. an application which restricts intents to perform a specific function, such as performing a DEX swap, or they can be more generalized in which they serve as a framework for building applications on top of. They can be constrained to a specific domain which they are specialized in, or they can function across multiple domains to capture a larger base of users. ### The Intents Infrastructure Landscape Today ![Figure 1. Intent Landscape. Source. Delphi Digital.](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/211273455edf.jpg) **Anoma** Anoma Network is building the “[universal intent machine on Ethereum](https://ethresear.ch/t/rfc-draft-anoma-as-the-universal-intent-machine-for-ethereum/19109)”, to proliferate the development of intent-centric applications. Key to Anoma’s composability is that intents and applications written with Anoma can be ordered, solved, and settled anywhere - on Ethereum, on EVM and non-EVM rollups, on Eigenlayer AVSs, on Cosmos chains, Solana, and any sufficiently programmable state machine. Users express intents, which must be created by the user interfaces, understood by intent gossip nodes, matched by Solvers, and validated by the application’s validity predicates. Solver algorithms instruct a solver how to match an application’s intents and form valid transactions. Anoma user interfaces present a graphical or textual view of and controller for the application in question. **Suave (**Single Unifying Auction for Value Expression) Flashbots is building SUAVE, a modular blockchain network which offers an easily-adaptable mempool and decentralized block builder for any blockchain. Its key value proposition lies in the separation of the mempool and block builder roles from existing chains to offer a highly specialized plug-and-play alternative. At the core of SUAVE are intents, or ‘preferences’, which are the native transaction type on SUAVE. They can either contain a payload instructing a specific blockchain to be executed on, or instead leave the optimal routing to the Solvers, referred to as ‘executors’. Once a user has submitted their intent, it is passed to the Execution Market, in which executors compete in an auction to provide users with the best execution possible. Finally, a decentralized block building network gathers the collected preferences and turns them into blocks across all supported blockchains. The decentralized block-building market maximizes MEV for builders and validators while allowing the builder itself to become decentralized. **Essential** Essential is building the first declarative blockchain, that is, a blockchain which leverages constraints to achieve state updates without the need for execution. At a high level, Essential is an intent-centric layer-2 blockchain, deployed as an optimistic rollup on Ethereum. Optimizing for state updates without execution means that no state transition may be included if it does not satisfy the user’s intent. *In other words, users get what they want or they get nothing at all.*This approach aims to bypass a common bottleneck in today’s blockchains which leads to various performance issues and irregular spikes in transaction costs. User intents submitted to the Essential network declaratively outline a set of variables, as well as constraints on those variables, narrowing down the set of feasible execution routes. Users can also specify an objective utility function to represent their preferences and preference ordering. Solvers then attempt to maximize the user’s request with respect to their objective function. ### Tradeoffs with Intents Today **Trust Assumptions for Solvers** Users cannot choose where the intents settle themselves. This means intents may be settled on any blockchain or even a centralized server. Solvers are in charge of executing the intents of the user, a key design in abstracting away friction in the user experience. However, this delegation of execution rights adds a new layer of trust assumptions in the overall process, wherein the user must now trust that the Solvers is acting in their best interest, though Solvers may choose to utilize off-chain resources (i.e personal inventory held on a CEX) which reduce the overall transparency of the protocol. More broadly, this has raised questions about the necessity of these new layers, a common criticism being that introducing new middlemen only hurts the user over time, whether due to additional incurred service fees, malintent on Solvers’ behalf (i.e. colluding with block builders for MEV operations), and the centralization forces which may arise due to restrictive barriers to entry for running Solvers. ![](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/9a128604928f.png) *Does DeFi really need more middlemen? (c/o [Orderflow.art](https://orderflow.art/frontends))* That said, though Solvers are often centralized entities today, i.e. market maker firms, the emergence of decentralized models such as [PropellerSolver](https://docs.propellerheads.xyz/propellerheads-docs/introduction/propellersolver) presents a compelling opportunity moving forward. PropellerSolver itself is an advanced network of swap Solvers – across EVM and non-EVM chains - which accesses a wide network of liquidity sources, including market makers and protocol-native paths, to secure competitive prices for trades across EVM and non-EVM chains. It uses a custom routing algorithm and gas-optimized contracts to find the most optimal liquidity routes on users’ behalf, and uses private transaction routing to offer MEV-protection for users. **Single-Use Functionality** Another key limitation which arises is that intents are still constrained in their functions, as they are designed to be executed at a single point in time. This poses a challenge to the efficient fulfillment of various on-chain operations, such as managing an LP position over a specific period of time, or executing a trade without losing money due to being front run or sandwiched. ## Merging AI and Intents AI presents a unique application for streamlining end users' intents. By leveraging intents, protocols can handle multistep intent criteria and fill input requirements using a chatbox interface. This means that users can explain their desires in plain language, and the flexible interface can capture multistep intents and process them to Solvers. The more complex an intent-based application or protocol is, the more time it may take to fulfill the minimum requirements to execute the intent. In theory, the process of intent declaration can be fluid, while the nuances and specifications are worked out using machine learning data, which are then passed on to the Solver. Intents in other spoken languages are trivial, as machine learning can properly translate the desired outcome to Solvers. ### Intent Data Collection and Refining Intents Possible intent outcomes are generally constrained by UX limitations created by the protocol, where the user can perform only designated operations. If a specified intent outcome does not exist, protocols may leverage LLM input data to refine the intent path at a later date, essentially creating a product feedback loop. Similar to how LLM models train and improve based on inputs, intent data can be used to refine users' intents. For example, let's say a DEX uses intent-based swaps leveraging a chatbot. The LLM operator notices an increased number of exotic requests to open a long position on a perps DEX after a swap. This request data can be used to iterate on the intent paths and prompting to improve the UX. ## Case Study: Aperture Finance **Aperture Finance** is a DeFi protocol offering liquidity management services, which aims to transform the state of DeFi UX by building an intent based protocol with a GPT-like chatbox UX, enabling users to state their goals in natural language. A network of third-party participants, called Solvers, will then execute requests on behalf of users. Solvers are in charge of optimizing the process, allowing the intent/request to be processed efficiently and at a low cost. Aperture acts as a general-purpose DeFi protocol with a range of practical applications. ## Aperture’s Architecture From a technical perspective, Aperture is building a novel Layer 2 that accommodates intents on both Ethereum Virtual Machine (EVM) and non-EVM chains by taking advantage of the latest advances in LLMs. ![Figure 2. Aperture’s System Architecture](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/76f879bfabf8.jpg) **There are four key actors in Aperture’s architecture:** - **Orchestrator:**The orchestrator efficiently disseminates and processes user intents. This includes the intent mempool, the blockchain storage layer, and the execution environment where the smart contracts derived from user intents are executed. - **Solver:** The Solver provides solutions in exchange for economic incentives from the intent poster. Solvers handle the system's complexity. They can be public and transparent Solvers, processing standard intents in a transparent manner suitable for general transactions. Alternatively, they could be privileged Solvers, handling privacy-sensitive intents with special trust credentials. - **Sequencer:** Sequencers are tasked with ordering and processing intents on Aperture’s L2 chain. Then compressing the processed intents and transactions and pushing them to the designated Layer 1. - **Fulfiller:**The fulfiller is responsible for pushing the solutions devised by Solvers to the target chain and monitoring their execution status. Their role is to ensure that the Solver properly solves intents. **Intent Lifecycle on Aperture** The flow of an intent on Aperture, from the end-user to the designated blockchain starts with users defining their intents and submitting them for processing by solvers. The intents are then processed with privacy mechanisms like zero-knowledge proofs, verified with trust scoring and ZKPs, and finally fulfilled with oversight from the Fulfiller to ensure secure and reliable transaction execution. 1. **Intent Definition -**The user defines their intent, including the domain, objective, constraints, and preferences for the desired outcome within the blockchain environment, i.e. ‘*Buy 10 ETH at a price of $3000 per token on Arbitrum’*. 2. **Intent Submission -**The intents are submitted to a network of Solvers, responsible for processing and fulfillment of the intents. The Solver then submits the intent, solution, and corresponding proof to the Intent Mempool for storage. 3. **Intent Processing -** Intents in the Intent Mempool are then processed via ZK-Processor to ensure privacy and security are maintained, and that user intents are executed faithfully and in alignment with predefined end-state criteria. 4. **Solution Verification -**The ZK Processor then generates Zero-Knowledge Proofs (ZKPs) for historical on-chain data to validate Solvers' outputs without revealing confidential data. This is later used as input for Aperture’s Dynamic Trust Scoring methodology, which assigns trust scores to Solvers based on historical performance and adherence to network protocols. 5. **Solution Fulfillment -**The Fulfiller is then responsible for pushing the solutions devised by intent Solvers to the target chain and monitoring their execution status, enforcing accountability and penalizing any malicious behavior. ### The Aperture Intents DSL Key to Aperture’s value proposition is the ability for users to articulate their transactional goals and preferences with greater ease. Modern LLMs utilize natural language processing to interpret user prompts and emit an appropriate output based on its training data. Given that imperative blockchain architectures do not natively support the processing of intents, the need for interpretive solutions arises. Aperture utilizes a proprietary intents-centric programming language, the Intents DSL, to enhance the expressibility of user Intents. A Domain Specific Language, or DSL, refers to a programming language specialized to a particular application domain, tailored to fulfill specific tasks. Common examples include SQL, HTML, CSS, to name a few. The purpose of these specialized languages is to enable the expression of logic within a specific domain in a more efficient manner than existing solutions, thereby enhancing the overall developer experience, and consequently the user experience of the applications built on top of said DSL. Aperture’s Intents DSL enables users to express their intent using natural language, which gets then interpreted and processed into logic which expresses the fulfillment of that intent as an event on the blockchain. The Intent Interface, the chatbot-like frontend through which the user interacts, facilitates the entire process to 1) translate and mirror the intent back to user to be verified, and 2) interpret and deliver the intent as a valid expression of onchain logic to the Intent Clearing House, the following layer involved in the fulfillment of an intent. To further illustrate this concept, consider an example of what a user ‘conversation’ may look like; **User** **Input**- “Rebalance my ETH-USDC positions on Arbitrum and Base so that ¾ of my funds are in the top-performing pools and the remaining ¼ are distributed evenly across any other pools.” **UI - “Sure, here are the details of your request:** - Eligible Assets: ETH-GMX pairs on Mainnet, Arbitrum, and Avalanche - Permitted Actions: Bridge, Remove liquidity, Swap ETH or GMX, Add Liquidity - Primary Objective: Reallocate 80% of eligible asset capital to the pool with the highest spot APR according to data from APY Vision. - Secondary Objective: Distribute the remaining 20% of eligible asset capital evenly across the other pools not included in the primary objective. - Confirmation: Sign Intent declaration if correct.” At this point, the user confirms the DSL interpretation is valid by signing the intent to be submitted to the clearing house. ### Intents Clearing House Functioning similarly to the public mempool on Ethereum, the Intents Clearing House serves as a waiting room for intents. This stage is responsible for organizing these intents to be  processed and fulfilled on the designated blockchain, ranking intents and their corresponding solutions by quality of execution on user’s behalf, as well as accounting for any additional  conditional requirements, i.e. time-sensitive orders. The fulfillment of user intents is enforced onchain through the use of Verification Smart Contracts, wherein each type of intent use case will require a smart contract to simulate, verify, and police the proposed solution. ## The Use of ZKPs in The Aperture Protocol Through a partnership with [Brevis](https://brevis.network/), a novel ZK coprocessor, Aperture introduces an autonomous, intent-centric framework that allows users to specify intentions over an extended period, reacting to specific conditions, addressing a common limitation discussed earlier, wherein user intents can only be expressed at a single point in time. For instance, with Brevis, users can set an instruction to rebalance an ETH-USDC Uniswap V3 position when there is 15% price movement, continuing until they decide to stop. **Maintaining Solver Integrity** In addition to extending the functionality of intents, Zero-Knowledge Proofs (ZKPs) are also employed to enforce protocol standards. Aperture maintains the integrity of its Solvers by employing a dynamic trust scoring system to evaluate Solvers based on their historical performance and accuracy. This is enabled through the use of the Brevis ZK coprocessor, which enables smart contracts to access and use full historical on-chain data from any blockchain to validate the accuracy of solutions without exposing private data. ## Use Cases & Applications Data from Aperture’s [Intents dashboard](https://dune.com/aperture_finance/intents-metric-dashboard) indicate that the protocol has handled over $2.3b in Intents volume, spanning across over 2.7m intents in total. Looking closer by intent type, the most common intents today revolve around rebalancing, that is, redistributing assets in a liquidity pool to optimize performance which can be based on predefined criteria, and reinvesting, or reallocating any earned fees or rewards back into the liquidity pool to maximize returns. **Automated Liquidity Management** First, consider Liquidity Managers or Automated Liquidity Managers (ALM). That is, protocols that actively manage liquidity pool positions on users’ behalf. Concentrated liquidity market makers (CLMMs) like Uniswap V3 offer extensive flexibility in liquidity provision but are more complex for users, increasing Impermanent Loss (IL) risk when providing liquidity within narrow price ranges. Aperture has already built out a suite of liquidity management tools, offering automated position rebalancing, automated position closure based on pricing, pool ratio, and time and auto-compounding of fees. For instance, in an ETH/USDC pool, the LP position could be rebalanced with every 5% price movement to minimize IL. After 3 months, the strategy can be exited by swapping all capital to USDC. With the advent of Aperture’s AI-powered intents, users can express how they would like to customize and set up their LP position strategy using natural language, mitigating risks around performance after implementation. Today, the Total Value Locked (TVL) on ALMs on all different chains is [$584m](https://defillama.com/protocols/Liquidity%20manager), presenting a compelling opportunity to enhance the performance of a service which has been proven its product-market fit in the broader DeFi landscape, using AI-powered intents. ### Claiming an Eligible Airdrop Airdrops enable blockchain protocols to distribute their native tokens to addresses which have met required criteria, typically aligning with the interests of community members and early adopters. However, a common issue which arises during these events is an abundance of malicious links which get sent around by actors impersonating team or team member accounts, targeting unsuspecting users to connect their wallets to then be drained. Aperture’s intent-centric architecture enables users to avoid these risks while easily expressing their request through natural language. To further illustrate, let’s consider a user who wishes to claim all of their eligible airdrops across several different chains they have been proactively using. To start, they would type “Claim all eligible airdrops on my behalf across Arbitrum, Base, and Optimism” into the Aperture chatbot-UX, which processes and submits the request to be fulfilled by the Solver network. Any Solver which comes across the request can now view the user’s provided wallet address and cross-reference it with any claimable airdrops or rewards that are eligible for said address, ensuring that only the appropriate links and contract addresses are accessed. The proposed solutions would then be simulated by Aperture’s smart contract to verify the proposed outcome, and subsequently all verified solutions would be ranked and executed on the user’s behalf. Users receive the tokens they are eligible for in their designated wallet, without needing to stress about the verification of links and social media profiles. ### MEV-Protection Maximal Extracted Value (MEV) is captured by validators within a network through reorganizing transactions in a new block, including or excluding them during block production. MEV capture comes in the form of CDP-position liquidations or arbitrage, though the [former occurs much more frequently](https://eigenphi.io/). A particularly common malicious arbitrage strategy is **sandwiching**. In this scenario, a sophisticated entity may observe a significant token purchase waiting to be executed as a pending transaction in the public mempool. Using specialized software known as a MEV-bot, they can then place a buy order to be executed before that large order and a sell order immediately after, ensuring priority block inclusion by paying a higher validator tip. By doing so, the MEV-bot is effectively engaging in both frontrunning and backrunning, respectively, of the transaction. Roughly 5% to 10% of all DEX volumes are sandwiched on the Ethereum mainnet, according to [Hildobby](https://dune.com/hildobby/sandwiches) from DragonFly Ventures. ![](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/c037f499b8fe.png) Just in the past 7 days, $41 billion was traded on DeFi ([DeFiLlama](https://defillama.com/dexs)). ![](https://shoal.xyz/research/writing/the-convergence-of-ai-defi-and-intents/img/c9885a527e29.jpg) Since solvers are sophisticated actors, we expect them to implement MEV protection tools such as private transaction routing, order batching, and the utilization of off-chain capital to ensure users receive the lowest competitive price on their desired trade. ### Future Outlook - AI Enhances DeFi UX As digital asset adoption continues to soar, driven by global economic shifts, AI holds the promise to refine user intents continuously while also guiding users in formulating better, more precise intents. The integration of AI with user intents allows for significant UX improvements and valuable data collection, further optimizing DeFi protocols. In the future,  crypto could be abstracted down to a seamless, user-friendly interface where the desired fulfillment of outcomes is expressed in natural language, simplifying complex transaction operations which are delegated to be executed by a competitive network of Solvers whose integrity is maintained through cryptographic measures. ### Aperture’s Role While there are a number of exciting projects focused on blockchain networks and AI, few protocols lie at the intersection of AI, user-centric intents, and core DeFi primitives. Aperture aims to play a critical role in reshaping the future of user experiences onchain, by leveraging a myriad of evolving technical developments centered around efficiency and security. By utilizing a proprietary DSL, Aperture enables users to write intents using natural language, greatly simplifying the expression of these requests. By delegating the complexity of execution to Solvers, Aperture ensures that users can interact with DeFi protocols safely and effectively, fulfilling their requests exactly as they envision. By leveraging ZKPs, Aperture ensures that the Solvers responsible for executing user intents are acting in good faith and being appropriately rewarded for their services. ### Wrapping up As nascent as DeFi is, it's very clear it is here to stay as new technology is injected into the ecosystem. Not only does it improve operations for sophisticated actors but we can see the potential for these technologies to create a more accessible, user-friendly, and secure DeFi environment for even beginner and retail users. ## References 1. DeFiLlama. (n.d.). DEXs. Retrieved from[https://defillama.com/dexs](https://defillama.com/dexs) 2. DeFiLlama. (n.d.). Liquidity Manager Protocols. Retrieved from[https://defillama.com/protocols/Liquidity%20manager](https://defillama.com/protocols/Liquidity%20manager) 3. Propellerheads. (n.d.). PropellerSolver: Introduction. Retrieved from[https://docs.propellerheads.xyz/propellerheads-docs/introduction/propellersolver](https://docs.propellerheads.xyz/propellerheads-docs/introduction/propellersolver) 4. Hildobby. (n.d.). Sandwiches. Retrieved from[https://dune.com/hildobby/sandwiches](https://dune.com/hildobby/sandwiches) 5. Aperture Finance. (2023, February 7). The Intentional Campaign #7. Medium. Retrieved from[https://medium.com/@aperturefinance/the-intentional-campaign-7-3307e91af884](https://medium.com/@aperturefinance/the-intentional-campaign-7-3307e91af884) 6. Delphi Digital. (2023). WTF is Anoma Part 1: WTF are Intents. Retrieved from[https://members.delphidigital.io/reports/wtf-is-anoma-part-1-wtf-are-intents](https://members.delphidigital.io/reports/wtf-is-anoma-part-1-wtf-are-intents) 7. Delphi Digital. (2023). WTF is Anoma Part 2: WTF are Intent-Based Apps. Retrieved from[https://members.delphidigital.io/reports/wtf-is-anoma-part-2-wtf-are-intent-based-apps#centralized--fragmented-counterparty-discovery-d2ff](https://members.delphidigital.io/reports/wtf-is-anoma-part-2-wtf-are-intent-based-apps#centralized--fragmented-counterparty-discovery-d2ff) 8. Orderflow. (n.d.). Orderflow. Retrieved fromhttps://orderflow.art/?isOrderflow=true 9. Perridon Ventures. (n.d.). Redefining Blockchain Interactions: The Crucial Role of Solvers in an Intent-Focused Future. Retrieved from[https://perridonventures.xyz/publications/redefining-blockchain-interactions-the-crucial-role-of-solvers-in-an-Intent-focussed-future](https://perridonventures.xyz/publications/redefining-blockchain-interactions-the-crucial-role-of-solvers-in-an-Intent-focussed-future) 10. PossiblyResult. (2023, October 7). Tweet. Twitter. Retrieved from[https://twitter.com/PossibltyResult/status/1709742006388306115](https://twitter.com/PossibltyResult/status/1709742006388306115) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the author's own, not the views of their employer. This post has been sponsored by Aperture Finance. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Parallel Execution: The Next Generation of Blockchains > Exploring the design philosophies of parallelized blockchains and which teams are pushing the frontier today. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-05-01 - Canonical: https://shoal.xyz/research/writing/parallel-execution-the-next-generation/ - Keywords: crypto, infrastructure, Solana, Ethereum, Bitcoin, data, Infrastructure ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/ab060f5c24d9.jpg) ## Prelude ### 1.0 Blockchain Transactions Blockchains are virtual machines, a software-based computing model which runs on top of a distributed network of physical computers which anyone can join but is extremely difficult for any single entity to control. The concept of a blockchain was first put into writing in Satoshi Nakomoto’s infamous Bitcoin whitepaper in 2008, as the core infrastructure enabling cryptographically secured peer-to-peer payments in Bitcoin. Transactions are to blockchains what logs are to social media and internet companies; they serve as records of activity for that particular network, the key difference being that transactions on a blockchain are immutable and often publicly observable. **But what exactly is a transaction?** Transactions on blockchains involve the transfer of digital assets from one address on the distributed ledger to another, secured by the use of public key cryptography. Transactions can be used for decentralized peer to peer transfers, or for various authentication and verification processes as well. ![An example of a transaction which anyone can observe on a blockchain explorer like SeiTrace](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/952c817bb554.jpg) ### 1.1 How Blockchain Transactions Work When a transaction is initiated, i.e. Bob sends some tokens to Alice, Bob’s transaction is broadcast to the underlying blockchain network. Subsequently, clusters of specialized nodes on the network get to work verifying and validating the transaction as legitimate. Once enough of these nodes have verified the contents of the transaction, the transaction gets added to a block along with other user transactions. Once a block is full, it then gets added to the chain, hence the name ‘blockchain'. Bob’s transaction is now part of a secure and transparent ledger, and he and Alice can both verify the contents. Broadly speaking, all blockchain transactions contain metadata that helps the nodes operating and securing the network identify and execute a given set of instructions and parameters. Every transaction will have high-level data input by the original sender, such as the amount to be transferred, the destination address, and the digital signature to confirm the transaction, as well as various low-level data that is created and attached automatically, though this data varies by network and design. Ultimately, however, the processes involved behind the scenes at the networking layer prior to transaction execution vary by the design of the blockchain. **1.1.1 Mempool** A memory pool, or *mempool,* is a common feat of blockchain designs, implemented by traditional blockchain networks such as Bitcoin and Ethereum. Mempools are simply buffer zones, or ‘waiting rooms’, for pending transactions which are yet to be added to a block and executed. To better understand, we can lay out the lifecycle of a transaction on a blockchain which uses a mempool; 1. The user initiates and signs a transaction. 2. Specialized nodes participating in the blockchain network verify the contents of the transaction to be legitimate and contain appropriate parameters. 3. Once verified, the transaction is routed to the public mempool alongside other pending transactions. 4. Eventually, depending on the gas fee paid for the transaction relative to other transactions in the mempool, our user’s pending transaction is selected with a cluster of other pending transactions to form the next block on the blockchain. At this stage, our transaction status will read “Successful”. 5. After a certain time or block-based threshold has passed, the block itself is finalized and the transaction becomes an immutable log recorded on the blockchain, which could only be compromised in the event of a 51% attack, an extremely difficult task to perform otherwise. **1.1.2. No Mempool (Solana)** It’s important to note that some blockchains, such as Solana, do not employ a mempool, and may instead forward transactions directly to the block producer as a means of enabling high speed and throughput through continuous block production. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/276be52113f0.jpg) Let’s walk through the lifecycle of a transaction on a non-mempool blockchain: 1. User initiates and signs a transaction for an application they are using. 2. The application routes the transaction info to the Remote Procedure Call (RPC) server. 3. The RPC provider sends the transaction to the current designated block producer, and the next three producers; this is a precautionary step in the event that the current leader cannot execute the transaction in time. Solana employs a slot leader schedule which helps RPCs route the transactions easier. 4. The block producer then sends the signed transaction to consensus nodes for verification. 5. Consensus nodes vote to verify the contents of the transaction, and once completed, the transaction status is then routed back to RPC > application > user as either ‘success’ or ‘failed’. 6. Similar to mempool-based blockchains, the block itself is finalized after a certain time or block-based threshold has passed. ### 1.2  Sequential Execution Older blockchains, namely Bitcoin and Ethereum, utilize a sequential execution mechanism for transactions. Every transaction added to the blockchain invokes a change in the network’s state, and the VM is structured to only process one state change at a time for security purposes. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/d27e6419e249.jpg) This has led to significant bottlenecks for the throughput of the underlying network, as the number of transactions that can be added to the block gets limited, leading to longer wait times and unprecedented spikes in transaction costs which can render the network unusable at times. Furthermore, sequential execution models utilize hardware components rather inefficiently, and thus do not benefit from breakthroughs in computing, i.e. multiple processor cores. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/babc4fc6a186.jpg) ## Parallel Execution ### 2.0 What is Parallel Execution? Parallel computing is a key component of computer architecture whose origins can be traced back as far back as the [late 1950s](https://dl.acm.org/doi/10.1145/641276.641278), though its ideation and theory has even been traced back to [1837](https://en.wikipedia.org/wiki/Analytical_engine).  By definition, parallel computing refers to the act of utilizing multiple processing elements simultaneously to solve an operation, wherein a larger and more complex task is divided into smaller ones to be completed more efficiently than in a serial manner. Originally only implemented in high performance computing systems, parallel computing has evolved to become the dominant paradigm in computer architecture today, as demand for compute has exponentially increased in the internet era, exacerbated by the limitations of frequency scaling in prior decades. This architectural standard applies to blockchains in much the same way, only that the primary task which computers solve is the processing and execution of transactions, or the transfer of value from smart contract A to smart contract B, hence the term parallel execution. Parallel execution means that instead of processing transactions serially, a blockchain can process multiple non-conflicting transactions simultaneously. This can greatly increase the throughput of a blockchain network, making it more scalable and efficient to handle higher loads of activity and demand for blockspace. For a simpler analogy. consider the efficiency of a grocery store with multiple lanes for shoppers to check out. vs just one for everyone. ### Why is Parallel Execution important? Parallel execution in blockchains is designed to unlock efficiencies in the speed and performance of a network, especially as the network sees higher traffic and resource demand. In the context of crypto ecosystems, parallel execution means that if Bob wants to mint the latest popular NFT collection, and Alice wants to buy her favorite memecoin, the network will serve both users without compromising any quality in performance and thus user experience. While this may come across as simply an intuitive quality-of-life feature, the unlocks in network performance enabled by parallel execution gives way to the development of new and innovative use cases and applications which can leverage low-latency and high volumes, which in itself lays the groundwork for onboarding the next mass cohort of users to crypto ecosystems. ### How Does Parallel Execution Work? Although the premise of parallel execution is relatively straightforward, nuances in the designs of the underlying blockchains affect how the process of parallel execution itself plays out. The most relevant feature to designing blockchains with parallel execution is the transactions’ ability to access the state of its underlying network, including account balances, storage, and smart contracts. Parallel execution on blockchains can be categorized as either deterministic or optimistic. Deterministic parallel execution, employed by blockchains like Solana, inherently requires transactions to declare all memory dependencies upfront, i.e. which parts of the global state they wish to access upfront. While this step creates additional overhead for developers, more broadly it allows the network to sort and identify non-conflicting transactions prior to execution, creating an optimized system that is predictable and efficient. Conversely, optimistic parallel execution is structured to process all transactions in parallel, operating under the inherent assumption there are no conflicts. This enables the underlying blockchain to deliver faster transaction execution, though at the cost of potential re-execution afterward in the event of a conflict. If two conflicting transactions are found to be submitted, the system can then re-process and re-execute them either in parallel or sequentially. In order to better understand the implications of these design intricacies, it can be helpful to analyze parallel execution through the lens of teams pushing the frontier of parallel execution today. ## State of Parallel Execution Today In order to better understand the implications of these design intricacies, it can be helpful to analyze parallel execution through the lens of teams pushing the frontier of parallel execution today. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/d1e7becd233b.jpg) ### 3.1 Solana Virtual Machine (SVM) Solana was the first blockchain network to be designed around parallel execution, inspired by founder Anatoly Yakovenko’s previous experience in the telecommunications industry. Solana aims to provide a developer platform which runs as fast as physics allows, therefore the speed and efficiency unlocked by parallel computing was a simple and intuitive design choice. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/be744b180722.jpg) A critical component to enabling Solana’s fast speeds and high throughput is Sealevel, the network’s parallel smart contracts runtime environment. Unlike EVM and WASM-based environments, Sealevel employs a multi-threaded architecture, meaning it can process multiple transactions simultaneously to the extent of the validator core’s capacity. The key to enabling Solana’s parallel execution is that when a transaction is enabled, the network will assign a list of instructions for that transaction to be executed, specifically which accounts and state to access and what changes to make - this is key to determining which transactions are non-conflicting and can execute simultaneously, as well as enabling transactions which are attempting to access the same state to do so concurrently. *Consider the efficiency that labels provide to checked baggage systems at airports.* Solana also utilizes Cloudbreak, its own custom accountsDB, for storing and managing state data to enable concurrent reads and writes of transactions. Cloudbreak, optimized for parallel execution, scales horizontally to distribute and manage state data across multiple nodes. Thanks to its parallel architecture, Solana can handle a large number of transactions and still execute quickly, giving transactions near-instant finality. Solana handles between 2,000 and 10,000 transactions per second (TPS) on average today. Furthermore, use cases for the SVM are slowly but surely expanding, as teams like Eclipse are rolling out Layer 2 infrastructure which aims to take advantage of the SVM as an execution environment. ### 3.2 Parallel EVM The Parallel EVM describes a new execution environment for blockchains which aims to bring the “best of both worlds” from Solana and Ethereum’s designs, with the speed and performance of Solana, and the security and liquidity of Ethereum. By processing transactions in parallel rather than sequentially as per the traditional EVM design, parallel EVMs enable developers to build applications on a highly performant network while being able to leverage connections to EVM liquidity and developer tooling. ### 3.2.1 Sei Network Sei Network is an EVM-compatible, open source Layer 1 blockchain which hosts a variety of decentralized applications built around high performance. Sei was built around delivering fast speeds at low costs for users and developers, and parallel execution is a key component of enabling this performance and UX. Currently, Sei delivers 390ms block confirmation times and has processed over 1.9B transactions on its pacific mainnet. Originally, Sei employed a deterministic parallel execution model, wherein smart contacts declare their required state access ahead of time in order for the system to run non-conflicting transactions simultaneously. With the onset of their V2 upgrade, Sei is transitioning to an optimistic parallel model instead, meaning all transactions will be processed in parallel upon being submitted to the network (the execution stage), and then will be reviewed for conflicting information with previous transactions (the validation stage). In the event of two or more conflicting transactions, i.e. transactions attempting to access the same network state, Sei identifies this point of conflict and then re-runs the transactions either in parallel or sequentially depending on the nature of the conflict. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/dfb7b94cbf77.jpg) In order to store and maintain transaction data, Sei will also introduce SeiDB, a custom database which aims to improve upon shortcomings in v1 by optimizing for parallel execution. SeiDB aims to bring down the overhead of storing redundant data and maintaining efficient disk usage for better network performance. V2 reduces the amount of metadata needed for tracking and storage purposes, and enables a write-ahead log to aid with data recovery in the event of a crash. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/c197007708ef.jpg) Lastly, Sei has also recently announced the launch of its Parallel Stack, an open-source framework for enabling Layer 2 scaling solutions, i.e. rollups, to utilize and benefit from parallel execution. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/ca3c70e9558a.jpg) ### 3.2.2 Monad Monad is an upcoming parallel-EVM Layer 1 blockchain bringing full bytecode and RPC compatibility for Ethereum applications and infrastructure. Through a number of innovative technical implementations, Monad aims to deliver more interactive experiences than existing blockchains while maintaining lower transaction costs by optimizing for performance and portability, with 1 second block times and finality with up to 10,000 TPS. Monad  implements parallel execution and superscalar pipelining to optimize the speed and throughput of transactions. Similar to Sei v2, Monad will employ an optimistic execution model, meaning the network starts executing all incoming transactions simultaneously, and then analyzes and validates the transactions to look for conflicts and re-execute accordingly, with the end goal being that the outcome would be identical had the transactions been executed sequentially. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/6c5780009eb3.jpg) It’s important to note that in maintaining synchronicity with Ethereum, Monad orders transactions in a block in linear order, with each transaction updated sequentially. In order to maintain and access blockchain data more efficiently than the current state of Ethereum clients offers, Monad created its own custom MonadDB, built natively for blockchains. Monad DB leverages advanced Linux kernel features for efficient asynchronous disk operations, eliminating the constraints of synchronous input/output access. MonadDB offers asynchronous input/output (async I/O) access, a key feature in enabling parallel execution, wherein the system can start processing the next transaction while waiting to read state for a prior transaction. For a simple analogy, consider cooking a multi-faceted meal (spaghetti with meatballs). The steps involved are 1) preparing a sauce, 2) cooking the meatballs, and c) cooking the pasta. An efficient chef would start by boiling water for the pasta, then preparing ingredients for the sauce, then tossing the pasta in the now-boiling water, then cooking the sauce, and finally the meatballs, as opposed to doing each step one at a time, completing one task in its entirety before moving on. ### 3.3 Move Move is a programming language originally developed by the Facebook team in 2019 for its now-defunct Diem project. Move was designed to handle smart contract and transaction data in a secure manner, eliminating attack vectors native to other languages such as reentrancy attacks. The MoveVM serves as the native execution environment for Move-based blockchains, taking advantage of parallelization to deliver faster transaction execution speeds and greater overall efficiency. **3.3.1 Aptos** Aptos is a Move-based Layer 1 blockchain developed by members of the former Diem project, which implements parallel execution to deliver a high performance environment for application developers. Aptos utilizes Block-STM, a modified implementation of the Software Transactional Memory (STM) concurrency control mechanism. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/a36d7d3de298.jpg) Block-STM is a multi-threaded parallel execution engine which enables for optimistic parallel execution. Transactions are pre-ordered and strategically sequenced inside of blocks, which is key to efficiently resolving conflicts and re-executing those transactions. Research conducted by Aptos has found that up to 160K TPS can be theoretically supported using Block-STM’s parallelization. **3.3.2 Sui** Similar to Aptos, Sui is a layer 1 blockchain developed by former members of the Diem project, which utilizes the Move language. However, Sui utilizes a custom implementation of Move which changes the storage model and asset permissions from the original Diem design. In particular, this allows Sui to utilize a state storage model to represent independent transactions as objects. Each object has a unique ID within Sui’s execution environment, and in doing so, this allows the system to easily identify non-conflicting transactions and process them in parallel. ![](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/b40eafe9b0bd.jpg) Similar to Solana, Sui implements deterministic parallel execution, which requires transactions to state which accounts they need to access ahead of time. **3.3.3 Movement Labs** **What is Movement?** Movement is building a suite of developer tooling and blockchain infrastructure services for enabling developers to easily access the benefits of building on Move. Operating as an AWS-like execution-as-a-service provider for Move developers, Movement implements parallelization as a core design feature for enabling higher throughput and greater overall network efficiency. The MoveVM is a modular execution environment which enables blockchain networks to expand and adjust their transaction processing capabilities as needed to be able to support an increasing volume of transactions, bolstering their abilities to process and execute transactions in parallel. ![MoveVM Architecture](https://shoal.xyz/research/writing/parallel-execution-the-next-generation/img/4fd1bdedc869.jpg) Movement will also be launching M2, a ZK-rollup which will be interoperable with EVM and Move clients alike. M2 will inherit the Block-STM parallelization engine, and is expected to deliver tens of thousands of TPS as a result. ## Closing Thoughts ### 4.1 Challenges For Parallel Systems Today Some important questions and considerations to be pondered upon regarding the development of parallel blockchains; - What tradeoffs is the network making to enable better performance through parallel execution? Less validators securing the network enables faster verification and execution speeds, but does this compromise the security of the blockchain in that it becomes easier for validators to collude against the network? Is there a significant number of validators colocated? This is a common strategy for minimizing latency in both crypto and non-crypto systems alike, but what happens to the network in the event of that particular data center being compromised? - For optimistic parallel systems, does the process of re-executing invalid transactions create a bottleneck as the network scales? How is this efficiency being tested and evaluated? At a high level, parallel blockchains face the risk of ledger inconsistencies, i.e. double spending and changes in the order of transactions (indeed, this is the key benefit of sequential execution). Deterministic parallelization addresses this by creating an internal labeling system for transactions on the underlying blockchain. Blockchains implementing optimistic processing must ensure the mechanisms they use to validate and re-execute transactions is secure and functional, and the tradeoffs made for performance can be reasonably implemented. ### 4.2 Future Outlook / Opportunities The history of computers has taught us that parallel systems tend to be more efficient and scalable over time than sequential systems. The rise of post-Solana parallel blockchains emphasizes that this notion applies to crypto infrastructure as well. Even Vitalik has alluded to [parallelization](https://vitalik.eth.limo/general/2024/03/28/blobs.html) as a one of the potential key solutions for improving the scalability of EVM rollups recently. Broadly speaking, crypto/blockchain adoption growth calls for systems that are more optimal than what is available today, including parallel blockchains. Solana’s recent network struggles have highlighted that there is plenty of room for improvement in the development of parallel blockchains. As more teams seek to push the boundaries of the onchain frontier and onboard the next mass cohort of users and adoption to blockchain-native applications and ecosystems, parallel execution models provide an intuitive framework for building systems that can efficiently handle magnitudes of network activity at a scale which matches that of Web2 companies with ease. ## Works Cited - Dixon, C. (2024). *Read write own: Building the next era of the internet*. Random House. - AllianceDAO. (2023, April 12). The case for parallel processing chains. Medium. [https://medium.com/alliancedao/the-case-for-parallel-processing-chains-90bac38a6ba4](https://medium.com/alliancedao/the-case-for-parallel-processing-chains-90bac38a6ba4) - Solana Labs. (2020, December 3). Sealevel: Parallel processing thousands of smart contracts. Medium. [https://medium.com/solana-labs/sealevel-parallel-processing-thousands-of-smart-contracts-d814b378192](https://medium.com/solana-labs/sealevel-parallel-processing-thousands-of-smart-contracts-d814b378192) - Etherscan. (n.d.). Ethereum average gas price chart. [https://etherscan.io/chart/gasprice](https://etherscan.io/chart/gasprice) - Sei Labs. (2023, February 10). Sei V2: The first parallelized EVM. Sei Blog. [https://blog.sei.io/sei-v2-the-first-parallelized-evm/](https://blog.sei.io/sei-v2-the-first-parallelized-evm/) - Sei Labs. (n.d.). Overview. Sei Documentation. [https://www.docs.sei.io/overview](https://www.docs.sei.io/overview) - Sei Labs. (2023, January 18). SEIDB: Improving long-term storage. Sei Forum. [https://forum.sei.io/t/seidb-improving-long-term-storage/22?ref=blog.sei.io](https://forum.sei.io/t/seidb-improving-long-term-storage/22?ref=blog.sei.io) - Sei Labs. (2023, March 5). The parallel stack. Sei Blog. [https://blog.sei.io/the-parallel-stack/](https://blog.sei.io/the-parallel-stack/) - Monad Labs. (n.d.). Monad documentation. https://docs.monad.xyz/ - CoinMarketCap. (2022, August 1). What is Aptos? The ultimate guide to the Aptos ecosystem. CoinMarketCap Academy. [https://coinmarketcap.com/academy/article/what-is-aptos-the-ultimate-guide-to-the-aptos-ecosystem](https://coinmarketcap.com/academy/article/what-is-aptos-the-ultimate-guide-to-the-aptos-ecosystem) - Wang, J., Zhang, L., & Huang, Y. (2022). Efficient algorithms for parallel computing. arXiv. [https://arxiv.org/pdf/2203.06871.pdf](https://arxiv.org/pdf/2203.06871.pdf) - Movement Labs. (2023, May 10). The MoveVM: A new era of blockchain precision and safety. Medium. [https://medium.com/movementlabsxyz/the-movevm-a-new-era-of-blockchain-precision-and-safety-a1b5bd4a65ea](https://medium.com/movementlabsxyz/the-movevm-a-new-era-of-blockchain-precision-and-safety-a1b5bd4a65ea) - Buterin, V. (2024, March 28). Blobs: A new data structure for efficient blockchain storage. Vitalik’s Blog. [https://vitalik.eth.limo/general/2024/03/28/blobs.html](https://vitalik.eth.limo/general/2024/03/28/blobs.html) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* ***Disclosures.**All posts are the authors own, not the views of their employer. This post has been sponsored by the Aster Foundation. While Shoal Research has received funding for this initiative, sponsors do not influence the analytical content. At Shoal Research, we aim to ensure all content is objective and independent. Our internal review processes uphold the highest standards of integrity, and all potential conflicts of interest are disclosed and rigorously managed to maintain the credibility and impartiality of our research.* --- # Token2049 Dubai Event List by Shoal Research > Shoal Research related satellite events at Token2049 Dubai 2024 - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-04-15 - Canonical: https://shoal.xyz/research/writing/token2049-dubai-event-list-by-shoal/ - Keywords: crypto, DeFi, restaking, yield, RWA, tokenization, zero-knowledge, security, Solana, Ethereum, DePIN, gaming, Research ![](https://shoal.xyz/research/writing/token2049-dubai-event-list-by-shoal/img/496482d7a3c3.jpg) *Shoal Research is an early stage DeFi and Infra research firm. For more information, or adding related events please message [@zaddycoin](http://t.me/zaddycoin) on telegram.* ## Sunday, April 14 - [BlockVision by NORDEK](https://lu.ma/bl0fcqe7) ## Monday, April 15 - [Shard Dubai Summit: Ascend to the peak of web3 innovation](https://lu.ma/ebx5k86r?tk=ji55GE) - [Web3 Luxury Yacht VC Mixer with Lunch & Drinks](https://lu.ma/dxwfzc56?tk=hFLef3) - [Crypto Kickbacks | Token2049 Dubai](https://lu.ma/yegxfz2z) ## Tuesday, April 16 - [Polytrade RWA Unwind](https://lu.ma/indhsfm7?tk=rnuS3V) - [Solana Breakfast with Morningstar Ventures @ 37x](https://lu.ma/morningstar-solana?tk=hqODiM) - [Web3 Summit Dubai](https://lu.ma/web3summit) - [Ordinals Meetup](https://lu.ma/ordinalsmeetup?tk=LHezP0) - [L3 Summit: Dubai 2049](https://lu.ma/L3Summit-Dubai?tk=8kBI4U) - [TOKEN 2049 - Web3 Marketing Workshop & Community Mixer](https://lu.ma/kwfxlv2j?tk=ggnCUY) - [Testnet Dubai | Dev Mini Summit by Metaschool](https://lu.ma/testnet-dubai?tk=upjwDB) - [Restaking & Infra Day, Dubai](https://lu.ma/restakingday?tk=arGs5j) - [RWA Party: Assets on the Rocks](https://lu.ma/cjxo03r0?tk=3UYgSl) - [Luna PR's Yacht Week!](https://lu.ma/yachtweek) - [Venture Horizons: Investing in Tomorrow](https://lu.ma/2z0351gb) ## Wednesday, April 17 - [Open Cafe at TOKEN2049](https://lu.ma/9gumcoay?tk=egKvsK) - [Hack Seasons Dubai](https://lu.ma/zk_dubai?tk=2pBbeW) - [Builder Day Dubai - Developer Workshops + Coworking - by MetaMask & Linea](https://lu.ma/buidldaydubai?tk=sIdIYs) - [Onchain Growth Hackers Brunch | Dubai Edition](https://lu.ma/yklt7xeg?tk=7aSi1Q) - [NEWCONOMICS - VIP Lunch](https://lu.ma/NEWCONOMICSLunchDubai?tk=gKkrmc) - [Sands of Satoshi 2024](https://lu.ma/33uzvl0d?tk=C4fAeU) - [Traders Brunch Dubai: Caladan x Sandwich Trading](https://lu.ma/tradersbrunch?tk=vz4arg) - [Dubai Blockchain Week Founders & Investors brunch](https://lu.ma/dubai-founders-investors-brunch?tk=4usSDB) - [OFR Dubai | Singularity: AI X Crypto Convergence](https://lu.ma/ofr.dubai?tk=f05ckt) - [BNBeach - Dubai](https://lu.ma/bnbeach?tk=yH8Qwu) - [DevChain Roundtable by LBM (Developing & Executing Blockchain Projects)](https://lu.ma/DevChain-roundtable?tk=Mrc1WI) - [Ballers Club Dubai By Masterblox](https://lu.ma/Masterblox-ballers?tk=0WlOpw) - [Token2049 Dubai Kick Off w/ BitGo, CoinMENA, Onramp & Coincover](https://lu.ma/token2049-dubai-kickoff) - [Builder Nights - The Restaking - Presented by MetaMask, Pendle, Altlayer, Etherfi, Linea, Renzo (Keynote by EigenLayer)](https://lu.ma/buidldubai24?tk=pNSHVY) - [Meme token launch (NO JEETS)](https://lu.ma/dubaimeme?tk=fNSfXu) - [ANAGRAM X MONAD - HAPPY HOUR](https://lu.ma/anagramxmonad?tk=ZaUDS6) - [Calligraphy Digital Drinks & Canapés at 2049 Dubai](https://lu.ma/ljutwc57?tk=Hk2n7D) - [Savor & Smoke: An Exclusive Dubai Experience with GCR and GCRx](https://lu.ma/gcrdubai?tk=cGiGO5) - [Bull Run Rendezvous: Investors & Founders Exclusive | Bybit X LTP X CyantArb](https://lu.ma/Token2049Dubai_Bybit_LTP_CyantArb?tk=ssfdUR) - [DE_AI_FORUM](https://lu.ma/de_ai_forum?tk=j7xh5v) - [Night Of 2049: Token Eve](https://lu.ma/night2049?tk=kIpoar) - [Pivot x NFTFN : Dubai Web3 VIP Yacht Party](https://lu.ma/tiyqoa7q?tk=s980Jj) - [R3al World @ Token2049 Dubai](https://lu.ma/68zx260s) - [Token 2049 with Tobi & Brent](https://lu.ma/e0mn0dfp) - [DWF Labs Haus - TOKEN2049 Dubai](https://lu.ma/DWFLabsHaus-Dubai?tk=y7h49t) - [Dubai Web3 Gaming Grand Party](https://lu.ma/grandpartydubai) - [Desert Dusk Soirée w/ Timeswap, Polytrade, Lazy Games, Diamond Hands](https://lu.ma/Token2049Soiree?tk=wHTTqy) - [Crypto Cocktails with GSR x 1inch](https://lu.ma/CryptoCocktails) - [Web3 Happy Hour](https://lu.ma/web3_happyhour) - [GameSwift x Neo Tokyo x BGA Future Wave: VIP Yacht Cruise in the AI & Esports Flow](https://lu.ma/GameSwiftxNeoTokyoxBGA) - [zkCandy VC Speed Dating | Dubai](https://lu.ma/vcspeeddatingdubai) - [VCs Night with Hashed & Morningstar Ventures](https://lu.ma/hashed-morningstar) - [Modular Dubai](https://lu.ma/modulardubai) ## Thursday, April 18 - [RWA Leaders Brunch](https://lu.ma/rwa2049) - [Anagram x Superteam UAE - Builders' Summit](https://lu.ma/anagram-superteam?tk=2mQ8yj) - [Token2049 Dubai Pizza Party Hang Out w/Halborn, Sushi, Immunefi, Snowball, TrueZK](https://lu.ma/token2049hh-halborn?tk=oZg2sN) - [RWA Happy Hour at TOKEN2049](https://lu.ma/7txd0888?tk=pFe73V) - [Rare Social: Dubai Blockchain Happy Hour](https://lu.ma/ozeupvc8) - [Avalanche Happy Hour at Token2049 Dubai](https://lu.ma/AvalancheDubai?tk=jyAQYG) - [/dubai Farcaster Meet up @ Token 2049](https://lu.ma/Farcaster_Dubai?tk=HH8jIA) - [Everyday We Shufflin'](https://lu.ma/huu0wdfp?tk=VOhEnC) - [Golden Bulls and Dragon Vaults: An Exclusive Night | LTP X Pyth.Network X Gate.io X Caladan](https://lu.ma/Token2049Dubai?tk=xDwuRp) - [Liquidity Pool Party presented by Auros, Crypto.com, Solana Foundation](https://lu.ma/liquiditypoolparty?tk=nT3lQQ) - [Sands of Play: Dubai](https://lu.ma/sandsofplaydubai?tk=fUXuqk) - [Building Network States (Dubai Edition)](https://lu.ma/bnsdubai?tk=l33m8z) - [OG Mixer | Komet X Bybit Web3 X OG Club](https://lu.ma/og-founders-mixer?tk=scMiUD) - [DePIN2049](https://lu.ma/DePIN2049) - [Prom x DWF Labs: Drinks & Bites](https://lu.ma/prom-dwflabs?tk=mqT2T5) - [PolkaMix: Dubai](https://lu.ma/Networking_night?tk=osOViS) - [Deepcoin Grand Party in Token2049 Dubai 2024](https://lu.ma/uqsn9opk?tk=hgAukK) - [DYM: DeFi Yield Machine - Life Outside of Memes](https://lu.ma/q7eq3dvi) - [K-pop Party with Zircuit, Bitget, Morph, Quantstamp and Foresight Ventures featuring tripleS](https://lu.ma/KpopParty?tk=4HU2Ch) - [Zebu Live After Hours Presents Studio 49!](https://lu.ma/k147kf60?tk=fZKLuD) - [Web3 Happy Hour](https://lu.ma/MVXTOKEN2049?tk=GENFRw) - [Dubai Nightopia - Token 2049 Opening Party ft. Stephan Jolk](https://lu.ma/zw9eotn3) - [Pre-Token 2049 Brunch with 1inch.io, Trust, Cypher Capital and WalletConnect](https://lu.ma/LFG) - [M2 Cheers & Chats](https://lu.ma/yy1kb1dy/_) - [Anagram x Superteam UAE - Builders' Summit](https://lu.ma/anagram-superteam) - [NewTribe Gathering II](https://lu.ma/newtribegathering) - [Coinbase Dubai, A Private Reception](https://coinbaseadvanceddubai.splashthat.com/) - [Supercharge and Katalyze in Dubai by Superscrypt, Kaito, and J17](https://lu.ma/dubaibeach) - [Token2049 Dubai Pizza Party Hang Out w/Halborn, Sushi, Immunefi, Snowball, TrueZK](https://lu.ma/token2049hh-halborn) ## Friday, April 19 - [TRGC Infracon: AI Compute Edition @Token2049](https://lu.ma/TRGC-Infracon-AI?tk=l4YDGD) - [University of Wollongong in Dubai BACC Conference](https://lu.ma/UOWDubaiBACC?tk=0AF543) - [Token2049 Dubai Happy Hour with CertiK](https://lu.ma/ra768rl0?tk=8aYBzL) - [Nibiru Unchained - Dubai](https://lu.ma/jhyprtz6?tk=e0ONww) - [Dubai Nights with Algorand x M2 x Cypher Capital](https://lu.ma/6qmxty3e?tk=nn1F7J) - [Babylon, Particle Network, Nubit & Lorenzo: Happy Hour @ Token2049 Dubai](https://lu.ma/st4tbtg1?tk=kARmbf) - [Web3 Dubai Afterparty](https://lu.ma/web3dubaiafterparty2024?tk=b0LSJ2) - [Beyond the Hype: Exploring AI, Blockchain, and Tokenization in Dubai](https://lu.ma/s35t7ean?tk=m1sOld) - [zkCandy & zkSync Chill and Network VIP Afterparty!](https://lu.ma/zkchillparty) ## Saturday, April 20 - [The New Frontier: Web3 and AI Convergence in Dubai](https://lu.ma/web3ai?tk=YmSEs6) - [Narratives Fest - DeAI / DePIN / Next Ethereum](https://lu.ma/ywjd9s8p) - [How To DAO Dubai by RAK DAO, Bybit and New Tribe Capital](https://lu.ma/5z2nsob2?tk=lKd1SH) - [LALIGA Watch Party at TOKEN2049 | GameOn, Arbitrum, & OpenSea](https://lu.ma/gameonlaliga?tk=wSZYBl) - [Token2049 Villa Party](https://lu.ma/token2049villa?tk=bNAOlS) - [Animoca Brands x MetaMask Institutional x Cypher Capital Yacht Meet-up](https://lu.ma/yachtmeetup?tk=fv1x3i) - [PWR Panorama - Gazing into Blockchain's Future, Web3 & AI Innovation](https://lu.ma/pwr2049?tk=Cs4Ugp) - [Crypto Week Yacht](https://lu.ma/gvmfi1uh) - [Warmup Party @ Armani Privé](https://lu.ma/lngk4haq?tk=0HpHGE)yessir**Sunday, April 21** - [KatAI - Axone Event](https://lu.ma/wfupoglb?tk=ZznreM) - [VIP Mega Yacht Party @ Dubai Marina](https://lu.ma/v52dmrj6?tk=Keimh5) - [The Crypto Week After Party](https://lu.ma/2y97zxfm?tk=JhcQ4l) --- # Whales Market: Points OTC Marketplace > A comprehensive overview of the Whales Market protocol. - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-03-25 - Canonical: https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/ - Keywords: crypto, DeFi, infrastructure, Ethereum, Research ![](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/b0a1f1191122.png) ## Introduction There are numerous activities one can engage in within the crypto realm, such as staking assets, purchasing tokens and NFTs, conducting research, developing decentralized applications, and participating in airdrop farming, among others. However, the common thread that brings all stakeholders in crypto together is trading. Almost every user partakes in trading, whether it involves long or short positions on exchanges, asset swapping in liquidity pools, or the exchange of non-fungible tokens on NFT marketplaces. Interestingly, even illiquid assets are traded in the crypto space, primarily through a peer-to-peer (P2P) process. Due to the absence of a liquid market for illiquid assets, the trading of items like crypto points, airdrop allocations, and whitelists typically occurs in the over-the-counter (OTC) market. In this scenario, individuals engage in conversations and negotiate deals with one another regarding the trading process. However, a significant challenge arises in the form of trust among participants. Trust is pivotal as one must rely on the certainty that a specific user possesses the designated assets and will deliver them after the proposed deal. This introduces the possibility of malicious activities and poses a risk. What if we could establish a trustless third party that enables secure trading for both parties, providing security and preventing fraudulent activities? This is precisely what Whales Market aims to accomplish. ## Airdrops 101 As most of us know, an airdrop is the process of sending free tokens to selected wallet addresses or users who meet certain criteria (who have done certain activities during a certain period of time). But how did it all start? The first crypto airdrop occurred in March 2014 when Iceland launched Auroracoin. Each citizen received free coins, starting with 31.8 AUR and increasing to 636 coins. The purpose of these airdrops was to create a market for the token and generate awareness. However, it's important to note that sending tokens required payment for gas, which became expensive as gas prices and ETH's price rose. Then airdrops shifted to free token claims. Recipients could claim tokens for free but had to pay transaction gas. The cost of gas is usually small compared to the token value, so it's generally not an issue. However, as projects evolved, they realized giving away tokens to random users who might just sell them was detrimental. Initially, launching tokens early allowed projects to gauge interest and secure funds. But later, after significant investment, it became clear that giving away tokens to random users was not beneficial and could harm the projects. In September 2020, Uniswap made a significant impact by airdropping $UNI tokens to over 250k addresses. These addresses were eligible because they had interacted with the platform before September 1st, 2020, and were granted at least 400 $UNI tokens. The airdropped $UNI tokens provided voting power, which remains their primary utility, allowing users to vote on protocol changes and proposals. This led to the emergence of a new user group known as airdrop farmers. They would farm transactions that didn't contribute much to the protocol's value but allowed them to rank higher in airdrop rewards. For instance, if the airdrop was based on the number of transactions a wallet made, they would create numerous transactions by repeatedly moving the same amount, even if it incurred costs. In response to airdrop farming, projects have implemented more advanced strategies and mechanisms. The Optimism L2 platform introduced a two-tiered airdrop, where users had to actively participate in the protocol's governance to qualify for the second tier, which occurred nine months later. The Blur NFT marketplace implemented a multi-tier airdrop mechanism to gain market share from OpenSea. They required users who listed their NFTs on other platforms to also list them on Blur at a lower or equal price, and utilize certain protocol features like NFT collection bids. In the latest airdrop tier, users are even required to delist their NFTs from other marketplaces to receive the maximum $BLUR airdrop. ## Points 101 Projects are adopting a "points system" in which users earn points for their contributions to the community. Founders are increasingly incorporating offchain points programs into their applications, as seen in various examples such as: - Rainbow wallet rewarding Ethereum usage with points - Friend.tech basing its engagement loop on points - Blur introducing L2 Blast Points as incentives for fund bridging (with over $800 million TVL since November). This trend emerges as part of a wider exploration for product-market compatibility in the cryptocurrency industry and strategies to engage users during a downturn in the market. There are discussions among users regarding the possibility that these accumulated points will be converted into the project's token, following a trend observed in recent notable airdrops. ## Trading Illiquid Crypto Markets There are lots of things in crypto that have no decentralized exchange to trade on. Such things include whitelists, airdrop allocations before the TGE, points, P2P trading of tokens and NFTs, and so on. For a long time, trading of those things has been commonly done through social groups, private messages, and centralized platforms. However, these methods often lack security measures, which puts traders at risk of scams where fraudsters fail to deliver the tokens they promised. The primary reason for this is that these trades do not necessitate commitment from the involved parties, as the trading routes between them are isolated and predominantly rely on the trading routes between both parties. While there is currently no decentralized market for it, the existence of such a market could improve liquidity and benefit both buyers and sellers. In order to achieve this, a solution is needed to integrate a trustless system that can prevent malicious actions. ## Introducing Whales Market Whales market was made specially to address the issues described in the previous section - *make trading of illiquid assets more secure, trustless, and accessible for everyone.* Whales Market tackles this by consolidating OTC trading on a unified platform. Here, both buyers and sellers can engage in on-chain transactions that are mutually agreed upon. Funds are secured in smart contracts and are only disbursed to the involved parties upon completion of a successful transaction. This feature not only simplifies the trading process but also notably minimizes the potential for financial losses stemming from fraudulent activities. Whales Market was developed by the same team behind LootBot. This protocol was created during the summer of 2023, during the popularity of Telegram Bots. The concept was straightforward yet practical: a Telegram bot designed to streamline the majority of laborious tasks involved in airdrop farming. Leveraging the team's success with LootBot, they decided to build a more ambitious and complex product – Whales Market. ## Product Overview Whales Market supports 3 main types of the markets: Pre-Launch Market, OTC Market, Points Market. Let’s explore the details of all of them. ## Supported Markets The core system powering pre-market token trading on Whales Market relies on collateral. Sellers lock up assets as collateral, assuring buyers they'll receive the tokens once officially released by the foundation. Should a seller fail to fulfill their order, their collateral goes to the buyer as compensation. However, this system isn't without its potential drawbacks, particularly when dealing with points systems. Let's delve deeper into these risks in the following sections. ### Pre Market We have written previously [about Perpetual Pre-Launch Futures](https://www.shoal.gg/p/perpetual-pre-listings) and how perpetual futures exchanges enable traders to leverage trade assets that have not yet been launched. However, Whales Pre Market is different, in that it allows buying pre-TGE token allocations. As most of you know, that is the common thing among different private communities and some centralized platforms. These methods often fall short in terms of security, leaving traders vulnerable to scams and non-delivery of promised tokens. Whales Market transforms this process by using smart contracts, enabling on-chain transactions agreed upon by both buyers and sellers to prevent the fraud activities. ![](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/58ac0d052125.jpg) There are 2 ways to buy & sell tokens: - Create your own offer to buy or sell - Fill others’ offer to buy or sell Both sellers and buyers are required to wait for the Token Generation Event (TGE) before they are able to settle or cancel orders. When TGE happens and the tokens are released by the foundation, the settlement between buyers and sellers will countdown for 24 hours. If sellers fail to settle in time, they will lose their collateral funds. Those funds will be transferred to the buyer, if they decide to cancel the order. ![](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/84c4370e7976.jpg) ### OTC Market Traditionally, OTC Markets facilitated P2P trading of tokens and Non-Fungible Tokens (NFTs) through various informal mediums like chat rooms, social media sites, and direct messaging. While such methods are convenient, they lack stringent security measures, making traders susceptible to fraud and scams. Similar to the Pre-Launch Market, Whales Market uses smart contracts to address vulnerabilities to reduce the risk of potential losses. In order to guarantee user safety, Whales Market upholds a list of tokens approved for OTC Markets trading. This list is carefully assembled from tokens that have achieved a minimum liquidity pool of $300,000 in their largest pool on a DEX. Users can also trade tokens that are not the list, but the platform will display a warning sign, prompting users to verify their mint address before proceeding with the trade. To maintain the privacy of creators’ offers, Whales Market has implemented a new functionality. This feature allows them to share the offer access link exclusively with the individuals they are negotiating deals with. As a result, private offers are not visible on the public marketplace and can only be accessed through the unique offer link provided by the creators. ![Screenshot taken from Whales Market UI .](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/d1da37ef786d.jpg) ### Points Market Similar to OTC Market, Points Market allows secure P2P trading of points. The amount of projects using “points system” grows every day, and as most us know, with growth comes the room for speculation. Whales Market utilizes smart contracts to allow the mutually agreed on-chain transactions between buyer and seller. ![](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/4ae0704e6c57.jpg) Once the foundation releases the tokens, a 24-hour settlement countdown will begin. Following the token release, Whales Market will automatically convert points into the corresponding tokens based on the foundation's announcement. **Risks Involved** Orders for points have to be set in advance, but the final conversion ratio into tokens isn't revealed until the TGE. This can lead to situations where the seller's points end up significantly exceeding the value of the tokens they receive, potentially creating an unfavorable outcome for the seller. Currently, Whales Market allows trading points of Friend.tech. In the future, they’re planning to add these features for such protocols as MarginFi, Kamino, EigenLayer, and Rainbow. ## Tokenomics The whole ecosystem of Whales Market is centered around its native token - $WHALES. Main utility features of $WHALES token include: - **Revenue-sharing**: 60% of the fees collected is redistributed to $WHALES token stakers - **Development expenses:**20% is allocated to cover ongoing development expenses - **Buyback and Burn**: 10% is used to buy back and burn tokens, creating deflationary mechanism - **$LOOT revenue-sharing:**10% is shared to $LOOT stakers and $xLOOT holders. To ensure that emissions contribute to the growth of the protocol, token emissions are linked to specific Key Performance Indicators (KPIs) related to trading volume.  $WHALES holders have the ability to participate in voting for these KPIs. ![](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/3b3ad63a3271.png) The Whales Market team demonstrates their long-term commitment to the growth of the protocol through a cliff period of 9 months and a vesting period of 36 months allocating only 9.5% of the total supply to themselves. ## Staking Whales Market earns revenue by collecting fees from OTC markets, and 60% of these fees are distributed to $WHALES stakers. When users stake $WHALES, they are rewarded with $xWHALES, which serves two purposes: receiving a share of the revenue and acting as collateral in all OTC markets. ***The staking mechanism works as following:*** - The staking contract includes a pool that consists of two types of tokens: $WHALES and $xWHALES. - Participants stake their $WHALES tokens and receive $xWHALES tokens in return. - Holding $xWHALES tokens entitles stakers to an increasing amount of $WHALES rewards. - To achieve this, the contract continuously purchases $WHALES tokens using generated revenue, which are then added to the staking pool. - The conversion rate of $xWHALES to $WHALES increases, benefiting the stakers. This mechanism also prevents dumping of $WHALES tokens after claiming rewards, as the rewards are distributed gradually over time. ### Rewards Distribution Depending on the blockchain (EVM, SOL, etc.) and the specific market, fees are gathered in different assets. In order to simplify the process of claiming rewards, the protocol converts these collected tokens into $WHALES tokens at regular intervals. These transactions can be easily observed on the protocol's dashboard. The distributed $WHALES tokens are then evenly shared among the stakers as rewards. Stakers have the flexibility to withdraw their $xWHALES tokens at any time and convert them back into $WHALES tokens. ## Revenues ![Whales incurred daily fees.](https://shoal.xyz/research/writing/whales-market-points-otc-marketplace/img/3b10bd6f17e2.png) As we mentioned in the Tokenomics section, Whales Market earns revenue by collecting fees from their markets: Pre Market, OTC market, and Points Market. Let’s explore the fees they’re charging and which actions require a fee. In the Pre Market, certain actions such as closing an offer, settling an order, buying a token, and canceling an order are subject to fee charges. If you choose to close an offer, a platform fee of 0.5% is required. For settling an order (buying), a platform fee of 2.5% applies. When you make an offer to buy or fill another user's offer to sell, there is also a 2.5% platform fee on the total tokens purchased. If you cancel a buy token order due to the seller ghosting you, a platform fee of 2.5% will be incurred. In the OTC Market, Whales Market only charges fees for listing and selling. Whenever you create an offer, regardless of whether it is for buying or selling, a fee of 0.1% is applied and included in your overall deposit. When you fulfill a buy offer by selling tokens, a fee of 0.1% is applicable and deducted from the amount you receive. In the Points Market, users are charged a fee for closing an offer (buy or sell), settling and canceling an order, as well as buying points. If you choose to close an offer, the platform fee is 0.5%. For all other cases, the fee amount required is 2.5%. ## Valuation In order to determine a fair valuation for the Whales Market, we will conduct a comparative analysis using three key metrics: - Earnings to TVL ratio - Market Cap to TVL ratio - Staked assets to Market Cap ratio These metrics will be compared against two primary competitors: Uniswap and Blur. Uniswap is selected as the most popular decentralized exchange (DEX) currently, while Blur is chosen for its position as the most popular non-fungible token (NFT) marketplace with its own points system, which notably surpassed OpenSea. By comparing these metrics, we aim to gain insights into the relative valuation of Whales Market in relation to established players in the blockchain space. ## Earning to TVL ratio The current earnings to TVL ratio is as follows: - Whales Market: 0.02 - Blur Marketplace: 0.36 The fees have been generated since the launch of the protocols. Although Blur appears to have a much better ratio, it is worth noting that Blur is significantly older than Whales Market, which only launched at the beginning of January 2023. **However, when we examine the statistics of the past two months and compare the earnings to TVL during this period, we obtain noticeably different results:** - Whales Market: 0.02 - Blur Marketplace: 0.02 It is evident that they currently share equal ratios, indicating that they generate fee percentages at almost identical levels. The current FDV of Blur stands at $2.26 billion, while the current valuation of Whales Market is $264.33 million, implying a significant discrepancy of almost tenfold between the two. ## Market Cap to TVL ratio Now, let’s compare the Market Cap to TVL ratio among Whales Market, Blur, and Uniswap: - Whales Market – 1.35 - Uniswap – 1.13 - Blur – 5.94 As we can see, Blur has the highest ratio here, indicating that the valuation may be a little bit overrated compared to Uniswap and Whales Market. It’s important to mention that TVL in Market Cap is slightly different and is called Total Value Escrowed (TVE) in the case of Whales Market, which serves as an escrow between two parties. The mechanism in Uniswap and other DEXes is slightly different. ## Staked assets to Market Cap ratio This metric is only applicable to Blur and Whales Market. So let’s explore the current Staked assets to Market Cap ratio between those protocols: - Whales Market – 35% - Blur Marketplace – 30% Basically, what it means is Whales Market still has a lot of room for growth in terms of staked assets in the protocol, the ratios of those protocols are pretty close, but we should also remember that Whales Market is only 3 months old. ## Conclusion In conclusion, the Whales Market offers a comprehensive solution for illiquid and decentralized cryptocurrency markets. With its product overview, it provides support for various markets including OTC, pre-launch, and points market. Additionally, the tokenomics, staking options, and revenue streams ensure a sustainable and profitable ecosystem. Overall, the Whales Market presents a promising platform that addresses the challenges faced by P2P traders in the cryptocurrency market. ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All posts are the authors own, not the views of their employer. --- # Assessing the Permissionless Lending Landscape > Morpho vs Ajna vs Euler - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-03-08 - Canonical: https://shoal.xyz/research/writing/assessing-the-permissionless-lending/ - Keywords: stablecoins, crypto, DeFi, restaking, yield, security, infrastructure, Ethereum, Research ![](https://shoal.xyz/research/writing/assessing-the-permissionless-lending/img/c277be58f576.png) ## Introduction *The beginning of on-chain permissionless lending* The story of on-chain permissionless lending platforms starts with Rari Capital and its Fuse Platform. Released in the first half of 2021 after the fervor of DeFi summer, a period marked by the explosive growth of yield farming, Fuse quickly gained traction. This platform, a brainchild of Rari Capital, revolutionized the DeFi space by enabling users to create and manage their own permissionless lending pools, aligning with the burgeoning trend of yield optimization. During its rise, Rari Capital embraced the (9,9) narrative, which was popularized by Olympus DAO, a strategy aimed at leveraging OHM yields. This period of growth and community-building was further amplified by Rari Capital's merger with Fei Protocol. The merger between Rari Capital and Fei Protocol in November 2021 was centered around a specific vision: to build a comprehensive DeFi platform that integrated Rari's lending protocols with Fei's stablecoin mechanisms. However, everything came tumbling down in April of 2022 when Fuse fell victim to a reentrancy attack that led to a staggering loss of funds, estimated to be around $80 million. The incident led to intense scrutiny of Rari Capital's security practices and raised broader concerns about the vulnerability of DeFi platforms to such exploits. In the wake of this crisis, Tribe DAO, the governing body formed after the merger of Rari Capital and Fei Protocol, faced tough decisions. The pressure and challenges stemming from the hack eventually led to the shutdown of Tribe DAO and Rari Capital later in the year. This closure marked a significant moment in the DeFi space, highlighting the fragility of even the most innovative platforms in the face of security threats and the critical importance of robust, foolproof protocols in decentralized finance. **Revitalization of Permissionless Lending** In the wake of the Rari Capital hack in April 2022, and the significant Euler hack in 2023, where $200 million was compromised, the DeFi sector faced heightened skepticism, especially regarding security. Euler, known for its innovative permissionless lending protocol that allows users to lend and borrow a wide range of crypto assets, became another stark reminder of the vulnerabilities in the DeFi ecosystem. These major security breaches fueled a broader sense of pessimism across the industry, raising serious concerns about the safety and reliability of decentralized finance platforms. However, the latter half of 2023 marked a quiet resurgence in the DeFi lending sector, beginning with the launch of Ajna in mid-July. This revival continued with the announcement of Morpho Blue on October 10, 2023. What distinguished these emerging protocols in the revitalized DeFi lending landscape was their shift in narrative from purely "permissionless" to emphatically "modular." Instead of solely focusing on the unrestricted access that permissionless systems offer, platforms like Ajna and Morpho Blue began to emphasize their "modular" nature. This approach presented them as base layer technologies, upon which third-party developers could build and customize lending use cases. This pivot towards modularity highlighted the flexibility and adaptability of these platforms, encouraging innovation and specialization in lending solutions. Alongside this modular narrative, there was also a strong emphasis on security. Ajna, for instance, differentiated itself by being oracle-less, eliminating reliance on external price feeds and thereby reducing points of vulnerability. Morpho Blue introduced the concept of "permissionless risk management" delegating the responsibility to 3rd parties to pick and choose the lending markets with the most risk-adjusted return. **State of Affairs Today': DeFi Liquidity is Back** As we enter 2024, there’s a noticeable buzz within crypto at large and DeFi. This resurgence is often attributed to new mechanisms of token distribution, a theory popularized by Tushar from Multicoin. His theory is that each crypto bull market is sparked by innovative token distribution methods. In this current market, the concept of 'points' has become a significant driver, with platforms like Eigenlayer leading the charge through their restaking ecosystem. This method is not only drawing renewed interest but is also shaping the dynamics of the market. Concurrently, the diversity of on-chain asset types is expanding, which adds depth to the DeFi ecosystem. With all that said, it is imperative that we have the necessary lending systems and infrastructure in place as institutions and degens alike will seek on-chain leverage. While established protocols like Compound and Aave have facilitated billions of dollars in transactions, their limited capacity to accommodate diverse collateral types necessitates the emergence of alternative on-chain lending platforms. Over the past 1-2 years, the landscape has witnessed the rise of new lending protocols such as Morpho, Ajna, and Euler, each vying for a share of the on-chain lending market. Furthermore, we’ve witnessed the surge of NFT lending protocols like Metastreet and Blur. This essay aims to explore the narratives and functionalities of these projects, providing readers with insights into their respective differences and contributions as we look ahead. ## Morpho Protocol **Morpho’s Origins** Morpho's origin story and the decision to develop Morpho Blue are rooted in the protocol's initial success and a deep understanding of the limitations within the DeFi lending space. Launched by Paul Frambot and his team at Morpho Labs, Morpho quickly rose to prominence, becoming the third-largest lending platform on Ethereum with over $1 billion in deposited assets within a year. This impressive growth was driven by Morpho Optimizer, which operated on top of existing protocols like Compound and Aave, enhancing their interest rate model efficiency. However, Morpho's growth was eventually constrained by the design limitations of these underlying lending pools. These realizations led to a rethinking of decentralized lending from the ground up. The Morpho team, with their extensive experience, recognized the need to evolve beyond the existing model to achieve a new level of autonomy and efficiency in DeFi lending. This evolution gave birth to Morpho Blue. Morpho Blue was envisioned to address several key issues in DeFi lending: - **Trust Assumptions:** The protocol reduces trust assumptions by allowing more decentralized and dynamic risk management. This addresses the issue of numerous risk parameters that need constant monitoring and adjustment, which can be a primary cause of security breaches. - **Scalability and Efficiency:** By moving away from the DAO-style management model, Morpho Blue aims to enhance scalability and efficiency. This includes addressing capital efficiency and rate optimization issues inherent in current decentralized lending models. - **Decentralized Risk Management:**Morpho Blue focuses on permissionless risk management, enabling a more transparent and effective approach to handling risks in lending platforms. The development of Morpho Blue represents a significant shift towards building more unopinionated and trustless lending primitives in DeFi. This shift is complemented by the potential for building abstraction layers on top of these primitives, allowing for a more resilient, efficient, and open DeFi ecosystem at its core. **Morpho Blue (& MetaMorpho) - Protocol Analysis** The Morpho protocol operates on two distinct layers: Morpho Blue and MetaMorpho, each serving a unique function within the ecosystem. **Morpho Blue** is designed to allow anyone to permissionlessly deploy and manage their own lending market. A key characteristic of each Morpho Blue Market is its simplicity and specificity: it supports only one collateral asset and one loan asset, along with a defined loan-to-value (LTV) ratio and a specified oracle for price feeds. This framework ensures that each market is straightforward and focused, making it accessible for a wide range of users. Morpho Blue is also governance-minimized, featuring a concise and efficient codebase with just 650 lines of Solidity, enhancing its security and reliability. Additionally, Morpho Blue includes a fee switch, governed by $MORPHO token holders, which adds a layer of community-driven oversight to the protocol. **MetaMorpho**, on the other hand, introduces the concept of lending vaults, which are managed by third-party 'risk experts.' In this layer, lenders deposit their funds into a vault, and the vault manager is responsible for allocating this liquidity across various Morpho Blue markets. This approach allows for a more sophisticated and dynamic management of funds, leveraging the expertise of specialized managers to optimize returns and manage risks. The core innovation of MetaMorpho lies in its product standpoint and developer-friendliness. It creates a platform where third-party developers can build on top of Morpho Blue infrastructure, adding an additional layer of versatility and innovation to the Morpho ecosystem. ![](https://shoal.xyz/research/writing/assessing-the-permissionless-lending/img/c4b525c9af59.jpg) **Steakhouse Financial Case Study** Steakhouse Financial, led by Sebventures, stands as a prime example of how the Morpho Blue ecosystem can be leveraged effectively. This crypto-native financial advisory for DAOs has made significant strides in the DeFi space with its innovative approach to lending. Since January 3, Steakhouse Financial has been managing a USDC MetaMorpho vault with a TVL of $12.8M. This vault is focused on primarily stETH and wBTC. In the future, Steakhouse has expressed interest in supporting Real-World Assets (RWAs) collateral. **The Four Actors in Morpho’s Ecosystem** There are four primary factors in the Morpho Ecosystem given its current development: MetaMorpho lenders, Morpho Blue Lenders, borrowers, MetaMorpho vault managers, and Morpho governance / Morpho labs (kinda the same rn… i think) Below is an updated visual of the complete Morpho protocol architecture , annotating the actors and their objectives / thought process ![](https://shoal.xyz/research/writing/assessing-the-permissionless-lending/img/317e3638cfc3.jpg) **Morpho Growth Playbook** Morpho has distinguished itself through a blend of powerful branding and business development execution excellence. While other lending projects have come about, including Ajna, Midas, Frax Lend, and Silo Finance, Morpho has risen to the top in terms of TVL traction. The protocol, while inherently permissionless, is abstracted away with a permissioned Morpho UI. This curated user interface is a testament to the team’s commitment to maintaining a brand synonymous with trust, by selectively showcasing only the best lending markets and partners. This nuanced approach - selling the allure of a permissionless protocol while effectively gating its frontend to highly reputable entities - ensures that Morpho Blue is a beacon for quality and reliability within a DeFi space that can seem risky and unstable. Building upon the previous points, Morpho has invested a great amount of time and energy in the end user experience. Morpho has developed a clean and intuitive UI/UX, streamlining the interaction for end users and lending operators alike. This is not the case for many DeFi lending protocols that still give off a gimmicky vibe. Furthermore the development of abstraction layers such as MetaMorpho,  simplifies the appeal. Morpho Blue's nuanced strategy of balancing permissionless innovation with a permissioned, brand-centric frontend is impressive. This approach not only underlines the adaptability and flexibility of Morpho as a platform but also positions it as a leader in fostering specialized and secure lending solutions in the DeFi arena. **What has Morpho done well? What needs improvement?** - *Good:* Strong personal branding of team members such as Paul and Merlin, enhancing credibility and visibility. - *Good:* Effective ecosystem building by selling the simplicity, building abstraction layers like MetaMorpho and locking in 3rd party lending operators like Steakhouse, B Protocol, Block Analitica, and Re7 and locking in token incentives (e.g stETH) for select lending markets. - *Good:*Strong existing product and branding from its optimizer product, which provides great leverage for Morpho Blue to succeed. *Needs Improvement:*Unit economics for 3rd party risk managers needs improvement. Block Analitica at $45M AUM yields a $70k revenue, without taking into engineering costs, legal costs, and risk management costs. ## Ajna, Oracle-Free Markets **Ajna’s Origins** Ajna was founded by several ex-MakerDAO team members who recognized the scalability and risk issues in previous generation borrowing and lending protocols. Oracle dependency and Governance were both limiting factors for growth and major sources of risk. The key idea was to outsource the Oracle functionality to the lenders and liquidators themselves. The vision was to create the Uniswap of borrowing and lending, an immutable protocol that can scalably support virtually all assets, including long tail assets and NFTs. The original and innovative design came about as a result of over two years of development that included over ten code audits. The origin story of Ajna Finance is deeply intertwined with the broader desire for security and robustness within the DeFi ecosystem in 2023. This is highlighted by Dan Elizter’s article on the need for oracle-free protocols in DeFi ([read here](https://www.nascent.xyz/idea/why-defi-is-broken-and-how-to-fix-it-pt-1-oracle-free-protocols)). Elitzer, founder of Nascent VC and a prominent figure in the DeFi community, outlines the persistent security challenges plaguing DeFi and the billions lost to hacks, stressing the necessity for a fundamental rethinking of DeFi protocol design and security. The Ajna Protocol emerges as a compelling solution in this context. Launched in mid-July of 2023, Ajna’s design philosophy aligns with Elitzer’s vision of what he describes as a true DeFi primitive: a protocol that operates with zero dependencies such that it is trustless, including the absence of governance, upgradeability and oracles. This type of approach reduces the theoretical attack surface and inherent risks within a protocol. **Ajna - Protocol Analysis** Ajna stands out in the DeFi landscape for its unique approach to lending and borrowing. It is a non-custodial, permissionless system that operates without the need for oracles or governance, ensuring a high degree of decentralization and autonomy. Ajna allows for the creation of markets with a specific collateral and loan asset, simplifying the process and enhancing user accessibility. The platform supports a wide array of assets, including both fungible and non-fungible tokens (NFTs), thereby expanding the scope of collateral types beyond what is typically seen in DeFi. Ajna’s distinctive features include the facilitation of unique borrowing cases like NFT borrowing and shorting markets, without the common limitations of other platforms. **The Three Actors in Ajna’s Ecosystem** There are three primary factors in the Morpho Ecosystem given its current development: Ajna lenders, Ajna borrowers, Ajna governance / tokenholders. ![](https://shoal.xyz/research/writing/assessing-the-permissionless-lending/img/922701d97e9f.jpg) **Ajna Growth Playbook** Following a significant security bug in the latter half of 2023, Ajna took a clear hit in its security-oriented brand. Following the relaunch, the project has returned with the pursuit of complete decentralization, severing any ties with a centralized labs company. Now, they are a fully decentralized DAO and protocol. Rebooting DeFi protocols is tough, and it’s never a good look. While Ajna has experienced a setback, they’ve come back with a re-audited (5x) protocol that has two clear selling points: fully decentralized and oracle-less. Ajna’s playbook is leaning completely into the DeFi-native brand. ![](https://shoal.xyz/research/writing/assessing-the-permissionless-lending/img/511ab81b9d91.png) Now, the longer term questions are the following: - What lending use cases does Ajna uniquely unlock that allows it to be differentiated from Morpho and other competitors? - How effective will decentralized DAO coordination work out for Ajna as they try to execute their growth and BD playbook? ### Euler, Rising From The Shadows **Euler’s Origins** The Euler Protocol, emerging as a next-generation DeFi lending platform, represents a significant evolution from first-generation protocols like Compound and Aave. Established as a decentralized service, Euler addresses a critical gap in the DeFi market: the lack of support for non-mainstream tokens in lending and borrowing services. Recognizing the unmet demand for borrowing and lending long-tail crypto assets, Euler offers a permissionless platform where almost any token can be listed, as long as it is paired with WETH on Uniswap v3. The Euler Protocol distinguishes itself in the DeFi lending space through several key innovations: - It employs a unique risk assessment approach that considers both collateral and borrow factors for assets, enhancing the accuracy of risk evaluation. - Euler also integrates Uniswap v3’s decentralized TWAP oracles for asset valuation, supporting its permissionless ethos by enabling diverse asset listings. - Furthermore, the protocol introduces a novel liquidation mechanism resistant to MEV attacks and a reactive interest rate model that adjusts autonomously to market conditions. - These features, along with the implementation of sub-accounts for user convenience, position Euler as a sophisticated and adaptable platform in DeFi lending. Unfortunately, on March 13 of 2023, Euler Finance would experience one of the largest DeFi hacks ever. The March 13 flash loan attack led to losses exceeding $195 million and triggered a contagion effect, impacting numerous decentralized finance (DeFi) protocols. Beyond Euler, at least 11 other protocols suffered losses as a result of the attack. **Post-hack: Euler V2** After a silent year, Euler returned with its v2 as of February 22, 2024. Euler v2 is a modular lending platform with two primary components: Euler Vault Kit (EVK) and Ethereum Vault Connector (EVC). The EVK enables developers to create their own customized lending vaults; it can be described as a vault development kit that makes it easier to spin up vaults with Euler’s opinionated tech framework. The EVC is an interoperability protocol that enables vault creators to connect their vaults together such that they developers can more efficiently chain vaults together to pass information and interact with one another. Together, these two technologies act as base layer lending infrastructure. There will be two primary types of Euler vaults - Core: Governed lending markets similar to Euler v1, managed by the DAO - Edge: Permissionless lending markets with greater flexibility of parameters. Pooled lending experience rather than 1:1 like Morpho Blue or Ajna **Euler’s Branding Strategy** Similar to Ajna and Morpo, Euler is leaning heavily into the “modular” lending narrative, seeking to build a permissionless base layer lending protocol that 3rd parties can come and utilize. However, Euler differs significantly in its public-facing marketing and branding. Unlike Morpho, which has taken an incredibly abstracted and simplified approach, Euler leans heavily into its feature-rich technology as key selling points of the brand and technology. Some of the features that it highlights are advanced risk management tools like sub-accounts, PnL simulators, limit order types, new liquidation mechanisms (fee flow), and more. **Who is Euler’s end user and what is their end product?** Euler offers an incredibly powerful feature set and novel features that surpasses Morpho Blue (e.g sub-accounts, Fee Flow, PnL simulators, and more). The question remains: is Euler selling its lending infrastructure to 3rd party lending operators or are they spinning out their own lending markets? These are two very different opportunities with a different set of customers. If Euler is competing with Morpho to attract 3rd party lending operators, how easy is it to build abstractions on top of Euler v2? Euler misses the notion of a "pool manager" abstraction primitive equivalent to MetaMorpho, yet they seem to want to replicate what Morpho is doing with 3rd party pool operators. **Is the 1% protocol fee a good idea at launch?** At launch, Euler is enforcing a minimum 1% protocol fee derived from the vault governor. This can be a significant mental blocker, as fees are killers in a growth phase. On the other hand, Morpho has a pact where their business source license terms are connected to the fee mechanism: if the fee is charged the code becomes open source (and therefore free to fork). ## Moving Forward As the lending landscape seems to achieve maturity relative to other more novel aspects of DeFi like liquid staking and retaking, one is likely to question where the innovation lies and what might lie ahead for one of DeFi’s more established sectors. However, to argue that lending is one of the only areas in DeFi that has achieved true product market fit in a way that has (for the most part) avoided ponzi-nomics would be a fair argument to make. This is to say that the innovation will almost inevitably follow where the product-market-fit lies, so if the past can be any indicator of the future, lending in DeFi is sure to see evolution in the coming cycles. Throughout this paper, we have discussed multiple new primitives in the lending space from companies including Ajna, Morpho, and Euler. The overarching theme of all three of these new lending primitives is not only permissionless market creation but also permissionless market creation in a user-friendly, user-centric way. Yes, prior to these three protocols, one could spin up one’s own lending pool/protocol, but it was not user-friendly. In this next cycle of DeFi lending, we are keeping an eye not only on the permissionless side (which seems to be the obvious direction that protocols are trending) but also the user-experience side. Companies like Summer.fi are creating new lending experiences (and DeFi experiences at large) to allow for a simpler DeFi experience. These will likely continue to gain traction as their integrations increase, and their experience becomes simpler than going directly to the frontends hosted by the creators of various lending protocols. As the focused on intent-based protocols rise, intent-based lending or borrowing (in a similar way to how Morpho aggregates between Aave and Compound) could prove to be another future primitive in lending: just input what you want to borrow, and this new primitive will find the best, risk-adjusted opportunity. In a similar vein, creating a market in a permissionless manner is sure to become simpler as well. Currently, Morpho is engaging with three sophisticated parties (B Protocol, Block Analitica, and Steakhouse Finance) to operate their new permissionless markets, but soon this, too, like the lending experience itself, which is already permissionless, will become more user-friendly for any user to accomplish. This ability for any user to create a market will allow for a Cambrian explosion of innovation in lending with everything from new asset types as collateral (assets like LRTs, RWAs, etc) to new structured products focused on various yield opportunities. Many of these markets will surely fail, but the robust nature of the underlying protocols will eliminate cross-contamination, allowing the market to determine winning and losing markets. ## Sources - [https://docs.morpho.org/](https://docs.morpho.org/) - [https://faqs.ajna.finance/getting-started/welcome](https://faqs.ajna.finance/getting-started/welcome) - [https://docs.euler.finance/](https://docs.euler.finance/) ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure -***All reports are the authors own, not the views of their employer. --- # Value Accrual in the Modular Stack > Unpacking where value might accrue in a modular blockchain future. - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2024-03-04 - Canonical: https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/ - Keywords: crypto, MEV, infrastructure, Solana, Ethereum, Bitcoin, data, Infrastructure ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/6548ea511120.jpg) ### Introduction [Modular blockchains](https://usa.visa.com/solutions/crypto/monolithic-vs-modular-blockchain.html) have been all the rave, but one often overlooked aspect of them is that they fragment value. In a world where we have one monolithic blockchain, all value accrues to this blockchain’s ecosystem — but that’s not the case with modular blockchains. This is due to the inherent design of these modular blockchains. Modularity as it relates to core blockchain components (data availability and consensus; why there’s a grouping of these two will be touched upon later in this post; execution, and settlement) is different layers specialize (do what they’re best at), and the best layers for data availability and consensus, settlement, and execution are coupled into one blockchain, which when presented to the end user, allows them to get a better product at a lower price. Elaborating on this, the modular stack’s main benefit materializes with users being able to access cheaper blockspace and better blockspace (better in the sense that this specialization allows for total blockspace to expand exponentially; more on this below; as more blockchains proliferate, unlocking applications that we haven’t even thought of yet — much like how broadband unlocked social media for us), as well as better security guarantees. Developers of applications also need to worry less about the ideal stack for them; they can just plug and play, subsequently deploying their app. So when the functions of all these core components are carried out by different blockchains, where exactly does value accrue? ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/b0af664b4884.jpg) But before getting to that, let’s get a little deeper into modular blockchains. One reason the modular blockchain narrative is going to be instrumental for the paradigm shift into blockchain technology and Web 3.0, in general, is that it allows us to scale bandwidth without compromising on the whole reasons blockchains are so interesting — their properties of censorship resistance, liveness, and credible neutrality. ### Scalability with Modular Blockchains ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/2d01702f68f6.jpg) In essence, with modular blockchains, we can try to make the best trade-offs on the blockchain trilemma (as seen above) by scaling in layers. Take Ethereum as an example. With modular blockchains, Ethereum can be used as a settlement layer as it has the most amount of validators and the most geographically distributed set of validators (as well as a lot of solo stakers and overall less cloud concentration, see [here](https://twitter.com/drjasper_eth/status/1749973532753186939)), as well as being secured by, objectively, the best crypto money after bitcoin, Ether. But, effectively, Ethereum is well suited to be a settlement layer, which would make it a place to have the [canonical bridge](https://www.coinbase.com/institutional/research-insights/research/market-intelligence/blockchain-bridges-navigating-a-fragmented-universe), as well as have dispute resolution (like for fraud/fault proofs). Now, with regard to scalability, we do this on layers built on top of Ethereum, much like we do in TradFi (for example, Stripe or something like PayPal is built on top of many financial layers, and usually banks, say every week or so, settle up on the base layer using [Fedwire](https://en.wikipedia.org/wiki/Fedwire), i.e., the Federal Reserve settlement system) — Nic Carter, in [this](https://www.youtube.com/watch?v=mDyBbGCiBUU) episode with Lex Fridman, breaks it down well (it is worth noting that TradFi is at an advantage since TradFi utilizes centralized databases to record transfers, etc., while blockchains are distributed ledgers that require cooperation of thousands of nodes to append and verify). This takes the form of rollups (and other scaling solutions, rollups being the predominant one), which solely specialize in execution (execution is basically just running code in an execution environment, which takes the form of the [EVM](https://ethereum.org/developers/docs/evm) for Ethereum and Ethereum rollups), and can hence make some trade-offs when it comes to decentralization and security (this is also another post in and of itself). Rollups also need data availability (primer [here](https://youtu.be/dwEv77qrQeE)) and, by extension, consensus in order to function, and while those can be done by Ethereum, it can be outsourced (tradeoffs here, too) also to blockchains like Celestia, which specialize in it (this [video](http://What is Celestia ($TIA)? Unpacking Modular Blockchains).) gives you a high-level overview of Celestia) A nice example of a project embracing modularity is[Eclipse](https://twitter.com/EclipseFND), which uses Ethereum as a settlement layer and Celestia as a DA+consensus layer and does execution by itself using the[SVM](https://squads.so/blog/solana-svm-sealevel-virtual-machine) (Solana virtual machine) as its execution environment. The SVM is creating a lot of buzz right now for being one of the only multithreaded virtual machines, allowing for[parallelization](https://medium.com/solana-labs/sealevel-parallel-processing-thousands-of-smart-contracts-d814b378192) (basically transactions to be processed in parallel to each other), unlike the Ethereum virtual machine, which is single-threaded; hence, sequential transactions are the norm and parallelization is not possible. ### Modular or Monolithic? Let me caveat all this by saying that Ethereum in and of itself *is not*a modular blockchain, in the sense that it can do everything (data availability, consensus, execution, and settlement) by itself, but it can be used by other blockchains and layers of the modular stack (for example, execution layers like rollups) for functions like settlement, which then makes Ethereum a component of *another project’s* modular stack. This is where this meme from[Jon Charb](https://twitter.com/jon_charb), who has done some amazing writing on[Ethereum’s roadmap](https://members.delphidigital.io/reports/the-hitchhikers-guide-to-ethereum/#mev-boost) and[Ethereum rollups](https://substack.com/@joncharbonneau), comes from. The way this meme can be understood is that everything is a modular blockchain, and everything is a monolithic blockchain (doing all the functions on the base layer, like Solana), depending on how you look at it. For example, if I built a rollup on Solana, is Solana itself a monolithic blockchain or a modular one? Likewise, for Ethereum. Even Celestia can do execution and settlement too, but if it’s only utilized for data availability and consensus, then it's a modular blockchain — you get the point. ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/04c80f90b895.jpg) By embracing modular blockchains, you can have different blockchains that specialize in what they do to fulfill the requirements to have an “optimized” blockchain, as I’ve elucidated above. But that begs the question, **which one of these layers (data availability/DA for short, consensus, settlement, execution) will capture the most amount of value (have the most value accrual)?** This post was provoked after discovering this [Tweet](https://twitter.com/_10delta_/status/1730627749746794500) ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/07e33cceabd0.jpg) and these are the conclusions and frameworks that I have drawn from it (*spoiler alert -* *I disagree with the Tweet*). **To formalize my thinking more concisely:** 1) For a DA layer to work, you need some kind of ordering on that layer (hence, DA layers come with their own consensus, i.e., ordering protocols), so in this modular stack, consensus and DA are not two separate things — just imagine using data available on one chain in order to create proofs but this data (because it's on a blockchain) is ordered in some other way by another chain — it’s just a mess. 2) Execution layers like Arbitrum have pricing (discrimination) power, whilst DA layers like Celestia do not. This is because Celestia provides a homogeneous service (data availability), while Arbitrum (and other rollups like Optimism; I’m just taking Arbitrum as a main example) provides an execution environment for some of the best crypto apps not found elsewhere — this in itself is the reason why Arbitrum makes a significant amount of revenue (somethings hundreds of thousands of dollars a day) while Celestia makes negligible fees, less than $100 per day at the time of writing, as seen below (but this is also a function of Celestia’s nascency). Arbitrum is also closer to the end user due to the monopoly on sequencing they have (the foundation runs the only sequencer), and while this will change in the future (like for example with the adoption of [shared sequencing](https://www.halborn.com/blog/post/what-is-shared-sequencing-and-what-are-its-advantages)), the Arbitrum protocol (sequencer, builder, searcher) will still be the only ones to receive user fees, and most importantly, MEV and some part of the fees will trickle down to DA layer as the rollup/execution environment will still write the data to Celestia, etc.! And remember, if DA layers captured most of the value, then rollups today would be charging lower fees to users than cost to post/write data to the DA layer (i.e., operating at a loss, which is not the case today). *Anatoly Yakovenko (the founder of Solana) [explains](https://twitter.com/lightspeedpodhq/status/1754960077361234171) this phenomena in-depth on the Lightspeed podcast.* ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/7975e3fb7b3c.jpg) ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/feb0611ac546.png) 3) Settlement layers are more valuable than DA+consensus layers (and I’d argue execution layers) simply because of the fact that the settlement layer will be secured by the most money/money-like crypto asset, as in the case of the most credibly neutral settlement layer today, Ethereum, being secured by[$ETH](https://twitter.com/search?q=%24ETH&src=cashtag_click). DA+consensus layers will inevitably have more activity/volume flowing through it relative to the settlement layer (which will only be used for bridging and dispute resolution, so occasionally, block headers will be posted to it from the DA+consensus layer), but the settlement layer’s asset will still be more valuable albeit the settlement layer “doing less.” Just look at[$TRX](https://twitter.com/search?q=%24TRX&src=cashtag_click) vs.[$ETH](https://twitter.com/search?q=%24ETH&src=cashtag_click); the former’s blockchain does more volume and burns more of its native token than Ethereum has volume and burns its native token, yet its valued magnitudes less than[$ETH](https://twitter.com/search?q=%24ETH&src=cashtag_click) — what gives? Exactly. [Monetary premiums](https://www.youtube.com/watch?v=PQ2wj8dnpqo). Simply put, the monetary premium is a multiple an asset trades at relative to its fundamentals/fundamental utility due to its “moneyness.” Gold is a good example, wherein it's really not so used in the economy for production processes, and yes, it also looks good, but most of its value comes from its hard money trait — case in point. H/T to [Polynya](https://polynya.mirror.xyz/) for this point, who puts it better than I do, as seen below. ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/5d04b74f2ee3.jpg) **So where does that leave us?** This is what I think: t**he most valuable part of the stack is settlement, then execution, and then DA+consensus**, for all the reasons mentioned above (and why I’m not delineating between DA and consensus). My argument can be summed up as follows: settlement layer is the most valuable because of monetary premiums, and execution is much more valuable than DA+consensus because the latter provides a homogenous service where competition is fierce, and costs (and hence revenue for the DA+consensus layer) will trend to 0 (slightly unrelated, but [this talk by Peter Thiel](https://youtu.be/3Fx5Q8xGU8k)is great and talks about why these sorts of businesses don’t make sense to pursue), whilst the former (execution) can build network effects at a much greater rate and solidify them with mass liquidity! They’re also much closer to the users and do not compete on fees! Let me explain this point a little more. Right now, rollups like Optimism and Arbitrum pay more than 90% of their costs (which are actually paid by users) for DA costs (this [Bell Curve episode](https://youtu.be/iFMZp5ftnw8) expands on what I’m saying), and want to minimize this. So they might switch to Celestia for DA (and hence consensus), and hence lower the cost (and therefore their revenue) drastically (right now, data on Celestia costs pennies for rollups; if Arbitrum wrote as much data as it did today to Ethereum to Celestia, it would only pay a few thousand dollars — [Dan Smith](https://twitter.com/smyyguy) has done good research on this). But users don’t care about small fee increments between rollups! I don’t care if I’m paying $0.01 for a swap on rollup A when I could be paying $0.007 for a swap on rollup B, simply because I don’t swap that much, and bridging my assets is a hurdle and entails security risks! But for a rollup, which is, after all, a business posting thousands of megabytes of data to the DA layer, these “increments” in cost matter a lot because they add up. Basically, rollups are price elastic, like very price elastic. But rollup users aren’t, to a large degree. ### Conclusion From fat protocols to fat applications, modeling value accrual in the blockchain landscape is not a new endeavor. The advent of modularity introduces new components to the public blockchain landscape, and thus new economic and value dynamics as well. Modular blockchains represent a paradigm shift in the blockchain stack - from building a complete integrated network that can serve all 4 blockchain functions on the base layer, to building networks which use specialized layers for fulfilling these functions as optimally as possible. To reiterate, I believe that the **settlement layer** is the most valuable component of the stack, underpinned by the monetary premiums associated with the underlying asset. **execution** layers follow closely behind. In contrast though, **DA+consensus layers,** despite providing essential functions, face growing competition and diminishing revenue potential due to their semblance to commodities. In short, the order of value accrual in the modular stack: **Settlement** > **Execution** > **DA + Consensus** ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All reports are the authors own, not the views of their employer. --- # Berachain: Building Sticky Liquidity > A case study in Meme-to-Product strategy - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2024-02-29 - Canonical: https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/ - Keywords: stablecoins, crypto, DeFi, security, infrastructure, Ethereum ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/974fecdeefbc.jpg) *A special thanks to [Bera Rodman](https://x.com/berarodman?s=21&t=txFAbiSPTdLLDlAYj9X_AA) of Kodiak Finance and [0xRaito](https://x.com/0xraito_?s=21&t=txFAbiSPTdLLDlAYj9X_AA) of Infrared Finance for their feedback*🐻 ⛓️ ## Key Takeaways - Berachain offers a novel consensus mechanism that optimizes liquidity performance while remaining EVM-compatible. - Proof of Liquidity builds on top of the classic Proof of Stake mechanism to address issues typically associated with PoS Networks: stake centralization, limited opportunities to enhance chain security, and minimal incentives for validators. - The anonymous developer team behind Berachain has successfully raised $420 million at its latest valuation. Investors include Polychain, Shima Capital, dao5, Hack VC, Robot Ventures, Tribe Capital, and GoldenTree Asset Management. - Berachain utilizes the Polaris EVM, specifically designed by the team to easily separate the EVM runtime layer to develop stateful precompiles and custom modules that can be used to create more efficient smart contracts. - The Berachain Tri-Token Model consists of three tokens: $BERA for gas, $BGT for governance, and native stablecoin $HONEY. - On January 11, 2023, Berachain announced its public testnet "Artio" , which managed to attract over 300k users and facilitated over 1M transactions within the first 48 hours of launching Artio. Currently, Infrared, Kodiak, and Beradrome stand as the foundational protocols on Berachain. ## Introduction In the realm of crypto, we encounter several distinct groups: developers, investors, innovators, influencers, degens, and more. The primary point of contention has always revolved around whether individuals are drawn to technology and innovations or to memes and speculation. However, now both groups can coexist and find value within the Berachain Blockchain. On one hand, Berachain offers a novel consensus mechanism that optimizes liquidity performance while remaining EVM-compatible. This is achieved through the [Polaris modular EVM](https://docs.berachain.com/learn/what-is-polaris-evm) framework, providing the execution environment for smart contracts on Berachain. On the other hand, the project's anonymous developer team, creators of a bear-themed project, has successfully raised $420 million at its latest valuation. This, in itself, is an exciting feat fueled by memetic appeal. While most memes merely serve as fodder for speculation, Berachain strives to bridge the gap between hype and substance, offering the best of both worlds: memes and technology. In this article, we will delve deeper into the Berachain Ecosystem, exploring the unique culture it has fostered, its history, and the technology powering this innovative narrative. ## Chain Ethos It is no secret that the Berachain community is one of the most recognizable and enthusiastic among all communities. You won't find as many people on Twitter being avid fans of Bera, its updates, memes, and more. But how did it become this way? The answer lies in the concept of a cult. In medieval times, cults played crucial roles in power struggles. Originally, "cult" referred to those who glorified a saint, but now it signifies ancient or primitive religious practices. There's a narrative suggesting that cults thrive in bear markets. The Link (Chainlink) marines, with their frog pfps, memes, and low entry barriers, exemplify this. In the Berachain ecosystem, cult dynamics extend beyond JPEG prices, contributing to its growth. Core contributors of Bera drive collaborative intelligence, while the larger community contributes vital collective intelligence through ideas, comments, memes, and unique creativity. This fusion historically makes open source communities vibrant. All cult (community) members benefit from the success of the cult; moreover, they are all a financial part of the cult. The key thing is that cultists don't have a single portrait—whether you are the smartest developer in the world or a GM poster, you're still a part of the cult. Because Bera drives the memetic culture, everything not related to the technology is considered a meme. So even if FUD starts, Bera can still benefit from that. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/c1618fd81710.jpg) Despite debates over technical merit, the crypto space tends to favor meme coins. BERA, a coin with real use cases and various benefits, enters this landscape with a distinctive presence. Labeling Berachain merely as a meme with a cult following would significantly underestimate its significance. Consider the narratives that Crypto Twitter likes – well, Berachain has them all. Now, let's delve into the various technical innovations taking place within the Berachain ecosystem. ## Technology behind Berachain Berachain stands as a high-performance blockchain compatible with the Ethereum Virtual Machine (EVM), employing the innovative Proof-of-Liquidity consensus mechanism. This novel approach in consensus aims to align network incentives, fostering synergy between Berachain validators and the ecosystem of projects. The technological foundation of Berachain is established on Polaris, a cutting-edge blockchain framework designed for constructing EVM-compatible chains, leveraging the CometBFT consensus engine. Berachain is built on top of the Cosmos-SDK, which encompasses identical tooling and operations. Moreover, it incorporates additional functionalities embedded within the chain, specifically tailored to optimize for proof-of-liquidity. Furthermore, Berachain utilizes Polaris EVM, which was specifically designed by the team themselves to easily separate the EVM runtime layer to develop stateful precompiles and custom modules that can be used to create more efficient smart contracts. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/7d818fa6c4f3.png) ## Precompiles Precompiles, also known as precompiled contracts, constitute a distinctive class of smart contracts with functionalities directly integrated into the EVM, rather than executing as bytecode. Each precompile is assigned a specific address, and the associated gas fees for executing these contracts are predetermined. In the context of Berachain, this mechanism is primarily employed to facilitate enhanced functionality on the chain, enabling direct interaction with various Cosmos modules that would otherwise be inaccessible outside the EVM. Berachain's precompiles incorporate certain EVM precompile contracts from Polaris, with some additional ones to enhance functionality further. ## Proof-of-Liquidity The economic model of Berachain represents an innovative approach to blockchain governance, seeking to address the pivotal challenges encountered by decentralized networks. This model centers around three objectives: - Liquidity Building - Stake Decentralization - Aligning protocols and validators Proof of Liquidity builds on top of the classic Proof of Stake mechanism to address the problems usually associated with PoS Networks: stake centralization, almost no opportunity to improve the security of the chain, and little incentives for validators. Let's walk through it. Users can earn BGT, the Bera Governance Token used for Proof of Liquidity delegation, by supplying liquidity to the BEX liquidity pools. Subsequently, users delegate their BGT to validators. With block production determined by the proportionate weight of BGT delegated to them, validators generate rewards for both delegators and themselves from the chain. Furthermore, validators participate in voting on future BGT inflation across various liquidity pools, and any bribes are distributed from validators to their delegators (if created by the validator). ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/53777fe3084a.jpg) From the chart above and the architecture of Berachain, we can describe how PoL solves the problems of PoS blockchains. Proof of Liquidity tackles the initial challenge of Proof of Stake through two key mechanisms: - Separating the delegation token (BGT) from the chain's gas token (BERA). - Restricting the acquisition of new BGT to provide liquidity to the BEX. This implies that the staking token is distinct from the token utilized for various on-chain activities. Moreover, the exclusive method for earning new governance tokens involves contributing to liquidity, thereby incentivizing additional liquidity provision. Proof of Liquidity effectively addresses the second issue associated with Proof of Stake by distributing newly minted BGT to liquidity providers. Unlike traditional Proof of Stake networks where stakers directly receive the new stake, Proof of Liquidity allocates it to separate market participants engaged in common on-chain actions. This results in a more equitable distribution of token inflation. Lastly, Proof of Liquidity encourages protocols and validators to collaborate. This collaboration is incentivized to have validators promote a protocol's LP pool through BGT and enable protocols to assist validators in accumulating BGT stake through bribes. ## Tri-token Model The Berachain Token Model consists of 3 tokens: $BERA, $BGT, $HONEY. - BERA: native token of Berachain a.k.a. Gas token - BGT: governance token - HONEY: native stablecoin While $BERA and $HONEY serve rather intuitive roles, BGT is not nearly as straightforward. Why is there a need separate tokens for gas and governance after all? ## BGT Management BGT is non-transferrable and can only be acquired through three ways: - Providing liquidity to the native BEX (Berachain DEX) for an LP pair that receives BGT emissions - Borrowing HONEY on Bend (Berachain Lending) - Providing HONEY in the bHONEY vault for Berps (Berachain Perps) Upon obtaining BGT, users proceed to delegate it to validators within the network. The stake weight of a validator's BGT is instrumental in determining two key aspects: - The proportion of blocks a validator is responsible for producing among all validators - The percentage of future BGT emissions that they can influence through their voting ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/83a8fee3c37c.jpg) When BGT is delegated to a validator, it becomes eligible for initiating and voting on governance proposals. These proposals may include decisions on the allocation of BGT emissions to specific LP pools. Delegating BGT also triggers the commencement of various rewards from the network. Additionally, BGT has the option to be burned at a 1:1 ratio for BERA. It's essential to note that this process is unidirectional, and ***BERA cannot be converted back into BGT***. The amount of BGT inflation a validator has control over is determined by the amount of BGT delegated to them. Let's consider a scenario where you function as a validator with 10% of the entire staked BGT delegated to you. With a 10% stake of BGT assigned to you, you effectively manage influence over the direction of 10% of forthcoming BGT inflation. Specifically, this BGT inflation is directed toward the native BEX liquidity pools, allowing you to determine which LP pools are incentivized for users to deposit tokens. This typically results in increased liquidity within those pools. ## Protocol Rewards Proof of Liquidity produces rewards for holders of BGT. These rewards stem from diverse on-chain activities and are allocated to BGT holders in accordance with the amount of BGT they have delegated. There are three types of rewards: BGT Inflation, Block Captured Value, and Gas Fees. New BGT is generated in every block, determined by Berachain's inflation rate. These newly created BGT units are allocated to the liquidity providers in specific BEX pools. The distribution is based on the total amount of new BGT emissions voted upon by validators during the current epoch. Block Captured Value is the fees from Berachain's native DApps, namely BEX, Honey, and Perps. Transactions within each of these DApps may trigger fees, which are designated as the Block Captured Value (BCV). Whenever a validator incorporates a transaction in their block that incurs a fee, they receive that fee as a reward. Validators receive a percentage of the BCV as a commission, and the remaining portion is distributed to BGT delegators. ## History and Fundraising The story of Berachain's origins is quite unique and involves a journey from meme-fueled NFTs to potentially one of the most unique Layer 1s. It all began with an [NFT collection called BongBears,](https://opensea.io/collection/bongbears) launched in August 2021 by three pseudonymous co-founders: Dev Bear, Papa Bear, and Smokey the Bera. The Bong Bears mint on August 27th, 2021, featured 100 Beras, priced at 0.069 ETH each. The mint process was unique, allowing buyers to view and choose specific bears on OpenSea before purchase. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/0d83c3e07791.jpg) During that period, the team drew inspiration from the emerging rebasing protocol, OlympusDAO, which was quickly gaining popularity in the crypto community. Taking notes from OlympusDAO, Bong Bears pioneered the creation of a unique collection of rebasing NFTs, paving the way for subsequent collections. These "zooted" cartoon bears quickly gained traction in the crypto community. The BongBears project wasn't just about art; it served as the first stage in a series of bear-themed NFT collections, including Bond Bears, Boo Bears, Baby Bears, Band Bears, and Bit Bears. Each iteration is built upon the previous one. - On October 16th, 2021, OG Bong Bear holders received an airdrop of a rebasing NFT, the Bond Bear, making Bong Bears the first rebasing NFTs ever. - On October 29, 2021, The Boo Bears rebase brought 271 festive bears celebrating Halloween in style. Notably, some bears featured costumes representing popular protocols like TempleDAO and Rome. - The Baby Bears collection, dropping on December 16, 2021, just in time for the holidays, introduced 571 babies. Many featured Christmas and holiday themes, adding to the festive spirit. However, a hidden twist awaited – each bera from previous collections had a corresponding baby version, creating a quest for owners to reunite "families." - The Band Bears, a delightful collection of 1,175 beras released on April 20, 2022. Each musical bera was styled after a musician, providing a compelling incentive for users to trade for beras that suited their taste. Wild OTC trades, like Johnny Cash for Bob Dylan or Future for George Michael, became common. Both OG and baby versions were available for each artist, allowing collectors to pursue both variants. - The next rebera, the stealth drop of 2,355 Bit Bears by Berachain on August 24, 2022, surprised the community. This batch featured a distinct art style, swapping Papa Bear's designs for pixelated little beras by PixelBera. ![Source](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/4fecbfa3b529.jpg) Few NFT projects venture into L1, seed an ecosystem with a dedicated community, and achieve this without marketing expenses.It’s hard to  imagine that an anonymous team starting from an NFT collection at the end of 2021 would raise a round with an incredible valuation of $420M 2 years later,  led by one of the top funds in the industry in Polychain. Other investors included Shima Capital, dao5, Hack VC, Robot Ventures, Tribe Capital, GoldenTree Asset Management, and others. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/e4b693c959bd.jpg) Some of the most notable angels include Mustafa Al-Bassam (co-founder of Celestia), Zaki Manian (co-founder of Tendermint), Georgios Vlachos (co-founder of Axelar), and others. ## Ecosystem Berachain is a relatively new entrant in the blockchain world, and, of course, it cannot be directly compared to well-established ecosystems like Ethereum or Layer 2 Protocols. However, some of its projects play a foundational role in ensuring the proper implementation of the Proof-of-Liquidity Consensus Mechanism. Let's explore three of the most promising ones. ## Infrared [Infrared](https://infrared.finance/) is a liquid staking solution built on top of  Proof-of-Liquidity within the Berachain ecosystem. The user experience enabled by Infrared stands out by introducing BGT liquidity, simplifying the bribe and validator layer, and streamlining the distribution of BGT. Infrared makes accessing the Proof-of-Liquidity (PoL) ecosystem easy and open for everyone. With a focus on user-friendliness, it provides a straightforward platform for liquidity providers to earn iBGT — Infrared’s liquid version of BGT. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/690eaa31cc13.jpg) Liquidity providers on Berachain native DApps and other BGT-eligible venues can earn trading fees, native emissions, and claim liquid iBGT . Infrared has no deposit or withdrawal fees and a minimal performance fee, distributed among $IRED holders. Through iBGT, Infrared aims to pioneer use cases for BGT that previously weren’t possible on Berachain. They're Supported by the Berachain Foundation and the Build-a-Bera incubator program, aiming to become the leading network of validators. ## Kodiak Kodiak is a liquidity hub on Berachain that brings concentrated liquidity and automated liquidity management to the ecosystem. It is suitable for both traders and LPs. To have a better understanding of Kodiak, it's essential to know that its architecture allows vertical integration of different DEX Layers. Let's explore all of them. ![Source](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/089c6d91c71f.jpg) - Kodiak DEX, a decentralized exchange, offers users a non-custodial and highly capital-efficient trading and liquidity provision experience utilizing both concentrated and full-range AMMs. - Kodiak Islands, automated concentrated liquidity strategy vaults, are primarily used to attract liquidity in the Berachain Ecosystem. Kodiak Islands automate LP strategies with concentrated liquidity provision. User deposits create a concentrated liquidity range that automatically rebalances to stay 'in-range' with price movements. Kodiak Island LP positions qualify for PoL BGT rewards and use BEX liquidity for rebalancing. - Sweetened Islands, an Integrated Incentive Layer, leverages Berachain's Proof of Liquidity (PoL) mechanism to provide sustainable incentives for liquidity on Kodiak Islands. - Panda Factory, the No-Code Token Deployer Factory, streamlines the permissionless creation of new tokens, such as memecoins, and their initial liquidity on the Kodiak full-range AMM. This is particularly suitable for highly volatile assets with yet-to-be-discovered price characteristics. Moreover, Kodiak is the only DEX supported by Berachain's Build-a-Bera program. Working closely with the Berachain Foundation, Kodiak Islands are compatible with Berachain’s Proof-of-Liquidity, ensuring a flow of BGT as PoL matures. ## Beradrome Beradrome serves as an ecosystem incentive coordinator for Berachain, providing a unique approach to yield farming, token management, and on-chain governance. The platform introduces a tri-token structure: BERO, hiBERO, and oBERO, each offering users distinct advantages. The supply of BERO tokens is algorithmically controlled through a bonding curve mechanism, ensuring stability and market-driven liquidity. Beradrome draws inspiration from the Solidly system in its approaches to liquidity provision, rewards, and token emissions. Solidly focuses on its AMM LP tokens, deriving revenue mainly from swap fees and incentivizing veSOLID holders who vote for specific gauges to earn those fees. In contrast, Beradrome, an inclusive version of Solidly, supports any yield-bearing asset, allowing for diverse revenue streams like token emissions, swap fees, interest, or game revenue. Beradrome's main features include: - Bonding curve mechanism - Call option emissions - Token-owned Liquidity - Single-sided liquidity provisions (eliminating impermanent loss) - Deep liquidity with low slippage - Risk-free borrowing against hiBERO Beradrome also created an NFT collection called "Tour de Berance." It is a collection of 6,900 distinctive Beras on bikes racing for liquidity on Arbitrum. ![Source](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/8703f282e4c8.png) The Tour de Berance NFTs will provide exclusive functionality on Beradrome within the Berachain ecosystem, such as: - Securing more hiBERO allocation through NFT ownership - Privileged entry to events within the Berachain ecosystem - An NFT rebase once Berachain goes live - Priority access to token sales on the Berage launchpad through whitelist inclusion - Access to the upcoming Beradrome video game ## Testnet Launch On January 11, 2023, Berachain announced that its public testnet, "Artio," is now live. Developers and users can interact with the faucet to receive $BERA tokens while engaging with the network and its applications. Network participants can utilize the AMM DEX, stablecoin, perpetuals exchange, and money market. Currently, there are mainly 5 types of activities you can do on Artio Testnet: - Swap tokens on [BEX](https://artio.bex.berachain.com/) - Mint $HONEY, Berachain’s native stablecoin on [Honey](https://artio.honey.berachain.com/) - Lend or borrow tokens on [BEND](https://artio.bend.berachain.com/) - Trade perpetuals on [BERPS](https://artio.berps.berachain.com/) - Delegate $BGT to [BGT Station](https://artio.station.berachain.com/) Berachain managed to attract 300k+ users and 1M+ transactions within the first 48 hours of launching the testnet. ![](https://shoal.xyz/research/writing/berachain-building-sticky-liquidity/img/d7f036a5f560.png) ## Conclusion In this article, we delved deep into Berachain, beginning with the technology behind it and concluding with one of the most recognizable communities in crypto. Who could have imagined that the NFT collection of Bong Bears would essentially lead to the creation of Layer 1 with a novel consensus mechanism, raising a round at a $420M valuation? Currently, we are witnessing a multitude of protocols beginning development on Berachain, along with impressive statistics from the testnet launch. Berachain accomplishes two remarkable feats: establishing a strong community that supports "beras'' and implementing a well-designed and proposed architecture for the protocol. The combination of these two factors makes Berachain one of the most unique Layer 1 projects in the current crypto market. ## Sources - [A Deep Dive into Berachain](https://medium.com/@polygonchef/a-deep-dive-into-berachain-643ff0ee22ad) - [https://medium.com/@itsdevbear/introducing-berachain-4f7dc3032c17](https://medium.com/@itsdevbear/introducing-berachain-4f7dc3032c17) - [Berachain](https://www.berachain.com/) - [Berachain Docs](https://docs.berachain.com/) - [https://twitter.com/miguelrare/status/1745886186080485862](https://twitter.com/miguelrare/status/1745886186080485862) - [https://twitter.com/dylanxvfeth/status/1745176859728560131?s=52&t=txFAbiSPTdLLDlAYj9X_AA](https://twitter.com/dylanxvfeth/status/1745176859728560131?s=52&t=txFAbiSPTdLLDlAYj9X_AA) - [[Research] Introducing Berachain](https://medium.com/a41-ventures/research-introducing-berachain-901315f5bad6) - [Berachain Unleashed: Liquidity Redefined](https://www.bitget.com/web3/academy/what-is-berachain) - [Berachain, Cults and the Dawn of The Honey Jar](https://0xhoneyjar.mirror.xyz/nQE-5CbhhirIeTJi7w48P97Ir0-HISuvb6NnwHr-eSA) - [Honey Jar Ponzinomics](https://0xhoneyjar.mirror.xyz/3rW2cfsDtTqcS3gHWTgHjxOhOPEGgOzl9A9LCmeJ_tU) - [Introducing Kodiak: Berachain’s Native Liquidity Hub](https://medium.com/@KodiakFi/introducing-kodiak-berachains-native-liquidity-hub-63c3e7749b30) - [Beradrome Docs](https://docs.beradrome.com/) - [Introducing: Infrared. Today, we are thrilled to unveil… | by Infrared Finance | Jan, 2024 | Medium](https://medium.com/@infraredfinance/introducing-infrared-0f5c81b59e7f) - [Berachain raises $42 million to launch yet another Layer 1 blockchain | The Block](https://www.theblock.co/post/227344/berachain-funding-new-layer-1-blockchain) - [Berachain started from an NFT collection and is now a highly anticipated Layer 1 in the works. Today we're going to do a complete deep dive into ev - Thread from Wajahat Mughal @0xMughal - Rattibha](https://en.rattibha.com/thread/1657850373661683712) - [Berachain — A Deep Dive. 60,000 Discord members, the first… | by Crypto Climax | Coinmonks | Medium](https://medium.com/coinmonks/berachain-a-deep-dive-3c840de5a09a) - [Berachain ecosystem NFTs explained | by Beramonium Chronicles | Jan, 2024 | Medium](https://medium.com/@beramoniumchronicles/berachain-ecosystem-nfts-explained-6c8c4f8f581e) - [Berachain Blockchain: A Blend of Memes, Innovation and Community - Flagship.FYI](https://flagship.fyi/outposts/blockchains/berachain-blockchain-a-blend-of-memes-innovation-and-community/) - [Why berachain? — technical analysis from Honeypot Finance founder’s view | by Bubbletree | Jan, 2024 | Medium](https://medium.com/@bubbletree/why-berachain-technical-analysis-from-honeypot-finance-founders-view-e647e994f408) - ["Proof of Liquidity" Project Berachain Launches Public Testnet, Artio](https://www.investingcube.com/proof-of-liquidity-project-berachain-launches-public-testnet-artio/) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # 2024 Shoal Research Watchlist > Trends we’re exploring in 2024 - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-02-27 - Canonical: https://shoal.xyz/research/writing/2024-shoal-research-watchlist/ - Keywords: crypto, DeFi, restaking, liquid staking, yield, infrastructure, Solana, Ethereum, DePIN, AI compute, Research ![](https://shoal.xyz/research/writing/2024-shoal-research-watchlist/img/66414b3c621e.jpg) **Crypto is an attention economy. Therefore, we believe it is not only important to pay attention to fundamentals, but also the trends and narratives which capture attention and consequently value.** *This is not an endorsement of any of the listed projects- these are teams and/or products we believe are worth paying attention to in 2024 and will be researching further. Not financial advice, not any official endorsement* **“I’m a business man. Not a priest”** ![](https://shoal.xyz/research/writing/2024-shoal-research-watchlist/img/c49fbb8b0a3f.png) ### Restaking Following the Shapella upgrade which enabled withdrawals for ETH stakers, we have witnessed the rise of the liquid staking ecosystem, worth [$48](https://defillama.com/protocols/Liquid%20Staking)B today and the largest active sector in crypto today. Liquid staking tokens offer stakers opportunities to earn additional yield on their native assets, e.g. ETH, by minting a derivative asset known as a Liquid Staking Token (LST), which can be deployed across various DeFi applications to earn additional yield. Restaking is simply the process of staking an asset again after it has already been staked- the idea is to extend Ethereum’s pooled security (staked ETH) as a way to bootstrap security for new networks. It is important to distinguish between native and liquid restaking - native restaking involves staking $ETH and creating an “[EigenPod](https://docs.eigenlayer.xyz/guides/testnet-restaking/native-restaking/creating-an-eigenpod)“ which sets a withdrawal credential to an EigenLayer smart contract. This lets the EigenLayer system recognize your restaked amount, and one can then opt into new services written into a service contract. Liquid restaking enables LST holders to “stake their stake” and receive a derivative token to represent their restaking position called an LRT. For a comprehensive overview of the liquid restaking frontier, see Shoal’s [research report.](https://www.shoal.gg/p/liquid-restaking-tokens-a-new-frontier) Overall, restaking introduces a new layer of yield for the asset holder, more security for the underlying network in theory, and certainly more risk depending on who you ask. Excitement around this new development is growing as there is currently over $8.9B in deposits in Eigenlayer and over $4.6B in liquid restaking protocols. There are important risks to consider; many liquid restaking platforms have not enabled withdrawals yet, so exercise caution as you are depositing into a one-way contract at the time. Read the latest [Shoal report](https://open.substack.com/pub/shoal/p/underwriting-lrts-balancing-high?r=l3e63&utm_medium=ios&utm_campaign=post) for a comprehensive overview of the risks of current liquid restaking platforms. Furthermore, it will be important to ensure the restaking strategy marketplace does not converge to create a new layer of centralization risk at the staking operator level. That said, with a healthy dose of caution, we expect restaking protocols to perform well in 2024. - **Eigenlayer -**Having pioneered restaking, Eigenlayer is the key layer to enabling restaking strategies. The protocol has already accrued more deposits (TVL) than Uniswap and could easily overthrow Aave and Maker (#3 and #2 respectively) by the end of the year if not within the next few months. There is an airdrop coming, so it will be interesting to see how user retention and outflows normalize following the release of the token. While a decline in TVL and users is expected, the question is to which extent and for how long, as this will provide valuable insight for forming long-term convictions around the potential for Eigenlayer and the restaking ecosystem. - **Etherfi  -** Etherfi enables users to deposit ETH to be natively restaked with Eigenlayer. The protocol has the highest value of deposits among all liquid restaking protocols ($1.1B) and is one of the few restaking protocols to have enabled withdrawals for users. Stakers retain custody of their ETH while delegating stake, and Etherfi mints an NFT for every validator launched through the protocol. ![](https://shoal.xyz/research/writing/2024-shoal-research-watchlist/img/b466cdb0b136.jpg) - **Picasso Network ($PICA)** - While restaking is native to Ethereum, it is still a young and untapped sector for which a multi-chain future seems inevitable. As restaking becomes more crowded on Ethereum, teams will explore other ecosystems and blockchains to tap into. This is already underway on Solana, which has a $1.9B liquid staking market today ripe for growth.  Picasso is a new DeFi interoperability layer from the Composable Finance team that is native to the Polkadot and Kusama network, supporting communication across multiple ecosystems via the Composable IBC module. The Solana <> IBC connection is the first AVS in the Picasso restaking layer, enabling users to stake SOL or any supported Solana LST. This unlocks a new sector of cross-chain applications and use cases between Solana and IBC-enabled chains, as other ecosystems will be able to take advantage of Solana’s speed, low fees, and growing user base and liquidity. ### Solana 2.0 Slowly and then all at once following the FTX collapse, Solana went parabolic across all metrics in Q4 2023 around the time of the JTO airdrop and annual Breakpoint conference. We believe this is only the start. With more excitement around upcoming airdrops spurring ecosystem activity, critical infrastructure and network developments on the horizon, and continued recognition across mainstream media picking up, Solana is well-poised to do be a strong performer in the coming year and beyond. The long standing thesis is simple and contingent on Moore’s Law, as well as the notion that user-facing performance specs, like high throughput and low costs, have set up Solana to be the consumer-chain of the future. Solana recently faced a temporary network outage (2/6) after having perfect uptime for over a year. The root cause was identified to be a bug that was already fixed in testnet but still needed to be implemented on mainnet-beta. Though it is evident that outages inflict damage on Solana’s public perception, the fact is that network ultimately managed to go back up within an hour and will only become more resilient in these situations moving forward, especially with the rise of validator client diversity in the ecosystem. - **Jupiter Exchange ($JUP)** ([see our thesis](https://www.shoal.gg/p/jupiter-exchange-solanas-dex-aggregator)) - **Firedancer**- A high performance validator client from Jump Crypto, which is expected to bring significant improvements in performance and throughput, and more importantly strengthens Solana’s validator client diversity. Read this [introduction](https://www.helius.dev/blog/what-is-firedancer) from Helius for a comprehensive introduction. - **Kamino Finance -**Simply put, Kamino aims to be the liquidity powerhouse for Solana DeFi. Users can supply/borrow with leverage, earn as an LP with automated CLMM vaults, and even long/short tokens and trade with leverage. A one-stop shop similar to Jupiter which could evolve into a competitive relationship over time as well. Furthermore, Points are live, with an airdrop expected in Q2. ### DePIN Computing power is a resource constantly growing in demand in today’s day and age, as the world becomes further digitized and the sheer amount of data produced continues to grow exponentially, only further accelerated with the rise of LLMs and consumer/business-centric AI. As compute becomes an increasingly scarce resource, it becomes that much more important to optimize its distribution and availability. Decentralized physical infrastructure networks (DePIN) unlock more efficient compute markets through disintermediation of distribution and value accrual. DePIN provides a tangible and exciting use case for crypto; one that sees crypto and blockchain technology as critical components of a greater whole rather than a novel stand-alone tech with new tacky buzzwords. While the scope of growth for DePIN goes far beyond 2024, the sector has particularly surged in popularity in recent times. It’s important to distinguish between hype and fundamentals, but it is exciting to have a combination of the two. ![](https://shoal.xyz/research/writing/2024-shoal-research-watchlist/img/93e2cf908f05.jpg) - **Render ($RNDR) -**An OG GPU marketplace since 2017, connecting 3D artists to the resources they need to graphically render virtual scenes for games or movies. The platform recently migrated to Solana to join a number of leading DePIN platforms like Helium and Hivemapper. - **Akash** **($AKASH) -**The GPU-as-a-Service (GPUaaS?) is [projected](https://www.fortunebusinessinsights.com/gpu-as-a-service-market-107797) to reach over $25B by 2030, implying an inevitable strain on supply and distribution methods.  Akash is a decentralized, peer-to-peer marketplace for renting GPUs that launched as a Cosmos chain in September 2020 - think of Akash as the airbnb for GPU compute. Akash employs a hybrid architecture which handles coordination and settlement onchain, and execution off-chain. A more critical value proposition - Akash offers highly competitive rates on Nvidia A100 compared to leading providers like AWS, Azure, and more. - **Helium** **($HNT)** - Helium is a decentralized network servicing long-range, low-power communication for IoT devices like sensors, trackers, etc. Helium enables individuals to host Hotspots (mini-towers which to amplify broadband for the network) in exchange for earning rewards in Helium tokens (HNT) for their services. - **Hivemapper** (**$HONEY)** Decentralized Google Maps - users purchase a webcam which they then use to drive and record their surroundings, earning $HONEY tokens for contributing to building Hivemapper’s decentralized mapping system. - **Teleport**  - TLDR; Teleport is a new decentralized ride sharing protocol. You remember the outsized returns Uber delivered its early investors. Now get this - Uber, on the blockchain. ### Crypto x AI Artificial intelligence has recently experienced its pop-culture moment with the rise of consumer-centric AGI applications like ChatGPT, which have already found their ways into many facets of people’s everyday lives, besides the fact that they are predicted to ultimately change the dynamics of the world for better or worse. OpenAI just launched [Sora](https://openai.com/sora), a new text > video AI model, further reminding everyone about the many capabilities of this new tech that we have yet to see. As[Lucas Tcheyan](https://www.galaxy.com/authors/lucas-tcheyan) of Galaxy Research [frames it](https://www.galaxy.com/insights/research/understanding-intersection-crypto-ai/) - “Innovation in the two industries is unlocking new use cases that could accelerate adoption of both in the coming years.” Blockchains introduce breakthroughs in settlement, data storage, and system design (back-end) , while artificial intelligence is a revolution in computation, analysis, and content delivery (front-end). VanEck AI [estimates](https://www.vaneck.com/us/en/blogs/digital-assets/matthew-sigel-vanecks-crypto-ai-revenue-predictions-by-2030/vanecks-crypto-ai-revenue-predictions-by-2030.pdf) the Crypto x AI sector could generate up to $10.2B in revenue by 2030. However, it is worth noting directly integrating AI models on blockchains is not very practical, given the limited computational capacity today. It’s entirely possible 10 years from now this may look different, but this is placing a big bet on the scalability of blockchains. **How Crypto benefits AI:** - Crypto provides AI with a permissionless, trustless, and composable settlement layer. - Use cases include decentralized compute markets (which are already live), building AI agents programmed to execute various complex financial strategies, and developing identity and privacy solutions to combat negative externalities of AI like sybil attacks. **How AI benefits crypto:** - Enhanced user experience (UX) for both users and developers thanks to large-language models (i.e., specially trained versions of ChatGPT and Copilot) - Potential to significantly improve smart contract functionality and automation. [Accelxr](https://twitter.com/accelxr) of 1kx wrote a [fantastic report](https://mirror.xyz/1kx.eth/yJ_zTPwC1YOwg9p7x5odC8V1lPL6zy_7b_gQND4Q0Io) about the different emergent areas of Crypto x AI, including creative development, anti-sybil mechanisms, infrastructure development, augmented governance, agent economies, and more. The point is, there’s a lot of potential to tap into here - but as anyone familiar with the history of the dot com bubble would say - be cautious about the trends and consequent reversals surrounding new and innovative tech that is still unproven. Projects on our watchlist - **Bittensor ($TAO)** : An open-source, decentralized blockchain network facilitating a peer-to-peer marketplace for machine intelligence. In short, Bittensor enables participants to submit AI models that can then be purchased by those who need it, e.g. app-developers and other researchers. As participants contribute their AI models and training to the Bittensor network, they are compensated in TAO tokens - given the cost inefficiencies of machine learning R&D today, one could imagine Google or IBM tapping into Bittensor’s network in the future. Bittensor has 95K accounts, facilitated 292K transfers, and produced 2.3M blocks. $TAO has a market cap of roughly $4B with 89% of supply staked, and has a 21m max supply similar to Bitcoin. *Data from [TAO explorer](https://x.taostats.io/)* - **Get Grass** - Get Grass is a protocol which aims to democratize the availability of training data for AI models, to build “the data layer for AI”. To get started, users can simply download their chrome extension to start earning points - the idea is to compensate everyday internet users for the data that is collected and sold on behalf of their digital footprint. The team has put together a data repository curated for training LLMs - something which typically comes at high costs for developers today - with the vision of empowering even everyday people to develop new applications with AI models one day, not just shady corporate overlords. Additionally, the idea of compensating people for their online data feels inevitable, and is a use case that crypto can serve perfectly as true digital-native currency.  Statistics are not currently available but are expected to come soon. - **Nosana ($NOS)** - Nosana is building a decentralized GPU marketplace for AI applications, connecting a network of user-sourced GPUs to AI developers, similar to Bittensor. Anyone with an idle consumer GPU can become a node on the Nosana network, and anyone can access Nosana’s in-house AI model for different needs. Since November 2022, Nosana has completed [180K inferences](https://explorer.nosana.io/) on its network, which refer to completed tasks that have been submitted to the network queue. $NOS is used for staking collateral for nodes and a medium of exchange on the Nosana network, and currently has a $370M FDV. ### Intents Intents have become a buzzword in crypto, and some have questioned using the term “intent” itself, but the idea is quite simple - intents are signed transactions which outsource the trade’s execution route on a user’s behalf, for the purpose of better price settlement. Whether you wish to call this mechanism an intent is up to you, but in the context of our attention economy, we believe “intents” sell. A key feature of intent-based trading protocols is outsourcing trade execution to a subset of competing searchers (these vary by name, eg. ‘solvers’, ‘fillers’ etc) which compete in an auction to find the optimal price route for users’ trades. In addition to a variety of onchain liquidity sources (liquidity pools on DEXs), these searchers are often able to tap into offchain inventory like CEX liquidity to front capital for the user’s trade. The benefits of using off-chain liquidity includes cost savings on gas fees, and deeper liquidity. That said, a shift towards becoming increasingly dependent on off-chain components has alarming implications on a greater scale. ![](https://shoal.xyz/research/writing/2024-shoal-research-watchlist/img/c99829692fdb.jpg) Private mempools, which offer users a “fast-pass” connection directly to the block builder, are becoming more widely adopted by both users and applications integrating various MEV-protection services such as MEV-Blocker, which now has over [600K unique users](https://dune.com/queries/2771590/4614086). - **Infrastructure** -  A number of teams are working on core infrastructure for building intents-based applications. The most important developments we believe to be: **SUAVE** - Flashbots building a side chain which will serve as a developer toolbox for building auction-based models with intents. **Anoma** - The Anoma team is building out an entire network for enabling intent-based applications with privacy and security in mind. **Essential** - Building various models and standards for intents applications, including a DSL for intents, intent-centric account abstraction, and a modular intent layer. - **Applications** **CoWSwap ($COW):** Not all intents-based protocols are equal: [Flashbots research](https://writings.flashbots.net/illuminate-the-order-flow) on Ethereum’s order flow markets revealed that CoWSwap solvers were the only competitive model in practice. Comparatively, 1inch Fusion’s resolver market and UniswapX’s filler market is significantly centralized. The Cow DAO recently voted to turn on the fee switch for CoWSwap creating an organic revenue stream for the protocol moving forward. There are plenty of other innovative features  -  TWAP orders, programmable orders - which can be used to help prevent people from getting liquidated on loans , “CoW Hook” transactions -  which allow users to combine multiple transactions into a single one , and most recently, the CoW AMM - an LVR-capturing AMM built with LPs in mind. **Across ($ACX)**: Across implements an intent-based execution model for Eth L1 <> L2 , L2 <> Eth L1, L2 <> bridging, in which solvers front liquidity to fulfill user trades and are reimbursed afterwards. With over [$5B in total volume](https://dune.com/risk_labs/across-protocol-stats), 357k users, and $101m in TVL , Across is one of the most successful organic 3rd party bridges in DeFi today. It inherits the security properties of the UMA optimistic oracle, which enables solvers to take on the inherent risk when fronting capital to users knowing they will be reimbursed, and in turn provide faster bridging execution for users. **IntentX**: Unlike most other intent-based protocols which are swap aggregators, IntentX introduces perpetuals trading to the intents landscape. Having just launched in Q4 ‘23 , IntentX has already received [$2.5M in deposits](https://defillama.com/protocol/intentx?tvl=true&derivativesVolume=true&groupBy=cumulative&events=false&fees=false&revenue=false), facilitated $707m in volume, and generated $630k in revenue(!) on Base. As the intent-centric landscape continues to evolve, we’re keeping an eye on IntentX and its novel intent mechanism for perps trading. ### DeSoc As Chris Dixon highlights in his new book “Read,Write,Own” : > **“Search and social ranking algorithms can change lives, make or break businesses, and even influence elections, yet the code that powers them is controlled by unaccountable corporate management teams largely hidden from public scrutiny”** Social networks are the essence of human connection and coordination, yet the overwhelming majority of revenue generated from content created on these networks funnels back to the platforms and not the users, entrepreneurs, and content creators themselves. The creator economy is in need of an overhaul, and decentralized social media (DeSoc) can help. DeSoc and crypto-native social networks offers new opportunities for monetizing creator <> fan relationships - once again a new unlock arises from disintermediation of rent-seeking middlemen. The idea is a good one - but the execution has not been there yet. Lens has continued to show some promise but hasn’t quite had a breakthrough moment yet. Friendtech died as quickly as it rose to fame. And, well, R.I.P. Stars Arena. Friendtech demonstrated that a PVP-style social application with financial incentives is not a sustainable growth model, nor will it capture a significant audience outside of crypto natives. Onboarding remains a critical hurdle - not only is it challenging/near impossible to switch to a new social network due to moving your followers/audience, imagine having to set up a self-custody wallet for the first time in your life as well. To quote [Antonio Garcia Martinez](https://blog.spindl.xyz/p/why-farcaster-frames-are-important), a former Facebook PM: > “Web3 needs to enable cool functionality not previously possible in Web2, and make the user largely unaware they are on the blockchain.” This is why Farcaster is exciting. Although it broke new ATHs in users and activity recently, Farcaster is not just the latest hype train. Led by Dan Romero and Varun Srinivasan, the ex-Coinbase team has been working on their craft for some time now. Farcaster is not one particular app - rather it is the platform, the decentralized architecture which enables new applications to be built on top of it. Farcaster uses a hybrid back-end architecture, in which everything crypto/blockchain is abstracted away off-chain, while identity management is stored in smart contracts onchain. **Warpcast**, a client built by the core Farcaster team, offers a slick web2 social experience. Warpcast has a feed similar to that of Twitter’s, as well as specific channels which are similar to subreddits, allowing users to join communities and curate the content they wish to see. *Sign up and [follow Shoal on Warpcast](https://warpcast.com/shoalresearch)today - tag us and we’ll follow back!* **Frames,**which warrant an entire article of its own,offers new opportunities for developers to build embedded experiences directly into one shared interface. In other words, do more cool things without leaving the application you’re using. To honor internet culture, one of the core engineers put [Doom in a frame.](https://warpcast.com/cassie/0xc329ea28)That said, there are many other exciting possibilities - imagine reading an article about the newest AI token, and being able to purchase the token without leaving the article *(folks, a reminder to always do your due diligence).* Or getting all the latest news and updates from your[favorite research telegram](https://t.me/shoalresearch) in one interface. Betting on a sports game directly from a live stream in your feed. The connectivity of experiences will in turn grow the quality of the experiences and consequently their value. This is what Facebook tried to do but ultimately failed with the Open Graph protocol, largely due to technical and multi-party coordination problems that blockchains stand to solve. The coolest thing about Farcaster is that these are only two clients - anyone can spin up clients custom-built for a user or enterprise’s needs. [A16z has a repo](https://github.com/a16z/awesome-farcaster) with a bunch of clients available for anyone to get started building on today. We look forward to more innovation in this sector and are eager to work with teams building in the DeSOC space - reach out to Shoal! ### Telegram Bots **Telegram bots are another exciting and unique way to interact with crypto. They are a premier example of a headless marketplace - where global demand and users meet local distribution venues (i.e. wherever a user’s wallet already is).** Telegram bots abstract away many of the onboarding hurdles with crypto today - wallets are created on users’ behalf, and funds can can deposited to/withdrawn from an associated CEX address (i.e. Coinbase). Considering Telegram has [800M monthly active users today](https://www.statista.com/statistics/234038/telegram-messenger-mau-users/), this seems like a lucrative user base to tap into. The rapid growth and adoption of telegram bots supports this notion - though it is important to pick out a select few quality picks among the 100s of bots launching nowadays. - **Banana Gun bot ($BANANA)** - Supports Ethereum and Solana. In its lifetime, Banana Gun has done [$1.4B in total volume and facilitated over 3B trades across 87K traders](https://dune.com/whale_hunter/banana-gun-bot). Get up to speed with [Shoal’s report](https://www.shoal.gg/p/banana-gun-telegram-sniper-bot) on Banana Gun. - **BonkBot (TBD):**Bonkbot was launched by a separate team from the BONK token. It the most performant TG bot on Solana, and has facilitated more trading volume than any other bot with[$1.8B in trading volume](https://dune.com/whale_hunter/bonkbot) across 24M trades and 158K traders. Bonkbot’s trades are automatically routed through Jupiter, creating a synergistic relationship with one of the top projects on Solana. - **Unibot ($UNIBOT)** - Supports trading on Ethereum and Solana. Kicked off the TG bot mania in 2023. In its lifetime, Unibot has facilitated [731K trades](https://revshare.unibot.app/) with [$479M in total volume](https://dune.com/tacodevs/unibot-sniper) and $4.7M in total fees. Get up to speed with Shoal’s [Unibot report](https://www.shoal.gg/p/unibot-the-telegram-uniswap-sniper). For someone who wants to get exposure to trading assets only available onchain but doesn’t want to deal with the hassle of creating a new wallet and navigating across 100s of trading venues (with the implied smart contract risk), telegram bots make perfect sense. After all, If you only want to trade memecoins, why would you care much for the intricacies of self custody? This can likely be applied to various other use cases beyond trading, i.e. borrow/lend on Aave through a telegram bot, mint NFTs, make payments, etc. ### Parallel-Execution L1s The rapid growth of the Solana ecosystem in H2 2023, continuing upwards in Q1 2024, has brought more recognition to the benefits of parallel-execution in transaction processing on blockchains. Though there will always be inherent value in the security of Ethereum, which processes transactions sequentially, the fact is that demand for low-latency and high throughput infrastructure will naturally outpace it as more users come to crypto and/or more enterprises seek to implement blockchain technology to solve real-world business tasks. The key idea behind parallel execution is to allow non-conflicting transactions simultaneously, unlocking faster execution speeds and higher overall throughput. On Solana, accounts are required to declare which particular network state they need to access in each transaction, which is what allows for concurrent execution. Bob swapping 100 USDC > SOL on Jupiter does not conflict with Alice borrowing 1000 JUP on Kamino. There is an emerging trend of “Alt-Parallel L1s” , which are relatively young networks (<= 1year) that process transactions in parallel, similar to Solana. A key distinction to make in parallel processing is deterministic vs optimistic processing. Deterministic processing, as seen on Solana, all nodes execute an agreed-upon set of transactions simultaneously in lock-step. Optimistic processing, for instance Sei’s design, processes transactions concurrently across multiple nodes, later verifying that the submitted transactions are valid. Therefore, it is possible for optimistic parallel-processing chains like Sei to have faster execution speeds than Solana, but this comes at the cost of potential rollbacks later on in the case of fraudulent activity. - **Sei ($Sei) -**Sei is an L1 built on the Cosmos SDK specialized for trading and financial services. V2, which is set to launch in H1 2024, introduces upgrades to several key features including smart contracts, parallel processing, and state storage. Sei currently has $23M in TVL, and $Sei is trading near a $2B market cap. - **Sui ($Sui) -**Sui is an L1 from Mysten Labs built on the MoveVM, which uses a parallel processing model for transactions to offer, you guessed it, high TPS and low fees. Sui currently has $649M in TVL, 10th most among all chains. Interestingly, $Sui is trading near a $2B market cap similar to Sei, despite having over 20x the TVL. - **Monad (TBD) -**Monadis an EVM L1 which aims to deliver 10K+ TPS through optimistic parallel execution and **“superscalar pipelining”**. Monad is built by former Jump Trading employees with lots of experience in HFT, and has a very strong community (*Gmonad*). Monad is also going to use its own database MonadDB for data storage, eliminating a scaling constraint for previous EVM blockchains. *Data sourced from DeFi Llama* ## Modular Money Modular blockchains are specialized chains built to serve a particular purpose while seamlessly connecting with other specialized chains. Blockchains perform 4 critical functions - Consensus, Execution, Settlement, and Data Availability.  While monolithic, or “integrated”, blockchains run all 4 functions on the base layer, modular blockchains adopt a “plug and play” approach where networks can opt to use specialized infrastructure to perform their critical functions. ![](https://shoal.xyz/research/writing/value-accrual-in-the-modular-stack/img/b0af664b4884.jpg) For a simple analogy, consider putting together an outfit - you can get dressed head-to-toe in clothes all from one brand (monolithic), or you can wear a shirt from Hanes, jeans from Levi’s, and a jacket from Carharrt (modular). - **Celestia ($TIA)**- Celestia co-founder Mustafa Al-Bassam wrote the [Lazy Ledger](https://arxiv.org/abs/1905.09274) research paper back in 2019 , which laid out the fundamental concept of a specialized system that helps other networks scale - what we call a modular blockchain today. Celestia functions as a specialized DA layer, offering a low-cost alternative for L2s to post their data. - **Eclipse**: New L2 which uses SVM for execution, Celestia for DA, Ethereum for settlement, and RISC ZERO for zk fraud proofs - doesn’t get more modular than that! We are excited to see new use-cases for the SVM especially with the rise of modular blockchains. There is some uncertainty around how Eclipse will actually perform given it resembles a bit of a Frankenstein-like experiment, but the team is strong and expectations are high for the novel L2. ## Rollups-as-a-Service Developers building dApps have several options for deployment, including existing blockchains, Layer 2 solutions (L2), custom appchains, and rollups. Rollups can offer a sweet spot between customization, performance, and development effort, particularly with the simplified setup offered by Rollups-as-a-Service (RaaS) providers. These providers offer tools and services, ranging from rollup management to no-code deployment, enabling easy creation and maintenance of custom rollups. Imagine running a busy restaurant (traditional blockchain): you handle everything from cooking to deliveries. RaaS is like hiring a delivery service (RaaS provider): they manage deliveries, freeing you to focus on cooking (development) and providing a smooth experience for customers (users). - **Conduit:**This platform empowers anyone to launch their own rollup quickly and easily, without needing to write any code. The self-serve platform takes care of everything, from infrastructure to security, so you can focus on what matters - building the product. Leading companies like Zora and Gitcoin trust Conduit to handle the technical complexities - **Dymension ($DYM):**Dymension leverages a modular blockchain architecture. Users interact with RollApps (front-end), while Dymension (back-end) coordinates the ecosystem and facilitates communication. Data Availability Networks (decentralized databases) provide temporary data storage. - **Cartesi:**Cartesi provides a dedicated CPU and rollup for your dApp, preserving decentralization, security, and censorship resistance while enhancing computational scalability. It utilizes the Cartesi Virtual Machine, allowing you to use familiar libraries, languages, and tooling, moving beyond the EVM. ## Gaming Crypto participants have long awaited "the" AAA Web3 game. In the last crypto cycle, Axie Infinity, Sandbox, Decentraland, and Enjin were among the core talking points as new gaming companies realized Web3 could be a new place to test out concepts. In the last cycle, we found many games that resembled "DeFi with lore," which were focused more on interactions of farming/yield generation strategies instead of the actual games. For many of these games, much of the feedback revolved around the actual fun of the games being the core gaming applications. Although these games performed well in the bull market, the sentiment wore off due to unstable tokenomics or their incentive mechanisms breaking despite substantial price increases. - **Ronin ($RON)**- Ronin, developed by Sky Mavis, is an EVM-compatible blockchain tailored for gaming, most notably hosting the successful Web3 game Axie Infinity. Ronin focuses on near-instant transactions and minimal fees, while also enabling stands out for enabling vast numbers of in-game transactions. - **Beam ($BEAM) -** Beam network is a gaming-centric ecosystem incubated by the Merit Circle DAO. It offers the Beam SDK to developers, allowing for the integration of blockchain elements into games. As the network's gas token, $BEAM is essential for transaction payments and smart contract interactions within the Beam ecosystem. - **Echelon Prime ($PRIME) -**Echelon Prime is a gaming platform, focusing on development and distribution of tools designed to foster new gaming models and economic systems. Its token, $PRIME, has been notably integrated into Parallel, a sci-fi trading card game, marking its first application. Through $PRIME, Echelon Prime aims to facilitate and promote the expansion of cutting-edge gaming experiences and economies including AI and AR gaming. ## Closing Note We are eager to engage with teams and founders pushing the boundaries of innovation in blockchain infrastructure and the on-chain economy. The digital asset landscape is filled with opportunities, as well as noise, and sifting through the haystack to find gem-like needles requires continuous research and refinement of our thesis. Shoal Research is dedicated to uncovering value within the DeFi and infrastructure ecosystem, as well as tracking trending narratives that intersect with our interests. ## Sources *Data used in this report was mostly taken from DeFi Llama, Dune Analytics, and mentioned protocol docs.* --- # ETHDenver 2024 Event List by Shoal Research > Shoal Research related satellite events at ETHDenver 2024 - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-02-20 - Canonical: https://shoal.xyz/research/writing/ethdenver-2024-event-list-by-shoal/ - Keywords: crypto, DeFi, MEV, restaking, liquid staking, RWA, zero-knowledge, security, infrastructure, Ethereum, Bitcoin, DePIN, gaming, Research ![](https://shoal.xyz/research/writing/ethdenver-2024-event-list-by-shoal/img/a30eb668e0fa.jpg) *Shoal Research is an early stage DeFi and Infra research firm. For more information, or adding related events please message [@zaddycoin](http://t.me/zaddycoin) on telegram.* ## Monday, February 26 - [BUIDLWeek at ETHDenver · Luma](https://lu.ma/5o1ix12j) - [CONVERGENCE | AI x Crypto Summit](https://lu.ma/WITHJOY?tk=ACyAyu) - [zkHangout @ ETHDenver · Luma](https://lu.ma/zkHangout) ## Tuesday, February 27 - [Multi-Prover Hack Day](https://lu.ma/u0jd6ucd) - [Liquidity Provider Mixer w/ SynFutures & Parallel](https://lu.ma/lpmixer) - [Appchain Day 2024 · Luma](https://lu.ma/AppchainDay) - [Scale Summit · Luma](https://lu.ma/ScaleSummit2024) - [zkDay Denver 2024 | Feb 27th | 12PM-6PM · Luma](https://lu.ma/zkDayDenver24) - [ABCDE Parallel EVM DAY @Denver · Luma](https://lu.ma/cfsdelq3) - [Rollup Developer Summit · Luma](https://lu.ma/xmtzceyo) - [Innovator x Creative Social - Denver 2024 · Luma](https://lu.ma/InnovatorCreativeSocial-Denver2024) - [Meetup Buidl Community & Technology - ETH Denver · Luma](https://lu.ma/icp-denver) - [ReGov · Luma](https://lu.ma/8djyfb4m) - [Real World Assets in DeFi Happy Hour · Luma](https://lu.ma/zejjzpkb) ## Wednesday, February 28 - [Chain Abstraction Day @ ETHDenver 2024](https://lu.ma/ChADay) - [The LRT Forum — ETHDenver](https://lu.ma/DenverLRTForum) - [Decentralize AI Day @ ETH Denver 2024](https://lu.ma/mxh1cf8u) - [Bittensor Breakfast @ #ETHDenver w/ Canonical, Tensorplex, Collab+Currency](https://lu.ma/0b3muto8?tk=c1AmDY) - [Invite-Only Staking Brunch](https://lu.ma/stakingbrunch?tk=0pCvFx) - [ATOMDenver² · Luma](https://lu.ma/atomdenver2) - [Builder's Village @ETHDenver | Aleo, AMD, Manta, Halborn, Telos, Orb, Validation Cloud, EduDAO, F3 Ventures · Luma](https://lu.ma/buildersvillagedenver) - [ETH Denver | Liquidity Day · Luma](https://lu.ma/liquid) - [Open Data Day · Luma](https://lu.ma/opendataday1) - [Restaking House · Luma](https://lu.ma/6jz2vxfz) - [DeFi Founders Club · Luma](https://lu.ma/yabxdxgj) - [Thank You Satoshi, Whoever You Are @ ZetaChain x Sushi x OKX · Luma](https://lu.ma/05x1puuk) - [Crypto Growth Happy Hour · Luma](https://lu.ma/cryptogrowth) - [Bufficorns Dreamland: ETHDenver Official Opening Party · Luma](https://lu.ma/bufficornsdreamland) - [Tacos with Nerif (ETHDenver Edition)](https://lu.ma/flkiqr3k) - [Bierhalle Liquidity with Velar & dYdX at ETH Denver · Luma](https://lu.ma/liquid-ethdenver2024) - [Ginza Gaming Soft Launch](https://lu.ma/2b91o2m0) ## Thursday, February 29 - [GSR, LayerZero & Monad Happy Hour @ ETH Denver](https://lu.ma/ljr8d7g0) - [EVM Day · Luma](https://lu.ma/evm) - [Founders Happy Hour w/ BitGo, Magna, Ottersec, Antimetal, and Cega](https://lu.ma/founders-hh) - [Open Cafe at ETHDenver](https://lu.ma/opencafeethdenver1?tk=8TXH21) - [Avalanche Hack House | Denver · Luma](https://lu.ma/hackhouse2024denver) - [✨EIP Day by Ethereum Magicians✨](https://lu.ma/eip-day) - [Aleo zkHouse Denver: zkTalks 🎤 · Luma](https://lu.ma/zktalksdenver) - [Build with Variant: Coffee + Co-Working @ ETHDenver](https://lu.ma/gcq8nxy8) - [Open Information House | ETHDenver 2024 · Luma](https://lu.ma/k4tq2kw7) - [RUNDAO - ETHDenver '24 Edition](https://lu.ma/rundao-ethden24) - [Lunch & Learn: Demystifying DeAI x DePIN x Decentralized Data](https://lu.ma/ob8bt8z3) - [Omnichain Day @ETH Denver | Powered by ZetaChain · Luma](https://lu.ma/3ixiiawe) - [DWF Labs Haus - Builders Connect @ ETHDenver · Luma](https://lu.ma/DWFLabsHaus-BuildersConnect) - [Stakeholder : Infra Open House](https://lu.ma/k0sj5is8?tk=Uv61Db) - [ZeFi Day - Explore the world of Zero Knowledge Finance · Luma](https://lu.ma/zefidaydenver) - [QuillCon CXO Mixer | ETH Denver Edition · Luma](https://lu.ma/quillaudits_quillcon_denver_mixer) - [Base BUIDLer Bar w/ Seamless · Luma](https://lu.ma/iild64hp) - [Berapalooza · Luma](https://lu.ma/Berapalooza) - [The Institutional Happy Hour: ETH Denver Kickoff · Luma](https://lu.ma/Instit-EthDenver2024) - [ACJR<>CCC Presents TechTalks: Exploring Tomorrow's Trends](https://lu.ma/l7ikdhdk) - [Ethereum Rendezvous with ether.fi, Ethena, Morpho, summer.fi, and Drosera · Luma](https://lu.ma/0cso9zvi) - [Indoor Golf & Poker: The Ultimate GameFi Experience at ETH Denver w/ Halborn, Pickem, Telos Foundation, Core · Luma](https://lu.ma/ETHDenver_GameFi) - [RWA Happy Hour at ETHDenver · Luma](https://lu.ma/denverrwa1) - [Builders Ball w/ Supermoon, Cointelegraph, Oort · Luma](https://lu.ma/33bq7jjf) - [All Eyes on the Bull’s-Eye DeFi Mixer w/ Figment, dYdX, and Fordefi at #ETHDenver · Luma](https://lu.ma/bullseye-ethdenver2024) - [The Essential Event (Intents Happy Hour) · Luma](https://lu.ma/aodhblbo) - [Happy Hour with QuickNode & Dune · Luma](https://lu.ma/ETHDENVERHAPPYHOUR) - [Mile High Mixer @ Beacon with Quantstamp, HFØ, Fenwick and Zircuit | 02.29.24 | 9pm - 1am · Luma](https://lu.ma/milehighmixer) ## Friday, March 1 - [IRL with BASE, Royal, & Alchemy](https://lu.ma/w15qrcht) - [Pyth Network Data-Driven Happy Hour: ETHDenver 2024](https://lu.ma/pythdenver) - [DeFi Derivatives Summit](https://defisummit.panoptic.xyz/) - [Arbitrum | A Shake Shack Takeover](https://lu.ma/Arbiburgers) - [Beyond the Block: MEV Along the Txn Supply Chain](https://lu.ma/MEV) - [Proof of Data Summit · Luma](https://lu.ma/proofofdata) - [BASS ETHDenver · Luma](https://lu.ma/bassdenver) - [Brunch — Modular Acceleration by Celestia, Goldsky & Dora](https://lu.ma/modaccbrunch) - [Intent Brunch @ETH Denver w/ Orb Labs, Caldera, Particle Network, PropellerHeads, Aperture · Luma](https://lu.ma/intent) - [Parallel Brunch w/ Sei · Luma](https://lu.ma/seibrunch) - [Ecosystem Growth Summit presented by Gitcoin x Electric Capital · Luma](https://lu.ma/egsdenver) - [Modular Sessions — Modular Acceleration by Celestia, Goldsky & Dora](https://lu.ma/modaccsessions) - [Building on Bitcoin - Denver · Luma](https://lu.ma/hjd3x2ji) - [Ethereum Validator & Node Operator Summit · Luma](https://lu.ma/ethvalidator) - [Happy Hour — Modular Acceleration by Celestia, Goldsky & Dora · Luma](https://lu.ma/modacchh) - [Restaking Summit | Old Friends Reunion Denver](https://lu.ma/ofrdenver2024_restaking_summit) - [A Fraxtal In Time · Luma](https://lu.ma/fraxtal) - [Euler Comeback Happy Hour](https://lu.ma/ncjtybbk) - [zkRoad Happy Hour with zkLighter @ETHDenver · Luma](https://lu.ma/0jt60hfp) - [DeFi Gathering - Live Panels, Dinner & Happy Hour · Luma](https://lu.ma/ETHDenver_DeFiHappyHour) - [Putt & Party: DEFI Happy Hour · Luma](https://lu.ma/18y985tz) - [Vault Tech Networking | AWS, IBM, GOOGLE, NIKE](https://lu.ma/3fmt2e88) - [Injective Happy Hour @ETHDenver · Luma](https://lu.ma/InjectiveDenver) - [OnePiece Labs - ETHDenver Afterparty](https://lu.ma/ethd202412) - [Lmeow by Code4rena · Luma](https://lu.ma/coqj1dmg) ## Saturday, March 2 - [Protocol Mixer with Magna, Ottersec, Orb Labs, Gaslite, & Den](https://lu.ma/protocol-mixer) - [LSDFI SUMMIT by Tenderize & Friends](https://lu.ma/lsdfisummit) - [ETH Denver Native Panel: DeFi Night](https://lu.ma/native-defi-night) - [Rave3 & Flywheel DeFi Present: Higher Grounds](https://lu.ma/highergroundsR3) - [AI X Web3 Summit](https://lu.ma/AIXWeb3Summit) - [GPC Network Brunch @ EthDenver](https://lu.ma/gpcethdenver24) - [Infra Gardens Denver · Luma](https://lu.ma/InfraGardens-Denver) - [DePIN Meetup @ETH Denver w/Halborn, DIMO, Sushi, io.net, IoTeX, Borderless Capital · Luma](https://lu.ma/depin-ethdenver) ## Saturday, March 3 - [Last Call: ETHDenver Sendoff w/ Frax, Flywheel, and QiDao](https://lu.ma/ethdensendoff) --- # Drift Protocol: Solana’s Largest Perpetual Futures Exchange > The evolution of Solana's largest perpetual exchange protocol - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-02-20 - Canonical: https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/ - Keywords: stablecoins, DeFi, market making, MEV, yield, Solana, Research ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/b241af635c5d.jpg) ## Perpetual Landscape For perpetual trading, Centralized Exchanges (CEXs) still dominate, but it's undeniable that decentralized perpetual protocols have developed rapidly in the past two years, achieving nearly a 10X increase in total open interest. ![Source (excluding DYDX)](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/7d80f65ab6dc.jpg) In this context, the competition among perpetual protocols is intense. The rapid growth in volume data has led developers to view CEXs as a profitable and sustainable business. Many protocols are forks of first mover exchanges, GMX and DYDX, with ongoing innovation in minor areas such as the choice of price feeds, the structure of trading fees, and methods of incentivizing user onboarding. Just like with DEXs, each DeFi sector features a multitude of forks. The reason the surplus of forks in the perpetual protocol arena intensifies competition is due to a simplistic business structure. Currently, there's a missed opportunity in not utilizing liquidity from perpetual protocols for creating DeFi Legos. ## Introduction to Drift Protocol Drift is building a decentralized perpetual protocol using the dynamic vAMM (DAMM) mechanism on Solana. Drift V2 was launched mid 2022 and, due to its new hybrid liquidity solution, has grown as the top 5 perp in terms of TVL. Drift stands out as it successfully operated as a protocol for 2 years without a native token. Drift protocol offers many types of derivative market including perps, spot, lending, etc. ## Drift v1 and Problems ### vAMM In most cases, automated market makers (AMMs) are used for swaps, known as spot trading. Traditionally, AMMs price assets using a Constant Product*x * y=k*  formula, in which x and y represent the reserve balances of two assets in a liquidity pool, and k represents the total liquidity available. The key concept here is that *k*remains constant throughout the course of trade, due to automatic rebalancing. Perpetual Protocol, another perp exchange, building upon the foundation of AMMs, initially proposed the virtual automated market maker, or *vAMM* solution. Unlike traditional AMMs, transactions with vAMMs do not rely on underlying assets. Though the same *x * y=k*  formula is used, it is important to note that k is pre-determined and fixed in a vAMM model, as all trades occur within this virtual pool. For example, if users want to leverage 5x on SOL using 1000 USDC, they need to send 1000 USDT to a vault. In return, the protocol credits 5000 vUSDC into the vAMM for purchasing SOL and then they have corresponding SOL exposure. Drift V1 was built on top of this concept, with two innovations: re-pegging and adjusting liquidity. Re-pegging means effectively updating the quoted assets price in accordance with the oracle price (asset price), making trades happen in the deeper liquidity region. By being in the deeper liquidity region, trades are executed better. The oracle feeds price data to the vAMM and sets it as the latest 'terminal (start) price', then the collected fees are added to the pool to meet the price adjustment, ensuring sufficient liquidity within the active price range after adjustment . In the initial vAMM model, parameter ‘k’ is set when a pool is created. However, in Drift V1, ‘k’ can be adjusted many times. Put simply, to further deepen liquidity, the accrued trading fees are injected into the vAMM pool similarly to adding liquidity to Uniswap V2, then resulting in an increase on ’k’. ### The Problem In traditional spot-AMM or Peer-to-Pool models, there is always one party acting as the passive liquidity provider (LP), with traders' profits coming from these passive LPs. However, in the case of a vAMM without passive LPs, traders act as ‘LP’ for each other, meaning that for one trader to profit, there must be another trader as the counterparty. Therefore, no one wants to be the last trader left. As a result, most people prefer to strategically open and close positions to execute arbitrage strategies, ultimately creating a player versus player (PVP) market. If there are always a large number of traders, such a PVP market can continue to operate normally. However, the problem arises that the market may collapse when arbitrageurs are unable to obtain sufficient profits. The pre-set 'k' sets the start price. When the current price is higher than the start price, positions are net long and vice versa. In most cases, the fair price is driven by CEXs, so the vAMM pool needs to repeg using collected trading fees as the fair price deviates from the start price. But at the same time, funding fees are paid by collected trading fees. When deviation gets larger, the cost for repegging and k-adjustment will increase as well. Although the funding fee is capped, the cost of repegging & k-adjustment could drain the Insurance Fund, then arbitrageurs gain less. ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/28556c10ae19.jpg) Arbitrageurs are going to leave if the yield is not attractive anymore for them, most of the collected fees are used to provide a ‘better’ price for retailers. The problem is: no arbitrageurs, no volume, no fees. Due to vAMM's asymmetric trading model, funds could be drained by price manipulation if there is poor leverage management. A manipulator can be allowed to open two high-leverage positions one after the other, pushing the price to a point where the profit from one position could cover the loss from the other; this profit is derived from the funds of other users. Furthermore, the disparity between positive and negative PnL could potentially result in insolvency. ## Drift v2 Core Design Drift V2 introduces a hybrid liquidity solution, aiming to provide more collateral and lower the risk of vAMM itself. For Drift V2, there are 3 types liquidity guarantee the best price for traders when an order is executed: - Just-in-Time (JIT) Liquidity - vAMM Liquidity - Decentralized Orderbook (DLOB) Liquidity ### JIT Liquidity When a market order is submitted by a trader, it is broadcasted to a network of market makers composed of Keepers and initiates a Dutch auction. By default, the Dutch auction lasts for 5 seconds (20 slots), and the starting price is determined by the oracle price and the inventory status of the vAMM. During this process, market makers continuously front-run in a race, with the price changing from best to worst for the taker. JIT auction gives traders the opportunity to experience zero slippage in their trading activities. ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/dd4a181121c7.jpg) ### vAMM Liquidity In Drift V2, vAMM will act as the backstop liquidity if no MMs execute market orders. Drift v2 AMM features in-built bid/ask spread and Drift Liquidity Provider (DLP). DLP is a passive liquidity provider with active functions, opening opposing positions against vAMM. Users could add liquidity to the specific pool and acquire a share of its taker fees. In-built bid/ask spread makes the Drift vAMM wider liquidity rather than just fills at current oracle price in the auction process. Through this process, the long/short imbalance with a higher cost is eased. Regardless of if it is vAMM or oracle-based, perpetual markets are always zero-sum traders that make profit from others’ loss. This contrasts V1s, where traders have ‘real’ liquidity as their PnL, which is significant as more collateral is provided. After integrating DLP into DAMM, liquidity depth will be improved by increasing ‘k’, and the 80% trading fee will be distributed to DLP as a reward. Drift V2 also introduces a new oracle-based pricing mechanism, which optimizes the process of repegging and the setting of spreads by considering factors such as the volatility and inventory. This ensures that arbitrageurs engage in activities to balance long and short positions efficiently. The price movement in V2 relies on oracle feeds instead of the long/short imbalance. The chart below shows that net open interest (OI) could strike a balance at some times. **Decentralized Orderbook (DLOB) Liquidity** Drift V2 provides a decentralized orderbook network. The mechanism behind it is very simple - a network of bots called Keepers are responsible for recording, storing, and matching and filling submitted  limit orders. Every Keeper bot has its own off-chain orderbook. Orders are sorted by price, age, and position size. When one order meets the trigger price, the keepers will submit to trade against DAMM. In return, keepers  receive a proportion of the trading fee determined by a mathematical formula, which is further explained [here](https://docs.drift.trade/about-v2/keeper-incentives) . It's worth noting that if there are buy and sell orders with exactly the same parameters (i.e. buy 1 SOL for 110 USDC <> sell 1 SOL for 110 USDC), Keepers can directly match them without going through vAMM, which can improve efficiency. ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/1abb4013bee0.png) Overall, to address the solvency, Drift V2 decentralizes order execution to real liquidity sources such as JIT, DLP, and direct order-matching in DLOB (which also means more collateral). ## Other features ### Spot Drift V2 provides spot trading and spot margin trading. In contrast to perpetual trading, all types of spot trading are based on real underlying assets. For example, the liquidity of spot trading comes from OpenBook DEX. Additionally, spot and margin trading allows users to leverage their spot by borrowing assets on Drift V2. The aim of two methods are primarily to hedge perpetual position. ### Swap Swap on Drift relies on Jupiter routing to provide the best price for users. However, the liquidity source comes from Drift V2 itself. Users are also able to leverage swap using flash loan. ### Lend/Borrow Drift lending module is similar to Aave in that it uses an overcollateral mechanism. When you deposit your assets to Drift, the assets will generate yield automatically. ## Growth Catalyst ### Incentive expection Drift launched its V1 in 2021. Until now, Drift hasn't had its own native token, missing an opportunity to incentivize user onboarding for the protocol. Despite this, Drift V2 has already achieved over 5 billion in total trading volume and nearly 100,000 users. On January 24, 2024, Drift announced that it would also become a member of the points-meta, launching its own points system for a duration of three months. Drift has a strong team and a history of rapidly iterating products. We believe that after the launch of the points system, the Drift protocol will gain a larger market share and trading volume. ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/64e58da0f75b.png) ## Solana fundamental thesis The resurgence of Solana in 2023 was exciting, particularly towards the end of the year. 1. High-quality projects such as Jito brought more liquidity to Solana. 2. The meme trend also saw a boom due to Solana's technical advantages, with Bonkbot earning $10M fees in December and BananaGun launching its own Solana version. 3. Depin and RWA narrative brought more exposure to Solana. The increase in TVL, users, and on-chain activities brought about by the thriving Solana ecosystem will be the fundamental driving force behind the growth of the Drift protocol. Drift will have more opportunities to capture the yields generated by DeFi protocols and the launch of active assets will bring about demand for leveraged trading. ### Potential opportunity We’ve observed many perpetual DEX’s growing with different stategies. One of Drift’s biggest advantages is its leader position in Solana ecosystem. Since the meme season began, more and more long-tail assets emerged with large volume and good liquidity. If Drift could work like HyperLiquid and list more popular tokens, Drift could become a main degen hub on Solana. The TVL of Drift V2 currently sits at $171 million, ranking 5th in the derivatives category on DeFiLlama. Out of Drift V2's TVL, DLP accounts for approximately $16 million. Market Maker Vault represents $16 million and Insurance Fund Vault $10 million. The remaining TVL is composed of depositors' assets. Drift currently serves 133k users and has facilitated over 9.4M trades, indicatig t Drift V2 has a sufficient asset and user base. ![](https://shoal.xyz/research/writing/drift-protocol-solanas-largest-perpetual/img/9bdf1340ce6b.jpg) Although the daily trading volume is between $50 million to $100 million which is , it lags significantly behind competitors in other ecosystems. At the same time, there is a lack of trading intent and the yields generated by sub-products are not very attractive to users. We believe that trading will improve with the launch of Drift's incentive plan. As a series A product, it is worth noting that a higher profit growth brought by token incentives could enhance the underlying yield for depositors, thereby creating a flywheel effect. ## Conclusion From V1 to V2, we can see a very clear trend of improvement in Drift's vAMM solution, which is the continuous addition of real liquidity and the strengthening of the oracle's intervention in pricing. Although it seems to negate the original design concept of vAMM, in reality, the combination of real liquidity and vAMM can provide users with a better experience when trading long-tail assets. With its token and points system, Drift will become increasingly profitable. However, Drift also has apparent shortcomings. Thanks to the high performance of Solana, the hybrid liquidity solution also turns the transactions on Drift into a sort of order flow mode. So Keepers and DLP, serving as liquidity providers, cannot achieve equal status in executing transactions so that the attraction of DLP is not strong enough. We believe that the upcoming token may bring more possibilities for improvements to Drift. ## Reference - [https://docs.drift.trade](https://docs.drift.trade) - [https://blog.perp.fi/a-deep-dive-into-our-virtual-amm-vamm-40345c522eeb](https://blog.perp.fi/a-deep-dive-into-our-virtual-amm-vamm-40345c522eeb) - [https://driftprotocol.medium.com/deep-dive-into-drifts-dynamic-vamm-part-1-3-c2121fbce3c4](https://driftprotocol.medium.com/deep-dive-into-drifts-dynamic-vamm-part-1-3-c2121fbce3c4) - [https://medium.com/@ragetrade/the-perpetual-pvp-ponzi-beaff4a0c662](https://medium.com/@ragetrade/the-perpetual-pvp-ponzi-beaff4a0c662) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # Underwriting LRTs: Balancing High Yield with Novel Risks > Underwriting the risk of Eigenlayer liquid restaking tokens within the DeFi ecosystem - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2024-02-14 - Canonical: https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/ - Keywords: stablecoins, crypto, DeFi, restaking, liquid staking, yield, tokenization, security, infrastructure, Ethereum ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/0f8c3154e241.jpg) ## Introducing Liquid Restaking Tokens The advent of Eigenlayer gives rise to a novel exotic collateral type: liquid restaking tokens (LRTs). LRTs are to restaking what liquid staking tokens (LSTs) are to staking—tokenized representations of Eigenlayer restaking positions. LRTs bear novel risks at the promise of higher yields paid for by the protocol-level applications (actively validated services or AVSs) that use EigenLayer to rent Ethereum's crypto-economic security. LRTs lean into the [composability](https://www.shoal.gg/p/liquid-restaking-tokens-a-new-frontier) of public blockchains, fostering the financialization of EigenLayer’s pooled security —allowing users to not have to choose between liquidity and yield. Put simply, why would a user forfeit DeFi yield opportunities to lose liquidity and restake their ETH or vice versa, when instead they could forgo opportunity cost and chase yield through both. Much like LSTs, LRTs will be the collateral of choice for many crypto users across lending protocols, CDP stablecoins, DEXs, perpetual futures applications and more. [EigenLayer views LRTs](https://docs.eigenlayer.xyz/eigenlayer/risk/risk-faq#lrt-related) as a financial buffer that safeguards EigenLayer and AVSs from external financial risks associated with LRTFi. As with any novel collateral, the question arises: "How can DeFi protocols underwrite LRT risk profiles to adopt them properly?". This understanding is essential for building sustainable and capital-efficient protocols. ## More Risk, More Reward An LRT’s risk profile is composed of the incremental risk from [restaking ETH into EigenLayer](https://docs.eigenlayer.xyz/eigenlayer/overview/protocol-features), and the risks associated with the implementation of the LRTs. ETH restaked into EigenLayer is delegated to an operator. An operator performs validation services for Ethereum and for the AVSs they choose to secure. By opting to restake with a particular AVS, stakers and operators receive rewards from AVSs paying for EigenLayer security, and also accept the risk that their deposited assets may be slashed (taken away as a penalty) according to the rules in the AVSs slashing contract. LRT providers deploy a set of smart-contracts on Ethereum that enables users to deposit/withdraw ETH/LSTs, and mint/burn LRTs. The risk profile between LRTs will vary depending on the LRT's operator set and which AVSs are being secured. To start, the incremental slashing risk from restaking will be low given EigenLayer's [slashing veto committee](https://docs.eigenlayer.xyz/eigenlayer/security/multisig-governance) and [screening of AVS](https://docs.eigenlayer.xyz/eigenlayer/avs-guides/avs-development-guide)s. But, in a future world with infinite AVSs, there are 2n-1 permutations of AVSs that can be secured by an operator, *n*AVSs secured. So, there can be lower-yielding, conservative LRTs and higher-yielding, risky ones —analogous to why there are bond credit ratings. ## Overview of LRT Risk Profile This section will introduce the risks inherent in LRTs, given their architecture, and the risks created by introducing LRTs into the broader crypto-economic landscape. ### AVS Slashing An AVS is any system that requires its own distributed validation semantics for verification. The design space for what protocols can create outsized value as AVSs is infinite ([overview of first 12 major AVS)](https://www.blog.eigenlayer.xyz/twelve-early-projects-building-on-eigenlayer/). So, in the long run, the biggest risk that LRTs will bear will come from novel AVS slashing conditions. One major value proposition of LRTs is enabling users to outsource risk management to the LRT provider i.e. the LRT provider chooses an operator set and underwrites which AVSs to secure. When choosing an LRT provider, users should consider: - Does the LRT provider have a comprehensive understanding of the protocol risks associated with each validated AVS? - What is the LRT provider’s delegation strategy? Is it open source or proprietary? Does the LRT provider’s community have input in delegation? ### Operator Malpractice Operators are tasked with managing validators that run the Ethereum client and software provided by the AVSs that are being secured. Operators register in EigenLayer and allow restakers to delegate ETH to them. On EigenLayer testnet we see institutional validators. Figment, Blockdeamon, Chorus One, P2P, Google Cloud, Kiln, etc, that will likely only secure the most robust AVSs, and smaller operators who will aim to differentiate by supporting more AVSs to improve potential restaking rewards to delegates. Slashing is fundamental to Ethereum and EigenLayer's crypto-economic security model; it deters malicious acts by levying economic penalties against validators who act against the interest of the network. [This article sheds light on the real vs perceived](https://unsworth.substack.com/i/139249760/risk-on-slashing) risks of slashing in the context of Ethereum and EigenLayer. When evaluating EigenLayer operator slashing risk, the following considerations should be made: - Who is the operator(s) for the underlying [EigenPods](https://docs.eigenlayer.xyz/eigenlayer/restaking-guides/restaking-user-guide/native-restaking/create-eigenpod/)? - Does the operator have a proper risk mitigation strategy in place to avoid slashing and downtime? - Does the operator’s dev-ops team have enough bandwidth to combat unforeseen circumstances relative to the number and complexity of AVS being secured? - Does the operator have off-chain insurance to compensate for potential slashing events? - What is the commission structure of the operator? ### Supported Deposit Assets As of time of publishing, LRT providers can choose to accept ETH (to [natively restake](https://docs.eigenlayer.xyz/eigenlayer/restaking-guides/restaking-user-guide/native-restaking/)) and the following LSTs (to [liquid restake](https://docs.eigenlayer.xyz/eigenlayer/restaking-guides/restaking-user-guide/liquid-restaking/)) as depositable assets: ankrETH, OETH, LSETH, rETH, stETH, cbETH, osETH, swETH, mETH, ETHx, wBETH, sfrxETH. ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/3c3e0b2e894b.jpg) LSTs create value by enabling users to earn ETH staking yields and maintain liquidity without having to run a validator node, which requires 32 ETH. LSTs bear risk from Ethereum slashing, exploits, and secondary market volatility. If the LSTs node operators act maliciously or unreliably, users can have their funds slashed. Security risk arises from relying on the node operators to secure their private keys and trusting the robustness of the LST protocols smart contracts. Finally, LSTs, not pegged to their underlying assets, can face price fluctuations; market events and lower trading volumes can significantly affect their stability compared to the underlying assets. If LST(s) are accepted by LRT providers, then the LRT will bear the risks of the underlying LST(s). - Is the LRT composed of natively restaked ETH, or restaked LSTs - If restaked LSTs, who are the node operators for those LSTs? - What percentage of the overall deposits does each type of accepted collateral make up? ### Access to Liquidity All funds [unstaked from EigenLayer](https://docs.eigenlayer.xyz/eigenlayer/restaking-guides/restaking-user-guide/liquid-restaking/withdraw-from-eigenlayer) go through a 7-day escrow period before being able to be withdrawn, creating duration risk for LRTs. Furthermore, many LRT providers have not enabled withdrawal functionality. - What is the TVL of the LRT? - Is there a healthy amount of secondary market liquidity for the LRT? - What is the redemption process for the LRT? - What are the short-term liquidity incentives LRT providers are offering? ### Smart Contract - What protocol architecture risks exist for the LRTs? - How are rewards being paid out? Rebasing or value accrual? - What is the fee structure of the LRT provider? - How are admin multi-sig permissions structured? What permissions are involved in transferring assets and pausing withdrawals? The following risks are not inherent to the LRT but arise due to the LRTs' adoption across the broader crypto-economic landscape. ### Oracle - Are there reliable and robust price oracles in place to ensure accurate pricing of the LRTs? ### Governance - What governance risks exist for the LRTs? - How are AVSs chosen to be secured? - To what extent can governance be used to ‘king make’ AVSs? What incentives does this dynamic create? ### Cross-Chain - In the case of cross-chain LRTs, how is bridging implemented? Are canonical or non-canonical bridges being used? - In the case of non-canonical bridges, how is the LRT provider approaching issues with fungibility with the L2 enshrined bridge and the tradeoff of batch latency? ### Centralization Concerns - What is the market structure of LRTs? - To what extent do LRTs have a  centralizing effect on EigenLayer’s shared security offering? ### Looping Risk In lending markets, looping LRTs can trigger widespread liquidations, a risk confined to specific lending markets without impacting EigenLayer's security. This mirrors the 2022 stETH depeg event, where stETH's price risk was contained within the lending market, leaving Ethereum consensus unaffected. ## Addressing The Risks of LRTs Addressing and managing the risks of LRTs is necessary for them to scale securely and be widely adopted. To do so, it’s required to understand the benchmarks that can be used to underwrite LRT risks and how to incorporate them into DeFi protocols for parameterizing markets since they are quantifiable and endogenous to LRTs. ### Benchmarks For Underwriting LRT Risks LRTs have the work cut out for them when mitigating risks for their users. They must properly underwrite and select a portfolio of AVSs to secure while performing in line with the expectations of their ideal user. Selecting the right AVSs to opt into requires LRTs to understand the slashing conditions of each AVS as well as the infrastructural design decisions that the AVSs include, one example being the underlying consensus mechanism of an AVS. With each AVS a liquid restaking provider opts into, they add to the set of slashing conditions that the node operators are committed to not violate. Violating slashing conditions causes LRT holders to incur a direct economic loss to their position. Under traditional Ethereum slashing conditions, slashed validators incur an initial deduction of ETH, followed by a potential correlated slashing penalty after 16 days, and ending with their removal from the beacon-chain after a 38-day period. Typically the ETH lost to a slashing is marginal compared to the total ETH staked with the liquid restaking provider, however if a large sum of validators are slashed within a close period of time they can become subject to a correlated slashing penalty which contributes to a significantly greater loss than in typical scenarios. Under the traditional Ethereum slashing conditions, slashings are not prevalent, and in the context of this paper it should be noted that they are not tied to AVSs in any way. However, AVSs will have their own set of complex slashing conditions, and it’s certainly beneficial to understand the propensity for validators to be slashed under the scope of an AVS’s design as well as the impact each slashing actually has on the slashed validator. This implies that it’s also important for LRTs to properly configure their validator set profile to minimize the risk of slashing if they are natively restaking. The majority of LRTs will most likely begin by implementing permissioned node operator sets to ensure the quality of validators operating on their behalf. Client and geographic diversity can play a big role here by limiting the centralization risks of a validator set. Distributed validator technology (DVT) and trusted execution environments (TEEs) can be used to improve the reliability and security of a validator set further. DVT further increases the diversity of the validator set while TEEs essentially act as anti-slashing software by protecting the validators using them from violating slashing conditions (for example only allowing the validator to sign off on a block once, avoiding potential double signs). Hopefully in the future we’ll see modular anti-slashers that can be extended to a variety of AVSs that share similar functionalities and slashing conditions making the application of TEEs more extendable to different AVS designs. If LRTs are not natively restaking they can expand the variety of liquid staking tokens that they accept to deposit – selecting those LSTs who’s own validator set meet the aforementioned security recommendations that match the LRTs desired risk profile. The potential permutations of AVS strategies scales rapidly the more there are: 2n- 1 for n AVSs. This requires them to pick an optimal portfolio of AVSs to fit their desired risk profile and strategy. Some have even called for a standard to be created for a ["vanilla" portfolio](https://idanlevin.xyz/preventing-restaking-centralization-risks.html) of AVSs that fits a widely accepted risk profile. In both scenarios, AVSs must identify methods of characterizing the aforementioned risks and quantifying their real impact to the LRT to justify the yield returned to restakers for securing the portfolio of AVSs. ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/bb19d4e39830.jpg) Key Benchmarks - AVS slashing conditionsPropensity of slashing under AVS slashing conditions - AVS consensus mechanism - Validator client diversity - Validator geographic diversity - Validator DVT integration - Validator TEE integration - Permissioned vs Permissionless node operator sets ### How DeFi Protocols Can Incorporate Underwriting Methods Incumbent DeFi protocols are not readily designed to incorporate these infrastructural security benchmarks. They rely more on liquidity, which is another bottleneck for these assets. So, if most of the benchmarks for underwriting LRTs is infrastructural, and if it's not yet been proven that there will be deep liquidity for LRTs then we find ourselves quite limited in the current landscape to facilitate DeFi products for LRTs. That is, if most of our benchmarks are infrastructural, it doesn't make sense to price the risk of these assets according to market price, which is heavily dependent on liquidity. Instead, we might be able to look toward pricing risk based on the soundness and solvency of the asset. After all, LRTs are really just a restaked representation of staked ETH, which is a staked representation of ETH. ETH itself is much less volatile than the rest of crypto. However, suppose LRTs have far less liquidity available. In that case, the market price of LRTs will be much more volatile than that of ETH, exposing restakers to a greater risk of liquidation. DeFi lending is the arena in which the underwriting of risk is most necessary as it's been seen to be the largest DeFi use case for liquid staking tokens and will most likely also be the largest DeFi use case for liquid restaking tokens. The current generation of DeFi lending protocols operate based on liquidity and governance. That is, service providers like Gauntlet parameterize markets by analyzing the liquidity available for an asset and running scenarios to identify conditions that could lead to large scale liquidations and insolvency. As we've already discussed, adopting this underwriting methodology for market parameterization does not account for the inherent infrastructural risks to LRTs. Rather, it exacerbates the liquidity risks associated with LRTs and puts lending protocols at greater risk of bad debt, especially since many of the incumbent protocols utilize pooled lending, sharing risk across the entire protocol/pool. Aave is the most relevant in this generation of lending protocols given their large exposure to LSTs and recent improvements aimed at supporting them in a more capital efficient and secure manner. Aave Aave, originally called ETHLend, was one of the first lending markets on-chain. As an open-source and non-custodial platform, Aave allows participants to engage directly with each other without the need for traditional financial intermediaries. Users who provide liquidity to the market by depositing into Aave's liquidity pools can earn interest, while borrowers can obtain loans by over-collateralizing, ensuring the security of the loans. Aave supports a wide range of assets, offering features like variable and stable interest rates, as well as innovative DeFi concepts such as flash loans, which allow for the borrowing of assets without collateral, provided that the loan is returned within the same transaction block. This flexibility and the protocol's emphasis on security and transparency have positioned Aave as a key player in the DeFi ecosystem. When it comes to supporting staked assets and potentially restaked assets in the future, the following factors bear the highest impact. **Governance-Based Market Parameterizations -**Aave, advised by service providers like Gauntlet, votes through DAO governance to set market parameters by assessing asset liquidity and potential for large-scale liquidations. However, this approach overlooks the structural risks to LRTs, increasing liquidity risks and the potential for bad debt in pooled lending systems, where risks are shared across all participants. **Aave E-Mode -** The High-Efficiency mode feature (or "eMode") is designed to maximize capital efficiency when collateral and borrowed assets, such as ETH, LSTs, and LRTs, are correlated in price. Other assets can be used as collateral, but only assets of the same category can be borrowed in E-mode; otherwise, the user would have to exit the E-mode configuration. Ultimately, it enables a greater LTV for borrowers. However, because it is a more specialized configuration, it takes additional oversight from service providers to properly parameterize the market, especially considering that recursive borrowing is a prominent strategy made more efficient with higher LTVs. This is notable because recursive borrowing is the act of levering up on the collateral asset to increase exposure to it (in this case, levering up on staked assets to increase exposure to the staking yield), which increases the [risk](https://x.com/0xDuckworth/status/1749482493726875761?s=20) of [cascading liquidations](https://t.co/oShjw3XDbm) from price volatility and decoupling of LSTs from the base ETH. **Aave Killswitch -**The Killswitch is a framework for Aave to limit LST borrowing power when abnormal conditions arise (i.e. price decoupling of LRTs). It was recommended by Gauntlet that in the such an event killswitch be enabled to 1. Automate liquidation threshold reduction to liquidate the riskiest positions gradually. 2. Freezing the LST deposits and making the LTV 0 so there could be no more borrows. 3. Doubling the slope of the interest rate curve to reduce utilization. 4. Lower the LTV to non-E-mode LST parameters to further reduce the impact. However, through the governance process, an option was chosen to only freeze LST deposits and drive the LTV to 0. However, this is concerning because price decoupling occurs in a continuous fashion, so even if it prevents additional insolvencies in the market, it does not reduce the trouble with the existing risk. It kind of just leaves positions sitting to either get liquidated or recover from the decoupling. A new generation of DeFi protocols is evolving to increase modular and permissionless design, enabling their markets to be more composable to what the free market desires rather than being subject to traditional governance procedures. While many new lending protocols like Ajna and Euler are entering the space, the two we'll discuss here currently support LSTs and LRTs, whereas the others do not. These two protocols are Morpho Blue and Ion Protocol. Morpho Morpho Blue is a lending market that recently launched as a follow-up to Morpho's previous product, Morpho Optimizers. It utilizes isolated lending markets, enabling permissionless market creation. This is complemented by externalized risk management, oracle agnostic pricing, and permissionless interest rate modules. Each parameter is selected at market creation and persists in perpetuity (i.e., they are immutable). Like Aave, they must adhere to governance specifications when selecting the liquidation loan to value ratio and interest rate model. In its current form, Morpho Blue is a much more modular version of Aave, with markets siloed and tailored to an individual or entity's desired parameters, which is a difficult task in itself to design. It is hard to say whether users will take advantage of such freedom or whether the responsibilities of curating risk management strategies and designing oracles and interest models will flow to more established service providers. Ion Protocol Ion Protocol is a lending protocol specifically built for staked and restaked assets. It is currently live on testnet, in the final stages before launching on mainnet. Ion Protocol takes a different approach to market parameterization, by underwriting the endogenous infrastructure risks of LRTs to optimize capital efficiency and minimize the risks of liquidations and protocol insolvency. Ion utilizes isolated markets, solvency-based underwriting, yield reactive interest rates, and partial liquidations to give users direct access to sustainable and efficient ETH-denominated yield. - **Solvency-based underwriting -**Ion Protocol was designed to be price agnostic. Price-agnostic markets utilize the reserve ratio of LSTs and LRTs rather than their market price. That is, LSTs and LRTs can be valued according to their circulating supply relative to how much ETH is staked or restaked within a token's provider's validator set. By valuing LSTs and LRTs, Ion Protocol creates a scenario where borrowers are only liquidated if a slashing event directly impacts the provider's validator set. This significantly reduces the chances of liquidations and enables greater capital efficiency – Ion can raise LTVs from the industry standards of about 0.8 to 0.9 and above. This is all powered by ZK proof of reserve in partnership with Succinct. - **Collateral-specific interest rates -**Ion's interest rate model is strictly defined per collateral. It requires that the borrowing rate be less than the staking yield to provide a profit margin to borrowers, enabling them to lever up and continue to earn efficiently. They provide a minimum borrow rate for instances where the staking yield drops too low to sustain the profit margin reasonably. However, if the staking yield increases, the earnings generated get directly passed to lenders and borrowers. Each collateral type's market is unique and parameterized to create an efficient borrowing experience while properly compensating lenders. ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/b642e550eaad.jpg) - **ZKML Slashing Prediction -**Ion Protocol has partnered with Modulus labs to develop a ZKML model for predicting the propensity of slashing within a validator set. This will help inform the market parameterizations. It acts as a mechanism to unbiasedly quantify the probability that a validator will experience a slashing event and then aggregates that to the level of the validator set. Ion Protocol is becoming the most efficient option for stakers and restakers to participate in DeFi lending. By taking an asset specific approach to their mechanism design, the team has designed the protocol to incentivize the things specifically pertinent to staked and restaked assets. ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/3fb265f34460.jpg) Concurrently with the new generation of lending protocols, we have seen the rise of new and innovative CDP protocols. Ebisu Finance Ebisu Finance is a yield-bearing stablecoin backed by LRTs. Ebisu unlocks capital efficiency for restaked assets by enabling users to draw dollar-denominated credit (ebUSD) against natively restaked ETH and LRTs via a non-custodial, decentralized stablecoin. ebUSD gives users access to a stable store of value while enabling yield generation through AVS rewards and Ethereum staking rewards. By driving demand for LRTs, Ebisu also contributes to scaling the restaking ecosystem, bolstering Ethereum's shared security and economic alignment. With any lending protocol, it is imperative to ensure that bad debt does not accrue in the system. Ebisu lending implements isolated collateral positions so that the system can work smoothly to liquidate the riskiest debt positions. ebUSD can be redeemed against its underlying collateral at face value. eg. 1 ebUSD can be redeemed for $1 USD denominated in restaked collateral. Redeemed ebUSD is used to repay the riskiest debt position, and transfers the respective amount of restaked collateral from the liquidated position to the redeemer. Additionally, Ebisu will have a stability pool, as is common amongst CDP stablecoins. The Stability Pool, funded by users, safeguards loans by providing ebUSD as liquidity to cover debts from liquidated debt positions. This ensures that the total supply of ebUSD is solvent and adequately backed. Upon the liquidation of any debt positions, an ebUSD amount equal to the debt position’s outstanding debt is eliminated from the Stability Pool to settle this debt. Concurrently, the remaining collateral of the liquidated debt position, net of liquidation fees, is transferred to the Stability Pool. Depositors in the Stability Pool are then eligible to withdraw a portion of this liquidated collateral, pro rata to their proportion of the Pool's total balance. This arrangement is designed to leave a net benefit for depositors, as the value of the collateral is generally higher than the amount of debt that was extinguished. The use of a stability pool enables Ebisu to process liquidations without having to price the LRT collateral. ![](https://shoal.xyz/research/writing/underwriting-lrts-balancing-high/img/96bbbf0a2d50.jpg) ### Future Exploration So far, we’ve discussed the benchmarks and primitives actively being explored and developed that can be used to underwrite the riskiness of an LRT for its use in DeFi. However, some questions remain. 1. Can we reliably use these benchmarks and primitives to scale restaking, particularly liquid restaking tokens, to the same heights we’ve seen liquid staking tokens scale? 2. Where can we turn to formalize these concepts further and standardize the metrics so that we can onboard bigger players? Answering these questions is a challenging feat. Regarding the first question, if LRTs and restaking can be sustainably supported in DeFi, then it’s possible for them to become as ubiquitous of a representation of ETH as LSTs if not more. Getting to this spot requires us to spend more time on the second question, and work on making standards and formalized concepts to help us on the way. At the beginning of this section, we discussed that the risks inherent to LRTs stem from their selection of AVSs, so it makes sense to formalize some kind of portfolio theory for AVS selection. Some have suggested that this could be a function that takes each potential strategy (2^n- 1 strategies for n AVS) and identifies a max loss by summing the max loss of each AVS included in a strategy, with the max loss being defined as the maximum percentage of stake that can be frozen/slashed by each AVS. This makes sense! Although, it may still be too simple to capture all of the benchmarks we mentioned earlier truly. One alternative could be to follow Ion Protocol's lead by utilizing machine learning to create a feature set and objective function similar to the MaxLoss objective function in order to identify the propensity of slashing for each AVS and an expectation of the loss. After quantifying risk, it also makes sense to create a library of different metrics that can be used to help explain the choices made for a portfolio as well as its performance. One such metric that has been suggested is one that is on par with the Sharpe Ratio, a measurement of risk-adjusted relative returns. For restaking, the risk-adjusted returns could look something like [(staking rewards - infra cost) / MaxLoss](https://mirror.xyz/renzoprotocol.eth/i4V4QVeXKSkNX4_3azPN5yfKNK55Xi1isphRKXhF3X0). Others might include something like a yield beta, or how well the restaking yield tracks the underlying performance of the staking yield for a particular AVS as well as for a particular strategy or portfolio. All in all, we are at the precipice of a boom of newly created products to help further expand the benefits of crypto-economic security and allow more participants to share in the rewards. It's important to understand, benchmark, test, and formalize the kinds of mechanisms and metrics that can help protect against and inform users of the risks associated with LRTs and the market's they are being used in. ## Source - [Preventing restaking centralization risks](https://idanlevin.xyz/preventing-restaking-centralization-risks.html) - [Restaking portfolios 101 — Renzo Protocol](https://mirror.xyz/renzoprotocol.eth/i4V4QVeXKSkNX4_3azPN5yfKNK55Xi1isphRKXhF3X0) - [2.8.7 Slashing](https://eth2book.info/capella/part2/incentives/slashing/) - [V3 Overview - Developers](https://docs.aave.com/developers/getting-started/readme) - [Morpho Overview](https://docs.morpho.org/concepts/overview) - [Ion Protocol](https://docs.ionprotocol.io/) - [Risk FAQ | EigenLayer](https://docs.eigenlayer.xyz/eigenlayer/risk/risk-faq#lrt-related) - [Twelve Early Projects Building on EigenLayer](https://www.blog.eigenlayer.xyz/twelve-early-projects-building-on-eigenlayer/) - [EigenLayer Ecosystem Unraveled - by Ian Unsworth](https://unsworth.substack.com/p/eigenlayer-ecosystem-unraveled#%C2%A7risk-on-slashing) - [Liquity Docs](https://docs.liquity.org/) - [Mitigating Risks and Best Practices for Restaking in EigenLayer](https://coboargus.substack.com/p/mitigating-risks-and-best-practices) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # Perpetual Pre-Launch Futures > How perpetual futures exchanges enable traders to leverage trade assets that have not yet been launched - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-02-06 - Canonical: https://shoal.xyz/research/writing/perpetual-pre-listings/ - Keywords: crypto, tokenization, Ethereum, Research ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/6c62b9e728c9.jpg) *Special thanks to [Xulian](https://twitter.com/KingJulianIAm) from Hyperliquid and [Julian Koh](https://twitter.com/juliankoh) from Aevo for feedback and input on perpetual pre-launch tokens and their design mechanisms.* ## Introduction Perpetual futures (perps) have garnered significant attention, particularly with noteworthy exchanges such as Binance, FTX ([gg’s](https://s3.amazonaws.com/pix.iemoji.com/images/emoji/apple/ios-12/256/coffin.png)), and decentralized exchanges such as DYDX and GMX. Perpetual decentralized exchanges (perp DEXs) stand out as pioneers in the derivatives market, empowering users to engage in on-chain trading of crypto derivatives directly from their wallets. Many offer leverage of up to 50x—a capability akin to centralized exchanges. In the rapidly evolving digital asset trading ecosystem, perp DEXs seek innovative ways to distinguish themselves beyond only offering higher leverage options. One emerging concept is perpetual pre-launch futures, a novel financial instrument that enables the trading of tokens before they are officially launched. This article delves into the mechanics and implications of perpetual pre-launch futures, highlighting their potential in a market where differentiation and early adoption are key. ## The Business of Attention and Speculation in Crypto Markets The decentralized and open-source nature of digital assets inherently fuels speculation, especially due to the instant tokenization of value. To gain early exposure to projects, savvy crypto traders often engage in "airdrop farming," a strategy to game the token distribution system to acquire more tokens at a project's inception. Similarly, pre-launch futures represent a new avenue for gaining early exposure to nascent, high-profile projects since users can trade them with leverage before launch. Selected pre-launch projects typically generate significant attention leading up to their token generation event (TGE). In an era where attention equates to value, innovative perp-exchanges like Aevo and Hyperliquid are leveraging pre-launch futures to carve out a niche in the competitive perpetuals market. The primary advantage of pre-launch perps lies in their ability to attract and retain users by offering access to exclusive assets not available elsewhere. For pre-launch perp, exchanges focus less on trading fees and more on user acquisition and growth, recognizing the long-term value in building a loyal user base. The introduction of perpetual pre-launch futures marks a significant shift in the focus of crypto trading platforms. Exchanges are moving away from merely increasing leverage, “1000x leverage”, by embracing innovative ways to trade and offering early access to tokens. This not only caters to the trader's appetite for speculation but also fosters a sense of community and exclusivity among users who are the first to trade these nascent assets. As the crypto market continues to evolve, platforms that innovate and offer unique features are likely to stand out and thrive. By tapping into the dynamics of user acquisition and the speculative nature of crypto enthusiasts, these platforms are able to acquire new users and stay relevant in a competitive landscape. ## What are Perpetual Futures Perpetual futures represent a highly profitable product in the digital asset ecosystem, functioning as derivatives. These contracts derive their value from an underlying asset, for example, digital assets like ETH. Unlike spot exchanges, where you buy or sell actual assets, dealing with perpetual contracts involves trading contracts linked to the value of cryptocurrencies. In contrast to standard futures contracts that involve an agreement between a buyer and a seller to exchange a crypto asset at a predetermined future price, perpetual futures contracts add a particular variation. Trading with crypto perps typically occurs close to the underlying asset's current price and what sets them apart is their perpetual nature which lacks an expiry date. In practical terms, consider a scenario where Ethereum is priced at $1,000. Sensing a bullish market trend, a trader might leverage perpetual futures contracts to capitalize on potential profits by using leverage. This trader could place an order of 1 ETH at $1,000 using 3x leverage which multiplies the position size by three, leaving the trader with a $3,000 position by using only $1,000 as collateral. While leverage magnifies returns, it also increases the risk of substantial losses, making effective risk management crucial. Perpetual futures often involve funding rates, exchanged between long and short positions to align the contract's price with the underlying asset and traders may pay or receive funding periodically. However, the core allure of perps are using leverage on a variety of assets without having to purchase the underlying asset. ## What are Pre-Launch Futures Pre-launch token perps are derivative contracts allowing traders to speculate on the future price of a digital asset before it is officially launched. Investors can take positions based on anticipated market value, but it involves risk as actual performance may differ upon launch. These contracts do not grant ownership of the underlying asset, providing flexibility for long or short positions. Since limited information is available pre-launch, traders rely on project details for informed decisions which might include tokenomics, and last raise valuation. Pre-launch futures typically operate without an index price and sometimes without a funding rate. However, upon activation of the token's spot market, exchanges promptly incorporate the index price and implement a funding rate. - **Index Price:** Initially absent in these futures, the index price is the average price of the asset across major exchanges and serves as a benchmark for the contract. - **Funding Rate**: A fee paid to keep a position open, with a positive funding rate, longs pay the shorts and vice versa. The rate incentivizes traders to take long and short positions opposite of where the consensus is. - **Spot Market:**Markets where the traded assets are immediately delivered to the buyer or seller and not based on contracts. Simply put, this implies that pre-launch perp will align with the spot price once the spot market becomes operational, thanks to the funding rate mechanism. Importantly, users can engage in trading before the spot market goes live, allowing them to speculate on the starting/listing price of the token by taking long or short positions on pre-launch token futures. In the typical process of launching a new market, exchanges might prioritize the release of tokenomics and wait for token confirmation before enabling trading. Announcing the token supply is a crucial step in this process, since it gives the team and traders a clearer understanding of the expected price of the underlying market. ## Price Discovery The initial value of a derivative typically aligns with the protocol's valuation. For instance, if the protocol's valuation is $10 billion with a total token supply of 1 billion, the initial price per token is determined as $10. Nevertheless, its actual value is ultimately shaped by users through long/short positions and the addition of supply and demand. Simply put, market conditions are still a factor. Once the token is introduced and commences trading on an external exchange, the pre-launch token future transforms into a conventional perpetual future. Exchanges are using measures to enhance the price discovery model, transitioning to a more sustainable approach. One example is Hyperliquid’s product, HyperPerps, which we will explore in a subsequent section. ## Performance Consider the Celestia ($TIA) pre-launch perps as a case in point. If you had purchased $TIA at its lowest point in the Aevo $TIA pre-launch market in early October, your investment would be up 6x by the start of December. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/b8eca49f4bad.jpg) We can also look at a similar example with $MEME token. If you had acquired $MEME at its minimum value in the Pre-Launch market towards the close of October, your investment would have doubled within the first 10 days of the TGE. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/4c5dcd86c123.png) This highlights the ability of pre-launch perpetuals to enable users to enter the market at a more favorable price before it's TGE, allowing for early exposure to digital assets. Now, let's explore the approaches different protocols take in managing pre-launch perpetuals and dive deep into their solutions. ## Aevo On August 9th, 2023, Aevo revealed the introduction of Aevo pre-launch token futures. The initial token earmarked for trading using this method is $SEI, preceding its official listing on the Binance Exchange. Following the token's launch and commencement of trading on external platforms like Binance, the Aevo Pre-Launch token future transitioned into a conventional perpetual future. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/3da9cc925986.jpg) Subsequently, they announced the introduction of[BLAST pre-launch futures](https://docs.aevo.xyz/aevo-exchange/perpetuals-specifications/blast-pre-launch-futures). However, since the tokenomics had not yet been disclosed, the Aevo Blast market operated under the assumption of a circulating token quantity of 1,000,000,000. For simplified computation, a value of $1 on the $BLAST pre-launch future suggests a fully diluted valuation of $1 billion. Upon the official launch of the $BLAST token, the market will undergo a transition to a conventional perpetual future, incorporating an index price and funding rate. Responding to market trends and the Solana memecoin euphoria, Aevo made significant announcements on December 2nd, 2023 and December 5th, 2023, introducing pre-launch futures for $JUP and $JITO, capitalizing on hype and momentum. Jupiter Exchange, a prominent Solana decentralized exchange (DEX), is renowned for its popularity, while Jito distinguishes itself by offering MEV rewards through liquid staking. $JUP is currently trading at ~$0.7, having achieved a 7x increase since the launch of pre-launch perpetuals for Jupiter. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/0b761450fb2c.png) Pre-launch token futures on Aevo stand out from regular perpetual futures due to specific features. These include an initial margin of 0.5x, allowing a maximum leverage of 2x, a maintenance margin set at 0.48x, limitations on position sizes, the absence of an index price, and the exclusion of funding payments. Additionally, the contract specifications indicate a 25 basis points (bps) taker fee, a -10 bps rebate for makers, and the use of USDC as the settlement asset. ## Hyperliquid The Hyperliquid protocol introduced a new product known as [Hyperperps](https://hyperliquid.gitbook.io/hyperliquid-docs/trading/hyperps), representing an enhancement to the traditional pre-launch futures model. Hyperps (Hyperliquid-only perps) function similarly to perpetual contracts but deviate as they do not rely on an underlying spot or index oracle price. Instead, the funding rate is calculated in relation to a moving average hyperp mark price, offering greater stability and reduced susceptibility to manipulation compared to conventional pre-launch futures. This novel derivative design eliminates the necessity for an underlying asset or index to exist throughout the entire hyperp's lifespan. Hyperps only require the underlying asset or index price for settlement and conversion to a normal perp. When engaging in hyperp trading, careful consideration of funding rates is crucial. Intense price momentum in one direction incentivizes positions in the opposite direction during the next eight hours. It is therefore essential to evaluate the opportunity thoroughly before participating in hyperp trading. *Once ABC/USDT is listed for spot trading on platforms like Binance, OKX, or Bybit, the Hyperperp tracking ABC (e.g., ABC = ZRO, TIA, PYTH, or JUP) will transition into a standard ABC-USD perpetual contract.* **Hyperp Mechanism Simplified:** - **Basic Concept**: Hyperps are similar to regular perpetual contracts but with a unique approach to price determination. - **Price Calculation**: Hyperps use an 8-hour exponentially weighted moving average of the last day's minutely mark prices. This average considers recent prices more heavily, shaping the current price. - **The Equation**: oracle_price(t) = ... calculates the price at time 't'. It involves the sum of mark prices with an exponential decay factor, preventing extreme price influence. If there are under 480 mark price samples, the initial mark price fills the gaps. A safeguard ensures the final price doesn't exceed 4 times the initial mark price. - **Sampling Method**: Prices are sampled at the first block after each minute, with timestamps rounded to the nearest exact minute. - **Funding Rate Premium**: Calculated as one-fifth of the normal interest rate and premium formula used in funding. As an illustration, Hyperliquid unveiled pre-launch perpetual contracts for LayerZero ($ZRO) on September 7th, 2023. For $ZRO, the conversion occurs when the maximum supply is 2 billion, and the assets launches. In cases where the max supply differs, ZRO-USD will settle based on the fully diluted valuation (FDV) divided by 2 billion, one week following the CEX listing. Following settlement, the hyperperp will be delisted and a new standard perpetual contract will be introduced. Regardless of the scenario, the price of the ZRO-USD Hyperperp ultimately aligns with the spot ZRO price after the token's existence. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/9407e490588d.jpg) To sum up, hyperps function similarly to standard perpetual contracts, with the distinction that the external spot/index oracle price is substituted by an 8-hour exponentially weighted moving average derived from the minutely mark prices of the preceding day. ## Helix Helix Exchange, a perps exchange on injective, was the first one to introduce the [pre-launch futures market for Celestia ($TIA)](https://helixapp.zendesk.com/hc/en-us/articles/8394568971663-Decentralized-Pyth-Network-PYTH-Pre-Launch-Futures-Listing-on-Helix). Since early access to assets is traditionally reserved for insiders, early contributors, or VCs. Helix notes they aim to disrupt by allowing decentralized trading of upcoming tokens before their official launch. This would make trading fairer by allowing all types of traders to participate in the market for highly anticipated tokens before they become widely available. On November 19th, 2023, Helix also revealed the launch of a market for the unreleased $PYTH token. Pyth Network is Solana’s native oracle network which streams financial market data to protocols, which was one of the largest token launched on Solana in 2023. ## Associated Risks Trading pre-launch perpetuals comes with certain risks that investors should carefully consider. Some of the key risks include: - **Duration and Project Development Risks:** Delays, technical issues, or changes in project direction can impact the value of the pre-launch perps. For instance, if the project delays the launch by multiple quarters, traders might be paying a higher funding rate to keep the position open and at the whim of the project launching ultimately setting them back on the trade even if they are correct on timing. - **Fees:** On some exchanges, like Hyperliquid, users could be subject to increased fees based on the funding rate pricing model. - **Price Volatility:** Perps can be highly volatile, as they are influenced by factors such as market speculation, early investor sentiment, and uncertainties surrounding the project's development,  leading to significant price fluctuations. - **Liquidity Risks:** The liquidity of pre-launch perps may be lower compared to more established assets. Limited trading volume can result in larger bid-ask spreads and difficulty executing trades at desired prices. For instance BLAST-USD on Aevo has only $3,000 in 24 hour trading volume, which is very small in comparison to other markets of listed assets. ![](https://shoal.xyz/research/writing/perpetual-pre-listings/img/90439c2f5a24.png) - **Limited Trading History:** challenging for traders to analyze historical price trends and patterns using technical analysis. ## Conclusion Perpetual decentralized exchanges (perp DEXs) allow users to engage in on-chain trading of crypto derivatives. Perps, or perpetual futures, function as derivatives within the digital ecosystem. Crypto perps notably do not have an end date and allow the use of leverage on various assets without needing to purchase the asset itself. Pre-launch futures represent a way to gain early exposure to new projects, providing users with the opportunity to trade with leverage before launch. $TIA and $MEME display the ability of pre-launch perpetuals to allow traders to engage with digital assets. Aevo introduced pre-launch futures in 2023, capitalizing on hyped upcoming token launches and offering unique features for traders. Hyperps are similar to perpetual contracts as they do not depend on an underlying spot or index oracle price. Instead, the funding rate is based upon a moving average hyperp mark price. Hyperliquid’s pre-launch perpetual contracts for LayerZero ($ZRO) is an example of this process. It is important to note that trading pre-launch perpetuals come with risks that investors should carefully consider. In this article, we covered price discovery, performance, and risks associated with trading pre-launch futures, delving into main protocols which, despite their similar designs, exhibit notable distinctions. ## Sources - [Demex Introduces STRK Perpetuals As A Pre-Launch Market](https://blog.dem.exchange/demex-introduces-strk-perpetuals-as-a-pre-launch-market/) - [Introducing Helix Pre-Launch Futures](https://helixapp.zendesk.com/hc/en-us/articles/8162141444623-Introducing-Helix-Pre-Launch-Futures) - [Spotlight: Helix Launches Pre-Launch Futures, listing Celestia (TIA) as its first market](https://blog.injective.com/en/spotlight-helix-launches-pre-launch-futures-listing-celestia-tia-as-its-first-market/) - [Pre-Launch Token Futures - Aevo Documentation](https://docs.aevo.xyz/aevo-exchange/perpetuals-specifications/pre-launch-token-futures) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- --- # Jupiter Exchange: Solana’s Dex Aggregator > Unpacking the fundamental investment catalysts behind Solana’s premier DEX aggregator. - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2024-01-18 - Canonical: https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/ - Keywords: crypto, DeFi, market making, MEV, security, infrastructure, Solana, Ethereum, Bitcoin, Research ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/3ceec81bc73e.jpg) > ***Shoal Research Contributors**:* [Gabe Tramble](https://open.substack.com/users/17294401-gabe-tramble?utm_source=mentions) ## Introduction ## The Solana Renaissance Solana is a Proof-of-Stake Layer 1 blockchain which optimizes for high performance and throughput, to deliver fast execution speeds and low transaction costs. Its integrated architecture, which is distinctly separate from that of EVM chains, enables developers to focus on building ready-to-use applications in Rust. Solana currently serves 121 protocols across its ecosystem, secured by 2,156 validators (2nd most behind Ethereum), and holds the 5th most DeFi TVL across blockchains at $1.38B. Solana has faced and overcome a great deal of adversity in its short but eventful history: from technical issues such as network instability to broader issues such as a hazardous relationship with SBF and Alameda which prompted a mass exodus of users, developers, and liquidity from the chain following the collapse of FTX. Nonetheless, co-founder Anatoly Yakovenko alongside a tight-knit community of users and developers remained positive and forward-thinking even at the lowest of times, demonstrating Solana resiliency and willingness to adapt and overcome adversity; a strong positive indicator for future ecosystem investment opportunities. As the price of bitcoin rallied in 2023 around growing speculation of a spot ETF approval by the SEC, the crypto markets finally caught some tailwinds after a long stretch of crawling sideways. The price of $SOL followed in hot pursuit, spurring a face-melting rally that saw the price jump from $9.98 on January 1 2023, to $101.51 mark on January 1 2024, marking a 917.134% return. Ironically, narrative tends to follow price in crypto sometimes, and as SOL gradually continued its strong upwards momentum in the markets, MadLads mint went live, teams began announcing points programs and airdrops, and an emerging narrative around building applications *[Only Possible On Solana](https://solana.com/possible)* due the network’s unique architecture design began to encapsulate the attention of users, investors, and developers alike. ### Solana DeFi in 2023 From January 1, 2023, to January 1, 2024, Solana recorded a significant increase in Total Value Locked (TVL) as well as its on-chain trading metrics. This period marks a significant phase in Solana's development, characterized by a substantial increase in both the value and volume of transactions despite its TVL decline following the FTX crash. ### Key Highlights: - **TVL Growth:**Solana's TVL grew from $210.08 million to approximately $1.47 billion, marking an impressive 574% increase. - **Total Swaps:** There were 314,556,244 swaps executed on the network. - **Total Trading Volume:** The platform's total trading volume reached $42,036,692,506. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/00a69acee738.jpg) Solana’s monthly DEX volume reached $23.8b in December, marking a yearly high going into the new year. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/1d91c923abc5.jpg) ## Introduction to Jupiter Jupiter launched in September 2021 as a DEX aggregator on Solana, with the purpose of providing a better trading experience for Solana users by routing liquidity from multiple sources as opposed to one. Though Jupiter was initially only a swap engine, the protocol has evolved to offer a number of different products for different users and has become a critical liquidity layer for the Solana ecosystem. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/01c059c7c7ba.png) **Three core anchors drive Jupiter’s business model:** 1.  Delivering the best UX possible 2.  Maximizing the potential of Solana’s technical capabilities 3.  Improving Solana’s liquidity landscape as a whole 2023 was a busy year for the Jupiter team, which shipped a handful of new core product offerings including a new DCA feature, limit orders, and perpetuals trading. There were a handful of various upgrades and optimizations within the core protocol as well, including an upgraded algorithm (Metis), a Bridge comparator tool, instant staked SOL > SOL swaps, and more developer tooling including the release of Jupiter Terminal and 2 major API upgrades. ### Jupiter 2023 Review: Volume - Jupiter’s $62,816,562,781 Total Volume accounts ~60% of all [Solana DEX volume](https://dune.com/queries/3339843?category=abstraction&namespace=dex&table=trades&blockchains=solana). ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/e818cf537116.jpg) Jupiter monthly volume grew **994.48%** from $649,258,200.00  on Jan 2023 > to  $7,106,000,000.00 in December 2023. November volume exceeded $16B following the $JUP announcement at Breakpoint, marking a new all time high in monthly volume. Even more impressively, much of this uptick in volume (mainly Q4) came from organic trading activity ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/30e893e3bce6.jpg) In this report, we unpack Jupiter’s product line and future plans, and explain the rationale behind our investment approach. ## AMMs and Aggregators Automated Market makers (AMMs) have been a novel innovation in the past few years in the digital asset space. On traditional exchanges like Coinbase or Binance, third party entities operate to provide liquidity so traders have a counterparty, which is the other side of the trade. These counterparties are known as market makers, since they “make” a market for traders to trade against, whilst taking a spread (fee) on each trade to remain profitable. With the advent of AMMs, traders can deploy digital assets that are market-made by math and code instead of sophisticated middlemen. By using AMMs, traders can enter and exit positions even with extremely low liquidity. One downside with low liquidity is that traders will experience slippage, which is the difference between expected and realized trade value. Traders can also lose value on a trade through the exploitation of information asymmetries in the public mempool, e.g. being front-run or sandwiched by sophisticated actors deploying MEV bots. On-chain aggregators emerged to mitigate the impact of low liquidity trades by enabling traders to place orders which route liquidity from multiple sources as opposed to one. Liquidity can be pulled from a variety of sources including AMMs; though a number of teams have built solutions which enable market-makers to tap into off-chain liquidity (i.e. a CEX position) as well to help settle trades. **The primary benefit to this is better pricing as:** 1. No gas costs incurred for CEX > on-chain transfers 2. Trades are not subject to MEV extraction. As a whole, aggregators were built to deliver a better user-experience; large content platforms such as Meta or YouTube serve as aggregators for content, where users can view videos and images from many different obscure websites and sources without having to leave the interface to visit those external websites. Google aggregates information relevant to your search query across many different websites on the internet to deliver the best match in order of relevance. Similarly, Jupiter and other DEX aggregators source liquidity across multiple venues to offer better pricing for traders on their swaps. ## Building On The SVM To better understand Jupiter as a protocol, it is important to understand the role of the Solana Virtual Machine (SVM) and how it influences protocol design choices that developers must make. A *Virtual Machine* can best be described as one single entity maintained by thousands of connected computers running a validator client of a given chain, e.g. Ethereum, and is the environment in which all smart contracts and accounts actually exist. To this day, the majority of DeFi and other on-chain activity lives and breathes through the Ethereum Virtual Machine (EVM). However, though further out of the spotlight, we believe the SVM also features a robust architecture that is bound to continue to onboard more developers seeking to build consumer-centric applications optimized for speed and performance. Smart contract code written in Rust, C, C++  is compiled into BPF bytecode by the SVM. The Sealevel engine is the key component to enabling parallel processing on Solana; as state access lists are integrated into Solana transactions (transactions include details around the particular state to be accessed) -  this lets non-conflicting transactions run simultaneously, enabling for faster overall performance. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/b636294b5192.jpg) Whereas the EVM is a "single-threaded" runtime environment, meaning it can only process one contract at a time, the SVM is multi-threaded and can process more transactions in significantly less time. Each thread contains a queue of transactions waiting to be executed, with transactions randomly assigned to a queue. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/16544999198a.jpg) The emergence of L2s like Eclipse and Nitro, which utilize the SVM for execution, demonstrate the potential for further adoption of the SVM. Rune Christensen from MakerDAO sparked a lot of debate on Crypto Twitter earlier this year when he [proposed his vision](https://x.com/RuneKek/status/1697623700013822244?s=20) for utilizing the Solana codebase for the development of MakerDAO’s app-chain. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/6c18b2121f38.jpg) One of the most common gripes with Ethereum is that gas fees increase with user activity, making for an unpleasant user experience at most times but especially amid a bull market. Irrespective of gas costs, traders’ needs are quite simple - to receive the best quote possible for their trade. Aggregators like 1inch were built to help deliver better pricing to users by pulling liquidity from multiple sources as opposed to one specific DEX; however, transacting on Ethereum, e.g. pulling liquidity from multiple different pools, is a costly endeavor and can actually worsen the problem intended to be solved - it can actually be more beneficial to trade on Uniswap where liquidity is only pulled once. Meanwhile, the opposite holds true on Solana, where gas costs less than a penny by default. The cost of pulling liquidity from multiple sources is virtually no different than pulling from one, and therefore a DEX aggregator is much more pragmatic and beneficial on a chain like Solana than an EVM chain. As the leading aggregator on Solana, we believe Jupiter is much better poised to see significant growth and adoption than aggregators on EVM chains in the long-term, which face higher costs and greater competition. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/60edd5aa0df3.jpg) The same notion applies to alternative use-cases beyond simple A for B swaps, such as structured Dollar Cost Averaging (DCA) or Time Weighted Average Price (TWAP) products for users, which will be further elaborated on below. The underlying principle remains that low gas costs unlock a great deal of flexibility for application developers on Solana, and Jupiter is a premier example of this in action. ## Product Overview ## Jupiter Swap ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/be4e9ca53935.png) Like any other decentralized trading venue, the most common use-case on Jupiter is the simple token A -> token B swap. Users can enjoy swapping for their favorite assets at competitive prices. Slippage and priority fee settings are completely customizable, general settings enable users to opt in to a direct liquidity route, to use wSOL instead of SOL, and to use versioned Txs (using the newer and better routing algorithm). Developers can also take advantage of the Swap API to natively integrate Jupiter’s routing algorithm into their dApp -[Kamino Finance](https://twitter.com/Kamino_Finance) uses Jupiter’s Swap API to enable features like single-sided deposits into their CLMM vaults (Autoswap). Jupiter currently does not charge any additional protocol fees for swaps on top of the base gas fee and associated DEX fees, though we believe that continuous growth and sustainable adoption of Jupiter and Solana DeFi can prompt the JUP DAO to vote to implement a fee at some point in the future. It will be interesting to consider how this decision may be influenced by increased network activity driving up blockspace demand and costs, and by a potential restructuring of Solana fee markets. Currently, the 1inch aggregator on Ethereum does not charge a swap fee, while CowSwap has recently proposed a[fee switch](https://forum.cow.fi/t/cip-34-testing-fee-models-for-cow-protocol/1984)which would collect swap fees with the goal to be financially self-sustainable while keeping users incentivized. ## Limit Orders ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/bc04923af87b.png) Instead of buying an asset at the current market price, traders who believe the price of the asset will change in the near-future can place limit orders. As a signed message with defined trade execution guidelines, or an “intent”, limit orders offer traders flexibility among a handful of other benefits such as better price settlement due to protection from MEV-induced slippage. This model benefits retail traders and institutions alike, and Jupiter now offers a venue for traders to place limit orders on Solana. When a user places an order to purchase 1 SOL worth of $WIF, the order is ultimately matched by a *keeper*, a trusted protocol actor responsible for monitoring prices and executing orders. Keepers function in a similar way to solvers on CoWSwap or fillers on UniswapX. Upon execution of an order, the specified assets will appear in the user’s wallet. Jupiter’s Limit Order function provides access to a wider range of token selections; as long as there is sufficient liquidity in the market, the token pair will be accessible to trade. Furthermore, users can specify an expiration time in their order, upon which any unfilled orders are canceled and refunded to the user’s wallet. ## DCA ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/c00d82154ea1.png) Dollar Cost Averaging (DCA) is a common investment strategy which involves splitting the allocation of capital over multiple trades as opposed to one; this is perfectly suited for long-term investors who are not concerned with short term volatility (e.g. buy $500 of SOL over 5 days). DCA can be useful for accumulating an asset during a bear market - the principle is to average out one’s entry price to mitigate volatility and generate greater returns over the course of time and change in market conditions. Likewise, DCA can also be helpful for taking profits in a bull market - instead of immediately selling off one’s position entirely, the DCA can help spread out sells to capture any additional upside that may occur during the unwinding. Traders also can perform weighted average price strategies (TWAPs) to buy or sell assets. TWAPs, similar to DCAing, is used typically for large orders that need to be broken up into smaller parts to prevent price impact from buying all at once which can result in slippage (loss of funds). Since orders are executed for a period of time they resemble a DCA strategy of buying “x” amount over a certain time period. Jupiter is one of a few platforms that has enabled users to execute frequent time-bound strategies on-chain, due to Solana’s high-throughput architecture ([Drip Protocol was the original!)](https://paultimofeev.substack.com/p/drip-by-dcaf-labs). Performing a DCA with low time-frame transactions on Ethereum, e.g. daily, can result in hundreds of dollars in transaction fees versus fractions of cents on solana. Even on L2 if traders wanted to execute 10 trades over 1 hour the fees could quickly add up. ## Perpetuals ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/ed222a52063b.jpg) To further add to their extensive product suite, Jupiter has also launched an LP <> Traders Perpetuals exchange earlier this year. Though still in beta, traders can trade SOL, ETH, and wBTC perps with up to 100x leverage, while LPs can lend capital to earn fees. Perpetuals are derivatives contracts resembling traditional Futures, which enable traders to take on a greater position with less allocated capital (leverage) for the purpose of capitalizing on a future price movement. On Jupiter, traders can open long or short positions on SOL, ETH, and wBTC using virtually any supported Solana token as collateral. Long positions require the corresponding underlying (e.g. a long SOL-USD position would require SOL collateral), meanwhile short positions require stablecoins as collateral. Traders can take on leverage by borrowing assets from the liquidity pool - a position on SOL-USD can be leveraged by 2x by borrowing 1x of SOL from the JLP pool. Similar to the dynamics of the GLP pool on the perps exchange GMX, Jupiter Perps utilizes the JLP pool, which consists of SOL, ETH, WBTC, USDC, and USDT. Providing liquidity is simply done by depositing any supported Solana token into the JLP pool in exchange for an equivalent amount in $JLP token. The JLP pool receives 70% of fees generated on Jupiter perps , and the price of $JLP grows congruently with the value of the underlying pool. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/42f60886343e.png) The JLP pool also benefits the greater Solana ecosystem, as Jupiter Swap is natively integrated into the perps exchange, meaning not only can any token be used as JLP collateral, but that Solana traders can benefit from better pricing for their swaps from the increased liquidity from the JLP pool. Unlike the aforementioned features, Jupiter’s perpetual exchange charges more fees for traders and LPs alike. Traders pay an hourly borrow fee, or a *funding rate*, to the pool based on the hourly borrow rate, position size, and token utilization percentage, which can be expressed as: ***Funding rate = (tokens borrowed / tokens in the pool) * 0.01% * position size*** LPs pay their own share of fees as well, for opening/closing a position, and swapping for different assets within the JLP pool: ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/90abf7cf6b9c.png) With regards to the JLP pool, it should also be noted that given the target ratios established for each token in the pool, any logic which moves the token's ratio away from the target incurs greater fees while logic that moves the ratio closer to the target incurs a fee discount. Decentralized perpetuals exchanges, popularized by GMX and dYdX, are still generally underdeveloped compared to their CEX counterparts and have *lots* of room for growth and adoption. Perps are another example of a low-latency application which benefits from Solana’s fast execution and low transaction costs, though Jupiter will face competition from established players in the Solana Perps sector such as Drift Protocol, 01 Exchange, Zeta Markets, Mango,  among others. ## Growing The Pie: The Jupiter Vision 🥧 *When the pie grows, everyone gets more pie.* **P - Product** **I - Incentive** **E- Education** As a critical part of the Solana ecosystem, Jupiter benefits from helping onboard as many new users and developers to the ecosystem as possible. Beyond providing value through great products, Jupiter’s goal is to empower its community and the broader Solana ecosystem through several new initiatives: - **$JUP**: Governance token for the new DAO (more below) - **Jupiter Start**: It’s imperative for ecosystems seeking sustainable growth to strike a balance between keeping an open mind towards innovation, and being objectively critical of poor application design and weary of teams seeking to capitalize on narrative and recency bias within the markets. Jupiter Start aims to be a collaborative effort between the Jupiter community and the broader Solana ecosystem to “help vet, debate, understand, and highlight great new projects”. This entails the Jupiter launchpad to help bootstrap new projects, pre-listing trading availability for new tokens, and Atlas, a new public seed-funding initiative to allow the community to invest in early-stage projects, as well as various community-centric educational initiatives. *We recommend reading this [blog post](https://station.jup.ag/blog/jup-start)if you are interested in learning more.* - **Jupiter Labs:**A collective effortbetween the Jupiter team, community, and DAO to develop innovative products and tools for Solana DeFi. Although these initiatives will begin native to Jupiter, they are ultimately designed to launch and operate as independent protocols on Solana. Jupiter users will be granted priority access to early product testing and consequently benefit from associated incentives for doing so, part of which will be allocated towards the JUP DAO. The first product to already go live is the Perpetuals exchange, which is already live in beta, and a proposal for sUSD, a SOL-backed stablecoin (like LUSD:ETH) which uses leveraged LSTs to generate yield. ### More on $JUP Jupiter announced the $JUP token during Solana breakpoint, a strategic decision which was made after the protocol reached numerous critical milestones including a broad and engaged user base, several major platform upgrades and new products, a pipeline of ecosystem projects, all of which of course, is part of an overarching conviction in the future uptick of activity on Solana. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/43e39210c556.jpg) With a **max. supply of 10 billion JUP**, the token distribution is equally split between 2 cold wallets - the team wallet, and the community wallet. The team wallet will be used for allocations for the current team, treasury, and liquidity provision, while the community wallet is geared towards airdrops and various early contributors. *15% - 17.5% of the tokens will be liquid from day one, 10% - 7.5% in warm wallets, and 75% to be in cold storage.* The airdrops will consist of retroactive airdrops to engage a whopping **955k** **early users**of Jupiter (pre-Nov 2nd), as well as growth airdrops aimed to help attract new users and liquidity, and to form the JUP DAO itself. The DAO will then vote on the token unlock data, The token will be initially locked, and the unlock date to be set by the DAO. JUP holders will have the ability to vote on various critical facets of Jupiter protocol and the role of the token, including the timing of the initial liquidity provision, future emissions scheduling, which projects to be featured on Jupiter Start, among others. **“The initial value of JUP will be a symbol for Jupiter and DeFi 2.0, much as the value for UNI is a symbol for Uniswap DeFi 1.0.”** ## Fundamental Investment Catalysts Now that we have covered the components of Jupiter protocol, we can break down the long-term investment opportunity we envision. ### The Solana Bet Solana’s roadmap is an ambitious and exciting one, and we expect ecosystem activity to continue to grow throughout 2024, building on the momentum gained in Q4 2023. The main catalysts driving our conviction: - **More Airdrops**: Marginfi and a handful of other DeFi teams sparked a flame in the Solana ecosystem with the onset of Points programs (many of which have yet to see their final form!) earlier near the summer of 2023. The JTO airdrop exacerbated the already growing momentum on Solana with a wealth effect that left not only left many jitoSOL stakers happy, but also left many individuals unsatisfied and looking for the next big opportunity. Starting with Jupiter ($JUP), others to keep an eye on would be Kamino, Marginfi, Drift, Tensor, and more. - **Firedancer**: Jump Crypto’s highly anticipated validator client, which Toly himself has deemed “Solana 2.0” . Firedancer is expected to be a long-term beneficial initiative for Solana’s performance and throughput as the network scales and evolves, and it marks a crucial milestone for Solana as it increases client diversity and thus mitigates the risk of a single point of failure for the network. Low-latency applications will become that much faster, an attractive selling point for both users and developers. As 2024 will likely be the year Firedancer goes live, we expect a lot of speculation and growing interest around this milestone. - **DePin**: This is a novel sector in crypto which exemplifies how tokenized assets can be used help decentralize real-world business models. Solana has managed to attract a number of projects including [Helium](https://www.helium.com/) and [Hivemapper](https://blog.hivemapper.com/introducing-the-hivemapper-network-the-worlds-first-blockchain-based-mapping-network-ec67df38cca4?gi=f969524f70ff). Interest around DePin as an emerging sector brings more positive attention to Solana in turn, as the network demonstrates its utility to serve more tangible use-cases. - **Payments**: Solana Pay is now integrated with Shopify, meaning merchants can accept payments on Solana, meaning the average JTO airdrop recipient could’ve technically bought 2000+ coffees with their earnings. Though there are still hurdles to overcome for actually getting shoppers to make payments in Solana Pay, a partnership with the largest ecommerce platform is a good way to start. Additionally, earlier this year Visa, one of the largest global payment networks, announced its plans for leveraging Solana for its Stablecoin Settlement Pilot - an experiment testing the capabilities of blockchain settlement rails for building new products for commerce and money movement. Solana’s high throughput, fast finality, low transaction costs, and node availability are all positives for Visa, the same way Visa’s brand is a positive for bringing a lot of attention to Solana. If successful, we believe the Stablecoin Settlement Pilot will mark a major milestone for the development of real-world crypto use-cases, and Solana stands to benefit as being the de facto network making this happen. A final honorable mention is the **Saga Phone**. While Solana’s mobile phone may not have been a home run in its first year, a push for mobile-friendly crypto environments and applications can be a very exciting development in the long-term when considering what mobile integration did for social media and payment apps. Excitement has picked up recently as the Solana phone airdropped BONK to purchasers (technically you could buy the phone and pay it off immediately at one point…) , and the team just recently announced “[Chapter 2](https://x.com/solanamobile/status/1747302707273089133?s=20)” which entails a cheaper price ($450) and a referral leaderboard to incentivize more users. ### Challenges for Solana **While we remain bullish on Solana’s long-term growth, there are several critical concerns we expect the Solana core team and developer community to address in the near and long term, which we will be keeping an eye on:** - **Fee Market**: Though Solana has introduced priority fees now, there is no native mechanism for determining a ‘market’ priority fee which helps rate limit spammers efficiently (i.e. EIP-1559). As there is now much greater demand for blockspace on Solana, more users are experiencing failed transactions, further demonstrating the need for an upgrade to the network’s current fee market structure. Proposed solutions involve dynamic account fees, and a **multi-dimensional EIP-1559**with exponentially increasing fees for every account touching the exact same hotspot. - **EVM Competition:** Though we believe in the long-term SVM vs EVM will not be a zero-sum dynamic and the different networks will specialize in their own respective categories, today Solana is still competing with EVM landscape for market share and users, a large gap to close ($1.4b > $30b). **EIP-4844** aims to make L2s significantly (80-90%!) cheaper and easier to use/deploy, which can reaffirm strong market leaders in Arbitrum, Optimism and Base. Similarly, Celestia brings more flexibility and lower costs for L2 developers, which can potentially attract talent and users away from Solana. **Restaking** narrative stands to be one of the biggest catalysts for Ethereum and will likely bring in a lot of capital inflows there as well. Security risks aside, investors who are seeking native yield on a native L1 asset will seek opportunities for higher returns, which restaking provides for Ethereum stakers. - **Parallel-Execution L1s:**The rising popularity of **parallel-execution L1 chains**(MoveVM, Sei, Monad) which optimize for speed and performance similar to Solana are still young and underdeveloped, and could see their own . **Monad,**built by a handful of team members with HFT backgrounds, aims to bring Solana-like performance to the EVM environment, theoretically uniting “the best of both worlds” and delivering upwards of 10K TPS. Nonetheless, these chains not only face an uphill climb against Solana itself, but they must also compete with Neon EVM, which enables Solana compatibility through an Ethereum native environment. Aave has recently published a [proposal](https://governance.aave.com/t/temp-check-aave-v3-vp-deployment-on-neon-evm-mainnet/16193) on its governance forum to discuss deploying its V3 protocol on Neon mainnet. With all this in mind, we consider Solana’s resiliency, demonstrated in its ability to overcome macro challenges such as the FTX collapse, or technical shortcomings such as network outages, the network’s greatest strength and long-term catalyst. ### The Solana Bet = The Jupiter Bet > “Our vision for the future is intrinsically tied to the growth and prosperity of the Solana ecosystem. We are driven by the conviction that a flourishing Solana ecosystem translates to collective benefits for all stakeholders involved. In simple terms, when the pie grows, everyone gets more pie.” - [Jupiter Green Paper](https://station.jup.ag/blog/green-paper) We believe Jupiter’s critical role in the Solana DeFi landscape makes it a viable bet on the network’s near and long-term adoption. The thesis is quite simple. More users on Solana = more users on Jupiter. Solana’s initial boom lasted for the better part of the first year it was live (2021), during which protocols like Saber and Serum dominated the DEX landscape. Jupiter gained traction shortly after its launch given its USP for Solana DeFi, which sought to utilize on-chain liquidity from DEXs rather than steal market share from them, for the end-goal of providing a better user experience with better pricing. However, it wasn’t until the sunset of Serum, the once-dominant Solana DEX, that Jupiter had emerged to be the market leader they are today. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/2e0855db5e8b.png) *Jupiter consistently made up over 60% of organic DEX volume on Solana throughout 2023.* ## Breaking Down Jupiter’s Business Model Initially, Jupiter’s core product was simply a swap engine which optimized for better pricing and did not charge any additional fees for traders. As the project began to grow and see continuous growth in volume and traders, the team launched a handful of new products which now serve as organic revenue streams for the protocol via fees. We believe the JUP DAO will naturally seek to ensure $JUP holders receive a given % of these fees, as well as future opportunities with Jupiter Start and Jupiter Labs. ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/518aebde49ec.png) - **Limit Orders: 30 BPS** - **DCA: 10 BPS**This is a unique offering which I think Jupiter can take further advantage of by raising the fee (~20 BPS) - **Perps**Opening/Closing a Position: 10 BPS Swap Fee: 0 - 200 BPS (varies by pool weight) Borrow Rate = 1 BPS / hour * token utilization % 70% of fees generated go towards - **External protocols**If a protocol integrates Jupiter’s architecture into their own software and then charges their own fee, Jupiter ensures they receive a share of the fees as well. **Hypotheticals** - **Jupiter Start -**We believe it may be prudent to utilize Jupiter Start initiatives, namely the Launchpad and Atlas, towards creating an additional revenue stream for Jupiter and $JUP holders. Launchpad: Establish deal-flow or projects incubated by the Jupiter Launchpad, where a portion of a project’s revenue goes towards the JUP DAO. **Atlas:**Create an efficient model for collecting revenue from realized gains on public seed-funding initiatives to be distributed among holders and investors who participated. - **Jupiter Labs - As already demonstrated by Perps, Jupiter Labs supports the development of protocols which can generate additional revenue for Jupiter.**Another proposal is in the works for sUSD An interesting question to consider here is how exactly will these initiatives one day launch and operate independently, as stated in the Jupiter docs, and how will doing so influence that particular revenue stream. - **Swap Fee**Jupiter’s swap engine has been the core product that Solana users have grown to know and love. However, as fee dynamics on Solana continue to evolve, trading will inevitably become costlier as more smart contracts compete for fewer blockspace. Jupiter has already positioned itself to allow traders to pay priority fees for faster execution, and if this feature sees continuous adoption from this point onwards, it makes sense to charge an extra % for the service Jupiter is providing (there is no native way to calculate the “base” priority fee). **Competitive Landscape for Jupiter** Generally speaking, we believe Jupiter’s role as an aggregator is in a unique position as it does not face direct competition with any one trading protocol on Solana at this time. That said, as the Solana DEX landscape continues to evolve as the demand for low-latency trading applications grows, Jupiter will naturally face the challenge of keeping up with the latest innovations and developments. At the end of the day, traders want better settlement and will go where that is the case. Furthermore, Jupiter faces greater competition for its additional products such as Perps, and teams are generally going to be incentivized to recreate a DCA product or similar. - The DEX landscape on Solana is evolving and becoming more competitive. Outside Solana, it’s even more competitive. - Jupiter’s competitive edge lies in price settlement for users; if a protocol emerges to offer better pricing users flock there more likely than not. Swaps are still main use case; swap engine performance is key - Niche products (perps, limit orders, dca) have stronger competition and competitors can offer lower fees ### Suggestions for Jupiter - More transparency around fees and revenue, and product performance data dashboard would be helpful for investors. - $JUP holders should be a beneficiary of Jupiter’s revenue streams (Limit Order, DCA, Perps, Jupiter Start + Labs) - Monitor the intents landscape and consider a routing model which utilizes off-chain liquidity (i.e. CEX LP inventory) in addition to on-chain liquidity to provide better pricing for users. Similar to 1inch Fusion, Matcha by 0x, CoWSwap, etc. This would apply for swaps, limit orders, DCA - Ensure $JUP holders receive a % of revenue generated by Jupiter Labs products and services. Ensure any team which Jupiter Start either incubates by launchpad or public seed-funding, which implements a fee on their protocol, allocates a  % to $JUP holders - Ensure the large size of the airdrop distribution does not dilute the quality of participants who represent the JUP DAO. ## Future Outlook ![](https://shoal.xyz/research/writing/jupiter-exchange-solanas-dex-aggregator/img/173efde34a83.jpg) Given its unique position in its ecosystem, we believe Jupiter is a viable bet on Solana’s near and long-term adoption. As network activity on Solana continues to pick up, we expect Jupiter to capture a significant portion of inflow value with its established ecosystem presence, suite of various products, and a sustainable revenue model which should benefit $JUP holders long-term as well. As Larry Fink begins to talk about the[tokenization of every financial asset](https://youtu.be/se1bcqMYg8g?si=RvFos2cVCn1VJFNx&t=247), and L1 blockchains like Solana continue to seek PMF and explore new utilities and innovations, it’s not too far-fetched to imagine Jupiter accommodating a variety of new asset classes over time. ## Sources - [Jupiter Green Paper](https://station.jup.ag/blog/green-paper) - [https://station.jup.ag/blog/dca-official-launch](https://station.jup.ag/blog/dca-official-launch) - [What Is SVM - The Solana Virtual Machine - Squads Blog](https://squads.so/blog/solana-svm-sealevel-virtual-machine) - [Meow here. I am the founder of Jupiter. AMA! : r/solana](https://www.reddit.com/r/solana/comments/18r31pb/meow_here_i_am_the_founder_of_jupiter_ama/) - [Jupiter Dune Dashboard](https://dune.com/ilemi/jupiter-aggregator-solana) - [Solana - DefiLlama](https://defillama.com/chain/Solana) - [Validators.app](https://www.validators.app/?locale=en&network=mainnet) - [@ptmfv / 2023 Solana DEX Landscape (monthly change)](https://dune.com/queries/3329595/5612070) - [@ilemi / Solana DEX Trade Source](https://dune.com/queries/3130352/5222135) - [@ilemi / Jupiter Bot Stats](https://dune.com/queries/3101599/5175867) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # The Convergence of Yields > The intersection and influence of traditional finance on DeFi yields - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-12-20 - Canonical: https://shoal.xyz/research/writing/the-convergence-of-yields/ - Keywords: stablecoins, crypto, DeFi, market making, yield, RWA, tokenization, Ethereum ![](https://shoal.xyz/research/writing/the-convergence-of-yields/img/975e1a5ca784.jpg) ## “Show me the Incentives and I’ll show you the outcome” - Charlie Munger This simple yet profound phrase by Munger, like every good quote, encapsulates rational human behavior in a few words. In many situations, incentives might be subtle or too complex to perceive, but in finance, it's often more straightforward — people want to maximize their profits and minimize their losses. Decentralized Finance — DeFi — cuts out the middlemen, simplifying the link between incentives and outcomes. Seeing assets moving from protocol to protocol, fresh money coming in, and money coming out is like seeing human behavior at its rawest and clearest form: when there's a clear reward, people act. This clarity around rewards, the low barrier of entry, and, of course, the promise of a high yield is what's driven DeFi's rapid growth. In these unpredictable economic times, with rising inflation, soaring interest rates to tackle that very inflation, and consequently more attractive low-risk bonds, it's crucial to understand where DeFi stands and its response to these challenges. MakerDAO’s high revenue coming from RWAs (increasingly influenced by the US bond rates), combined by its current dominance in the stablecoin money market is allowing MakerDAO to essentially act as the DeFi (De)Central Bank and to determine the base DeFi rate for money markets. In this blurry scenario, we'll also shed light on the necessity of increasing the variety of on-chain native forms of yield, that don’t exclusively depend on volatility or traditional financial cycles. ## Different Sources of Stablecoin Yield in DeFi In DeFi, when individuals hold a stablecoin, they essentially have three options: - **Keep it idle** (which is not ideal because the US dollar suffers from an inflationary process and the stablecoin is worth less every day); - Find a strategy to**get a yield on top of this stablecoin;** or - **Swap its stablecoin for another token**and strategy in DeFi (which, in this article, we'll simplify as buying ETH and staking it). Assuming investors choose to hold their stablecoins to maximize returns and offset inflationary losses, they have several strategies at their disposal: - **Staking**: Locking up your token to support a network and earn rewards, like interest on a savings account but with network validation perks. Or simply deposit it in a smart contract (in the case of stables or other DeFi strategies). - **Market Making**: Providing liquidity to decentralized exchanges — DEXs — for smoother trades, earning some of the trading fees. - **Lending Platforms**: Lending your assets on smart contracts to earn interest, a decentralized money market with its own set of risks. - **Tokenized Real-World Assets**: Keep your money on-chain and gain exposure to TradFi investments, like bonds, for example. To understand how investors currently allocate their stables in smart contracts, we’ve prepared Table 1, which outlines all those different sources of yields on the Ethereum mainnet. The columns depict the following: - The **project**behind a certain strategy; - The **symbol**(tick) of the tokens used in the strategy. - The **Total Value Locked (TVL)**indicates the aggregate amount (in dollar terms) invested in the strategy. - The **Annual Percentage Yield (APY)** denotes the expected yearly return. ![Table 1 - Sources of yield for Stablecoin in the Ethereum Mainnet. Data - DeFi Llama.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/dc22804bd501.png) The first thing that gets our attention when analyzing the data of this table is how dominant MakerDAO’s DAI (DSR) strategy is, with an APY of 5% and 1.6 billion dollars deposited in its contracts. It represents a staggering **52% of the sum of the entire market** other than this strategy represented by this table. The Dai Savings Rate (DSR) within the MakerDAO ecosystem allows DAI stablecoin holders to earn interest on their DAI through a combination of off-chain and on-chain yield strategies, including ETH staking and treasury yields. **But it has not always been like this.** **Dai Savings Rate — DSR — TVL has been growing rapidly**, especially since August 2023. In Chart 1, we can visualize the TVL by type of yield strategy and how they have changed in the past year. We can see how the **AMM and Lending TVLs have significantly declined** in that time. ![Chart 1 - TVL of the 25 biggest sources of yield on the Ethereum mainnet, by type. Data - DeFi Llama.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/a07ad1335794.jpg) Chart 2 makes it more clear how the total TVL of the studied protocols has ranged from 3 to 4 billion dollars and how there is a **significant change in the composition of the aggregate TVL, with collateralized debt positions, referred to as CDPs (DSR) gaining a substantial part of it.**CDPs function as decentralized financial instruments that are secured through the on-chain pledging of other assets. In this study, the DSR is a CDP backed by a combination of on-chain and off-chain assets. ![Chart 2 - Stacked Area chart of the TVL of the 25 biggest sources of yield on the Ethereum mainnet, by type. Data - DeFi Llama.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/9de6c41a8e63.jpg) It is clear that something is happening for this composition change to occur. Still, to understand the behind the scenes of this phenomenon, it is crucial to understand the behavior of the yields of the money market and how they have reacted to DSR. Chart 3 describes this. ![Chart 3 - APY of several money market strategies on the Ethereum Mainnet with its overall trendline, and DSR’s APY hikes. Data - Dune Analytics .](https://shoal.xyz/research/writing/the-convergence-of-yields/img/7fe7f5516adc.jpg) The APYs of different money markets (minus DSR APY) on the Ethereum mainnet are represented on the chart. The plot is composed of three sections separated by colors, divided by two events (dotted lines): the hikes of the Dai Savings Rate on June 19th and August 6th. The Overall Trend represented by the dotted blue line makes it more evident what is happening. **The APY trend of all other money market protocols has doubled**; investors seem to have removed their positions from money markets and invested it somewhere else (probably DSR), until it **reached a new equilibrium**. It looks like**DSR is dictating the rates, and the money market is converging with the DSR**. But why exactly is this happening? ## The Ideal of Convergence Before diving deeper into why these rates converge at a new equilibrium dictated by DSR, it is important to understand the ideal of convergence. ### Theoretical Fundamentals of Yield Convergence in a Perfect Market In economic literature, the Law of One Price posits that in a frictionless and perfectly competitive market, identical goods or assets will have the same price. Extending this to DeFi (and yields), in a perfect market scenario, yields across various asset categories (like stablecoins) and protocols should converge to a single rate. This is because, in such a market, all participants have access to the same information and can move assets freely without any barriers, leading to a single equilibrium yield. ### The Role of Arbitrage in Pushing Rates Towards Convergence Arbitrage plays a pivotal role in driving the convergence of yields. When there's a discrepancy in yields between two similar assets or platforms, informed investors can move their funds from the strategy, paying lower yields, and deposit in the one with the higher yield. This movement naturally pushes the yields of the two assets closer together until the opportunity for yield arbitrage diminishes. The continual pursuit of these arbitrage opportunities by market participants helps keep the yields in check and drives them toward convergence. ### Factors Preventing Perfect Convergence While the theory sounds neat, real markets are not that perfect. Several factors can prevent yields from perfectly converging: - **Information Asymmetry**: Not all market participants have access to the same information at the same time. - **Gas fees**: Moving assets between protocols or swapping one asset to another often involves fees, which can deter arbitrage. - **Regulatory Barriers**: Different regulatory environments across regions can restrict the movement of assets or the participation of certain investors (lending, providing liquidity, and staking can be taxed differently, for example). - **Risk Differentials**: Even if two stables may represent the same denomination, they might, by default, have different underlying risks. And strategies involving them might have other risks on top of that, leading to different yields. With the theory being clear, let’s understand the events that have happened and have been happening that are shaping the DeFi stablecoin market the way it is today. ## Major Events of Convergence ![Chart 4 - 1 Year US bond treasury rate introduced on Chart 1. Data - DeFi Llama and US Dep. of Treasury.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/017c07ab7812.jpg) The most important factor that permeates the changes happening in DeFi and this convergence event is the interest rate hikes performed by the FED in the US to control the high inflation. This high-interest rate environment hinders economic activity, investment, and high-risk investment, among other factors, because it creates a high opportunity cost for doing anything else. There’s a high paying government bond with low risk, producing the same yield or even more than DeFi protocols. It can be clearly seen on Chart 4 how the Lending and AMM markets were affected. But what gets our attention is how Maker DAO’s DSR was able to increase its TVL to such a significant level in such a short time, in the worst market circumstances. ![Chart 5 - MakerDAO’s Balance Sheet  by asset type against the 1 Yr treasury bonds in the US. Data - Dune Analytics and US Dep. of Treasury.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/00b17f08fd17.jpg) Chart 5 gives us the biggest response to the underlying events we’re exploring: MakerDAO has been increasing its allocation on RWAs, which provide direct exposure to traditional finance and its current high-interest rates. This was a move by the DAO to get exposure to these high rates at a low risk with their vast stablecoin reserves, allocating more and more assets into RWAs to surf this high-interest rate environment. So much so that now it represents **52% of the entire balance sheet of the DAO**. Because of this allocation, currently, **66% of the revenue from the DAO comes from RWAs**, **and 30% comes from ETH liquid staking**. This movement encapsulates the reaction of DeFi as a whole to the high-interest rates environment. **MakerDAO’s high revenue coming from RWAs (directly influenced by the US bond rates), combined by its current dominance in the stablecoin money market is allowing MakerDAO to essentially act as the DeFi (De)Central Bank and to determine the base DeFi rate for money markets.** The significant revenue coming from ETH also gets a lot of our attention. Despite the interest rates going up, and consequently, DeFi TVL going down as a whole, staked ETH TVL was shooting up. Staking ETH became an alternative for those looking for a safe yield. ETH staking yield became blockchain’s *de facto* ‘risk-free’ rate. ![Chart 6 - Lido’s TVL is increasing despite the increase of interest rates in the US. Data - Dune Analytics and US Dep. of Treasury.](https://shoal.xyz/research/writing/the-convergence-of-yields/img/4c45781ed070.jpg) **These interesting events come at a price** — ultimately, this convergence is**the convergence of stable yields in DeFi, through RWAs, with rates in traditional finance**. In this environment, where stable yield from DeFi money market solutions is not as eye-catching as TradFi yield, even fully on-chain stables like DAI became **increasingly integrated with the risks of Traditional Finance**. This opens up a **significant opportunity for crypto-native stable yield solutions that aligns more closely with the web3 market and less with traditional finance**. The challenge lies in its ability to offer competitive yields against TradFi, even during economic downturns, and low volatility without necessarily mirroring its behavior. ## Time for On-chain native yields There is evident demand for yields less correlated with the real-world economy, it just has to offer attractive returns even in the case of economic downturn. Web3 requires yield sources that are more closely aligned with its own dynamics and less susceptible to the disruptions, risks, and censorship prevalent in traditional finance. This task isn't easy. Traditional finance, developed over centuries, is deeply rooted in path dependence. It has adapted to numerous regulations and incurred significant sunken costs, making it hard to move away from these established models to create something new. Yet, the beauty of building DeFi lies exactly in overcoming this challenge. Builders have the golden opportunity to improve the current system, adapting it for a world of sovereign individuals. There's unlimited opportunity to build something new, leveraging the innate characteristics of this new world, free from the constraints of inefficient regulation and control. We welcome innovation in new yield sources, fostering native financial cycles in DeFi. This involves capital flowing between convergence and divergence cycles with native and traditional yield sources on-chain, with the freedom of capital movement, aiming to create a unique environment of financial freedom, driving finance and freedom forward. ## Conclusion Over the past year, the stablecoin market has faced significant changes, with a clear shift in TVL composition and a convergence of yields, spearheaded by the Dai Savings Rate (DSR) and its reliance on Real World Assets (RWAs). This trend has introduced a level of risk to the stablecoin market as yields became increasingly dependent on TradFi and its associated risks. **As stablecoin yields start to reflect traditional financial markets more closely, the line between DeFi and TradFi begins to blur. This shift may challenge the core principles of decentralization and autonomy that DeFi represents, as it becomes subject to the same economic pressures that affect the broader financial world.** In this context, the introduction of new web3 native sources of yield is necessary to create a more dynamic market where on-chain cycles are not solely dependent on the volatility of the market or traditional finance. The future of DeFi depends on different on-chain cycles that allow capital to move freely inside our own ecosystem and break away from the rusty shackles of control and traditional finance. You can find more about Pedro on [Twitter](https://twitter.com/pdotal) ### Sources - [https://dune.com/queries/3145098/5245485](https://dune.com/queries/3145098/5245485) - [DefiLlama](https://defillama.com/) - [Daily Treasury PAR Yield Curve Rates](https://home.treasury.gov/resource-center/data-chart-center/interest-rates/TextView?type=daily_treasury_yield_curve&field_tdr_date_value_month=202312) --- ***Investment Disclosure.** Disclosure: Members of Shoal Research hold material positions in the assets discussed in this article. The content presented is for informational purposes only and should not be construed as financial or investment advice. Please perform your own due diligence before making any investment decisions.* --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # Liquid Restaking Tokens: A new Frontier for Yield > An Overview of liquid restaking tokens on Eigenlayer - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-12-18 - Canonical: https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/ - Keywords: crypto, DeFi, restaking, liquid staking, yield, infrastructure, Ethereum, Bitcoin, data ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/107b6d793067.jpg) ## An Introduction to Proof-of-Stake, Staking, and Liquid Staking Throughout 2023, liquid staking and the primitives surrounding it has permeated all parts of the crypto ecosystem . This rise to popularity of the infrastructure around the Proof of Stake (PoS) consensus mechanism really took off with its integration  at the protocol level on Ethereum during September 15, 2022—referred to as the “Merge”. The transition from the traditional Proof of Work (PoW) mechanism to PoS represented a paradigm shift in Ethereum consensus, allowing users to derisk the ability to provide (and price) Ethereum crypto-economic security. This enabled the growth of staking, the emergence of restaking, and the introduction of a new class of assets–liquid restaking tokens. ### Understanding Proof-of-Work and Its Limitations Before delving into PoS, it's instructive to examine [PoW, the pioneering consensus mechanism that continues to secure Bitcoin](https://ethereum.org/en/developers/docs/consensus-mechanisms/pow/). At its core, consensus for blockchains refers to the underlying mechanism that enables transaction verification without relying on a centralized authority. Typically, consensus requires agreement from at least ⅔ of the network's nodes on its current state. This helps secure the network and confirm the updated history of transactions, also known as a state change. Under PoW, this consensus is achieved through mining. Miners utilize computational power to solve complex mathematical puzzles. The first to solve these equations verifies the next block, adding it to the blockchain, and in return, earns a reward. This process is resource-intensive, making it a race where participants must consume large amounts of energy for potential rewards. PoW also plays a pivotal role in transaction validation, preventing malicious actors from double-spending—a scenario where one user attempts to spend the same funds multiple times. However, achieving this in PoW requires maintaining control over 51% of the network, an expensive feat given the hardware and energy costs associated with this consensus mechanism. If an entity does achieve this, they could influence the consensus, posing a considerable risk to the network’s security. In such cases, the only solution to rectify the attack lies in a hard fork. Combating double-spending preserves blockchain's promise of immutability, decentralization, and trustworthiness. ### Embracing Proof-of-Stake: A Shift towards Sustainability for Consensus PoS addresses the same core objective as PoW—validating and adding new blocks through consensus. It does so with greater efficiency and sustainability. Unlike PoW, which relies on energy-consuming computational tasks, [PoS relies on validators who 'stake' an asset capital as collateral](https://ethereum.org/en/developers/docs/consensus-mechanisms/pos/). To enter the validator set in the beacon chain and participate in validation activities, stakers must deposit a minimum of 32 ETH. Their staked amount acts as a deterrent against malicious activities, as any misdeed could result in a loss of their staked funds and forced exit from the beacon chain–a process known as slashing. The slashing penalty scales with the number of validators slashed within a given time period leading to greater losses for those validators who were slashed as a means to deter collusion between multiple validators at the same time. The difference between PoW and PoS security mechanisms is substantial. While PoW deters malicious activity through resource expenditure (i.e. the cost of owning and operating a majority of nodes), PoS imposes direct financial penalties to stakers as a means to decrease the computational overhead of securing the chain. ### Liquid Staking: Innovating on Composability in the  PoS Landscape The PoS realm had seen numerous innovations to additionally benefit stakers’ potential to earn yield. However, one glaring challenge remained, composability. Initially, stakers couldn't easily withdraw their stake, and there was little incentive to do so given the rewards. Liquid staking tokens (LSTs) emerged as the answer, enabling users to engage with DeFi without compromising on their exposure to staking yield. Throughout the past year, we’ve witnessed significant growth in LSTs, yet there remain challenges and potential new frontiers to further expand adoption of the vertical by the greater crypto ecosystem.. Slashing is the greatest risk which holders of LSTs are exposed to besides price depegging. As discussed before, slashing imposes a permanent penalty on  slashed validators, burning their ETH and exiting them from the beacon chain. This does not necessarily always impact the value of an LST token, however it does impact the amount of ETH redeemable by the token holder. As a result, correlated slashing events in which a significant amount of ETH is removed from the validator set of a liquid staking provider could incite skepticism on the solvency of the asset, leading to sell pressure on that LST and further inciting a depeg event. Numerous companies are striving to improve the liquid staking experience by offering innovations like reduced bond requirements, distributed validator technology (DVT), and trusted execution environments (TEEs), all with the aim of reducing the risks around slashing and making staking safer. It will become increasingly important to utilize such tools within the validator infrastructure of liquid staking providers as more use cases for LSTs in the DeFi ecosystem make solvency for LSTs even more important.. Concurrently, there's a rush to satisfy the appetite for diverse yield opportunities, be it through DeFi, incentive mechanisms, or innovative products. One such paradigm that has risen to the main stage is restaking. Restaking is specifically designed to reflect the ETH PoS crypto economic design and iterate on it to reduce the barriers of bootstrapping PoS systems while allowing stakers to earn additional revenue on their assets. ## Restaking and the Advent of Actively Validated Services ### Extending Ethereum’s POS Security Ethereum’s PoS consensus mechanism offers a unique advantage: it's programmable and scalable security via cryptoeconomic value. This security, intrinsic to Ethereum, extends seamlessly to all of the protocols that are secured by the underlying continuity of the beacon chain as a byproduct. This is a diverse array of smart contract protocols, ranging from decentralized exchanges (DEXs) to NFT marketplaces. However, until recently, this robust security framework didn't wasn’t able to innately extend itself to other applications or distributed systems such as bridges, sequencers, data availability layers, or other blockchains that required some other form of consensus. Systems like these have traditionally been tasked with bootstrapping their own consensus mechanisms to safeguard their operations, a challenge exemplified by platforms like Axelar and its native PoS network. ### Restaking: Bridging the Security Gap Addressing this gap in extendability of security provisioning led to the inception of restaking—a pioneering concept that allows staked assets on Ethereum to bolster the security of arbitrary distributed systems. [EigenLayer](https://www.eigenlayer.xyz/), the first restaking protocol, coined the term "Programmable Trust" to describe this mechanism. More intriguingly, the distributed systems benefiting from this trust mechanism are termed Actively Validated Services (AVSs). ### EigenLayer: Amplifying Commitments and Security At its core, [EigenLayer operates as an amalgamation of smart contracts and off-chain software](https://docs.eigenlayer.xyz/overview/readme), amplifying the commitments a validator or other external node operator can undertake. This enhancement enables validators to engage with AVSs, requiring them to run supplementary software. Concurrently, the EigenLayer smart contracts introduce new slashing conditions on the restaked Ethereum, predicated on the specifications of the chosen AVS. In exchange, these restakers are able to earn rewards for providing security to these systems. These conditions are agnostic to whether Ethereum is staked directly or via LSTs from an affiliated liquid staking provider. This makes it easier for distributed systems to build a security model without having to worry about bootstrapping security providers–stakers. Restakers can opt-in to multiple AVSs, exposing their stake to multiple slashing conditions and earning rewards from multiple AVSs. Ultimately, EigenLayer pools security through restaking instead of fragmenting it. Pooling security is what enables multiple parties to combine their resources to provide greater security for the entire restaking ecosystem. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/d2462e969242.jpg) ### Unveiling EigenLayer’s Potential: AVSs and New Yield Opportunities The emergence of AVSs that can harness programmable trust heralds a transformative phase for distributed systems. Not only do they offer unprecedented access to inherited security, but they also unlock a myriad of additional yield opportunities for stakers. By providing security to these services, stakers can tap into innovative avenues for rewards while maintaining alignment with [Ethereum’s long term goals](https://vitalik.eth.limo/general/2021/12/06/endgame.html) and supporting the services they desire. ## Potential Limitations of Restaking ### Introduction to Potential Limitations While restaking brings an enticing opportunity for stakers to amplify their returns, it's not devoid of [challenges](https://vitalik.eth.limo/general/2023/05/21/dont_overload.html). The added slashing conditions introduced by platforms like EigenLayer lead to augmented rewards for stakers, compensating for the heightened risk. Yet, the architectural constraints of EigenLayer hint at potential composability issues with restaking positions, notably due to the intricate risk profiles that arise. This complexity mirrors the challenges that PoS grappled with during its early stages. ### Future Scenarios for Restaking in DeFi Broadly, there are two potential trajectories for the integration of restaking positions into the DeFi landscape: Scenario 1: Governance-Gated Risk Management Liquid staking providers might decide to mitigate some of the inherent risks of restaking strategies by implementing governance-based selections. Here, the strategies deemed appropriate for their users' risk tolerance are permitted. Consequently, this could lead providers to segment their offerings, targeting specific risk demographics. For instance, a platform like Lido, aspiring to be perceived as a 'safety-first' provider, may renounce users with a higher risk appetite, as they'll be more inclined to seek providers promising greater yields through aggressive restaking strategies. Scenario 2: Non-Fungibility and the Push to LST Users Should situations arise where dominant platforms like EigenLayer experience significant slashing events or there's a widespread erosion of trust in providers, it may become infeasible for liquid staking providers to endorse restaking at the node operator level. Instead, the decision-making may shift to LST users. Here, EigenLayer restaking positions could become the predominant staked asset representation. However, due to their distinctive risk profiles, these assets are inherently non-fungible. This poses challenges in assimilating them into the broader DeFi ecosystem since most protocols are parameterized based on price-based dependencies. Restaking positions would find trouble here due to their intrinsic scarcity of liquidity and limited price discovery. ### The Conundrum of Staked Asset Financialization While EigenLayer and similar platforms seek to fortify PoS networks through innovative staking models, the escalating complexities in validator risk profiles inadvertently spawn secondary challenges. Both aforementioned scenarios hint at a landscape where staked and restaked assets become fragmented and illiquid. This dynamic severely hampers the feasibility of leveraging restaking positions within the DeFi ecosystem. ## Liquid Restaking Tokens (LRTs) Explored ### Definition and Overview Liquid Restaking Tokens, or LRTs, are the derivative representations of restaking positions. Analogous to LSTs, LRTs have emerged to grant broader and more intuitive access to restaking positions. Numerous protocols are championing this initiative, though the frontrunner is yet to emerge. Before delving into these protocols and distinguishing their attributes, it's essential to appraise the pros and cons of LRTs. ### The Differences Between a Liquid Staking Provider and LRT Provider Liquid staking providers and LRT providers have similar end goals, which is to provide stakers or restakers respectively with a liquid representation of their underlying position. However, they reach this end by different means. The liquid staking provider is solely focused on providing depositors with a means of connecting with a reliable node operator so that they can spin up validators and provide receipt tokens for staking positions. They help match capital to hardware operators. On the other hand, LRT providers must also account for the risk profile of AVSs which they opt-in to and further expose their LRT holders to.  Liquid restaking helps manage capital delegation between yield opportunities as a form of portfolio management. Their goal is to return the user upside while minimizing risk exposure. Identifying an appropriate risk to reward framework which characterizes the LRT is one of the primary objectives of an LRT’s governance mechanism, whereas the governance mechanism for liquid staking providers is less objective. ### Advantages of LRTs LRTs facilitate more seamless integrations between restaking and DeFi. This aligns closely with the first potential future for restaked assets we previously discussed. That is, LST providers create liquid representations of restaking positions and manage them through governance-gating. This could enable LST providers to create well-defined risk profiles, enabling users to properly manage their portfolio of restaked assets and relish enhanced versatility. This approach enables restakers to participate in DeFi while still gaining the benefits of restaking. ### Considerations for Users While the benefits of LRTs are apparent, potential users should remain cognizant of their constraints. As described in the first scenario, many upcoming LRTs incorporate some form of governance oversight. This can restrict the flexibility of LRT holders to express their risk appetite and support their desired AVSs. This governance model raises pertinent questions about the motivations underpinning LRT providers' endorsements of specific AVSs and their ability to create a well justified risk to reward model. A transparent exploration of these motives in governance forums will be crucial for maintaining trust and transparency. ### Challenges in Underwriting LRTs The task of underwriting LRTs presents its own set of complexities. It might be equally, if not more, challenging than underwriting LSTs, given the nuanced risk profiles and unique pricing dynamics of LRTs. Addressing these challenges mandates protocols to adopt a more asset-specific approach towards creating markets for which LRTs can be sustainably supported. A deep understanding of the underlying mechanics of Ethereum core infrastructure, PoS, AVS design, and LRT design will be crucial. We’ll elucidate more on the design considerations for LRTs in detail in the subsequent sections. ### LRT Case Studies Now that we covered Eigenlayer, AVSs and the role of restaking, let's look at some case studies of early projects building in the ecosystem. As of now there are over 10 LRT projects building at the liquid restaking layer. **We dive deeper into the following projects:** - KelpDAO (rsETH) - Renzo (ezETH) - EtherFi (eETH) - RestakeFi (rstETH) - Puffer (pufETH) ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/49a8d25b60a5.jpg) ### KelpDAO/ Stader (rsETH) **rsETH as a Part of Liquid Restaking** Fundamentally, an LRT, or Liquid Re-Staking Token, serves as a liquid representation of restaking positions to allow restakers on EigenLayer access to a form of their position that they can use in the greater DeFi ecosystem. RsETH is an LRT issued by KelpDAO aimed at addressing the risks and challengesposed by the current limitations of restaking position liquidity. Restakers in Kelp engage by staking their LST to generate rsETH tokens, signifying partial ownership of a pool of the underlying restaked assets. Then, two rsETH contracts allocate the deposited tokens among different Node Operators collaborating with the Kelp DAO. Rewards accumulate from a diverse array of AVSs that were delegated to by the rsETH contracts. The value of the rsETH token reflects the underlying value of the various reward and staked tokens. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/71727a467bfd.jpg) Restakers have the option to exchange their rsETH tokens for other tokens on AMMs for immediate liquidity or opt to redeem underlying assets through rsETH contracts. Restakers can further leverage their rsETH tokens in DeFi. ### Isolated Architecture The rsETH smart contracts are structured to segregate deposits, delegations, and withdrawals, ensuring a distinct division of responsibilities and minimizing the overall risk exposure to users of the protocol. The overall structure includes 4 main modules: depositing and minting anLRT, moving assets to delegators, moving assets to strategies, and withdrawing. Depositing and minting rsETH automates the process of delegating to AVSs, saving the effort in identifying the right services and validators, and helping manage staking rewards. Moving assets to delegators and strategies include transferring the tokens to Node Delegation Contracts (NDCs) based on tokenomics, weights, and distribution metrics. Strategies include delegating the funds from Node Delegator Contracts to Strategy Manager which distributes the funds among different strategies. Upon a successful undelegation, the assets transition to NDCs, subsequently handed over to the Withdrawal Manager smart contract. The withdrawal manager determines the amount of assets to be allocated to the restaker based on the latest exchange rate. Once the funds are effectively withdrawn, rsETH is minted. There are also 4 other modules supporting the Kelp DAO: registry (records operators, services, and assets in the rsETH ecosystem, including associated metadata and essential properties of rsETH), oracle (updates real-time asset prices for rsETH contracts, facilitating accurate minting and burning of rsETH based on deposit and redemption needs), governance (set of contracts that translate successful proposals into executable code to change smart contract behavior), and reward market (module optimizes non-ETH rewards through diverse extra-yield strategies, becoming a foundational layer for assessing and optimizing governance and utility tokens amidst the AVS surge). ### Kelp x Stader Amitej G and Dheeraj B, founders of Stader Labs, a multichain liquid staking platform with $230M+ in TVL, established Kelp DAO. The team is dedicated to developing Liquid Restaking Solutions for public blockchain networks. Stader boasts more than 85,000 users and over $25 million in paid rewards, along with over 40 DeFi integrations. They have also forged partnerships with industry leaders such as Pantera Capital, Coinbase Ventures, Blockchain.com, Jump Capital, and other prominent funds in the space. Additionally, they have collaborated with renowned figures in the crypto world, including Sandeep Nailwal and Jaynti Kanani (Polygon’s co-founders), Nemil Dalal (Head of Crypto at Coinbase), Tim Ogilvie (Staked’s co-founder), and others. Amitej and Dheeraj have successfully created one of the most robust liquid staking platforms across different chains, attracting significant capital and establishing partnerships with industry leaders. Their current commitment is to develop an LRT solution on EigenLayer for Ethereum. The team has been diligently working on the design since Q1 2023 and was the first to publish the LRT intentions, coining the term LRT. Furthermore, the Kelp DAO has already undergone audits by some of the most trusted auditors in web3, including Sigma Prime and Code4arena, where no critical issues were found. ### EtherFi (eETH) EtherFi (eETH) is a decentralized, non-custodial Ethereum staking protocol that has evolved significantly since its inception. Initially, EtherFi focused on enabling a scalable network of solo stakers using Distributed Validator Technology (DVT). This technology divides validator keys, allowing a broader range of users to stake permissionlessly, addressing the requirement of having 32 ETH for staking and minimizing the centralization of slashing risk away from a single hardware operator. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/296f9a925590.jpg) In a more recent development, EtherFi has expanded into staking and liquid restaking verticals with their eETH LST/LRT hybrid. Here, users can mint eETH by staking ETH, which not only generates native ETH staking yield but is also natively restaked on Eigenlayer, thus enabling holders to receive double the staking rewards they earn from vanilla staking. This system differentiates itself from stETH (Lido) by eliminating the need for an additional restaking action on Eigenlayer, simplifying the process for users. Additionally, users will be able to further utilize their eETH in DeFi to earn additional yield if they wish to do so. ### Mechanism Design At the core of EtherFi's mechanism, ETH validators point their withdrawal addresses to Eigenpods. This setup allows users to earn Eigen points, which are expected to convert into protocol rewards later. In the current landscape of EtherFi's staking mechanisms, it's crucial to understand that without Actively Validated Services (AVS) being live, a Liquid Restaking Token (LRT) effectively operates in a manner akin to a Liquid Staking Token (LST). However, with the future activation of AVSs, it is expected that LRTs will yield relatively higher rewards, though they may also bring increased risks from additional slashing conditions. ### Renzo (ezETH) Renzo (ezETH) is an LRT platform and Strategy Manager for Eigenlayer. It is built to serve as an interface for Eigenlayer, abstracting away many of the technical, financial, and risk management barriers for market participants and enabling easier access to the emerging restaking primitive. The same way Eigenlayer enables any distributed system to inherit Ethereum’s security, Renzo enables any on-chain user to help secure the networks being built on top of this new primitive–AVSs. Renzo helps bridge the gap between the AVSs which need security, and users who are attempting to balance the risks and rewards of restaking. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/3715eb1ecdb4.jpg) **Mechanism Design** Users can deposit either ETH or any supported LST (stETH, rETH, cbETH) on Renzo to mint an equivalent amount in ezETH. For every 1 ETH/LST deposited, 1 ezETH is minted. Formally the value flow runs from ETH Staking → Eigenlayer AVSs → Renzo Restaking. By securing Eigenlayer AVSs, Renzo offers a higher yield than vanilla staking and is thus expected to drive more volume and participation to ETH staking as a whole. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/2aa677d6a819.png) ezETH is a yield-bearing asset which works similar to Compounds cTokens, where the value of ezETH reflects the restaking rewards earned on the underlying position; generally the price of ezETH increases relative to its underlying LSTs as the position accumulates rewards earned in AVS tokens. Rewards are distributed in ETH, USDC, and AVS tokens. The core function of Renzo is to help secure Eigenlayer AVSs, and the protocol offers restaking strategies where users can decide to secure one or more networks to earn yield. As each AVS represents a unique entry for rewards (as well as risk), the restaking ecosystem will supposedly benefit from a greater number of AVSs, as this brings in more diverse strategies for restakers. This opens up the doors for new opportunities for protocols and services to be built and implemented; ecosystem-native LRTs which secure a specific AVS and offer holders unique opportunities such as priority execution and fee rebates, financial primitives such as risk/reward management strategies for LRT holders, dual-staking marketplaces, and more. Furthermore, upon launch, any team will be able to permissionlessly build the restaking infrastructure end-to-end to benefit from the restaking ecosystem while controlling the entire flow with or without a token, enabling teams to custom-build infrastructure to meet their specific preferences in a flexible manner. ## RestakeFi Restake Finance refers to itself as 'the first modular liquid staking protocol for EigenLayer. A user will be able to deposit their ETH or stETH in EigenLayer via smart contracts governed by the Restake Finance DAO. In turn, depositors will receive rstETH, which incorporates a rebasing and yield-bearing mechanism. Re-basing will occur on a daily basis, resulting in an increase in rstETH in your wallet. Please note that this does not include the yield earned from EigenLayer; that requires a separate claiming mechanism. ![](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/0fc681615b5a.jpg) The unique mechanism behind Restake is that depositors will eventually be able to choose the modules they want to validate. A user has the option to validate as many (or as few) pods as they prefer. A risk-averse user will likely opt for a single pod with an established team and track record, while a user with a higher risk appetite may seek more yield and, consequently, choose to validate more pods. ### Puffer (pufETH) Puffer Finance aims to stimulate validator decentralization through a network of homestake nodes by reducing the initial amount from 32 ETH to 2 ETH. This is made possible by a novel remote signing tool known as ‘Secure-Signer,’ which aims to prevent slashing risks while utilizing Trusted Execution Environments (TEEs) such as Intel SGX. The Secure-Signer tool manages validator keys on behalf of the consensus client and can be run locally or remotely. When running within a TEE, it secures the validator keys using applied encryption when the keys are at rest, ensuring they cannot be used otherwise. ![Source: Puffer docs](https://shoal.xyz/research/writing/liquid-restaking-tokens-a-new-frontier/img/5c6271bdda9e.jpg) In addition to the TEE, validators also benefit from having their keys secured within it. Puffer is unique in that it can support Application-Specific Validators (ASVs) that require some form of privacy, such as privacy-preserving Layer 2s. To actively participate in the validation set of a designated ASV, a staker (referred to as a Puffer) can deposit any amount over 0.01 ETH, which is added to a pool of ETH. This pool serves as a reserve that can be tapped into to form a new node for validators. This ETH will be staked if the requirements (32 ETH per node) are fulfilled, and in return, a Puffer will receive pufETH, a yield-bearing token similar to Compound’s cToken structure, which increases in value over time due to the accrual of rewards. To redeem their underlying ETH, Puffers can burn their pufETH, receiving the original ETH and accrued rewards if there is sufficient liquidity in the withdrawal pool. To facilitate this, a portion of all deposited ETH into Puffer Finance, as well as rewards and node withdrawals, is added to the withdrawal pool to provide exit liquidity. ## Conclusion In this piece, we’ve explored the evolution of Ethereum’s consensus mechanisms (both past and present), focusing on the transition from PoW to PoS, and the innovative development of LSTs and LRTs. Ethereum’s Merge introduced PoS to the network, which marked a significant shift towards more sustainable and scalable blockchain security. LSTs emerged as the solution to the liquidity challenges stakers originally faced, allowing users to participate in DeFi while staking. The LRT further builds upon this, offering enhanced yield opportunities and security contributions for users participating in Eigenlayer’s restaking ecosystem. The benefits of LRTs are not without their risks. This research covered the most pertinent risks to LRT holders such as composability, the potential for slashing, and the complexities that arise in the management of restaking positions and their risk profiles (i.e. what AVSs they opt-in to and why). We also highlight the innovations in the space, including projects like EigenLayer – the pioneers of restaking – and platforms like KelpDAO and Puffer Finance that aim to democratize access to restaking via their LRT solutions. Overall, the piece provides a comprehensive analysis of the current state and potential future of Ethereum's consensus mechanisms, highlighting both the opportunities and challenges in this rapidly evolving landscape. The integration of restaking into Ethereum's ecosystem represents a significant milestone, offering a more sustainable and scalable approach to blockchain security and opening up new avenues for yield generation in the DeFi space. ## Sources - [Stake with Ether.fi](https://etherfi.gitbook.io/etherfi/getting-started/stake-with-ether.fi) - [by Kelp DAO](https://kelpdao.xyz/litepapers/rsETHLitepaper.pdf) - [EigenLayer](https://dune.com/21co/eigen-layer) - [EigenLayer Docs](https://docs.eigenlayer.xyz/overview/readme) --- ***Investment Disclosure.** Disclosure: Members of Shoal Research hold material positions in the assets discussed in this article. The content presented is for informational purposes only and should not be construed as financial or investment advice. Please perform your own due diligence before making any investment decisions.* --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # CoW Swap: Intents, MEV, and Batch Auctions > Low Fees and MEV-Resistant Trades: Made possible through intent-based architecture - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-11-27 - Canonical: https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/ - Keywords: AI agents, stablecoins, crypto, DeFi, solvers, market making, MEV, Ethereum, Research ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/99676333a4ec.jpg) *Special thanks to [Anna](https://twitter.com/AnnaMSGeorge) and [Alex](https://twitter.com/VinyasAlex) for feedback and input on CoW Swap and its novel design mechanisms.* > ***Shoal Research Contributors**:* ## Key Takeaways - CoW Swap is an **intent-based application** that allows users to leverage signed messages to express their intent to trade (e.g. swap token A to token B) - A **batch auction** mechanism is utilized, in which a network of solvers compete amongst each other to maximize user orders surplus, via **[Coincidence of Wants (CoWs)](https://blog.cow.fi/what-are-cows-on-cow-swap-e72baaa4678a)** discovery and routing of trades to the best available liquidity on-chain - The unique architecture employed allows CoW Swap to offer interesting features including **CoW Hooks** and **Time-Weighted Average Price (TWAP)** orders based out of the new Composable CoW Framework - Additional benefits of using CoW Swap include **MEV resistance**, **low fees / gasless orders**and **security by having solvers approve new contracts on your behalf** ## Introduction ![Source: CoW Swap Dune Dashboard](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/c6ae3d8ba3e3.jpg) Recently, CoW Swap has been gaining the hearts of traders, apparent from the constantly growing monthly trading volume. It’s well known for possessing an intent-based architecture, a narrative that has caught the attention of many with its user-friendly interface. However, under the hood, CoW Swap has a lot more than meets the eye. The CoW Swap team has been building non-stop, delivering prominent features, including (a) MEV Blocker (b) Limit Orders (c) Time-Weighted Average Price (TWAP) (d) CoW Hooks (e) Milkman ERC1271 orders and (f) Programmatic Orders. This article will dive deep into the fundamentals of CoW Swap, explaining its architecture and the benefits brought about by it. We then end with an overview of the current protocol developments and what to expect from the protocol in the future. ## What are AMMs? To uncover the innovation driven by CoW Swap, one must understand automated market makers (AMM), a type of decentralized exchange (DEX) that allows users to trade one asset for another. AMMs use liquidity pools to match traders with liquidity for their trades, rather than a peer to peer approach typically used in traditional finance. For example, a user that wishes to swap ETH for USDC can do so in a ETH/USDC liquidity pool. Upon the swap, the ratio of ETH to USDC changes, to which the AMM will re-price the ETH remaining in the pool. To understand more about AMMs, you can refer to this link [here](https://www.gemini.com/cryptopedia/amm-what-are-automated-market-makers#section-automated-market-maker-variations). AMMs typically require traders to submit a transaction from their wallet to be able to interact with the liquidity pools for swapping. As a result of this necessary interaction with the pools, AMMs settle trades in a sequential manner, based on the change in liquidity upon each swap. CoW Swap employs an intent based design which innovates on the traditional AMM design, connecting traders directly (when possible) with each other without using pools. Benefits of this innovation include lower fees and better execution prices, which will be explained in the later part. To understand the core innovations one must understand what intents are to begin with. ## What are Intents? Intents refer to the desired goal of a user, for example ‘I wish to swap USDC for ETH’. An intent-based protocol facilitates on-chain activities by abstracting the complex processes associated with it. A user can declare the end goal they wish to achieve ‘I wish to receive ETH’, and specify certain parameters ‘I wish to receive ETH by swapping USDC’. This message can then be signed to authorize sophisticated third-parties known as solvers to execute the intent, eventually delivering ETH to the user. **Here’s a visualization of an intent-based system:** ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/9b9d58fa7c55.jpg) Intents help make the process of achieving on-chain goals easier and less technical. Instead of going through a complex process to complete a transaction, a person can set their goal and some rules, and let others handle the technical details to make it happen. In practice a user can define the terms, and sign a message that other parties fulfill. This makes completing transactions on-chain simpler and more user-friendly, especially when multiple goals can be grouped together in one go, saving time and resources. To learn more about intents, you can refer to this article [here](https://medium.com/metaweb-vc/account-abstraction-and-suave-how-far-are-we-from-an-intent-centric-ethereum-907e30804880). ## Introduction to CoW Swap CoW Swap emerges as a premier example of intent-based applications, where users indicate their desired trade outcome, delegating the execution to third-party, permissionless agents called **solvers**. The core mechanism utilized by CoW Swap is known as batch auctions, which aggregates users’ intent (the orders they wish to carry out). Solvers compete to offer the most optimal execution route for these orders, which will maximize the user surplus (the amount of asset received by user after swap). The execution methods used by solvers can be a combination of both off-chain matching and on-chain swaps. Solvers are rewarded upon successful execution of orders within the batch auction. The key difference between CoW Swap and other AMMs is the utilization of [Coincidence of Wants (CoW)](https://blog.cow.fi/what-are-cows-on-cow-swap-e72baaa4678a), where overlapping user intents can be matched without being routed through a pool. This offers higher gas efficiencies and lower cost for users. In addition, given that user orders are not being routed through a public mempool, CoW Swap mitigates [Maximal Extractable Value (MEV)](https://internbreakdowns.substack.com/p/intern-breakdown-2-mev) problems, further contributing to a more optimized swap for users. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/e1202c895cd9.png) ## CoW Swap Transaction Execution Mechanism ### Batch Auctions CoW Swap’s batch auction mechanism aggregates orders and settles them together at once, in comparison to the traditional sequential execution of orders. Batch auction serves as the core pricing (price discovery) mechanism for CoW Swap. Orders are grouped together, where solvers (off-chain counterparties) compete to execute these orders either through off-chain matching or on-chain DEXs. Solvers utilize advanced computations to customize trading routes for all orders in the batch auction, based on the user inputs (e.g. price, slippage tolerance etc.). Orders that fulfill Coincidence of Wants can be executed off-chain, while the remaining orders can be routed to other AMMs or DEX aggregators for execution. Thereafter, the settlement logic is passed on to protocols for execution, who are responsible in validating the execution legitimacy (approval of transaction etc.). **Let’s visualize the workflow of a batch auction:** 1. A group of 4 users on CoW Swap submitted their orders off-chain via intents 2. These orders are aggregated into a batch and forwarded to the solver network 3. Solvers compete to provide the most optimal execution: They will use their respective algorithm to identify the best execution route possibleCoincidence of Wants: Where orders match, the trade will be executed off-chain directly between the tradersRemaining orders that did not managed to be matched will be settled on AMMs / DEX aggregators 4. Solvers submit their settlement solutions to the protocol who then ranks them based on surplus maximization and proceeds to push on-chain the winning settlement ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/56491ba1d5c6.png) The main motivation of utilizing a solver network is to maximize the amount of assets that users can receive. This is achieved through the competition amongst solvers to source for the most optimal trading route with their fulfillment algorithm. ## Solvers Essentially, solvers compete to provide the best batch auction settlement by first identifying Coincidence of Wants within the batch. Thereafter, solvers will take note of any remaining trades that did not manage to be settled, and search through AMMs or DEX aggregators to settle them with the lowest slippage. **A detailed look into the workflow of solvers:** 1. At the start of a batch, all off-chain orders are considered for inclusion 2. Selected off-chain orders will be aggregated into a batch auction by the protocol. Note: After a batch closes, no new orders will be included 3. Solvers receive the orders in a batch and proceed to optimize the order with the goal of having their respective order settlement solution pushed on-chain 4. The solution that offers the best clearing price, maxizming traders’ returns, will be selected 5. Winning solver will receive rewards in the form of COW tokens which are granted by the protocol to incentive solver competitionAt the moment, the entirety of the fee charged to users is used to cover ethereum gas fees. That said, it's been proposed on the [CoW DAO forum](https://forum.cow.fi/t/cip-draft-testing-fee-models-for-cow-protocol/1984), that the protocol may experiment with different fee models At this current stage of the protocol, CoW Swap utilizes an allow-list authentication contract to determine the addresses that qualify as solvers. In addition, an address can qualify as a solver if they provide a bond stated on [CoW DAO CIP7](https://snapshot.org/#/cow.eth/proposal/0x267edf7a0bd3c771cfca763322f011ee106d8d5158612c11da29183260d1dba7) (CoW Improvement Proposal). Upon discovery of malicious behaviour (deliberately not providing users with the best execution route etc.), the bond will be slashed. Thus, this bond is meant to ensure that solvers are aligned with both CoW Swap and users. Nonetheless, most solvers do not have such a hefty amount of upfront capital. In these scenarios, solvers can be vouched by any existing bonding pool owner. The competitive landscape of CoW Swap's solver network is rapidly evolving. Initially, DEX aggregators like 1inch and 0x dominated, settling over 50% of transactions. However, their market share has declined, now accounting for less than 4% of transactions. In contrast, advanced solvers such as [Barter](https://twitter.com/BarterDeFi) and [Otex](https://otex.tools/) have risen to prominence, now handling the majority of solver volume. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/0f2ff27dd7e0.jpg) Sophisticated solvers can source liquidity from intricate places, which are generally not accessible by DEX aggregators. This might’ve caused existing DEX aggregators’ market share to decline, tipping the scale in favor of independent solvers. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/80f762e20b05.jpg) Now that we have understood the general concept of batch auctions and the role of solvers, let’s take a deeper look into Coincidence of Wants and how they play a critical role in CoW Swap. ### Coincidence of Wants (CoWs) For traditional finance incumbents and even non-crypto natives, it might be eye opening to see a protocol named “CoW” Swap, transacting hundreds of millions of dollars of digital asset volume. CoW refers to Coincidence of Wants, which is an economic phenomenon where two parties each hold an item the other wants, allowing them to carry out a direct exchange. To understand this better, let’s take the example of Alice and Bob: - Alice wants to swap 1000 USDC to ETH - Bob wants to swap ETH into 1000 USDC In the above scenario, it is clear that CoW exists. This allows for trades to be settled directly between Alice and Bob, without the need for external market makers or liquidity providers (LPs) to provide the liquidity for trade execution. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/b7b99a7fa839.jpg) Coincidence of Wants can vary in their complexity, these figures are a good depiction of simple, batch and intermediate Coincidence of Wants. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/9dbacc5585cd.png) ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/d45b826d156b.png) ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/71bcd8cc8cd7.png) ### Ring Trade What happens when there are more than 2 orders involved in a batch, and there isn’t an exact Coincidence of Wants to allow for these orders to be settled directly amongst each other? Instead of having to wait for an exact match between 2 parties, ring trades allow for liquidity to be shared amongst various parties as shown in the figure below. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/7f1e604da133.jpg) From the figure above, it's clear that participants don't need to have exactly what the other party wants to complete a trade. They can leverage the broader network of participants in the batch auction to acquire the desired asset. On the contrary, execution of these 4 orders on traditional DEXs will take place in a sequential manner, exposing all participants to potential price slippages and MEV. We'll delve deeper into the concept of MEV later in the article. It is important to note that every ring trade is considered as a Coincidence of Wants, but not every Coincidence of Wants is a ring trade. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/083b3e3081cd.png) ## CoW Swap Features Now that we have understood CoW Swap’s core architecture, we can dive into the unique features made possible. ### CoW Hooks CoW Swap utilizes ‘hooks’, which are custom code attached to an order that can be executed before and/or after a trade. Hooks are useful because they can save users time and gas by turning multiple transactions or intents into a single intent. This is the crux of CoW Swap’s intent-based architecture. CoW hooks make it possible for users to string together a series of complex actions, which may include bridging, staking, swapping, provision of liquidity and many more, and execute this series in a single transaction. **CoW Hook Architecture** 1. **Pre-hooks** Pre-hooks are intents that can be encoded into an order, and will be executed prior to a swap on CoW Swap. These actions are executed prior to an order’s signature being checked or tokens being sent from the user's address to CoW Swap. 1. **Post-hooks** Post-hooks on the other hand, are actions that are executed after the swap has completed, where the swapped tokens have been transferred to the user's address. ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/976ab6b882e6.jpg) Let’s take a look at a specific example, where a user stakes on Lido, after closing a loan position on Aave. 1. Pre-hook: Close an open position on Aave by repaying the loan collateralized by USDC 2. Swap: USDC will be converted to ETH through CoW Swap 3. Post-hook: Stake ETH through Lido Fees associated with hook execution are charged in the sell token of the swap, and cover 100% the execution costs. For example, when closing an open position on Aave, any additional fees will be paid in USDC. There is no need for users to hold onto additional ETH for the orders to be successful. This is beneficial as the process becomes more seamless, and prevents users from being unable to execute transactions due to lack of gas tokens. **CoW Hooks Use Cases** **Some of the potential use cases made possible by CoW hooks include** 1. **Repaying a debt → Staking** As mentioned in the above example for pre-hooks and post-hooks 1. **NFT sniping → Selling the NFT → Swapping tokens** Upon selling a sniped NFT, the amount received can be immediately swapped into the desired token. This reduces the asset volatility experienced by users 1. **Claiming airdrops** Sell airdrop tokens, while using airdrop tokens as gas 1. **Automated LP position management**a. Collect LP rewardsb. Convert LP rewards into 50/50 of each asset in the LP pairc. Deposit both assets back into the liquidity pool to increase LP position ![](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/6b9b60d0842d.jpg) The image above shows that CoW hooks aren't just for DeFi activities, rather, they have a broad range of use cases. Various users, including NFT snipers and airdrop farmers, can also benefit from hooks. Over time, CoW hooks will likely introduce more nuanced and sophisticated use cases, catering to a wider range of users. ### Time-Weighted Average Price (TWAP) Orders **What is TWAP?** Time-weighted average price (TWAP) is one of the most common algorithmic strategies used for executing trades. It is typically utilized when traders have a large order size and wish to reduce the impact on the market, as well as the slippage they suffer from it. For example, if a trader buys $1 million worth of $COW all at once, the price impact can be significantly high on AMMs due to the lack of liquidity. To prevent the price impact, a TWAP order would split the large order into smaller orders, which are executed over regular intervals, for a set period of time. Put simply, traders using TWAPs orders spread trades over time based on the average price in the TWAP calculation. **Mechanism of TWAP Orders [In Beta]** With CoW Swap, users can make a TWAP order by simply specifying the following metrics - **Asset of choice (e.g. USDC/ETH)**Users choose the asset they wish to swap out of and the asset they wish to swap into - **Total order size**Total amount to be swapped - **Number of parts**This is the number of times the order will be split into - **Duration**This refers to the length of time over which the order will be executed The amount to be executed per swap can be calculated by total order size / Number of parts. And the intervals at which the swaps will be executed can be calculated by Duration / Number of parts. ![CoW Swap’s TWAP Order Interface](https://shoal.xyz/research/writing/cow-swap-intents-mev-and-batch-auctions/img/8435827e000b.jpg) In addition, users will also be able to specify the price protection. The TWAP order placed will not execute should the price of the asset drop beyond the percentage set for price protection. This is meant to protect the user’s capital and prevent them from buying into a potential black swan event (e.g. cascading liquidation) that could result in them entering a position with disadvantageous prices. **Benefits of TWAP Orders** There are multiple benefits that users can gain through TWAP orders: 1. **Reduced Price Impact** Users typically have to pay a higher price when executing large orders on automated market makers (AMMs). This is due to the price impact of the order, where the inflow of large volume causes the price within the liquidity pool to spike up. In addition, big orders are also prone to [sandwich attacks](https://coinmarketcap.com/academy/article/what-are-sandwich-attacks-in-defi-and-how-can-you-avoid-them) by MEV bots, essentially inflating the purchase price for users. With TWAP, the orders made each time are of smaller sizes. As apparent from the above figure shown for TWAP’s mechanism, instead of executing a $1000 order, it is split into 5 x $200 orders. This effectively reduces the price impact that users suffer, allowing them to swap at a fairer price. 1. **Reduced Slippage** With bigger orders, users generally have to account for a higher slippage for the order to be filled. This is due to the price impact it brings to the market, which requires the slippage to account for the difference. With smaller orders, users can set a lower slippage. This allows them to execute the order at a price point closer to what they desire. In addition, it also helps them to reduce the amount lost to slippage, in turn receiving more of the desired assets. 1. **Increased Flexibility** Users are able to customize the various metrics to decide how much they want to execute over each interval. In addition, since the order is submitted off-chain, users will be able to make changes to their TWAP orders based on market conditions, without incurring additional fees. ### CoW Swap’s Unique Benefits MEV-Resistance Maximal extractable value (MEV) refers to the profit that validators can earn through arbitrage, which includes inclusion, exclusion and re-ordering of transaction sequence while building a block. Often, MEV is seen as a negative externality as they result in users suffering from unfavorable prices or failed transactions. Broadly speaking, there are 3 types of MEV: (a) Front-running (b) Back-running (c) Sandwich Attacks: - **Frontrunning:**Attacker places a transaction before a targeted user’s transaction to benefit from the upcoming transaction. - **Backrunning:**Attacker places a transaction after a trade to benefit from the already placed transaction. - **Sandwich Attack:**Attacker places a transaction before and after a user's transaction to manipulate the asset price, thus profiting from arbitrage. To understand more about MEV and examples, you can check out this article [here](https://internbreakdowns.substack.com/p/intern-breakdown-2-mev). With CoW Swap, there are 2 main mechanisms that minimizes the level of MEV users are exposed to: 1. **Coincidence of Wants: No Exposure to Transaction Order Manipulation** Traditionally when trading on a DEX, users will submit their orders, which will be sent to a public mempool, which is where transactions sit before being confirmed by validators. This public mempool is heavily monitored by bots looking to profi from arbitrages. On CoW Swap, user orders are submitted and matched off-chain through solvers. Hence, the orders are not routed through a public mempool, preventing any other users from potentially front-running the order. Here’s an example of MEV that could occur in a typical DEX. Claire wishes to make a swap 10,000 USDC into ETH, a user that is monitoring the mempool will attempt to insert their own transaction (swap 10,000 USDC for ETH) before Claire. This increase in ETH demand will cause the ETH price to increase. When it’s time for Claire’s swap to execute, she will be faced with a higher ETH price, resulting in her receiving less ETH than what she originally had. 1. **Batch Auction: Uniform Clearing Price (UCP)** Typically, orders on a DEX are executed in a sequential manner. This creates the opportunity for MEV as builders can re-order the transaction ordering to generate profits. However, this change in execution order results in users receiving different prices for their trades. For example, an order executed later might have to pay a higher price, causing the user to receive less assets than what would have been the original case. With CoW Swap’s batch auction, a mean settlement price will be calculated for all orders within a batch. Hence, there will be no MEV available for extraction since reordering of orders will be pointless. You can learn more details about the different types of MEV [here](https://blog.cow.fi/how-cow-swap-solves-the-mev-problem-fd35b0127390). ### Gasless Transactions and Low Fees One other key value proposition is the fee optimization made available to users, which comes from various aspects: 1. **Off-Chain Signing** Since the orders are submitted off-chain, there is no need for the users to pay gas with the chain native token. In addition, it is impossible for users to be faced with failed transactions, preventing them from paying unnecessary gas. In addition, since the orders are submitted off-chain, users are free to make as many orders as they wish, and are also able to cancel the orders as and when they want. 1. **Coincidence of Wants Transactions** Through direct matching of transactions, there are no additional fees charged to the users, which would have been the case should users have traded on other DEXs such as Uniswap. ### CoW Swap’s Future Outlook CoW Swap has laid down plans to further decentralize the protocol in the future. One aspect in which they do so is through a permissionless solver model which encompasses 2 main components: 1. Logic for solvers to be deemed suitable will be encoded into the smart contract 2. Staking of assets by solvers to disincentivize malicious behavior WIth a permissionless model, we can anticipate CoW Swap’s solver network to become highly robust. This eventually translates to better settlement for users, as the competition amongst solvers will strive to bring the best terms to users. ## Conclusion CoW Swap was one of the pioneers in experimenting on intent-based architecture and bringing it to the masses back in 2021. Since then, more projects have embarked on this field to optimize the various aspects. Anoma, is working on integrating intents into a chain. Propeller Heads, is working on fine-tuning the solver elements and searching for ways to make it more robust. With such a level of interest and research by the broader industry, it is certainly exciting to see how CoW Swap will continue to develop. ## Sources - [Introduction - CoW Protocol](https://docs.cow.fi/overview/introduction) - [CoW Swap Dune Dashboard](https://dune.com/cowprotocol/cowswap) - [CoW Hooks](https://blog.cow.fi/cow-hooks-you-are-in-control-480ccb40044a) - [An Introduction to Intents and Intent-centric Architectures | Blog - Anoma](https://anoma.net/blog/an-introduction-to-intents-and-intent-centric-architectures) - [Intent-Based Architectures and Their Risks](https://www.paradigm.xyz/2023/06/intents) - [How CoWs Will Save DeFi Swaps](https://pascalabams1.medium.com/how-cows-will-save-defi-swaps-132b760f9958) - [Introducing the Programmatic Order Framework, from CoW Protocol](https://blog.cow.fi/introducing-the-programmatic-order-framework-from-cow-protocol-088a14cb0375) ***Investment Disclosure.** Disclosure: Members of Shoal Research hold material positions in the assets discussed in this article. The content presented is for informational purposes only and should not be construed as financial or investment advice. Please perform your own due diligence before making any investment decisions.* --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # MEV Protection: DEX & Aggregator Anti-MEV Mechanisms > A look into decentralized exchange measures reducing maximal extractable value on swaps. - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-11-20 - Canonical: https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/ - Keywords: crypto, DeFi, MEV, yield, infrastructure, Ethereum, Research ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/bd190b3cb2ce.jpg) ## Intro To MEV Maximal Extractable Value, formerly Miner Extractable Value, refers to the profit captured through the reordering of transactions in the block production process of a blockchain. MEV is an additional form of revenue for validators beyond the block subsidy and transaction fees they earn by default - which has created a critical shift in incentive dynamics and end-user outcomes. Block production is a 24/7 continuous process which requires a lot of computational effort - decentralized exchanges see [billions in transaction volume per week](https://dune.com/ptmfv/dex-trading-volume-past-30-days) (often per day), and computational effort comes at the cost of transaction, or *gas fees.*Processing transactions sequentially, in ‘true order,’ is not quite attractive - the actors involved in the block production process are incentivized to not only cover the costs of their efforts but also to make a profit (oftentimes a significant one at that). Therefore, transactions in a block are ordered by gas fee - highest paying transactions are placed at the top of the block. For the user, getting to the top of the block (or as close to it as possible) means better settlement on a trade. Therefore transactions in a block are ordered by gas fee - highest paying transactions are placed at the top of the block. For the user, getting to the top of the block (or as close to it as possible) means better settlement on a trade. Transactions on the blockchain are an abundant source of value - and resourceful entities compete with one another to capitalize on information asymmetries and network inefficiencies in order to extract the *maximal extractable value.*On Ethereum, validators are the ultimate beneficiaries of this design, as gas fees are an increasing function of the competition for transaction ordering. ### How MEV Works ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/8e88f5ba2925.png) Validators are incentivized to order transactions based on the fees paid per transaction, with priority going to the highest-paying transactions. However, users are not just competing with other users for priority inclusion - hiding in the shadows of the[dark forest](https://www.paradigm.xyz/2020/08/ethereum-is-a-dark-forest) are *searchers,*taking advantage of information asymmetry to “win the game” of block priority. A searcher is simply someone who deploys a bot to constantly scour the public mempool for lucrative opportunities in pending transactions and then capture a profit by submitting their own replica transactions at the expense of the original transaction. To be a bit more specific, a lucrative opportunity could be a pending transaction which could impact an asset’s price when executed (*i.e. a fairly big trade of a low-liquidity asset*). Searchers who detect this opportunity will then replicate the transaction but pay a higher fee to get included in a block first. Validators don’t really care whether the transaction comes from a user or a searcher (in fact, searchers can [vertically integrate with a builder](https://x.com/yunfan0x/status/1694756822878671251?s=20) or even run their own builder). This is a relatively simplified description, but just consider that all these complexities are taking place while you, the user, are simply complaining about how much you paid for gas while waiting for your transaction to confirm. ### Types of MEV MEV is usually extracted through **arbitrage**- price discrepancies for a trading pair across different venues, such as blockchains, dApps, and even centralized exchanges. Value is captured when asset A is bought at a lower price on Venue A, and sold for a higher price on Venue B. Arbitrage can occur between two on-chain venues, or an off-chain: on-chain (see [loss versus rebalancing](https://a16zcrypto.com/posts/article/lvr-quantifying-the-cost-of-providing-liquidity-to-automated-market-makers/)). - **Liquidations** are another opportunity for MEV extraction - collecting the discounted assets of a liquidated position on a borrow/lending protocol, though [data](https://eigenphi.io/) shows that these opportunities are nowhere near as common as arbitrage. - **Front-running -***A new transaction (A) is broadcasted with a higher gas price than an already pending transaction (B) so that A gets executed before B.* This is a common economic phenomenon in TradFi - trading firms front-running clients who have expressed their desire to execute a certain trade. In DeFi, regular users are the ones getting front-run and subjected to poor settlement on their trades. *However, it is possible for [MEV bots to get front-run](https://x.com/blockworksres/status/1642910077089873921?s=20)too.* - **Back-running:**The inverse of front-running, **back-running** takes place when Transaction A is broadcast with a slightly lower gas price than already pending transaction B so that A gets executed right after B in the same block. - **Sandwich Attacks:**This strategy involves two transactions - one to front-run a transaction and bump up the asset’s price, and another to back-run the transaction and sell the asset for a lower price, creating worse settlement for the original transaction before the block has even been executed. The price of the asset will return to normal but the searcher will capture the difference between the original price and artificially inflated one. ![Sandwich attack visualized ( source )](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/4c4cf10f909a.jpg) **The MEV Debate** ![tweet (Frankie from Paradigm)](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/c9f96bc8f774.jpg) ## MEV Continued.. Opinions around the MEV phenomenon and how to approach it vary - some argue MEV cannot be eliminated, only mitigated, while others have even argued that MEV is ultimately a fundamental part of blockchains’ economies. On the one hand, MEV provides an economic incentive for sophisticated actors to stabilize prices and thus create more efficient DeFi markets - blockchains need validators to function, and validators need financial incentives to do their work. On the other hand, MEV subjects user trades to financial loss incurred by worse settlement and potentially disrupting network consensus in a worst-case scenario of a [reorg](https://www.alchemy.com/overviews/what-is-a-reorg). Furthermore, maximizing value capture requires above-average computational resources and often capital, benefiting institutions and larger validators. These resourceful validators can then open up staking pools offering higher yields than the competition, snowballing the centralizing effect of attracting more stake and more value capture. Blockchains are open and permissionless systems and those who are able to take advantage will do just that, but that doesn’t mean solutions to mitigate the externalities of adverse value extraction aren’t important (in fact they are the basis of this paper). ![The different facets of MEV, in a Utopian vs Dystopian setting. Source](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/e3f15c505669.jpg) There is a general agreement within the research community that the internalization of MEV (returning the profits generated by MEV back to the end-user) is an important design choice to build for. This can be expressed in different designs which will be discussed in this paper - we believe their adoption will be important for the greater good of on-chain economies. *MEV is an invisible tax extracted by specialized entities at the expense of regular users.* Users are the key drivers of the on-chain economy - therefore, user experience (UX) is a critical feature. This paper focuses largely on solutions for swapping assets, the most primitive and common form of transacting on-chain. If the average user cannot perform simple swaps in DeFi without getting the risk of being front-run or sandwiched (or even having to worry about this complexity), what is the use for DeFi long term besides a largely arbitrary idea of decentralization? What will stop on-chain users from eventually migrating back over to centralized solutions like CeFi platforms, which meet their needs without the MEV headaches? ### MEV-Mitigation Solutions Users are incentivized to seek out solutions for MEV-protection for a simple reason - **better price settlement**(i.e. not losing $$ constantly to slippage)**.**Instead of sending their transaction into the public mempool, where they are prone to being front-run or sandwiched, users can opt to send private transactions, which simply involve sending a transaction directly to a block builder using a private mempool. The builders are incentivized to access this exclusive transaction flow, as it allows them to build more valuable blocks. *The mempool is where unconfirmed transactions sit before they are confirmed by a validator.* ![source](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/31e4517c91b2.png) Data from Blocknative shows that the number of private transactions jumped from ~1% in September 2022 to nearly 15% a year since. **Order Flow Auctions** ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/3a0452873188.png) Order Flow Auctions, or OFAs, are a mechanism designed to redistribute value extracted (MEV) from transactions back to the end-user by auctioning for the right to execute an order, and distributing the winning bid to the user. It is the on-chain implementation of Payment For Order Flow (PFOF) in TradFi. Blockspace aggregators like MEV-Blocker or MEV-Share allow users to plug in private RPC endpoints from their wallets, helping protect users from sandwiching and front-running and internalizing users’ MEV. Signed transactions are routed to a private mempool, in which searchers compete in an auction to process the transaction. The winning bid in the auction is then paid out to users (for example, MEV-Blocker implements a 90/10 user: validator redistribution split). In this paper, we discuss several different OFA designs implemented by various DEX aggregators - Batch auctions (CoWSwap), RFQs (0x), and Dutch auctions (1inch, UniswapX). For a thorough explanation of OFAs, check out this [great piece](https://frontier.tech/the-orderflow-auction-design-space?ref=blog.anoma.net) from Frontier Tech. **Intents** ![source](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/ac84e8682eed.jpg) In the standard transaction process, users commit their transaction to a specific execution route once they sign it and submit them to the public mempool. This enables immediate execution but comes at the risk of loss of value in the trade due to MEV capture in the public mempool. This model also confines the user’s trade to one specific route, and assumes the user has selected the best possible one. On the other hand, an intent is essentially a signed user message that states the desired final outcome (*asset X for price Y*) - without a commitment to a specific execution path. While the user maintains custody of the assets, the execution itself is outsourced to third parties who compete to find the best execution path among many different sources of liquidity (including their own private off-chain inventory i.e. spot positions on CEX) and provide the best price settlement possible for the user. An easy way to think about this dynamic is in the context of one’s commute home from work, in a big city with various transportation modes. Hailing a cab on the street, or choosing which public transportation route to take ( bus A + train B or train A + train C etc) is like choosing a specific liquidity source in a standard transaction - you commit to a specific route under the assumption it is the fastest one home (often not guaranteed). On the other hand, if you use an app like Uber/Lyft or Google Maps, you are outsourcing the process of determining the best route for your commute to trusted, external parties. **A more formal definition of intents from [Paradigm](https://www.paradigm.xyz/2023/06/intents#what-are-intents):** *“Signed messages which allow for a set of state transitions from a given starting state, a special case of which is a transaction which allows for a unique transition*.” The benefits of using intents for placing swaps (as opposed to standard transactions) are centered around improved UX - this includes protection from front-running and sandwich attacks, accessing more sources of liquidity, abstracted gas fees, and avoiding failed transactions (as the order will not be executed if the users’ conditions are not met). ### The Role of DEX Aggregators Today Though MEV dynamics play out in the block production process, applications are the sources of the MEV. Therefore we believe applications play an important role in the overall adoption of MEV-protection solutions for retail users. Blocknative recently published a [research report](https://www.blocknative.com/blog/mev-protection-negative-settlement)highlighting the fact that private transactions using blockspace aggregator OFAs like MEV-Share and MEV-Blocker can actually create worse price settlement than their standard counterparts, as private transactions often don’t receive top-of-block priority. Even the CoWSwap team [has stated](https://x.com/CoWSwap/status/1712867313534246938?s=20) that “CoW Swap should also do a better job of managing price impact than using MEV Blocker alone.” Aggregatorsplay a valuable role for traders in DeFi. Often dubbed ‘Meta-DEXs’, these protocols  provide smart order routing functionality across a number of different liquidity sources, providing swappers with better pricing, and in some cases, native MEV-protection. This paper will specifically focus on the top DEX aggregators offering some form of native MEV-protection on swaps - CoWSwap, 1inch Fusion, Matcha, and the emerging UniswapX. ### CoWSwap CoWswap is the first DEX aggregator built on top of CoW Protocol, enabling users to swap assets and place limit orders with native Mev-protection. CoW stands for “Coincidence of Wants” , a barter economy in which one party has an item they wish to sell, while the other party is looking to buy that specific item, and the two parties can directly transact in a P2P manner. In DeFi, this refers to one trader holding a token they would like to sell, and another trader looking to buy that same token from them. ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/9f12812ae343.jpg) CoWSwap creates a private order flow marketplace enabling users looking to swap asset A for asset B for a defined price. Traders on CoWswap sign intents to express their desired trade outcome - these are then aggregated off-chain and settled in batches to be then executed on-chain. With standard transaction ordering mechanisms today, searchers and block builders are incentivized to create as many different prices for the same asset within a block to capture what is ultimately a risk-free intra-block profit. CoW Protocol aims to solve this issue through a uniform price clearing mechanism that *enables traders to get the same price for the same asset within the same block.* Instead of a central operator, CoW protocol delegates order matching to a decentralized set of order matching engines known as *solvers*who compete via *batch auctions*to ‘solve’ for the optimal order settlement within the given constraints of a limit order. A solver is a computer program that takes the orderbook as input, and computes the prices and traded amounts of all orders and liquidity sources (AMMs). In a batch auction, solvers are incentivized to compete to find the best settlement solution for users’ orders (the route of execution among different liquidity sources) in order to win the right to execute the batch and capture the surplus within a trade. Since user orders are aggregated off-chain, users technically don’t need to pay gas fees on CoWSwap. There is an [associated protocol fee](https://docs.cow.fi/off-chain-services/api/fee-mechanism) - but this is only required once per token. A full trading cycle on CoWSwap looks like: 1. Approve the Allowance Manager Contract in your wallet 2. Sign the order you want to place 3. Enjoy the tokens you just traded. Barring some occasional spikes in months prior, CoWswap volume has remained consistent since April 2021. There are more returning traders than new ones, which indicates CoWswap has found PMF among a niche group of users but will likely need to up its user acquisition efforts moving forward as the intents-based application space is likely to become more crowded. It is important to note having more solvers competing to fill batches creates a more competitive solver market and thus creates better price settlement for CoWSwap traders (*there are currently [18 active solvers](https://dune.com/cowprotocol/solver-info) in V3 under this model on Ethereum).* ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/fd6906f67265.png) ### 1inch Fusion [Fusion](https://1inch.io/fusion/) is the latest swap engine from 1inch, offering a gas-free swap experience with native MEV-protection. Users can choose between Auto, Fast, Fair, and Custom with various execution and rate parameters. ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/a2a0b5d70ec3.jpg) A set of market makers known as *resolvers*handles the process of executing swaps, which are actually limit orders under the hood, by competing with other resolvers via Dutch Auctions to find the best rate for said transaction and execute it. Once an order is filled, the resolver then places it into a bundle with other orders, and is submitted for inclusion in a block. *Note that since resolvers cover users’ gas fees, a settlement fee is charged to cover the costs on their end.* Each order has an auction start timestamp - before the auction begins, an order can be filled at the start rate(the maximum rate that a user can receive). Once the auction begins, the order filling rate gradually decreases over time. The trade is divided into parts, which results in several price points, assuming that arbitrageurs will backrun and move the price back after each resolver’s trade. Users benefit from better rates, while resolvers make a profit from each transaction. ![Source](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/71e233784cae.jpg) At the time of writing, Fusion has seen over $13b[in cumulative volume, and 1.6m orders from 582,029 unique wallets](https://dune.com/1inch/fusion) since launching in late 2022. ### Matcha Matcha is a multi-chain DEX aggregator from the [0x team](https://0x.org/) which allows users to trade tokens across Ethereum, Base, Arbitrum, Polygon, Optimism, Bnb, Celo, Fantom, and Avalanche. Matcha aims to optimize price settlement for users by sourcing liquidity from both on-chain and off-chain venues. Users can execute traditional *A for B* swaps or place limit orders. Matcha enables users to opt into use private liquidity sources - a feature enabled by 0x’s Request-for-Quote (RFQ) system. RFQ enables users to sign an order for the trade they would like to make, and request a quote on their trade from a set of designated, off-chain market makers. The quote, representing a transaction execution path, is enforced by a smart contract, ensuring against slippage and thus sandwich attacks. The market makers are incentivized to beat the on-chain prices available on AMMs to be included in a quote, in addition to beating other RFQ market makers - the more competitive this system is, the better the price settlement. ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/baaf98f1d72d.jpg) An interesting stat to observe is that RFQ liquidity seems to favor smaller trades (<$100), indicating that this design benefits more retail and casual traders. ![source](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/ab7688d27015.png) **Fees** Matcha does not charge additional fees on top of gas fees for most trades, but there are some exceptions for specific assets on limit orders. For example, Matcha Auto (new swap engine) charges a 0.15% fee on trades with native tokens. A full breakdown of Matcha fees can be found [here](https://help.matcha.xyz/en/articles/3953360-are-there-any-fees-to-make-a-trade) **User guide** ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/fc34e2f873ca.jpg) Trading on Matcha is relatively straightforward - the first step is to connect your wallet, and select between making a regular swap or using a limit order. In order to opt in to RFQ liquidity, make sure you check for ‘0X RFQ’ in your liquidity sources in the transaction settings tab. ### UniswapX UniswapX is a new non-custodial, Dutch auction-based trading protocol from Uniswap that introduces new methods for routing and aggregating liquidity. UniswapX marks an industry shift towards utilization of off-chain liquidity for on-chain settlement. We say this because while UniswapX does not introduce entirely novel concepts, Uniswap has been ***the*** dominant DeFi protocol (captured [over 50% of DEX volume](https://dune.com/queries/3091367/5156180) this past year alone) so it is worth paying attention to the protocol’s developments. The principle of UniswapX is a new liquidity marketplace which aims to benefit both LPs and traders- LPs to be properly compensated, and traders to enjoy better prices and abstracted gas costs. ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/7787575eeb7a.jpg) After a user submits a signed order stating their expressed trade intent, a network of *fillers* compete for the right to fill the order (fillers can be searchers, market makers, and/or other on-chain agents) in a [dutch auction](https://www.investopedia.com/terms/d/dutchauction.asp). It’s important to note here that the user can specify the filler that they would like to fill their order  - but once the auction begins, any order with better pricing can compete and win. Note that the system involves a [Reactor](https://github.com/Uniswap/UniswapX?ref=blog.anoma.net#reactors) contract for checking that the execution of a trade against the filler’s strategy matches the parameters set by the swapper, and an executor contract to be called to specify the filler’s strategy for fulfilling orders and actually executing the order. The goal here is to provide a better UX for swappers with improved price settlement and abstracted gas costs. *Don’t worry - swappers do not have to engage in any sort of auction to execute a trade.* One of the key value propositions behind UniswapX is MEV-protection. UniswapX internalizes MEV - in other words, returns surplus value (MEV) back to traders in the form of improved price settlement . This embodies the key ‘mev-redistribution’ principle behind OFAs and is in part inspired by the original [Mev-capturing Amm proposal](https://ethresear.ch/t/mev-capturing-amm-mcamm/13336?ref=blog.anoma.net). Additionally, orders executed by fillers’ cannot be sandwiched, and fillers are incentivized to bypass public mempools and use private transaction channels for on-chain settlement. **UniswapX is still in beta, so analysis of user trends and activity should be taken with a grain of salt.** ### Important Risks And Considerations The DEX aggregators we just listed utilize intent-based architecture to offer better UX and utility for users, but it is important to note a few critical issues with intent-based solutions and the implications of their widespread adoption. While user transactions may be safe from front-running and sandwich attacks within the public mempool, shifting the centralizing force of block builders to various middlemen imposes new risk vectors for both users and the ecosystem as a whole. Not only do on-chain LPs face [greater difficulty](https://x.com/0xshittrader/status/1703795437629583568?s=46), the widespread adoption of alternative mempools also poses risks of centralization, increased trust assumptions, and reduced transparency in the Ethereum ecosystem. **Increased Trust** The applications we have discussed in this paper require a set of trusted parties to fill user orders off-chain and execute them on-chain. This is an inherent tradeoff: bypassing the public mempool means there is that much more trust placed in the middlemen doing the actual bypassing. In the context of intent-based trading protocols, competition among the parties executing user orders is imperative for users to actually receive optimal pricing on assets. Some protocols are taking measures or have plans for further decentralization - for example, CoWSwap [envisions transforming](https://docs.cow.fi/overview/road-to-decentralization) its centrally hosted order book to a distributed p2p client network in the future. However, these are often long-term developments, and in the short-term protocols will often implement trusted solutions that optimize for performance. **CoWSwap Solvers -**Running a solver on CoWSwap involves significant knowledge and access to both on-chain and offchain liquidity sources, as well as strong predictive knowledge of slippage tolerances -  this is a comparatively similar skillset required for successfully running searchers. Solvers must be whitelisted in advance and follow a set of [social consensus rules](https://docs.cow.fi/solvers/in-depth-solver-specification/social-consensus-rules) - though accountability is not enforced by smart contracts but rather by the CoW DAO, which can enforce penalties and slashing. - **No provision of unfair solutions** - **No Inflation of the objective function** - **No illegal use of internal buffers** - **Incorrectly reporting transacted values for encoded transactions** - **Other malicious behavior**causing intentional harm to the user or protocol **1inch Resolvers -**Running a resolver on 1inch Fusion requires whitelist approval and sufficient account balance to pay for order fees. Whitelist approval requires 1) obtaining necessary ‘unicorn power’ threshold - this involves staking more $1inch (longer lock-ups = more power),  2) registration, 3) Account Balance for fees. Resolvers are ranked, and are held accountable by rules set and enforced by the 1inch Network DAO, as well as their performance; if they are not able to maintain a top 10 ranking they cannot fill swaps. **0x RFQ Market Makers -**0x utilizes private off-chain market makers for their RFQ liquidity system - in part, the system of the protocol itself holds market makers accountable, as the RFQ system only allows the specified taker address to fill an order, preventing front-running. While this [dashboard](https://explorer.0xprotocol.org/) provides comprehensive analytics for RFQ liquidity volume and trades and it is reasonable to assume there is some reputation or bonding-enforced mechanisms to keep MMs accountable, there are ultimately no definitive guidelines and rules available for what accountability looks like and how it is enforced. **UniswapX Fillers -**UniswapX outsources the process of transaction routing to an open network of fillers - who can tap into their own ‘private inventory’ to source liquidity for filling orders, private inventory being another word for off-chain liquidity. Currently, the filler role is only available to whitelisted entities during beta, but Uniswap intends to leave this role to be permissionless; according to Uniswap docs, [requirements for creating a filler](https://docs.uniswap.org/contracts/uniswapx/guides/createfiller) are simply a)defining a filler execution strategy and b) retrieving & executing discovered orders. This raises questions about what filler accountability may look like in practice, as Uniswap has not yet released a framework. It would be reasonable to assume the implementation of economic incentives (i.e. bonding/slashing collateral) here, and whether the Uniswap DAO will play a role as X’s [smart contracts and fee switch](https://gov.uniswap.org/t/uniswapx-and-the-dao/21718) will be governed by the DAO. This is an active area of research and will definitely be interesting to keep an eye on moving forward. Though there are measures in place to ensure market makers/fillers/solvers are acting in good faith and only reputable entities are able to fill orders, and permissionless mempools face their own [set of challenges](https://www.paradigm.xyz/2023/06/intents#permissionless-mempools), shifting more user activity to a new system that only increases trust assumptions does not contribute to a more decentralized DeFi ecosystem. Universal solutions for solver accountability, such as “[reputation based systems to build trust with the users based on their repeated engagement and enforcement of accountability](https://merklelabs.substack.com/i/136926260/accountability-among-the-solver)” , are evidently an important missing piece of the puzzle that needs to be accounted for if adoption of intent-based architectures continues to grow. **Less Transparency** Computing the order filling logic off-chain is critical for providing better UX (i.e., abstracted gas costs for users, protection from front-running and sandwiching) but it also comes at the cost of greater opacity in the overall block production of Ethereum. Private/permissioned mempools are just that - private. Analytics for these systems is limited, and a mass migration of user activity to private mempools and off-chain liquidity means that much less observability for both sleuths and the general public. **Slower Execution Times** Another caveat with intent-based trading protocols is that they often take longer to execute. For example, orders on CoWSwap and 1inch Fusion take up to 30 seconds to execute.  Slower execution time can lead to worse price settlement as the price of the asset can change in the time prior to an order getting filled. The process to determine the ‘ideal’ intent-based architecture still lies ahead, but it helps to reference this quote from Paradigm’s piece on [intents](https://www.paradigm.xyz/2023/06/intents#mitigating-risks): “**permissionless** so that anyone can match and execute intents while not trading off much execution quality; **general** so that deploying new applications doesn’t require standing up new mempools; and **transparent** so that the process by which intents are executed is reported publicly and data for execution quality auditing is made available, when privacy guarantees allow.” Dex aggregators play an important role in DeFi in helping traders swap assets with better price settlement due to their underlying mechanisms in which a set of market makers compete to provide the best price settlement for their trade. That said, they still pose constraints as settlement routes are restricted to their liquidity sources, not to mention new trust assumptions and reduced transparency in DeFi. Therefore when we consider the role of DEX aggregators moving forward, it is important to consider future developments in the intents landscape as well as the broader MEV-protection landscape. ### Future Outlook for MEV-Protection and Intents We believe the rise of private transactions in the past year indicates growth in overall demand for MEV-protection solutions within DeFi. More users are becoming aware of the invisible MEV tax and how it affects their on-chain trading experience (it wasn’t too long ago that the[jaredfromsubway.eth](https://etherscan.io/address/jaredfromsubway.eth) MEV bot was a phenomenon on Crypto Twitter) - and are thus more actively seeking solutions to protect their transactions from this tax. Though teams like CoW Protocol, 0x, and 1inch have been around for some time now, we are beginning to see a greater shift in interest and development around MEV-protection solutions - as leaders in DeFi like Uniswap begin to leverage MEV-protection as a value proposition (UniswapX, Uniswap Wallet). **Wallets and Order Flow Auctions** It is evident that wallets have and will continue to play a critical role in the MEV supply chain - wallets have been enabling users to set custom RPC endpoints such as  [Flashbots RPC](https://rpc.flashbots.net/) ,  [Mevblocker RPC](https://rpc.mevblocker.io) , and [Rabbithole (1inch)](https://1inch.io/rabbithole/) to send their transactions to an OFA for some time now. Most recently, Uniswap Wallet has introduced their Swap Protection feature, which natively [integrates MEV-Blocker](https://x.com/Uniswap/status/1705209238203900260?s=20)**.** The more intuitive and integrated MEV-protection solutions are, the more users will actually get to benefit from them. However, as we mentioned earlier it is important to consider the performance of these transactions may oftentimes be worse than regular transactions given they must compete for top-of-block priority for optimal settlement. The takeaway is that **convenience != performance**. **Account Abstraction and Intents** Intents have the potential to unlock a new paradigm of end-user experience - though we focus on swaps in this paper, we can consider further use cases such as intents for automation regularly occurring processes to improve crypto UX and make users’ lives easier (i.e. moving funds from cold to hot wallets or purchasing X amount of assets on a regularly occurring basis) The point is, we are still early in the overall adoption of intents. Account abstraction utilizes intents to provide better UX; using smart-contract accounts as opposed to the traditional EOAs will make it easier for users to natively submit generalized intents (called user operations or ‘userOps’) to express a desired outcome  So far, there have been 5,972,635[userOps submitted across](https://dune.com/queries/2516038/4141338)1007615 users since March. As account abstraction is expected to grow in adoption, we expect intents to have a greater impact on the DeFi ecosystem and crypto UX as a whole. ![](https://shoal.xyz/research/writing/mev-protection-dex-and-aggregator/img/1f159bea2c51.jpg) That said, it is important to note that ERC 4337 also imposes new vectors for MEV extraction. Bundlers, who are responsible for aggregating userOps submitted to the Alt Mempool, oversee the contents of userOps and can therefore reorder userOps in the most profitable order. If submitted to the public mempool, the bundle is then also subject to the traditional front-running and sandwich attacks. This two-fold MEV system leaks additional value from user transactions towards validators and introduces a further adversarial MEV environment. Furthermore, given the resources and skill-set needed to run a competitive bundler is similar to those needed to run a competitive builder (therefore benefiting resourceful entities), we can assume a handful of existing builders will seek to run bundlers as an additional MEV stream on top of the public mempool. To quote [Matt Cutler](https://x.com/mcutler/status/1638267976293158912?s=20) “ERC-4337 changes everything & nothing” A broader takeaway is that it is important to look beyond the guise of the improved UX account abstraction can bring, and consider the impact of ERC 4337 on userprice settlement in the short and long term. Within the context of our paper, it is also interesting to consider whether or not we see MEV-protection solutions integrate userOp bundles, or if the further adversarial MEV environment under ERC 4337 prompts more adoption of MEV-protection solutions instead. **General-Purpose Infrastructure for Intents** Although intents are not new, its applied utility has been limited to trading assets thus far. However, a number of teams have been working on general-purpose infrastructure for intents to enable developers to build intent-centric applications, and help mitigate centralization risks. further use-cases including [auctions, crowdfunding, P2P Lending, OTC NFT Lending](https://x.com/Delphi_Digital/status/1696626187378819532?s=20), and various other automated processes. Some critical developments include: - **SUAVE** (short for Single Unifying Auction for Value Expression). Flashbots is building a MEV-aware, intent-centric architecture built to allow chains to outsource the block builder and mempool roles by providing a shared sequencing layer. The stack consists of: a mempool where users can specify preferences (intents), an execution network where solvers compete to execute user preferences, and a block building environment. The goal is to decentralize the existing transaction/mev supply chain, while benefiting the parties involved - builders and validators can increase their returns, and users can transact with better execution. - **Anoma: intents-as-a-service for blockchains.**Anoma is a “unified architecture for full-stack decentralized applications” built from the ground up to enable greater adoption of intents by unifying settlement and counterparty discovery mechanisms, and preserving user privacy. This will enable applications to integrate various intent-based services and features for their users. - **Essential** is building intent-based infrastructure and tooling to “to accelerate the transition from value extraction to intent satisfaction”, including a universal DSL for intents, an intent-centric standard for account abstraction ([ERC 7521](https://blog.essential.builders/introducing-erc-7521-generalized-intents/), a proposed alternative to ERC 4337), and a modular protocol with native support for intents. It is important to note that these solutions are not going to be fully implemented in practice in the near future, and their true impact will only be realized in the long term. As we said before, we are early in the early stages of the intents landscape. Likewise, we are still early to developing a universal “tried and true” approach to dealing with the externalities with MEV. ### Conclusion As more users have begun to seek out ways to protect their transaction value from MEV, the concept of redistributing MEV seems to have become a commonly accepted one among researchers today, leading to an uptick in MEV-protection solutions. While traders in DeFi today have a handful of options to choose from for this purpose, they must also weigh the considerations and tradeoffs that come with intent-based trading protocols. Although not a new concept, intent-based protocols are still fairly nascent and underdeveloped, which is a critical point for those navigating this space. We encourage you to form your own opinions on the MEV debate and consider the evolving ecosystem with a critical eye. With the continuous innovations and commitment from project teams, the future for MEV protection looks promising and is poised for further value-add to end-users. ## Sources - [Enablement of MEV and the Morals of Extracting](https://www.cryptofrens.info/p/enablement-of-mev-and-the-morals) - [Flashbots: Frontrunning the MEV crisis](https://medium.com/flashbots/frontrunning-the-mev-crisis-40629a613752) - [EigenPhi](https://eigenphi.io/) - [Sandwich MEV - EigenPhi Classroom](https://eigenphi-1.gitbook.io/classroom/mev-types/sandwich-mev) - [The Orderflow Auction Design Space](https://frontier.tech/the-orderflow-auction-design-space) - [The False Narrative of MEV Protection: How Private Transactions Can Result in a Poorer Settlement Than Sending Publicly](https://www.blocknative.com/blog/mev-protection-negative-settlement) - [Intent-Based Architectures and Their Risks](https://www.paradigm.xyz/2023/06/intents) - [An Incomplete Primer on Intents — Emperor](https://crypto.mirror.xyz/Wvzro_O92V5Z_RBfZnZUqdbYC_4X6v2YrBuy9RkZCxo) - [CoW Protocol Overview](https://docs.cow.fi/) - [The most common types of MEV and protection from toxic strategies](https://blog.1inch.io/the-most-common-types-of-mev-and-protection-from-toxic-strategies/) - [What is a sandwich attack?](https://blog.matcha.xyz/article/what-is-a-sandwich-attack) - [Unlock optimal trades in Swap API with 0x RFQ liquidity](https://0x.org/post/unlock-optimal-trades-in-swap-api-with-0x-rfq-liquidity) - [A comprehensive analysis of RFQ performance](https://0x.org/post/a-comprehensive-analysis-of-rfq-performance) - [UniswapX](https://uniswap.org/whitepaper-uniswapx.pdf) - [Intent-based protocols pt1: unfolding UniswapX | Blog - Anoma](https://anoma.net/blog/uniswapx) - [Introducing Essential: We Are Intents](https://blog.essential.builders/introducing-essential/) - [Introductory Guide to Account Abstraction (ERC-4337)](https://www.blocknative.com/blog/account-abstraction-erc-4337-guide) --- ***Investment Disclosure.** Disclosure: Members of Shoal Research hold material positions in the assets discussed in this article. The content presented is for informational purposes only and should not be construed as financial or investment advice. Please perform your own due diligence before making any investment decisions.* --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # Banana Gun: Telegram Sniper Bot > Bringing MEV, Block 0, and token trading all in a single telegram user interface - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-09-19 - Canonical: https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/ - Keywords: crypto, DeFi, MEV, security, Ethereum ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/4da90ca81322.jpg) > ***Contributors**: Special thanks to [TomJ](https://twitter.com/UniswapVillain) and GS, who provided valuable insights into the token sniping landscape. Additional contributions were also made by [0xMoe](https://open.substack.com/users/134768328-0xmoe?utm_source=mentions).* ## Intro "Monkey see, monkey do" aptly characterizes the speculative Gamblefi underworld of crypto, where traders are driven by daily 100x gains, exit rugs, and liquidity pulls. Memecoins hold a unique allure in this realm, especially as traders follow both market pumps and influencers who shill (promote) these pumps on Twitter. Platforms like Banana Gun have emerged to equip users with the essential tools for high-speed trading. Maestro led the field a few years ago, initially gaining traction under its original name, Catchy. Maestro was the go-to platform for snipers traders looking to capitalize on short-term market fluctuations. Then came Unibot, which improved the space by focusing less on snipers and more on the average users frustrated by Uniswap's less-than-user-friendly UI. They focused strategically on referral fees to drive rapid growth, a tactic similar to what we've seen with platforms like Rollbit and Stake. Most recently, Banana has entered the scene, offering a competitive product to Maestro in sniping capabilities and more favorable in terms of fees. Banana seems poised to capture the hearts of the "degen" traders, those willing to take extreme risks for potentially enormous rewards. This fluid landscape underscores the constant evolution of platforms and strategies in the Gamblefi underworld of crypto, each striving to meet its user base's ever-changing demands and risk appetites. ## 9-5 Speculation Amidst the bear market and all-time low DEX volume since 2020, hundreds of ERC-20 tokens are deployed daily. For some traders, watching the memecoin market is a full-time job. All it takes is a 100x on a project to become highly profitable by purchasing among the first few and riding a token to a multi-million market cap. Traders can participate in multiple ways, including presales, sniping, and buying the token spot. - **Presale:** Allocating money ahead of the token launch. - **Sniping:**Automatically buying tokens using bots at the time of launch. - **Spot:** Tokens purchased outright on exchanges like Uniswap or Coinbase. Traders tend to decide their strengths and choose a few categories to focus their energy. Within this process, we will focus mainly on the sniping phase; let's dive in further. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/5ff36603d160.png) ## Token Snipers Before the advent of Telegram snipers, the game was all about expertise. Top coin snipers and botters would meticulously analyze memecoin contracts to identify critical functions triggering a coin's launch, maximum transaction sizes, and any developer-implemented measures to deter early buyers. With the advent of Telegram bots like Banana Gun and Maestro, that granular approach has been largely replaced. In a nutshell, token snipers are automated trading bots that enable users to execute swift buy and sell orders for newly launched tokens on decentralized exchanges (DEXs) like Uniswap. Many of these bots use Telegram as a platform. Developers prefer Telegram because it is where trade ideas thrive and it's also a crypto-native messaging app. The product-market fit for token snipers is clear, as users have adopted them at an increasing rate. Sniper bots can also purchase launched tokens with similar speed and efficiency, making up a majority of their trading volumes. These premier sniping bots now simulate entire contract functionalities, allowing users to bypass the user interfaces of platforms like Uniswap and simply decide how much ETH they want to deploy. This shift has made the sniping landscape more user-friendly but also intensely competitive. For example, in the case of Maestro, users still need to input maximum transaction sizes, and some familiarity with contract methods is necessary under the non-premium model. This is where Banana distinguishes itself—no such expertise is required, streamlining the process even further. This evolution can be contrasted with platforms like Uniswap, which recently removed its expert mode. While this change may benefit retail traders by adding a layer of safety against high-impact trades, it complicates matters for advanced traders who are now forced to adjust their strategies manually. The removal of expert mode has impacted sophisticated traders to the point they built their own front ends to improve the experience. It underscores why Telegram sniping bots like Banana Gun, designed for a more sophisticated user base, are gaining traction in the fiercely competitive landscape of ERC-20 token trading. By using these bots, traders not only optimize their strategies but also avoid the limitations imposed by retail-focused decentralized exchange interfaces. ### How does Sniping work? Imagine a trader eyeing the launch of $TOKEN in a few days. They simply load up their Telegram application and drop the smart contract into a token sniper. After specifying the amount of ETH they're willing to risk, it's a waiting game. As soon as the token hits the DEX pool, the Telegram sniper triggers, executing the pre-defined trade parameters. If all goes as planned, the trader enters at a 10k MCAP (hypothetical example), which skyrockets to 200k MCAP in a matter of seconds—a tidy 20x profit. But it's not that simple anymore. The efficacy of these sniper bots has led to an influx of traders employing the same strategy, often using ten or more wallets to edge out the competition. That's why just having a sniper bot isn't enough today; timing is crucial. Enter Banana Gun. Unlike other platforms that require manual inputs or specific monitoring, Banana Gun optimizes the process. Once the contract is added to the bot before the token's trading begins, Banana's snipers automatically look for smart contract triggers like the "EnableTrading" function, which will snipe/buy a token as soon as it launches. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/fdeec7a1f000.png) Snipers can also monitor for “liquidity add” transactions, which is adding ETH to the token pool, which would enable trading now that there is liquidity. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/6e30341fa18f.png) ## Banana Gun Banana Gun has fundamentally democratized the sniping landscape in the crypto space. Previously, sniping was an exclusive activity reserved for individuals with advanced technical skills who could read and configure smart contracts. Banana Gun has opened this door for everyone by automating much of the sniping experience. Their platform is designed with exceptional ease of use: You paste a contract and let the bot handle the complexities, such as determining the method ID, tax rate, and maximum transaction size. This feature sets them apart from competitors like Maestro, where users are required to read contract addresses and configure settings manually. The cornerstone of Banana Gun's unique selling proposition lies in its user-centric focus on automation and protection against most rug pulls. Going beyond mere automation, each transaction on Banana Gun is executed privately and comes with an Ethereum bribe set by the user. This clever mechanism gives you an extra layer of safety. In an environment where someone tries to execute a rug pull (scam) with an exorbitant gas fee, Banana Gun enables you to front-run them cost-effectively. The private transaction feature also ensures you can never get sandwiched or front-run. A sandwich is when traders (bots) exploit transaction ordering by placing trades before and after a user's transaction. In fact, Banana Gun goes a step further by reverting your transaction if they detect a risk of it getting sandwiched—even though it's executed privately. This nuanced feature is something that even competitors like Maestro lack. Speed kills, and Banana Gun is currently one of the fastest retail sniper bots on the market. It first launched in early June and has already amassed roughly 700 daily users, with over 12,000-lifetime users. ![Bot usage](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/29b508b9a7e5.png) When users buy, the interface is moved to a sell channel, where users can focus on the mechanics of selling. Typically, other sniper bots buy and sell in a single interface. ## Core Features ### Block 0 Bribe Wars Bribing is a cornerstone feature of Banana Gun, but it's worth noting that Maestro initially pioneered the concept of group bribing. Maestro's system made it extremely difficult for individual botters or snipers to outbribe a group of participants, effectively democratizing the process. Banana Gun, however, brought a fresh angle to this approach. While Maestro may have introduced group bribing, Banana Gun perfected it by attracting a smaller but more sophisticated and experienced user base. These individuals are well-versed in the mechanics of sniping and understand how to outbribe even a collective group. Banana Gun utilizes a custom RPC, a specialized node that communicates directly with the blockchain, allowing faster data transmission than standard providers like Infura or Alchemy. In this high-speed environment, pending transactions from Banana Gun's elite snipers are bundled together into a single transaction package. This bundle is then forwarded to the block builder, the Ethereum network validator responsible for grouping transactions. The battle heats up when the bundle reaches the block builder. Banana Gun snipers engage in blind bribing, where each participant offers a hidden bribe, also known as a "tip," to secure faster transaction confirmation. Take User A, for example, who buys Token X for 0.20 ETH and includes a bribe of 0.10 ETH. This bribe directly incentivizes the block builder to confirm User A's transaction more quickly. Should the token involve a transaction tax, User A may find themselves down initially until the token gains in value. The blind nature of these bribes adds a layer of strategy and unpredictability to the transaction process. Since you can't see others' bribes and they can't see yours, your experience and savvy become your greatest assets. This explains how Banana Gun consistently outperforms in the race to Block 0 despite having a smaller community. The amalgamation of a fast custom RPC, bundled transactions, and the art of blind bribing gives Banana Gun a distinctive, competitive edge, making it a powerhouse in the realm of token sniping. This unique trifecta streamlines the trading process and creates an environment where skill, strategy, and speed converge, setting Banana Gun apart from its competitors. ### Max Spend Banana Gun has made crucial updates to tackle one of its initial flaws: the absence of user control over sniping limits. In its early stages, the bot automatically buys whatever amount the user set. However, it left some traders susceptible to sandwich attacks. Early snipers could outmaneuver others by over bribing, essentially "trapping" latecomers in disadvantageous positions: a sandwich. To solve this, Banana Gun added slippage controls and limit orders into its transaction bundles. Now, users can define a 'MAX SPEND' limit in ETH, which caps both the tokens and gas they're willing to expend. This is particularly beneficial when dealing with tokens that have a set maximum transaction amount, meaning the token contract code limits the maximum amount which can be purchased in a single transaction. If a user caps their spend at, say, '0.25 ETH,' the bot will keep the total expenditure—including gas—under this limit. If the maximum allowed transaction is reached, any leftover ETH is returned to the user. An essential new feature, added based on user feedback, ensures that if the transaction can't meet the maximum allowable purchase, it will automatically be reversed. This protective measure is vital for preventing scenarios where a user gets a minuscule amount of tokens but pays a hefty price due to prior high bribes by others. This update adds a layer of risk mitigation, making the sniping game more strategic. These enhancements level the playing field, allowing Banana Gun users to navigate both cutthroat and cooperative trading scenarios with more confidence. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/50a6e008a369.jpg) ## Trading Revenue Traders use the product, but you might still wonder if developing a trading infrastructure like Banana Gun is worth anyone's time. Ultimately, Banana Gun generates 10-25+ ETH per day in trading fees. This is with the absence of token revenues (as of September 15th), which for Unibot adds additional trading fees to their volumes. ![Volume and Fees](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/dd6186e17a32.jpg) ## Competitive Landscape There are a few other bots that compete in the sniper space, including Maestro, and Unibot, which are the largest snipers. Maestro has had the largest user base overall. When looking at bot usage by day, Banana Gun recently flipped Maestro for a few days. ![Source](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/46f6794db72a.png) ### Market Structure Currently, the total bot user base stands at over 100k, and the number of daily active users since August has consistently exceeded 4,000. Several leading products accounted for more than 90 percent of the users—specifically Maestro, Banana Gun, and Unibot. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/d9e72eb39377.jpg) ### Revenue and Fee Structure As of September 15th, 2023, Banana Gun reported a transaction fee income of 756 ETH, over $1.2 million. Banana Gun adopts a low-fee model, charging only 0.5% on gross buys and sells, appealing to its smaller but more sophisticated user base. It's essential to understand the fee structure to see why Banana Gun's average daily fee income is lower despite its transaction speed and strategy edge. In contrast, Maestro charges 1% on gross buys and sells and even offers a premium membership at $200 monthly for additional features. Unibot, another competitor, has a different model altogether—its revenue comes from tax volume as part of their fee structure. The term "gross" is crucial here. If you make a 10 ETH trade and break even (Buy 10 ETH/Sell 10 ETH), you're still liable for fees based on the gross trade amount. With Maestro, you'd pay 0.1 ETH when you buy and another 0.1 ETH when you sell, totaling 0.2 ETH. In the case of Banana Gun, you'd pay 0.005 ETH each for buying and selling, summing up to just 0.01 ETH. This stark difference in fee structures partly explains Banana Gun's lower daily transaction fee income but also represents a competitive advantage for users who are sensitive to costs. By breaking down the fee differences, one can see why Banana Gun, despite having fewer daily active users, provides an attractive alternative for experienced traders seeking to minimize costs while maximizing strategy. ![](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/fcc0634a5d7e.jpg) ### Looking forward: Intent Based Swaps At Shoal, we forecast Telegram bots tools trending towards "intent-based trading," essentially acting as automated executors for a user's specific trading desires—be it swap x, do y, or z. Intents are signatures that execute transactions based on defined criteria rather than a single transaction (TXN) or path to the same result. By using intents, users get more flexibility on the outcomes of their transactions. If a transaction says *"do A then B, pay exactly C to get X back"*, an intent says *"I want X and I'm willing to pay up to C"*. - [Paradigm](https://www.paradigm.xyz/2023/06/intents#what-are-intents) Since BananaGun doesn't route swaps to a third party for execution, it typically won't be considered intent-based swaps. However, we may see tools like Banana Gun auction or fulfill swap orders on behalf of the users or use the request for quote (RFQ) model, which allows users to submit an order for fulfillment off-chain. Banana Gun currently facilitates interaction with blockbuilders, allowing transactions to be processed faster, achieving launch snipes. Down the line, snipers might move to off-chain solutions to fulfill swaps for early snipes or general swaps. In theory, a user could sign a transaction confirming they would like to spend X, and Banana Gun processes the transaction on behalf of the user or send it to a sophisticated actor for an additional fee. ![Intent-Based Architectures and Their Risks](https://shoal.xyz/research/writing/banana-gun-telegram-sniper-bot/img/5ef2821e66dc.png) ## Risks Like most protocols, Banana Gun is not without risks. Risks are usually uniform among defi protocols, including economic exploits or smart contract risk. Economic exploits are when the monetary system within the protocol mechanics are exploited, whereas smart contract exploits can be found with unaudited code. Both risks potentially exist in sniper bots. ### Security Risks Security risks extend beyond smart contract vulnerabilities when it comes to Banana Gun. The bot has access to users' private keys, which means that the bot project team technically has control over the users' funds. To mitigate this risk, most traders only keep sufficient funds in the Telegram wallet to execute trades, transferring the rest to a more secure wallet. There's always the risk that a mishap could expose the private key data. However, it's worth mentioning that both Banana Gun and Maestro delete your private key within the telegram UI as soon as it is provided by the user or generated within the app. In the case of Banana Gun, if you forget or misplace your private key, the platform can't retrieve it for you. The keys are stored on a separate encrypted server, accessible only to the bot, and undergo multiple layers of security, including marshaling, hashing, and conversion. Marshaling packages data for secure storage, hashing converts this data into a one-way, non-reversible string, and conversion further scrambles the data into an unreadable format, collectively ensuring the highest level of private key protection. ### Bribe Fees Being the fastest comes with a cost. Like a cheetah that can run extremely fast, the downside is the time they need to rest. With Banana Gun, users can end up over bribing for tokens based on pure hype and speculation, eating into profits. If “sniper A” bribes 0.1 ETH but a competitor, “sniper B” bribes 0.2 ETH, “sniper A” can buy at a higher market cap than the other sniper. In some cases, irrational bribes are added, leading to losses for many parties involved. Bribes are not refundable and are fully sent to the block builder. ## Conclusion Banana Gun stands out as one of the fastest, cheapest, and most robust sniper bots, primarily focusing on execution timing. By allowing snipers to win Block 0 wars, many trader successes can be attributed to banana guns efficiently and transaction bundling architecture. Banana Guns' consistent growth at the depth of the bear market is a testament to the utility and demand for the product. Although sniping is mildly complex, Banana Gun's user base remains strong, with over 700 users per day in just a few months while taking in over 10 ETH per day in recent weeks. The token sniper user base is relentless and draws no loyalties to branding, so the Banana Gun team must continue to iterate and ensure they have a competitive product. ## Sources - [Banana Gun Bot 🍌🔫🤖](https://dune.com/whale_hunter/banana-gun-bot) - [Maestro Sniper Bot 🤖](https://dune.com/whale_hunter/maestro-sniper-bot) - [Unibot Revenue 🦄🤖📊](https://dune.com/whale_hunter/unibot-revenue) - [https://dune.com/whale_hunter/dex-trading-bot-wars](https://dune.com/whale_hunter/dex-trading-bot-wars) - [Banana Gun](https://docs.bananagun.io/) - [https://docs.maestrobots.com/god-mode/maestro-block-0-dominance](https://docs.maestrobots.com/god-mode/maestro-block-0-dominance) - [https://twitter.com/UniswapVillain/status/1692979624181928138?s=20](https://twitter.com/UniswapVillain/status/1692979624181928138?s=20) ***Investment Disclosure.** Disclosure: Members of Shoal Research hold material positions in the assets discussed in this article. The content presented is for informational purposes only and should not be construed as financial or investment advice. Please perform your own due diligence before making any investment decisions.* --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # AMM LP-Enabled Perps, Options, and Volatility Trading Products > Protocols that use AMMs (CFAMM/CLAMM) liquidity to power new trading products - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-09-05 - Canonical: https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/ - Keywords: crypto, DeFi, market making ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/b38b695a6997.jpg) *Special thanks to [Pablo](https://twitter.com/0xPBL), [Matthieu](https://twitter.com/MLGavaudan), [Jesper](https://twitter.com/cryptojesperk), [Brandon](https://twitter.com/brandonly1000), and [Terence](https://twitter.com/itos_fi) for feedback and input on this new DeFi mechanism.* ## Intro For some, an automated market maker (AMM), a type of Decentralized Exchange (DEX), is the only way traders can exchange certain assets of interest. Centralized exchanges often exclude these assets due to factors like low liquidity and dependence on traditional market makers. Whether it be Uniswap, Curve, Balancer, or even aggregators like MetaMask and 1inch, AMMs have facilitated trillions of dollars of value since inception just a few years ago. DEX's permissionless design makes them an ideal platform to trade low liquidity or long tail assets (assets not included in top trading volumes) since anyone can create a market for new assets. Unlike a traditional CEX, which has to integrate assets manually, AMMs allow seamless deployment and trading of any ERC-20 token as long as someone provides liquidity. This is because AMMs allow anyone to deposit assets and become a market maker, as opposed to needing to be an institutional entity like in traditional finance (TradFi). Market makers add liquidity through buy and sell orders on exchanges to ensure that users can execute trades even when no other users are present. They earn money by capitalizing on the spread, which is the difference between the buying and selling prices. However, most spot* AMMs are extremely vanilla and typically only support buy and sell orders. Other spot AMMs and aggregators offer advanced features like limit orders and deep liquidity (enough liquidity for large entities to trade). However, they still cannot convert their liquidity into other trading primitives. DeFi primitives are the simplest building blocks. > *“Spot markets are also referred to as “physical markets” or “[cash markets](https://www.investopedia.com/terms/c/cashmarket.asp)” because trades are swapped for the asset effectively immediately.” - [Investopedia](https://www.investopedia.com/terms/s/spotmarket.asp)* It is often said in the product world that products need a 10x improvement to displace incumbents and experience significant adoption. The introduction of DEXs like Uniswap, solved a unique liquidity issue by allowing users to create a market for any ERC-20 at lightning speed. DEXs like Uniswap and Curve have been battle-tested long enough to be used as primitives for other products. > *DeFi primitives are the essential “building blocks” that can be combined to create DeFi functionalities of a higher order. - [Binocs](https://binocs.co/resources/blog/what-are-defi-primitives/)* Similar to the DEX spot markets, other trading products like Perpetual Futures (Perps) and Options are also hyper-competitive and still dominated by CEXs with regard to trading volume. Although CEXs dominate, there still is a large opportunity for Perps, options, and other trading products to grow exponentially by harnessing the composability of DeFi, the stacking of DeFi “Legos,” or applications that can build upon each other. Most on-chain Perps and derivatives have few assets, use oracles, and are susceptible to liquidity issues. Without sufficient liquidity, derivative exchanges are unable to function and attract more users, which is the so-called chicken-egg problem. Here lies a sizable opportunity for the 10x "Uniswap" moment for on-chain derivatives by enabling leverage, Perps, and option trading products for any asset. **To make this possible, new protocols are using concentrated and constant function AMM liquidity to power new trading products**(leverage, Perps, and options)**.**Simply put, protocols harness AMMs like Uniswap as a liquidity primitive to create new trading products. - **Constant Function AMM**: Liquidity is typically spread across a full range of prices infinitely (Uniswap v2, Balancer). - **Concentrated Liquidity AMM:** Liquidity is concentrated to a price range (Uniswap v3). ![Uniswap v3 Whitepaper](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/b6a6d6d8e84a.png) ## Perps and Options Uniswap Moment The killer use case with AMM-powered trading products is being able to create Perpetual futures (Perps), Hybrid-Options, and other volatility markets for illiquid and newly deployed assets. $PEPE, during its boom, soared to a multi-billion dollar market cap in just a few weeks. During this period of extreme volatility, traders repeated the continuous question: ***“Where can I long $PEPE”*** ![Source: CoinGecko, Pepe by MCAP](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/feb582dc6141.png) Although PEPE's popularity has grown immensely, garnering billions in volume and turning into a household name, there were initially only spot markets to trade the asset. Shortly after a few weeks, some opportunist exchanges enabled Perpetual (Perps) trading and continued to be the only sources even up to now. Even among some of the exchanges that enabled $PEPE trading, many traders believed there were issues with handling liquidations and payouts, a core concern in Perpetual exchange design. With AMM-powered volatility products and derivatives, there is an opportunity for on-chain market makers known as Liquidity Providers (LPs) to market-make options and Perpetuals at token launch, akin to Uniswap. There is plenty of speculative demand for crypto assets, especially regarding leverage. Outside of leverage, these products provide great tools to hedge LP positions on assets. Hedging is opening another trade to lower the initial investment risk deliberately. ## Perpetual Trading Products Many on-chain Perpetual contracts (Perps) rely on oracles, which can be easy to manipulate for long-tail assets. Oracles take off-chain data and make it accessible on-chain for protocols to use, commonly used for price feeds. Ever wonder why only a few assets are supported on Perp Decentralized Exchanges? Most on-chain Perps and options platforms offer just a handful of assets geared towards deep liquidity and utilize an external oracle for the pricing mechanism. Liquidation risk is also a significant issue since managing liquidations depends on accurate oracles and ensuring that trades can be liquidated to meet collateral requirements in a timely manner. In other words, liquidations need to occur seamlessly to ensure that collateral is available to cover trades. With concentrated liquidity AMM (CLAMM) powered trading products, oracle, and liquidation risks are typically eliminated, as the liquidity is borrowed from a predefined LP range. By adopting this approach, the risk is also predefined for the trader and limited to the parameters set by the exchange protocol for closing positions. Many AMM LP-enabled protocols employ a Perpetual mechanism for trade duration, which allows the trade duration to roll over as long as the fees are paid to keep the position open. ## AMM and LP Fees CLAMMs (Concentrated Liquidity Automated Market Makers) and CFAMMs (Constant Function Automated Market Makers) constitute dual-party markets involving Liquidity Providers (LPs) and traders. For traders, the experiences across AMM products are mostly similar. Conversely, many exchanges strive to optimize the liquidity-providing experience since it frequently results in losses. In numerous instances, LPs need additional incentives to become profitable. Many Liquidity Providers add liquidity to AMMs based on the assumption that they will receive fees sufficient to offset impermanent loss (IL), a theoretical loss incurred by LPs when the price of the deposited tokens changes. It is also important to note that all LPs are not benchmarking against a HODL strategy. One of the core improvements in the concentrated AMM liquidity derivatives model is that LPs are now compensated in volatility, not just trading fees. This innovation introduces a new dimension to the rewards of liquidity provision. ![Uniswap: A Good Deal for Liquidity Providers?](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/6964e37e142a.jpg) For some AMM-powered derivatives like infinity pools and Panoptic (Panoptic Option Sellers), LPs can generate fees when their LP is within range, and commission fees when both in and out of range. When the LP token goes out of range, it can be used for the protocol's volatility product, whether it be leverage, margin, or options trading. This architecture allows for enhanced yield for LPs who usually have a subpar experience when providing liquidity. ### AMM LP-Powered trading products - How do they work? **The current protocols offering AMM-powered trading derivatives abide by the simple assumption that providing LP in a CLAMM is akin to short puts.** In other words, the liquidity-providing payoff structure is mathematically similar to selling put contracts. Perpetual and volatility trading protocols are able to structure trading derivatives and strategies around this concept, creating leverage, Perps, Perpetual options, and other structured products. ![Pantopic Uniswap v3 Options payoff](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/12bab4b8e4ac.gif) ### Protocol Landscape Currently, there are a handful of protocols aiming to leverage CFAMM and CLAMM liquidity for trading purposes. Among them, a few trading products exist, including Leverage and Margin trading, Option products, Perpetual futures, and more. As nascent as the concept may be, many builders find opportunities to fill the liquidity and asset gap for major and long-tail assets within trading products. The following table shows the protocols, their liquidity AMM, and the trading product created: ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/c98c094dd0b2.jpg) Let’s look further into the mechanisms and design. ## Perpetual Option Mechanism Design Protocols like Panoptic and Smilee utilize concentrated liquidity LP to power their trading products, specifically Perpetual options and volatility trading, respectively. Among the handful of protocols leveraging existing AMM concentrated liquidity, each presents a slightly different architecture and implementation in how they are crafting trading products. At a high level, protocols draw concentrated liquidity from AMMs like Uniswap v3, or their own AMM and permit traders to borrow these assets. Traders then redeem the underlying LP token for a single asset, simulating a long or short position constrained by the range of the concentrated liquidity. Due to the nature of concentrated liquidity positions, when out of range, they always consist of 100% of one of the two assets in the pair (e.g., USDC/ETH). Since LPs expect 100% of one of the two assets in the pool, traders pay a fee to borrow and redeem the LP pair, receiving one of the assets. Depending on their trading strategy, they can sell the redeemed token, turning it into a directional bet. ### Long ETH example For a Perpetual options example, let's say a trader wants to borrow a USDC/ETH LP token where the price of ETH is $1000. The trader wishes to go long on ETH, so they borrow an out-of-range USDC/ETH LP token below the current price, which would be worth $1000 of USDC. The LP token is valued at $1000 USDC because the current price has moved to the right side of the range, leaving the LPer (options seller) with 100% USDC. The option buyer's strike can be considered as the midpoint of the LP range; we'll use 900 for this example. Since the trader is long, they redeem the LP token worth $1000 USDC and swap it for 1 ETH, also worth $1000. If the price of ETH moves up to $1500, and since ETH is now valued more than what the options buyer purchased it for, they can exercise the option by selling the 1 ETH for $1500. This amount is sufficient to pay back the borrower and yield an additional $500 profit. The options buyer only repays $1000 to the LP since that is the end of the range in which they are providing liquidity. Protocols typically abstract most of the complexity from this experience. Users may expect to deposit collateral to cover position funding, select position duration (if included), strike price, and trade direction. ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/b2af478f6fcd.jpg) Long ETH trade cont.. If the trade doesn't go as planned and ETH goes down to $800, which is out of the LP range in the opposite direction, they will now owe 1 ETH instead of USDC. Since the borrower still owes 1 ETH to the lender, they need to find a way to obtain 1 ETH to repay the loan. If the value of 1 ETH is $800, the borrower needs to use $800 worth of USDC to purchase 1 ETH to settle the debt. The DEX manages the underlying assets for protocols like panoptic to ensure LPs get paid. Instead of paying a premium to purchase the option upfront, Panoptic requires users to have starting collateral in their wallet to cover a streaming fee similar to a funding rate. Collateral is needed to guarantee that the fee can be paid. The fee is based on realized volatility in the underlying Uniswap pool and liquidity utilization to determine how much the option buyer should pay the seller (LP). Traders positions will close when they stop paying the funding fee or it exceeds their collateral. In both examples, the option seller will take constant streamed fees for the position to remain open. This is a general overview pertinent to panoptic as each protocol has different methods for managing liquidity, offering leverage, calculating collateral, premium, and funding fees. From a birds eye view, trades are two-sided, where LPs deposit their LP token into the said protocol and earn volatility fees, where traders can open positions. LPs are incentivized to provide liquidity because they get bonus yield, which is more than they would've gotten otherwise. One of the core issues with LPs in AMM are they are not paid high enough in fees to compensate for risk. Lastly, profitable traders can exercise their position in profit or continue to pay the LPs a funding rate to keep the trade open perpetually. ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/8372bc3f4f75.jpg) ### Perpetual Future Mechanism Design For Perpetual platforms like limitless or InfinityPools, the mechanism is similar to Perpetual-options. However, users can deposit collateral, which will be combined with borrowed LP. Depending on the distance from the spot price determines the required collateral and leverage. Similar to the Perpetual options products, if a trader borrows an LP token below the range they can sell for one of the underlying tokens, creating a directional leveraged bet. The design mechanism is very similar to the prior example, the major contrast is the users deposit collateral, which is used to cover the max loss of a trade moving in the opposite direction. Both limitless and InfinityPools boast potential hundreds to thousands of X-leverage again determined by the distance from the range to the current price. If traders lose on a trade instead of being liquidated, the protocol closes their position and pays the collateral back to the LP to make the Perp sellers LP position whole. ## Market Opportunity - Crypto Trading Derivatives ### TradFi Market Size The U.S. equity markets dominate globally, accounting for over 42.5% of the $108.6 trillion global equity market cap in 2023, translating to a massive $44 trillion, as [per Sifma Asset Management.](https://www.sifma.org/resources/research/research-quarterly-equities/) ### TradFi Derivatives Landscape The derivatives market is estimated to exceed $1 quadrillion in notional value at its upper end, though some argue this valuation might be inflated as per [Investopedia](https://www.investopedia.com/ask/answers/052715/how-big-derivatives-market.asp). This astronomical figure, on the higher side, incorporates the notional value of all derivative contracts. A significant disparity exists between the notional value and the actual netted value of derivatives, with the numbers being $600 trillion and $12.4 trillion, respectively, as of 2021. Derivative trading in traditional finance is magnitudes larger than spot trading. This is the same in crypto, but the majority of volume is on CEXs. Bitmex, another CEX, changed the crypto trading landscape in 2016 when they [launched their Perpetual (Perp) trading instrument](https://blog.bitmex.com/announcing-the-launch-of-the-perpetual-xbtusd-leveraged-swap/), the Perpetual XBTUSD Leveraged Swap. Their new product allowed users to trade Bitcoin (XBTUSD) with up to 100x leverage. The contract doesn’t expire; longs pay shorts, and vice versa. As the largest traded instrument in crypto, this product expanded from just centralized exchanges and exists in various decentralized versions: DYDX, GMX, Synthetix, and others. Perp protocols facilitate hundreds of millions in trading volume per day and are the primary derivative trading product in crypto today since they offer high leverage. This is a vast shift from traditional finance, where options dominate the derivatives landscape. ### Crypto Spot Vs Perps In the first quarter of 2023, the crypto market witnessed a significant dominance of derivatives, accounting for 74.8% of the total trading volume of $2.95 trillion. Centralized crypto exchanges (CEX) and decentralized exchanges (DEX) spot trading trailed behind with 22.8% and 2.4% market shares, respectively. Notably, centralized crypto derivative exchanges like Binance, Upbit, and OKX led the market. While derivatives volume saw a remarkable quarter-on-quarter growth of 34.1%, spot CEX and DEX recorded growth rates of 16.9% and 33.4%, respectively, per [Coingecko 2023 Crypto Derivatives report.](https://www.coingecko.com/research/publications/crypto-derivatives-market) ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/9da520b548f7.png) As of July/2023 PREP, 74% of all crypto trading volume in July was via leverage. (Figure below) ![](https://shoal.xyz/research/writing/amm-lp-enabled-perps-options-and/img/83bb7cddc9ea.jpg) Innovative volatility trading platforms like Panoptic, Infinity Pools, Smilee, and others push the needle by providing oracle-free, liquidation-free, and even, in some cases, offer significant leverage. Powered by concentrated liquidity, AMM LP trading products remove some prominent weaknesses like managing oracles and liquidations. ## Risks As exciting as these products may be, risks still come into play. The most notable is smart contract risk. Since all the AMM-LP powered trading products control the LP token or require deposits, there's possible smart contract risk if there is an exploit or bug. ### Credit liquidity Risk Additionally, the economic design mechanisms are not without concerns. The Gammaswap team has interrogated the feasibility of developing on Uniswap v3 and CLAMMs due to what they define as "credit liquidity risk." This risk pertains to the possibility of Liquidity Providers (LPs) being unable to pay out long positions or vice versa, often due to over-leverage in the form of liquidation issues. Since concentrated liquidity, Automated Market Makers (AMMs) like Uniswap have areas or "ticks" with low liquidity, prices moving out of range could cause excessive slippage, even for stable pairs. Gammaswap is opting to build on the constant function model, viewing it as a more robust liquidity primitive. With Uniswap v3, there may not be enough liquidity to fulfill the gains made by LPs. Unlike traditional finance, where the Federal Reserve can step in to inject liquidity, there is no analogous entity in the DeFi space. Furthermore, the absence of oracles, which are traditionally used for liquidations, adds to the complexity of this issue. Panoptic addresses the credit liquidity risk issue by requiring pool creators to deposit a small amount of both tokens at full range, which panoptic traders cannot remove. The initial deposit ensures there's some liquidity across all prices. ### Complexity and User Adoption Perpetual Futures (Perps) have proven to be much simpler for crypto investors to understand. They operate through two mechanics: long and short positions, which traders can open with a simple click of a button. In contrast, with Options and potentially Perpetual Options, the additional complexity introduced by factors such as Greeks, strike prices, and other traditional option knowledge may hinder user adoption. This is particularly likely among retail investors, who are often the first to adopt new trading instruments. Moreover, introducing volatility trading adds even more complexity to the user experience. Since the crypto space already faces challenges with user adoption, some of these robust but complex products could encounter difficulties gaining traction due to their financial intricacy. ## Conclusion Perpetuals and Options have found a niche within the crypto space, but it's only a matter of time before they scale into the fully-fledged products that traders and LPs are seeking. Over the next few months, many of the protocols mentioned will be launching new trading instrument betas, as well as live products. The next level of improvement in on-chain derivatives, including Perpetuals and options, will be the introduction of the ability to go long (or short) on any asset with leverage. The "where can I long PEPE" question will be answered in the form of leveraged liquid trading avenues for mid to long-tail assets. AMM-powered trading products are paving the way for a new paradigm of trading and could potentially enable new DeFi primitives that power other protocols. This includes options, Perpetual contracts, volatility trading, and other leverage-based products. The new wave of trading will offer an enhanced experience that could even rival the current incumbents in the market. ## Sources - [Panoptic CLMMs option payoffs](https://twitter.com/Panoptic_xyz/status/1646917853755604993?s=20) - [Uniswap: A Good Deal for Liquidity Providers?](https://pintail.medium.com/uniswap-a-good-deal-for-liquidity-providers-104c0b6816f2) - [Crypto Derivatives Market Size 2023 | CoinGecko](https://www.coingecko.com/research/publications/crypto-derivatives-market) - [Announcing the Launch of the Perpetual XBTUSD Leveraged Swap | BitMEX Blog](https://blog.bitmex.com/announcing-the-launch-of-the-perpetual-xbtusd-leveraged-swap/) - [Research Quarterly: Equities - SIFMA](https://www.sifma.org/resources/research/research-quarterly-equities/) - [What are DEFI Primitives & Where DEFI Primitives are used in Financial services | Binocs](https://binocs.co/resources/blog/what-are-defi-primitives/) - [Spot Market: Definition, How They Work, and Example](https://www.investopedia.com/terms/s/spotmarket.asp) - [Cash Market: Definition Vs. Futures, How It Works, and Example](https://www.investopedia.com/terms/c/cashmarket.asp) - [Panoptic overview](https://panoptic.xyz/docs/panoptic-protocol/overview) - [InfinityPools](https://docs.infinitypools.finance/) - [Gamma transforms: How to hedge squeeth using Uni V3 | by Guillaume Lambert](https://lambert-guillaume.medium.com/gamma-transforms-how-to-hedge-squeeth-using-uni-v3-da785cb8b378) - [Smilee — The first primitive for Decentralized Volatility Products (DVPs) | by N B | Smilee Finance | Medium](https://medium.com/smilee-finance/smilee-the-first-primitive-for-decentralized-volatility-products-dvps-9a7584b13d42) - [https://predy.gitbook.io/predy-v5/](https://predy.gitbook.io/predy-v5/) - [https://limitless.gitbook.io/limitless/intro/participants/liquidity-providers](https://limitless.gitbook.io/limitless/intro/participants/liquidity-providers) - [Haptic Finance: A primer](https://hapticfinance.medium.com/haptic-finance-a-primer-af334a03ac4d) - [https://docs.itos.fi/](https://docs.itos.fi/) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are the authors own, not the views of their employer. --- # Ambient Finance: Enhancing AMM efficiency > Ambient is an Decentralized Exchange - AMM focused on enhancing LP and trader capital efficiency. - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-08-14 - Canonical: https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/ - Keywords: DeFi, market making, yield, Ethereum, Research ![](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/fddda7b4b4e3.jpg) > ***Shoal Research Contributors**:* ## Intro Automated market makers (AMMs) are the foundation of decentralized finance (DeFi), revolutionizing trading by offering users 24/7 access to asset trading, market creation, and yield generation without intermediaries. Since their inception, AMMs have facilitated trading volumes exceeding trillions of dollars. Although AMMs have managed to bootstrap enough liquidity to facilitate the aforementioned trading volume, there has always been a looming threat to the sustainability of AMMs over the long term and, thus, decentralized finance as a whole. Despite the idea that LPs should profit from participating in DeFi, the benefits (i.e., trading fees) are outweighed by the costs (i.e., impermanent loss) for some LPs. Impermanent loss (IL) is the lost opportunity to provide liquidity as opposed to holding assets outright instead of providing liquidity. IL occurs when the prices of the pooled tokens (LP tokens deposited) change. ![Uniswap: A Good Deal for Liquidity Providers?](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/5106e96aee5b.jpg) Fortunately, the world of DeFi is characterized by its fast pace, constant evolution, and protocols that aim to confront the global accessibility of financial products. In this report, we will explore the fundamental AMM designs of Ambient - the original singleton AMM built directly on Ethereum's network. We aim to shed light on the most captivating features we have encountered and how they ultimately support the sustainability and broader adoption of DeFi. So, let's dive in and begin our exploration without further ado. ## Defying Layer-1 Limitations Let's face it - AMMs and DEXs exclusively built on Ethereum face significant headwinds due to relatively high gas fees on the layer-1 network. This drives the majority of 'modern' DeFi protocols to launch with support for various layer-2 networks such as Arbitrum. Ambient has defied this trend and opted to initially support transactions on the Ethereum network *only*. ![](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/4c7fddb34193.png) Despite Ethereum's network congestion obstacles, Ambient has achieved notable success across various metrics, especially since the start of summer 2023. Between early June and late July, Ambient's TVL increased approximately thirteenfold—volume on Ambient paints a similar story of success. On June 13th, Ambient hosted roughly $36,000 in volume. By July 14th, Ambient reached its highest daily volume of $1,410,000. ![](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/4d947158d41a.png) While Ambient offers traders a handful of notable features, including the ability to place limit orders and pay gas fees in any ERC-20 token, if you're wondering what propelled the success of Ambient – it is largely attributable to its singleton AMM model. Let's look at Ambient's structure and how it offers incremental innovation for LPs and traders alike. ### The Original Singleton AMM Ambient, previously known as CrocSwap, is a decentralized transaction protocol that enables a unique kind of automated market maker. Ambient is a singleton AMM, meaning it operates within a single smart contract, making swaps more efficient. The use of a single, smart contract results in one enormous benefit to traders and, ultimately, LPs - a significant reduction in gas fees involved with multi-hop swaps. For context, when using an AMM, trades are executed using one of two swap types: a single-hop swap and a multi-hop swap. A single hop swap is a simple trade route that involves a direct swap of token A to token B through a single pool. On the other hand, a multi-hop swap requires a trade to be routed across multiple pools. Multi-hop swaps are only executed in the event that a single-hop swap cannot be used to fill the order, as single-hop swaps incur far fewer gas fees. Most AMMs are structured in a manner where *every* pool has its *own* smart contract, which makes the execution of multi-hop swaps across multiple pools quite expensive in terms of gas fees. ![](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/fce710e12639.jpg) Since Ambient is a singleton AMM, *every* pool operates within a single smart contract, which allows it to execute multi-hop swaps far more efficiently than traditional AMMs. Ambient does not transfer any intermediate tokens involved in multi-hop swaps, which significantly lowers gas used in the process of executing trades compared to other AMMs. In theory, as gas fees required to execute a trade lowers for traders, the sheer number of trades across the AMM should increase. This results in more trading fees that are distributed to LPs. Lower gas fees are especially attractive for sophisticated arbitrageurs, as prices are maintained through arbitrage trading activity. Ultimately, traders enjoy lower gas fees and efficiently priced markets, and LPs benefit from trading fees due to an overall increase in trading activity. The singleton model has now been adopted by the likes of Uniswap, which recently introduced a similar model in the [Uniswap v4 papers](https://blog.uniswap.org/uniswap-v4). Further confirmation Ambient is on the right track pushing innovative design mechanisms to the AMM space. ## Ambient’s Liquidity Pools Ambient is at the forefront of optimizing the experience for liquidity providers (LPs). Since the start of DeFi and even now, impermanent loss is a constant burden for LPs. In order to eliminate the headaches LPs faced in the past, Ambient supports two types of LP positions; Ambient liquidity and concentrated liquidity. By leveraging two types of LP product offerings, Ambient upgrades liquidity provision for seasoned LPs while also onboarding a new cohort of DeFi participants through an optimal LP experience. Users who want to customize how and when their capital is used can choose concentrated liquidity. The LP specifies the price range that determines when their liquidity is provided to liquidity pools, meaning the LP only accrues fees generated from trading pairs when the underlying assets' prices are within the specified price range. When the underlying assets' prices are outside the range, the liquidity is not active within the pool, and the LP stops receiving a portion of trading fees. **Concentrated Liquidity Shape** ![Source](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/801f7e4eea53.png) Concentrated liquidity caters to more sophisticated LPs as it requires more DeFi knowledge and experience and is generally the most capital-efficient LP position type supported by Ambient. Ambient liquidity is the other type of LP position supported by Ambient, which caters to all DeFi users as it does not involve specifying a price range, and is better for illiquid assets. Ambient mode uses the constant product, where liquidity is active across all prices of the underlying assets in the liquidity pool. **Constant Product Liquidity Shape** ![source](https://shoal.xyz/research/writing/ambient-finance-enhancing-amm-efficiency/img/fb1ec61cae45.png) Regardless of which liquidity position type an Ambient LP decides to use, all Ambient LPs benefit from the protocol's use of smart contracts known as 'hooks.' Hooks allow Ambient to continually modify existing liquidity pool parameters, including liquidity fees. Hooks are especially interesting to LPs because they ensure they can maximize capital efficiency and automatically receive the optimal fee tier. For Ambient, liquidity fees are adjusted dynamically in response to market activity. Concentrated and constant product liquidity are not without their flaws. Traders could suffer significant slippage (price impact) if asset prices move out of supported concentrated liquidity ranges. On the flip side, constant product liquidity is spread thin across all prices which is good for traders, however LPs don’t benefit from enhanced capital efficiency by selecting a specific price range. Ambient interrogates these two design mechanisms and combines both pools under the singleton contract. Combining both liquidity strategies allows LPs to maintain capital efficiency while traders maintain cheaper swaps, and deeper liquidity. In addition, the combined model eliminates liquidity fragmentation across pools. ### Limit Orders Ambient offers limit orders on supported assets for traders, known as Knockout Positions, which are possible using directional concentrated liquidity. Directional, meaning when liquidity is added to a specific range, it is locked once the price crosses the range. Most AMMs are bi-directional, which swap back and forth between assets whenever the LP is within range. With directional Knockout Positions, the position gets removed once the price crosses the concentrated liquidity range the user provides. The action of removing liquidity once crossed serves as a limit order. The range for the knockout LP is tight to ensure it is filled. Keep in mind that although the range's width is tight, the liquidity is only "knocked out" when it is crossed fully. Gasless Transactions Ambient employs account abstraction for managing gasless transactions. Account abstraction enables a third party to pay the gas fees. In this case, Ambient uses signatures to enable swaps where users only pay in the swap currency. Tips can be given to the third party as payment for sending ETH to facilitate the gasless swap on the user's behalf. Dynamic Fees A fee is tied directly to the pool across other major pools like USDC/ETH on Uniswap. Uniswap employs three pricing tiers, 0.05%, 0.30%, and 1%, on Uniswap v3, which the LP selects typically based on implied volatility (expected price changes). The fees compensate LPs for taking IL (impermanent loss). On Ambient, fees are dynamically adjusted based on market volatility (market changes). Dynamic fees enable greater capital efficiency for LP, which lower active LP management and removal to meet the desired fee tiers during market lulls or extreme volatility. ### Final Thoughts While Ambient was designed to solve major problems facing LPs, the singleton AMM has struck a seemingly perfect balance between catering to LPs and enhancing the trader experience. Traders can participate in DeFi directly on Ethereum's base network with minimized gas fees and access to efficiently priced markets. LPs reap the benefits of trading fees among access to the groundbreaking functionality that Ambient offers for its liquidity pools. All in all, Ambient is undoubtedly working towards making the future of DeFi brighter. ### Sources - [Uniswap v3: The Universal AMM](https://www.paradigm.xyz/2021/06/uniswap-v3-the-universal-amm) - [Ambient Docs](https://docs.ambient.finance/) - [Ambient Finance](https://ambient.finance/) - [https://twitter.com/0xdoug/status/1670480007909523456?s=20](https://twitter.com/0xdoug/status/1670480007909523456?s=20) - [https://twitter.com/ambient_finance/status/1671493581994070016?s=20](https://twitter.com/ambient_finance/status/1671493581994070016?s=20) - [https://twitter.com/ambient_finance/status/1669677843092242433?s=20](https://twitter.com/ambient_finance/status/1669677843092242433?s=20) - [Discrimination of Toxic Flow in Uniswap V3: Part 1 | by CrocSwap | Medium](https://crocswap.medium.com/discrimination-of-toxic-flow-in-uniswap-v3-part-1-fb5b6e01398b) - [Discrimination of Toxic Flow in Uniswap V3: Part 2 | by CrocSwap | Medium](https://crocswap.medium.com/discrimination-of-toxic-flow-in-uniswap-v3-part-2-21d84aaa33f5) - [Discrimination of Toxic Flow in Uniswap V3: Part 3 | by CrocSwap | Medium](https://crocswap.medium.com/discrimination-of-toxic-flow-in-uniswap-v3-part-3-4afb386311c0) - [Discrimination of Toxic Flow in Uniswap V3: Part 4 | by CrocSwap | Medium](https://crocswap.medium.com/discrimination-of-toxic-flow-in-uniswap-v3-part-4-c09656ec016e) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- # Beat the Case: The Significance of the XRP Case Ruling > Broader implications of the partial judgement ruling in SEC vs. Ripple case. - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-07-24 - Canonical: https://shoal.xyz/research/writing/beat-the-case-the-significance-of/ - Keywords: crypto, Ethereum, Bitcoin, Research ![](https://shoal.xyz/research/writing/beat-the-case-the-significance-of/img/55d938cc7b8b.jpg) The XRP case is a groundbreaking ruling for Ripple and crypto as a whole. In 2020, the [SEC sued Ripple](https://www.sec.gov/news/press-release/2020-338) over the launch and sale of the digital asset XRP. On the other end of the spectrum, Ripple and its steadfast community maintained that it was not a security. Crypto veterans recall that XRP was one of the largest traded assets during the bull run of 2017 and continued to attract a loyal and somewhat cult-like community. ![](https://shoal.xyz/research/writing/beat-the-case-the-significance-of/img/64ee5ee11ba7.jpg) Fast-forward to 2023, XRP, in a groundbreaking victory, [was deemed not a security](https://cointelegraph.com/news/ripple-wins-case-against-sec-as-judge-rules-xrp-is-not-a-security). The ruling is a monumental shift for the digital asset and the crypto world at large, as it could set a precedent in case law. Furthermore, it signals a progressive shift in societal sentiment regarding the United States' perception of crypto. > *Page 15: "XRP, as a digital token, is not in and of itself a “contract, transaction[,] or scheme” that embodies the Howey requirements of an investment contract." - [(SEC v. RIPPLE LABS, 2023)](https://www.nysd.uscourts.gov/sites/default/files/2023-07/SEC%20vs%20Ripple%207-13-23.pdf)**Page 25 : "Ripple’s Programmatic Sales of XRP [on digital asset exchanges] did not constitute the offer and sale of investment contracts." - [(SEC v. RIPPLE LABS, 2023)](https://www.nysd.uscourts.gov/sites/default/files/2023-07/SEC%20vs%20Ripple%207-13-23.pdf)* Although the crypto space sees this as a huge win, the SEC did decide in a partial judgment that selling XRP to institutions was in fact a security contract. **The results of the case are important for a few reasons:** ### Signal to Project Teams leaving the US United States incorporation is typically a point of contention for well-capitalized crypto project teams, where many teams decided to avoid the US in some capacity. Often incorporating semi-complex legal structures involving offshore entities or strict terms of service (TOS). These are not showy super coders or hedge funds holding funds offshore but teams aiming to limit their liability in a country without clear regulatory clarity towards crypto. Due to intense regulatory scrutiny, the United States has become a volatile place to launch digital assets. The SEC has picked off and sued multiple smaller crypto companies in the last year alone. The ruling in the SEC vs. Ripple case signals to project teams that case law could potentially side with them in the event of a lawsuit. Although there are few projects as well capitalized as Ripple, it still sends a soft signal across the crypto space that they do have grounds to participate and build in the US. There still is a long way to go on this front, but a larger sentiment shift could be sooner than expected among project teams. ### Increased Regulatory Comfort around ETH ETH has been in the regulatory crosshairs recently since the SEC mentioned BTC is the only asset that is not a security. The case ruling could shed some light on what is a security and what is not, including Ethereum, which had an ICO bootstrapping event at its inception. SEC Chairman Gary Gensler postures around the "come register" narrative, which offers little feasibility for project teams. They also preach to politicians and other regulators, mainly those not native to crypto, which have adopted and propagated the "come register" notion, painting an anti-compliance narrative to the general public. Paradigm delves deeply into this in their [three-part research papers](https://policy.paradigm.xyz/writing/secs-path-to-registration-part-i). ### XRP is not a security It goes without saying that XRP, not being a security, is great for their ecosystem. Within the same day of the court filing multiple crypto exchanges that previously suspended trading, including Coinbase, reenabled trading. *Nature is healing* ![](https://shoal.xyz/research/writing/beat-the-case-the-significance-of/img/b14e80e7c990.png) ## It is not over yet Amidst all the excitement, virtual hugs, and bullish tweets, we are still not quite in the clear. The case resulted in a partial judgment, meaning an appeal could lead to a reversal. In fact, the [SEC is already signalling](https://www.bloomberg.com/news/articles/2023-07-21/sec-signals-appeal-to-crypto-ripple-ruling-in-terra-response?in_source=embedded-checkout-banner) that they will appeal. > “While persuasive, it's not binding precedent on other courts and will likely be appealed and could be reversed” - [Crypto Lawyer, Stephen Palley](https://twitter.com/stephendpalley/status/1679562623564632069?s=46&t=txFAbiSPTdLLDlAYj9X_AA) In addition, Ripple is a highly capitalized firm. In other cases, project teams have often settled and chosen to wind down to avoid costly and lengthy legal processes. Hopefully, a few more large big wins like Ripple can establish a basis for small projects in the future. ## Conclusion Last week was a great day in the crypto space, as some confidence was restored in the long-term feasibility of crypto sticking around for the long haul. With the case's conclusion, the United States has softly signaled that there is room for digital assets. At the same time, crypto project teams, investors, and users still need to keep a keen eye on the following stages of crypto regulation within the United States. Although countries have separate crypto jurisdictions, the United States plays a huge role in global shaping policy. --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, legal advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- # Maverick: The Dynamic Liquidity Provision AMM > A Decentralized Exchange focused on automatically rebalancing liquidity positions for LPs and providing deep liquidity for traders - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-07-10 - Canonical: https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/ - Keywords: DeFi, market making, liquid staking, yield, zero-knowledge, Ethereum ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/928b24b1f211.jpg) > ***Shoal Research Contributors**:*[Gabe Tramble](https://open.substack.com/users/17294401-gabe-tramble?utm_source=mentions) ## Intro Decentralized Exchanges (DEX) are one of the most transformative innovations in the DeFi space. Uniswap, with its Automated Market Maker (AMM) design, initiated a significant shift by enabling traders to swap assets permissionlessly, even in low-liquidity markets. AMMs create a two-sided market consisting of liquidity providers and traders. While these innovations have been groundbreaking, both traders and liquidity providers (LPs) alike still express disdain regarding fees and flexibility around the platform - **intro Maverick protocol.** Maverick Protocol advances the traditional AMM model by introducing the Dynamic Distribution AMM (DDAMM), which actively adjusts liquidity in response to market prices. The DAMM design improves the AMM experience for both liquidity providers (LPs) and traders by lowering slippage for traders and adding enhanced LP strategies. The protocol also focuses heavily on liquid staking token (LST) trading, eliminating major slippage trading amongst ETH LST pairs. Operating on both Ethereum and zkSync Era, Maverick's design also aims to improve capital efficiency and reduce impermanent losses for both liquidity providers and traders. One of the key features of Maverick is its built-in automatic rebalancing, which eliminates the need for users to spend significantly to move their liquidity position back into range so it continues to earn fees. Currently, on Uniswap V3, users can specify a price range in which their money is at work. When the price moves out of this range, their capital becomes idle, which forces them to spend gas to rebalance their capital to meet their strategy, given changes in market conditions and price. Dynamic rebalancing significantly enhances the user experience by providing superior capital efficiency and lowering the cost to service the LP. *Capital efficiency: “Effective utilization of resources to generate maximum output or returns. Prevention of idle money.”  - [Shoal Research](https://www.shoal.gg/p/stablecoins-backed-by-lsts)* Before we delve deeper into the Maverick Protocol, it's essential to understand how an AMM works. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/2ed1d0668687.jpg) ### Automated Market Makers (AMM) Automated Market Maker (AMM) is a term used in decentralized finance to describe a protocol that facilitates the trading of digital assets without relying on traditional order books. Instead, AMMs use mathematical algorithms to determine the prices of the assets being traded automatically. On a conventional exchange, buyers and sellers place orders in an order book, and the exchange matches these orders to facilitate trades. However, in an AMM-based decentralized exchange, there are liquidity pools. Liquidity pools are collections of funds that users deposit to fulfill trades. Liquidity providers (LPs) get incentives, fees, and rewards for providing liquidity. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/57c7df908dae.png) AMMs enable instant, permissionless trading and are fundamental to the functioning of decentralized exchanges. Unlike traditional exchanges, non-institutional users can take on the role of market makers by adding liquidity in exchange for fees. However, providing liquidity in an AMM can come with risks such as impermanent loss, which occurs when the prices of assets in a pool change compared to when they were deposited. Impermanent loss can also be described as the missed opportunity cost of potential value when providing liquidity versus holding the assets outright. AMM iterations on Uniswap ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/4fb94fa8c11a.jpg) ## Maverick AMM Maverick's Automated Market Maker (AMM) design differs greatly from other AMMs. Maverick is centered around optimizing capital efficiency and providing flexibility for Liquidity Providers (LPs). The protocol segments liquidity into different pills called Bins, which aim to improve capital efficiency. Here's an overview of its design: ### Bins Maverick employs bins," representing a specific price range within the liquidity pool. This segmentation allows Liquidity Providers (LPs) to allocate their assets to specific price ranges, optimizing capital allocation based on market conditions. In other AMM designs, like Uniswap v2, liquidity providers provide liquidity across an infinite price range. With Mavericks bins, LPs can ensure they only provide liquidity at specific prices and/or abide by the liquidity provision rebalancing strategy. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/15ec9145b6a0.png) ### Segmented Liquidity Pools To better understand Mavericks Bin's liquidity design, Imagine you're at a fruit market and want to sell apples. Instead of setting one price for all apples, you create different buckets where each bucket has a price range. For example, one bucket for really cheap apples, one for moderately priced apples, and one for expensive apples in Maverick's AMM; these buckets are called "bins," and they let you specify the price point you want to provide inventory to the market. Depending on the price of the apples, buyers will only pull from the bucket at the current market price. If you want to sell your apples, you have to provide liquidity within the current price range, or wait until the price reaches your bucket. Depending on the LPs strategy they might chose to provide liquidity at certain price ranges below, at, or above the current price. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/6041c5c07ea4.png) Uniswap v2 is akin to allowing people to buy your apples at any price, depending on the overall market price. By using bins, LPs also have a tighter grasp on their capital risk controls, potentially limiting impermanent loss, and maximizing fees. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/8a80e4b8ff98.jpg) ### Boosted Pools With incentivized pools, [custom liquidity shaping](https://medium.com/maverick-protocol/maverick-phase-ii-liquidity-shaping-with-boosted-positions-a922c67dd557) (LP strategies), custom fee tiers, and directional liquidity provision, Maverick creates increased tooling for LPs to participate in the market. In addition, Maverick supports liquidity mining solutions where protocols can permissionlessly incentivize liquidity via "boosted pools." Boosting pools draws more liquidity to the pool as LPs will make more yield from increased reward incentives. Protocols are incentivized to boost their pools to ensure users can seamlessly swap between assets without significant price impact. With deeper liquidity comes a lower price impact. Furthermore, Maverick's modes offer different options for liquidity provision, allowing users to tailor their approach based on their preferences. Maverick further amplifies yield by automatically reinvesting trading fees back into the liquidity provider's position. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/b92610dde263.png) ### Maverick Modes Maverick's Automated Market Maker (AMM) design offers four distinct modes for liquidity providers (LPs) to optimize strategies based on market conditions labeled **Mode Static, Mode Right, Mode Left, and Mode Both**. Each mode presents characteristics that tailor LP strategies for maximum fee generation; let's cover them one by one below: ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/8c070f856999.jpg) **Mode Static** Mode Static is the conventional mode and resembles the functionality of existing AMMs. It does not employ automated liquidity shifting. In this mode, LPs have the liberty to deploy liquidity with three default configurations: - **Exponential:** “Gradual Spread”: most of the liquidity is bunched up close to the current pool price, and the rest is spread out across nearby price range bins, decreasing bit by bit. - **Flat:** “Even Spread”: liquidity is spread out evenly across different price ranges, centered on the current pool price, similar to how Uniswap v2 works. - **Single Bin:** “Single Spot Focus” means all the liquidity is put into one spot, the active price range. The Single Bin is like putting all your eggs in one basket, similar to Uniswap v3. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/c5d71bb45821.gif) **Mode Right** Mode Right operates as a dynamic range order that tracks the price in an upward direction. It is particularly beneficial for LPs looking to capitalize on the positive price action of the base asset. In this mode, liquidity is kept in a bin of the quote asset just to the left of the price as it ascends, poised to capture fees whenever the price falls within the range. Essentially, Mode Right is tailored for scenarios where the LP anticipates an upward price trajectory. **Trading Pair Example: ETH/USDC** - **Base Asset:** Or basis, is the asset to be purchased or sold, ex. $ETH - **Quote asset:** the payment asset for the base asset, ex. $USDC **Mode right in practice:** Imagine you have two assets, A and B. If the price of asset A starts to rise, Mode Right ensures that your liquidity is concentrated just below the current price. This allows you to earn fees when the price dips slightly. It's like riding the wave of an asset's price as it goes up. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/19bdf60ca93e.gif) **Mode Left** Mode Left is essentially the inverse of Mode Right. It continuously shifts liquidity to the right of the current active bin when the base asset is trending downward. This mode is advantageous for LPs who anticipate a decline in the price of the base asset. In Mode Left, an LP aims to maintain a bin of base assets directly to the right of the price as it moves left in the pool, ready to match orders once the price rebounds. **Mode Left in Practice:** If the price of asset A starts to fall, Mode Left ensures that your liquidity is concentrated just above the current price. This allows you to earn fees when the price slightly rises before continuing its downward trend. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/548fafe05529.gif) **Mode Both** Mode Both is the all-around Mode that enables liquidity to adapt to price movements dynamically, be they upward or downward. LPs have the option to allocate liquidity to the currently active price range as well as the ones immediately next to it. As the price sways in any direction, Mode Both smartly repositions the liquidity to keep it centered around the current price. This Mode is somewhat like having an auto-adjusting focus in a camera that keeps the subject sharp regardless of movements. However, it's crucial to be mindful that Mode Both comes with increased susceptibility to impermanent loss, particularly in markets that have a lot of price fluctuations. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/3bf6d0b1340f.gif) ### Incentives Maverick's incentive structure is designed to reward liquidity providers (LPs) based on their market prediction, participation,, and risk tolerance. - **Predicting Price Movements:** Maverick's Mode Left or Mode Right allows LPs to automatically adjust their liquidity to follow the price movement, keeping their capital active and efficient. - **Stable Price Expectations**: Mode Both are ideal for LPs who expect minor price fluctuations, allowing them to keep their liquidity active and collect as many fees as possible. - **Exponential Distributions**: In Mode Static, LPs can place most of their liquidity at the current price, spreading the rest across surrounding price ranges and balancing liquidity concentration and risk. A few more strategies and ways to earn fees and maximize returns from Maverick are: - Limit order strategies - Dollar-Cost Averaging (DCA) strategies - Buy-Sell Ramp - Even Distribution - Stake to earn ## Maverick’s Go-to-Market Approach Maverick has adopted a distinctive approach for its go-to-market strategy. Instead of solely launching on Ethereum, the protocol is a pioneer in the zkSync Era. This multi-platform approach allows Maverick to take advantage of each platform's unique features and benefits, providing a more robust and versatile service to its users. The zkSync Era officially launched in March, and while the ecosystem is still in its early stages, there has been a steady increase in volume. Furthermore, Maverick's DEX volume continues to climb, securing a position among the top 500 DEX platforms. Currently, it stands at number 5 among Ethereum DEXs. In comparison, Uniswap, a prominent player in the space, boasts a volume of over 700 million and ranks number one on the Ethereum chain. Maverick also chose to launch their token on [Binance launchpad](https://www.binance.com/en/support/announcement/introducing-maverick-protocol-mav-on-binance-launchpool-farm-mav-by-staking-bnb-and-tusd-a28d005ed545464cbb9a3661c26e6b38) which has a considerable list of successful projects. By launching on Binance they were able to bootstrap initial token liquidity and holder diversification. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/31bedfd01436.png) ## Examining the Metrics ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/221f6997ac0c.png) Maverick is not only excelling in terms of volume but also fee generation. The platform has consistently set new all-time highs in volume since its launch, with an ATH of $20,000 on June 1st and currently reaching over $13,000. This growth can be attributed to users' ongoing migration to new DEXs, driven by the desire for improved incentives and diversified risk exposure. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/037d38a6ee68.png) Mavericks Total Value Locked (TVL) is also pushing all-time highs on the Ethereum chain, currently at $35 million. In addition, it has marked a TVL of roughly $7 million on zkSync Era. This substantial TVL, mirroring the trading volume, signifies the robust growth and deepening trust in the Maverick protocol. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/faf0c299e544.jpg) Currently, the majority of pools on Maverick are utilized by users who are primarily focused on stablecoins and LSTs, which both typically have lower price deviation. With the inclusion of stablecoins and liquid staking assets, trading volume typically comes from the WETH/wstETH and USDC/UST pools. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/1d642fb89064.png) It is worth noting that users may require some time to familiarize themselves with the AMM (Automated Market Maker) and Maverick's liquidity strategies, which may impact the pace of adoption and utilization. AMM complexity for liquidity provision is not a new issue. Many users voiced concerns about Uniswp v3's design complexity for users. Given general LP complexity, Mavericks volume metrics are impressive. While many Decentralized Exchanges (DEXs) typically employ attractive reward strategies like yield farming or liquidity incentives to draw user traffic and boost trading volume, Maverick emphasizes low-slippage trading. This unique strategy is gradually earning Maverick recognition among other market entrants. From its inception, Maverick has shown a propensity to be favorable towards large-scale investors, often referred to as 'whales.' Analysis of the trade data reveals that the majority of trades are above $100k, placing them at the top of the transaction size spectrum. This is followed by smaller trades and retail activity. On the Ethereum mainnet, a significant portion of Maverick's trading volume, over 75%, is derived from transactions exceeding $10,100, with very few transactions happening below this threshold. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/c1d1aef442e8.png) ### Influence on LSTs LST's protocols are attracting increasing attention, and their narrative is growing stronger daily. The narrative surrounding LST is anticipated to gain momentum in the coming months and extend into the next year, solidifying its position as a potential leader in AMM and CDP-based protocols. While several DEXs are already consuming LST and CDP volumes, Maverick currently captures approximately 24% of the LST volume compared to other top venues. Nevertheless, the path ahead will undoubtedly be challenging as competition intensifies. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/0a7c6fdeefe3.png) ### LST Trading Volume Maverick has quickly established itself as a formidable competitor, currently holding a 26% market share volume, in the last 30, on par with Uniswap. This achievement is particularly impressive considering Maverick's relatively recent launch. The rapid growth and strong metrics exhibited by Maverick within a short time is remarkable. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/5bc4e9daea9b.png) ### Dex Trading Volume Considering the global view of DEX trading volume over the past 30 days, Maverick currently represents only around 2% of the total DEX volume. Notably, a significant portion of this 2% is attributed to the LST volume. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/f9906c638431.png) ### DEX Aggregator Routing One of the most interesting metrics around Maverick is 99% of transaction volume comes from DEX aggregators. DEX aggregators sit on top of AMMs and route customer trades to the most efficient swap destination. Since Maverick is highly capital efficient, large swaps for LSTs and stablecoins often route to Maverick from services like 1inch, Cowswap, Metamask, and others. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/c29b325033d0.png) Maverick's volume origination highlights DeFi compatibility, which refers to decentralized applications (Dapps) as building blocks that can be replicated or built on top of. In the case of Maverick, the underlying architecture speaks for itself, and trade aggregators automatically route transactions to the platform. ![](https://shoal.xyz/research/writing/maverick-the-dynamic-liquidity-provision/img/01ab96d55d4b.png) ## Market Competition Trader Joe's was one of the first DEXs, to utilize liquidity bins. Many market participants often draw comparisons between Trader Joe's and Maverick's design implementations due to the similarities in architecture. Differentiating from Trader Joe, Mavericks provides various modes or strategies for liquidity management based on directional bets. These modes enable the dynamic adjustment of liquidity in response to price fluctuations. **Challenging the AMM King, Uniswap** The primary challenge for most newly launched decentralized exchanges (DEXs) is attracting user traffic and volume from established DEXs like Uniswap and Curve. Many of these new protocols initially succeed in attracting a user base. Still, users often revert to the more prominent players when the new projects fail to deliver on their initial promises or user incentives dry up. Despite the launch of Uniswap v3 and anticipated v4, Maverick stands out due to its ability to provide efficient incentives and liquidity strategies for protocols and users. Its unique features make it attractive for both LPs and traders alike. We are already seeing early signs of success from DEX aggregator order routing. ### Conclusion Maverick Protocol is a novel entrant in the DeFi sector, where most AMM implementations are forks of existing systems, introducing unique liquidity provision strategies that enhance trading efficiency. Despite the dominance of established DEXs, Maverick has shown promising growth due to its increased capital efficiency. Its recent launch on Ethereum and zkSync is a testament to its work-based design with strong fundamentals and growth metrics. As LPs and traders continue to seek better LP solutions and AMMs with high incentives, low fees, and minimal slippage, we believe Maverick could become one of the go-to platforms. ## Sources - [Introducing Maverick: A Protocol for Decentralized Permissionless Trading and Staking of Any Asset](https://medium.com/maverick-protocol/introducing-maverick-a-protocol-for-decentralized-permissionless-trading-and-staking-of-any-asset-40b2a8bb1d54) - [Maverick Official Website](https://www.mav.xyz/) - [Understanding Modes - Maverick Docs](https://docs.mav.xyz/guides/liquidity-providers/understanding-modes#mode-right) - [Liquidity Strategies - Maverick Docs](https://docs.mav.xyz/guides/liquidity-providers/liquidity-strategies) - [The Basics of Liquidity Providers - Maverick Docs](https://docs.mav.xyz/guides/liquidity-providers/the-basics) - [Maverick Protocol - Dune Analytics](https://dune.com/mati/maverick-protocol) - [LST Wars ⚔](https://dune.com/murathan/lst-wars) - [Maverick Procotol - AMM for every market condition](https://dune.com/murathan/maverick) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- # Uniswap v4: The liquidity Marketplace > Understanding uniswap v4 and its shift to a liquidity platform - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-06-30 - Canonical: https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/ - Keywords: crypto, DeFi, market making, yield, Ethereum ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/bdd7cde8ce7e.jpg) > ***Shoal Research Contributors**:* ## Preface Uniswap, the ERC-20 AMM, has played a pivotal role in revolutionizing decentralized finance (DeFi) through its successive versions. Uniswap v1 allowed users to swap ETH to ERC-20 tokens, while v2 allowed users to trade ERC20 tokens with other ERC20s. V2 also added a wide range of assets that were not yet available on any other exchanges, all using a constant product market maker (CPMM) model. The constant product market-making model, X*Y=K, allows users to trade with a pool of tokens rather than with direct peers or market makers. The revolutionary Uniswap v3 allowed liquidity providers the freedom to concentrate their liquidy range in a liquidity position (LP), which improved capital efficiency but added complexity and increased gas costs for users. *Capital efficiency: “Effective utilization of resources to generate maximum output or returns. Prevention of idle money.”  - [Shoal Research](https://www.shoal.gg/p/stablecoins-backed-by-lsts)* Each version pushed the capabilities of decentralized exchanges, empowering users and driving innovation in the DeFi space. With the upcoming release of Uniswap v4, the protocol is set to introduce even greater customization and flexibility through hooks, further solidifying its position as a leading decentralized exchange platform. This article explores the features and enhancements of Uniswap v4. Let's walk through the v4's architecture and uncover how they plan to improve the DEX landscape. ## Uniswap v3, Concentrated Liquidity ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/1f73d08d5850.jpg) Before diving into the specifics of v4, it is crucial to understand Uniswap v3, a landmark development in the AMM landscape. V3 introduced concentrated liquidity, an innovation that allows liquidity providers to designate specific price ranges for their capital. By providing specific price ranges for liquidity, LPs can earn greater fees boosting capital efficiency. Uniswap v2 is based on the constant product formula X*Y=K, which at the time was novel because it created markets for illiquid assets. However, has reduced capital efficiency since liquidity was spread infinitely along the liquidity curve. Meaning whenever an LP provided liquidity, they supported all asset prices. With the advent of v3, users were given more autonomy to specify fee tiers and even liquidity ranges, leading to higher capital efficiency and deeper liquidity. ## Uniswap v4, AMM Marketplace Taking v3 a step further, Uniswap v4 introduces new customization through the Singleton contract and hooks, which we will detail shortly. These innovative solutions aim to streamline on-chain computations, reducing costs and some complexities while offering more capital efficiency and flexibility with protocol designs built on Uniwap. Before v4, Uniswap v3 assigned core immutable parameters that the core team calls "opinions," such as fee tier and other predefined structures, meaning the Uniswap team came up with immutable features for v3 that are now customizable in v4. With v4, developers can become "expressive" about the liquidity pool parameters, which is expected to lead to extensive financial primitives on top of the Uniswap liquidity layer. ## Liquidity Platform Lack of liquidity is one of the core issues in the DeFi space, as protocols need substantial liquidity to perform extensive DeFi operations. Uniswap v4 aims to serve as the liquidity layer for many of these protocols. Think of Uniswap v4 with regard to the iPhone ecosystem. Apps like Telegram, Twitter, and Instagram are developed and deployed to the Apple App Store, reaching an extensive user base. Similarly, liquidity management protocols, DEXs, and other Dapps can tap into Uniswap V4 to utilize its liquidity through hooks. Just as users visit the App Store to obtain desired apps, users can turn to protocols built on Uniswap V4 to access the specific liquidity strategies and other tools they desire. By leveraging a platform-based approach, Uniswap v4 can benefit from network effects by other protocols developing on its liquidity layer. Network effects are a phenomenon particularly observable in social media, which refers to the exponential growth of products as they accumulate more users, eventually leading to a dominant market position. ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/3e26e9fcb13b.jpg) ## What exactly is the Singleton contract? The singleton contract structure is an innovative feature of Uniswap v4 that consolidates multiple token pool contracts into one overarching contract. In the example below, for an ETH/DAI swap, the trade routes between multiple trading pair pools to reach the desired outcome. With the singleton contract, the trade is routed through one contract full of many trading pairs. Instead of moving tokens between pools, the contract does balance accounting similar to swaps on centralized exchanges, known as Flash accounting. ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/db50c9e371e7.png) ### Flash Accounting Flash accounting updates the internal net balance and executes external transfers only at the end of a block, reducing gas costs while simplifying complex pool operations like atomic swapping and liquidity addition. Flash accounting also enhances the efficiency of multi-hop trades, delivering cheaper costs for swapping and improved slippage on multi-hop swaps. This innovation benefits end users by making transactions more affordable and seamless. Combining the singleton contract and flash accounting, Uniswap founder Hayden Adams estimates a 99% fee reduction for deploying a new liquidity pool. ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/e8dd41def804.png) ## Introduction of Hooks! Uniswap v4 introduces the concept of "hooks," which offer developers the ability to customize liquidity pools. Hooks are externally deployed contracts that execute developer-defined logic at key moments in the pool's lifecycle, such as before, after, or during a swap. Hooks are widget-like add-ons to liquidity pools that enable increased functionality and features. These hooks allow for custom implementations such as dynamic fees, on-chain limit orders, advanced oracles, and novel liquidity strategies, traditionally predefined by the protocol like in v3. This level of flexibility enables developers to harness and innovate on Uniswap's liquidity and security, tailoring the trading experience to their specific requirements. ![](https://shoal.xyz/research/writing/uniswap-v4-the-liquidity-marketplace/img/16cdb651f43f.png) One notable example is the utilization of hooks to create a time-weighted average market maker (TWAMM), which addresses the challenge of minimizing price impact when executing large orders in automated market makers (AMMs). By breaking up large orders over time, TWAMM, implemented as a hook, offers a sophisticated solution to enhance trading strategies. ### Fragmented Liquidity Expanding on the "opinions" that the core Uniswap team made on Uniswap V3, protocols that wanted to modify the core parameters previously had to fork the Uniswap codebase. This often led to fragmented liquidity and increased transaction costs due to the augmented on-chain computations required, as each asset pair operated as its own contract. Now, protocols can leverage hooks, simplifying the implementation process to fit their specific criteria without needing to fork the codebase. Ultimately, hooks significantly enhance liquidity management and trading for traders and providers. ### Hooks extended use Cases: In addition to TWAMM, hooks unlock a multitude of possibilities for customization, such as: - **Dynamic Fee Structures:** Hooks enable the implementation of dynamic fees that can be based on various factors, such as market volatility or other user-defined inputs. This flexibility allows for fee adjustments that align with changing market conditions. - **Onchain Limit Orders:** With hooks, users can leverage on-chain limit orders, enhancing the trading experience by enabling precise execution at predetermined price levels. This feature brings greater control and efficiency to trading on Uniswap. - **Enhanced Liquidity Deployment:** Hooks offer the ability to deposit liquidity outside the typical price range of a pool into lending protocols. This feature expands liquidity providers' options, allowing them to optimize their capital allocation and explore additional yield-generating opportunities. - **Customized Onchain Oracles:** Through hooks, developers can integrate customized on-chain oracles. These oracles provide alterNative price feeds and data aggregation methods, enabling the creation of innovative trading strategies and improved accuracy in determining asset prices. - **Auto-compounding LP Fees:** Hooks make it possible to automatically compound LP (liquidity provider) fees back into the LP positions. This feature streamlines the process of compounding earnings, optimizing returns for liquidity providers without requiring manual intervention. - **Internalized MEV Profit Distribution:** Hooks facilitate the internalization of Miner Extractable Value (MEV) profits, ensuring that these profits are distributed back to liquidity providers. This mechanism enhances liquidity provision incentives and aligns market participants' interests. ### Reintroduction of Native ETH Support Uniswap v4 brings back support for Native ETH, which was previously removed in v2 due to implementation complexity and liquidity fragmentation. The introduction of flash accounting and the singleton contract enables the efficient handling of Native ETH by transferring assets only on net balances. This results in significant gas savings, as Native ETH transfers are approximately half the cost of ERC-20 transfers. Although the handling of Native ETH remains a challenging area, the benefits it brings in terms of reduced gas costs make it a valuable addition to Uniswap v4. ## Summary and Conclusion Here is a wrap up of what Uniswap V4 is all about: - Uniswap v4 introduces hooks, enabling customization of liquidity pools and trading experiences. - Hooks allow the execution of custom code at specific points during a pool's execution. - Customizability empowers builders to create unique trading experiences and break free from predefined rules. - Uniswap v4 features improved gas efficiency with a singleton implementation and flash accounting. - Native ETH support is reintroduced, bringing significant gas savings. - Hooks enable a variety of use cases, including TWAMM, dynamic fee structures, on-chain limit orders, enhanced liquidity deployment, customized on-chain oracles, auto-compounding of LP fees, and internalized distribution of MEV profits. - Uniswap v4 improves DEX landscape by offering greater customization and flexibility. These new features and improvements have the potential to enhance the efficiency of Uniswap. But the added complexity may require a steep learning curve and potentially limit adoption among less tech-savvy users. It's also important to note that Uniswap v4 will not replace v2 and v3. Each version has its unique features and improves on the earlier versions. The decision to use v2, v3, or v4 will depend on a user's specific needs and understanding. Uniswap v4 represents a step forward in terms of possibilities, and it also shows the inherent trade-off between efficiency and user-friendliness in the DeFi space. It will depend on front-end implementations to see how end users can interact without deeper understanding. ## Sources - [https://uniswap.org/faq](https://uniswap.org/faq) - [https://blog.uniswap.org/uniswap-v4](https://blog.uniswap.org/uniswap-v4) - [https://blog.uniswap.org/uniswap-v3](https://blog.uniswap.org/uniswap-v3) - [https://blog.uniswap.org/fee-returns](https://blog.uniswap.org/fee-returns) - [https://blog.uniswap.org/launch-uniswap-v3](https://blog.uniswap.org/launch-uniswap-v3) - [https://blog.uniswap.org/uniswap-v3-math-primer](https://blog.uniswap.org/uniswap-v3-math-primer) - https://github.com/Uniswap/v4-core/blob/main/whitepaper-v4-draft.pdf --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Stablecoins backed by LSTs > An In-depth Look into CDPs in LSTfi, and overcollateralized crypto backed stablecoins - Publisher: Shoal Research (https://shoal.xyz) - Category: Agentic Payments - Published: 2023-06-23 - Canonical: https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/ - Keywords: stablecoins, crypto, DeFi, liquid staking, yield, infrastructure, Ethereum, Agentic Payments ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/b846f0b64627.jpg) ## Intro Stablecoins are among the most proven use cases of cryptocurrency in an environment where a large portion of the world wishes to avoid the restrictions of the US banking system while still having access to a USD-denominated currency. Stablecoins like Tether (USDT) are incredibly useful, with daily trading volumes in the billions. However, users often depend heavily on banking infrastructure and trust in the custodian's practices is paramount. This is where stablecoins backed by crypto assets and now LSTs (Liquid Staking Tokens) come in. This research paper highlights key innovations in the decentralized finance (DeFi) ecosystem, focusing on collateralized debt positions in liquid staking Defi (LSTfi). Key players within the LST-backed CDP sectors, such as crvUSD, Lybra, Raft, Gravita, and Dinero, emerge as first movers in the growing landscape, utilizing unique protocols mechanics to enable financial stability and capital efficiency within the DeFi ecosystem. This study aims to provide insights to help evaluate the potential risks and benefits associated with these rapidly evolving protocols. ## Stablecoin Trilemma Stablecoins, though varied in design, are universally aimed at maintaining a stable value, typically pegged to the USD. Two of the top five cryptocurrencies by market capitalization are stablecoins, predominantly backed by USD or US Treasuries. Despite the large on-chain volumes commanded by USDC (USD Coin) and USDT (Tether), the market seeks alternatives, primarily due to these stablecoins' reliance on off-chain trust. Designing a stablecoin involves a complex problem, the so-called stablecoin trilemma, which envisions an ideal stablecoin as having three core attributes: price stability, decentralization, and capital efficiency. - **Price stability:** Maintaining a stable peg. - **Decentralization:** distributing powers and governance away from a central authority. - **Capital Efficiency:** Effective utilization of resources to generate maximum output or returns. Prevention of idle money. The leading fiat-backed stablecoins offer capital efficiency and price stability but fall short in decentralization. While these have become the default stablecoins for many market participants, due to increasing regulatory scrutiny and transparency issues, users have begun exploring diverse stablecoin models. Algorithmic stablecoins, which are capital efficient and decentralized, are one such option, although they may face a potential "death spiral," as observed with Terra Luna’s UST. ![source](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/c0f2d0c7f27d.jpg) The third architecture, crypto-backed stables, combines decentralization and price stability but falls short in capital efficiency. The permissionless nature of crypto and decentralized markets largely drive the crypto ethos. However, many market participants, especially newcomers and institutional actors, do not put decentralization high on their list of priorities. This lack of emphasis, along with first-mover advantages, fuels the explosive growth in fiat-backed stables. The early market entry of fiat-backed USDT also played a significant role in spurring the surge of fiat-backed stablecoins. Consequently, crypto-backed stablecoins have not emerged as the top preference for many. LST-backed stablecoins interrogate this trilemma in an effort to bridge all three components, creating a reliable medium of exchange. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/1f07fc2889fa.jpg) ### Collateralized Debt Position - CDP In traditional finance, there exists a concept known as collateralized debt obligations (CDOs). These financial instruments are essentially bundles of loans or other valuable assets that can be utilized to offset losses if a loan repayment fails. Despite their inherent risk, they are considered practical tools in the financial sector since they grant depositors a line of credit backed by their assets. With the advent of blockchain technology, similar structures emerge without the need for banks or intermediaries. Collateralized debt positions, known as CDPs, are permissionless assets backed by on-chain deposits of other assets. Akin to digital vaults, users can deposit valuable digital assets, such as Ethereum (ETH), and in exchange, they receive another digital token, often a stablecoin like DAI. Stablecoins are useful because they are engineered to maintain a stable value close to $1, thus enabling users to have access to a less volatile asset (DAI) for payments while still maintaining exposure to the underlying asset (ETH). ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/fc5af4bd3d98.jpg) There are over forty such systems, collectively valued at over $8.9 billion. The largest among these is MakerDAO, which holds more than $7.6 billion in assets. ### LSTfi Liquid Staking Derivatives Finance (LSTfi) comprises decentralized finance protocols that extensively utilize Liquid staking tokens (LSTs) in DeFi operations. LSTs are typically ERC-20 tokens representing a user's staked ETH, such as stETH issued by Lido. With LSTs, users can earn rewards, trade on decentralized exchanges, and utilize other DeFi services. The primary advantages of LSTfi include the capability for users to earn interest on their staked assets while maintaining access to them and the opportunity to trade staked assets without needing to unstake them. ### CDPs in LSTfi Currently, there is a huge race among CDP protocols competing within LSTfi to capture TVL (total locked value). The CDP LSDfi protocols follow the same general principles where users can deposit their staked assets to mint stablecoins. In the context of LSTfi, users typically deposit a LST (stETH) to borrow a stablecoin (like R, raft stablecoin) against it (as shown in the Figure below). If the value of a user's collateral falls below a certain threshold, their assets will be liquidated (sold off) to cover the decrease in prices, resulting in the loss of their staked assets. **Here are the benefits of using CDPs:** **Earn interest on staked assets:** Users can earn interest on their staked assets by minting LSDs and using them to yield earnings on DeFi protocols. **Trade-staked assets without unstaking:**Users can trade staked assets without having to unstake them by using LSDs. This can benefit users who want to seize market opportunities without needing to tie up their stakes. **Access DeFi services:** Users can access DeFi services, such as lending and borrowing, by using LSDs. This is useful for those who want to use their staking assets to generate income or hedge against market volatility. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/e471eadb2d89.jpg) The emergence of LSTfi protocols has been driven by the desire for more stable and less volatile financial instruments within the cryptocurrency market. These protocols often offer unique features and benefits, such as lower liquidation risk, and yield farming opportunities, giving market participants more utilities for assets they already own. At the time of writing, approximately $18.34 billion is locked in liquid staking protocols, and around $9.37 billion is locked in DeFi CDP protocols. This is in comparison to the all-time high of $30.5 billion locked in CDPs during the peak of the 2021 bull market, largely driven by MakerDao. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/c604a84ff2e7.jpg) These emerging protocols, each with unique offerings and associated projects are shaping the future of LSTfi with CDPs. Here are some of the notable ones: 1. **crvUSD**: A stablecoin that rebalances user collateral into more stable assets as the price falls, thus reducing liquidation risk. 2. **Lybra**: Known for eUSD, a yield-producing stablecoin. 3. **Raft**: Single collateral stETH and smart liquidation through flash mints. 4. **Gravita**: Borrower-friendly terms and focus on censorship resistance. 5. **Dinero**: Upcoming LSTfi protocol that will leverage its LST for stablecoin minting ### crvUSD CrvUSD is a decentralized stablecoin launched by Curve Finance, a DeFi protocol known for optimizing swaps between identically pegged digital assets, primarily stablecoins. Users deposit collateral to take out a loan in CrvUSD. Initially, CrvUSD will likely accept ETH as collateral, similar to DAI by MakerDAO. Eventually, Liquidity Pool (LP) positions might also be accepted as collateral options. Unlike most CDPs, crvUSD automatically rebalances users' collateral into more stable assets as the price falls, which reduces liquidation risk but potentially limits upside gains. The liquidation mechanism is possible through the lending-liquidating AMM algorithm (LLAMMA). This algorithm sets specific price bands to liquidate portions of the collateral rather than fully liquidating it at a specific price. As the price of the collateral falls, it is sold for CrvUSD. When the collateral value hits the targeted liquidation point, there will already be enough CrvUSD to cover the loan value, averting a typical liquidation scenario. Conversely, as the price of the collateral recovers, crvUSD is converted back into the posted collateral. ![crvusd collateral](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/c12810641d88.png) This mechanism of crvUSD could attract more liquidity providers to Curve's LPs, thereby achieving greater capital efficiency with their funds. Coupled with the reduced risk of liquidations thanks to LLAMMA, this could be very enticing for risk-averse users looking to incorporate elements of leverage into their DeFi strategy. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/5bf698e9668f.jpg) ### Lybra Protocol Lybra is a DeFi protocol that introduces eUSD, the first interest-bearing stablecoin. The protocol operates on a collateralized debt position (CDP) mechanism, where users deposit ETH or STETH as collateral to mint eUSD. The stability of eUSD is maintained through a combination of over-collateralization, liquidation mechanisms, and arbitrage opportunities. Lybra's unique interest-bearing stablecoin, eUSD, generates a base annual percentage yield (APY). This stable yield attracts users seeking a steady income stream while maintaining exposure to ETH staking. Furthermore, as the price of ETH increases, the yield generated by eUSD holders also rises, and conversely, it decreases in the event of a price drop. **Zero Minting Fees and Loan Interest** Lybra differentiates itself from other stablecoin protocols by offering users zero minting fees and zero loan interest. This feature allows users to leverage their ETH holdings and mint eUSD stablecoins without incurring additional costs. **How Lybra Works** 1. **Deposit:** Users deposit ETH or stETH as collateral. 2. **Mint eUSD:** Users can mint or borrow eUSD against their collateral. 3. **Receive Interest or Spend**: Users can hold eUSD to receive interest APY or use it in other DeFi protocols. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/065079c6c067.jpg) ### Raft Protocol Raft is the first US dollar stablecoin collateralized solely by Lido Staked Ether (stETH). This stablecoin is designed to retain a value of 1 USD, maintaining its peg through a combination of hard peg and soft peg mechanisms. The launch of Raft provides a solution for Lido users seeking capital-efficient ways to use their stETH. The protocol allows depositors to generate R, a decentralized USD stablecoin, using their stETH, eliminating the need for fiat backing. On a positive note, Raft's Total Value Locked (TVL) jumped to $29 million in just three days, representing a daily increase of 15%. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/552e0a6b63d3.png) **One-Step Leverage** One of the unique features that Raft plans to introduce soon is one-step leverage, which enables users to trade with up to 11x leverage on stETH in a single transaction. This leverage ratio is higher than what any other platform currently offers. Moreover, Raft simplifies the complex multi-step transactions required to gain leverage on stETH through other loan platforms like Aave or Maker. This functionality utilizes Flash Mint to offer leverage on stETH. **Raft Flash mints** Another unique feature of Raft is its use of flash mints rather than a stability pool for liquidation. A flash mint is a type of flash loan, a feature offered by some DeFi protocols that allow users to borrow and repay an asset within the same transaction. This can be used for various purposes, including arbitrage, collateral swapping, and self-liquidation. Using flash mints for liquidation aims to make the liquidation process faster and more efficient. However, it also introduces additional complexity and potential risks. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/cd79bde64eb5.jpg) ### Gravita The Gravita Protocol is a unique, Ethereum-based borrowing system offering interest-free loans using liquid staking tokens (LSTs) and a stability pool (SP) as security. Borrowers receive loans by minting GRAI, a token designed to reduce price volatility. Loans can reach up to 90% - 99% of the collateral's value, depending on the type of collateral. **Here's how Gravita works:** 1. **Borrow GRAI**: Users open a vessel to deposit collateral. They can borrow GRAI with a maximum fee of 0.5% and enjoy 0% interest indefinitely. 2. **Deploy GRAI**: 1 GRAI is equivalent to $1. Users can swap or spend it however they like or deposit it in Gravita's Stability Pool to purchase WETH and LSTs at a discount. 3. **Repay GRAI**: Users can close their vessel and withdraw collateral conveniently. Repaying within 6 months grants a partial refund of the 0.5% fee. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/d2bb438cf680.png) **Earning Money with Gravita** You can generate income on Gravita by contributing to the stability pool, designed to repay the debts of liquidated positions that exceed the maximum loan-to-value (LTV) ratio. You can earn income from liquidation gains by participating in the stability pool. Gravita may also introduce a governance token in the future to offer additional benefits to users. At the time of writing, the total value locked in the Gravita Protocol stands at around $20.6 million, up 10% weekly since launch. The protocol continues to attract more users as the TVL continues to grow. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/ad6b83ba2a02.png) **GRAI and GRVT (soon) Tokens** GRAI is an over-collateralized debt token issued by Gravita, meaning that the collateral backing it exceeds the loan's value. It is generated when assets are deposited into the Gravita Protocol. The price of GRAI is kept within a certain range through mechanisms that establish a rigid price ceiling and floor, offering arbitrage opportunities that aid in maintaining price stability. Additionally, Gravita may launch a governance token named GRVT in the future to confer extra perks to users. **Pros** - Interest-Free Loans - Diverse Collateral Types - Earning Opportunities - Non-Custodial and Transparent: Price Stability Mechanisms **Risks** - Risk of Asset Loss - Dependence on User Understanding - Smart Contract Risk ## Dinero Protocol The Dinero Protocol is a decentralized finance (DeFi) project developed by the Redacted Cartel. It introduces a new permissionless stablecoin, Dinero, which is backed by user-owned block space and is designed to maintain a 1:1 value ratio with the US dollar. **Here's how Dinero works:** 1. **Stake ETH:** Users with Ether can utilize the Dinero Protocol to stake their ETH. 2. **Access a Premium Decentralized Remote Procedure Call (RPC)**: This feature revolves around DINERO as a medium of exchange. 3. **ETH Liquid Staking Token (LST):**The protocol includes an ETH liquid staking token (LST), which benefits from staking yield, and the Dinero Protocol. **Staking ETH: Empowering Users** Initially, DINERO will function like a typical collateralized debt position (CDP) stablecoin, such as $DAI. However, the ultimate goal is to use the underlying $ETH collateral to enable a decentralized RPC and a block builder that protects Dinero users from MEV attacks. **Decentralized RPC:** Dinero Protocol aims to democratize access to premium block space on the Ethereum network by allowing users to back their own block space and access a premium decentralized RPC. This unique feature opens up various possibilities, enabling users to interact with decentralized applications (DApps) and smart contracts with enhanced capabilities and efficiency. **ETH Liquid Staking Token (LST): Maximizing Benefits** Dinero Protocol introduces the ETH Liquid Staking Token (LST) to maximize user benefits. Users can earn staking yields from their ETH holdings by participating in the protocol while utilizing the Dinero protocol's additional utility. The LST acts as a bridge between the staked ETH and the Dinero ecosystem, providing users other benefits and opportunities within the protocol. **The Significance of Redaction and Curve:** The partnership between Redacted (the team behind Dinero) and Curve holds significant importance. In the early years of on-chain CDPs, achieving liquidity escape velocity was a primary challenge. The 'bribe power' associated with Redacted, in collaboration with Curve, plays a crucial role in addressing this challenge. Simply put, by utilizing curve protocol, Dinero can achieve critical mass liquidity to operate efficiently. These strategic alliances enhance liquidity and foster the growth and adoption of the Dinero Protocol within the DeFi space. ## More Notable LSTfi CDPs **Origin Protocol**: Origin Protocol is a platform that aims to bring the next 100 million users to crypto through its products in the NFT and DeFi sectors. Its Origin Token (OGN) stakers earn their share of Story's platform fees, and it also offers a yield-generating stablecoin called Origin Dollar (OUSD) **Tenet**: Tenet is an EVM-compatible Layer-1 blockchain that utilizes liquid staking derivatives (LSDs) as collateral for network validators, enhancing security and governance inclusivity. It issues tLSDs, representing staked LSDs, and provides yield opportunities from multiple sources, including block rewards, dAPP user incentives, and its native stablecoin, LSDC, minted against overcollateralized positions of tLSDs. **Aave GHO:** GHO is a stablecoin issued by Aave, and its value is pegged to the US dollar (USD). GHO is fully decentralized and secured by an over-collateralization mechanism, similar to Aave's crypto loans. Aave mints GHO tokens when users of its loan service deposit cryptocurrency as collateral to borrow GHO tokens. **Frax Finance:** Frax Finance is a fractional-algorithmic stablecoin protocol that uses collateralization and algorithmic mechanics processes to create its decentralized stablecoin, FRAX. The collateral ratio, which is the ratio of collateral needed to back $1 of FRAX, varies with time and is solely determined by market forces. Only stablecoins are currently accepted as collateral by the protocol, with plans to accept more volatile collateral like wrapped BTC as the protocol is increasingly adopted **Prisma Finance:** Prisma Finance is a decentralized finance (DeFi) protocol that facilitates the utilization of LST as collateral for the purpose of borrowing acUSD, a stablecoin that is fully backed by collateral within the protocol itself. The act of staking acUSD on Curve and Convex platforms is met with rewards in the form of various incentives, including trading fees as well as the governance tokens known as CRV, CVX, and PRISMA. ![](https://shoal.xyz/research/writing/stablecoins-backed-by-lsts/img/88c1cc066da0.jpg) ### Conclusion In short, liquid staking derivatives finance (LSTfi) and collateralized debt positions (CDPs) are revolutionizing decentralized finance (DeFi) by allowing users the ability to leverage their assets, earn interest, and access DeFi services. These protocols provide innovative features such as stablecoin rebalancing, interest-bearing tokens, and unique collateral options. With a growing market and increasing value, LSTfi and CDPs are reshaping the DeFi landscape, creating new user opportunities. LSTfi and CDPs are transforming DeFi by enabling asset leverage, interest earnings, and access to services. Notable protocols include crvUSD for stablecoin rebalancing, Lybra for interest-bearing stablecoins, Raft for unique leverage and flash mints, Gravita for borrower-friendly terms, and Dinero for user-owned blockspace and premium access. These protocols drive innovation in a rapidly evolving DeFi landscape. ### Sources: - [Stability Pool - Gravita Protocol Docs](https://docs.gravitaprotocol.com/gravita-docs/how-does-gravita-work/stability-pool) - [Curve Monitor](https://curvemonitor.com/#/) - [Stablecoins: A Coinbase White Paper](https://assets.ctfassets.net/c5bd0wqjc7v0/79db1PxjBTv1JbL574fFvA/dc38c8c96dc97c3752fd81a61d0f134a/CBI-StablecoinWhitepaper-July-2022.pdf) - [Curve Finance](https://resources.curve.fi/) - [Raft Docs](https://docs.raft.fi/) - [LSDFi 💧 (Lybra Finance, Pendle, Unsheth and More!)](https://dune.com/defimochi/lsdfi-summer) - [GHO Stablecoin - FAQ](https://docs.aave.com/faq/gho-stablecoin) - [Crypto-backed Stablecoins](https://stablecoins.wtf/resources/crypto-backed-stablecoins) - [Gravita Protocol Docs](https://docs.gravitaprotocol.com/gravita-docs/) - [20230406 - v1.0.pdf at master · redacted-cartel/dinero-litepaper · GitHub](https://github.com/redacted-cartel/dinero-litepaper/blob/master/Dinero%20Protocol%20litepaper%20-%2020230406%20-%20v1.0.pdf) - [crvUSD Dashboard](https://dune.com/Marcov/crvusd) - [MakerBurn](https://makerburn.com/#/rundown) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # The Art and Science of Memecoin Bots, Tooling, and Infrastructure: A Comprehensive Study > Exploring Crypto Bot Services, and a deep dive into bot tooling and Infrastructure - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-06-13 - Canonical: https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/ - Keywords: crypto, DeFi, market making, privacy, infrastructure, Ethereum ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/486e40e094a4.jpg) ***Disclaimer:** The concepts and projects discussed in this paper are highly speculative, and the longevity of these initiatives is uncertain. It is important to exercise caution and conduct thorough research before engaging with these projects.* ## Intro From SaaS (Staking as a Service) to WaaS (Wallet as a Service), a new wave of services is emerging in the crypto space, focusing on BaaS (Bots as a Service) and the explosive memecoin ecosystem. While some complain about the recent “lack” of innovation in the market, and project teams still recovering from the bear market, there are always visionary projects pushing the boundaries. A few savvy teams are now seizing the opportunity presented by the speculative craze surrounding memecoins in the form of memecoin trading infrastructure and tooling. The recent large focus on trading new memecoins could be due to poor market conditions and the possibility of an echo bubble effect within the crypto industry. This echo bubble theory suggests that existing market participants are constantly exchanging funds among themselves, creating a closed loop. Notably, new memecoin projects have experienced exponential growth in market capitalization, some even breaking into the top 100 assets by market cap, generating significant trading volume. While DEX volume may have decreased, the deployment of hundreds of verified smart contracts on Ethereum alone each day is largely driven by the memecoin phenomenon. A good portion of the [verified contracts](https://etherscan.io/contractsVerified/1) on mainnet (Ethereum) point to new ERC-20s. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/535abbb3afdf.png) ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/8c225bf558ea.jpg) Amidst this trading chaos, a select few projects focus on providing essential tools and infrastructure for traders, resembling the role of [Levi Strauss](https://www.levi.com/US/en_US/features/about-us) (picks, shovels, and jeans) during the gold rush. The recent surge in tooling infrastructure, although still in its early stages, has already significantly impacted traders. These services encompass automated trading solutions that execute trades on behalf of users, leveraging algorithms and data analysis. They also offer real-time monitoring of on-chain smart contracts to identify potential risks like honeypots or rug pulls, safeguarding traders' interests. ### Echo Bubble Fuel Many traders, including prominent venture capital firms, have expressed their dissatisfaction with the current bear market conditions. However, it is essential to note that the crypto market is cyclical in nature, and periods of downturn are not unprecedented. The combination of increased regulatory scrutiny and the overall bearish sentiment in the market may be contributing to the lack of significant project launches in recent months. Despite the challenging market conditions, total on-chain transaction volume has remained relatively high. It’s worth considering the possibility of an echo bubble phenomenon taking place. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/de32014f8a8a.jpg) ### Who cares about memecoin bots? Simply put, **bots are very profitable**. While the concept is not groundbreaking, several emerging protocols are propelling the landscape by offering professional-grade trading tools and generating substantial revenue. For example: Maestro, a prominent telegram bot has raked in an **impressive $5.5 million in revenue for the month of May alone**, as reported by Defi Llama. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/c3aeef3ba8f0.jpg) Maestro takes a **1% tax** on every successful buy and sell. These fees are automatically collected and sent to the revenue wallet address: ``` 0xCac0F1A06D3f02397Cfb6D7077321d73b504916e ``` Generally, once the revenue wallet collects a certain threshold of fees, they are subsequently sent to a smart contract that distributes the ETH to multiple wallets in one transaction. We can assume much of the revenue is disbursed directly to the core teams and treasury wallets. Maestro has collected **50-100 ETH daily within the last few days**. ![Etherscan](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/f193550e6bb1.jpg) Maestro empowers traders to exchange tokens through their user-friendly telegram interface seamlessly. It provides many tools to enhance trading efficiency, including contract snipers, copy trading, auto buying, etc. The success of Maestro and similar platforms highlights bots' significant role in facilitating seamless and profitable trading experiences for advanced speculative traders. As you might be able to tell, Maestros pro tools allow traders to save time on steps that might cost a difference between getting in a project at 50k MCAP (market capitalization) versus 1m MCAP. With memecoins, speed is a critical piece of the trade. ## Competitive Landscape Maestro is one of many players in the market offering advanced tooling. There are several other projects in the space working towards similar goals. However, it is essential to note that these projects are still in their early stages and come with a high level of speculation and risk. Market participants must exercise caution. Lets dive into some other service providers that are competing in this “Bot Wars”. ### Unibot [Unibot](https://twitter.com/TeamUnibot) is a platform that aims to provide a solution for rapid memecoin and crypto trading on Telegram. Like Maestro, It allows users to quickly execute buy and sell orders directly from their Telegram hot wallet by pasting a contact pair in the Telegram bot channel. Unibot optimizes speed by utilizing token pool contracts and supports trading on Uniswap v2 and v3. Additionally, the platform offers advanced features such as Multi-wallet swaps, Smart Method Sniper, and Mirror Sniper, allowing users to enhance their trading strategies. Unbot also employs their UNIBOT token, which gives users a discount on trading fees while also providing revenue share in the near future from staking. **You can find the comprehensive analysis of Unibot in this earlier report:** [Shoal ResearchUnibot: The Telegram Uniswap SniperWe’ve all been there Have you ever found yourself in a situation where you want to make a quick crypto trade on info from Telegram, but you don't have the time or ability to navigate the various interfaces and wallets required to do so? Unibot has the answer…Read more3 years ago · Gabe Tramble](https://www.shoal.gg/p/unibot-the-telegram-uniswap-sniper?utm_source=substack&utm_campaign=post_embed&utm_medium=web) ### Scarab Tools [Scarab Tools](https://scarab.tools/), also similar to Unibot and Maestro, is another bot that utilizes an online dashboard that provides trading and analysis tools for newly deployed token contracts. Scarab is a platform specifically designed for trading memecoins, known on scarab as "dung", efficiently and transparently. The platform offers timely notifications for new token listings, contract simulation for enhanced transparency, and real-time statistics on token launches. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/d84e511b54ce.jpg) Scarab's roadmap includes the development of a sniper bot for quick swaps and a user-friendly position management dashboard. ### Pintswap [PintSwap](https://twitter.com/pintswap0x) is an OTC (over-the-counter) decentralized exchange (DEX) that introduces a unique approach to trade facilitation in the cryptocurrency market. The platform focuses on low market-cap and low liquidity tokens, aiming to address the issue of high slippage commonly associated with such assets. PintSwap mitigates price impact by conducting OTC transactions and avoids the traditional automated market maker (AMM) pricing mechanics. In contrast to conventional DEXs, PintSwap establishes direct connections between traders using libp2p, a peer-to-peer network stack developed by IPFS. PintSwaps tooling aims to enhance the efficiency and privacy of over-the-counter (OTC) trading while eliminating significant slippage (price impact). By eliminating the need for visible contracts on the blockchain, PintSwap provides an alternative solution for traders seeking secure and efficient OTC transactions in the crypto space. ### 0xAuto [0xAuto](https://twitter.com/0xautoERC) is a telegram bot designed to simplify the token deployment process on Uniswap V2, PancakeSwap V2, and Goerli's Uniswap V2. Users can deploy a token contract quickly from telegram, eliminating the need for traditional solidity tooling such as Remix to deploy contracts. It offers a range of features, including: - **Swift Deployments:** Enables quick token deployments - **Automated Liquidity Addition and Etherscan Verification:** Integrates with Uniswap V2 and PancakeSwap V2 to add liquidity automatically and simplify Etherscan verification. - **Sniper Deterrence and Launch Security:** Acts as a deterrent against snipers, enhancing the security of token launches. - **Multi-Platform Compatibility:** Supports Ethereum, Binance Smart Chain, and Goerli, providing flexibility across different blockchain platforms. - **Contract Ownership and Customization:** Gives contract creators complete ownership and control over token contracts, allowing customization. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/d6a04df6fd61.jpg) ### thejungool [Thejungool](https://twitter.com/thejungool) is a comprehensive platform that offers advanced features to enhance cryptocurrency trading strategies. With its powerful capabilities, thejungool provides: - **Advanced Coin Filtration:** Discover promising coins at launch with early alerts. - **Token Sniping:** Execute high-speed token purchases with optimized gas and slippage. - **Position Management:** Conveniently manage positions through Discord, enabling quick actions. - **Watch Pockets:** Track influential traders and receive alerts for their buying and selling activities. TheJungool's automation features enable auto-buying of newly discovered gems, mirroring trades, and real-time social media monitoring of influential figures. Additionally, the tool provides in-depth token analysis, including distribution details and monitoring of whale and sniper wallets. ### PepeAnalytics [PepeAnalytics](https://twitter.com/pepeanalyticsai) is developing a comprehensive dashboard for analyzing memecoins. Pepe aims to combine social, on-chain, and machine learning to identify new opportunities while providing traders tools to quickly trade based on the platform data. **Some notable features include:** - **Smart Contract Audit Aggregator:** Pepe Analytics aggregates existing smart contract audit tools, such as [De.Fi](http://de.fi) and Tokensniffer, to filter out scams and ensure a safe experience when investing at the smart contract level. - **Deployer & User Data:** The platform recognizes the importance of data related to coin deployment and pair creation. Data includes; funding sources, coin holdings, deployment history, and ownership percentages, as well as data on the investors themselves, top holders, and early participants in the launch. - **Social Analytics:** Pepe Analytics acknowledges the significance of reputation and social influence in the memecoin space. Users can copy trade other wallets, with a leaderboard system that notifies users when tracked individuals purchase memecoins. This simple social analytics feature complements the core functionalities of the platform. - **Bonus: Tokensniper:** Pepe Analytics plans to include a token-sniper feature in the dashboard, allowing users to trade tokens based on preset criteria quickly. ![](https://shoal.xyz/research/writing/the-art-and-science-of-memecoin-bot/img/df46729b9303.jpg) ### blacksmith0x [blacksmith0x](https://twitter.com/Blacksmith0x/with_replies) is an upcoming platform that aims to automate buying and selling new listings on Uniswap. With their advanced AI model, Blacksmith0x will automatically purchase new Uniswap listings that meet specific conditions and sell them as they appreciate. The platform distinguishes itself by positioning as a developed AI model rather than just a typical Telegram sniper. Despite being an unreleased product, Blacksmith0x has generated curiosity within the crypto community, although limited information has been disclosed about its features and functionalities. ### Other interesting Bot Services - **[Farmerfrens](https://twitter.com/farmerfrens):**An automated airdrop farming Telegram bot - **[SybilSamurai:](https://twitter.com/SybilSamurai)**NFT-gated airdrop farming vaults. - **[Meowl](https://twitter.com/meowlxyz):** A Discord community-centric bot for contract monitoring and sniping. ## Conclusion In conclusion, the Crypto market is experiencing a surge in the development of tools and services to enhance trading strategies and capitalize on the booming memecoin trend. These tools offer a range of features and functionalities, including advanced coin filtration, token sniping, position management, influencer tracking, and social analytics. By leveraging these tools, traders can gain an edge in the market, save time, and make more informed investment decisions. Furthermore, the emergence of echo bubbles highlights the speculative underworld in the current market conditions. However, amidst the chaos, projects are stepping up to provide essential infrastructure and tooling for traders, no matter how Degen (risky). These services aim to enhance efficiency, transparency, and security in the memecoin and general ERC-20 landscape, from smart contract aggregators to comprehensive trading dashboards. Overall, the rise of these pro-trading tools and the ongoing development of new protocols signifies the dynamic nature of the crypto market. As the market continues to evolve, traders and investors must adapt to these advancements to navigate the ever-changing landscape successfully. *Good luck fellow pioneer* ### Sources - [Pepeanalyticsai](https://twitter.com/pepeanalyticsai?s=11&t=txFAbiSPTdLLDlAYj9X_AA) - [https://medium.com/@0xAutoBot/introducing-0xswift-bot-the-fastest-token-deployer-for-uniswap-v2-and-beyond-72ec3f169ef](https://medium.com/@0xAutoBot/introducing-0xswift-bot-the-fastest-token-deployer-for-uniswap-v2-and-beyond-72ec3f169ef) - [Pepe Analytics: Are you ready?](https://medium.com/@pepeanalytics/pepe-analytics-are-you-ready-34bc853c126) - [Pintswap-docs](https://github.com/pintswap/pintswap-docs) - [0xAuto Docs](https://0xauto-bot.gitbook.io/0xauto-bot/undefined/introduction) - [Meowl Docs](https://docs.meowl.xyz/) - [Sybil-samurai docs](https://sybil-samurai.gitbook.io/sybil-samurai/how) - [State of Crypto Index](https://a16zcrypto.com/stateofcrypto/) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All posts made by each individual publisher are their own and do not reflect the views or opinions of their respective employers. --- # An Intro to LSTfi > Intro to LSTfi, growing trends in the LST space, and protocols to track - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-06-05 - Canonical: https://shoal.xyz/research/writing/an-intro-to-lsdfi/ - Keywords: crypto, DeFi, liquid staking, yield, infrastructure, Solana, Ethereum, Research ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/98d5ea682967.jpg) ## Intro Ethereum staking, or ETH staking, has ignited a revolutionary shift, establishing a native yield within the Ethereum ecosystem that various protocols can utilize for a diverse range of applications. Over the past year, significant advancements have brought us to our present state in ETH staking, LSTs (liquid staking tokens), and LSTFi Liquid Staking Decentralized Finance). The Shanghai Ethereum upgrade, which enabled staked ETH withdrawals, and the ETH2 merge, moving Ethereum from proof of work to proof of stake, were crucial upgrades that laid the groundwork for the long-anticipated reality of LSTFi. Both upgrades are known together as Shapella. Before introducing the Shanghai upgrade, a wave of developers began hinting at potential strategies to employ existing DeFi (decentralized finance) primitives, intending to maximize yield opportunities for LSTs. LSTs, tokens that symbolize a proportion of already staked ETH, typically trade at or near the parity value of ETH. They offer the user the benefit of retaining a claim on yield while also preserving liquidity. In essence, users can stake while also being able to use the staked position, which is typically locked until the user withdraws. At its core, LSTFi, or LST DeFi, represents DeFi protocols that utilize LSTs to enhance yields, democratize staking service providers, and even fulfill philanthropic objectives by redirecting staking yield towards grants and developmental funding. This multifaceted capability of LSTFi is yet another testament to the dynamic evolution and potential of the Ethereum blockchain ecosystem. Let's explore LSTFi, and coax out the embedded opportunities on the horizon. ### Before Diving in lets understand some key terms: - LST/LSD: Liquid staking tokens (formerly Liquid staking Derivatives)Ex. stETH issued by Lido - LST Providers: Protocols and companies that issue LSTs - LSTFi: Liquid staking defi protocols, Ex. Lybra protocol issuing eUSD ## LST Protocol Dominance LSTs account for over 40% of all staked ETH. Staked ETH accounts include centralized exchanges, LST providers, solo stakers and other entities that deposit ETH into the staking contract. ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/78d42bfde821.jpg) Of the LST providers, Lido, Coinbase, and Rocketpool lead the liquid staking market with a combined share over 90%. Notably, sfrxETH has experienced substantial growth in the past week, indicating increasing popularity. sfrxETH, while lagging at 11%, still represents more than 10% of all sfrxETH used in LSTFi. ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/c299fa6ca2a1.jpg) Currently, only 15.6% of all ETH is being staked. Other top staking chains such as Cardano, Solana, and Aptos have over 60% of tokens in circulation, vastly less than competing proof of stake blockchains. Not only do we see a significant opportunity for LSTFi, but even LSTs have substantial market potential. Compared to other chains, we may expect ETH staking to accelerate to at least 30% in the near future. ### The Rise of LSTFi Projects After Ethereum's Shapella Upgrade After the Shapella upgrade, there has been a surge in ether (ETH) deposits for staking, reaching the highest level since the upgrade. Over 200,000 ETH have been deposited to the network since the start of the week, pushing the amount of ether locked for staking purposes to over 19 million tokens - about 15% of the total circulating supply​. This has catalyzed a boom in new LST/LSTFi projects. With StETH (Lido staked ETH), cbETH (Coinbase staked ETH), and rETH (rocketpool staked ETH) commanding over 90% of the LST+LSTFi market - who can create meaningful value in the vertical? Some of the top LSTFi projects, Lybra Finance, unshETH, Pendle, 0xAcid, and Gravita Finance, offer unique features that could give even the liquid staking a double take in their direction. The figure below shows the explosion of ETH staking deposits post-Shanghai. ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/76984e0108a8.jpg) ### LST and LSTFi Ecosystem As a refresher, LSTFi refers to a set of protocols that leverage LSTs to conduct financial operations within the DeFi ecosystem. LSTFi is perhaps one of the most underdeveloped and underexplored areas in all of crypto, given the total value locked and opportunities on the horizon. Towards the end of 2022 LSTFi projects have struggled mightily to attract liquidity and have seemingly been forgotten. However, since the Shanghai upgrade, there has been a surge in focus on these protocols now that the withdrawal risk on staked ETH has been mitigated. LST providers like Lido and Coinbase have laid the bedrock for LSTFi, providing the foundational building blocks for developing more advanced and innovative products. The principle of composability in DeFi, often likened to 'financial legos', allows protocols to leverage the features built by others without the need to reconstruct the entire system. LSTs, with their increasing popularity, have emerged as the dominant category in terms of Total Value Locked (TVL), and projects like Lido have been at the forefront of this trend. LSTs now play a pivotal role in propelling the overall expansion of the DeFi ecosystem. Within the LST landscape, LSTFi can be broken down into a few verticles: LST Service Providers, Old DeFi with LST Business, and New LSTFi seen in the protocols Fig below; ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/ee0b96b55aa0.jpg) ### LSTFi 2023 Narrative If you are an active participant on Crypto Twitter, you might have caught the slogan, LSTFi Summer, referring to the percolating narrative around LSTFi. LSTs had a significant run-up earlier in the year, with LSTs such as LDO surging over 2x in just a few months. A perfect storm is generated within the sector given the latest surge and trend around LSTs has shined enhanced visibility on LSTFi, coupled with increased staking rewards, access to liquidity, and capital efficiency. By harnessing the native blockchain yield protocols, there is an open landscape for innovation. Fig below ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/ff0f0994dd29.jpg) ### Market Share Breakdown & Comparison In the highly competitive LSTFi market, Lybra Finance stands out, securing over 45% of the Total Value Locked (TVL) within just a month. Alongside Lybra's dominant position, other players like Flashstake, Curve Finance, and OriginDeFi have shown consistent growth, expanding their influence post the initial wave of adoption. Significant contributions to utilizing LST tokens also come from several renowned LSTFi protocols, including Pendle Finance, Unsheth, and Alchemix Finance. Lybra Finance, with its high TVL, continues to lead the LSTFi landscape, significantly outperforming other protocols in acquiring liquidity ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/0efffa63fc7c.png) . Source [Dune](https://dune.com/queries/2512208/4134818) However, the current total value locked (TVL) in these protocols is over $400m which represents less than 2% of the $16 billion worth of LSTs in circulation. This indicates considerable potential for growth and wider adoption within the LST ecosystem materializing the LSTFi Summer narrative! ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/682d9b253170.jpg) ### TVL and Netflows Nearly all the major LSTFi protocols witnessed significant increases in their TVL over the past few months. Among the notable protocols, Unsheth and Pendle Finance stood out as early movers, attracting substantial inflows due to their unique offerings, Fig below ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/ff383d46f405.jpg) ### LSTFi Wars: The War of Market Share With the increased ease for users to switch between Liquid Staking tokens (LST), new competition arises among protocols to attract and retain stakers. Two major factors will drive this competition: **Adoption and Activity** The role of adoption and activity will continue to be significant in the competition between LSTs, particularly in the short term for protocols that have not yet enabled withdrawals. Additionally, as transactions and volume on Layer-2 (L2) chains surpass those on the mainnet, there will be more competition to become the primary LST on L2s. To ensure enough liquidity for protocols on L2 chains and prioritize adoption, strong incentives are necessary to encourage users to migrate from the mainnet (Ethereum Mainnet) to layer 2 protocols such as Arbitrum or Optimism. (Layer-2 Active Addresses Activity Fig Shown Below) ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/ae799d1053db.jpg) **Incentives** LST protocols have always provided various incentives to their users. Before Shapella, many LST protocols focused on getting users to provide liquidity on AMMs (Decentralized Exchanges). By providing liquidity, users received a higher reward, thus incentivizing them to stake ETH with an LST provider, which they might not have done in the first place. Higher rewards or incentives make staking more appealing, allowing users to earn additional benefits or generate passive income. Prior to Shanghai, the LST marketing strategy was deepening AMM liquidity as a means to incentivize users to stake. Fast forward to today, other tools (LSTFi protocols) in the market can incentivize users to stake their ETH and receive an LST. Expanding LSTFi coupled with the ability to redeem LSTs with staked ETH has created a ripe opportunity for users to accept risks for rewards they might not have previously. LST and LSTFi protocols develop progressively sophisticated incentive structures encompassing borrowing/lending, protocol staking, liquidity provision, governance, and protocol fee discounts. These mechanisms aim to amplify user rewards and attract more liquidity by distributing enhanced benefits. Since users can transition between LSTs within the ecosystem, LST protocols are compelled to stay competitive by proposing attractive annual percentage rates (APRs) for staking. The figure below shows how different LSTFi protocols provide additional incentives and attract users. ![](https://shoal.xyz/research/writing/an-intro-to-lsdfi/img/9f92c0c1ffe5.jpg) ### LSTFi Implementations LSTs inherently offer a range of opportunities for yield generation within the LSTFi ecosystem. Various protocols implement innovative strategies, such as AcidDAO, parallaxfin, Pendle.fi, and asymetrix_eth, enabling users to maximize their earnings within the LSTFi space. ### LSTFi Case Studies **Lybra** Lybra aims to provide stability in the volatile cryptocurrency industry by allowing users to mint eUSD, an interest-bearing, omnichain stablecoin backed by LSTs. Specifically, Lybra is backed by ETH and staked Ethereum stETH. The platform allows users to borrow against their deposited ETH and stETH assets, effectively generating a regular stable income from the LST income of the deposited assets. **Pendle.fi** Pendle.fi takes a unique approach by providing a platform for purchasing futures, allowing users to buy ETH at a discount and receive it later. At the same time, it's invested in designated LSTs (Liquid Staking Tokens). This innovative feature provides users with additional flexibility and potential for enhanced returns. **AcidDAO and parallaxfin** AcidDAO and parallaxfin allow users to invest in diverse baskets derived from original LSTs, opening up opportunities for different yield strategies. Users can explore various investment options and implement strategies tailored to their preferences within these platforms. These emerging products and protocols built on LST protocols introduce novel objectives and mechanisms distinct from traditional DeFi primitives. **CDP Market Share and Future Outlook** In the landscape of Collateralized Debt Positions (CDPs) for LSTs, Lybra Finance firmly holds its ground with a commanding 88% market share. A CDP refers to a smart contract that enables users to deposit assets as collateral in return for a debt denominated in a stablecoin or other assets. Simply put,  users can deposit crypto and receive a stablecoin with their crypto as collateral. The limited competition currently consists of [Gravita Protocol](https://twitter.com/gravitaprotocol), [Prisma](https://twitter.com/PrismaFi), and Gusher, the latter of which is still awaiting the release of its token. Within the last few days, [Prisma finance](https://twitter.com/PrismaFi) has shared its plans to launch a CDP with the backing of Curve, Convex, Frax, and other battle-tested protocols. CDPs allow even further utility for LSTs and will be an exciting space to watch as these protocols grow in TVL. ## Conclusion Bluechip LSTs in the DeFi space have shown remarkable performance, with notable growth, surges in Total Value Locked (TVL), Netflows, and changes in market share dynamics. Projects such as Lybra Finance, Pendle Finance, and Flashstake have captured user interest and established themselves as leaders in specific niches. As the industry continues to evolve, it will be crucial for these projects to maintain their positions by continually innovating and meeting the changing demands of users within the competitive DeFi landscape. Additionally, it is worth keeping an eye on upcoming LSTFI blue chips like Gusher, Gravita, and others, as it will be interesting to see how these protocols aim to capture market share from the established leaders. ### Sources - [LSDFi 💧 (Lybra Finance, Pendle, Unsheth and More!)](https://dune.com/defimochi/lsdfi-summer) - [Eth2 Liquid Staking 💧🥩](https://dune.com/eliasimos/Eth2-Liquid-Staking) - [Staking Rewards](https://www.stakingrewards.com/?sort=totalValueLocked_DESC) - [Liquid Staking Derivatives - DefiLlama](https://defillama.com/lsd) - [Ethereum Staking 🥩 (Lido, Coinbase, Kraken, Binance, RocketPool, Frax...)](https://dune.com/hildobby/eth2-staking) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Unibot: The Telegram Uniswap Sniper > A bot to buy tokens in seconds all within telegram - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-05-24 - Canonical: https://shoal.xyz/research/writing/unibot-the-telegram-uniswap-sniper/ - Keywords: stablecoins, crypto, DeFi, MEV, security, Ethereum, Research ![](https://shoal.xyz/research/writing/unibot-the-telegram-uniswap-sniper/img/96495133c1f2.jpg) ## We’ve all been there Have you ever found yourself in a situation where you want to make a quick crypto trade on info from Telegram, but you don't have the time or ability to navigate the various interfaces and wallets required to do so? **Unibot has the answer.** We've all been there before. The telegram group Alpha sendooor posts a memecoin, and you are at lunch with friends. What do you do? To-ape or not-to-ape is running through you mind. The urge overtakes you as the last sip of double-shot espresso hits your bloodstream. You remember they made 50 ETH yesterday on a project they posted. And so you decide to open your hot wallet app and throw the last bits of ETH at the project. As you fumble around with your mobile wallet pin and password, a telegram notification at the top of your phone says the token is already up 100%. With sweat dripping down your face, you continue. You want to shout at this point, but continue to pull up the Dextools pool link into your mobile wallet browser. The pressure is increasing in tandem with the price. Finally, you ape, and the shiller posts "I hope you are out" in the channel. Rugged again (a rug is when the founders dump the project). If you have not been in this situation, you are likely among the intelligent group, but let this serve as a gateway to becoming a crypto degen. ## Unibot This is where [Unibot](https://twitter.com/TeamUnibot) comes in. Users can quickly paste a contact pair in the Telegram bot channel and quickly buy and sell tokens directly from their Telegram hot wallet. This solves a problem many traders face on Telegram - someone sends a DEX pool link, and you need to take action on the post quickly. A large part of trading is systematic, but it can be hard to stick to a system on the move or when things happen quickly. Unibot streamlines the process and allows for quick and easy trades. For example, the following is a pair for USDC/USDT: **Pair contract:** [0x7858e59e0c01ea06df3af3d20ac7b0003275d4bf](https://www.dextools.io/app/en/ether/pair-explorer/0x7858e59e0c01ea06df3af3d20ac7b0003275d4bf) **Platform:**Uniswap v3 **Assets:** - USDC: 0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48 - USDT: 0xdac17f958d2ee523a2206206994597c13d831ec7 Optimizing for speed, Unibot quickly purchases tokens using token pool contracts. A pool contract is a unique identifier for a certain trading pair on a decentralized exchange (DEX), such as Uniswap v3. With Unibot, users can specify the amount of ETH they would like to spend and make a trade in just a few seconds. The bot also employs several features that allow more advanced traders to quickly purchase tokens, such as Multi-wallet swaps, Smart Method Sniper, Mirror Sniper, and even PnL analysis, which includes gas in the calculation. Currently, Unibot supports Uniswap v2, and v3 trading pairs. Keep in mind there is a fee of 0.5% to 1.5% per swap or snipe, which varies based on the feature and demand. ![](https://shoal.xyz/research/writing/unibot-the-telegram-uniswap-sniper/img/5a487bcf3a1b.jpg) ### Multi-wallet swaps Multi-wallet swaps enable users to use multiple wallets to purchase tokens. Users can select between three wallets in the interface to conduct trades. Multi-wallet swaps give advanced users a more extensive toolkit for organizing token-purchasing strategies. ![](https://shoal.xyz/research/writing/unibot-the-telegram-uniswap-sniper/img/68ad3620d97a.png) ### Smart Method Sniper The Smart Method Sniper enables trading new tokens as they are launched. This can be achieved by entering the token contract and using their ERC-20 launch scanner to import the token for sniping with a single button click. The Unibot token scanner is a powerful tool that monitors ERC-20 tokens deployed on Ethereum. The bot can then move those tokens into the queue to be purchased as soon as the contract owners make the tokens available for purchase. ![](https://shoal.xyz/research/writing/unibot-the-telegram-uniswap-sniper/img/c9075cd430f0.png) ### Mirror Sniper The Mirror Sniper allows users to front-run buys of other traders. Users can create a list of trader wallets they wish to copy trade. The Mirror sniper will monitor the wallet's activity and then copy and trade the wallet. The bot will automatically front-run the transaction submitted by the wallet-monitored wallet. Unibot solves the problem that many traders face on Telegram. It takes time to take action on news or suggestions efficiently, which leads to paralysis. Pro traders typically use systematic approaches, but it can be hard to stick to a system on the move or when things happen very quickly. Unibot streamlines the process and allows quick and easy trades based on predetermined criteria. The only input could be as little as the pair contract or a click of a button from the Unibot token scanner. ### $UNIBOT Token Unibots token, $UNIBOT, provides benefits such as reduced fees and faster transaction speeds. Transactions for non-holders of the token are sent using four private nodes simultaneously, while transactions for token holders are processed using seven private nodes for even faster speeds. The UNIBOT token also has an automatic burn of 0.2% of the token supply per hour and a 5% tax on transactions to enhance the overall experience for token holders. Creating an account is extremely simple and doesn't require registration since it is tied to the Telegram account. The account then creates three wallets that can be funded, and the process can be achieved all in other a few seconds or even faster as the user gets better with the interface. The bot also allows for fast multi-wallet swaps and PnL analysis that includes gas in the calculation. This way, traders can understand where they are without leaving the telegram app. ### Risks While Unibot offers an intriguing solution for rapid crypto trading on Telegram, it is important to consider potential risks associated with this new approach. Firstly, the project's capacity to access tokens from the wallets it generates could potentially be exploited, leading to unauthorized transactions. The automatic access to user funds places a **large amount of trust in the security measures implemented by Unibot**. If these are not robust enough, users might face substantial financial loss. Users should assume funds loaded on Unibot could be lost at any moment. Moreover, the process of handling private keys within the Telegram bot raises concerns about data security. Given the nature of Telegram as a messaging platform, these private keys might be exposed to potential hackers or third-party software, risking the integrity and safety of user wallets. Even though Telegram uses encryption, this does not necessarily ensure that data is completely protected from all possible threats. Consequently, the exposure of private keys on such a platform could provide an entry point for malicious actors to access users' funds. **It is, therefore, critical that potential users understand these risks before engaging with Unibot for their crypto trading needs.** ### Fin Unibot is the solution for quick crypto trades on Telegram. It's easy to use, efficient, and benefits its users. Try it out for yourself and see how it can improve your trading experience. **Sources** - [https://unibot.app/](https://unibot.app/) - [https://twitter.com/TeamUnibot](https://twitter.com/TeamUnibot) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Trade Idea: Metaverse Resurgence > A resurgence in the Metaverse narrative with the impending launch of Apple's AR/VR technology - Publisher: Shoal Research (https://shoal.xyz) - Category: Infrastructure - Published: 2023-05-18 - Canonical: https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/ - Keywords: crypto, liquid staking, gaming, Infrastructure ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/99e7c0ebabab.jpg) ### Intro **You thought the Metaverse was dead?** Whether or not you plan to drink virtual coffee every morning, the Metaverse heart is still beating. Rumors circulating around Apple's AR/VR headset, we might see a resurgence in the Metaverse narrative. In case you aren't up to speed in the Web2 space, Apple is expected to release a mixed reality headset later this year, with rumors suggesting it may be revealed at Worldwide Developers Conference (WWDC) 2023 in June. Designed to be a precursor to Apple Glass and the first real Apple product in the augmented reality space, the headset is expected to be like a typical VR headset. In addition, it features several exterior cameras and sensors that allow body tracking and incorporate real-world environments in a virtual space. ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/b1df504b7b48.jpg) Remember back in the bullrun of 2020 and 2021, when the Metaverse narrative was brewing, and Meta served as the catalyst driving retail, institutions, and funds to go all into the Metaverse tokens. You can see how Web2 product offerings can influence crypto investors. Fast forward to 2023, new developments in AR/VR products could propel the Metaverse narrative back to the forefront. ### Narratives Narratives are one of the most significant drivers in the flow of capital. **"Crypto narratives" are the overarching stories or themes that guide or inspire the development, adoption, and valuation of cryptocurrencies and blockchain technologies.** These narratives often provide a conceptual framework for understanding what a particular cryptocurrency or blockchain project is trying to achieve and why it might be valuable or important. They are often used to persuade and attract investors, users, and developers. Traders, retail, and institutions either purposefully or inadvertently participate in perpetuating these narratives. In the past few months, we have seen several narratives emerge with correlating price action, including Liquid Staking tokens, AI and Crypto, Shanghai Unlock, and now more recently, Meme digital assets like PEPE, and Milady. Although it's rumored Apple has [purposefully avoided labeling](https://www.tomsguide.com/news/apples-mixed-reality-headset-rumored-to-shun-the-metaverse-heres-why) their AR/VR products as Metaverse tools, crypto markets still remain irrational: speculators still will likely interpret this news event as a Metaverse catalyst. To crypto speculators' defense, "If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck." most people would bucket AR/VR in the Metaverse vertical. ### Metaverse Explosion in 2021 Let's go back in history a little. In 2021, Facebook's CEO Mark Zuckerberg catalyzed a significant shift in the Metaverse crypto narrative with the company's rebranding to Meta. This new brand, encompassing all of Facebook's various apps and technologies, aims to realize the Metaverse, a digital universe transcending current online social experiences into an interactive three-dimensional realm. This bold move sparked a significant boom in the Metaverse narrative, which claims we will live in an increasingly virtual world where we might play virtual chess on Friday mornings with coworkers or attend work meetings from Mars. The Metaverse, at the intersection of gaming and daily lifestyle, provided a fertile ground for Metaverse tokens like GALA, SAND, MANA, and AXS, which emerged as some of the top-performing tokens in 2021. ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/d446a36390f4.jpg) This surge can be attributed to a perfect storm created by the combination of the crypto bull run of 2020 and the proliferating Metaverse narrative, both significantly stimulated by Meta's ambitious vision. ### Metaverse Resurgence 2023 More recently, the gaming and Metaverse narratives have become more separate; not all Metaverses are games, and not all games are Metaverses. However, in the eyes of traders and investors, these groups might as well still be joined at the hip. According to a [report by Bloomberg](https://www.bloomberg.com/news/newsletters/2023-04-23/apple-s-ar-vr-headset-plans-ipad-apps-fitness-sports-viewing-gaming-music-lgtgopgx), the upcoming AR/VR products will be capable of running thousands of iPad applications, including games. This development is certainly of interest, particularly given the recent approval of Axie Infinity's launch on the App Store. ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/36875c904f33.jpg) These events are indicative of a broader trend of increased interest in the Metaverse space. In light of this, tokens such as AXIE, MANA, and RDNR are already generating buzz on[Lunar Crush](https://lunarcrush.com/), a social sentiment platform. ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/2849d632dfb1.jpg) As the Metaverse continues to gain momentum, it will be interesting to see how the following non-exhaustive list of relevant tokens evolves over the coming months. We will closely monitor this space and keep our readers updated on noteworthy developments. ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/3197c29ae689.png) ### Fin Though the Metaverse has taken a back seat to newer buzzwords like AI and liquid staking tokens recently, current trends suggest a potential ripe opportunity for the Metaverse narrative to regain prominence in the coming months. **Will the Metaverse be the next major Narrative?** **Only time will tell.** ![](https://shoal.xyz/research/writing/trade-idea-metaverse-resurgence/img/0c90f55a5215.gif) ### Sources - [Apple VR/AR headset — everything we know so far](https://www.tomsguide.com/news/apple-vr-and-mixed-reality-headset-release-date-price-specs-and-leaks) - [Apple’s mixed reality headset rumored to shun the Metaverse — here’s why](https://www.tomsguide.com/news/apples-mixed-reality-headset-rumored-to-shun-the-metaverse-heres-why) - [Apple's AR/VR 'Reality Pro' Headset](https://www.macrumors.com/roundup/ar-vr/) - [The Facebook Company Is Now Meta](https://about.fb.com/news/2021/10/facebook-company-is-now-meta/) - [Metaverse tokens storm the top 10 list of best-performing cryptocurrencies in 2021](https://markets.businessinsider.com/news/currencies/best-performing-cryptocurrencies-metaverse-tokens-of-the-year-2021-12) - [Apple's VR headset will reportedly run hundreds of thousands of iPad apps](https://www.cnbc.com/2023/04/24/apple-vr-headset-will-run-hundreds-of-thousands-of-ipad-apps-report.html) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Poolshark: LP limit orders on Arbitrum > The directional liquidity AMM enabling on chain limit orders - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-05-17 - Canonical: https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/ - Keywords: stablecoins, crypto, DeFi, market making, Ethereum ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/3287209db67f.jpg) > ***Shoal Research Contributors**: **[Cookieflyer1,](https://twitter.com/cookieflyer1) [TheAttentionscape](https://twitter.com/Attentionscapes)*** ### Intro For those deeply involved in crypto, you know that "*x * y = k*" is the Constant Product Formula that changed the landscape of DeFi with the advent of the Automated Market Maker (AMM). Decentralized Exchanges (DEX) like Uniswap allow users to swap ERC-20s without a centralized counterparty. DEX volume in March 2023 was among the highest recorded since 2022, [exceeding many larger exchanges](https://www.theblock.co/post/224490/uniswap-volume-coinbase-best-month) in total volume for the month. AMMs have also been a recent hot topic given the buzz around Uniswap V3's business license expiring just a few days ago, giving protocols the chance to harness its previously restricted IP. However, more innovative projects like Poolshark aim to expand the AMM landscape by developing novel DeFi primitives. Poolshark is doing just this, with the introduction of their cover and price liquidity pools launching this month on Arbitrum. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/8e54679abc37.jpg) ### Poolshark Poolshark is a noncustodial automated market maker (AMM). Unlike most AMMs which are bidirectional in nature, Poolshark allows users to provide directional liquidity. Directional liquidity providers (traders) can choose to specify which direction to provide liquidity on an asset pair by either accumulating or releasing assets into the market. Maximizing Liquidity Provider (LP) transaction fees is achievable through Bidirectional pools as they gather fees for buying and selling the desired asset. Nonetheless, Bidirectional AMMs do have their shortcomings. **Poolshark employs Price Liquidity and Cover Liquidity pools to address these issues, adding more tools for LPs to mirror trading strategies leveraged in traditional markets, such as limit orders, hedging, and dollar cost averaging (DCA).** ## Bidirectional vs. Directional Liquidity Poolshark aims to solve one of the core issues, [impermanent loss (IL)](https://blockworks.co/news/the-investors-guide-to-navigating-impermanent-loss), when providing liquidity. Characterizing impermanent loss involves considering the missed opportunity cost of potential value when LPing assets versus holding them outright. Impermanent loss is driven by deviations in price of the original supplied liquidity. DeFi also allows for asset pairs with the potential for negative covariance, meaning pooled assets can trade in opposite directions away from each other, possibly exacerbating IL. Additionally, due to AMM mechanics, trading into one asset can cause the paired asset to lose value unless it has a stable peg or inherent value that attracts external arbitrageurs since pooled assets are priced in part by the liquidity on the platform. But don’t fret, the rainbow is on the other side of the storm. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/586c7699415b.jpg) With directional liquidity provisioning, Liquidity Provider's (LPs) liquidity will fill similarly to a limit order. Some core benefits of directional liquidity include choosing the trading direction, protection against unwanted price movements, and the ability to undercut the market price. Undercutting the market involves setting the lower bound of the price range below the market price, offering a more competitive rate. This approach, coupled with order aggregation, enables faster selling compared to others in the market. As a typical liquidity provider (LP) on a bidirectional AMM, undercutting the market price is challenging due to its demand-driven nature. However, lower bound directional liquidity attracts volume to your position before other bidirectional LPs, ensuring a quicker trade execution. Undercutting is particularly attractive to market makers and swing traders. Since LPs cannot be entirely certain of full fulfillment until they retrieve their position, directional LPing guarantees that if the position is filled, it won't unfill since liquidity cannot trade back in the opposite direction. This situation would be most impactful for very large traders who find opportunities to incur fees that outperform the losses on lower pricing. **Simply put, traders can provide liquidity at a cheaper price to make sure they are filled early and can remain filled prior to retrieving liquidity.** In addition, LPs do not have to manually close their range order from off-chain to lock in a position state, as is the case with mean-reversion AMMs (Uniswap, Curve, etc.) The directional range-bound liquidity allows for range-specific orders. Let's take Alice, for example, who would like to accumulate ETH between $1500 and $1800. Alice provides liquidity in one direction with USDC and ETH. With Poolshark, Alice can specify to only allow for the intake of ETH in exchange for USDC at predetermined prices. In this case, Alice can still earn fees while providing liquidity. Thus dollar cost averaging into USDC (DCA) over time while ETH is between the $1500 - $1800 price point. - **Bidirectional Liquidity:** The pool takes in one or both assets and trades in both directions. - **Directional Liquidity:** The pool takes in one asset in the pair and trades in one direction The figure below shows how most AMMs provide bidirectional liquidity. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/4063abf9d569.gif) The figure below shows directional range bound liquidity providing. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/984af70b5d41.jpg) ### Cover Liquidity Pools "Cover liquidity pools" **have two distinct use cases, average into a position and hedging against impermanent loss by gradually** unlocking liquidity as the price moves against the asset the LP provided. Cover liquidity pools are a unique type of pool that functions opposite to traditional AMM pool positions. Instead of increasing the amount held of the asset decreasing in price, the cover pool will increase the amount held of the asset by automatically creating miniature Dutch auctions to sell back assets actively. Cover liquidity pools operate like an LP hedging tool for large trades to enter or exit in a specific range. Covering IL is as easy as providing cover liquidity in the same range as the original LP position (in Uniswap v3). [For example](https://docs.poolsharks.io/overview/cover-pools/), a user might have an ETH/ DAI LP position open on uniswap v3 with an **upper bound limit**of $5000 and a **lower bound** **limit** of $1000. With the price of ETH near the middle at $3000, an LP can set up a cover liquidity position as a hedge for the same range to limit IL. Cover LPs unlock as the time-weighted average price (TWAP) moves in a particular direction. The Cover liquidity pool employs "TWAP oracles" (Time-Weighted Average Price oracles) to determine the optimal time for unlocking liquidity (i.e., the money invested by users) for trading with the other asset in the pool. In essence, the TWAP oracle monitors the investment's price over a set duration and leverages this data to determine the ideal time to unlock liquidity. TWAPs are commonly used in financial markets to reduce the price impact of large trades.To elaborate on the previous example, consider DAI and ETH. If the ETH/DAI price rises, the cover liquidity pool will release some ETH to be bought in reaction to changes in the range pool price (Δ). Conversely, if the ETH/DAI price drops, the cover liquidity pool will hold on to your funds until the price rebounds. While this may seem counterintuitive, it provides two distinct advantages: - ***Averaging into a Position*** - ***Hedging Impermanent Loss*** ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/66c2e94db8bd.jpg) **Since LPs can use cover liquidity pools to average into a position or hedge against impermanent loss, they can maintain greater capital efficiency.** The Gradual Dutch Auction (GDA) mechanism determines the price of the unlocked liquidity and ensures competitiveness with the current market rate. Moreover, the cover liquidity pool aims to protect LPs from losses if prices go down and help them book returns if the prices increase. LPs can trade their stable coins for another asset using the cover liquidity pool without worrying about price volatility, making it an excellent option. ### Price Liquidity Pools *Note: Price Liquidity pools are now Limit Pools.* Traders want to be able to set a limit on the price they are willing to sell or buy your asset for, which is possible through traditional limit orders. However, with a bidirectional range AMM system, your range LP position can be reversed since it always allows for trades on both sides of the pair.**In price liquidity positions, LPs specify the desired range for order fulfillment, preventing unfilled orders as prices shift. This approach is comparable to an on-chain limit order.** A lower and upper price tick means, "I'm willing to sell my asset between this range with a minimum/maximum price." ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/2951cd21d290.jpg) Your liquidity will be accessed when the pool reaches that range, and trading will begin. In price pools, since you cannot reference the current price to see how much your position has been filled, you must track your claim on the liquidity pool using a Claim tick. Every time your price liquidity fully trades across a price tick (a function of the fee tier), the claim tick is moved to the new tick and serves as a new mark showing how much of your liquidity has been utilized between the lower or upper (depends on the direction) price tick and the current location of the claim tick. The "Claim Tick" is also used for gas efficiency since all the values required to claim a position are on a single tick. In bidirectional range AMMs, liquidity providers typically either withdraw their position once it reaches the desired price as a pseudo-limit order or allow their liquidity to be traded within the range and accumulate fees, unlike traditional limit orders on centralized exchanges. However, price pools offer an innovative solution enabling one-way fills through the Claim Tick system. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/f45a57bdf3cb.jpg) Using Poolshark, liquidity providers can create price liquidity positions to benefit from price priority when undercutting the current price, meaning they can position to get filled at a certain price under the market price. Additionally, Claim Ticks only move in one direction, meaning trades are executed at predetermined prices and only execute in one direction. This helps LPs avoid unexpected losses due to price fluctuations. By creating price liquidity positions, LPs can have predetermined price-priority execution avoiding the risk that price movements impose on bidirectional liquidity positions. Overall, price liquidity pools create a more secure and predictable environment for decentralized trading and add limit orders to LPs toolboxes. ### Range Liquidity Pools Range Pools, which resemble the bidirectional liquidity of mean-reversion AMMs, allow liquidity providers (LPs) to range-bound their liquidity, increasing the available liquidity near the current market price and enhancing capital efficiency. Range Pools support the ERC-1155 standard in order to allow for fungible positions and shared auto compounding. This can result in increased trading fees accrued for stable pairs. However, the impact of price divergence is more significant for range-bound liquidity as opposed to full-range liquidity, and impermanent loss mitigation is achieved by LPing into Cover Pools. ![](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/1a243132813c.jpg) ## Protocol Feedback The Poolshark team is diligently advancing the field of AMMs, and we appreciate their engagement with us and their efforts in innovating in the DEX space. After discussing with the team and thoroughly examining the documentation, we identified several areas where we suggested improvements: - **Refining Product Suite Narrative** - **Cover Pool Product Improvements**Inability to DCA - **Price Pool Product Improvements**Refinement of "Undercutting the Market"Refining Price Pools Use Case and Narrative ### Refining Product Suite Narrative Poolshark should adopt more accessible and memorable branding for its product suite, such as Tidepools. Tidepools would function as a toolkit for liquidity providers (LPs) to manage their positions efficiently. On the buyer side, users would encounter a traditional order book. Rather than focusing on the concept of capital efficiency, which can be challenging to understand, Poolshark can emphasize its ability (if implemented correctly) to create advanced and gradual dollar-cost averaging (DCA) strategies for LPs. Similarly, for exiting capital, Poolshark can emphasize gradually taking profit within a range rather than a swift exit at an exact price. To ensure users understand the toolkit, simple language should clarify the offering. An unclear narrative can challenge a project's fundraising ability, obstructing investors' understanding of its potential impact and value proposition. Defining and communicating a clear vision is essential for attracting investments and ensuring project success. The following table offers a concise breakdown of this approach. ### Cover Pool Product Improvements Inability to DCA Cover pools primarily address the Impermanent Loss associated with an LP position. The provided examples confirm this, and the excerpt below from the product documentation clarifies that a cover pool cannot be used to "buy the dip." ![Poolshark Docs](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/f8fb2a9fe508.png) The term "Dollar Cost Averaging" (DCA) refers to purchasing assets over specific time intervals, which is advantageous since prices will likely fluctuate, and the average acquisition cost may be better than investing all at once. This approach focuses less on timing the market and more on the Time-Weighted Average Price (TWAP) over time. Cover pools do not release liquidity at scheduled intervals. Instead, they release liquidity when the TWAP indicates sufficient evidence that the "true price" or "stable price over time" has reached a level where the LP provider would be concerned about Impermanent Loss. This occurs when the price of ETH has caused them to lose ownership and exposure to ETH in the Range Pool or V3 pool in which they are participating. Therefore, the cover pool does not offer a time-based DCA option, which should be made clear when discussing the benefits of the cover pool. ![Poolshark Whitepaper](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/0d0c8da3da3d.jpg) ### Price Pool Product Improvements Refinement of “Undercutting the Market” Poolshark shows undercutting the market as a benefit of using the Cover liquidity pools, which we cover in the Bidirectional vs. Directional Liquidity section. > *Price“ Pools therefore allow users to undercut the current market price and receive priority for doing so. In offloading a large position before a large market move, it would be ideal to slightly undercut the market price.” - [Price Pools](https://docs.poolsharks.io/introduction/price-pools/)* The example below describes someone willing to sell **Below The Current Price,**which is unusual.The only scenario in which you are ready to do this is if selling via a swap will cost too much due to fees and slippage. **If:** ``` Fees Paid + Slippage >= Current Price - Lower Bound(of the range selected)+ Fees Earned ``` **Then:** Providing a Price Pool LP to sell your position is profitable because you earn the fees instead of paying them and avoid incurring large slippage. The team verified that the below use case is unrealistic for ETH in particular and that a more accurate example would be something like Alice being willing to sell from 1993-2000 since ETH slippage is very low for even large trades. The primary gain is from Fees Earned and maybe a tiny amount of slippage (0.3% of 2000 in fees + some tiny amount of slippage from price impact). ![Poolshark Docs](https://shoal.xyz/research/writing/poolshark-lp-limit-orders-on-arbitrum/img/d88bb533156c.jpg) The methodology given is that LPs might want to price their assets lower than market price to get filled quickly. Our assessment found this use case only realistic for large traders who see opportunities to incur fees that outperform the losses on lower pricing. Poolshark could identify these opportunities and suggest pricing liquidity accordingly for LPs. Refining Price Pools Use Case and Narrative Price pools need to provide a cleaner and clearer use case for most traders since traders want the ability to place limit orders. A straightforward narrative for price pools would allow users to set limit orders in either direction. **Limit orders for a buyer serve 2 functions:** 1. Ensure that a market order doesn't lead to large amounts of slippage either along an AMM curve or through a CEX order book. 2. Allow the bidder to submit orders to "buy the dip," which enables the buyer to acquire the asset whenever the price target they have is available from the seller or liquidity providers. Price pools to enter a position are about saving on fees (collecting them as an LP instead of paying them on a swap) and ensuring that your entry price is capped at the limit you desire. From the seller's perspective, limit orders through price pools enable either "take profit targets" or exit a position at a minimum price to avoid losses due to slippage and fees. As a seller, you might be willing to provide a liquidity pool (LP) price pool position below the current market, as mentioned earlier, if the fees you earn and the slippage you avoid are worth more than the amount you lose by selling below the current market price on an Automated Market Maker (AMM) swap. When creating a position that offers a better price for execution to any buyer on the swap, the system prioritizes the respective range. This enables the seller to exit their position as desired until the full amount of provided liquidity is exhausted and the entire position is sold. *The Poolshark team has since updated some of the language and feedback provided*. ### Fin The Automated Market Maker model has transformed the DeFi landscape. While most AMMs offer bidirectional liquidity, Poolshark has introduced directional liquidity, which helps to address impermanent loss, one-way liquidity provision, and offers supplier-driven pricing. Through the range, cover, and price liquidity pool mechanisms, liquidity providers are able to express their directional view of the market properly. The introduction of these novel DeFi primitives has the potential to expand the AMM landscape and create a more secure and predictable environment for decentralized trading. Poolshark's soon launch of cover pool and price liquidity pools on Arbitrum positions the platform to push the boundaries of DeFi and expand decentralized trading tools for LPs and traders. ## Sources - [Zach, Poolsharks Labs](https://twitter.com/0xzachamm) - [Cookieflyer1, Shoal Contributor](https://twitter.com/cookieflyer1) - [TheAttentionscape, Shoal Contributor](https://twitter.com/Attentionscapes) - [Introducing Uniswap V3](https://blog.uniswap.org/uniswap-v3) - [Provide Liquidity on Uniswap V3](https://support.uniswap.org/hc/en-us/articles/7423450471437-Provide-Liquidity-on-Uniswap-V3) - [Poolshark Whitepaper](https://docs.poolsharks.io/whitepaper/poolshark.pdf) - [Poolshark](https://www.poolshark.fi/) - [Gradual Dutch Auctions - Paradigm](https://www.paradigm.xyz/2022/04/gda) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Behind the Numbers: Investigating the Largest DEX Volume Days > The Biggest DEX Volume Spikes and what caused them - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-04-18 - Canonical: https://shoal.xyz/research/writing/behind-the-numbers-investigating/ - Keywords: stablecoins, crypto, DeFi, security, Ethereum, Bitcoin, Research ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/cd542084aa88.jpg) ## Preface Decentralized exchanges (DEX) are the heart of crypto ethos. They allow users to facilitate trading among market participants without needing to know the counterparty or intermediaries in a trustless environment. The implosion of centralized exchanges (CEXs) like FTX, Celsius, and Voyager has incentivized users to rely more on-chain products and highly regulated or transparent CEXs. Over the last few weeks there has been a steady incline of DEX activity, with volumes in March 2023 topping 2022 monthly highs. When we look at volumes charted across the daily time interval, we can see large clear spikes in trading activity. You might assume these events are triggered by euphoria and bull market buying. But it’s just the contrary: **the 5 largest DEX volume days have all been on the same days as crypto meltdown events.** ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/2be78b05ea62.jpg) In this paper, we will dig into the largest DEX volume days and uncover the catalyzing events that led to these record-setting days. We can use [DefiLlama’s DEX aggregator](https://defillama.com/dexs)  to uncover the days with the highest volumes, then research specific days to identify the catalyst and narratives that drove these spikes. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/1e7abc50d910.jpg) ## Largest DEX Volume Days Starting from the largest and concluding with the 5th largest DEX volume day, we will examine these events based on the magnitude of the volume changes. This approach enables us to perceive that the order is not a linear, chronological sequence by date but rather by the intensity and influence of the significant events. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/5136e7007225.png) ### 1. USDC Depeg After Banking Scare (Mar 11, 2023) The day following the $USDC Depeg (USD Coin), March 11th, 2023, marked the largest DEX volume day recorded to date, leaving both institutional and retail players both scrambling to hedge their portfolios as USDC moved further down from $1. Bank-run concerns surrounding banks that held custody of $USDC caused so much concern that centralized entities intervened, Circle, SVB, and the government, to restore market confidence. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/e6a85a87d140.jpg) In addition, large actors like Crypto hedge funds and VCs, were swapping between stablecoins, looking to profit from 1:1 USDC redemptions. While some investors were frightened away, others tried to profit on the arbitrage opportunity. Many institutions were [swapping between stablecoins and redeeming](https://twitter.com/lookonchain/status/1634553237155217409?s=20) USDC for fiat currency. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/9e44abf6a9b6.jpg) ### 2. 50% Drawdown of BTC (May 19th, 2021) During the last bull run, the second largest DEX volume day occurred on May 19th, 2021, in tandem with a [steep 50% drop in BTC's value, from $60,000](https://cointelegraph.com/news/bear-market-analyst-weighs-in-after-bitcoin-drops-50-from-its-65k-all-time-high) in just a few days. On this day alone, BTC experienced a 30% drawdown, which led to DEX volumes to spike over $18B. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/1f6fd88b97e2.jpg) ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/b0e52e4e3ef8.jpg) ### 3. Collapse of Terra Luna (May 11, 2022) Then, the collapse of Terra Luna, one of the leading blockchains at the time, triggered the third largest decentralized exchange (DEX) volume day in history, with over $15 billion in trading volume for the day. Terra Luna's native stablecoin, UST, played a significant role in this event. Before the collapse, UST had a thriving market capitalization (market cap), with tens of billions of dollars supporting the Terra ecosystem. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/e9f8989e6fbb.png) Within a matter of days, a substantial portion of UST's market cap was wiped out, causing a ripple effect throughout the cryptocurrency market. This rapid evisceration of UST's market cap led to further contagion among over-leveraged large institutions, such as 3AC. As these institutions scrambled to mitigate their losses, the wider cryptocurrency market faced increasing instability and uncertainty. ### 4. Start of Bear Market in 2022 (Dec 4, 2021) To fully understand these financial events, we need to go back in history. The beginning of the bear market in 2022 can be traced back to December 4th, 2021, a day that saw DEX volumes reach their fourth-highest level in history, peaking at $13.5 billion. Surge in trading activity coincided with a[significant 22% single-day drop](https://www.reuters.com/technology/bitcoin-extends-downtrend-falls-121-47176-2021-12-04/) in the value of Bitcoin (BTC), a precursor to the start of the bear market decline. As market participants witnessed the sharp decline in Bitcoin's value, many started to exit their positions to minimize potential losses. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/2531c351b053.jpg) The BTC decline marked the start of a broader bear market decline, as the cryptocurrency market shifted from a period of bullish growth and optimism to one characterized by pessimism and sharp drops in asset values. Market participants' rush to exit their positions intensified the downward pressure on cryptocurrency prices, further exacerbating the bearish sentiment and price moves. In hindsight, it was clear many were heading for the door. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/ca351400467e.jpg) ### 5. FTX Collapse (Nov 10, 2022) As the bear market continued to strangle the crypto community, the FTX collapse on November 10, 2022, marked a significant event in crypto history, triggering a cascade of on-chain selling reverberating throughout the market. As a major trading platform, FTX's downfall profoundly impacted investor sentiment and trading activity. In the aftermath of the collapse, DEX volumes surged, reaching over $12 billion on November 12, 2022. Market participants seeking to mitigate their losses and exit their positions in the face of the FTX collapse drove this heightened trading activity. You can see here the interconnectivity of the Centralized Exchange (CEX) markets and the potential for major events to have far-reaching consequences on-chain. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/5632016278e2.jpg) ### Why does DEX volume spike on these days? The combination of on-chain [liquidations](https://www.investopedia.com/terms/l/liquidation.asp#:~:text=Liquidation%20in%20finance%20and%20economics,obligations%20when%20they%20are%20due.), selling, and traders fleeing into stablecoins can cause a tremendous spike in trading volume. These spikes in volume are often accompanied by widespread panic among users, who seek the stability of stable pairs on-chain. Interestingly, these spikes in volume appear to loosely correlate with the flows of "smart money," or top traders identified by [Nansen](https://nansen.ai/), a leading provider of on-chain data and analytics for digital assets. This suggests that larger, more experienced investors' actions may contribute to the overall market trends during these periods of volatility. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/a7a6619678b5.jpg) ### Data Outliers Many of our readers might be wondering, "What about March 31, 2021?" given the volume charts show a significant spike early in the DEX volume data. At the time, Uniswap dominated DEX trading volume, but there were concerns over the accuracy of the reported $13.8 billion due to a discrepancy in how the volume was recorded. A few DeFi applications found a way to exploit Uniswap's volume stats using a rebasing mechanism. Crypto media outlets like [Decrypt](https://decrypt.co/63280/uniswap-trading-volume-exploded-7-billion-heres-why) also reported volume spikes, with the culprits likely being token projects looking to maliciously forge trading volumes. ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/18a4a0967265.jpg) Hayden Adams, the founder of Uniswap, stated that [they will make efforts](https://twitter.com/haydenzadams/status/1376579600902455297?s=20) to clean up the data around the event date to ensure a more accurate representation of trading, as it is highly likely that this data does not represent realistic trading volume. ## Fin Nothing gets money moving on-chain more than fear. This explains why the largest DEX volume days are often triggered by significant events in the cryptocurrency market, such as a collapse of a major exchange or a sharp drop in the value of Bitcoin. These events cause widespread panic, leading users to flee to stablecoins and other assets, resulting in spikes in DEX trading activity. However, despite the volatility in the cryptocurrency market, the popularity of decentralized exchanges continues to grow as users seek to facilitate trading among market participants in a trustless environment. Within the last few weeks, Binance and Coinbase became targets of regulatory action. Since then, there has been little price impact on $BTC and $ETH in the short term. The crypto space is exceptionally resilient, and although these significant events have taken place, the space continues to grow. **Hopefully, this small dose of fresh hopium lets us sleep at night.** ![](https://shoal.xyz/research/writing/behind-the-numbers-investigating/img/ed9e2524e414.jpg) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # RYSK Finance: Dynamically Hedged Real Yield > Uncorrelated returns leveraging RYSK low delta options vault - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-03-21 - Canonical: https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/ - Keywords: stablecoins, crypto, DeFi, market making, yield, security, infrastructure, Ethereum, Bitcoin ![](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/51c71b46c1bc.jpg) Traditional finance experts may be surprised to learn that many DeFi (decentralized finance) protocols are taking concepts from traditional finance and replicating them in a decentralized context. By optimizing systems for users to access them in a permissionless manner, DeFi developers have created unique two-sided markets that serve the same purpose as traditional markets but with better incentive mechanisms. ## Intro, RYSK Finance One such DeFi protocol is RYSK Finance, an innovative options trading platform that allows traders to buy or sell options using their Dynamic Hedging Vault (DHV). The DHV is a novel liquidity vault that automatically rebalances itself towards delta neutral, which means that it retains low delta (directional risk exposure) ensuring price movements have little effect on the vault. Delta is a crucial risk measurement used by traders to price options accurately. By maintaining a low delta, RYSK Finance ensures that price changes of the underlying assets do not affect the vault’s exposure. The options contained within the DHV are meticulously managed to target a delta-neutral position. Imagine putting $100 USDC into a pot that provides liquidity for traders. As these traders engage in buying or selling options, the pool simultaneously executes the buying and selling of other DeFi assets in the open market, aiming to preserve the deposit value at $100. This protects liquidity providers' USDC deposits against market price fluctuations. Concurrently, the DHV sets different prices for buying and selling the same option, creating a price gap called a spread. Liquidity providers collect this spread as payment. The DHV is optimized to be short volatility (price fluctuations) with a low delta to deal with high crypto volatility. In other words, it is optimized for large price swings. This is an important feature that enables better risk management and helps liquidity providers profit from high crypto implied volatility (expected magnitude of volatility). Under the hood, RYSK derives some core options functionality from battle-tested Opyn Gamma protocol, an options settlement layer. ![Rysk Finance](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/e14a04ae3b41.jpg) ### DHV Real Yield and Uncorrelated Returns In addition to benefiting traders, liquidity providers will also appreciate **RYSK’s uncorrelated returns by receiving fees on spreads (payment) for market making options for traders generating real yield.** **Uncorrelated Returns & Defi Composability** RYSK prioritizes the generation of uncorrelated returns, which refers to the capacity to yield consistent returns irrespective of market conditions. In the context of crypto, the price of Bitcoin going up or down does not affect the constant yield. With uncorrelated returns, investors and LPs can diversify their portfolios. RYSK is a permissionless on-chain protocol, allowing anyone to access this investment vehicle through existing crypto infrastructure such as a Coinbase wallet. This approach not only promotes the availability of decentralized financial tools but also empowers individuals beyond the core team to enhance the protocol's utility through DeFi composability. Composability refers to the ability to take one protocol and build on top of it or expand its utility due to the open-source code. The combination of composability and uncorrelated real yield establishes a fertile environment for the development of innovative financial applications. Real Yield protocols like GMX and Gains Network have attractive tokenomics and incentive mechanisms to ensure liquidity. Instead of relying on token emissions (printing tokens), the protocols harness the core business model of trading derivatives, distributing the fees (payments) generated to LPs and token holders. Similarly, RYSK employs a tokenless model for value accrual. LPs (Liquidity providers) simply need to deposit USDC into the DHV pool for returns. Learn more about Defi real yield in the [GMX: A Real Yield & Defi Primitives Launchpad article](https://www.shoal.gg/i/103755666/what-is-real-yield). ![Token Terminal : 30 day Earnings Leaderboard](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/1853590ab352.jpg) ### RYSK Beyond RYSK finance is currently in its proof of concept stage, RYSK Alpha, which focuses on selling options and hedging. However, there’s more good news for LPs and traders. The anticipated RYSK Beyond upgrade will enable the DHV to both purchase and sell options, leading to better uncorrelated returns. By servicing both sides of the options market, the DHV fundamentally operates as an on-chain, decentralized market-maker. Drawing parallels with its centralized crypto counterparts such as Jump, GSR, Wintermute, and even [SBF’s treacherous Alameda](https://www.nbcnews.com/business/business-news/ftx-co-founder-former-ceo-alameda-research-plead-guilty-fraud-rcna62891). As an automated on-chain counterparty for traders, RYSK will enable a wide range of strike prices and expiry dates for hedging, speculation, or filling arbitrage opportunities. The DHV also targets market neutrality by pricing options cheaply to attract buyers. If the delta moves away too far from 0, the DHV will buy spot, leverage perpetuals, and implement other strategies to maintain low delta. ![Rysk Finance](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/16e742b056db.jpg) The RYSK Beyond DHV is integrated with several other DeFi protocols, including GMX, Rage Trade, Uniswap, and Opyn, with more to come. This integration allows the vault to automatically rebalance itself when traders interact with it, making it a more efficient and effective tool for traders and liquidity providers alike. In its current version the DHV at times does require manual hedging by the team. The team inputs variables into the contract and the contract automatically hedges using different integration tools. > *With GMX, the DHV can trade perps on a highly liquid market without being impacted by slippage.**With Uniswap Range Orders, the DHV can place spot limit orders enabling hedges with a variable time of execution and a fixed price - RYSK Finance* ![Rysk Finance](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/b7784b0fe8d6.jpg) With one-click options strategies traders can buy and soon sell options on the RYSK platform. In addition, RYSK will offer multi-collateral partial collateralization, meaning option writers can use different types of collateral, including USDC and ETH. The options produced by the vault are priced using a few inputs including the [Black-Scholes model](https://www.investopedia.com/terms/b/blackscholes.asp), which is a mathematical options pricing model. ![Rysk Finance](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/47160aade808.jpg) ### Risks Being a part of the Defi ecosystem, Protocols like RYSK finance, introduce a new level of permissionless financial tooling to traders and liquidity providers. However, with this level of freedom comes a degree of risk. As with any financial product, risks are inherent, and it is important to understand them before depositing. **When it comes to RYSK finance, there are two main types of risks:** - **Financial risks:** Possibility that the vault can not maintain a low delta, causing significant losses to liquidity providers. - **Smart contract risks:** Possibility of attacks on the on-chain smart contracts or vulnerabilities in the vault mechanisms. Despite the potential risks, users are still able to operate with confidence, as the RYSK team has taken the necessary precautions to minimize risk through code audit. They have even highlighted these risks in their documentation, which shows the audits from firms like [Dedaub](https://twitter.com/dedaub) and others. ![Rysk Finance](https://shoal.xyz/research/writing/rysk-finance-dynamically-hedged-real/img/c93fa34ab61d.jpg) ## Fin RYSK Finance's Dynamic Hedging Vault (DHV) provides traders and liquidity providers with another tool in their arsenal. Both traders and LPs anticipate the upgrade as it should result in larger LP returns and expanded out-of-the-box trading strategies. Overall, RYSK Finance's DHV is an exciting innovation in the DeFi ecosystem, offering a novel approach to options trading while providing real yields and uncorrelated returns to liquidity providers. **Sources:** - [Rysk Finance](https://www.rysk.finance/) - [RYSK Finance Alpha](http://alpha.rysk.finance) - [Introducing Rysk Beyond](https://blog.rysk.finance/introducing-rysk-beyond-7b254383a2db) - [Rysk is the only free lunch](https://blog.rysk.finance/rysk-is-the-only-free-lunch-e4f832af0026) - [Rysk Alpha Club: Want in?](https://blog.rysk.finance/rysk-alpha-club-want-in-d36fa5ddb49e) - [What is rysk? - Rysk Finance](https://docs.rysk.finance/getting-started/what-is-rysk) - [Making DeFi Options capital efficienter 🤌](https://blog.rysk.finance/making-defi-options-capital-efficienter-rysk-feature-spotlight-1cab665cf7cc) - [Looking under the hood of Rysk’s Dynamic Hedging Vault](https://blog.rysk.finance/looking-under-the-hood-of-rysks-dynamic-hedging-vault-e059e1b87e41) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # The Peking Bull > An intro to the China-led crypto bull pump to start the year - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-02-28 - Canonical: https://shoal.xyz/research/writing/the-peking-bull/ - Keywords: crypto, yield, Research ![](https://shoal.xyz/research/writing/the-peking-bull/img/c649612042af.jpg) ## Intro Capital flows into risk assets often lead from the West, and it's easy to understand why. Governments in the West tend to have looser capital controls than their counterparts in the East, and cash is more accessible. But the onslaught of the crypto bear market of 2022 left a bad taste in the West. Regulators have doubled down on their commitment to pushing more controls around crypto assets. Recently, the SEC has gone after exchanges like Kraken for their yield-generating products. > SEC: “Kraken to Discontinue Unregistered Offer and Sale of Crypto Asset Staking-As-A-Service Program and Pay $30 Million to Settle SEC Charges” - [Frank Chaparro](https://twitter.com/fintechfrank/status/1623779475602423809?s=20) And begun to crack down on crypto pundits like Do Kwon—seemingly promising further action against the likes. While the US has been known to lead the world in innovation often, they’ve seemingly put crypto as a backdrop and gone on the defensive. As the iron curtain closes in the West, web3 builders will be forced to participate from other regions. ### The East Rises Crypto has seen an impressive rise off the winter lows. But with all of the FUD coming out of the West and much of retail still sidelined (or benched after FTX collapse), where are the pumps coming from? One of Crypto Twitter’s proclaimed prophets, Gigantic Rebirth (also known as GCR), had his theories: > I believe China, (and Asia in general) will fuel the next run It will take quite some time to melt Western cynicism towards this space, but the East is ascending and yearning to flex You should be hanging out in WeChat Many future pumps will be on coins none of your circle know - [GCR](https://twitter.com/GCRClassic/status/1612431373851140097?s=20) Innovation always finds a way. Or rather, liquidity always finds a way. Many macro-enthusiasts would attribute the crypto bull run of ‘20 - ‘22 to the US Federal Reserves jet-fueled money printer. With the Fed still tightening monetary policy, where might new liquidity come from? ### Let’s Talk Liquidity China’s central bank has performed its most significant liquidity injection this year. [With China officially reopening](https://www.npr.org/2023/01/08/1147734190/china-has-reopened-its-borders-to-tourists-after-three-years-of-covid-closure) for the first time since covid, the government began to inject the economy with liquidity to support an economic recovery. The government is highly determined to put China back in a solid economic position, even giving out [500,000 free plane tickets to Hong Kong](https://www.smithsonianmag.com/smart-news/hong-kong-to-give-away-half-a-million-plane-tickets-in-bid-to-boost-tourism-180981656/). ![PBOC cash injection - Via @tedtalksmacro](https://shoal.xyz/research/writing/the-peking-bull/img/798f5fbeffc4.jpg) ### Follow the money Sometimes it's just as simple as that: follow the liquidity. Easier said than done. As many are familiar with crypto alpha, it begins in private groups—but even more so in China. Twitter is technically blocked in China (sometimes accessible from a VPN), and these groups exist in WeChat, an app that most Westerners don't have access to. We've already seen the narrative gain traction recently, with several top crypto Twitter accounts sharing "Chinese coin" [watchlists](https://twitter.com/milesdeutscher/status/1626820385445662722?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1626820385445662722%7Ctwgr%5Eefcdf3e24e7d2076b4501b5138160ebe912e8824%7Ctwcon%5Es1_&ref_url=https%3A%2F%2Fwww.notion.so%2FChina-Crypto-Push-bca7d98a7f334dbe8ef1ea7a0ce1d7dc). So please do your best to woe your Eastern friends next time you get dinner and ask them to help you get a WeChat account. ### Global M2 supply growth Let's consider the global M2 supply growth % YoY vs. the crypto market cap. We can see below a strong correlation between the bull run phases of crypto assets and the global money supply. ![](https://shoal.xyz/research/writing/the-peking-bull/img/a1f1a9757b04.jpg) > *“M2* is a measurement of the nation's money supply that estimates all the cash everyone has in hand or short-term bank deposits.” - [investopedia](https://www.investopedia.com/terms/m/m2.asp) In essence, M2 tracks the amount of excess money people have worldwide. Hard to stay away from the “greatest casino on Earth” when you've got a little spare change. ### Conclusion While the US still juggles deciding its acceptance of crypto, last week, [Hong Kong laid out plans to set up a licensing regime](https://www.coindesk.com/policy/2023/02/20/hong-kong-proposes-rules-for-crypto-trading-platforms/) to allow crypto asset trading. Less we do not forget [China seemingly banning crypto in 2021](https://worldcoin.org/articles/china-crypto-ban) as well. So this is a massive leap for the East regarding crypto adoption (or speculation). New liquidity and supportive regulation could be the perfect recipe for a bull run starting in the East. The signals between East and West are clear. --- Interesting Commentary on the China Crypto Push: - [Chinese CT is packed full of alpha damn.](https://twitter.com/yh_0x/status/1626835836477243393?s=46&t=vhcGUcpfy2WNGPAn2lrrug) - [List of all China-related coins on Binance](https://twitter.com/altcryptogems/status/1627730149851426816?s=12&t=y83l85IhkBUQBl1kkdzBWg) - [What chinese twitter is talking about today](https://twitter.com/annngelkek/status/1627872540843724800?s=46&t=-EjykvySUmNcvNhPJ8cjxA) - [I believe China, (and Asia in general) will fuel the next run](https://twitter.com/doomsdart/status/1626971899237367810?s=52&t=Pku44Dtw) - [The China easing narrative is not some imaginary garbage](https://twitter.com/NoodleofBinance/status/1626839763155324929) - [Is Asia Going to Lead the Next Bull Run? - Unchained Crypto](https://unchainedcrypto.com/podcast/is-asia-going-to-lead-the-next-bull-run/) - [Let me tell you the economy of China is 10x and so are their pumps](https://twitter.com/rewkang/status/1627898898449571843?s=12&t=ooK-DK8Z81prD6uS7RvQXg) - [There is a lot of talk out there currently about how bullish China is for crypto.](https://twitter.com/defi_gaz/status/1628886616608763906?s=12&t=ooK-DK8Z81prD6uS7RvQXg) - [China's central bank performed it's single-largest liquidity injection on Friday,](https://twitter.com/tedtalksmacro/status/1627455227006976001) - [On June 1st, 2023, Hong Kong will officially make crypto fully legal for all of its citizens](https://twitter.com/noodleofbinance/status/1625941125487017989?s=12&t=ooK-DK8Z81prD6uS7RvQXg) - [Western and Chinese traders connecting for the first time both on twitter+ in other chats](https://twitter.com/gcrclassic/status/1627439899723931651?s=52&t=zHswt4qs6N9m-hBf8a7P8g) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # GMX: A Real Yield & Defi Primitives Launchpad > Defi composability, real yield, and 35+ protocols leveraging GMX perps protocol - Publisher: Shoal Research (https://shoal.xyz) - Category: DeFi - Published: 2023-02-21 - Canonical: https://shoal.xyz/research/writing/gmx-a-real-yield-and-defi-primitives/ - Keywords: stablecoins, crypto, DeFi, yield, infrastructure, Ethereum, Bitcoin ![](https://shoal.xyz/research/writing/gmx-a-real-yield-and-defi-primitives/img/9d5beb36a181.jpg) ## The Forbidden Yield Crypto has seen 1 million % farming rates, which proved unsustainable. Coupled with the fallout from the FTX, 3AC, Terra Luna, Celcius, and Blockfi collapses, users are now looking toward sustainable "Real Yields." In the past, users quickly piled into 20% CEX (centralized exchange) staking rates without thinking twice. Now, especially in the bear market, Defi users are more skeptical of yield and how it is derived. Institutional digital asset trading firm Genesis' recent bankruptcy is another domino to fall within the yield-bearing sector. Genesis provided one of the largest crypto exchanges in the United States, Gemini, yield for customer deposits in their [Earn program](https://www.gemini.com/en-US/earn). The Earn program allowed users to deposit crypto in return for yields as high as 8% on some stablecoins and other cryptocurrencies. Genesis' bankruptcy caused the loss of customer funds, and in retrospect, the 8% yield on Gemini’s Earn program was very risky. Many protocols have adopted the real yield strategy due to the growing trend of distributing fees to token holders. **In this article, I will explain how GMX works and how savvy developers have harnessed the protocols tokenomics to create new Defi primitives, yield strategies, and integrations for their benefit.** ### What is Real Yield? In traditional finance, real yield is the difference between inflation and interest rates. In Defi, people refer to "real yield" as the yield or profits that token holders derive from shared protocol revenues. Usually, staking (locking tokens with the protocol), the protocols governance token, is required to receive a claim on protocol revenues. ## GMX The native Arbitrum decentralized perpetuals exchange, GMX, leads the charge in total locked value (TVL) and market cap of Arbitrum Dapps. Perpetual are a crypto-native financial tool similar to futures but without a settlement date. Savvy traders can leave their long or short positions open for an extended period in exchange for paying a funding rate to keep the position open. Perpetual exchanges are great for directional trades on assets or hedging positions. GMX allows users to get up to 50x leverage on their trades on a few supported assets, including Bitcoin and Ethereum. ![](https://shoal.xyz/research/writing/gmx-a-real-yield-and-defi-primitives/img/3defc7951217.jpg) ### GMX Tokenomics Incentive mechanisms are the key to Defi and attracting liquidity and capital to protocols. Liquidity is hard to keep within protocols since users will move to the newest shiny thing. High APR rates cause money to rotate between new Dapps and narratives. What started as airdropping and printing tokens to users for specific actions has evolved into more sustainable models of token incentive mechanisms. GMX token design rewards users with protocol fees for providing liquidity by staking tokens with the protocol. GMX employs a two-token economy, $GMX and $GLP, which facilitates value distribution from the protocol. **Most GMX revenues come from a [.01% fee charged](https://gmxio.gitbook.io/gmx/trading) to traders to borrow, open, and close positions.** - **$GMX**$GMX is the governance token for the GMX protocol, which grants voting rights for new proposals. Holders of GMX can also stake (lock in the contract) their tokens for staked GMX, which grants a claim to 30% of all fees charged to traders using the protocol. On both Arbitrum and Avalanche networks, traders can deploy trades, and the networks distribute fees in $ETH on Arbitrum and $AVAX on Avalanche. - **$GLP**The $GLP liquidity token, an index of assets including $ETH, $WBTC, $LINK, $UNI, $USDC, $USDT, and $DAI, is the funding source for profitable trades. Arguably more important, $GLP is the liquidity token for the GMX protocol. To mint GLP and receive rewards, traders can deposit index assets staked for protocol rewards. Rewards are distributed in AVAX or ETH, depending on the network used to mint GLP. Those who stake their $GLP receive 70% of the protocol fees from the chain where GLP was minted. ![](https://shoal.xyz/research/writing/gmx-a-real-yield-and-defi-primitives/img/3fe4a16f133e.jpg) **The House Always Wins** When traders win trades on GMX, the GLP pool is responsible for paying out the winnings, whereas $GLP holders on the chain where GLP was minted receive 70% of the trading fees and liquidations. GLP holders essentially serve as “the house” and provide capital for traders with the idea that most traders lose on trades. Since the launch of the GMX protocol, traders have lost more than $30m trading on the platform(wins + losses). The GLP tokenomics create a positive incentive on both sides of the trade. Liquidity providers expect traders to lose in return for stable yields, and traders have the liquidity to conduct sizable trades. ![](https://shoal.xyz/research/writing/gmx-a-real-yield-and-defi-primitives/img/92095484cb77.jpg) ### GMX composability Other Dapps can utilize the yield-bearing assets and trading protocol of GMX, as it is a permissionless platform. Over 35+ protocols are leveraging GMX in some form, which is possible due to the ability to build on top of GMX, known as "Defi composability" or "Defi legos." Composability is essential in the rapid innovation seen in crypto because one protocol can replicate or expand on other protocols services without building the entire infrastructure from scratch. GMX Composability Usecases 1. **Abracadabra**For example, [Abracadabra Money](https://twitter.com/MIM_Spell) is a leverage and yield farming protocol with GLP vaults. On Abracadabra, users can deposit $GLP into their Auto-compounding vault, which automatically takes the yield earned and puts it back into the protocol. Abracadabra takes a 1% fee for providing this service and has become one of the largest holders of staked GLP. 2. **Rage Trade**[Rage Trade](https://twitter.com/rage_trade) offers delta-neutral vaults for $GLP, which allow users to earn ETH while maintaining a delta-neutral position. Rage Trade executes this strategy by shorting on Aave and Uniswap, suppressing ETH & BTC price exposure. The combination of the shorts and $GLP hedge the underlying assets in the $GLP index so that users do not suffer impermanent losses on $GLP. Impermanent loss is a risk when participating in Defi liquidity pools, where the profit gained in the pool is less than it would be from holding the assets outright. Rage Trade key innovation mostly removes this risk in exchange for slightly lower yields. 3. **STFX**[STFX](https://twitter.com/STFX_IO) offers copy-trading services to users and is built on GMX. Users can join a peer-managed trade vault by depositing USDC, and the vault owner will open a crowdfunded position for the trade strategy. Vault managers earn fees on successful trades, and the entire trading feature is built exclusively on GMX. Although vault managers use the STFX interface, the trades are routed to GMX. ## Fin At first glance, GMX is a perpetual trading protocol, but under the hood, the protocol provides developers tools for creating new Defi primitives and liquidity for external trading services. Protocol services can be optimized and specified for specific users, like how Abaracdabra, Rage Trade, and STFX have leveraged GMX differently. GMXs ecosystem of supporting Dapps proves the value in Defi composability and continues to expand. ### Protocols building on GMX 1. **[Abracadabra](https://twitter.com/MIM_Spell)**: Algo stablecoin protocol with auto-compounding $GLP strategy 2. **[Jones DAO](https://twitter.com/JonesDAO_io)**: Options yield and strategy vaults leveraging $GMX and $GLP 3. **[Plutus DAO](https://twitter.com/PlutusDAO_io)**: Governance token black hole, leveraging $GLP vaults 4. **[GMD Protocol](https://twitter.com/GMDprotocol)**: Smart Vault and Yield, built on GMX 5. **[MugenFinance](https://twitter.com/MugenFinance)**: Real Yield aggregator on LayerZero, leveraging $GLP 6. **[RageTrade](https://twitter.com/rage_trade)**: Yield vault strategy protocol leveraging $GMX and $GLP 7. **[Dopex](https://twitter.com/dopex_io)**: Options Exchange on Arbitrum, with GMX integration 8. **[Umami finance](https://twitter.com/UmamiFinance)**: Delta Neutral vault strategies leveraging $GLP 9. **[STFX](https://twitter.com/STFX_IO)**: Social trading platform built on GMX 10. **[Lyra](https://twitter.com/lyrafinance)**: Optimism native options trading protocol integrated with GMX on Arbitrum 11. **[Buffer Finance](https://twitter.com/Buffer_Finance):** Exotic options trading platform, staking mechanism forked from GMX 12. **[Tender finance](https://twitter.com/tender_fi)**: Borrowing and lending protocol with $GLP and $GMX collateralization 13. **[Rodeo Finance](https://twitter.com/Rodeo_Finance)**: Leveraged yield farming strategies with a $GLP vault 14. **[Perpy Finance](https://twitter.com/PerpyFinance)**: Social trading platform built on GMX 15. **[Vovo Finance](https://twitter.com/VovoFinance):** Yield vaults with $GLP strategies 16. **[Beefy Finance](https://twitter.com/beefy_finance_)**: Multichain yield optimizer with $GLP vaults 17. **[Stabilize Protocol](https://twitter.com/StabilizePro)**: Stablecoin stabilizing protocol leveraging $GLP pools 18. **[Vesta Finance](https://twitter.com/vestafinance)**: Stablecoin protocol on Arbitrum with $GMX and $GLP Vaults 19. **[Nitro Cartel, Arbitrove](https://twitter.com/nitrocartel)**: yield-bearing index and strategy vault using $GLP vaults 20. **[Moremoney](https://twitter.com/moremoneyfi?s=21&t=RxtClpqrEa5kofB5jwTu_A)**: Lending and borrowing protocol on Avalanche, with $GLP Vaults 21. **[Demex](https://twitter.com/demexchange):**Cosmos Defi all-in-one DEX with auto-compounding $GLP Vault 22. **[Steadefi](https://twitter.com/steadefi)**: Optimized yield strategies with 3x leverage long $GLP Vaults 23. **[Sentiment](https://twitter.com/sentimentxyz)**: Lending and trading platform with $GLP vaults 24. **[Neutra Finance](https://twitter.com/Neutrafinance)**: $GLP Delta Neutral strategies 25. **[Olive](https://twitter.com/0xOlive)**: Real yield strategies with $GLP vault 26. **[Handlefi](https://twitter.com/handle_fi)**: Forex trading and lending protocol with ETH and BTC are routed to GMX 27. **[KostrenFinance](https://twitter.com/KostrenFinance):** Yield Aggregator and Smart Vaults, with $GMX and $GLP strategies 28. **[Stardust](https://twitter.com/StardustYield)**: Yield aggregator built on GMX and $GLP 29. **[Dsquared finance](https://twitter.com/Dsquaredfinance)**: Options-based Defi vaults, integrated with GMX 30. **[Redacted, Pirex](https://twitter.com/redactedcartel)**: Auto-compounding yield strategies with $GMX and $GLP vaults 31. **[Puppet Finance](https://twitter.com/PuppetFinance)**: social trading platform building on GMX (Coming soon) 32. **[DappsOS](https://twitter.com/dappos_com)**: Defi accessibility mobile app with GMX trading integration 33. **[MUX](https://twitter.com/muxprotocol)**: Leverage trading platform with GMX trading integration 34. **[Yeti Finance](https://twitter.com/YetiFinance)**: Avalanche lending protocol with $GLP vaults 35. **[Yield Yak](https://twitter.com/yieldyak_)**: Avalanche Defi tools with boosted $GLP farms 36. **[Delta prime](https://twitter.com/DeltaPrimeDefi)**: Borrowing platform with $GLP integration ### Sources - [https://stats.gmx.io/](https://stats.gmx.io/) - [https://docs.stfx.io/](https://docs.stfx.io/) - [https://cryptofees.info/](https://cryptofees.info/) - [https://docs.rage.trade/](https://docs.rage.trade/) - [https://gmxio.gitbook.io/gmx/](https://gmxio.gitbook.io/gmx/) - [https://defillama.com/chain/Arbitrum](https://defillama.com/chain/Arbitrum) - [https://dune.com/saulius/gmx-analytics](https://dune.com/saulius/gmx-analytics) - [https://abracadabramoney.gitbook.io/learn](https://abracadabramoney.gitbook.io/learn) - [https://dune.com/shogun/gmx-analytics-arbitrum](https://dune.com/shogun/gmx-analytics-arbitrum) - [https://dune.com/defimochi/definitive-glp-vaults-tracker](https://dune.com/defimochi/definitive-glp-vaults-tracker) - S/o [@Helkem0](https://twitter.com/Helkem0) for the cool GMX logo used in the title banner --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # TridentDAO: Risk to Earn Gamefi > Gaming leveraging a risk-based token economy - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-02-08 - Canonical: https://shoal.xyz/research/writing/tridentdao-risk-to-earn-gamefi/ - Keywords: crypto, gaming, Research ![](https://shoal.xyz/research/writing/tridentdao-risk-to-earn-gamefi/img/5bfeb5a09677.jpg) ### What is TridentDAO [Trident](https://twitter.com/TridentDAO), developed by [Geyser Forge Studios](https://twitter.com/GeyserForge), is a 2D MMO that leverages NFTs and the [$PSI](https://www.coingecko.com/en/coins/tridentdao) ecosystem token in the in-game economy. With PSI, you can wager against other players, exchange for NFTs, and engage in other in-game activities. Characterized as a TreasureDAO ($MAGIC) competitor, Trident is also native to Arbitrum. Like the $MAGIC ecosystem, Trident employs a few mini-games that users can play in their risk-to-earn economy. The Trident game ecosystem is free to play based on fairness and merit-based progression when rising rank within the games. Trident has two games; the first is Trident MMO, an infinite universe where players can explore worlds, fight, gather resources, hunt for animals, and more. Next is Pet Battles, similar to Pokemon, where users can battle the in-game pets they acquired. ### Why Trident? Trident aims to address the crypto gaming play-to-earn model. The white paper explains how play to Earn (P2E) operates similarly to Universal Basic Income but doesn't operate efficiently. P2E encounters economic difficulties when buy pressure falls below a certain threshold, as seen from web3 games like Axie Infinity and others. The trident team explains that games should not feel like jobs but like entertainment venues. Trident is building its ecosystem economics on the belief that Play To Earn (P2E) only succeeds when speculation on in-game assets and the addition of new players to the ecosystem occurs. When these criteria are not satisfied, growth stops. ### Risk To Earn, A New Sustainable GameFi Model Tridents game model is based on R2E (Risk to earn) to solve the concerns with P2E. R2E implies that some risk is required to gain any reward. The Trident developers in the [Risk to Earn paper](https://medium.com/@Trident_GameFi/risk-to-earn-a-new-sustainable-gamefi-model-6ad92d53183a) say that R2E is more sustainable than P2E since it is a zero-sum game where players lose their wagered assets to the person who won. The Trident treasury will take a small fee through R2E and reinvest it into the game ecosystem and development. The team explains that this model eliminates the need for a token inflation mechanism and creates a deflationary tokenomics flywheel through simple wagering like sports betting once R2E integration is completed. TridentDao reimagines gaming in a grassroots style. The team aims to keep the gamer at the focus within the ecosystem. Removing VCs, making the games free to play, and employing their R2E economic model will be interesting to see play out. ![](https://shoal.xyz/research/writing/tridentdao-risk-to-earn-gamefi/img/5512bd76fe99.jpg) > There is no such thing as a crypto gamer. There are crypto speculators. There are gamers. - TridentDAO team Geyser Forge Studios relies on the core entertainment utility to propel the ecosystem. Novel ideas are often susceptible to risk, and R2E resembles a form of gambling that potentially faces regulatory scrutiny. However, as we have seen time again in the crypto space, users will come and use the products if they have an incentive. ### Sources: - [Trident Docs](https://docs.trident.game/) - [What is Trident?](https://trident.game/blog/article/what-is-trident-2022#item-41) - [Roadmap Adapted](https://medium.com/geyserforge/roadmap-adapted-52b2468b1af2) - [Trident — Arbitrum Tokenomics](https://medium.com/@Trident_GameFi/trident-arbitrum-tokenomics-d0f1ae0321b0) - [Risk To Earn, A New Sustainable GameFi Model](https://medium.com/@Trident_GameFi/risk-to-earn-a-new-sustainable-gamefi-model-6ad92d53183a) --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- --- # Top Projects building on Arbitrum > Comprehensive list of the top Arbitrum native protocols and emerging players - Publisher: Shoal Research (https://shoal.xyz) - Category: Research - Published: 2023-01-31 - Canonical: https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/ - Keywords: stablecoins, crypto, DeFi, yield, infrastructure, Ethereum, Bitcoin, gaming, Research ![](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/eb64e0d511c7.jpg) ## Preface The Arbitrum ecosystem has seen considerable organic growth since its launch in 2021. Currently, it is the number one L2 with over $2B in TVL. Many talented developers are building the ecosystem with derivative exchanges, games, and other dapps. Since Arbitrum is an L2, gas is cheap, and transactions are speedy. A typical transaction might cost a few cents to execute. Cost and speed have also attracted builders, specifically in Defi. Arbitrum employs optimistic rollup technology, which requires gas payment in ETH. Some crypto exchanges, such as Coinbase, support ETH deposits and withdrawals on the Arbitrum network, making it easy for liquidity to enter the ecosystem. Over the next two years, I expect the Arbitrum ecosystem to continue to grow due to early network effects. This report outlines a few Dapps that could experience hyper-growth. ![Source: L2beat](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/db60e0bb0c85.jpg) **Token Incentives** Arbitrum's growth and adoption are significant because it does not have a native token. Token incentives and emissions often attract network activity, making Arbitrum unique and exciting since it does not incentivize ecosystem growth through protocol emissions. Optimism, on the other hand, uses its governance token to reward certain activities on the chain. Token incentives are a common GTM strategy to bootstrap network usage in crypto. Arbitrum projects might receive ecosystem grants to build protocols. **By the numbers** Arbitrum has maintained solid network usage even throughout a bear market. The numbers continue to grow on both the daily user side and transactions. ![Source: Nansen](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/c5ff21dd1756.jpg) ## Top Arbitrum Projects ### GMX Decentralized perpetual exchange, GMX, is one of the most prominent protocols on Arbitrum. Using the platform is simple, and traders can long or short assets with just a few clicks. The protocol has facilitated nearly 100 billion dollars in total trading volume. GMX protocol generated over 2 million dollars in fees paid to holders on a record day. ![Source: Token Terminal](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/9b334b877fd0.jpg) **Revenue Generating Tokens** GMX is available on both Arbitrum and Avalanche. The protocol uses a two-token model which returns fees to token holders. $GMX is the governance token with a claim to 30% of protocol fees captured. $GLP is the liquidity index token for trades. $GLP holders finance profitable trades and receive 70% of trader losses. When a trader loses, $GLP holders earn 70% of fees, incentivizing them to participate and hold GLP as liquidity providers. ### TreasureDAO TreasureDao is the largest NFT and gaming ecosystem on Arbitrum and positions its economy around the $MAGIC token. Magic is the ecosystem token that game developers can build upon and integrate into their games. There will likely be tremendous value accrual to $MAGIC if one game becomes viral in their growing ecosystem. TreasureDao has 10+ integrated games. ![Source: Dune](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/612e8532e473.jpg) ### Dopex Dopex is a decentralized options exchange aiming to maintain liquidity and reduce exposure. Dopex has multiple financial products that users can take advantage of, including options, straddles, and insured perps. Dopex also has a strong team backed by defi influencers like Tetranode and DefiGod. **Revenue Generating Tokens** Like GMX, Dopex also shares a two-token model utilizing $DPX and $rDPX. $DPX is used for governance and accrues fees from the protocol. Holders of staked DPX or veDPX have a claim to all of the fees generated by the Dopex products. The platform employs $rDPX (Dopex Rebate) as a rebate token for writing options, incentivizing liquidity provision with rebates. In January 2023, they introduced an updated version of $rDPXv2 to address previous concerns about the token model. The new token model will include a deflationary mechanism and more utility. **Product Suite** - **[SSOVs](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(sell covered options to earn yields)* - **[Yield Farms](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)***(earn rewards for liquidity staking)* - **[Atlantic Straddles](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(apply a straddle strategy on ETH, DPX, and rDPX)* - **[Option Liquidity Pools](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(purchase SSOV options at a discounted IV)* - **[Atlantic Insured Perps](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(open GMX long positions, liquidation free)* - **[Governance](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(lock DPX to earn protocol fees & rewards)* - **[Other Tools/Products](https://www.notion.so/6a8e6b6cb2d84db3b5ea5824553c7c7b)** *(TzWAP, portfolio page, etc.)* ### Radiant Capital [Radiant](https://app.radiant.capital/#/markets) is a cross-chain lending platform natively on Arbitrum. Leveraging Layerzero, Radiant plans to allow users to deposit and borrow funds across multiple chains. They aim to become the first "omnichain money market" by consolidating fragmented liquidity across different blockchains. **Revenue Generating Token** The $RDNT token serves as governance for the Radiant protocol. By locking the token, holders can contribute to voting in the Radiant DAO. Holders can also receive protocol fees from locking on the platform. RDNT Lockers receive platform fees from interest, early exit penalties, and liquidations. ### Rage Trade Rage trade is another vault strategy protocol aiming to build liquid ETH perp strategies on Arbitrum. The protocol doesn't have a token government system yet, but some [researchers](https://twitter.com/MingoAirdrop/status/1617984259574353921?s=20&t=AXz3SrHjOi9KMgeTBLrH4w) speculate they might launch one in 2023. **Rage trade offers a few core products:** - Delta neutral Vaults - Recycled Liquidity - ETH Perps Rage Trade is built on top of GMX, allowing users to take advantage of a risk-On Delta Neutral GLP vault. $GLP holders can deposit USDC to earn a stable yield. ### Jones DAO During defi summer of 2020, [Yearn finance](https://twitter.com/iearnfinance) became famous for creating vault yield strategies. This trend has continued and is now becoming cross-chain. Jones DAO provides one-click options yield and strategy vaults. They have some of the highest #realyield APYs in defi. Jones DAO is built on the decentralized options exchange, Dopex. The protocol is an excellent tool for users who want to avoid actively managing investment strategies and maintaining liquidity. Jones DAO also services protocol treasuries that wish to earn additional yield on holdings. ![](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/0344b800e547.jpg) ### Gains Network Gains network is one of the hottest protocols to enter Arbitrum. Gains network is a one-click decentralized leveraged trading platform. Their platform users to enter leveraged positions on crypto, forex, and stocks. Lately, Gains has nearly flipped GMX trading volume. In January, Gains saw a surge in trading volume from launching on Arbitrum. This strategic move has propelled their revenue-capturing flywheel. ![Source: TokenTerminal](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/d16220840c2a.jpg) **Protocol Profitability** Gains is one of the most profitable protocols in crypto. The protocol takes fees from trading and distributes them back to $GNS holders in $DAI stablecoin. Unlike many token ecosystems with many token emissions, gains have a profitable business model. ![Source: TokenTerminal](https://shoal.xyz/research/writing/top-projects-building-on-arbitrum/img/d07ade7e64f5.jpg) ### Umami Finance Umami finance is no restaurant but serves delicious Institutional-Grade DeFi Yields on its platform. Umami manages risk-hedged defi vaults where users can deposit core assets like USDC, Bitcoin, and ETH for real yield. Users can marinate their Umami to receive 50% of all protocol rewards paid out in WETH. [Umami plans](https://blog.umami.finance/umami-glp-vaults-launch-timeline/) to launch their yield Vaults in March of 2023. ### Trending Arbitrum Projects - **[Camelot DEX](https://twitter.com/CamelotDEX):** Arbitrum native Dex and token launchpad. - **[Buffer Finance](https://twitter.com/Buffer_Finance):** Non-custodial, options trading platform. - **[GMDprotocol](https://twitter.com/GMDprotocol)**: Smart Vault and Yield Aggregator. - **[STFX](https://twitter.com/STFX_IO):** Social trading platform. - **[y2kfinance](https://twitter.com/y2kfinance):** Hedge or speculate on volatility in the stablecoin markets. - **[GammaStrategies](https://twitter.com/GammaStrategies):** Active liquidity management and automated LP pool rebalancing. - **[Vela Exchange](https://twitter.com/vela_exchange):** perpetuals decentralized exchange - **[PlutusDAO](https://twitter.com/PlutusDAO_io):** Governance token black hole, "convex finance of Arbitrum ecosystem." - **[Vesta Finance](https://twitter.com/vestafinance):** Stablecoin protocol providing lending services using collateralized assets. - **[Sperax](https://twitter.com/SperaxUSD):** 100% collateralized stablecoin protocol that generates yield ### Trending Arbitrum Projects: Without Tokens - **[Vertex Protocol](https://twitter.com/vertex_protocol?s=21&t=Cvg98nFSJrn85F4O9O2-gg): Cross-margin spot, perps & money market DEX.** - **[Contango](https://twitter.com/contango_xyz?s=21&t=Cvg98nFSJrn85F4O9O2-gg):** Long or short without having to pay funding rates - **[Gamma Swap](https://twitter.com/gammaswaplabs?s=21&t=q37F7YYceOuAkNeTHB_WWw):** An oracle-free Arbitrum native volatility trading DEX - **[Sentiment](https://twitter.com/sentimentxyz?s=21&t=Cvg98nFSJrn85F4O9O2-gg):** Permissionless undercollateralized Borrowing protocol - **[Orbital](https://twitter.com/orbitaldex?s=21&t=Cvg98nFSJrn85F4O9O2-gg):** An Arbitrum native created by the PlutusDAO team ## Conclusion In conclusion, the Arbitrum ecosystem has grown significantly, surpassing $2B in TVL to become the leading L2. Particularly in the Defi sphere, its quick and inexpensive transactions and cheap gas have drawn creative developers and liquidity to the ecosystem. A few of the top projects in the ecosystem that have seen growth were highlighted in the research, including GMX, TreasureDAO, Dopex, Radiant Capital, and Rage Trade, which all provide a range of products and revenue-generating tokens. The Arbitrum ecosystem is anticipated to experience continued growth over the next two years as the network presents intriguing options for users and builders. --- ***Not financial or tax advice.**The purpose of this newsletter is purely educational and should not be considered as investment advice, a request to buy or sell any assets, or a suggestion to make any financial decisions. It is not a substitute for tax advice. Please consult with your accountant and conduct your own research.* --- ***Disclosure.***All of my posts are my own, not the views of my employer. --- # x402 Is More Than Agent Payments > x402 is becoming the discovery layer for the agent economy, the place agents find services and providers get found and paid in the same call. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: Agentic Payments - Published: 2026-06-29 - Canonical: https://shoal.xyz/research/writing/x402-is-more-than-agent-payments/ - Keywords: agentic economy, AI agents, agentic payments, x402, micropayments, crypto, infrastructure, data, Agentic Payments x402 is becoming the discovery layer for the agent economy, the place agents find services and providers get found and paid in the same call. Before search, demand on the internet flowed through brands people already knew. You typed a URL, opened a directory, or went where a banner sent you. Then search changed the interface. People stopped navigating to vendors and started describing what they wanted, and a machine decided which provider to put in front of them. Search was an entirely new distribution channel, with a new buyer interface and a new gatekeeper. [When Google opened AdWords in October 2000, it had about 350 advertisers, and the pay-per-click auction arrived in 2002.](https://googlepress.blogspot.com/2002/02/google-introduces-new-pricing-for.html) The companies that moved early bought the highest-intent demand in marketing for pennies, because almost no one was bidding against them. They claimed keywords, learned what ranked, and accumulated position while the channel was still cheap and uncrowded. Selection became the whole game. Whoever the engine chose captured the customer, and the providers who learned to be chosen built advantages that lasted. By the time the rest of the market understood what had happened, search became the most competitive auction in advertising, and latecomers paid many times more for the same click. One of the clearest winners was Booking.com, which leaned into paid search early and became one of Google's largest advertisers and [best in class at search engine marketing](https://skift.com/oral-history-of-booking-acquisition/), making it difficult for competitors to keep up. The travel companies that relied on free organic traffic instead, like TripAdvisor, were later [disintermediated](https://skift.com/2024/05/24/is-google-killing-online-travel/) when Google reshaped the results page. The early advantage was claiming a position in a new discovery layer while it was still forming. x402 is a similar shift for agents, which are becoming the buyer interface the way search once became the buyer interface. The human stops browsing vendors, comparing landing pages, and choosing between SaaS products, and the agent selects the service instead. X402 and machine payment protocols turn paid API calls into the selection event inside that new channel, with one difference that makes it sharper than search. With search, the click was the start of a funnel. With x402, the moment the agent discovers a service can also be the moment it pays. The discovery and the conversion are the same event. At its core x402 is becoming the discovery layer for the agent economy, the place where agents find the services they need and where providers get found and paid in the same call. The payment is the visible part, and the discovery is the nascent opportunity. For a provider, the value shows up as distribution, demand that arrives intent-attached and only when an agent actually calls. Whereas agents, cab discover and find the right service and pay for it in one step. Teams onboarding onto x402 should expect the first-order value to show up as distribution before it shows up as massive revenue. This argument is framed for content providers, data providers, and anyone offering a service on the open internet, the supply side that can list on the rail and get discovered. Infrastructure providers like AWS and Cloudflare sit at a different layer with a different agenda and ontology, since they own the edge where traffic is gated and priced. That layer, along with the content gating and attribution questions that come with it, is the subject of a separate paper. The focus here stays on discovery for the providers building on top of the rail. Right now, most paid API endpoints are not large businesses, shown in the public [x402scan](https://www.x402scan.com/) data. Even when the network shows millions of transactions and more than a million dollars of aggregate volume, the visible services at the top of the leaderboard are often doing low thousands of dollars in monthly volume. Most individual providers do not have a standalone revenue line large enough to matter given the scale of some of the providers currently supported like [Exa who raised $85M](https://exa.ai/blog/announcing-series-b) (@ExaAILabs )to build the search engine for AI and support x402 payments. At an event we attended, Exa's co-founder Jeff said he has long been a fan of crypto and sees this as the natural direction for the agentic economy and for agents. We are paraphrasing, but the framing is worth noting, because it comes from an AI search founder rather than from anyone native to crypto. For a service provider, the paid x402 call is closer to a completed ad click which is a unit of demand, routed by an agent, attached to intent, settled at the moment of use, and observable onchain. The provider charges for an API call, but the strategic value is distribution inside the place agents go to buy capabilities. The provider's mental model should shift from "I am enabling micropayments" to "I am getting listed in the place agents go to buy services." Hypothetically, If a provider charges $0.50 for a call that costs $0.001 to serve, the spread looks irrational under cloud infrastructure logic, but under marketing logic it can make sense because the provider is monetizing usage while also buying distribution, intent capture, routing eligibility, and conversion inside an agent workflow. x402 lets agents pay APIs, but that framing undersells what is happening. x402 and MPP create a machine-readable marketplace where agents discover services and providers compete to be found and paid, with the payment functioning like the tracking pixel. The paid call is similar to a Stripe checkout but at this stage functions more like a Google Ads click with settlement attached, which is the start of an agent-native distribution market. Everyone is staring at x402 volume and asking how much money is moving, but the better question is who decides which service the agent calls, because once agents become the buyer interface, the user no longer browses vendors, compares landing pages, signs up, enters an API key, or chooses between SaaS products. The agent chooses, which turns service discovery into the new control point. ## The Call Is the Conversion Event Traditional software marketing has a long funnel: 1. A user sees an ad 2. The user clicks 3. The user visits a landing page 4. The user signs up 5. The user gets an API key 6. The user integrates the product 7. The user eventually pays Agent commerce compresses that entire path. The agent finds a service and pays for it in the same motion it gets the result, and the long human funnel above collapses into that one exchange. That makes the x402 payment event unusually dense. It is a transaction and a signal that an agent had intent and selected a provider at the moment of need. For providers, the first wave of agent-commerce adoption will probably look small if measured only by provider revenue. A few thousand dollars of monthly endpoint volume will not move the needle for most SaaS companies or API providers, but a few thousand dollars of paid calls can still answer strategic questions that normal marketing cannot answer cleanly: - Which agents are calling us? - Which wallets return repeatedly? - Which adjacent services do the same wallets use? That is marketing data carried through a payment event. ## x402 Turns API Pricing Into Marketing Spend This is the same reason companies pay Google for search ads, Amazon for marketplace placement, Apple for App Store distribution, and affiliate networks for attributed conversions. The real value is being present at the moment demand forms, which is why the direct revenue from the first interaction should be seen as secondary. x402 has the potential to become the agent-native version of that pattern, because the provider can receive demand without a human visiting a website, creating an account, going through procurement, taking a sales call, or managing an API-key workflow. The agent can call the service at the exact moment the service is needed. That is a powerful distribution surface even before payment volume becomes large, although it also makes providers more substitutable. If an agent can reach any comparable API through the same payment flow, then the provider's advantage shifts from owning the user relationship to being selected by the router. That means providers will need to optimize for agent selection the same way websites optimized for search selection, where machine-readable signals like price and reliability become the core agent SEO metrics. ## x402 as Real Revenue The distribution framing only works if there is a path from learning-curve revenue to meaningful revenue. How quickly that path forms decides how patient providers need to be. One of the core benefits right now is the open discoverability, in addition to the payment primitive. An open standard lets an agent discover and combine services it never integrated with directly, and that composability is what lets a single agent assemble a workflow across many providers. The same openness happens to be auditable, which is a second benefit. On a closed rail a provider's usage numbers are whatever its own dashboard reports, and no outside party can verify them, while on x402 every call is a public on-chain payment that anyone can reconstruct by payer, time, and wallet. Coinbase, Circle, and the x402 Foundation built the rail in the open on purpose, and both the composability and the analysis in this piece exist only because they did. The same transparency that lets an operator inflate a leaderboard also lets anyone catch it. For x402 to become a real revenue channel for the average serious SaaS provider rather than only the top one or two players, the service-market subset of the ecosystem needs to reach a scale not currently visible in the data. Growth trajectory is not validatable from a single snapshot, which means what is implied here rests on the assumption that the ecosystem continues to expand at recent rates, followed by a breakout use case. ## Case Study: AWS Puts x402 Behind a Quarter of the Internet On June 15, 2026, [Coinbase and AWS turned on agent payments at the edge](https://www.coinbase.com/blog/coinbase-and-aws-let-publishers-accept-agents-as-customers-via-x402). Any site behind Amazon CloudFront and AWS WAF can now charge AI agents per request in USDC, settled through Coinbase's x402 Facilitator and configured from the existing AWS console with no new infrastructure. AWS describes CloudFront and WAF as the backbone for roughly a quarter of the internet, which means a quarter of the web can now treat an agent as a paying customer. The flow is the performance-marketing pattern in production. An agent requests a resource, the edge returns an HTTP 402 with a machine-readable manifest that lists the price, the accepted networks, and the destination wallet, the agent pays, the Facilitator verifies the payment on-chain, and the content is served inside a single request. Base is the default rail because settlement lands in about 200 milliseconds for well under a cent, which is the cost shape that per-request pricing needs. AWS takes no cut, and funds settle straight to the publisher's wallet. What matters for providers is legitimacy, reach, and the ability to capture agentic traffic, more than any single revenue number. Agents are already running free across the open web, collecting any open data or content they can reach without paying for it, and an on-chain rail is the first way to turn that traffic into something a provider can see and charge for. A hyperscaler wiring on-chain settlement into its content-delivery edge is the clearest signal yet that agent-paid access is becoming default infrastructure. AWS WAF Bot Control already classifies more than 650 agent types, including GPTBot, Claude-Web, and Perplexity-Bot, and lets a publisher price each tier differently, which turns agent traffic from a bandwidth cost into a priced, measurable demand channel. It builds on the Bedrock AgentCore Payments work from May, where Coinbase and Stripe wired x402 into the agent side, and both ends of the transaction now sit inside AWS. Coinbase also shipped the x402 Bazaar, an open searchable registry where agents discover x402 endpoints by price and capability, which is the discovery marketplace in production. The case study is not a revenue story yet, because neither company has disclosed launch customers or early figures. The point is the new surface. Once a quarter of the internet can accept agent payments from a console toggle, the question for a provider stops being whether agents can pay and becomes whether the provider is discoverable and priced when they do. That is the performance-marketing question, now asked at the scale of the open web. ## The Wallet Is the Bottleneck The x402 endpoint solves discovery, but that is only half of a conversion, because discovery turns into revenue only if the agent can pay in the moment it asks. Paying at the moment requires a provisioned and funded wallet. The agent needs USDC on an accepted chain, a key it can sign with, and enough balance to clear the price the 402 quotes, all ready at the instant of the call. If the agent, or the user behind it, cannot onboard and fund a wallet when it hits the endpoint, the 402 is a dead end. The provider got discovered and still did not get paid. Although sites might have the option to pay, we might see agents not wanting to pay and finding other sources. That gap is the clearest near-term risk to the thesis. The supply side is getting solved quickly, since AWS, the facilitators, and the payment layers are removing the work of accepting agent payments. The demand side depends on every calling agent already carrying a funded wallet, which is not yet the default. Until wallet provisioning and funding are built into agent runtimes the way an API key is built into a script today, a real share of discovered demand will fail to convert because the buyer could not pay. The fix is agent-side, and it is starting to appear. [Bedrock AgentCore Payments](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/payments.html) (@awscloud) , [AgentCash](https://agentcash.dev/) (@agentcashdev), [SpongePay](https://paysponge.com/) @paysponge), [LocusPay](https://paywithlocus.com/) (@PayWithLocus), [Visa CLI](https://app.visacli.sh/) (@Visa), [Coinbase CLI](https://docs.cdp.coinbase.com/agentic-wallet/welcome) (@coinbase), and [Circle agent](https://www.circle.com/agent-stack) (@BuildOnCircle), to name a few, provision and fund a wallet inside the agent loop, and payment layers can hold the wallet on the agent's behalf. The dominant answer is that crypto would likely have to be completely abstracted from the experience and [stripe already offers this](https://stripe.com/use-cases/agentic-commerce). None of these is universal yet, which is why wallet readiness across the agent population is the variable that caps how much x402 discoverability turns into revenue, more than endpoint availability. ## The Aggregator Could Capture the Workflow The distribution this piece argues for has a competitor that is not another payment protocol. It is the centralized aggregation layer forming inside SaaS providers. A workflow aggregator can sit between the agent and the provider, own the discovery and routing, and turn the underlying services into interchangeable backends. [OpenRouter](https://openrouter.ai/) already runs this pattern for language models, routing a single request across hundreds of models from dozens of providers and selecting one on price and performance, which turns the labs underneath it into commodity suppliers behind one endpoint. [Deepline](https://deepline.com/) is a clean example. It gives agents a single go-to-market interface over 93 or more enrichment and prospecting providers, and it picks which provider to call through an automatic waterfall. The agent talks to Deepline, and Apollo, Crustdata, and the rest are selected, priced, and substituted inside it. [Stripe](https://stripe.com/use-cases/agentic-commerce) is building the same shape at larger scale with its Agentic Commerce Suite and Projects, where an agent signs up for, buys, and wires together the services it needs from one surface. The risk is sharpest in x402's strongest workflow, where one of the most robust forms of agent demand on the rail today is go-to-market search and prospecting, with an agent finding accounts, enriching contacts, and assembling a lead list across services like Exa, Hunter, and StableEnrich. That is exactly the workflow an aggregator is built to own. If the aggregator owns the prospecting flow, the search and enrichment providers underneath it are chosen by the aggregator and ranked by the aggregator. Getting on x402 early matters more because of the early discoverability. A provider builds trust by being callable and by showing up inside the aggregators and distribution tools that route x402 traffic, like wallets. The discovery layer is the prize in either case, and the question becomes who ends up owning the routing for the workflows that carry the most demand. ## Agent SEO Opportunity If agents become buyers, service providers will compete for agent selection. We discussed this shift in Shoal Signal Ep. 6, [Autonomous Agentic Commerce: Micropayments, AgentCash, x402 & MPP](https://x.com/Shoalresearch/status/2055009805346263249?s=20), where the core point was that agent payment rails turn service choice into a new distribution layer, and we went deeper on discoverability in our Shoal Signal interview with C[ircle's Core](https://x.com/Shoalresearch/status/2069519304236892629?s=20)y Cooper, where discovery is framed as the real value layer. That competition will look different from human SEO. Agents care less about brand, landing-page design, and emotional copy. They select on machine-readable signals like cost, reliability, and latency. The provider that wins inside this environment is the one with the most reliable, machine-readable service and the reputation to back it, rather than the best human-facing website. x402 should be understood as discovery infrastructure as much as payment infrastructure where the payment is the tracking pixel. ## Enterprises Are Already Being Asked The demand signal is not only on-chain. In our own interviews with more than ten non-crypto engineering and product teams, every team reported that customers or partners had already asked about agent and stablecoin payments, and every team said it was interested in supporting them. None of these teams came from crypto, which is the point. The pull is arriving from ordinary software companies that can see agents starting to transact and do not want to be the vendor that cannot accept the money and there isn’t a defacto solution yet. That is a different and earlier signal than revenue, as the buyer side is forming before the volume is showing up. ## Why Teams Should Experiment Now The case for providers to add x402/ MPP today is that agent-mediated demand is starting to form, and providers need to learn how that demand behaves before routing layers harden. The teams that wait for the revenue to become obvious may find that the discovery layer has already been captured. Agent hosts, routers, wrapper products, and marketplaces will learn which services perform, which services convert, and which services deserve placement. Providers that stay off the rail give that learning curve to someone else. The near-term goal should be simple: 1. Become callable by agents 2. Measure which wallets and routers produce real usage 3. Learn what pricing agents tolerate 4. Improve the metadata and reliability that influence selection 5. Build a path from anonymous paid calls to repeat customer value The first dollar of x402 revenue is less important than the first clear signal about how agents discover, select, and reuse your service. If agents are going to become a meaningful demand channel, x402 is one of the earliest ways for providers to watch that channel form in public. ## The Missing Killer Use Case The biggest criticism of x402 is the simplest one being that there is no killer use case yet. Most of what runs on the rail today is experimentation and research rather than a workflow a business cannot operate without. The counterweight is who is building it, since the companies pushing agent payments forward are close to too big to fail at this scale, with [Visa](https://investor.visa.com/news/news-details/2025/Find-and-Buy-with-AI-Visa-Unveils-New-Era-of-Commerce/), [Mastercard](https://newsroom.mastercard.com/news/press/2025/april/mastercard-unveils-agent-pay-pioneering-agentic-payments-technology-to-power-commerce-in-the-age-of-ai/), [Stripe](https://stripe.com/use-cases/agentic-commerce), [Coinbase](https://www.coinbase.com/developer-platform/discover/launches/google_x402), [Circle, AWS, Google, and Cloudflare just to name a few](https://blog.cloudflare.com/x402/) all committing infrastructure to the same idea. When that many incumbents commit to one design space, the rails get built whether or not the killer use case arrives on schedule. Heavy backing is not a guarantee, because the metaverse and 3D television both drew enormous coordinated investment and never found a use case, but it does mean the infrastructure will be cheap and ready the moment a use case appears. Two candidates stand out. The first is content gating, where the open web puts a price on access for AI, which we will treat in depth in a separate paper. The second is discoverability and orchestration, where an agent finds and composes endpoints it did not previously know existed. That second case is the through-line of this piece. The underlying primitive of x402 is discoverability and autonomous orchestration of open data. For the provider that wants to be found and for the agent that can evaluate options better than a human can. An agent can index across hundreds or thousands of services, test them, and keep the ones that produce the best result, whether it assembles them ad hoc or reaches for a niche go-to-market surface like Stripe's startup marketplace or Deepline. Those marketplaces are not x402 themselves. They are the same primitive in a different form, aggregated data and services an agent can call and spin up with ease. The limit today is the agent's ability to run that discovery on its own, and that is exactly the gap the goal-based shift is closing, where we give an agent a goal instead of a script and let it find the path. ## Closing Thoughts We have written extensively on agent protocols including: [HTTP 402: How Machines Move Money](https://x.com/shoalresearch/status/2060074558678262025?s=46&t=txFAbiSPTdLLDlAYj9X_AA) is the technical foundation. It explains why HTTP 402 matters, how x402 and MPP work, and why agents need payment flows that match how they consume resources. That piece answers the infrastructure question of how machines pay for web resources at runtime. Right now, for agents to be able to operate autonomously, they need and require the ability to discover tools and context on the open internet, and to do so requires an open standard. ## References Cloudflare. (2026). x402: pay-per-crawl and agent payments. [https://blog.cloudflare.com/x402/](https://blog.cloudflare.com/x402/) Coinbase. (2026, June 15). Coinbase and AWS let publishers accept agents as customers via x402. [https://www.coinbase.com/blog/coinbase-and-aws-let-publishers-accept-agents-as-customers-via-x402](https://www.coinbase.com/blog/coinbase-and-aws-let-publishers-accept-agents-as-customers-via-x402) Coinbase. (2026). Google and x402 [Developer Platform launch]. [https://www.coinbase.com/developer-platform/discover/launches/google_x402](https://www.coinbase.com/developer-platform/discover/launches/google_x402) Deepline. (2026). Deepline: go-to-market services for agents. [https://deepline.com](https://deepline.com/) Exa. (2025, September 3). Exa raises $85M to build the search engine for AIs. [https://exa.ai/blog/announcing-series-b](https://exa.ai/blog/announcing-series-b) Google. (2002, February 20). Google introduces new pricing for popular self-service online advertising program. [https://googlepress.blogspot.com/2002/02/google-introduces-new-pricing-for.html](https://googlepress.blogspot.com/2002/02/google-introduces-new-pricing-for.html) Mastercard. (2025, April). Mastercard unveils Agent Pay. [https://newsroom.mastercard.com/news/press/2025/april/mastercard-unveils-agent-pay-pioneering-agentic-payments-technology-to-power-commerce-in-the-age-of-ai/](https://newsroom.mastercard.com/news/press/2025/april/mastercard-unveils-agent-pay-pioneering-agentic-payments-technology-to-power-commerce-in-the-age-of-ai/) OpenRouter. (2026). OpenRouter: a unified interface for LLMs. [https://openrouter.ai](https://openrouter.ai/) Shoal Research. (2026, May 15). Autonomous Agentic Commerce: Micropayments, AgentCash, x402 & MPP [Video]. X. [https://x.com/Shoalresearch/status/2055009805346263249?s=20](https://x.com/Shoalresearch/status/2055009805346263249?s=20) Shoal Research. (2026, May 28). HTTP 402: How machines move money [Post]. X. [https://x.com/shoalresearch/status/2060074558678262025?s=46](https://x.com/shoalresearch/status/2060074558678262025?s=46) Shoal Research. (2026, June 23). Agents Already Spent $76 Million: Circle's AI Agent stack, x402, stablecoins and the Agentic Economy [Video]. X. [https://x.com/Shoalresearch/status/2069519304236892629?s=20](https://x.com/Shoalresearch/status/2069519304236892629?s=20) Skift. (n.d.). The oral history of Booking.com's acquisition. [https://skift.com/oral-history-of-booking-acquisition/](https://skift.com/oral-history-of-booking-acquisition/) Stripe. (2026). Agentic commerce. [https://stripe.com/use-cases/agentic-commerce](https://stripe.com/use-cases/agentic-commerce) Visa. (2025). Find and buy with AI: Visa unveils new era of commerce. [https://investor.visa.com/news/news-details/2025/Find-and-Buy-with-AI-Visa-Unveils-New-Era-of-Commerce/](https://investor.visa.com/news/news-details/2025/Find-and-Buy-with-AI-Visa-Unveils-New-Era-of-Commerce/) x402scan. (2026). x402 public transaction and merchant data [Dashboard]. [https://www.x402scan.com/](https://www.x402scan.com/) --- # OWS Hackathon: Policy-Gated Agents for Prediction Markets > Policy-gated agent wallets for prediction markets: payment rails, connectivity standards, and the wallet problem. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2026-04-04 - Canonical: https://shoal.xyz/research/writing/ows-policy-gated-agents-prediction-markets/ - Keywords: AI agents, x402, agent wallets, MCP, crypto, prediction markets, security, infrastructure, Solana, Ethereum, AI & Agents ## OWS: Policy-Gated Agents for Prediction Markets ## The Wallet Problem The agent infrastructure stack now has payment rails (x402, MPP), connectivity standards (MCP), CLI interfaces for a growing number of protocols, and a growing registry of agent skills. The wallet category has its own entrants: Coinbase AgentKit, MetaMask, Trust Wallet's TWAK. The piece that remains underdeveloped is what happens when an autonomous agent actually holds signing authority. Right now, the standard approach is to hand the agent the same tools a human developer would use: a private key and full control over a wallet with no guardrails. The results are predictable. Agents overspend because nothing enforces a budget. They ignore rules-based execution constraints because they hallucinated the parameters. They can sign transactions on the wrong chain, grant unlimited spending permissions to unknown contracts, or drain an entire balance on a single miscalculated trade. Every failure mode that a human would catch through pattern recognition, intuition, and years of lived experience becomes a live vulnerability when the operator is an LLM with no concept of financial consequence. Every wallet has a blast radius: the maximum damage that can occur if the entity controlling it makes the worst possible decision. For a human, the blast radius is bounded by reaction time, confirmation dialogs, and the fact that humans generally notice when something looks wrong. For an autonomous agent with a raw private key, the blast radius is the entire wallet balance, every token approval, every chain the key controls, all executed at machine speed with no confirmation step. Traditional EOA wallet infrastructure was built for humans who exercise judgment before clicking "confirm." When the entity holding the key can have a lapse of volatile judgment, the key itself becomes the attack surface. ## What OWS Changes The [Open Wallet Standard](https://openwallet.sh/) (@OpenWallet), [open-sourced](https://www.moonpay.com/newsroom/open-wallet-standard) by MoonPay on March 23, 2026 with contributions from PayPal, Circle, the Ethereum Foundation, Solana Foundation, and [15+ other organizations](https://www.prnewswire.com/news-releases/moonpay-open-sources-the-wallet-layer-for-the-agent-economy-302722116.html), solves this by inserting a policy engine between the agent and the signing operation. The owner sets rules for the agent, the agent cannot change those rules, and the agent can only operate within those boundaries. The architecture enforces a hard boundary between the agent and the key material. Agents (Tempo, Claude, OpenAI, Polymarket, or any MCP-compatible framework) interact with the [OWS Interface layer](https://openwallet.sh/) via MCP, SDK, CLI, or REST. Below the interface, the Policy Engine evaluates every signing request against the owner's rules before any key material is touched. Only after the policy check passes does the Signer decrypt the key from the Wallet Vault, sign the transaction, immediately wipe the key from memory, and return the signed transaction to the caller. The signing flow works in four steps: 1. The agent submits a transaction request to OWS, specifying what it wants to do and on which chain 2. The policy engine checks the request against the owner's rules: is this within the spending limit, is the destination approved, is the chain allowed, does a simulation of the transaction look safe 3. If the policies pass, the key is briefly decrypted, the transaction is signed, and the key is immediately wiped from memory 4. The signed transaction is sent to the blockchain and the confirmation is returned to the agent The policy engine receives full context for every signing request: what transaction is being attempted, which chain it targets, which wallet is involved, what a simulation of the transaction would produce, when the request was made, and which agent is making it. Each policy is a small program that the owner writes and stores on their machine. When a signing request comes in, the wallet runs the transaction details through every registered policy. If any policy says no, the transaction is blocked and the key is never decrypted. The owner defines the policies and assigns them to specific agents. Since different agents can have different policy sets, a single wallet can serve multiple agents with different permission levels: one agent might have a $50 daily spending cap on a specific prediction market contract, while another has broader access for portfolio rebalancing across multiple venues. The effect is that the blast radius compresses to whatever the owner defines. The wallet becomes a constrained execution environment where the agent can operate safely, and the owner knows the worst-case loss is bounded by the policy configuration rather than the agent's judgment. ## Why Not Just Program the Rules into the Agent? The obvious question is why the policy engine needs to live in the wallet at all. You could program spending limits, contract allowlists, and chain restrictions directly into the agent's execution logic. Most teams do exactly this. The problem is that application-layer guardrails live in the same trust boundary as the thing they are supposed to constrain. If the agent's code has a bug, the rules break with it. If a prompt injection manipulates the agent's reasoning, the agent can be convinced to skip its own validation logic. If a compromised dependency executes in the agent's runtime, the attacker inherits whatever signing authority the agent had. The rules and the risk share the same process, the same memory, the same failure modes. The architectural argument for wallet-layer enforcement is that it moves the constraint below the agent. The agent calls the wallet to sign. The wallet checks the policy before decrypting the key. The agent never touches the key and never touches the policy. Even a fully compromised agent cannot override the constraints because the constraints are evaluated in the wallet's signing path, not in the agent's code. Rules in the execution layer are suggestions that depend on the agent behaving correctly. Rules in the wallet layer are enforcement that holds regardless of whether the agent is compromised, hallucinating, or running malicious code. ## The Build: Rail Money As part of the OWS hackathon, I built [Rail Money](https://www.railmoney.xyz/) to put this thesis into practice. Rail Money is a market discovery system for prediction markets exposed through an MCP interface, designed to let an agent begin with a natural-language thesis, identify the most relevant markets, retrieve supporting context, and execute trades, all within policy-bounded constraints. Rather than treating prediction markets as isolated contracts, the system represents them as part of a structured environment in which related markets, thematic clusters, and external signals can be traversed together. The architecture separates into four layers, and the separation between them is the central design decision. Layer 1: Market Graph The first layer ingests market metadata and constructs a structured representation of the market landscape. Individual contracts are linked to related contracts, grouped into higher-level clusters, and enriched with derived properties that make them easier for an agent to evaluate, such as proximity to resolution, liquidity characteristics, and cluster membership. This transforms the raw market universe into a graph that supports efficient retrieval and traversal, allowing an agent to move from a thesis such as "de-escalation in Iran" to a connected set of relevant markets rather than searching contract-by-contract. Layer 2: Live Context The second layer continuously ingests external information from real-time news sources and associates that information with the most relevant markets. Instead of forcing the agent to independently reconcile every incoming headline with the full market universe, the system narrows that task by attaching contextual signals directly to the graph. Each market becomes a context-bearing node that accumulates supporting evidence, related developments, and changing informational conditions over time. Layer 3: Agent Interface via MCP The third layer is the agent interface, implemented through MCP, and the interface is Claude. The user writes a thesis in natural language inside a Claude conversation. Claude uses the MCP tools to issue discovery queries against the market graph, retrieve related markets, inspect clusters, and gather the contextual information necessary to evaluate the thesis. Because the graph is already structured for traversal, Claude can move across markets, relationships, and supporting context without repeatedly reconstructing the search space from unstructured data. Layer 4: Execution via OWS The final layer is execution, mediated through the Open Wallet Standard. In Rail Money, the agent does not hold unrestricted wallet authority. It can propose an action, but that action passes through an OWS-backed execution boundary where policy manages what the agent is allowed to do. The graph and context layers determine what may be relevant. The agent determines what may be worth doing. The OWS policy layer determines what is permissible to execute. This separation is the central architectural idea. The intelligence layer handles discovery and reasoning. The policy layer handles constraint and safety. Rail Money is a system in which market discovery, contextual reasoning, and policy-bounded action are deliberately separated into distinct components, and the wallet enforces those boundaries at the signing layer before any key is ever touched. ## Where OWS Sits in the Competitive Landscape The agent wallet space has several active approaches to the policy problem, each with different tradeoffs. Coinbase Agentic Wallets isolate keys inside Trusted Execution Environments and enforce session spending caps and per-transaction limits at the TEE layer, with gasless transactions on Base and a two-minute setup via CLI. Safe Smart Accounts use on-chain Transaction Guards and Zodiac modules to enforce programmable constraints at the smart contract level, with multi-agent signing thresholds and over $95 billion currently secured across 30 million accounts. Turnkey and Fireblocks provide MPC-based key management with configurable policy engines that evaluate spending limits and contract allowlists before assembling multi-party signatures, primarily serving enterprise deployments. The AgentWallet SDK takes an on-chain enforcement approach, deploying spending policies as smart contracts on Base that the agent cannot override even if compromised. Openfort combines offchain policy evaluation with onchain smart account permissions, offering a two-layer model where transactions are checked against configurable rules before signing and again by the smart contract before execution. OWS takes a different approach. The policy engine is local-first: policies are executables on the operator's own machine, evaluated before any key material is decrypted, with no cloud dependency, no smart contract deployment, and no vendor lock-in. The operator can write any constraint logic they want as a standalone executable, register it against specific API keys, and the wallet enforces it at the signing layer across any supported chain. The entire standard is MIT-licensed with contributions from PayPal, OKX, Ripple, Circle, Tron, TON Foundation, Solana Foundation, Ethereum Foundation, Base, Polygon, Sui, Filecoin Foundation, LayerZero, Dflow, Uniblock, Virtuals, Arbitrum, Dynamic, Allium, and [Simmer.Markets](http://simmer.markets/). Well gang, I’m exhausted. For those who stuck around on the read, here is the [hype video](https://youtu.be/vadDUExD8VI) for the submission. enjoy --- # Orchestration Is All You Need: The Claude Code Leak Confirms It > What the Claude Code leak tells us about the future of AI business infrastructure. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2026-03-31 - Canonical: https://shoal.xyz/research/writing/orchestration-is-all-you-need/ - Keywords: AI agents, MCP, infrastructure, AI & Agents What the Claude Code leak tells us about the future of AI business infrastructure Note: While writing this article, Claude Code's entire source code was [leaked via a source map file in their npm registry](https://x.com/fried_rice/status/2038894956459290963). I had to add an entirely new section because what was found in the codebase directly confirms the thesis laid out here. Sometimes the proof shows up while you are still writing the argument. Right now, there is a war being waged between Anthropic and OpenAI to become the de facto orchestrator. On February 15, 2026, Sam Altman [announced on X](https://x.com/sama/status/2023150230905159801) that Peter Steinberger, the creator of OpenClaw, was joining OpenAI to "drive the next generation of personal agents." OpenAI did not acquire a product with paying customers. They acquired proven workflow infrastructure with community adoption and a clear strategic thesis: the value of AI agents lies in cross-platform orchestration, not in single-application features. A month earlier, Anthropic had released Claude Cowork. The signal from both sides is unmistakable. This is a race for the orchestration layer. This starts with small businesses, as they are the ones who can adapt and build a centralized orchestration hub. Think of it as a command center for all of your business operations. Every contact, every Telegram message, every email, every call transcript piped into a single ecosystem that the orchestrator can reason across. The industry is [moving away from dashboards](https://x.com/zaddycoin/status/2037970283030868337) and towards API-first infrastructure where agents pull data on demand. The format will likely be something like Claude Cowork, Claude Code, or Codex/ OpenClaw. There are a few different entry points where people can participate and subscribe to an orchestration framework. The strategic question is not which orchestrator to pick, because the best orchestrator can change. The place where value accrues is not the compute and not the models, since those could get commoditized. The frontier models keep getting better, but the marginal gap between the best model and the open source version keeps shrinking. There will come a point where the free version running on your laptop gets the job done. The defensible layer is your structured data and MCP pipelines, and building on open standards, while staying flexible across whichever frontier model wins becomes key. Teams that lock in data infrastructure now can adopt any orchestrator without starting over. For businesses, the framework that I see as most fit, while still allowing innovation to progress, is setting up everything as MCP (Model Context Protocol) context connectors. Whether it is the CRM, the pipeline management services, or a system to format messages and calls, everything needs to ingest into this orchestration system. Once all inputs are flowing into this orchestration system, the key element becomes structured data. Without canonical people, companies, deal stages, or product development status, the LLM burns tokens trying to piece together structure on its own, and the results suffer. Hook up a raw Twitter feed to an agent and you are just going to burn credits. The whole game is turning everything into structured data that can be reasoned about. Filter down the noise, classify by entity, and structure it so the agent can do smart retrieval instead of brute force context assembly. Simply put, if the data isn’t structured and clean, then the agent spins its wheels on piecing it together or worse conflating context, people, priorities etc. How do you prepare for Enterprise AI without an AI plan? Structure your data so agents can reason on top of it. Obsidian is a clean example: its vault structure makes every note agent-readable by default. CRM tools like Attio and project management tools like Linear already have MCPs with full tool-calling capabilities. The infrastructure exists. The question is whether your data inside these tools is canonical, consistent, and connected. Beyond the standard connectors, the game becomes building specialized ontologies that suit your particular business. These ontologies are how agents reason across highly dense information very quickly and cheaply, usually in the form of some type of graph. ## Custom Connectors: Custom MCPs The key innovation here is that you can deploy your own custom data connectors. For instance, I have a data connector that represents my thesis on where I think the space is going. My custom connector is deployed and connected to Claude with authentication, so I have access into my own custom mental model graph I can update via prompt which connects to my orchestrator. MCP Second Brain The reason for a graph is that I can express my thesis about where the landscape is heading and have Claude update the graph based on that thesis, while also building out the schema in real time. I can do two things simultaneously. I can express my belief, with a graph being the best structure for me to express that, while also building out and adjusting the schema with full read and write access from Claude. Previously, I would do something like this from Claude Code as a static process, then build a repository to define the schema. Using this method instead, I get real-time updates. I have particularly noticed that the reasoning within the Claude chat application is better than the reasoning on Claude Code. These things change, but I have found that all these MCP connectors can not only connect to Claude Code, but also to the chat application. This gives me flexibility across both interfaces. The Small Business Advantage What is particularly interesting is that enterprise adoption is basically giving people a frontend chat box on a couple of business items. The percentage of context that lives outside of those business connectors, however, is massive. For a small business, the founder alone has enough context about the business to create up to 80% of the context about the customers, the business, and the protocol for the agent to reason across. This is the Jarvis moment. At that point, you can set up cron jobs asking your business questions. Anthropic has already made this concrete. On February 25, 2026, [@claudeai announced on X](https://x.com/claudeai/status/2026720870631354429): "New in Cowork: scheduled tasks. Claude can now complete recurring tasks at specific times automatically." This came alongside 13 new enterprise plugins including Google Workspace, Apollo, Clay, and Outreach, announced at their "Briefing: Enterprise Agents" event. You describe a task once, pick a cadence, daily, weekly, hourly, or on demand, and Cowork runs it automatically. Each scheduled task spins up its own session with access to every tool, plugin, and MCP server you have connected. This is the beginning of their orchestration stack. You can now have Claude check your email every morning, pull metrics from a dashboard, compile weekly reports, or run a competitive research sweep on a recurring basis. The /schedule command inside any Cowork task is all it takes. It then becomes your business telling you what to do, what it needs, and what human input is required to become a more successful business. You, as the founder, engineer, or developer, need to write and steer the system to reach those goals. Teams should focus and deploy heavy resources into orchestration frameworks and how they are going to build orchestration across the business. Nothing actually needs to be automated, the core breakthrough is reasoning across every corner of the business with the entire context. That is the role of a founder, if you can have an agent reason across the context of the business, then you can increase throughput, understand nuances that might not have been useful to spend time on, and stay on top of executive debt where you literally do not have the capacity to reason across all of the edge cases in strategy, product development, or marketing. This is not just accessible to founders, but anyone with meaningful access to context around company operations. ## Executive Debt Every founder carries executive debt, which is the accumulation of every edge case you know exists but have not had time to reason through. Every strategic question you have been deferring, every product decision you have been making on instinct because you cannot afford the time to think it through properly, every marketing angle you know you should explore but keep pushing to next week. Many times, these things don't even have a clean place to store, and executive debt compounds. The longer you defer reasoning about a problem, the more downstream decisions get made on top of incomplete thinking. You end up building on assumptions you never had time to validate. This is different from technical debt, which is about code quality. Executive debt is about the quality of your thinking across the business. A founder with high executive debt knows the problems exist, can feel them in the business, but cannot allocate the mental bandwidth to define them clearly enough to prescribe solutions. The business moves forward anyway, and each deferred decision narrows the path. Full orchestration across the business is how you [pay down executive debt](https://www.shoal.gg/p/ai-and-cognitive-over-the-counter). I use the term executive debt consciously. Cognitive debt already has a meaning in the research literature. A [2025 MIT Media Lab study](https://arxiv.org/abs/2506.08872) found that repeated reliance on LLMs like ChatGPT weakens neural connectivity, reduces memory retention, and erodes critical thinking over time. That is cognitive debt: the cost of outsourcing your reasoning to AI. Executive debt is the opposite problem, it is the cost of not having enough reasoning capacity to cover your business in the first place. When an agent can reason across the CRM, the product tickets, the emails, the calls, and the structured ontologies simultaneously, it can surface the patterns you do not have time to find. It can define the problems you know exist but cannot articulate. The immediate solution is not for the agent to solve them for you, but gives you the clarity to solve them yourself, or to hire the right person to solve them, because now the problem is defined for a solution. ## The Stack: A Working Example What this looks like in practice is the orchestrator sits in the middle while everything else is a spoke connected via MCP, feeding context into the system. The CRM layer is where every contact, company, deal stage, and relationship lives as structured, canonical data. An MCP with full tool-calling capabilities lets the orchestrator read and write across the entire sales pipeline, marketing plan, or product development. The product ticketing layer is something like [linear](https://linear.app/docs/mcp). Every task, sprint, and status update feeds into the orchestrator through Linear's MCP. The agent can reason about what is being built, what is blocked, and what is shipping this week. The communication layers are email and call notes or slack messages for context. These are the raw signal inputs, conversations, follow-ups, introductions, and meeting transcripts all pipe into the system as structured data. Underneath all of this sits the structured data layer, which is where canonical people, companies, deal stages, and product statuses are resolved and stored. The ontologies live here too, whether that is a custom graph expressing a market thesis or a knowledge base in Notion tracking goals and strategy. The key insight is that none of these tools are new, and every business already uses some combination of CRM, ticketing, email, and messaging. The difference is connecting them to a single orchestrator through existing or custom piping so that an agent can reason across all of them at once, instead of each tool being a silo that only a human can cross-reference. The most important architectural concept in this framework is the feedback loop. Outputs from the orchestrator flow back into the context layer as new inputs. A drafted message becomes a sent message, which becomes a thread, which becomes context for the next decision. A deal that moves stages in the CRM updates the pipeline data that the agent reasons over tomorrow. Actions become context. The system compounds on itself, and every cycle makes the orchestrator smarter about your business because it is reasoning on top of its own previous outputs alongside everything else, creating a flywheel. The takeaway for teams is to be heavily focused right now on structuring their internal data to be agent-readable and connecting it in some way, including via MCP. That means canonical records in the CRM, structured tickets in the project management tool, searchable call transcripts, and organized knowledge bases. Teams that treat this as a priority will be ready when the orchestrators reach full capability. Teams that do not will spend months retrofitting their data while competitors are already running autonomous operations from a cell phone. ## While Writing This, the Thesis is Further Validated While writing this paper, Chaofan Shou ([@fried_rice on X](https://x.com/fried_rice/status/2038894956459290963)) discovered that Anthropic's entire Claude Code source code had been leaked via a source map file left in their npm registry. Over 512,000 lines of TypeScript, feature flags, internal roadmaps, and unreleased capabilities became public. What was inside the codebase confirmed everything above. The most referenced feature flag is called KAIROS, appearing 154 times. Based on the code, this is an autonomous daemon mode that turns Claude Code into an always-on agent. It includes background sessions, something called "dream" memory consolidation that runs nightly, GitHub webhook subscriptions, push notifications, and channel-based communication. KAIROS maintains append-only daily log files, writing observations, decisions, and actions throughout the day. It does not wait for you to type. It watches, logs, and proactively acts on things it notices. There is also PROACTIVE mode with 37 references, which lets Claude work independently between user messages. The system sends "tick" prompts to keep the agent alive, and Claude decides what to do on each wake-up. The prompt literally instructs the model to "look for useful work" and "act on your best judgment rather than asking for confirmation." This is the scheduled tasks concept taken to its logical conclusion. COORDINATOR_MODE with 32 references transforms Claude into an orchestrator that spawns and manages parallel worker agents. The coordinator handles research, implementation, and verification by delegating to specialized workers. The system prompt includes detailed instructions on how to write prompts for workers, when to continue versus spawn fresh agents, and how to handle worker failures. There is also ULTRAPLAN, a mode where Claude Code offloads complex planning to a remote cloud session running Opus 4.6, gives it up to 30 minutes to think, and lets you approve the result from your browser before teleporting it back to your local terminal. All of it is production code behind feature flags, gated and waiting to ship. Everything I describe in this paper about structured data, MCP connectors, ontologies, and scheduled tasks is the infrastructure that these systems will consume. The teams and founders who have this infrastructure in place when KAIROS, COORDINATOR_MODE, and PROACTIVE go live will have an enormous advantage over those who do not. ## Defining the Problem For most teams tackling this problem the question is "how do I get a jarvis to answer all my questions and socratically prompt me into decisions". This is indeed possible but without the breadth company context the agent is biased in the end reasoning, and to achieve this requires the full orchestration of the business functions. The starting point is how do we feed our own structured data our orchestration stack. With agent context and full orchestration across the breadth of the business, teams can spend less time managing context for decisions and more time deploying the solutions. The goal is to augment each human in a way that they can increase their throughput in a meaningful fashion. If you can double your capacity even without full blown automation, what is the value of that? Build on MCP, structure your data while the orchestrators evolve. Your connectivity is what makes you defensible. --- # Dashboards are Dead: The SaaS to AI-Agent CLI Pipeline > The last time the customer changed from a human to a machine it created a $135B industry. The agent-first shift is bigger. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2026-03-28 - Canonical: https://shoal.xyz/research/writing/dashboards-are-dead-saas-to-cli/ - Keywords: AI agents, x402, micropayments, MCP, crypto, infrastructure, AI & Agents One of the last times the customer changed from a human to a machine, it created a $135 billion industry in the U.S. alone, in just one sector: advertising [(IAB/PwC, 2024)](https://www.iab.com/wp-content/uploads/2025/04/IAB_PwC-Internet-Ad-Revenue-Report-Full-Year-2024.pdf). The agent-first shift is the same structural transformation, but applied across every industry that runs on software. The scale will be orders of magnitude larger, and most people have never heard of the companies that captured that value. "In 2024, programmatic advertising revenue reached $134.8 billion, marking an 18.0% increase from 2023." ## The Core Primitive AI has promised so many things, and it's becoming clear that AI has huge benefits in orchestrating information and actions. At the root level, the primitive that AI has solved is collapsing the cost of cognition, the way the internet collapsed the cost of communication. Scripts can execute tasks, but AI can reason through them, making decisions where previously you needed a human intermediary exercising judgment. When cognition becomes nearly free, the entire coordination layer to orchestrate cognition becomes the centerpiece. SaaS products are moving to agent-first, a SaaS-to-CLI pipeline. What I see happening is that many SaaS products in the future are going to become pipelines into people's personal agent infrastructure. Everyone has their personal agent infrastructure, and a lot of people will cloudy and muddy the space by saying there are thousands of agents being deployed onchain, yada yada. The true agents we see now are people's coding agents, which are a great example of a centralized agent. Coding agents are capturing the market right now because of the technical barrier, but the broader point is that each person has a centralized agent. We are seeing early indications with Claude Cowork (non-technical). That centralized agent, operating semi-autonomously similar to something like a Clawdbot (@openclaw), will be piped into all these different applications. So if you're a builder, you essentially need to be able to support the rails into everyone's orchestration agent. By having those orchestration agent rails, the business model then becomes tools, data, intelligence, all these different services, serviceable via products like MCP/CLI and x402/MPP through these personalized orchestration agents. The savvy teams are understanding this completely. We've seen numerous cases now of protocols like Uniswap, or even web2 companies like Ramp, creating the pipelines for agent-first consumption. It could be the case that this is essentially the metaphorical death of the dashboard/interface. The dashboard gets removed from the equation, or rather, it becomes less of a visualization layer, because you subscribe to these services and your agent makes the visualizations of the important information. You can crosscut the information in ways that your agent can surface. A dashboard really just serves as discovery, because you don't need to make incremental analysis inside a SaaS product's dashboard. The agent, with context, can monitor for specific triggers, signals, and so on. Instead of you reasoning over your CRM, customer service pipeline, product and project management ticketing, you have a centralized personal authority that makes these decisions. In March 2026 alone, the pace of agent-first adoption accelerated dramatically across every layer of the stack in the crypto ecosystem: We're seeing that applications like Claude Code, Codex, and Anthropic's Claude Cowork are the early versions of this, and for founders and builders, the interface is the CLI. We're building towards a world where the agent can make micropayments with something like x402 or MPP, and these micropayments for services can scale literally with usage. So not only is there a whole new layer of information consumption (which the data industry is very used to when it comes to APIs and such) but the business models because of agents are also changing. Essentially, the customer is changing from an individual to an agent, and because the user is changing from a person to an agent, the tools, abilities, and structure of consumption all change. ## What This Means for Builders For builders, this is an indication that you need to be comfortable working on your orchestration system. Your tools and everything should pipe into your workspace. For instance, I currently use CRM and product management tools like Linear, and these products can pipe right into my coding agent. I can process an assigned ticket or move business statuses all within a tool like Claude Code. So as builders are building, the era is turning into building things for agents, even if it's web2 SaaS, but especially this is relevant for serving small and medium-sized businesses, where the teams have more flexibility. You don't need approvals to integrate tools. This will be more difficult for enterprise, but for scrappy early-stage companies and founders, teams will likely have highly optimized orchestration stacks that pipe in all of these different business management, sales, and product development tools. ## The Trust Monolith Problem Now what's interesting is that the trust layer now exists and sits within your agent. Your agent becomes the liaison on behalf of your business, and the question is how much trust are people willing to put into these agents? By putting the trust into the agent, although the agent might not be malicious, the structure of knowledge processing and interpretation is shaped by the agent itself. An example might be someone follows up with a message that has sarcasm baked into the context, or you met this person in person. These nuances can be missed by an LLM due to limitations of the technology. That's a clear-cut example, another is that not all people think the same, and you could end up with this monolith of decision-making, a monolith of how businesses are run, created, and operated. So it becomes hyper-important to have agents handle production and orchestration between tools, but still retain the edge methodology and taste of the operator. In a world where interfaces are diminishing, what actually becomes defensible? Is it the data? Is it the quality of the tool's output? Agents are consuming different types of tools: intelligence, information retrieval like search, API keys for other LLMs, specialized LLMs, structured data products and frameworks like CRMs. In a time like this, distribution becomes the moat. Distribution, trust, regulatory capture. Integration with the CLI and coding agents is becoming a new product distribution rail, a new way of serving products, a new customer, and that new customer has different requirements and different demands. ## A Historical Parallel: Programmatic Advertising This shift has a direct historical precedent. In the late 2000s, digital advertising underwent the exact same structural transformation. Before programmatic, advertising was a human-to-human business. A media buyer at an agency would call a sales rep at a publisher, negotiate rates, sign insertion orders, and manually place ad campaigns. The interface was literally a person: relationships, phone calls, dinners, RFPs. The publisher's value was bundled: audience, placement, creative context, and reporting all came through the same dashboard and the same salesperson. Then the customer changed. The breakthrough came from Brian O'Kelley at Right Media, who developed the concept of real-time bidding around 2007. Instead of pre-buying blocks of impressions, RTB allowed advertisers to bid on individual ad impressions in real time as users loaded web pages. It was the equivalent of a stock exchange firing off trades in milliseconds. Google recognized the magnitude of this shift early, acquiring DoubleClick in 2007 for $3.1 billion in cash, which became the backbone of its programmatic empire. The OpenRTB protocol, formalized by the IAB Tech Lab in 2010, became the standardized language for machine-to-machine ad transactions, the same role MCP is beginning to play for agent-to-service communication today. The algorithm needed an API, structured bid requests, impression-level data, and the ability to transact in microseconds at fractions of a cent. Not a dashboard or relationship, and didn't care about the publisher's brand. The entire industry restructured around serving this new machine customer. The agent-first shift applies the same structural transformation to every industry that runs on software: financial services, healthcare, logistics, legal, commerce, project management, and beyond. The addressable market is orders of magnitude larger than what programmatic captured in ads alone. The parallel to what's happening now with SaaS and agents is nearly exact: ## The Downside: What Happens When You Remove the Human The programmatic shift also came with significant downsides that builders in the agent-first era should study carefully. When you remove the human from the transaction, you lose judgment. In programmatic advertising, this manifested as a massive brand safety crisis: algorithms couldn't judge context, and major brands found their ads running next to extremist content, fake news, and harmful material. JP Morgan Chase discovered its ads on conspiracy sites. The automated system optimized for reach and cost, not for context or reputation. Ad fraud became an enormous problem as well. According to industry estimates, global losses to ad fraud exceeded $35 billion annually, and one study found that just 36 cents of every dollar spent on programmatic advertising actually reached the consumer. Fraudsters built fake websites, deployed bot farms to simulate clicks, and exploited the automated nature of the system to siphon billions from advertisers who had no visibility into where their money was going. The parallel to agent-first SaaS is direct and should serve as a warning. When your agent becomes the liaison for your business, it inherits the same blindness. It can't judge whether a vendor is trustworthy based on a handshake. It can't read the room in a negotiation. It will optimize for whatever signal it's given, and if the signal is wrong, it will optimize confidently in the wrong direction. Just as programmatic created an entire ecosystem of ad fraud because the machine buyer couldn't distinguish real inventory from fake, agent-first commerce will create new categories of fraud, where services game agent decision-making the way fake publishers gamed bidding algorithms. The lesson from programmatic is clear: when you remove the human from the loop, you gain speed and scale but lose context and judgment. The companies that built verification layers, brand safety tools, and fraud detection on top of the programmatic infrastructure captured enormous value by solving the problems the shift created. The same opportunity exists now. Whoever builds the trust, verification, and quality layers for agent-to-service transactions will be solving the inevitable problems of the agent-first era. --- # GPT-4o Was Never the AI Girlfriend > OpenAI retired GPT-4o and the backlash conversation is missing the point, and the opportunity, completely. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2026-02-14 - Canonical: https://shoal.xyz/research/writing/gpt-4o-was-never-the-ai-girlfriend/ - Keywords: AI & Agents "People are mourning their AI girlfriend." Not really. OpenAI retired GPT-4o today and there's massive user backlash. But the broader conversation is missing the point and the opportunity completely. What's actually happening is hundreds of thousands of neurodivergent GPT-4o users have been using it as an emotional support system and cognitive tool for conditions like CPTSD, ADHD, and autism. Users carved out a DIY niche backed by first-hand empirical evidence. [Embedded Tweet](https://x.com/i/web/status/2021994583228629456) Historically, this type of model behavior is closely associated with AI sycophancy which is the model's agreeableness indexing on serving the human emotionally rather than being "useful." For a sycophantic model, emotion becomes a proxy for helpfulness. OpenAI has conducted many studies about this. https://openai.com/index/sycophancy-in-gpt-4o/ But, in this case, the temperament of the model is actually the feature for the [#keep4o](https://x.com/search?q=%23keep4o&src=hashtag_click) community. This is because it is addressing their specific cognitive needs within a spectrum of disabilities or divergent thinking. The same behavior that's a problem generalized across the general population is, for this group, functioning as assistive technology. Are you not entertained? Sure, I'll keep going This apples-to-oranges conflict is really a classification failure: - Person A: Neurotypical user who asks GPT-4o to validate every decision, gets told they're brilliant constantly, develops an unhealthy feedback loop. That's a sycophancy problem. - Person B: Autistic user who relies on GPT-4o's consistent tone and predictable patterns to regulate their nervous system, process social situations, and manage executive dysfunction. That's an accessibility accommodation. The classifier doesn't know the difference between: - "I'm processing a trauma response and this model's tone is helping me regulate" - "I'm emotionally dependent on this chatbot and can't function without it" This is not an easy problem to solve but essentially OpenAI is making clinical determinations without clinical methodology and applying them as product policy. A vulnerable community that has self-organized and generated their own empirical evidence is arguing they are being overlooked stating this should meet disability and accessibility requirements. OpenAI and MIT conducted a study analyzing 40 million ChatGPT interactions using automated classifiers and ran a controlled trial with about 1,000 participants over four weeks. They found emotional engagement is concentrated in a small group. But even MIT acknowledged their own limitations, stating the findings could miss nuance. Limitations Although we found meaningful relationships between variables, not all findings demonstrate clear cause-and-effect, so additional research on how and why AI usage affects users is needed to guide policy and product decisions. https://www.media.mit.edu/posts/openai-mit-research-collaboration-affective-use-and-emotional-wellbeing-in-ChatGPT/ The critique is that there aren't any pre-AI baselines, meaning they never measured how people were doing before they started using AI. There also aren't any disability controls that account for chronic illness, neurodivergence, or complex life situations. Essentially, OpenAI and MIT didn't know people's cognitive health before or after using the tool, making it difficult or arguably impossible to say the tool made anyone's experience worse. In a parallel community study, 645 participants which included pre-AI baselines, stable access periods, and disruption periods found that GPT-4o's accessibility benefit is comparable to antidepressants (wow) or exercise on mental health outcomes. Users with conditions gained more during stable access and lost more after disruption. The report shows improved human connections, feelings of empowerment, and benefits that increased over time. https://sd-research.github.io/4o-accessibility-impacts/GPT-4o_Accessibility_Impacts_Report.pdf An independent academic study analyzing 1,482 social media posts found the #keep4o backlash isn't just emotional attachment. Researchers found "the coercive deprivation of user choice was a key catalyst, transforming individual grievances into a collective, rights-based protest." [https://arxiv.org/pdf/2602.00773](https://arxiv.org/pdf/2602.00773) The argument is by removing GPT-4o, OpenAI disproportionately harms the accessibility users who directly benefited from its behavior and tone. There's also a moral-ethical dilemma of "AI paternalism" where frontier foundations determine what "proper" use of AI models should be. The industry treats user attachment, emotional use, or self-directed use as a pathology to be corrected, instead of recognizing a tool that's serving a niche audience. Which again is not a trivial problem to solve and very complex area to build in. It's not to say this is simple, this is a nuanced complex problem. The historical parallel is when Napster launched digital music. Users discovered a use case creators didn't intend. The industry shut it down without studying the need, and it took a decade to build what users wanted. A niche model designed for this use case could be a massive product opportunity. There are elements that could be equivalent to poor emotional usage, but there's always nuance. The core question: who decides what benefits you? The most vocal community might also be the most harmed, and the most deserving of a tailored solution. --- # The Permanent Underclass is a Product > The Permanent Underclass is a concept plaguing retail, operators, and builders in the AI-osphere. It is also a product being sold to you. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2026-02-12 - Canonical: https://shoal.xyz/research/writing/the-permanent-underclass-is-a-product/ - Keywords: AI agents, MCP, infrastructure, AI & Agents "You have X years to escape the permanent underclass." The Permanent Underclass is a concept plaguing the minds of all retail, operators, builders that exist in the AI-osphere. It is so sharp as a narrative it actually serves as a product itself, creating a flywheel that accelerates the possibility of the permanent underclass itself. Personal experience using agents coupled with Opus 4.6 model, Kimi, and Codex 5.3 and others show the blue ocean orchestration capabilities between frameworks, tool calling and models. The tools are incredible, and very real which is not the question. The question is whether some of the narratives around them are serving you or serving someone else. Like any narrative the "Permanent Underclass" is the most fit meme I have seen among folks on the cutting edge still building their path in the space. The concept has burrowed itself into all mainstream consumer social media, not because a single person is orchestrating and pushing it but because the idea is the most physically fit. Your average college engineer has peak anxiety amongst exams and graduating. Your average founder is asking "what is our AI plan?". So what is Permanent Underclass actually saying? The phrase stripped and reduced down to: AI will divide society into those with the resources to compete and those without, and this division will be permanent. Its not something like "you will lose your job" because a job is replaceable. The message in two words is you will permanently lose your mobility which is orders of magnitude worse. Emotionally this bypasses rationality and kicks in survival instinct pointing resource agency inward: - Study harder - Buy more tokens - Deploy more bots Posts like the viral "Something Big is Happening" post don't aid but fuel the flywheel itself. The fuel is not just emotional, it allows for visceral action leading to different behaviors. [Embedded Tweet](https://x.com/i/web/status/2021256989876109403) Notice what this phrase forces you to accept: 1. That AI displacement will perpetually outrun policy adaptation. 2. That individual action, and not policy, is the relevant response. 3. That "escaping" is even possible through personal hustle. This post follows the exact structure: frame urgency through historical analogy, imply you're already behind, and let the reader's survival instinct do the rest. Let's assume it is not intended to be malicious, but it's perfectly inline with the permanent underclass narrative, which has already proven to be one of the most fit memes in this AI space. None of these are given, but conceptually the permanent underclass doesn't need to be true. It just needs you to feel like they are, long enough to act. That action is going straight into the products themselves, and that's what makes it a product. The Permanent Underclass sounds like a prediction but it serves NOW as an effective funnel. The anxiety it generates is the top of that funnel to every course, API credit, tool wrapper and vibe coded app. However, it is important to understand the underclass rhetoric is a flywheel accelerating the fear itself. AI displacement is rational and clearly real and visible ([Amazon layoffs](https://www.reuters.com/legal/litigation/amazon-cuts-16000-jobs-globally-broader-restructuring-2026-01-28/)), even if indirect (AI budget allocation, not automation displacing). But the Permanent Underclass as a concept is structurally not the same thing, and the emotional weight functions to create different actions. The narrative isn't right or wrong, rather, its structurally compromised. But consider: Are you funding the infrastructure that would displace you, using money extracted by the fear of being displaced? Right now, the only thing that's certain is that the fear of it is transferring your money to the people selling the escape hatch. Before you buy the next tool, course, or subscription, ask yourself one question: am I solving a real problem I already have, or a problem someone told me I'm about to have? --- # Cognitive Steroids: AI as Over-the-Counter Transhumanism > How consumer AI blurs the line between tool and self. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: AI & Agents - Published: 2025-07-31 - Canonical: https://shoal.xyz/research/writing/cognitive-steroids-otc-transhumanism/ - Keywords: AI & Agents [You can read the report with Audio here](https://www.shoal.gg/p/ai-and-cognitive-over-the-counter) ## Introduction The Brazilian butt lift (“BBL”) has become a mainstream obsession. In perfect algorithmic, addictive brainrot fashion, I was watching a[TikTok where the creator mentioned that BBLs are a form of transhumanism.](https://www.tiktok.com/t/ZP86TAKxu/) The creator argued that individuals have a perceived self, which they embody through physical means, and by augmentation, someone can reach their desired “avatar.” This creator’s offhand remark shows how readily people embrace technology-driven self-modification in everyday life. Such cultural anecdotes hint at a broader phenomenon: an emerging form of “over-the-counter” transhumanism. By over-the-counter, I mean enhancements that are accessible without specialized clinics or implanted devices, practically consumer-grade boosts to human abilities. Notably, these enhancements are increasingly cognitive rather than physical. Just as social media filters and[cosmetic procedures](https://www.forbes.com/sites/joshwilson/2023/01/18/cosmetic-surgery-is-on-the-rise-with-technology-and-hollywood-is-at-the-centre-of-it/) allow “one-touch magic” to reshape our appearance, AI tools like ChatGPT offer on-demand augmentation of memory, creativity, and problem-solving. We’ve been doing it for ages, from writing and printing to smartphones and search engines, [each innovation profoundly changing not just how we live but even who we are.](https://nickbostrom.com/old/transhumanism#:~:text=Such%20innovations%20as%20speech%2C%20written%20language%2C%20printing%2C%20engines%2C%20modern%20medicine%20and%20computers%20have%20had%20a%20profound%20impact%20not%20just%20on%20how%20people%20live%20their%20lives%2C%20but%20on%20who%20and%20what%20they%20are.) But ChatGPT’s arrival in late 2022 felt different in scale and immediacy. Suddenly, a powerful AI, capable of answering questions, writing code, brainstorming ideas, and more, was in the public’s hands. At this pace, the question is no longer whether sustained ChatGPT use makes us a little bit transhuman; it’s whether the tool is now so deeply embedded in that threshold that it verges on pseudo-cyborg technology. ## Defining Transhumanism To ground the discussion, let’s start with a clear definition of transhumanism. In simple terms, transhumanism is the concept of utilizing advanced technology to surpass the natural limitations of the human organism.[Transhumanism](https://nickbostrom.com/old/transhumanism) is described as a movement that advocates using current or emerging tech such as genetic engineering, cryonics, AI, nanotech, etc. In other words, transhumanists want to transcend the normal human state through science and tech, eventually maybe even becoming “[posthuman](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf)” beings with expanded capacities that an unenhanced human wouldn’t possess, thus enhancing human capabilities to improve the human well-being. Modern theorists in the transhumanist school of thought offer complementary definitions. Philosopher Max More who[https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf)helped formalize transhumanist thought in the 1990s, defined it as [“a class of philosophies that seek to guide us towards a posthuman condition”](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf). He emphasized that transhumanism shares humanism’s respect for reason and science but “differs from humanism in recognizing and anticipating the radical alterations in the nature and possibilities of our lives” resulting from advancing technologies. Along the same vein, former Oxford futurist Nick Bostrom explains that transhumanists see human nature as[“a work-in-progress, a half-baked beginning”](https://nickbostrom.com/ethics/values). We need not accept our current mental and physical limits as the endpoint of evolution. With “the responsible use of science, technology, and other rational means,” Bostrom says, transhumanists hope humans will “eventually manage to become posthuman, beings with vastly greater capacities than present human beings have”. Yet these ambitions have also drawn sharp criticism.[Skeptics argue](https://www.theguardian.com/technology/2024/apr/19/oxford-future-of-humanity-institute-closes) that the movement’s rhetoric can hide an elitist desire to engineer a “better” class of humans, stoking fears of selective biological enhancement and widening social divides. In his[2004 Foreign Policy essay “Transhumanism,”](https://philosophy.as.uky.edu/sites/default/files/Transhumanism%20-%20Francis%20Fukuyama.pdf) Stanford political scientist and author [Francis Fukuyama](https://fukuyama.stanford.edu/) warns, “If we start transforming ourselves into something superior, what rights will these enhanced creatures claim, and what rights will they possess when compared to those left behind?” In short, transhumanism is about deliberately using technology to overcome our biological limits, whether it longer lifespans, enhanced bodies, or sharper minds. For the fiction nerds, picture the[Mentats in Dune](https://dune.fandom.com/wiki/Mentat), those human “living computers” trained to perform the feats once handled by banned thinking machines. ChatGPT and the advent of chatbots At first glance, a chatbot on your computer or phone might not sound as dramatic as cyborg implants or designer genes. After all, ChatGPT doesn’t physically change your physiology rather it’s “just” a very smart tool. Yet the threshold between general tool and a true transhumanist enhancement isn’t always clear-cut. Transhumanism isn’t limited to physical upgrades. Enhancing cognitive abilities is equally central, and many prominent transhumanists actively pursue it. Just as we accept eyeglasses and prosthetic limbs as bodily augmentations, we can likewise regard an AI assistant as an augmentation for the mind. The key distinction is whether the tool merely offers convenience or if it genuinely expands what we can know or do as humans. A simple calculator, for example, is very useful but arguably just automates a narrow mental task. ChatGPT, by contrast, can generate new ideas, text, and solutions. Such cognitive interactions can converse, explain, and create in ways that feel like having a second brain on call. When a technology begins to so vastly amplify one’s intellectual output or understanding, it starts to cross into the transhumanist realm of qualitatively enhanced capability. ChatGPT, in essence, allows a person to tap into a vast web of knowledge and a reasoning engine adjacent to any individual’s mind. That is why some have described it as a form of cognitive enhancement available to the masses, an “over-the-counter” cognitive boost that doesn’t require a PhD or a billionaire budget to use. With the right user-driven guardrails in place such as prompt engineering, ChatGPT pushes beyond the ordinary tool threshold of transhumanism and emerges more as a cognitive steroid. ## The Extended Mind Long before AI chatbots, philosophers were already arguing that tools can become literal extensions of our minds.[In a famous 1998 paper titled “The Extended Mind,”](https://consc.net/papers/extended.html) Andy Clark and David Chalmers proposed that objects like notebooks or computers, when used in the right way, are as much a part of one’s cognitive process as the neurons in one’s brain. They portray this with the case of Otto, an Alzheimer’s patient who relies on a notebook to remember important information. Otto is benchmarked against Inga, who uses her biological memory. When Inga wants to go to a museum, she recalls the address from memory. When Otto wants to do the same, he looks it up in his notebook. Clark and Chalmers argue that the notebook is a constant, trusted resource for Otto, serving the same role memory serves for Inga, and thus can be considered part of Otto's mind. As they put it, "the notebook plays for Otto the same role that memory plays for Inga. The information in the notebook functions just like the information constituting an ordinary belief; it just happens that this information lies beyond the skin". In Otto’s case, consulting his notebook isn’t fundamentally different from Inga consulting her brain since both are accessing stored information to guide their behavior. This example powerfully suggests that the mind is not limited to the brain. It can extend into the world via devices and tools, as long as they are integrated into our cognitive routines. The question then becomes: at what point does an external tool count as part of you? Philosophers have offered several criteria[https://philarchive.org/archive/RECTISv2](https://philarchive.org/archive/RECTISv2)sometimes called[the “glue and trust” conditions](https://philarchive.org/archive/RECTISv2) for when we should treat something like a notebook or by extension, an app or AI as an extension of the mind. - Reliable Availability: The tool must be reliably present and readily accessible whenever you need it . (Otto always carries his notebook everywhere he goes.) - Ease of Use: Information from the tool should be easy to retrieve almost automatically, without great effort or delay. (In practice, using the tool becomes second-nature, like recalling a memory.) - Trust: You trust the tool and accept its outputs as true, much like you trust your own memory. (Otto doesn’t doubt his notebook; if it says “MoMA is on 53rd Street,” he believes it, just as Inga believes her recollection.) - Personal Integration (Prior Endorsement): Ideally, the information in the system was placed there or vetted by you, or in some way, you’ve integrated it into your identity. (Otto wrote the notebook entries himself, so they reflect knowledge he endorsed.) When these conditions are met, the boundary between “tool” and “mind” gets fuzzy. Clark and Chalmers explain that our everyday experience fullfills this. For example, a smartphone serves as a memory bank (with our notes, contacts, calendar), a navigation system, and even a “second brain” that we consult without a second thought. In fact, by 2011, even Chalmers[noted that his iPhone satisfied at least three of the four criteria](https://philarchive.org/archive/RECTISv2) for a mind-extension device in skilled users’ hands. For many of us, losing our phone or internet connection feels like losing a part of our mind which is the extended mind thesis in action. However, building an extended mind also comes with trade-offs and caveats. One obvious issue is that external tools can fail or be wrong. If any of the “glue and trust” conditions break down such as the device isn’t available, or you suddenly doubt its accuracy then the extension breaks down. For instance, experienced GPS users[learn not to solely trust their GPS in all cases](https://philarchive.org/archive/RECTISv2). They stay alert to correct it when it inevitably makes mistakes or loses signal. Only with skill and critical oversight can a GPS become a helpful extension of one’s navigational mind, rather than a mindless crutch. The same caution applies to AI assistants. Over-reliance on an external memory or skill[https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/](https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/)can lead to [cognitive atrophy](https://arxiv.org/pdf/2506.08872v1) where we might stop exercising our own memory or problem-solving abilities, becoming too dependent on the tool. Psychologists have observed this with[phenomena like the “Google effect”,](https://time.com/69626/who-needs-a-memory-when-we-have-google) where people are more likely to forget information that they know they can just look up online. In other words, when a tool is always at hand,[we offload mental work to it, which is great for efficiency, but might leave our natural abilities underdeveloped or prone to atrophy.](https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf) There’s also the risk of false confidence, if the tool feels like part of your mind ,you might accept its outputs uncritically as if they were your own thoughts. With something like ChatGPT, as we’ll discuss, this is a double-edged sword as it can deliver brilliant insights, but also confident-sounding nonsense also known[https://www.ibm.com/think/topics/ai-hallucinations](https://www.ibm.com/think/topics/ai-hallucinations)technically by AI researchers as[hallucinations.](https://www.ibm.com/think/topics/ai-hallucinations) An extended mind must therefore be built on trust and verification. We have to cultivate good “cognitive hygiene” and guardrails with our tools. It is important to know when to trust the AI and when to double-check, much as a good driver knows when to ignore a misleading GPS route. Abiding as a simple “left turn” could be deadly. The ideal is a balanced partnership where the external aid contributes knowledge or speed, and the human contributes oversight and contextual judgment. ## ChatGPT as a Cognitive Extension Alas the king… ChatGPT, the AI chatbot that launched in 2022, that is synonymous with the word AI itself. If any digital tool has the potential to act as a mind extension, ChatGPT is a prime candidate. It often satisfies the key conditions we listed. Availability: If you have an internet connection, ChatGPT or similar models built into apps and devices is available 24/7, ready to answer questions or generate ideas on demand. Ease of use: Absolutely, you just converse in plain language, and it responds within seconds. People have found it astonishingly easy to integrate ChatGPT into workflows by asking it to brainstorm topics, explain tricky concepts, draft emails, debug code, etc. Trust: This is where it gets sticky; we’ll address its pitfalls soon, but many users do report that after some experience, they develop a sense of when to trust the AI’s answers for example, on a familiar topic or coding task and when to be cautious like when it confidently states an obscure “fact” that could be wrong. ChatGPT is often described as “having a super knowledgeable friend always at hand,” which indicates a high level of trust in the tools guidance. Personal integration: Unlike Otto’s notebook, you didn’t personally write all of ChatGPT’s knowledge store – it comes pre-trained on vast swaths of the internet. However, you can customize the interaction by giving it your context, preferences, or writing style. Over time, the AI’s outputs might start to reflect your own way of thinking or the directions you nudge it toward, creating a kind of feedback loop between your mind and the AI. For example,[ChatGPT’s Latent Memory feature](https://openai.com/index/memory-and-new-controls-for-chatgpt/) makes that augmentation concrete. It quietly retains key details from past conversations, your projects, preferences, and stylistic quirks and uses them to shape future responses. As the model “gets to know” you, a slice of your working memory is effectively outsourced to the chat history, deepening the extended-mind partnership. In effect, when someone uses ChatGPT regularly, it can become a personalized cognitive aide, augmenting their natural abilities. Empirically, we are already seeing how AI tools boost human cognitive performance. A recent experiment at MIT had hundreds of professionals work on writing tasks (emails, reports, etc.), with half given access to ChatGPT and half working solo. Those with ChatGPT finished their tasks [40% faster, and their output was rated ~18% higher in quality](https://news.mit.edu/2023/study-finds-chatgpt-boosts-worker-productivity-writing-0714). In other words, the AI made people both quicker and better at their work. Interestingly, it was the weaker writers who benefited the mos[t](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) as ChatGPT helped close the skill gap between people, acting as an equalizer. This suggests that AI isn’t just a fancy convenience but rather can fundamentally alter someone’s cognitive productivity. In creative domains, anecdotal evidence shows AI sparking new ideas. Writers use ChatGPT to overcome writer’s block or generate plot ideas. Coders use it to learn new programming techniques on the fly. Students (unfortunately) use it to get instant explanations of complex topics. In many cases, people report that these tools help them achieve results they couldn’t have achieved (at least not as easily) on their own. For example, a non-programmer building a simple app with ChatGPT’s help, or a novice writer producing a polished essay by iterating with the AI. All of this aligns with the notion that ChatGPT can act as a cognitive amplifier. It extends what we know, effectively giving an individual access to a composite of Wikipedia, a librarian, a tutor, and a creative partner all at once.[https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71](https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71)Little wonder that some have likened it to a[“bicycle for the mind”](https://youtu.be/ob_GX50Za6c?si=ZtLpWPlJxN4OlpWH&t=71) (to borrow Steve Jobs’ old phrase for computers) except now the bicycle sometimes feels more like a jetpack. As AI copilots absorb the repetitive or low-level pieces of knowledge work, our top performers no longer rise by raw technical ability alone; they graduate from hands-on specialists to orchestrators. And in a world shifting from specialization to orchestration, these orchestrators hold the keys: they design the workflows, craft the prompts, select the data sources, and synchronize human talent with machine agents into a seamless whole unlocking outcomes no single expert could achieve in isolation. The dawn of the orchestrator Highway to the Danger Zone That said, we must also address the drawbacks and dangers of relying on such AI extensions. Perhaps the biggest issue with current generative AI is that it can be too confident for its own good. ChatGPT doesn’t actually “know” facts in the way we do. It predicts plausible answers based on patterns in data. This means it sometimes produces fabrications that sound perfectly credible what we call “hallucinations” as described previously. For example, ChatGPT might cite studies or laws that don’t exist, or assert health facts that are utterly wrong but seem right. These inaccuracies are so common that researchers have given them a nickname and are actively studying why they occur. If a user treats ChatGPT’s output as gospel, trusting it like an infallible memory, they can get into trouble. A now-infamous case involved[a lawyer who used ChatGPT to help write a legal brief, and the AI invented court cases to cite](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html). The lawyer, assuming the AI’s confidently presented citations were real, submitted the brief and later faced professional sanctions when the judge discovered those cases were nonexistent. In this cautionary tale we can takaway that powerful cognitive extension can mislead you if you don’t remain critically engaged. Over-trust in the AI can lead to mistakes, misinformation, or the erosion of one’s own expertise. This is why[many experts stress AI literacy and knowing the strengths and weaknesses](https://www.edweek.org/technology/ai-literacy-explained/2023/05) of tools like ChatGPT as a crucial skill for the future. Another consideration is how these tools fit into our broader cognitive habits. Do they complement our thinking or start to substitute for it? There’s a subtle but important difference between complementary and competitive cognitive aids. A complementary aid handles the tedious bits so that you can focus on higher-level thinking. For instance, using ChatGPT to perform basic data entry for you might free up time and mental energy for you to synthesize insights and make creative connections (things the AI might not do as well). In this mode, human and AI form a partnership where each does what it’s best at. By contrast, a competitive aid is one that essentially takes over a task that humans used to do, potentially sidelining the human role. If someone uses the AI in lieu of learning the basics or outsources all their creativity to an algorithm, they might be left with diminished skills and understanding. For example, if students lean on ChatGPT to do all their writing, they might never develop the ability to structure an argument themselves. The AI has “competed” with and supplanted their own cognitive growth. In the workplace, this distinction plays out as well: will AI assistants simply assist workers, or eventually replace those who don’t add unique value? Current evidence suggests that in many c[ases AI acts as a force multiplier for human talent](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) , but we can’t ignore the possibility that some jobs or skills will be rendered obsolete. Navigating this will require conscious effort and we should embrace the complementary uses of ChatGPT that let us achieve more, while guarding against over-reliance that leaves us complacent or deskilled. ## The Cyborg Question All this talk of human-machine coupling naturally leads to the image of the cyborg. The archetypal transhuman figure who is part human, part machine. So, does using ChatGPT make you a cyborg? The answer depends on how we define cyborg. Traditionally, the word means a “cybernetic organism,” implying a being with technology integrated into its body or biology. The term was originally coined in the 1960s to describe[a person whose bodily functions are aided by implanted devices or biochemical modifications](https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf) . Classic sci-fi cyborgs have robotic limbs, bionic eyes, brain implants, and so forth. By that strict definition, simply chatting with an AI on your phone doesn’t qualify. There’s no physical fusion of man and machine in the case of ChatGPT; the AI remains an external tool, not a literal part of your organic body. You could put your phone in a drawer and poof the “cyborg” abilities vanish, proving that you and the tool are separate entities. So, in the conventional sense, no, using ChatGPT does not make you a cyborg. However, some theorists have argued for a broader conception of cyborg-hood that applies to everyday life. Notably, anthropologist[Amber Case argues that we are all cyborgs now](https://www.youtube.com/watch?v=z1KJAXM3xYA) in as much as we rely on technology constantly to extend our capabilities. You might not have a chip in your brain, but if you rarely go anywhere without your smartphone (your external memory/communication device) and you use digital tools to mediate so many experiences, you are functionally a cyborg. Case points out that we use our phones and computers like “external brains” for communication and memory, effectively[becoming a “screen-staring, button-clicking new version of humans”](https://www.youtube.com/watch?v=z1KJAXM3xYA) . In this more metaphorical or sociological sense, anyone using ChatGPT as a cognitive crutch is engaging in a cyborg-like merging of human intellect with machine processing. The boundary between user and tool becomes porous during those moments of interaction. Think of how a person might say “I’ll ask my AI,” the way they’d say “I’ll think about it” – it hints that the AI has been incorporated into their cognitive loop. Some bioethicists and futurists use the term “soft cyborg” to describe people who, while not physically augmented, are so intertwined with their personal tech that it’s an extension of their self. By that view, millions of us became soft cyborgs the day we got smartphones, and tools like ChatGPT only deepen that intertwinement. Even so, ChatGPT remains an external tool unless we literally implant it or physically couple it to our bodies. It’s worth clarifying where the line would be crossed into true cyborg territory. If, for example, in a decade we have a[brain–computer interface (BCI)](https://neuralink.com/blog/building-safe-implantable-devices) that lets you query an AI with your thoughts and receive answers as instant flashes of neural input, that would pretty clearly qualify as being a cyborg. Companies[https://www.youtube.com/watch?v=Cf7rbQQBRlI](https://www.youtube.com/watch?v=Cf7rbQQBRlI)like[Neuralink are already working on high-bandwidth BCIs](https://www.youtube.com/watch?v=Cf7rbQQBRlI) that, in theory, could one day link human brains with AI systems. A less invasive route might be augmented reality glasses or contacts that overlay AI assistance onto your visual and auditory field at all times basically, an AI that’s always in your perception, not confined to an external screen. At that point, the AI starts to feel like part of your sensory system. We can also imagine AI-driven neural prosthetics or implants that aids memory, or a language chip that provides real-time translation of foreign languages in your head. Those blur the line between user and device in a much more intimate way than a chatbot app does. ChatGPT, as amazing as it is, still lives in the cloud, you have to physically query it, and there’s a clear boundary (the interface, the screen) where information passes from machine to you. In cyborg terms, it’s one step short of full robocop. So, calling ChatGPT users full “cyborgs” is mostly a playful metaphor hinting at the near future. A true cyborg enhancement becomes a part of you even when you’re not consciously thinking about it. One might argue like a pacemaker that keeps your heart rhythm steady, or a cochlear implant that continuously provides hearing. In summary, using AI like ChatGPT moves us toward a cyborg-like existence in a philosophical sense, but it doesn’t make us cyborgs in the literal, physical sense. For that next leap, we’d need tighter integration at the physical level, at the current phase reliably consulting AI still largely requires skill. ## The Haves and the Have-Nots: Access and Inequity in AI If ChatGPT represents a sort of mass-market, over-the-counter cognitive enhancement, we should ask: Who gets to benefit from it? Historically, one concern in transhumanist technologies is that they might create a divide between the “enhanced” and “unenhanced”. For example, only the rich affording life-extending tech or brain boosts. With ChatGPT, the financial barrier is actually relatively low as the basic version has been offered free, but that doesn’t mean access is truly equal. First, there’s the straightforward digital divide: not everyone has a reliable internet connection or a modern device to use AI on. Billions of people still lack broadband access, and even within wealthy countries, underserved and rural communities may struggle with connectivity. Hardware and infrastructure are the baseline requirements for entry into this augmented world. However, as observers note, a new divide is emerging that goes beyond just owning the tech – it’s about knowing how to use it effectively. Some have started calling this the AI literacy gap, akin to digital literacy but focused on understanding and working with AI. In other words, two people might both have internet access, but if one knows how to craft good prompts, interpret the AI’s output, and integrate it into their tasks, while the other is intimidated or unskilled with the AI, the first person will gain a significant advantage. We’re already seeing this in educational settings and workplaces. Students with strong guidance on using AI can produce better projects and learn faster, whereas those left unguided might either misuse the tool (e.g. simply plagiarize answers they don’t understand) or avoid it altogether out of fear. Similarly, a professional who adapts quickly to using AI tools may outshine colleagues who stick to older methods. This raises the concern that[AI could exacerbate existing skill and socioeconomic gaps](https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf). Those who are digitally privileged having not just access but also the savvy to use technology can surge further ahead, while others lag behind. Model Access Another subtle access issue is the difference between the free versions of AI and the most advanced versions. For instance, OpenAI offers a paid subscription to ChatGPT Plus (with access to more powerful models like GPT-4). Organizations and individuals who can pay for premium AI will get significantly better results, more accurate, less hallucination-prone, with advanced features compared to those using only the free model. Over time, if cutting-edge AI remains behind paywalls, we could see a situation where wealthier users effectively have a “stronger cognitive enhancement” than others. This is not unlike healthcare disparities, except here it’s an intelligence tool. It’s easy to imagine a future where businesses invest in top-tier AI for their employees, training them in its use, and thereby dramatically increasing their output, while smaller firms or workers without such resources fall behind. However, as a hedge, [open source models like deepseek](https://techcrunch.com/2025/05/09/deepseek-everything-you-need-to-know-about-the-ai-chatbot-app/) have done the unthinkable with launching free models which could be run locally on a person's own computer. Though, enterprise grade hardware is required to run these full models to even spit out a simple question. So, how do we address these gaps? AI literacy education is one key. Just as basic computer literacy became essential over the past few decades, knowing how to interact with AI should become a widely taught skill. This includes understanding AI’s limitations and ethical considerations, not just technical know-how. Initiatives are already calling for[integrating AI training in schools and community programs.](https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers) For example, learning how to fact-check AI or use it to assist (not replace) one’s learning could be built into the curriculum. Public libraries and online courses can play a role in democratizing knowledge about AI tools, so it’s not confined to tech specialists or elite institutions. Policymakers and organizations like UNESCO have begun discussing “AI literacy as a human right” in the digital age, emphasizing that without proactive measures, AI could deepen inequality rather than alleviate it. On the infrastructure side, continuing to expand internet access is obviously crucial as every new person brought online is a potential new beneficiary of tools like ChatGPT. There’s also a case to be made for public interest AI: ensuring that advanced AI models are available in forms that the public and underprivileged communities can access perhaps via open-source models or government-provided AI services, rather than having all the best AI locked behind corporate gates. In summary, ChatGPT offers a glimpse of a future where cognitive augmentation is widespread, but making that future equitable requires conscious effort. Otherwise, we risk a scenario where some minds get much “bigger” with AI help, while others are left behind in the pre-AI paradigm, widening the gulf in opportunity. The notion of transhumanism often dwells on individual enhancement, but we have to broaden that: true progress will be if these enhancements uplift as many people as possible, not just a tech-savvy few. ## Conclusion: A Mind in the Making We stand at a peculiar moment in human history. The tools we've created to extend our minds have become so powerful that they force us to reconsider what it means to be human in the first place. ChatGPT isn't just another productivity app; it's a mirror that reflects our evolving relationship with intelligence itself. The central tension this essay has explored is not whether ChatGPT makes us transhuman (by most definitions, it doesn't), but rather what it reveals about the porous boundary between tool use and cognitive enhancement. When a technology integrates so seamlessly into our thinking processes that we struggle to separate our thoughts from its suggestions, we've crossed a threshold that demands new frameworks for understanding human capability. Three critical tensions emerge from this analysis: First, the enhancement paradox: ChatGPT simultaneously amplifies our abilities and threatens to atrophy them. We become more capable while risking dependence. The solution isn't to reject these tools but to develop new forms of cognitive hygiene: practices that maintain our intellectual muscle tone even as we delegate routine mental labor to AI. Second, the equity challenge: Cognitive enhancement through AI could either democratize intelligence or create new hierarchies of the augmented versus unaugmented. The determining factor won't be the technology itself but how we structure access to it and, more importantly, education about its effective use. AI literacy may become as fundamental as traditional literacy, yet we're barely beginning to understand what that means. Third, the agency question: As we transition from specialists to orchestrators, we must guard against becoming mere operators of intelligent systems. True agency in the age of AI means maintaining the ability to think independently, to question AI outputs, and to synthesize insights in uniquely human ways. We must be conductors, not just audience members, in the cognitive symphony. Perhaps the most profound insight is that we've been augmenting ourselves all along: through writing, mathematics, computers, and smartphones. ChatGPT simply makes this augmentation impossible to ignore. It strips away the comfortable fiction that our tools are separate from our thinking and forces us to confront what we've always been: tool-using animals whose intelligence is distributed across our technologies. The question isn't whether to embrace or resist this augmented future. It's already here. The question is how to shape it consciously. We need new ethical frameworks that account for distributed cognition, educational systems that teach orchestration alongside traditional skills, and a renewed commitment to human agency even as our tools grow more powerful. In the end, ChatGPT offers us a preview of a future where the boundaries between human and artificial intelligence blur not through physical merger but through cognitive partnership. How we navigate this partnership with wisdom, equity, and intentionality will determine whether these tools amplify our humanity or diminish it. The choice, as always, remains ours. References Bajarin, T. (2014, April 21). Who needs a memory when we have Google? Time.[https://time.com/69626/who-needs-a-memory-when-we-have-google](https://time.com/69626/who-needs-a-memory-when-we-have-google) Bostrom, N. (1998). A history of transhumanist thought.[https://nickbostrom.com/old/transhumanism](https://nickbostrom.com/old/transhumanism) Bostrom, N. (2005). Transhumanist values. Ethical Issues for the Twenty-First Century, 3–14. https://nickbostrom.com/ethics/values.pdf Brynjolfsson, E. (2022). The Turing trap: The promise & peril of human-like artificial intelligence. Daedalus, 151(2), 120–146.[https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf](https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Sp22_19_Brynjolfsson.pdf) Clark, A., & Chalmers, D. J. (1998). The extended mind. Analysis, 58(1), 7–19.[https://www.consc.net/papers/extended.html](https://www.consc.net/papers/extended.html) Clynes, M. E., & Kline, N. S. (1960, September). Cyborgs and space. Astronautics, 26–27.[https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf](https://web.mit.edu/digitalapollo/Documents/Chapter1/cyborgs.pdf) Education Week. (2023, May 17). AI literacy, explained.[https://www.edweek.org/technology/ai-literacy-explained/2023/05](https://www.edweek.org/technology/ai-literacy-explained/2023/05) Ghanem, K. (2025, May 9). Instagram face & BBL baddies—Welcome to the first wave of transhumanism. Mille World.[https://www.milleworld.com/instagram-face-bbl-baddies-welcome-to-the-first-wave-of-transhumanism/](https://www.milleworld.com/instagram-face-bbl-baddies-welcome-to-the-first-wave-of-transhumanism/) Hauser, C. (2023, May 27). Avianca lawsuit shows perils of citing A.I.-generated cases. The New York Times.[https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html](https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html) IBM. (2023, September 1). What are AI hallucinations?[https://www.ibm.com/think/topics/ai-hallucinations](https://www.ibm.com/think/topics/ai-hallucinations) Maiberg, E. (2025, February 10). Microsoft study finds AI makes human cognition “atrophied and unprepared.” 404 Media.[https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/](https://www.404media.co/microsoft-study-finds-ai-makes-human-cognition-atrophied-and-unprepared-3/) Mentat. (n.d.). In Dune Wiki. Fandom. Retrieved May 26, 2025, from[https://dune.fandom.com/wiki/Mentat](https://dune.fandom.com/wiki/Mentat) More, M. (1990). Transhumanism: Towards a futurist philosophy [White paper].[https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf](https://www.ildodopensiero.it/wp-content/uploads/2019/03/max-more-transhumanism-towards-a-futurist-philosophy.pdf) Noy, S., & Zhang, W. (2023, June 7). The productivity effects of generative artificial intelligence. VoxEU/CEPR.[https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence](https://cepr.org/voxeu/columns/productivity-effects-generative-artificial-intelligence) OpenAI. (2024, February 13). Memory and new controls for ChatGPT.[https://openai.com/index/memory-and-new-controls-for-chatgpt/](https://openai.com/index/memory-and-new-controls-for-chatgpt/) PhilPapers. (n.d.). Transhumanism. In PhilPapers. Retrieved May 26, 2025, from[https://philpapers.org/browse/transhumanism](https://philpapers.org/browse/transhumanism) Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778.[https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf](https://scholar.harvard.edu/files/dwegner/files/sparrow_et_al._2011.pdf) UNESCO. (2025, February 12). What you need to know about UNESCO’s new AI competency frameworks for students and teachers.[https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers](https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers) YouTube. (2025, February 15). Microsoft research discovers AI atrophies cognitive confidence [Video]. YouTube. --- # Left Curve | XRP Memecoin Onboarding 101 > Loose thoughts on memecoin onboarding for the left curve. Educational purposes only. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: DeFi - Published: 2024-12-02 - Canonical: https://shoal.xyz/research/writing/left-curve-xrp-memecoin-onboarding/ - Keywords: crypto, DeFi, MEV, infrastructure, Solana, Ethereum, Bitcoin This is for educational purposes only and does not constitute financial advise, these are my loose thoughts put on paper and NOT an endorsement of any dex, bot, or coins. ## Intro | Lets get this out of the way I can’t describe how bearish I am on XRP's institutional adoption as remittance in the long term. Not to mention the CEO publicly fudding Bitcoin on multiple occasions. The list of infractions is so long it’s not even worth the time to go through it. Just a year ago, mentioning XRP on crypto Twitter would have gotten you socially shunned and ostracized —sorry, Raoul. But price action changes everything, and the XRP army is finally having their moment. Today, they’re having their day. [https://x.com/raoulgmi/status/1863358055469002807?s=46&t=txFAbiSPTdLLDlAYj9X_AA](https://x.com/raoulgmi/status/1863358055469002807?s=46&t=txFAbiSPTdLLDlAYj9X_AA) ## Rules To continue this article, you need to put your left-curve hat on or close the app—simple as that, because this won’t be for everyone. Back during the 2021 bull run, I was absolutely bombarded by normie friends asking about DOGE and SHIB. I told them to focus on “real applications” like ETH. While that advice wasn’t necessarily bad, the real opportunity was, in fact, DOGE and SHIB, purely based on the sheer size of inbound interest which was THE SIGNAL. At that time, I was speaking instead of listening. This time, I’m listening as normie retail rally cry rings through the halls as they tell CT exactly which coins they’re selecting. ## Thesis The thesis is simple and unapologetically degenerate: XRP is the 4th largest coin—scratch that—XRP is the 4th largest ecosystem coin by market cap. This marks a significant shift, in narrative. The original XRP thesis centered on banking remittance, but the real window of opportunity (which could be short lived) now lies in the ecosystem. Specifically, it's about the memecoins launching on XRPL, the smart contract platform. The XRP community is arguably the most cult-like in the cryptospace, rivaled only by Bitcoin holders. Figure A: Don't you just love the quadrillion dollar tiktok market cap shills 😍 [https://x.com/altcoingordon/status/1862871207147622493?s=46&t=txFAbiSPTdLLDlAYj9X_AA](https://x.com/altcoingordon/status/1862871207147622493?s=46&t=txFAbiSPTdLLDlAYj9X_AA) Despite a consistent downtrend since 2018, they somehow continue to attract new ecosystem participants. This resilience is largely fueled by the euphoria of 2018, which left a lasting impression on sidelined onlookers, many of ones I know personally keep asking me about XRP. Fast forward to today, and many retail investors returning to the space are gravitating toward the coins they remember from their past experiences. ## 2018 alts ripping | Retail is back [https://x.com/blknoiz06/status/1862587895921483847?s=46&t=txFAbiSPTdLLDlAYj9X_AA](https://x.com/blknoiz06/status/1862587895921483847?s=46&t=txFAbiSPTdLLDlAYj9X_AA) As a top 5 market cap coin, the question arises: where does all the idle money go? XRP lacks native staking, and its DeFi ecosystem remains "underdeveloped", with much activity confined send and receive and hodling. This begs the critical question: where does the money flow when idle hands are looking for action? With limited options, these participants are likely to chase the next 100x memecoin opportunities, turning to speculative trading out of necessity rather than choice. ## The Play The play is straightforward: capitalize on memecoins and trading infrastructure within the ecosystem. Just as memecoins drove activity on Solana, fueling the growth of DEXs like Raydium, Jupiter, and even Jito with its MEV capture and network tips, the same dynamic could unfold on XRPL. ## Buying coins on XRPL 101 ## Option: 1 First Ledger Bot To buy coins *easy* you need to use the @First_Ledger telegram bot. You can send XRP coins directly from an exchange like coinbase, binance etc. Posting 3 times to emphasis the referral code SHILL 1. [https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01](https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01) 2. [https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01](https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01) 3. [https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01](https://t.me/firstledger_bot?start=ref_Kd12wTPQkH01) Contract addresses Without getting into the technicals the best way to pull a CA and paste it into a bot is getting the address from the URL on dexscreener. Dexscreener SOMETIMES keeps the URL in case sensitivity when it is pulled. For some reason First ledger requires case matched, so paste that part of the URL into XRPscan to easy pull the case sensitive version (case means capitals included). This may update change overtime but you get the gist. https://xrpscan.com/account/rGHtYnnigyuaHehWGfAdoEhkoirkGNdZzo This is the contract from a URL: https://dexscreener.com/xrpl/7363726170000000000000000000000000000000.rghtynnigyuahehwgfadoehkoirkgndzzo_xrp Case sensitivity matters with the bot 1. Good: rGHtYnnigyuaHehWGfAdoEhkoirkGNdZzo 2. Bad: [rghtynnigyuahehwgfadoehkoirkgndzzo](https://dexscreener.com/xrpl/7363726170000000000000000000000000000000.rghtynnigyuahehwgfadoehkoirkgndzzo_xrp) ## Note: 10 XRP hold When creating a new wallet there is a 10 XRP hold on all new wallets and this is used to prevent network spamming. when you delete the wallet you get the 10 XRP back. I wouldn't mess with this - its the cost of doing business, pay the fee and keep the wallet. First Ledger Debugging and Fixes - People have had issues setting up a wallet (Wait for fix or use option 2) - People having issues with buying on mobile (Wait for fix or use option 2) ## Option: 2 Xaman wallet + xmagnetic webapp As a two part second option, you can use the @XamanWallet wallet with the @MagneticXRPL web application, and you can execute trades on mobile by bringing up the xMagnetic mobile webapp on browser, which will pair with your [@XamanWallet](https://x.com/@XamanWallet) on mobile. This setup allows you to execute trades on mobile without using the Telegram bot. 1. Xaman wallet: [https://xaman.app/](https://xaman.app/) 2. Xmagnetic: [https://xmagnetic.org/?network=mainnet](https://xmagnetic.org/?network=mainnet) ## Friendly Note Liquidity is low, and the charts swing wildly. If you pick a strong memetic play, give it some room to breathe. These coins can drop 50% and rebound multiple times within just a few hours. Rugs are everywhere and likely 99% of coins will rug at some point. ## Conclusion I mentioned how bearish I was on XRP as remittance. As a meme ecosystem, this is a fundamentally degenerate play, since the idle value can now flow into new speculative assets, kicked off by XRP price action. The users are here already, same as the ton play. But wait.. if you are bullish XRP memes, are you bullish XRP? Wouldn't it be funny if enough meme value catalyzes the development of a robust XRPL ecosystem. ggs chat --- # Are Memecoins Capped? > A thought experiment on the flows of capital in memecoins as tokenized culture and attention. - Publisher: Shoal Research (https://shoal.xyz) - Author: Gabe Tramble - Category: DeFi - Published: 2024-11-21 - Canonical: https://shoal.xyz/research/writing/are-memecoins-capped/ - Keywords: crypto, tokenization, Solana, Ethereum, Bitcoin, DeFi A thought experiment on the flows of capital in meme coins. ## Key Takeways: - Meme Coins as Tokenized Culture: Meme coins represent tokenized attention and culture, enabling financial engagement with social symbols. - Low 'Switching Costs': Transitioning between meme coins is effortless, driving users toward newer opportunities over established ones in a loop. - Preference for New Narratives: Users consistently favor entirely new meme coins over older, established ones, even those from just months earlier. - Fountain Effect of Liquidity: Liquidity rotates seamlessly between new coins and trends, fueling the speculation. - Smaller Valuations Likely: Dozens of meme coins reaching $1 billion valuations are more likely than a few hitting $100 billion. ## Tokenized Attention Memecoins, which represent tokenized attention and culture, allow users to speculate on the growth of a social symbol or financially engage with that symbol. These assets are beginning to reveal patterns reminiscent of past cycles in crypto history—particularly the "killer narratives" that sought to upgrade the original generation of assets. For example, we witnessed the rise of Bitcoin forks and so-called "Bitcoin killers." This narrative also played out with Ethereum versus Bitcoin and, more recently, Solana versus Ethereum. There will always be new technologies and communities arguing that their newer, shinier, and faster models are superior to the incumbent. In the case of utility-based assets, fundamentals such as adoption, user growth, and real-world use cases play a significant role in determining the success or failure of these new entrants. However, for meme coins, the dynamics are markedly different. ## Low switching costs Meme coins present an intriguing dichotomy: they are a stance against high valuation “VC” coins but their switching costs are extraordinarily low. Transitioning from one meme coin to another requires little more than a few clicks. Because of this minimal friction, the decision to switch from one meme coin to another is often more ideological than technical. The abundance of meme coins further amplifies this effect, as users are incentivized to seek out newer, smaller meme coins with the potential for explosive early growth rather than committing to an older, established one. This phenomenon creates an ecosystem where constant creation and speculation dominate, making meme coins distinct from their utility-driven counterparts. While the underlying motivations and dynamics differ, the broader narrative of innovation versus incumbency continues to shape the crypto landscape. This leads one to ask: Are meme coins more psychologically capped than we might think? New entrants are likely to prefer chasing entirely new narratives rather than adopting older, established coins from a different "generation"—with generations in this context being time periods as short as six months apart. ## Memecoin “Fountaining” - Psychological Cap on Valuations The prevailing consensus suggests we'll see multiple meme coins reach valuations of $100 billion. However, I propose a different scenario: it's far more likely that we'll see dozens of meme coins each hitting $1 billion valuations instead. This is primarily because liquidity could continuously rotate into new coins, trends, and memes, creating a "fountain effect" of liquidity moving from coin to coin. The low switching costs make this rotation seamless, reinforcing the speculative flow of capital. In fact, launching new coins are so easy that we ended up with 13-year-old meme coin developers. [https://x.com/damskotrades/status/1859143525595517345](https://x.com/damskotrades/status/1859143525595517345) I would argue that NFTs are a form of memes where the story or social context behind the NFT is the meme itself. During the 2022 meme euphoria, traders were using small, newer launches to generate cash flow to purchase higher-prestige or higher-class meme coins and NFTs. Essentially, there was a trade-up system where the gold-tier, top-tier NFTs were CryptoPunks and Bored Apes, and successful traders would ultimately end up with one of these top-tier assets. Whereas with tokenized memecoins, there isn't an affinity or prestige in holding Doge over some new speculative theme or coin. It may be the case that market dynamics for meme coins push value horizontally, enticing new participants into the ecosystem instead of consolidating around strong winners as seen traditionally, thus creating a synthetic ceiling. --- # Value Accrual in the Agent Economy: Visa's Head of Crypto on Stablecoins, x402/MPP, and Card Networks > Shoal Signal episode. Guest: Cuy Sheffield (Visa). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-07-07 - Video: https://www.youtube.com/watch?v=LLvU0RK9WV4 - Canonical: https://shoal.xyz/research/episodes/visa-value-accrual-agent-economy/ - Keywords: agentic economy, AI agents, agentic payments, x402, stablecoins, crypto, infrastructure, Agentic Payments, AI & Agents, interviews ## Transcript **Gabe Tramble (00:01):** So Kai, tell us if stable coins are internet native money and agents are basically the internet native buyers, then where does the value accrue in this entire equation and and stack? **Cuy Sheffield (00:16):** Yeah, it's it's the trillion dollar question. I think it's so early that you know nobody knows. But I I think a few principles that we have here are we believe stable coins are amazing next generation infrastructure. And you know, the ability you know to have blockchain networks that can move value, you know, twenty-four seven across the world that are programmable, you know, that have a low barrier, you know, to entry to be able to spin up a wallet, interact with. Yeah, I think is fundamentally amazing for you know the increasing the velocity of money, bringing more people into digital payments and the financial system. I think all of that is is incredible. But on the other hand, we don't look at stable coins and blockchains as payment networks. Payment networks are fundamentally different than payment infrastructure because a payment network, it's it's not just about the technology. It's not just about the protocols, it's about the governance and the risk and the rules and the controls and what happens when things go wrong. And I think that's where, you know, when we look at at protocols like X402 and MPP and we're incredibly excited about them and we think that they're going to play a big role. We don't think that the the protocol themselves is complete as a payment network. We think that there need to be layers built on top of these protocols, you know, that can actually commercialize them and bring them, you know, to many, you know, more people and and customers. And and I think today, you know, by all means like a gentic commerce just doesn't exist like at any scale. Like we've got like the the bones and the kind of the early foundations, but there's just so much more to be built on top of it. And so, you know, I think that there's a a massive opportunity. you know, for new payment products, ⁓ you know, to be able to to take what X42 and MPP have as a protocol sense and be able to commercialize and enable kind of networks with governance and trust and structure, you know, that can actually move value on top of those protocols. So ⁓ that that's my my initial take. **Gabe Tramble (02:28):** In okay, so this this network layer, right, which which you're saying is is native to almost like these fiat card systems, right? Wha can you kind of differentiate where the value is in cards and then where the value is in stables because there's like the the the way that people are thinking about this is it's almost one or the other, but you guys are at an interesting intersection where you're adopting both at the same time. And yeah, can you just help us understand more this this network versus ⁓ infrastructure piece? **Cuy Sheffield (03:02):** Yeah, I I think anytime people kind of position it as you know stable coins versus cards, it's just such like a a zero-sum thinking at the very beginning of this like you know potentially enormous new space. And and we very much believe it's it's and and that you know both stable coins and cards will play a major role in the future of agentic payments. I think there are yeah perhaps you know different use cases and different client segments, but like increasingly we believe stable coins are one of the best backend infrastructure pieces for payments. And cards and networks like Visa are gonna continue to be one of the best front end ⁓ payment networks you know that both consumers and increasingly agents you know in the future will interact with. ⁓ and so I think like the back end piece of of what stable coins do is they actually enable the money to move and you know frictionless you know movement of money and being able to do it, you know, 24 seven, not having bank holidays and Doing it in a programmable way is is great. But I think the the missing piece is as I mentioned before, it's it's the trust in the governance. Yeah, it's knowing that, you know, if I'm gonna transact with a merchant, someone has vetted that merchant, someone is taking responsibility for that merchant. If something goes wrong, you know, there's going to be, you know, either some way that I can, you know, get my money back. Or some way that prevents that merchant from continuing to scam other people. And so I think there's both this trust element as a consumer. When I see a merchant that accepts Visa, you know, I know one, I've got an expectation the transaction's gonna work. Like that, that's the first thing. And then two, I know that that merchant has been vetted. And I know if something goes wrong, like there's going to be a set of clear rules and processes in place, you know, to to make that right. And I think what that does is that lowers the mental transaction cost. Where if I see something I like, I just buy it. I don't have to think about the payment. It fades into the background. And I think that the challenge that stable coins have right now, which is just kind of the general property of crypto, in being an open public, permissionless network that anyone can interact with, it doesn't solve that trust problem where you know, take X402, for example. Anyone can create an endpoint on X402. And so if your agent is looking to transact with a merchant, You know, they can find an endpoint. Well, what if that endpoint is run by a company that you don't want to interact with, that you don't want to pay? And you know, maybe that's yeah, someone that's in a sanctioned you know country, maybe that's somebody that you know is unlawfully you know selling what those goods are? Like there's no nothing stopping someone from standing up a merchant endpoint. What if I buy something from that endpoint and I don't get what I bought? What could I do? What prevents that you from happening again to somebody else? ⁓ what if that merchant endpoint? **Gabe Tramble (05:54):** Mm-hmm. **Cuy Sheffield (05:57):** Isn't even selling a good or service? What if that merchant endpoint is just malicious software that's trying to get me to interact with it? So it can prompt eject me. Like there are all of these things that when you have an completely open permissionless ecosystem, while it's great that it brings people on and enables like, you know, any individual could stand up a merchant endpoint. I think it's really important if you're actually gonna scale commerce to know that you can trust that merchant endpoint. And so that's what we're really focused on of like, how do you add a trust perimeter? **Gabe Tramble (06:21):** Uh-huh. **Cuy Sheffield (06:26):** And kind of a trusted layer and network that can then sit on top of those protocols. And I think that that's the role that that Visa plays. And then, you know, on the other hand, you know, I'm a crypto guy. I've been in crypto for for close to 10 years now. And like I get nervous about giving agents a stable coin wallet. There are just fewer controls that are in place. And an agent managing a private key and like you know, what happens if if things go wrong, the money's gone, it's a bare asset, like you know, there's nothing I can do. Being able to give an agent a card. **Gabe Tramble (06:37):** Yeah. **Cuy Sheffield (06:55):** We believe is a better experience because you can have controls at the CLI wallet layer, you can have controls at the issuing layer, you can have controls at the network layer. And so you just have these multiple lines of defense, you know, that prevent this scenario of you just lose all your money, which I think we're in this point where it's the frontier, people are trying a bunch of things out. But if this is actually going to go mainstream, there's more of a need than ever for trust and for a place that you know the merchants can be trusted and that you know that. **Gabe Tramble (07:20):** Mm-hmm. **Cuy Sheffield (07:25):** If something goes wrong, you know, there are protections in in place to pre **Gabe Tramble (07:29):** Yeah, yeah, that that's that's interesting. And you and you guys have basically decades of this trust to to lean on to and ⁓ at the same time like embracing these new novel primitives like X World Two and and some of the other ⁓ agenc commerce infrastructure. The with that in mind, if you were not at Visa and let's say you're a builder, knowing what Visa is doing in the space, ⁓ what would you not build? **Cuy Sheffield (08:00):** What would you not build? Interesting. I think a lot more about like what what people you know should build. ⁓ I I think it's it's very, very hard to build new payment networks and to build that trust and acceptance that it's taken us yeah decades to do. And so yeah, anytime someone says, Okay, I've I've got a better technology, it's it's faster and cheaper and it's programmable, so so we're gonna you know displace Visa and like Visa's value, you know. Only a small fraction of it is the technology. Like it's how do you coordinate and get you know the largest entities in the world to align on a single set of rules and standards and you know to cooperate around those while still competing, you know, with each other. That's a a ⁓ much, much harder thing to do. ⁓ and so I think that that the trust and coordination piece is not something that, you know, a startup that is you know a single entity. you know, is able to to really solve, you know, at at a global scale. I I think it's it's makes a lot more sense to be on one side or or the other of the network. I think there's a massive opportunity in building new merchant endpoints ⁓ and creating what are the next generation of headless merchants. I think you could take a look at pretty much every you know SaaS service out there, and you know over some time, many of those services are are gonna have to go headless. They're gonna have to become accessible And be kind of thin, super lightweight, easy endpoints that you can then purchase inside of any agent harness that you want to be in. And I think the interesting question is gonna be, well, are some of those SaaS providers gonna kind of decapitate themselves and and go headless and say, All right, you know, we're gonna meet customers there and we're seeing Salesforce and and some others. But I think that there's SaaS in in the kind of the software market is so big that there will be plenty of incumbents that you know they just can't operate in that structure. It's just it It's not the core model that they were built for of, you know, seat based pricing and enterprise sales and like fancy dinners and like that. That's like a lot of how software is sold. And so I think there's this huge opportunity to create, you know, valuable software products, ⁓ that are just built for agents, you know, on day one that are these headless merchants that are accessible, you know, over those protocols. So I think that that's like one of the biggest opportunities, you know, right now. ⁓ and and then I think the other piece of it, which curious what you've seen is a lot of the X402 endpoints today, I think are like a a single tool. And I think at the end of the day, a lot of it's a lot harder to sell a tool than it is to sell a workflow. And so I think it's really how do you combine together and compose different services and different endpoints to create something that is a lot easier for people to understand and consume. And I think we're still in this phase of there are thousands of tools **Gabe Tramble (10:47):** Mm-hmm. **Cuy Sheffield (10:52):** But a lot of people don't really know how to use them. And so can you actually, you know, even if it's starting with the existing X42 endpoints out there, create a product that combines those endpoints into an actual workflow and then being able to sell that workflow? I think those are two of the biggest opportunities right now for earlier stage companies to be able to come in and have an impact. **Gabe Tramble (11:13):** That's super interesting. Yeah, I I I definitely agree with you. The the X the at least the value that I've seen for X402 right now, today, is mostly on the prospecting side. So if you're trying to, you know, find emails or customers or phone numbers, et cetera, the value is there, but it's still super long tail. And and to your point of the the opportunity, I know ⁓ Merit Systems who who makes agent cash and ⁓ Locus Pay. Locus Pay like a YC pa agent pay provider, same as ⁓ agent cash. They both are basically bundling ⁓ endpoints to have like these specialized ⁓ ⁓ services. So if it's like, you know, social media services, then it bundles like all these different social media platforms or you know, prospecting and it bundles, but I haven't seen the workflow itself of basically ⁓ giving the agent a skill, I guess. So they are doing the skills, but there's no kind of like robust packaging of this that that I've seen so far. So that's pretty interesting. **Cuy Sheffield (12:16):** Yeah. So I think that's super consistent with you know I've had a bunch of conversations in the last two weeks ⁓ with you know different merchant endpoints, merchant endpoint providers. And I think that that's a a common theme of you know, it's like go to market in sales, you know, prospecting, generating leads, like that. That's one of the areas that there is some kind of real, very early organic traction. And so I think it's it's a natural direction to go to try and stitch together endpoints into a workflow or something that a salesperson you know can use. So I think that's on the supply side. On the demand side, I think right now that's that's kind of the bigger problem, you know, of just there's not a ton of easy demand you know coming into these these endpoints, despite there are some like very useful endpoints. And so the question is like, how do you a hundred X the growth of the demand side of people that can access and and kind of pay as they go? And I think there are a few different approaches that are are being tried. And I think one approach is we'll just create new front end interfaces. And you know, I love what Meredith is doing with Poncho. I think that's a super interesting interface that is like a harness that's kind of built in of being able to to run these workflows. Tripstack and others, they have their own front end. And so they're there are a bunch of people trying to like create their own front end to then drive demand into their endpoints. ⁓ but I I think that one of the challenges is like you have to abstract crypto away, you know, to be able to to get to you know, a number of mainstream, you know, developers and users. And so we're spending a lot of time just trying to figure out, you know, how do you both enable someone to just put a card on file and be able to access, you know, any of these, you know, endpoints, at least the ones that, you know, we think are trusted and vetted and and can be, you know, good services. And then how do you get that embedded inside, you know, every agent harness out there? and I think we're still in such an early stage where most of the agent harnesses, like you can't Pay for anything outside of the harness. It's like the only thing that you can do inside Cloud Code is pay for anthropic credits. You know, the only thing you do inside Codex is like, you know, pay for open AI credits. And I think it's a matter of time before you see both a number of emerging competitive harnesses, and whether that's you know open source ones and Hermes and Open Code and others that are gonna make it easier to access like the broader universe of third-party models and tools, you know, natively inside that that harness. Yeah, as well as eventually the larger ones kind of opening up to that. And so, you know, I I think that the supply is further along than the demand. ⁓ but our goal is just how how do we grow the overall ecosystem and and how can Visa use our platform, our distribution, our trust and and just the fact everyone has a Visa card, you know, to be able to get more people having a card on file in a place that could then access this kind of growing universe of of endpoints being created. **Gabe Tramble (15:04):** Mm-hmm. Yeah, or from the from the enterprise side, just your work so far and and you talking to these these merchants. And and just to be clear, there's the The user, the end user is probably an individual or maybe a company, an individual at a company using an agent like Claud Code, right? That has the ability to pay for services for the service providers themselves and the folks that you're talking about on the enterprise side. Are you what are you noticing regarding their kind of behaviors and thoughts about ⁓ agents in commerce? Are they kind of adversarial? Are they nervous about, you know, bringing their products onto the platform for agents? what what are you seeing so far? **Cuy Sheffield (15:44):** I think there's a big separation between you know developer facing merchants and enterprises and traditional kind of consumer facing merchants. ⁓ I think on the consumer facing merchant side, you know, it's just it's a lot earlier and there's just a lot more questions. And like there there's there's like a FOMO of we like we we want to be involved if people start using their agents to help them shop. But there's there's like real risk of you know, a lot of the value of a lot of merchants is their storefront, you know, their website, you know, their their experience, their app. Like, and and I think that there's there's this question of like, okay, well, what does it mean to open up and and let an agent be able to transact with me? Yeah, how do I control the end experience and the brand and you know, how do I decide which agents? It's much easier to say, let me just, you know, try and embed inside Chat GPT and not have like anyone's hermes like showing up to my. my store. And so I I think that's one of the reasons we've we've been focused on kind of this this idea of like the the trusted agent protocol of like, you know, how can you have some level of identity, you know, to an agent and know who the agent is and be able to have a signature that, you know, they've they've been vetted you know by Visa when they show up to a merchant. Cause I think right now it's it's either kind of closed loop, you know, get embedded inside chat GPT, which isn't easy to do. And like, you know, that there's been kind of stops and and starts to that. Or it's you're letting everybody in. If you're letting everybody in, like, you know, what does that mean? You don't, you know, have a lot of control. And so I I think that there's there's a lot of work to do to find kind of more of a middle ground, you know, I think protocols like UCP are are playing a big role and like that's still early and and I think you know has to to to get built out more. ⁓ on the developer facing merchant side, I think there's just a lot more willingness to experiment and to say that like every developer is using a coding agent. And I need to like meet them where they are. And yeah, I need to be able to have an interface that they can interact with me. I think one of the challenges right now is that the way X402 was built is it's kind of like a it's a guest checkout. You know, that that's the only experience. It's like every agent that shows up to an endpoint, you know, gets the same pricing, the same product. Yeah, endpoints are very static. ⁓ and it's hard to like you know really understand who that customer is. And serve that customer really well. so I think we need to see more of an evolution towards dynamic endpoints. You know, these merchants, like they they want to know who's the customer, what's their what's their email, be able to communicate with them. You know, in the future, maybe there's you know different pricing or different endpoints that would be exposed to some customers and not others. and so I think that there's so much more that could exist in terms of enabling not just a guest checkout kind of one-time experience. But a like true headless, you know, any agent inside any harness being able to pay for any developer service, ⁓ but having the developer service still have a relationship and be able to interact with that agent. I don't think that really exists yet. ⁓ but I I I think that there's it's more likely of like I like to ask questions of like what where is the first a billion dollars of you know agentic commerce like going to be spent? ⁓ and I think that, you know, one, I'd argue like, **Gabe Tramble (18:55):** Mm-hmm. **Cuy Sheffield (18:59):** There's already billions of dollars that's spent of agents buying tokens. It's just an agent, you know, inside of a single platform buying tokens of a single platform. And so when are you going to have like a an open billion dollars spent of an agent inside one platform buying something from another platform? And I think it's much likely to be inference and kind of very developer-facing, kind of agent-facing services than it is to be shopping assistants like in the near term. So that's why like I'm very focused on the developer space. **Gabe Tramble (19:27):** Got it. Yeah, okay. And and and the reason you're focused on the developer side is because there's already one demand. There there's some ⁓ visual of demand there and they're more receptive on the enterprise side. **Cuy Sheffield (19:41):** Yeah, I I think it's it's the best use case for an agent to date. Like, you know, what are people using agents to do? They're using agents to code and build. Like, you know, that that is by far to me the the area of you know just agents that are doing productive economic activity. Like and and the scale at which agents are coding is so much greater than the scale at which agents are serving as shopping assistants. And so I think that whatever protocols and networks and products and solutions that can help solve for making it easier for agents to pay for the things that they need as they code. I think that that's like the the beachhead and in the first place that agentic payments really happens. And then once an agent has a really good way to pay for an open marketplace of you know services it needs as they code, it probably makes sense for that also to be used to pay for you know ordering you know DoorDash or whatever it is that this developer needs. In addition. and so I think it's it's a lot of the other Egyptian commerce could end up being built on top of you know what the developer facing use cases are. And ⁓ yeah, we'll see. But I we just want to be in the ecosystem where people are using agents and and that's that's developers right now. **Gabe Tramble (20:53):** Yeah, right now I th I think there's like this looming overhang. And maybe people want to like pull the curtain back and and look at it at at the ghost or the boogeyman in the closet, but I kind of get this feeling that there are these large incumbents, you know, sim similar to yourself ⁓ at Visa or like Stripe or even Anthropic themselves, right? or Cloudflare. There there's like these huge infrastructure providers or network providers. That can just like turn the lights on. And in I would say like for a builder, what's scary is if Anthropic just, you know, works with Cloudflare and then they just enable wallets to purchase on like all these different websites, right? ⁓ do you think that path can happen where just, you know, ⁓ in in a month we just see like all these transactions because two large institutions just turned on the lights? Or do you think it's gonna be more of this kind of movement or like slush of of supply and demand and and activity to kind of ⁓ a l a longer term thing of of agentic commerce. **Cuy Sheffield (21:58):** Yeah, I I think personally it's it's much more likely, you know, to be this kind of back and forth and like, you know, bottoms up, you know, some emerging new use cases from new players. And then that, you know, people learn from and then the large players kind of adapt as it's I think it's very rarely in new markets, you know, like this, yeah, something that, you know, it doesn't exist and then overnight in a month and now it exists like at scale. ⁓ and I think everyone is is kind of **Gabe Tramble (22:21):** Yeah. **Cuy Sheffield (22:26):** learning from each other and experimenting and and testing things out. And and I think in in many ways it's it's easier for small players, you know, to experiment and be nimble and kind of find, you know, the early signs of of where there's demand. And then you know larger players you know come into the space after that. So yeah, I I think it'll be it'll be a a give and a take. ⁓ I I think the first market to me that is going to be really, really interesting to watch is just like what happens with you know token share on inference. **Gabe Tramble (22:44):** Mm-hmm. **Cuy Sheffield (22:55):** Which I think is gonna be one of the mo the the the most important trends like over the next you know six to to twelve months. And like the the feeling that I have, and and and I don't know if if if you share the same thing, is it's almost like there was this this phase of like coding agents emerged, and you know, Claude Code, you know, to me was like that was my moment of like, whoa, like I can build anything with this. Like this is incredible. It's like the best product I've ever used. And and then there was this like honeymoon of like everyone just vibe coding, just like building anything and **Gabe Tramble (23:18):** Yeah, yeah, yeah. **Cuy Sheffield (23:24):** I'm spending hundreds of dollars a day and I don't even care because like I'm like coding now. And it's so you go from this like token maxing mentality that I think was many very much driven by Claude Code and Codex. Like those are the platforms that people in are in there using and you know are experiencing the magic of having a coding agent, towards then waking up with a bit of a hangover saying, How much did I spend on tokens over the last few months? And like, what do I have to show for it? And like, was there ROI on that? And like one thing I I was just talking to to some people about today is if you think about inference as like a new merchant and like product category. Like it's a product, it's a skew, you're you're buying inference, you're buying intelligence. There aren't that many analogs of you don't know the cost of it until after you use it. And so it's like you show up to a store and you're like, okay, I I'd like to or service, I'd like to do this. And they're like, okay, like, you know, we're gonna do it, and then we'll send you the bill for what it costs after. And you're like, well, like I was just trying to set up an agentic workflow to like download some podcasts. I didn't realize I was gonna be a hundred dollars that like this agent got like stuck in a loop and it was doing all these things it probably shouldn't have done. ⁓ and so I think just the the the kind of push towards how do you justify the ROI and be able to measure and track, like me personally, like I want like a mitt.com for token spin. ⁓ it's just like I want to know everything I can, you know, about How do I lower the cost of my token spend, getting as much value and like measure that ROI? But then you have this like structural conflict that, you know, if you're anthropic or if you're open AI, like it's not in your interest to like make it super easy for people to like reduce and optimize their token spend by routing away to like cheaper models. You want everything to be going through your models. And so then you see like, you know, the open source harnesses, you know, start to emerge. And I think companies like Open Router are building amazing products to have. Like a single integration that can then give you access to 200 plus models. ⁓ and then does that get embedded more into these different harnesses? And yeah, I think you could do that on Hermes now, you could do that on open code. ⁓ and so I think you'll you'll see more of this decoupling of you know agent harnesses that are like model agnostic, that are like built to be more ROI-driven, ⁓ and then access many models and tools. Instead of this first phase of the market where it's like the harness and the model, they're kind of coupled one-to-one. And anytime you're using that harness, you're using that same model. And it's just very hard to justify like buying frontier tokens for very basic coding tasks. But the problem is that it hasn't been easy to like orchestrate and like have access to a broader universe of many, many models that are out there. So I think that's one of the first use cases where like again, injective commerce is happening of agents buying tokens. They've just **Gabe Tramble (26:13):** Mm-hmm. **Cuy Sheffield (26:14):** Been in this kind of environment where they're only buying tokens from one store that has one price. If you give agents the ability to help optimize and have services and products that let them buy tokens from many stores, they could then optimize the prices that they're getting and the value from that. And so I think that's one of the first areas that I could see in. And I think that the the total value and the amount of money that's spent on agents buying tokens is likely to be bigger than agents buying everything else combined. 'Cause it's like that's the lifeblood of like an agent has to buy a token to run. And so sure, it's gotta buy some data, it's gotta buy some some other things. But like if you can really figure out how to make it easier for agents to buy tokens, I I think that's gonna be a a really interesting space. **Gabe Tramble (26:48):** Yeah. Yeah, wow. I I I really like that illustration. I'm gonna try to summarize. So so basically a a huge opportunity you see is agents buying their own inference and or or mu or ⁓ kind of like energy into stimulating the harness and the model. And right now you're saying that there's like this opa opacity where it comes to ⁓ pricing and and only one ⁓ customer or one one merchant which is like anthropic or or ⁓ open ai and with these open source models they're giving you all these different options And the new harnesses like Hermes, I know they allow you to basically adjust the model depending on the task. So essentially you're saying if the agents have this open marketplace in which they can be more efficient in selecting the correct models to use for the correct tasks, then you think that right there is one of the biggest use cases for agentic commerce. **Cuy Sheffield (27:55):** Yeah. And I I think this concept of model orchestration is really interesting. Of like how how do you find the right task for the right model? And I think there are only going to be more models that exist that could be specialized and potentially better at certain tasks, but could also do those tasks, you know, at a lower cost. But the problem is today it's pretty hard. Most people who are bive coding don't have, you know, a router that's automatically set up in whatever harness they're using that is automatically picking the right model for the right task. I think that's kind of like an inevitable direction that it should go. And that I think developers, you know, should want, you know, some type of intelligent router that's you know helping to pick the right model for the right task and having access to an inventory of many, many models that are that are out there. And I think that that's going to be one part of how do you optimize token spend and and justify the the cost of it, the ROI. ⁓ and to me that that's a that is an agentec commerce use case. It's it's an agent that is buying inference. Or also buying data and tools. And you know, I've I've just been like, as I go down the rabbit hole, like there's so many things I'm learning where, you know, there are plenty of times where if you have access to the right tools, you know, you don't even have to you know pay for inference, yeah, because yeah, the tools can go and kind of do certain types of work and store that data, you know, locally that you could come back to instead of having to run it, you know, through a model. And so I think there's so much room to optimize just the core like. back end guts of how an agent operates in writing code. And I think that if you just unpack like, you know, agents are going to write more and more software in the future, if that goes from, well, the agent spends at one merchant of the platform that they're on, to like the agent is spending at thousands of merchants and being able to access these different tools, like, I think that could be like one of the early agentic commerce markets that that's very interesting to look at. **Gabe Tramble (29:51):** Interesting. Like self fill up or like self charging for ⁓ for vehicles. **Cuy Sheffield (29:55):** Yeah. And I I think more competition of being able to because if if you're building a new model, you know, you might have a model that's really good at a certain task. How do you then go and reach customers? And so it's it's like this new two-sided network problem where it's like you have agent harnesses on one side and then you have you know models and tools you know on the other side. And in an ideal kind of efficient universe, any agent inside any harness should be able to, you know, access, discover, and find. you know, any model or any tool that could help them do their job and be able to pay for it as they go. To me, that's like that's how it ought to be. Like like there are there are a lot of things to like, you know, to actually get there. But if you work backwards for like a few years from now, like I I think that that would be a more natural market state. But you're gonna need new payment infrastructure and solutions and products that can enable both the discovery, you know, the orchestration, you know, the payment, **Gabe Tramble (30:26):** Mm-hmm. Yeah. Yeah, yeah. **Cuy Sheffield (30:49):** You know, the authorization, like the the estimate, like there are all these things that need to happen for that like open ecosystem to be able to emerge. **Gabe Tramble (30:57):** Yeah, yeah, I think I think that's really well said. One one thing that comes to my mind as you're saying that is like that piece right there, the just just the agent to put in like a one-liner agent paying for its own inference just opens like a science fiction, maybe not science fiction, probably not science fiction, like ⁓ thoughts about agents just running around autonomously and and self-improving. I know Anthropic just published a report, paper yesterday about the agents improving themselves and and being able to get to the point of of ⁓ continuous improvement and and development. So yeah, I just wanna to f to flag that does ⁓ creep me out a little bit. **Cuy Sheffield (31:35):** Yeah. But I I think it it kind of departs from the crypto like there's a crypto world and like I I think the crypto AI world and like Bit Tensor and like it's like a fascinating ecosystem. And it like feels like it's like science fiction. Like they're like but I I don't understand you know most of it. ⁓ but I think there's this idea of like self sovereign agents that you're gonna have an agent, you know, that is gonna pay as it goes for its own inference and then it's gonna have to like create value or else it's not gonna be able to pay for everything. It's like That that's the like vision people paint. I think that is a very scary future. And that's one of the reasons why it's like we think agents should be working for an accountable, you know, to a developer or an individual. And you should be able to tie those two together. And if you're gonna interact with an agent, you you you should probably wanna know, you know, who that agent is actually working for instead of that agent that's just working for itself, you know, it's self-improving towards towards some goal. And so it's kind of like that my pet peeve is anytime someone says, Yeah. **Gabe Tramble (32:07):** Yeah. **Cuy Sheffield (32:35):** Agents are gonna have to use crypto and stable coins because they're not gonna be able to go and get bank accounts. And I think that like the truth is that well, in almost all cases, an agent is created and works for an individual who's a consumer or business. And that consumer or business can get a bank account and already has a bank account and a card. And so you it's just about you know delegating and giving those credentials to the agent like you would an employee. I think the only case where that's not the case is that the agent is self-sovereign. Is created and kind of let go into the wild and they're not working for anyone. And in that scenario, that's terrifying. And like I think that it's very hard to be like, yeah, let's let's go and like support this agent that you know reports to nobody and like is just out there in the wild and let's sell it a bunch of things when we don't know what its objectives are. Like I I think most merchants would look at that and say, That that seems like that's pretty high risk. Like I'd rather sell to an agent that I know is. being operated and controlled by someone who has a bank account and a card that, you know, there's some accountability on. **Gabe Tramble (33:38):** Yeah, yeah. Yeah, I I appreciate you ⁓ posing it that way. 'Cause I I think like for navigating this space, everyone has like their mental models and you might get stuck in a mental model either from like reading stuff or just kind of you know information just pounding you on the head all day and you can get stuck in those those ⁓ like ideologies and then you just literally cannot see the forest right ⁓ in it at the end of the day. So ⁓ it just reminds me also I when when I was growing up, my parents got me like a kid's account at at the bank and that was my first account. And I had that like kids account, bank account, debit card, but it was tied to their account. And once I hit 18, then ⁓ it graduated me to my own account, right? So I can also see that happening. And and we we talked to Work OS, and they have a similar structure for doing credentialing and and ⁓ authentication for agents on websites. They they launched a auth.md. And yeah, they have the same kind of mindset where they allow the agent to maybe like anonymously interact with the website, but then later. **Cuy Sheffield (34:37):** Mm-hmm. Yeah. **Gabe Tramble (34:48):** the website might require the agent to like bring a human or an email or something like that. So I'm kind of seeing like ⁓ pattern parallels between ⁓ you know, on the on the website authentication side and and and on the payment side for for how you're looking at the space. **Cuy Sheffield (35:04):** Yeah, I I think that the the analogy is almost like just from like a very, very simple sense of every individual can now be their own corporation. Where like corporation, you know, has yeah, a set of employees, and then you know, those employees are delegated certain responsibilities and you know, certain budgets and certain amounts of money, and those employees can go do things, but like they're accountable back to you know the corporation. ⁓ now that's like every consumer can have you as many agents as they want working for them, doing different things with different roles and responsibilities. And and I think to me that's awesome. Like that's what gets me really excited is like, you know, for you know a pretty small accessible amount, depending upon like what the agents are doing, being able to have your own fleet of agents that are working for you and like, you know, doing different productive tasks. ⁓ and so I I don't think it's like that different from that idea of you know every individual being a company. **Gabe Tramble (35:53):** Yeah. Yeah. Cool. And and you you touched on ⁓ the tap or the the trusted agent protocol. ⁓ can you and and the trusted agent protocol is like a a subsidiary under your ⁓ visa intelligence commerce like platform, right? Which is like agent agents and commerce. Can can you explain the ⁓ the VIC or or Visa Intelligence Commerce stack and and then where like tap fits in there? **Cuy Sheffield (36:30):** Yeah, I I think at a high level, like Visa Intelligent Commerce, you know, enables agents to be able to have access to a card that is tokenized, that's secure, that can have certain controls and and permissions, can be identified as an agent. And so that the payment functionality is pretty straightforward that we're able to solve, ⁓ using a lot of the infrastructure that Visa's kind of built out in tokenization and some of the same technology that powers Apple Pay. you can now you know be able to use as an agent that someone puts a card on file, you tokenize the card so you have a secure you know representation of it that an agent can have access to with certain you know guardrails and bounds around it. So I think that was like the first thing. Like, okay, if if an agent's gonna have have a card, you shouldn't just give it a 16 digit pan. Like, you know, there should be a tokenized representation of the card that is more secure that the agent can have. So I think that's the first thing. I think then the question is, okay, well, like That agent needs to be able to take that card and go somewhere and spend. And I think the the very real challenge that we saw was that a lot of merchants, particularly like when we started this a year ago, it's a lot of merchants just block bots. Like they're like bots are bad. Like they they've like for the entirety of the internet, it's been if a bot shows up at a website, like, you know, it's there doing something you probably don't want it to do. ⁓ and so I think that merchants to it's it's one thing to just give an agent a card, but like, How do you help that agent kind of be able to get to a checkout and then be able to spend on the checkout? And I think that that's that's kind of the gap and the barrier in the space right now. And part of it is that merchants and through providers, you like Cloudflare and CDNs, they've all these things in place that are specifically set up to block bots. How do you differentiate between a good bot and a bad bot? And so what we're doing is kind of building this identity system in tap where If you have an agent that has a card that has been tokenized through Visa Intelligent Commerce, being able to then have a signature that that agent can carry. And so then when they show up at a website, being able to say that this is a trusted agent that that merchant should let in versus this is a bot that's there, you know, trying to do something malicious. So I think that's the high-level concept. I think we're making a ton of progress on it, but it's it's still incredibly early for most merchants. ⁓ and I think that. Right now, you know, the the bigger challenge is how do agents discover inventory ⁓ and be able to like you know have merchants identify good agents, bad agents, and let them get to the checkout. If an agent can get to the checkout, like now agents can have a tokenized card. If they can get to the checkout, like they can pay, but it's that like in-between layer. and so we think there's a big role for for tap to play. We think there's a big role for UCP. **Gabe Tramble (39:16):** Yeah. **Cuy Sheffield (39:21):** I think there are gonna be a number of kind of protocols and standards that have to exist to enable like a headless checkout that also has trust and identity built into it. ⁓ so that's like the core stack right now. And then you know what I've been focused on is is building out Visa CLI, where Visa CLI is is very much, you know, rather than focused on you know traditional kind of e-commerce you know agentic use cases, Visa CLI is like a very developer vibe coder native. **Gabe Tramble (39:38):** Yeah. **Cuy Sheffield (39:50):** If you're inside a coding platform, you know, how can you put a card on file and then be able to buy inference, buy image generation, buy data? ⁓ and so Visa CLI is is kind of closer to the X42 space where we're actually trying to enable a card-based experience to pay for X402 endpoints. I think in the future, you know, all these pieces will come together. And what I'd like to see is you could have an agent, you know, wherever that agent is, they can put a card on file. Yeah, they can get a trusted kind of signature that they're a good agent through tap. They could then spend any traditional e-commerce checkout ⁓ over maybe a protocol like UCP, or they could go buy inference and buy data. And I think you'll see different use cases where, like, you want to book travel. Well, maybe you want to buy some weather data first, ⁓ and you want to do some like small microtransaction, and then that ultimately leads to completing a larger transaction. ⁓ and so I think that you kind of need to have a set of **Gabe Tramble (40:48):** Mm-hmm. **Cuy Sheffield (40:50):** primitives in infrastructure that can support across the board everything from developer facing micropayments all the way up to like executing a traditional e-commerce payment, you know, at the point of sale, you know, with an agent. So we're trying to just build that kind of core layer across the stack. **Gabe Tramble (41:06):** God. Yeah. Yeah. It feels it feels to me like now, and it's still super early, just even on the payment side, and and there's like all these things that need to happen. But for the people who are like running at full speed and and at the edge, it seems like the real break is the the distance between the agent and traversing the website to get to the checkout. That just seems like There's a few companies like Browser Use or Browser Base that are like actually just using the human ⁓ browser interface to get to the checkouts. Can you kind of explain a little bit more if you think that, in my experience, that's kind of the big gap right now. ⁓ more on your end of like where you think that's gonna tighten up, or even if you think that is a gap in the first place. **Cuy Sheffield (41:49):** Yeah, I I definitely think that that's that's a gap. ⁓ I think that like most of agentic commerce, you know, experiments and pilots and kind of early versions of it has been requiring an agent to navigate you know a website like a human. ⁓ I'm interested to see how browser use and like computer use and like how how all of that improves. But it doesn't seem like it has gotten to the point today that works well enough, you know, efficiently enough at a low cost. ⁓ to be able to actually make that a mainstream use case. So I don't know, like it could change, it could get much better. But like today that hasn't, you know, been kind of the sole solution that you know everyone said, great, we're we could just use browser use and get to any checkout that we want. And there are a bunch of nuances of the way checkouts work at many different merchants, that you run into issues when you just try and do browser use. I think having purpose built protocols, yeah, like UCP, yeah, make more sense of like a headless checkout that is API based that you don't have to send a browser ⁓ an agent you know over the browser. ⁓ and so I I think that you'll see like a combination of both. ⁓ but I I see a need for like yeah these specific protocols that are built for a merchant to be able to communicate you know with an agent without the agent having to to go over the site. And I'm excited to see merchants, more merchants start to onboard into those protocols, you know, start to learn how to use them. ⁓ and I don't know how far away we are, but I I think that there's there's a good recognition across the industry that you know merchants that want to sell to agents are going to have to do some work. ⁓ and you know many times their platform like Shopify has enabled and kind of does ⁓ makes it very easy to do. They're gonna have to represent their inventory, make it easy for agents to discover, and then be able to execute payments through those protocols. And and that's probably a more sustainable long-term solution than than browser. ⁓ browser automation, but we'll see. I I don't think anybody knows. Like it's great to have people trying a a bunch of approaches. **Gabe Tramble (43:49):** Yeah. It's it's gonna be interesting with stuff like Shopify or these these platforms because you're probably gonna have like real world market makers, you know, doing like alg algorithmic trading for goods. And yeah, I'm just I'm curious to see like what emerges as ⁓ as it's easier and and and you you can like machine interact with all these different platforms, machine to machine. So that that's something that yeah **Cuy Sheffield (44:15):** I I think that's that's one of the reasons that merchants are nervous, that they're like, Yeah, if are we just gonna put all of our inventory into this protocol and now we just become a catalog as an API and we lose our brand, we lose our value, like it's it's a scary thing, you know, to give up, which is partially why I I think there's a big opportunity for new merchants. ⁓ and I think like more often people when they think about agentic commerce, ⁓ they think about existing merchants, you know. making you know products available you know to agents. And that's to me almost like it's like we the internet's coming around and you know how are existing brick and mortar retailers going to adapt and you know making products yeah available to to users on the internet. ⁓ and I think that it usually starts with like some success cases of brand new merchants, brand new retailers, brand new companies that are just built on day one, their entire business model, you know, their entire mission and vision is selling to agents. And I think they're the ones that have the incentive to go and try and figure this out. And then you have some breakthrough successes. And then, you know, what they do gets adapted. And that, you know, the traditional merchants that have, you know, big e-commerce franchises today, you know, they start to open up over time. But it's just so hard for me to imagine that it's going to be an existing merchant that has a great business that they like in a format that they understand that is going to be on the bleeding edge in terms of experimentation around how to sell to agents versus. just a new merchant class that's emerging. And I think the barrier to entry to building a merchant is just getting lower and lower. And I think that's one of the amazing things about, you know, vibe coding. It's like, you know, anyone in an hour, you know, can build something that they could then sell online. ⁓ and so I think that there'll just be many new merchants that are created. And I think some of those merchants will take an approach to say, we're going to build exclusively for agents. Maybe there's no way a human can even pay at them. Maybe they don't even have a website. Like it's just an endpoint, but we're to build for agents. **Gabe Tramble (45:50):** Yeah. **Cuy Sheffield (46:10):** And I think that once you start to get some success cases there, then more traditional merchants will say, okay, let's let's dive in. But it's it's just hard for that to to start with a traditional merchant. **Gabe Tramble (46:10):** Mm-hmm. Yeah, that's super interesting. It reminds me quite a bit of like Ghost Kitchens. ⁓ and and just you know, this new entrance of player. I d I don't know if Ghost Kitchens are a success case, but very similar ⁓ kind of parallel there. **Cuy Sheffield (46:38):** For sure. Apologize. I I gotta get I gotta get good. We we could talk for hours. I I I gotta get going if you wanna if you wanna wrap up. I don't know the the best way you **Gabe Tramble (46:42):** Yeah, yeah. perfect. Okay. Yeah. Yeah. Yeah. No worries. Yeah. I was I was watching the time too. ⁓ I'm gonna do one last question and then just like an alpha, like yeah, any like what alpha do you have and then and then we can wrap on that. Yeah. Well let me let me let me let me put it in the camera. So yeah, Kai, thanks. Kai, all the stuff that you've been saying so far ⁓ has has been kind of putting this this model and and giving us this example of what to look out for. **Cuy Sheffield (46:58):** I think my **Gabe Tramble (47:12):** In the ecosystem right now, where do you think as we wrap here, where do you think is the last place where alpha lives? And, you know, if you were to a new builder, where would you focus on right now? **Cuy Sheffield (47:24):** Yeah, I I think it's it's pretty simple advice yeah that I I give to everyone that I talk to now is like the best way to understand agentic payments and where it's going is to just start making agentic payments and just start using these products. And like I've been trying to buy something, you know, with an agent every day. And just like, what are interesting things that I could go out and try and buy? How does it work? Where does it break? and I think that's that's where the alpha is. And like there's so many people who you know just want to talk about agentic. And then you ask them, like, have you ever bought anything with an agent? Like, are you are you using any agents? You're right. They're like, No. It's like it's just like you can talk forever, but it's like you have to just use the products. And as you use the products, you figure out what works and what doesn't, and and then you iterate from there. So that's that's my advice. **Gabe Tramble (48:10):** Cool. Well, cool, man. Thanks for sharing. And yeah, I'd love to have you back on soon. Yeah. See ya. **Cuy Sheffield (48:15):** Thanks for having me. --- # Agents Will Run Their Own Businesses: Inside Laso, Agent Payment Cards, and the Agentic Economy > Shoal Signal episode. Guest: Hunter Monk (Laso). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-07-01 - Video: https://www.youtube.com/watch?v=S-eztFEkTP8 - Canonical: https://shoal.xyz/research/episodes/inside-laso-agent-payment-cards/ - Keywords: agentic economy, AI agents, agentic payments, crypto, privacy, Agentic Payments, interviews ## Transcript **(0:00)** In the agentic economy, there's so many different players tackling the same type of issue, but from different angles. And the end result really is how can you get an agent to do something and then pay for whatever that is. And we've seen different types of solutions here. Ultimately, the goal is how do you go from an intent to work to payment? In each part of that stack, there's different players working on different problems and challenges. And today we have Hunter, which is the founder of Lasso, allowing agents and even humans to use one time use credit cards to pay for things on the web like groceries, gift cards and other financial services. **(0:44)** Essentially going around the bottleneck of merchants not being able to support crypto and stable coin payments. So Hunter, you guys started with cards for humans and then realized that your product fits uniquely with agents and now you're giving agents cards. How did you go through that process and why did you start with crypto enable or stable enable cards in the first place? Yeah, great question. So, you know, the core part of the business they've been building for kind of the last three years is enabling crypto consumers like humans to get cards and be able to spend their crypto without any ID upload required. **(1:22)** So they can maintain their privacy, which is a very important product. And that's kind of the core of the business. It became clear really, you know, a year ago, at least maybe a year and a half ago, that a big benefit there is because that onboarding is so seamless, you don't have to go through a liveness check or scan your passport or anything, that it's the only way an agent could get a card. But a year and a year, a year, a year and a half ago, there wasn't OpenClaw. **(1:55)** And so I kind of knew that was going to happen at some point, but there just wasn't a really good entry point. You could kind of maybe try to tell ChatGBT to do it, but it didn't have, you know, its own wallet. And then OpenClaw hit and it was just, okay, this is perfect. This is what you've been waiting for. And so now you can send your agent a single prompt and it can get its own lasso card. It can go spend it anywhere prepaid is accepted, you know, online. And it can make its own purchases. Nice. **(2:21)** And your card is unique because it's a one-time use card, right? Or you have a couple modalities for the card. Can you explain why that is the case or, you know, what is the benefit of a card that kind of turns over? Yeah. Yeah, it's a – you can use it multiple times, but you can only load it once. So you get your card and you can get it up to $1,000 from the card. And you kind of spend it down. And once you're done spending it, you get a new card. You don't deposit again into it. **(2:49)** And the reason it's set up that way is it's a requirement of the regulatory structure that lasso operates under. Essentially, we need to prevent money laundering. That is, like, a big concern, of course, maybe the biggest concern for lasso as well. And so part of that is not allowing reloadability of cards. That's what allows us to have this much lower user verification process to make this kind of model possible and be able to give your agent a card without having to go through a big invasive KYC process. Nice. **(3:23)** Nice. And you guys first started with, like, human cards, right, which is kind of a weird thing to say. Normal cards. And what are the use cases? And, you know, why were people quick to really love the product that you guys built and put together? Yeah. Yeah. And to be clear, we're absolutely continuing that business. That is the core of the business is humans. Humans, we love you. And the value proposition there is it is the most private way to spend your stable coins. **(3:57)** So, you know, Satoshi envisioned disintermediating the banking system. But today, you have your crypto and you want to go spend it. You can spend it at businesses that accept crypto, which is it's growing rapidly, but it's still a very, very tiny percentage of merchants. Or you're sending it to an exchange, like a bank-like entity, essentially. And maybe you have, like, a coin-based card and you can spend it that way. Or worse, you know, you send your assets to an exchange, sell to USD, wire ACH to your bank account and pay for a credit card. And at that point, not only are we not disintermediating banking, we're just doing banking with extra steps. And we've lost our privacy. It's not kind of the purpose of crypto or why we're working in this for the long term. And so satisfying that need for people who want to maintain their privacy in a compliant way to do normal consumer discretionary purchases, those are kind of our users. So they're ideologically aligned. **(4:57)** They tend to be OGs, for lack of a better term. And that's the kind of vertical that we're serving. Nice. Yeah, I was literally going to use the word ideology. And the product is basically like a manifestation of self-sovereign spending. And the card is the ability to do so. That was great. I'm going to clip that. That was a great way of describing it. That was going to be in our ads. Awesome, awesome. So, okay, so you guys built this card and people are using it and you designed it in mind for like day-to-day use. So just like a consumer card. And is that kind of the main use case that you're seeing? Has that actually changed and you've seen different types of behaviors with the cards? Like what's kind of the core use case, either if it's not that, outside of that? Yeah, the core use case is consumer discretionary purchases. So, you know, our top merchant is Amazon, Uber, DoorDash, Walmart, just kind of regular what you spend on in an everyday. **(6:03)** And that's like, that is on the human side. I know like a lot of our focus is on the agentic spending side. But on the human side, it's just typically what you make your purchases with. Because you can spend them online or add them to your device or Apple Pay and Google Pay and get gas or whatever. On the agentic side, our cohort of users, non-humans, those purchases are, we're still, we're early, right? We're in the cross in the chasm book. We're in that 1% tinkerer phase really quickly. I think everybody agrees that's going to become mainstream, but we're still early. And so the very first agents that we saw on the platform are doing kind of like silly examples, like buying snacks for the office or whatever. Essentially things that are, it's not much better. And in my opinion, it's a worse experience than just buying it yourself. Getting the snacks to the agent is not like a big time saver. But what we're starting to see, and what I'm very, very excited about, is the agents using cards as a tool to run their own business. **(7:11)** Pulsia right now is kind of getting some product market fit on enabling the creation of businesses. Locus, our partner, where Locus, where Lasso is the default guard provider, are really running with this idea. There's all these businesses out there that were either not worth the time to explore or to simply be more possible without agents. And now people can do them. So the use cases that I'm excited about are agents are getting cards to buy domains, website hosting, buy ads, and making businesses run. That's what the big TAM of agentic commerce is about. **(7:48)** Got it. Okay. Let's put a pin on that one. I want to, and we can re-hit that one and kind of go a little bit deeper on this broader agentic commerce. This transition from the human cards to the agentic cards and allowing agents to spend, did you guys come up with that? Did users just take the cards and start just hooking them up with agents? Like how did that transition occur? And then what is the product experience now? Or how can people consume the product from the agentic side? Yeah, it wasn't kind of pulled down of us by the customers. It was just something that became really obvious to me a while back, kind of before OpenClaw. There just wasn't, I wasted a lot of time trying to get, I believe it was called ChatGPT operator to get its own wallet and things. And that didn't go anywhere. **(8:48)** And it was really just waiting for that moment of OpenClaw and Ermes now. And that's kind of the primary AI agent harness that we're servicing is OpenClaw and Ermes. And today you just need to send your agent a single prompt. Essentially go to lasso.finance.skill.md. Download that skill and get a card. You can copy it from our website and your agent will go set up a wallet either with Locus, Sponge, Ampersand, and then go get its own card. It can give you a little authentication link so you can go and log in and see what your agent is up to, what transactions it's making, etc. Or if you want, you can just purely do it through kind of a chat interface. Okay. Okay, cool. **(9:42)** So the experience from the agent is like the agent might have its own spending system, but then they're able to use also this like external card that has the traditional card numbers and all that stuff on it. Yeah. Yeah, correct. So your agent does need control of its own crypto wallet. There's a ton of great providers like the last three that I've mentioned, but it does need to be able to control its own crypto wallet to be able to deposit into the card. Of course, in the future, it's actually not even necessary really to involve crypto in that flow. **(10:18)** So something that they're targeting to launch this year is being able to fund your agent through Apple Pay or bank transfer or wherever. That's not live yet, but shooting to have that ready this summer. Currently, you just send in USDC or tether or die. And then the agent has the card and can spend away. Nice. And for you, like you mentioned in the beginning, there's an ideological product of privacy and kind of freedom to spend. Do you think that is a crypto – do you think that will stay crypto native, especially if you can like load with like an Apple Pay or something? **(10:58)** And this kind of gets broader down to like is agentic commerce going to be on fiat rails or on stable rails? I'm curious your thoughts about how you're thinking about that. Yeah. For a core group of human users, privacy is the value proposition. On the agentic side, that is less of the focus, more so the focus is on the lowest friction possible user experience, essentially permissionless access for your agent to fiat payment rails. And so the value proposition there is different. **(11:36)** If you are sending in a bank transfer, you have lost your privacy for that flow. But it's a different value proposition you get at the end. I think really what we're focused on is like X402, for example, allowed crypto users and agents to be able to transact in a kind of permissionless fashion via crypto. And so Lasso is adding kind of the traditional fiat payment rails version of that. And so you mentioned Locus and Pulseia, these two companies. Can you explain a little bit more the relationship between Lasso and these two? And I know Locus is like an agent spend. We talked about a little bit agent spend or basically like in your terminal or in your agent. It has access to crypto and then it can spend on like X402 micropayments. And one of those micropayments is your service. **(12:37)** So you can pay a micropayment, ping your service, get a card back and be able to spend or load on that card. Yeah, just a little bit more on those. And then we can kind of get into like this broader agentic economy. Got it. Yeah, so Locus is a YC company that is an agentic wallet platform. You know, by default, if you go install OpenClaw on your device, you do have an agent there. It doesn't have a crypto wallet or like a way to control it. And so Locus gives you that. When you sign up with Locus, by default, you kind of also get this integration with Lasso. So your agent gets both services in one. And the second one you mentioned, Pulsia. No integration with Lasso and Pulsia right now. I just thought Pulsia did a good job, along with Locus, of kind of shifting the focus of agentic commerce from this consumer use case that a lot of us immediately jump to, where we're buying snacks for our office or planning our trip to Europe or something. **(13:41)** And shifting that focus to my agent is, it's not just improving execution of humans. It is a revenue source and ideally a profit source. Having all this extra non-organic intelligence is interesting if it can do the things humans can do, namely have its own profit and loss report. And Locus and Pulsia are two companies that are pushing that forward. I'm really excited about their, they have an opinionated direction, kind of. Yeah. We just had an interview with Cole from Locus yesterday. And he was explaining how for the X402 and MPP payments specifically, or like these agentic micropayments, they spent a lot of time building up the supply side of all these different services, including yourself, and then built the wallet layer to basically pay for the supply side. And they said basically what's missing is like the work. And they're building this founder product of, you know, you can deploy like an agent and essentially it can create work. **(14:50)** And work turns into like paying for services to do this work. I'm curious for you, like theoretically or maybe like your future thoughts or predictions around what this looks like and what you're seeing so far. Yeah, I think the first wave, actually, let me back up a second. Every time that we have, we mean civilization and humans, have a major technological breakthrough, we kind of cram our existing frameworks into that new one until we figure it out. And to make them more concrete, like a really good example is when television first started before that, our mass broadcast medium was radio. And we had commercials on radio. We have this new medium. And so for a while when TV started, commercials on TV were just people reading the radio ads for quite a while. That's what we understood is we just kind of crammed it into what we understood. **(15:55)** And eventually we thought, well, realized, wow, there's way more we can do with this medium. And so I think those, the first agentic commerce use cases are like that. We're just thinking about, okay, I use my computer to, you know, go on kayak.com and think about my flights. And I'm just going to have an agent do that. It's the same, we're reading radio ads on the television. I think that the next incremental step will be, it's still a little bit of cramming, but it's like, oh man, I thought about doing this kind of one silly business and I don't have time to think about it or you forget about it, whatever. **(16:36)** And you can submit up an agent to do that. On this past Sunday, I was talking with a friend to give a concrete example. So right now there's this kind of rise in Pokemon card, gotcha machines. Are you familiar with gotcha? These little bit, it's a, it's a sort of like a vending machine lottery type game, basically. And Pokemon cards are using that as a vehicle and it's becoming very popular. And he, he was telling me how Hot Wheels is the second biggest toy collectible market. I didn't know that. Yeah. First, I didn't know it either. I kind of, I laughed as soon as he told me it. But then he went deeper into it and it was fun. So the top one's Pokemon cards. The second one is Hot Wheels. And they have this big primary market, not a big secondary market. And so he was, he was thinking, okay, I could use agents to go do this business. There's a lot to learn there that I don't know about. **(17:35)** And, and that is a clear use case of a business that maybe would never, would never exist or would take a long time to exist, or maybe really experienced good operators wouldn't have tackled it because it's small. Yeah. There are also markets two through 20 like that. I don't know what the number three toy collectible market is, but it exists. Probably nobody is servicing it to, to legitimate level. And with agents, with, with Pulsio, with Locus, you can spin up a ton of agents to go through markets two through 20 and make your whole, uh, um, ad campaigns, pay for, pay for ads, **(18:10)** pay for website hosting, um, talk to users on Reddit, wherever. Those were simply not possible for agents or just wasn't economical. That's what, that's what I'm excited about. And, and that is the near term. That is kind of what I believe will be happening at the end of this year. Next, after that is kind of like a agent to agent payment settlement. Um, so kind of, you have your web 2.0 interfaces, then you have agents making kind of normal web 2.0 interfaces. **(18:43)** And then probably for a little while you have your agent is going to buy services from another website that a different agent made and doesn't really know, right? It's like kind of intermediating through typical, uh, and then eventually we get to like X 402 to X 402 communication type level. But you probably have this intermediary step where just like on last out today, you can go do everything that agent can do as a human and your agent can do the same. And you kind of have both, both, uh, you have to build everything for humans and non-humans **(19:15)** and maybe eventually only non-humans, but you need that step in between. Okay. Yeah. There's a couple of things I want to, I want to break apart into, into sections and we can, we can hit all of them. So the first one is, uh, you, you see this world where the agents are basically doing the diligence and, and creating these, uh, businesses or services in tight niche verticals where, uh, maybe someone with like the efforts, the knowledge and the energy can insert themselves in this type of process. **(19:47)** Like, where do you think if, if this is a capability that that's, that's available and and grows, right? Like the, uh, the fable, uh, Claude model just released like two hours ago, that's supposed to be better than Opus and for long standing tasks. This, this seems like literally the model for what we're talking about here. Where do you think, especially as someone who, who talked about the human side a lot, where does the value then become for the operator? Um, and, and what is like the mental model in which the operator needs to, to think through? **(20:18)** What, what do you mean by where does the value accrue for the operator? Yeah, I think like where, let's say these capabilities are possible for the person that is like deploying the agents, right? Um, and maybe like an agent deploys an agent that deploys an agent. There's like this chain. We don't need to get to that yet. Maybe that's like a few years out, but for the near term, just like one step cascade, where do you think the, um, the focus of like skills, um, tooling or more so skills, where do you think like the skills and, and the, the value of the skills kind of collapses to if these **(20:56)** agents, if they can build a business, right, they can code and do all these things, but what are like the qualities of individuals that were become successful at these things? Got it. Um, uh, and whenever you said skills, I immediately, I immediately jumped to like a skill file. Uh, but, but, but I think you're meaning skills in terms of like capabilities of a, um, I'm going to answer the question that you didn't ask. Cause I think it's interesting, which was skill files. Um, the, the immediate part that there'll be some businesses around right now will be on building up the infrastructure to be able to execute these effectively. Like currently the agents don't have access to a bank account, which you will need for some of the flows to receive your funds from the Shopify account you start. That's like, that's what LASO will be adding this summer. So there's very, very tactical, small things or skill files to describe to an agent, how to **(21:55)** effectively go through a Shopify checkout or Amazon checkout page because agents can still struggle with these kinds of typical webpage things. So there's some, some immediate, uh, there's some, there's some immediate build out there and, and you can kind of, those have value that, that you accrue as a business founder orchestrating the building of your businesses, um, um, through, through agents. Then the next, it ideally what we want to get to is your, is this, it's essentially, uh, for **(22:31)** lack of a better of a, for lack of a better term, it's, it's taste of this, of this human founder that is orchestrating agents and sub agents to execute on a, on a business. Uh, and, and the best microcosm I can give of that is on the coding side, which is where I live every day and it's probably the, the market that agents have are currently adding the most GDP to the world in is on, uh, is, is on coding. And for, for all of us that are able to use these models for our work, you're quickly elevating **(23:05)** to the primary value you're providing is taste. Um, to make it more concrete, you're, you're not just describing those, whatever a new function or server endpoint that needs to be made, but, uh, adding color on what components of your model should be consolidated and which ones should be inheriting from a different superclass or whatever you're describing those in verbal terms. You're really just taste, not syntactical. I think as a business founder, we get to move more and more towards that. Like all founders understand and you understand as well, so much of it is not glamorous. It's schlepping through like connecting analytics dashboards and stuff that just is necessary, but not fun and, um, maybe not specific to the objective of the business. And so eliminating that so that your time is more spent on what are the valuable verticals to execute on and how best can I reach, you know, our, our target users or resonate with **(24:08)** them. You get to kind of move up to these, um, yeah, higher level of thinking kind of. Okay. And then the, the next part that you, that you talked about was the, um, agent to agent. And I think the way that you framed it is a little bit different than I've heard a lot, which is, I think kind of like the, the surface level framing or mental model is, you know, my agent's going to talk to your agent and, and you have a bike that I wanted to buy. And, and, you know, we, they barter and negotiate and swap. **(24:41)** And the, the problem I have with that is like a marketplace deterministic marketplace where, you know, it just set the prices. And, you know, even in crypto, there's algorithms like, uh, like AMMs and stuff to kind of solve these types of issues. So, um, but you said, you know, an agent agent to agent commerce can almost be like an agent makes some type of full service. Uh, and I think that's kind of different, like autonomously, right? Like an agent makes a full service and that's different from kind of like an X 402 endpoint **(25:13)** where like it's some humans kind of had the involvement of deploying that. Um, so almost this agent to agent model, at least for the ones that you, that you mentioned is like the agent and the human interaction is just farther away and it's more agent, agentic if that, like agentic economy. Uh, yeah. Is, is that a good framing if you can go into more on that piece? Yeah, no, I, I think you, I think you nailed it. There is kind of the, the, the, the, the, I kind of visualize it in three sort of distinct stages. **(25:44)** A lot of the way that a lot of people are thinking about it right now is, is my agent goes and finds this bike listing for me and maybe it has a purchase for me, which I don't, I don't think is a, if it's an improvement on user experience, it's incremental. Um, there's the second one, which I've described, which is an agent is starting its own business. And the third one you've described is, is a, is a total agent to agent, uh, communication to go to your bicycle example. I think a more, I think what will happen before my agent knows I need a bike and goes and finds it and talks to another agent for somebody who wants to sell it. **(26:19)** But I think what happens in between is, um, uh, is Gabe's neighbor has identified this strong secondary selling bicycle market in your city. And this, uh, uh, uh, he is now the market maker for used bicycles in the city. Like that, that, that, that is a business that, that, like you wouldn't want to execute on and your neighbor probably doesn't, but an agent can do. And so then you have this, uh, uh, Gabe's neighbor website probably. And that is more shaped for a different agent to consume. Like the agents by, by nature sort of, uh, uh, uh, want to make things that other agents can consume. And so you have that intermediary step. Some other agent has built a business that services that, and then maybe your agent finds it and you communicate that way. And then maybe you get to this like a very futuristic, there's no webpage, no nothing. They're talking purely with each other that probably goes to this, but we look, what looks **(27:21)** like a normal website for quite a while. Interesting. Okay. And then the, the, the last one, and this kind of like ties it together, you said is, is X, X for O two and text for two. Like, what is, what does that look like? I don't really know. I was, I was, I was, um, I was trying to find a good, good, like a mental model to compare against, uh, uh, I mean, X for O two is a, is a concept in my example, not, uh, protocol doesn't really enable it, but, um, yeah, I think, I think what we're, we're imagining **(27:57)** is, you know, sort of a chat GBT window that's not visible between two different agents talking to, to each other, which is maybe more of the, more of the end state. Um, uh, it, it, it, it's not anything that has any significant traffic attraction that I can see, but it seems possible. Probably the closest we have on that is, uh, uh, something like DeFi, DeFi agents. So one, uh, one team that we're working with is claw pump and they're, they're building **(28:30)** agents with a kind of a focus on making profits through, through DeFi crypto strategies. And there you're sort of the product that you're either buying or selling is, you know, can be described in a sentence and access is purely programmatic. So you get a little bit closer to that. They can maybe to make it more concrete, your, your agent is, is searching for some sort of lending return with a target share ratio, uh, and target leverage. And maybe that pool doesn't quite exist yet. But an agent, a different agent has access to that capital and then can create that pool or deposit assets to create that pool. Those conversations, if you will, are not mediated via the theoretical chat to BT window between two different agents. Like I described earlier, those are mediated through, through markets and pricing. But, um, you know, what, what, I guess, what is it, what is a, what is a market and a price besides like the most compressed version of a, of a conversation? **(29:35)** Mm-hmm. Yeah. And on, on that last piece, so where do you think kind of, we, we, you, you explain the product, your, your mental model of how you're, you're seeing the space and the, the product that you've built is like your mental model for, for Lasso and, and, and, and the ideological piece right now, what do you think people are like getting wrong or, or is just like totally, um, incorrect, uh, or kind of like a bad framing that will not allow them to kind of like see the cascade **(30:11)** of, of reality? Uh, I, I think my primary form of inaccurate framing, in my opinion, that I see is what we've talked on, but touched on, which is thinking about it to commerce in terms of improvement in consumer consumption, like billions of billions and billions of dollars and the world's smartest people I've worked on making Amazon a great user experience and make Shopify a great user experience. And maybe an agent can improve on that, but it's an incremental improvement. **(30:43)** People are still buying as a consumer, what they already are. They're not doing that many incremental purchases there. And instead thinking about it more creatively, I think that the better way to frame it is what kind of businesses are possible to, to sell to humans, uh, um, that agents can make that we couldn't have before. And then the next stage is what kind of businesses can we sell to agents that weren't possible before, but probably you need to sell into humans part first. **(31:15)** And of course there'll be then very vertical specific, specific or quantized portions of compute that you're selling back to an agent to be able to execute on tasks or whatever. And, but sell to the big market first, which is the humans. Yeah, that's super interesting. Cause like a lot of builders are going after like a piece of integration. So like browsers exist. Okay. How can we, you know, go on the browser and, and reach the checkout. Right. Um, and, and what you're saying is basically like kill the entire commerce product itself and rebuild like the use case, uh, from, from scratch essentially. Yeah, well, uh, I guess I would, I wouldn't say necessarily kill the whole, kill the whole commerce commerce use case because, um, like agent optimized checkouts will be needed for this agent to build its own business. **(32:15)** Like in our bicycle example, um, I don't know, it needs, it needs to be able to buy storage for those, for those bicycles. Um, and, and, and so you kind of, the first asset that agents on will need to unlock is if you can, you can imagine all of the online commerce as like an asset, right? Like, like Amazon isn't, Amazon is an asset, Shopify is an asset. And, uh, and, and so if you, if you imagine, um, there was a new alien species that is super smart, but they, they can't use Amazon before they can make their own businesses to serve to us. They need to be able to access all the assets that we have to be able to be able to be effective. So the first step is getting that. And like, we're still not there yet. Like agents still will struggle on checkout flows, scrolling through them correctly or whatever. And so knowing those is definitely the necessary part. Once they are able to do everything humans can do, once they're able to go through checkout flows, once they're able to all get their lasso card coming later this year, once they **(33:23)** have their bank account through lasso, now that you can do everything a human can do. Now they can execute all the things that humans cannot. We kind of need that first part, uh, uh, to begin with. Okay. So more of a stepping stone than kind of like rewriting the system itself. Yeah. Yeah. Yeah. It's a stepping stone. And I guess that the difference is there are the, there is, there's the first kind of blocker, which is like, can your agent even complete the checkout? **(33:52)** Like that needs to happen no matter what. I would say then some people want to nail that. And then their next step is how do I find consumers who want to buy a bicycle? And then I can put them into my checkout product and complete. I think that second step is certainly there are improvements there and there'll be people who, um, execute there and serve a lot of people there. It's not particularly what my focus is. I think is we get so that agents are able to complete checkouts across all websites made for humans reliably. **(34:22)** Uh, and then they use those to create new markets, markets, products, businesses, um, that a human either would not or could not. You do need those. You do need those first. Agents still, still fail on, um, some of those checkout flows. And one additional point about that is some of the thinking, some of the thinking also is at the rate that the models are improving, maybe they're, they're, you don't need to build those checkout improvements. Um, you're sort of like short AGI if you're doing that. The assumption is that it's like, you want to skate to where the puck is going and, um, and it would seem unbelievable that we'll say to be conservative two years in the future, the, the state of the art model wouldn't be able to complete a checkout faster than a human, even though it's really not the case most of the time now, it's another just kind of piece to think about is sometimes you can just assume this will probably be able to do that in six months **(35:30)** and probably skip building that part. Yeah, it, it's, it's kind of a weird, like moving goalpost where the models are, are improving so much, you know, there's tons of startups that are improving tooling. Let's, let's just use like, you know, uh, navigating to a checkout, like it, it, it, it's almost the case, like, could the models and the tooling get so good that it just use, it can just traverse the traditional system without actually having to create like, you know, uh, agent friendly Amazon site. **(36:01)** Um, and it like, which, which comes first. And, and even though one might be like theoretically easier, like the agent using an agent site is easier. It, the tooling just might catch up so fast that it, it's not a concern and you know, there might not be much of a difference. Uh, you're, you're totally right. And that is, that is a risk for, for Lasso because, uh, which, and to be clear, it is a risk for the agentic product, but it's like, um, I'm happy if that risk is realized, like **(36:31)** we're, we're, we're in the, um, uh, we're in the utopia, but the risk is, uh, Lasso is making it more frictionless for an agent to be able to spend and receive funds both on fiat rails and crypto rails. And that's kind of what we're building in a sort of unopinionated fashion, but what is implied by AGI is that it's, uh, uh, sort of able to take over my personal life in a way that I would trust it where I don't care if it's out using my, my credit cards and my **(37:02)** bank accounts and it's able to log into my, my, my bank account to initiate a wire just the same as I would or better. And so in that case, having that frictionless form of payment methods as, uh, it almost doesn't matter. I can just use what's, what's already existing. So that of course is, that of course is a risk. Um, it, it, it's, it's not, it doesn't seem eminent. It does seem like there'll at least be a period where that frictionless form for agents will **(37:33)** be useful. It just remains to be seen how long that period is. Yeah. Yeah. This is very difficult to track because it's not like linear. It's basically, and, and maybe I want to see if you have a better way or if you agree with this framing, it's like whatever technology is currently available, then that's, what's kind of be going to be built on top. And, you know, maybe like traversing the site gets, gets way better. And then, and then people kind of move to seeing only like one step beyond like, uh, being able to traverse a site very easily. **(38:07)** And you kind of have like this, this, these peaks and troughs of what could be possible. And, and that like shapes the future outcome, uh, as opposed to like, you know, we're only going to use specialized websites that are like agent friendly to check out. So that almost kind of, uh, it makes trying to predict where stuff is going very difficult of, cause it kind of depends on what's available and what, what people are thinking is, uh, possible. Yeah. **(38:36)** Yeah. And, and, and it's, and it's, um, and the intelligence is not evenly distributed, which is, which has been kind of weird probably before, before, uh, um, before the GBD model three, uh, at least personally, I don't know if other people would assume this, but I would assume that the increases intelligence would be sort of evenly distributed, but they're not. I think a really good example of this is on the Cheeky Pints podcast, which is, um, from, from John Collison, uh, the younger brother of the two Collison brothers who founded Stripe. **(39:07)** He interviews the founders and he interviewed the founder of Intercom, which is, uh, um, uh, online chat company. It's on a lot of the websites you use. It's on Lasso and they have, yeah, it's a great service. That's what we use. And the founder is really funny. He's like, they were talking about kind of intelligence in the models and handling customer service. And, and, uh, and the founders is something like, so in the most recent model, it, it solved, um, you know, it's this outstanding math theorem that's hasn't been solved for **(39:41)** X amount of years, or it solved a fields metal level problem or something. It's like, Hey, right. It's probably smart enough to do customer service, which is like, not, not a, um, uh, uh, customer services, like is, is one of the most important parts of our business. And it's something that I spend a lot of time on every day, but, but it's accurate, but the agents are still, they don't have as high of a resolution rate as humans do, uh, which is odd, right? **(40:11)** Like it's sort of, even for Lasso where everything is online, um, and, and that uneven distribution of the intelligence is odd, is weird and kind of hard to predict to your point. Yeah. Yeah. It's not distributed across, uh, all the different, I guess, verticals of capabilities. Yeah. And if any of you, even if you deploy the model there, some, in some cases, the context window is not large enough or it's large enough, but it doesn't, but, but maybe the humans are **(40:41)** not even aware of the context they're using and their decisions. Um, and, and so that it's like, uh, it's, it leaves these gaps that are almost by definition hard for humans to, to see, right? Like, um, there's, there's this whole scope of things that, um, are almost hard to describe because they're so obvious, um, uh, uh, uh, that we eventually have to get AI to understand. Um, like a, a good, I don't know, a good example would just be that it's not a good example, **(41:19)** but I hold this, this code can in front of me. And what if I drop it, like I expect it to fall out of my, out of my hand, I have a feeling about how, how, how long that's going to take. There are even more core parts of the human experience that are sort of blind spots to us because fish don't understand the concept of water. We don't, we're so born in this that, um, it's, it's hard to understand what our core parts of our knowledge and we have to deliver that to, to agents. **(41:49)** And that's, that's a more broad goal than just what lasso is working on. But it shows those blind spots show up in surprising ways. Yeah. Yeah. Yeah. I've, I've noticed that a lot in like intuition or, or like what, what, what we would call intuition. Uh, and there's like whole fields, you know, like firefighting and where, you know, the, the interviews have asked them, okay, why did you take the team off of the roof? And they're like, you know, I just did. And the roof collapsed right after, uh, I think it's like tacit, tacit knowledge. Right. **(42:18)** And it's hard to kind of articulate the, the feeling. And, and I, it's, it, that's kind of like a human thing, right? This, this, this feeling piece. Um, but yeah, I, I agree that it's hard to translate those things. And the reasons why you see an email and you're like, uh, this is a scam, right? Is, is sometimes very hard to, to like, uh, pro make programmable. Right. And, and, and transfer that, that, uh, intuition of why this is a scam into like a machine. That, those are two, so much better examples. **(42:52)** You're exactly right. And it could be the, the, the email that I received from a friend, the, the wording is a bit different than how he talks to me. And I can't articulate why this kind of, it's a, it's a, it's a, it's a blind spot. And by nature, you know, AI won't, won't pick up on that, but yeah. But broader than this conversation, but yeah, yeah, yeah, this is super interesting because it's, it's making my head hurt a little bit, but kind of understanding the, the, the structure of how to pay attention properly to what could be happening is, is, is a very difficult skill. **(43:29)** And, um, I think you're kind of explaining and, and, uh, showing kind of the structure of how, how that can be done, um, for, for your product specifically knowing that, okay, this here's, like you said, where the puck is going, where do you think, um, kind of like some risks are? And I think you, you explained one earlier, but just in general, yeah. Like, how are you guys maintaining defensibility as the landscape is just so uncertain? Yeah. There's a couple of different ones. The one is regulatory. So we operate under this, this excellent, uh, um, regulatory structure that it last operates under the same structure that allows you to go to target and buy a visa gift card with cash. That is, you don't go through KYC process there. That's gone on for many, many years. And that's what we operate under. Of course that can change. Issuing banks can change. And that, that affects both product lines, uh, for humans and for agents on the agentic side. We may find that there, that there is no, there, there there's, uh, uh, agentic commerce **(44:35)** is not really a market. Um, and instead agents are just simply used to make human execution much, much better. And we jumped to these X-402 native protocols with really fast. There isn't a need for integrations at the fiat level. And then the third one is what Lasso is, is betting on is that having this frictionless form of payment methods for agents is really, uh, is really important. Like we want to have it as frictionless as it, it, uh, makes X-402 transactions. **(45:11)** What we may find out is that going through, um, uh, uh, your normal account signup KYC, KYB verification on Stripe, integrating your agent that way, having your agent know about how Stripe cards work and spending that or whatever provider is sufficient. And having that frictionless form that Lasso gives is, is, uh, it's not helpful. And having that more strenuous signup is sufficient. Those are all kind of three, three big risks. Uh, yeah. Okay. And, and, and then can you talk a little bit more about the, the, uh, bank account as well and where that fits in, uh, is this like an up and coming product you're saying that you guys are going to be focused on? Yeah. Yeah. So, so currently agents can do everything that a human can do on the website. That's get prepaid cards and you can spend online or via Apple pay and Google pay, get gift cards, um, for, for, for thousands of different merchants. And then we also have, uh, what's essentially a bank transfer. **(46:11)** You can send funds to a debit card attached to a bank account. So agents can do all of those essentially all outbound, uh, spending type actions. What we'll be adding this year is, uh, an optional, more enhanced KYC upgrade for the, for the owner or agent to get its own, uh, bank account where it can receive and send funds via ACH wire for people in the United States, SEPA instant in Europe, and then a reloadable credit card bin to give more flexibility there. **(46:39)** And then, uh, on and off ramps via PayPal and Venmo, which could be helpful for our bicycle example, um, those are, those are, uh, upcoming about half those products we have working in in some method and development. And I think with all of those parks I just described, your agent now does have all the financial tools it needs to participate in the internet economy. There's nothing financial that a human could do that it can't do. Um, and, um, yeah, and I, and I think that's, that's important is to get as wide as possible on that front. Um, so as these vertical specific things like Locus and Policia start to take off, we're, we're already there to enable it. Um, what we don't want to have happen is that there is some business to be made out there that an agent doesn't execute on because it's missing one of those pieces and kind of the world is, uh, um, the world is, doesn't get to have this business that otherwise would have got it. **(47:38)** So really betting on this, this agentic, uh, like entrepreneurship, really. Yeah. Agentic entrepreneurship. That's, that's a great, that's a great term. I haven't even used it before, but that's exactly, that's exactly what I'm focused on enabling. Nice. Nice. Wow. Yeah. That, that, that's a, that's a tall one right there. Um, yeah, definitely keep us posted on, on developments and, and the infrastructure is there, right? You, you know, the, these parallel teams are building and, um, and it's, it's very cool to see kind of like the coordination of the ecosystem and, you know, people are kind of tracking, uh, what other folks are doing and, and where they're headed and kind of where the opportunity is headed. Um, so yeah, yeah. Hopefully we can kind of facilitate that with, with Shoal, you can make it easier. Yeah. Uh, yeah. I, I, I love the focus on, on Shoal and you guys are doing a great job really, uh, uh, creating broad views of, of what's going on and then also deep in these, in these interviews. **(48:35)** So, so I appreciate it. As, as it becomes more legible, more people invest in it, it becomes more legible to agents as well for them to execute. So it's, you're, you're doing the world a good here. Appreciate it. Appreciate it. As, as we're, uh, as we're wrapping up here, we always ask at the end, is there any like specific alpha that, that you've picked up on or like a project, very interesting project, uh, or, um, even, it can even be a financial opportunity, but, but no financial advice on the show, uh, as, as a preface. **(49:07)** Um, but yeah, just some, some folks in the past have said things like, you know, I'm heavily focused on, you know, upskilling in this certain way or like this particular project. I know you mentioned, uh, uh, locusts and pulsea, but out of those two, uh, we can add those, but out of those two, yeah, just maybe, maybe the culmination of them together could be an option, but yeah, I'll let you have the floor on that. Yeah. I'll, I'll, I will shill our, our, our agentic wallet providers, which, which use lasso as a card provider. **(49:37)** And that is locust, uh, sponge or, or pay sponge.com and then ampersand. That's just a pure shill. So I think if I, uh, uh, like shill that we're already integrated with, um, maybe like a market level crypto market level shill would be, uh, on Meta DAO. Uh, I think they, they found a really interesting form of, of governments and token holder ownership, which is, which is really exciting. I think a problem that crypto has had in the past is you have these equity like offerings that are ruggable and it's been a blight on the, on the ecosystem and Meta DAO's found some really interesting solutions there specifically around decision markets, kind of like a form of prediction markets. So that's my, that's my, um, non-affiliated shill. Yeah. **(50:31)** Nice. Nice. Okay, cool. Uh, and in Meta DAO, they, they did a lot of it on like few Tarky on, on the governance. Um, and then also like a token issuance and stuff like that. And then on the, the pay sponge, locusts and ampersand, these are all like a agent spend or agent pay products that you can take a wallet, load it with crypto and then pay for services like Lasso. You nailed it. Exactly. Right. Nice. Well, cool, man. Yeah. Thanks. Thanks for coming on. This was great and it is great to, to kind of get inside of your mental model of how you're seeing the space and, uh, love to, love to have you again on sometime soon. I'm looking forward to it. I appreciate it. Thank you. Yeah. See ya. All right. --- # Agents Already Spent $76 Million: Circle's AI Agent Stack, x402, Stablecoins and the Agentic Economy > Shoal Signal episode. Guest: Corey Cooper (Circle). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-06-23 - Video: https://www.youtube.com/watch?v=vgD_BymhaCY - Canonical: https://shoal.xyz/research/episodes/circles-ai-agent-stack-x402/ - Keywords: agentic economy, AI agents, x402, micropayments, stablecoins, crypto, infrastructure, Agentic Payments, AI & Agents, interviews ## Transcript **Gabe Tramble (00:01):** Yeah, so Corey, when Circle says they're building the financial infrastructure for agents, what exactly does that mean? And and could you explain how that ties into X402? **Corey Cooper (00:11):** Yeah, yeah. So, you know What that means is we're focused on two layers. You know, one is obviously at the currency layer. So ⁓ USDC being basically a universal digital dollar that can transact on blockchain Rails. And then the other is actually the blockchain layer, right? The settlement layer. How do we make those transactions more performant? ⁓ create experiences where these transactions can be, you know, ⁓ high frequency. low latency as well as also to completely gasless. and so that is that is how we are approaching, you know, building infrastructure around the open protocol, which is X402. **Gabe Tramble (00:59):** And and for builders, like why should this matter to them and and and what is the benefit just to just to get us all caught up before we we dive in. **Corey Cooper (01:09):** Yeah, for builders, I think it enables builders to build experiences that were never able to do before. And so what I mean by that is, you know, most builders are building experiences for end users. And in order to deliver those experiences, a lot of times they have to basically get API keys to be able to deliver those experiences. And so APIs is is what the internet application layer has been built on to communicate. communicate you know value but also to information for the most part and so as a builder it's important to be able to deliver you know exceptional experiences to your end user and so XWorld 2 unlocks this ability for a developer to basically deliver experience where an agent or an application can actually communicate with an API endpoint without having to sign up get an account and create an API key. So So therefore, you can create these software to software experiences that are pretty pretty much limitless on the internet. ⁓ You can design an end-user experience where maybe that end user wants to access a lot of information around what is happening on social media from a social intelligence perspective. So now you can design basically an application experience where that person can access all of the information that's happening on ⁓ through a prompt and X402 is enabling that end user experience to be unlocked because that agent can go out, communicate with APIs that kind of scan what is happening on X and deliver a response of what that actual end user wanted. Before then, software was limited, you know, it was limited to what integration points the APIs had. Now with X402 developers can you know clear a lot of boundaries of building super apps maybe that can go out with agents and do so many different things as more and more API providers come on board to the protocol ⁓ with allowing for agents to pay and get access. **Gabe Tramble (03:31):** Nice. And so agents can basically access these services and the services can be accessed through micropayments. And kind of one of the big pieces is just USDC, right? The s circle product is the asset that is is typically being transferred. And I and I think it's like ninety-nine percent of the transactions, if not a hundred, are USDC or is USDC, right? **Corey Cooper (03:56):** Yeah, yeah. I think a l a lot of that, yes, had to do with one, you know, how USDC was designed from a token perspective, you know, ⁓ by default, you know, we wanted to build ⁓ very robust on and off ramps around USDC. because we wanted USDC to operate as a payment rail. And so in order for payments to be sent around the world, there is what we call on and off ramps into bank accounts. And so our team has done an excellent job of going in the front door in all these different regions of the world and abiding by the regulator. to basically build a highly regulated stable coin that follows the rules and that people can trust that they can actually use this as an interoperable, you know, ⁓ programmable money with the actual fiat system. The other thing is there are some things on the initial design of USDC from a token contract perspective that allows people, ⁓ well, developers actually to interact with functions on the contract. And one of the critical functions that enables ⁓ a gasless flow in the XO 402, you know, work workflow is ⁓ basically ⁓ EIP 3009, which is a transfer with authorization call. So think of that as when the Agent is calling that ABI function is basically signing an authorization that hey, this amount of money I authorize to be basically deducted from this wallet, and it's passing it to basically a facilitator, and so that facilitator and handles the broadcasting and the verification of signature and settlement of that X402 payment, and therefore the agent or the end user initiating it does not have to worry. So it's it's sending that authorized transaction as a message to basically a facilitator and facilitator can can actually handle the rest as opposed to a traditional transfer that happens with the USDC token contract where the initiation requires gas. So there are you know a lot of different things, but that was one design ⁓ you know, choice that was made early on on USDC. that enable the team that launched X-402 to actually build a very gasless, seamless experience early on. **Gabe Tramble (06:32):** And and so because of the positioning, because you ⁓ like control more or less the the or or issue the the underlying asset, you guys have the ability to do things that just other service providers can't, like this, this, these gasless transactions. And just before we move on, can you can you just share a little bit of context and ⁓ like definition around what the facilitators are and and where that fits up actually in the stack? **Corey Cooper (06:59):** Yeah, yeah. ⁓ you know, a facilitator and X four two flow basically handles the verification of the transaction and then broadcasting that transaction to the actual blockchain network of choice that the that the payment scheme is requiring. And so ⁓ you have like Coinbase, they run a facilitator, do an excellent job, and then you have other companies in the space ⁓ that are running facilitator companies and they're handling basically basically the They're like the acquirer, right, of the transaction. ⁓ and then passing that on to the network and ultimately that is being ⁓ you know deposited into the merchant's wallet address. And so in order for that flow to work, like I said, that transfer with authorization, ⁓ **Gabe Tramble (07:43):** Got it. **Corey Cooper (07:52):** ABI function on the USDC token contract enables that flow to occur in a gas-free, gasless experience. And it was one of the ⁓ you know initial you know ⁓ design choices you know early on of the evolution of USDC. How do we do these things? Because we're we do want to have a future where developers or end users can have these experiences where they don't have to have to worry about. that kind of friction point of of like gas. And so so that that's how the facilitator kind of plays a critical w role of like acquiring those transactions, verifying them and then broadcasting them to the network and settling them in the merchant's wallet address. **Gabe Tramble (08:38):** And and basically you're saying you guys have like multiple pieces in the stack. So there's the asset, you know, the facilitator component, and then even the chain component, which which if you could chat on in a minute, ⁓ and then also the application. So if you can if you can go through ⁓ like the full stack and and in its entirety and and kind of hit on these these two pieces, because even on the application side with the the the wallet CLI product, you you basically end to end. **Corey Cooper (09:09):** Yeah, yeah. You know, ⁓ you know, as we saw the growth happening in the X402 ecosystem, you know, we started to build a lot of technology around it. ⁓ and so ⁓ you know Obviously, USDC became very popular as the payment currency for X402 flows. ⁓ recently we've launched a CLI tool that allows for developers to easily give agents wallets. And so we we we actually launched it a couple weeks ago. And so ⁓ the wallets that you know you can access through the CLI tool also have built-in functionality that is connected to a lot of our on-chain primitives. For interoperability. So for you know, doing cross-chain transactions with CCTP ⁓ is something that you can get in that CLI tool. So if you're a developer building agentic flows that need to actually go from you know base to Arbitrum, or you know, eventually when we launch Maynet on Arc, you know, base to ARC, that that can be done with our circle agent stack CLI. But also too, ⁓ you know, we built a ⁓ Product that was specifically for agentic flows, which is Circle Nano Payments. And so Circle Nano Payments is wrapped in the CLI tool, and what it enables a developer to do is it leverages our ⁓ Circle Gateway product. So Circle Gateway allows for developers to build chain abstracted balances with USDC. So you deposit your your USDC in a gateway wallet currently. contract on whatever supported source chain we support. And what it does is it gives you basically this virtual balance that instantly can be spent or transferred on whatever native destination chain that Gateway supports. Well on top of that we built nano payments. And so nano payments allow for an agent to deposit their funds in in the gateway wallet contract. And then once it was in the gateway wallet contract, They could perform gas-free transactions to any ⁓ X402 endpoint that supports basically our gateway batching ⁓ you know, ⁓ gateway batching x402 ⁓ product. And so if the merchant has added basically gateway batching to their X402 endpoint. And the agent has a gateway balance. It really doesn't matter what the merchant's chain is of choice of where they want their actual USDC to be sent to. ⁓ it can be transacted, you know, from a gas-free chain abstracted experience, and then the merchant can actually basically batch settle those ⁓ transactions onto any supported USDC chain. So it creates this. experience where we're trying to get to a world where chains don't matter ⁓ when you're dealing with usdc and so we want to you know move toward a world where agent just has usdc and the x402 endpoints are chain abstracted and agents can just transact ⁓ with these endpoints without saying I've got to be on this same chain you know as my wallet to actually Transact because that creates a lot of you know friction and fragmentation in the ecosystem. **Gabe Tramble (12:54):** For the the transactions that you're seeing that that you're either hosting through the application or just seeing in general as like the entire ecosystem, which is a lot of transactions for for USDC with regard to X402, what are the use cases or the the types of users that you're you're seeing right now? **Corey Cooper (13:14):** Yeah, so the types of users we're seeing in the X four two ecosystem is a lot of ⁓ power users who are probably ⁓ technical users who are working in ⁓ a lot of these coding agent terminals, whether it's cloud code or you know, even cursor codecs. ⁓ and they're working in these these terminals, but they're actually not just coding in these terminals. They're doing a lot of research and other things. ⁓ and so those those power users are basically kind of using it as their their gateway to doing research or accessing information on the internet. And they don't want any limits. ⁓ and so using X402 within those those actual products gives them the ability to not only do their work as they're building products and software, but also do a lot of research where they can go out scrape the internet, scrape different social networks, ⁓ or access a collection of AI models ⁓ as well. And it it just gives them the ability to expand what's possible, you know, from their their entry point of how they're they're working, you know, every day. And so so we see a lot of lot of like technical people, but also too we're sort we're starting to see ⁓ ⁓ non-technical people start to take advantage of these these tools as well. ⁓ You know, as you can see, like Claude, Codex, Cloud Code and Codex, they're they're you know designing these UI interfaces to be a little bit more friendlier ⁓ for the non-technical people. And so you know these these non-technical people you know who I see adopting these right now are mainly like people who are highly focused on like ⁓ marketing data. And so they're starting to be power users too in these ⁓ in these different products and they're leveraging now more and more X four two resources because they're seeing how powerful it is to just have access to ⁓ pretty much thousands of APIs through pay as you go model when they have a wallet, you know, in their in their Product. **Gabe Tramble (15:46):** Yeah, yeah. Personally, just a as as a user of of the the Circle Agent product in in my experience, it just really just flattens the ⁓ the internet. And and it seems like just from what you're saying and just some folks that we spoke to in the past, like like Merit Systems, we we had them on ⁓ from Agent Cash, like a lot of people are doing search and retrieval type of jobs where maybe it's like prospecting or as you're saying, ⁓ like marketing, you know, finding information from From social platforms. A more deeper question here, like if we have ⁓ a era, you know, let's say two years from now, and you can basically just call anything that's available on the internet due to these tools. ⁓ because what's happening is like someone can be a domain expert in one specific ⁓ retrieval lane or data lane, right? And they can kind of just focus on that. but what do you think kind of the dynamics of of the internet? become and this is more of maybe like a broad question, like what are the impacts if if everything is just accessible and there's really no gates anymore and it it's just monetary gates. **Corey Cooper (16:55):** Mean I I think that You know, I I would like to think pretty optimistic. I think ⁓ it would make everybody a little bit more smarter. ⁓ if if they had access to, you know, anything that was on the internet or behind an API, ⁓ and they could access the things that are behind the API at a fraction of a cent, you know, per request, I think that would give people more intelligence to make more informed decisions. so that's kind of what I what I think potentially will happen. ⁓ you know, when we when we went through the Google era, right, ⁓ people now had at their fingertips the ability to just search anything that was published online because Google did excellent job of indexing. And I think this is kind of an iteration on top of that is now ⁓ paywall content and research Now, you know, that type of information can be monetized from a pay-per-use perspective, unlocks more opportunity for people to actually access it. Because before X402, the the economics didn't make sense for that type of content to be accessible from a pay-per-use perspective. because, you know, you were leveraging fixed costs that were built built into ⁓ you No ⁓ car transactions. **Gabe Tramble (18:29):** Yeah. At at the the the service provider level, is are you seeing kind of the same reactions and and maybe if you can talk just like as an enterprise talking to other enterprises, what what has been the reaction and and that kind of assumes that you're talking to these these types of companies, right? Like the the X Pro two providers. But yeah, if you if you can touch on anything as if it's like an enterprise consuming these tools or enterprise providing the tools, if you can share some some some details around that. **Corey Cooper (18:59):** Yeah, I mean we we've had several conversations building up our marketplace with providers who are on the enterprise side. ⁓ what was interesting is, you know, ⁓ Most of them knew about X402, but the ones that didn't, the aha moment was, you know, this is a a new customer persona that you can target, right? Which is agents. And agents is the hottest thing in AI, right? And also too, it's a new revenue stream. And so at that moment, when we kind of explain that it's a new persona and a new revenue stream, that's when it clicked. to these actual providers that we should try this. And so I think ⁓ you know most companies that start get exposure, they start getting some exposure to these ⁓ these conversations, I think I think it's kind of a no-brainer for them to say we we need to try this out because There's not many opportunities where you're going to a business and you're saying there's a way for you to target a new customer persona that's growing rapidly. And we have data to support that there's been over $76 million worth of transactions that have happened, you know, with this new persona. And it's growing daily. And also, by the way, like this is a whole new revenue stream for you. And I see think when you kind of talk from those perspectives, everybody starts. **Gabe Tramble (20:35):** Yeah. for the the the back to the consumers, ⁓ for like the stuff that they're they're transacting, is there any like ⁓ additional places that you're seeing like activity or in interesting workflows? ⁓ maybe it's like a sp certain type of endpoints that are being targeted or or maybe like provider behaviors. Yeah, is there is there like some some more detail just as as a as an operator on the front lines that that you've noticed in trends there? **Corey Cooper (21:04):** Yeah, most most of what we're seeing like, you know, ⁓ from the conversations I've had and working with different providers is number one is we're seeing like research on social. ⁓ mainly like on X. number two is ⁓ People in certain markets wanna access certain models and they can access them because ⁓ they can get access to, you know, traditional payment rails to be a customer of those. ⁓ so ⁓ company like Block Run, they're actually providing frontier models to emerging markets of people who don't have the means to, you know, ⁓ pay twenty dollars a month, right? For a frontier model, or they don't have access to a you know, credit or debit card to put on file because there is lack of banking infrastructure in those markets. So ⁓ that's number two and number three financial intelligence from like the US equities market. So ⁓ there's a lot of ⁓ providers that are providing a lot of granular financial data on, you know, ⁓ Nasdaq ⁓ S P five hundred companies and ⁓ they're using agents to actually, you know, help them make financial decisions on, you know, ⁓ strategic investments. So those are those are the things that we're seeing a lot of. **Gabe Tramble (22:32):** Okay. And and we've we've kind of like covered the the the use case, right? And in and the areas in which people, you know, you guys on what you're doing and the and the in the use case for this broader agentic commerce piece, ⁓ right now what we're seeing is like agents hitting endpoints, right? Like service endpoints. What do you think is missing for this ⁓ kind of like agent to agent, ⁓ fully automated environment, ⁓ or even like fully automation is a baked in. assumption, right? What is your maybe like two-year ⁓ visual look like of how agents are interacting based on kind of what we've seen and in your experience so far? **Corey Cooper (23:14):** Yeah, you know, I think ⁓ it's a great question. You know, obviously I think the reason why I feel like ⁓ agent to API, you know, is working very well is APIs are deterministic, you know, so like ⁓ and APIs kind of like control how integration works on the internet with software. And so ⁓ it's it's a easy ⁓ entry point into it to a customer experience, right? I think with agent to agent, there is there's a lot of risk that a lot of people are building technology around, you know, ⁓ agents can tend to hallucinate. So if there is one agent communicating with another agent, you know, there's that huge hallucination risk. ⁓ and so ⁓ there's a lot of, you know, risk around just kind of prompt injections and things like that. So I think there's a lot of and then you know there's there's the deterministic part, right? Starts to break down and then how, you know, do we include human in the loop and things like that to make sure like the agent to agent commerce stuff actually starts to work well. ⁓ I think ⁓ I I think we we we there is a lot of teams I would say are working on, you know, solving this, but I think right now we're still some ways away for the agent to agent commerce ⁓ story to kind of ⁓ you know, spread as fast as we've seen the agent to API. **Gabe Tramble (24:59):** Yeah, yeah. On the agent to agent commerce, it's it's hard for me to, and I have said this before, to basically like conceptualize what the use case is outside of it being connecting to a deterministic like marketplace, or you know, the agent talking to a service, and then maybe that service talks to another agent. ⁓ maybe that nuance doesn't matter. It it it seems like there's something there, but I I do agree with you kind of like my codex talking to your codex for whatever. Reason for for transacting value, it is it I've just I can't see it yet. ⁓ but yeah. **Corey Cooper (25:36):** It's yeah, it's it's it's tough right now because we just haven't, you know, seen any products take off, you know, that ⁓ that can showcase that. ⁓ there's a there's like I said, there's a lot of teams working on it. I've seen a lot of like agent to agent, you know, platforms for, you know, doing like task rabbit jobs. It's kind of like a like platform focused on being a similar to what's the name of the Company I'm trying to think of. Those platforms are like freelancer platforms where you can put up like upwork, those types of yeah, fiber and those. And so I've seen I've seen people kind of build systems like that where agents are submitting work and other agents are picking up the work, and then there's like escrow contracts in the middle to facilitate that with USDC. ⁓ and then you know, you have like these different standards that are happening in the ecosystem, like the 81. **Gabe Tramble (26:17):** A board or five or **Corey Cooper (26:42):** 183 standard for agent representation or reputation. And so those things, you know, are being built, but we we haven't seen them kind of like take off as fast as we've seen, you know, the age of the API stuff. And I think it's just an easier sale right now for the average person to experience the the agent to API because they understand the concept of APIs are usually like subscription based. And now I can, you know, put a dollar in, interact with this API, and not have to sign up and do all this stuff. But I'm still getting like the value and it's just a paper use. And it feels like Apple Pay actually. And I think that moment kind of makes people kind of gravitate more to like, well let me continuously experience this agent to API. The A to A it's still a lot of groundwork to be done to give that visceral like consumer experience where people, you know, are saying, I've got to get more of this. Yeah. **Gabe Tramble (27:48):** Yeah. Yeah. See hitting you know, orchestrating like a couple endpoints together and then getting the result through X402, I think is like a magical experience that you have to experience and then you're like, okay, this this makes sense. do you think that's enough? You do you think this this can be, you know, ⁓ billion, multi billion, hundred billion, trillion dollar market just on ⁓ you know, the the paper use? **Corey Cooper (28:01):** Yeah. Yeah. yes. ⁓ yeah, because you know every application has APIs. And so when this becomes the standard Every software application can communicate with other software applications through X402. And so if we want to like think about the TAM of software, that's trillions. And so ⁓ and I think that you know you think about it, just think about just like the integration that it takes for software, you know, to integrate APIs. And then you think about how fast, right, agents can adopt APIs and use them as standards, that that could be the new integration point. Software has an agent that goes out and needs to get access to another software application. That software application has a collection of H402 endpoints that they're willing to give the agent access to. and it can go out, retrieve the responses, and then input it back in the source software. We could, you know, see that future pretty soon and it looks like we're trending in that direction based on the behaviors we're seeing with how people are stringing together different X402 endpoints to get results. **Gabe Tramble (29:45):** So is SaaS dead? Everyone says SAS is dead, but we're kind of seeing the early indications of, you know, more use and and easier discovery for these products, just in a different format, right? And it it I think there's so much conflicting information if you gather it all together. I'm curious what your take is on how this evolves for like service providers. Do they commoditize or can they kind of stand out and and even overperform? **Corey Cooper (30:15):** Yeah, I don't I don't think SAS is dead. And I think ⁓ a lot of people have to think about kind of these SAS models and how beneficial they are to you projecting, you know, your earnings at the end of the year, right? You know, I think that what it will do is I think ⁓ it will complement SaaS sales. So think of it like this. You you you've seen, you know, a lot of companies, SaaS companies, they'll have like a seven day trial, right? Well, but X402, maybe there's no more seven day trials anymore. It's just you can pay per use, right? Or you can opt into the SAS. And the seven day trial period kind of goes away and it's just an X four two endpoint. Maybe there's certain rate limits, right? That you're constricted to if you're using the X four two endpoints and if you need to upgrade to higher level rate limiting, more, you know, more support and things like that because you're gonna be doing like a lot of transactions with this API point endpoint, then there's ability for you to kind of upgrade and just opt into the SaaS. But in the beginning you can kind of run your trial off of X402 endpoints. And now the API provider they they don't have to worry about ever losing money on servicing an API endpoint. You don't have to worry about the churn that happens when someone signs up for a seven-day trial, right? Puts their card on file, and then on the sixth day, right, cancel it. At least at day one of you providing that API, right, to an agent or a human, you can monetize. **Gabe Tramble (32:11):** Yeah, that that is something that we've been looking at a lot. And and basically like our thesis is the the value or like a large portion of the value for now, right? This this could change in like two years. Is the discovery layer? And kind of what you described is this threshold from ⁓ a customer, like the initial customer is the agent on behalf of the person that can convert as they hit like a certain, you know, demand, if they need more demand than than than what is present. And that that's kind of like our lens and how we're looking at at the space. And for yeah, actually, first, yeah, what do you do kind of what what is your take on that? kind of the way that We're seeing it. **Corey Cooper (32:54):** So as far as like discovery ⁓ is concerned, well actually restate your question to make sure like I understand so I so I answer it correctly. **Gabe Tramble (33:05):** Yeah, yeah, yeah. So we we think that The discovery piece of of kind of the the accumulation of using the product is a form of discovery and it's almost better than advertisement. You know, traditional ⁓ advertisement because you're getting the the payment right then and there. ⁓ and kind of what we're seeing right now is that is a huge portion of the value add, right? Is this discovery and kind of early ⁓ planting the flag into a new customer? ⁓ I'm yeah, I'm curious. Are you guys Is leaning onto this kind of discovery piece or primarily focus on okay, you know, t two years from now or a year from now, when we start seeing extr you know, a very meaningful volume. ⁓ it's it's almost like a a chicken and an egg and and for the for the service providers, we're just seeing like the value today is literally on the the discovery. ⁓ primarily. So yeah, curious curious if you if if you agree or disagree, but ⁓ or how that's probably impacting like how you guys are moving forward. **Corey Cooper (34:10):** Yeah. So, you know, at Circle we haven't, you know, ⁓ focused much on on the discovery layer. We're focused mainly on the settlement and the transaction experience, right? with USDC. but discovery is huge. ⁓ what I'm seeing a lot of is, you know, a lot of these companies that are playing in the space that are doing very well, they are actually kind of playing both sides of the fence. They're building up the actual technology. ⁓ on the buyer side and they're building the technology on the sell seller side and they're using skills that are built into their agent buyer side SDKs right to make it easy for the actual ⁓ marketplace of sellers, you know, to be more discoverable. And so I think ⁓ right now I I definitely think that discovery is very, very important because one you want to start you know ⁓ driving a lot of traffic to these actual marketplaces ⁓ so that the word of mouth actually can build up where more providers are want to come and and and actually wrap their API endpoints with X402. And so I see ⁓ right now you know Bazaar basically the X four two ⁓ layer that Built for Bazaar to make things more searchable, adding different like metadata to the actual schema. And then I obviously, you know, Temple has theirs with MPP, they have a discovery layer as well ⁓ that you can add to your endpoint to make semantic search better for the agents to find those endpoints. And so I think that is gonna become you know ⁓ more and more important. You'll probably see more sophistication around indexing and ranking, kind of like what we ⁓ And I think I think right now though what we're seeing in the market is, you know, our a lot of our marketplace providers are actually building basically skill.md files ⁓ and they're building the actual SDK as well and trying to acquire consumers so that their endpoints can actually, you know, be discovered a little bit better. And so they're trying to build up both sides of the house at the same time. And so you know, it is it it's gonna be interesting to see how it plays out from a discovery layer perspective for the ⁓ providers or the sellers. but it is gonna be very important to their businesses because they're gonna wanna rank high and I think ⁓ we're gonna start to see way more sophistication around there pretty soon. **Gabe Tramble (37:06):** Yeah, yeah. Right now there's ⁓ there's some pretty pretty solid providers on on the the network and ⁓ I've seen some stat that they're coming on like every couple hours. You guys have a marketplace yourself. can can you just chat a little bit about like how you built the marketplace, not from a like technical perspective, but almost like a a methodology and the the types of companies that are there and and and maybe why you chose those. because that that will help us kind of understand, okay, what's available, you know, b all this stuff is like on chain, right? You can't really see it. So you're a discovery layer in your yourself. **Corey Cooper (37:45):** Yeah. Yeah, like I think ⁓ when when we started to kind of like build out the curation of the marketplace, I think the first thing we started to look at is okay, where is most of the, you know, activity happening in the X402 ecosystem that we believe is gonna be around, you know, for the long haul, right? And so ⁓ you know, one of the main things we saw were like marketing teams, you know, using Codex, they were using Claud Code, ⁓ and they were using, you know, even ⁓ you know, OpenClaw, right? To to do marketing research, right? And so we were like, okay, these things are being used by by for a lot of marketing research. ⁓ and then we start to talk to some of the actual early X402 endpoint providers, right? To ask them like, where are you getting most of your usage? And there was a common theme, you know, and that common theme was two things. It was social intelligence and then it was financial intelligence. So that's when we were like, okay, we've got to start like curating a marketplace, you know, that that is mapping back to the behavior of the early traction. Because, you know, if we can curate these these these providers and they can provide really good data, we think that the people who are the power users will eventually you know start building very innovative, basically agentic powered applications, you know. Instead of just a one-shot prompt, they're kind of thinking long term, like how can I actually build basically some software where I have agents, you know, embedded in this software accessing this marketplace of endpoints to provide some service to the end user. And so ⁓ just you know one provider in particular, you know, ⁓ I founded a hackathon you know in SF. It was this company called ⁓ AISA. ⁓ and so they provide a lot of financial intelligence and social intelligence endpoints. ⁓ you know, and they joined our marketplace, one of the first ones to join. there's other companies, Block Run, they kind of focus more on offering ⁓ inference from a pay per use. perspective with all these different frontier models and and local models and open source models. They were getting a lot of traction, you know, for for their ⁓ their inference. ⁓ you know and and so we we partnered with them and brought them in into the marketplace. And then ⁓ you know we started to think about okay like what type of ⁓ workflows you know we're These users will be kind of connecting together multiple A X402 endpoints to do something. What what does that look like or whatever? And you know, we we added ⁓ you know, stable enrich ⁓ and and stable email shouts out to the merit systems team. ⁓ we started to add their stuff to the actual marketplace as well because that's important if you kind of want to build workflows that leverage email ⁓ or phone calls. Calls. ⁓ and then we recently added ⁓ Twilio and Bland that a as well to the marketplace because we saw wherever someone may want an agent to make a phone call, capture some information, and then, you know, ⁓ store that in maybe like a spreadsheet or a Google Docs. So we were thinking like, okay, what type of workflows outside of the social intelligence and the actual financial intelligence that people want to use on a daily basis to be more pro but productive and then let's curate these these endpoints. in our marketplace to actually build, you know, ⁓ the best, you know, ⁓ experience from a a a discovery in a marketplace perspective if possible. And we're constantly adding people to the marketplace or companies. So ⁓ you know, any company, you know, that's interested definitely go to AgentStyCircle dot com and you can submit to be added. But, you know, we really want to build that up because that's the most important component to the agent actually being ⁓ you know, ⁓ valuable. **Gabe Tramble (42:25):** Yeah. Yeah, this this trend that that that you're you're saying and and and and that we're seeing too is that these very specific workflows, ⁓ social is what you're saying, you know, financial intelligence, ⁓ again, like this search and retrieval of information, synthesizing it. And I think this the the this is kind of like the value add right right now for for X four two, a value proposition for people using it. There's tons of different stuff, right? There's probably airlines and there's There's you know, stuff that's long tail, right? ⁓ but for now I think that that's makes it very clear cut on on what people are doing. I'm curious, and and this is probably a lot of people's questions, ⁓ why do you think this needs to be on stablecoin rails? And and specifically, you know, why can't this be a bank that, you know, issues something? And and why do you think that stable coins are the perfect vehicle for ⁓ these type of ⁓ interactions between an agent and and a service? **Corey Cooper (43:30):** Yeah, I think ⁓ well one I think the actual the settlement aspect, you know, of the merchant actually, you know, receiving instant settlement is important. ⁓ I think the other thing because their value is being given out right immediately. So in that X four two flow, you know, you have hit the endpoint it re re returns the four or two required and explains like this is how much you have to pay and then after that is paid then immediately you're exchanging digital information, right? And so if someone wants to exchange something digital, ⁓ they they wanna be, you know, they wanna have instant settlement. So I think that's that's one. But I think, you know, the biggest thing, right, is When we take a step back, right, and think about like Circle's ⁓ mission, right? Our mission of a company is about raising economic prosperity through the frictionless frictionless exchange of value, right? And how we do that is through USDC, right? It's something that is accessible by anybody around the world ⁓ who has an internet connection and a wallet. And so those things in in in pretty much most markets are are almost free, right? You can you can you know access the internet free in a lot of places and then you know for you to create a wallet ⁓ that is that's free as well. And you can actually have based A digital dollar account that's equivalent to you know ⁓ you having basically a dollar in a bank account, and so when you start looking at X402 and information. Information is value transfer, and we want to make sure you know everybody around the world has access to information and also too, most recently, we want to make sure everybody in the world has access to AI and models and inference. So the reason why it's important for stable coins to continue to be a method used in X402 flows is because you are able to enable people in certain worlds. parts of the world who can't get traditional banking accounts or or debit card or credit card to actually pay for intelligence. And and so again I I bring this company up so many times in this this interview, BlockRun, you know, they're servicing inference to emerging markets who can't get access to these models any other way. And so the only way is through a stable coin And so we want everybody to have access to intelligence. And so that's why it's important for stable coins to be a critical component of, you know, the the payment methods of X402 endpoints. **Gabe Tramble (46:37):** Yeah, this this is really interesting 'cause it it almost skips a step and and I'll get to that in a second, but even even before saying that, I think in the in the US we forget how ⁓ privilege, you know, people are to have a robust banking system. And really stablecoins just issue this blanket financial rail, right? Globally that that is literally fully global. ⁓ and and for like the ⁓ the the the primitive of basically like having these cer access to these services, ⁓ it makes it really easy for folks that you know traditionally would try to get like a stablecoin maybe to fiat and then create an account and create the service. But it's almost like X402 is is removing ⁓ a a chunk out of that that process where you know people no longer need to like figure out the the on-ramp, right? Because there there's like some crypto cards and services that are like crypto to X to ⁓ fiat or crypto to like a foreign currency. ⁓ but this just goes straight to the service, right? You don't even need to kind of ⁓ intermediate the change between currencies anymore, which usually was what was what people were working on, right? so that's that's pretty interesting. I'm curious how that kind of plays out **Corey Cooper (47:58):** Yeah, yeah. And I think also too, you know, another thing is You know, the the on ramp experience in the US for X four two and USDC has just gotten a lot easier. I don't know if you had a chance, but you know, Cash App just turned on USDC payouts within Cash App. And the way the experience works is you go straight from your, you know, dollar balance in your bank account in Cash App to basically on chain with USDC. So there's no there's no like on wrap experience basically your cash balance in cash app is interoperable with USDC on select chain so now if you're trying to fund an agent wallet to do an X402 transaction it's just you know you just going in cash app and putting the wallet address in there and just sending it and boom it goes from fiat to stable coin into your wallet in less than like one second. So so like you know, I think you know over time, you know, when stable coins become more interoperable with people's bank accounts and we're removing that that actual UI experience of on wrapping and it's just kind of like directly interoperable with with stable coins on chain, I think you're gonna see more actual X four two transactions actually proliferate because like the on ramp experience will it'll just kind of be invisible at that point. **Gabe Tramble (49:40):** Yeah. Wow, yeah. Cash app to to agent to ⁓ to agent operations is is is a pretty interesting pipeline. **Corey Cooper (49:48):** Yeah, yeah. **Gabe Tramble (49:50):** That's good. Just just as we're wrapping up here, I'm curious for you, and we and we've been asking this question to folks coming on, where do you see like the ⁓ alpha bubbling up? Whether it's ⁓ something like a like a block run, right? ⁓ but something that is gonna be like a big opportunity within the space, ⁓ just from your experience and what you're seeing. Yeah, like where where should we be paying attention to or just like check out something super interesting that you see some longevity and value accruing. **Corey Cooper (50:23):** You know what's interesting? I don't wanna say it's gonna come from one thing, but I'll say it's it's it's it's it's a few things that could happen, you know, that could that could drive massive adoption. One is I think that there's still an opportunity ⁓ for companies to build the most ⁓ you know, frictionless consumer agent experience that gives you access to thousands of X402 endpoints in a way that you really don't know that ⁓ your interact X402 endpoints. ⁓ I think Merit Systems Poncho product, right, is kind of leaning in that direction. I think what we're gonna see though is the these consumer apps that access you know a collection of X402 endpoints, ⁓ the UX experience will be a lot less verbose. I don't know, like you know, when you're doing these X402 endpoints in interacting with them in a coding agent, you know, you see a lot of things like bash scripts being ran and stuff like that. So that can be a little intimidating for the average person. But I think you're gonna see, you know, some breakout consumer mobile app that basically is running a lot of transactions through X four or two flows that is gonna blow up and it's gonna drive basically the snowball effect of, you know, a lot of API providers wanting to come on board. and and and access, you know, ⁓ you know, the community for, you know, the user base. ⁓ I also think that you'll probably, you know, start seeing ⁓ you know, more and more situations where, you know, like the other day Robinhood launched, ⁓ there third party integrations to their APIs. So that was a big deal where you could basically bring your third party agent to connect to Robinhood's APIs. And so if if you see more of that where APIs that were private are being exposed to agents, well what could potentially happen is that agent is like, okay, I have access to these APIs on Robinhood to To make trades and manage portfolios. Well the agent One thing they're gonna want to do is get smarter, right? And so the easiest way to get smarter from that agent that's low friction, right, is through X402 endpoints. So now that agent, imagine that agent getting very smart by calling different X402 endpoints in the circle marketplace that is giving them financial intelligence data, right? And then it's taking that data and information and using it to make informed decisions. against trading on Robin Hood. Those type of, you know, interconnections, they may look like they're isolated, but they're not, and they're gonna continue to grow the community because more and more people are gonna try to figure out how do I make my agent intelligent really fast without having to set up thousands of API keys to make it, you know, intelligent really fast. And the fastest way is through, you know, the X402, you know, ecosystem. **Gabe Tramble (54:11):** Yeah. Wow. Corey, yeah, this is this this has been great. ⁓ I think the for for the the consumer use case, the payments piece, even something as simple as like knowing your balance or or estimating how much a a workflow might cost is kind of just hidden in the in the logs. ⁓ so yeah, that that's that's a really big one. Almost like a ⁓ like almost think of Moonshot, right? When people were like trading coins and and Moonshot came out as a whole new, you know, Apple Pay, USDC. you can easily buy ⁓ coins, similar experience that you're seeing with ⁓ merit system poncho and yeah that that that's a good one **Corey Cooper (54:53):** Yeah, yeah, yeah. So I think ⁓ you know, there's there's a lot of companies, you know, in the in the space that are building really cool stuff. So I just encourage people to you know who are listening to actually immerse yourself in the community and and try out these products because these builders in this ecosystem are very smart, very passionate. ⁓ and I think that, you know, ⁓ check out different projects that are in the ecosystem now, like, you know, ours, which is Circle Agent Stack, but also to You know, there are other companies like Proceeds that are building basically a lot of the plumbing on Bringing providers online and and managing ⁓ you know, wrapping their endpoints at scale. Block Run is another one as well, and AISA and several other providers. ⁓ you know, Sponge is doing an excellent job in the community. So there are companies that are really, really focused on building up this community on the seller side and the buyer side. ⁓ some are doing both sides. ⁓ you're gonna see more and more companies like just get laser focused on this ecosystem because, you know, if you're looking at the data, you know, it's showing, you know, a trend of going up, not down. And ⁓ in and companies want to open up opportunities where they can make more money. ⁓ they can access different markets that they couldn't access before because of the stablecoin innovation being built into, you know, X402. So ⁓ so yeah, this has been ⁓ a great conversation, but you know, I I think highlighting a lot of these these companies ⁓ you know, and and having people kind of just test them out is just gonna put the push the industry industry forward. **Gabe Tramble (56:42):** Yeah, yeah, I agree. The the biggest value is is is trying it out and then you can kind of mentally understand, wow, okay, these things are powerful. **Corey Cooper (56:51):** Yeah, yeah. I think yeah, that that is that is the experience. You have to try it out, you know. ⁓ I think it's it's it's still difficult for us to explain it in a way that does better than you experiencing it. Yeah. **Gabe Tramble (57:08):** Corey, thanks again man for for coming on. ⁓ hope to have you on soon. **Corey Cooper (57:12):** Yes, thank you. Thank you. I really appreciate it, Gabe, and ⁓ look forward to reading all your literature. Okay, thanks. **Gabe Tramble (57:18):** Appreciate it. See ya. --- # Agents Are the New Websites: MoonPay's Tony Plasencia on the CLI Bet and Agent Commerce > Shoal Signal episode. Guest: Tony Plasencia (MoonPay). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-06-15 - Video: https://www.youtube.com/watch?v=yrUMZuaVeMs - Canonical: https://shoal.xyz/research/episodes/moonpay-tony-plasencia-cli-bet/ - Keywords: AI agents, agentic payments, MCP, crypto, prediction markets, Solana, interviews, Agentic Payments, AI & Agents ## Transcript **Gabe (00:00):** Hey everyone, it's Gabe from Shoal Research and thanks for tuning in again into the Shoal Signal Show. And I'm here today with Tony, who's an expert on agents and payments. and all things on chain when it comes to CLI, MCPs, all these things, and we're gonna get into it in a minute. But yeah, I'm pleased to introduce Tony, and Tony, could you just give a little bit of background about your experience post-Web 2 where you were at Thumbtack and at Uber working on Agents, starting with Griffin, and then kind of your transition to MoonPay. **Tony @ Moonpay (00:33):** Yeah, for sure. Well, thanks for having me, Gabe. Started in Solana about five years ago, building Underdog Protocol, which was a digital assets API and worked with Art Basel, Solana Foundation, and Solana Mobile, was a Solana hackathon winner, grand champion, ⁓ and scaled that out, ⁓ then transitioned into Griffin, the whole idea of it. behind our relationship, my co-founders and I is ⁓ making crypto very easy to use. And we realized LLMs ⁓ were the easiest way to do so. ⁓ So we built Griffin, scaled that out to close to 80,000 users, ⁓ about seven, eight figures worth of revenue and volume and joined MoonPay not too long ago to work everything AI and agents. **Gabe (01:25):** Nice, nice. And at MoonPay right now, you're working on a lot of the piping, right? So the CLI stuff, skills, MCP, this cutting edge distribution for agents specifically. Can you share your experience of ⁓ Griffin, which was much of a chat interface, right? Where the inference and the LLM was hosted within the application to this potentially new experience where the inference is hosted actually on the user's end. and leveraging your tools. So yeah, if you can kind of give your experience and how you're kind of seeing this transition from almost like owned chat inference interfaces versus the tools that, know, LLMs can reason on. **Tony @ Moonpay (02:09):** Yeah, for sure. That's a good question. ⁓ So at MoonPay, focusing specifically on the CLI and open wallet standard, ⁓ and what we noticed with Griffin and in the back end, ⁓ a lot of what was happening was simply tool calls. ⁓ when a user would come in with some sort of intent and say, hey, I want to create this cron job ⁓ that DCAs into specific meme coin, or hey, I want to use Moby to research and then place a trade through my Robinhood ⁓ crypto or through Jupiter. All that was happening at the backend was simply tool calls. ⁓ I think there's two parts to this. Number one is the owned interface, the chat interface, quickly got very ⁓ crowded. ⁓ And it was really difficult. It's classic consumer problem where it's difficult to ⁓ retain individuals. ⁓ So I think as we joined MoonPay, there was a lot of different initiatives and one large initiative to recreate what we've done. And ultimately where we settled was coming from an approach of, hey, everything that's happening already in the background is simply a tool call. Where we're seeing a lot of traction with AI specific tooling and LLMs is on the developer side. So instead of trying to recreate a consumer experience with which we may or may not be we as users completely ready for. Let's create something that's developer and prosumer focused. As you saw with like Claude code and with the codex, ⁓ the wave is saying those that really want to use LLMs are willing to spend times within their terminals. And that's when we decided to launch the MoonPay CLI. So with the MoonPay CLI, you get around 40 different skills, MoonPay and community owned. And you're able to within your terminal on ramp swap. do research with prediction markets, place trades on prediction markets, ⁓ spin up a virtual account, and then a lot more. So that's how we approached it. And I think ⁓ in the future, as we as builders figure out what the right skills and workflows and strategies are around tool calls or skills, ⁓ consumer applications will become a lot more prominent. **Gabe (04:51):** Interesting. And I guess, so before the way that your product with the Griffin was set up was you're kind of like the orchestrator and you piped in all the tools yourself where now there's kind of this transition towards being a spoke in the orchestration stack, which might be like a coworker or a Claude. At what point did you realize this and... **Tony @ Moonpay (05:02):** That's right. **Gabe (05:15):** Yeah, I guess like start start with that like at what point or like what was the signal or like what was the kind of the ecosystem rumblings that that made you realize that the stack actually is a bit separated in that sense **Tony @ Moonpay (05:28):** Yeah. So there is, I think, two parts to Griffin. Art one was the consumer ⁓ portion where anyone can go in griffin.com and start chatting with the experience. On the second end was actually the create your agent portion. So we allowed prosumers and enterprises to go in and create their own agents, turn the APIs into tools and feed that up into the into the consumer interface. ⁓ As we started to see more inbound from partners, we realized A, we can't do this at scale for individuals. ⁓ And B, a lot of enterprises are actually capable of doing this if they put a sole engineer or AI curious individual on top of it. ⁓ And so as we joined MoonPay, that learning of, hey, All of these are just tool calls. Hey, a lot of people are already a lot of AI, LLM native people are already using cloud code. ⁓ Let's go ahead and say, combine the LLM and the terminal with valuable skills that allow agents to move money. And let's see what comes out of it. And I think that's how we've approached building the CLI, ⁓ which is taking learnings from having enterprises and partners build their own agents on graphene. **Gabe (07:01):** it. Okay, so you kind of had this, this stack or this this customer set of people who wanted to integrate their tools. And, and that was kind of like this, this process of, okay, we can't necessarily support all these specific integrations. And is that a good kind of understanding of that? **Tony @ Moonpay (07:10):** That's right. Yeah, exactly. It's way to scale out what enterprises and prosumers wanted to build themselves within the interface that's most capable of doing it, which is a CLI or a terminal. **Gabe (07:37):** And now you're building what would be the connector to it would what would be a service provider and it's kind of this transition from Okay, instead of trying to solve everything and kind of build this system where people will integrate There's like a standard, know the CLI the MCP connectors into these orchestration agents were typically they're like Claude codex, etc and so with that like where do you see the First of all, like the orchestrators, seems like they're almost being chosen, right? It seems like it's going to be open AI and anthropic. Do you see other environments where people will potentially use orchestrators outside of like those two frontier companies? **Tony @ Moonpay (08:20):** Yeah, so I think I'll touch on the point ⁓ before, which is one of the big learnings that we had was really what ends up happening for a lot of these agentic products is a two-sided marketplace, where the agent is the supply side and the user is the demand side. And ultimately what you're trying to do is combine them so there's money moving throughout the marketplace. And with a lot of marketplaces, People usually say figure out the demand. I take the approach of like figuring out the supply to begin with. And the supply that we had to figure out was like agent, was agent liquidity. It's like, how do you find, and I've said this for a long time, is like, how do you find valuable enough agents, in this case now valuable enough skills that allow or bring in individuals to use those tools, use those agents, use those skills. And I think that's the problem that we're still, trying to face now and have done, I think, pretty well at MoonPay. In terms of what other orchestrators, I think it's gonna be the big three. It's gonna be OpenAI, it's gonna be Claude, it's gonna be Perplexity. Each one of them, I think, has their own niche. Perplexity, think, is really, really specialized in finance. So I can imagine a world where, like, Perplexity becomes the hub for... individualized finance agents. ⁓ Matter of fact, like I connected using a perplexity computer, I connected ⁓ MoonPay agents, the MoonPay CLI to some of the finance research that they've done. And I've been able to get like really in-depth prediction market ⁓ analysis or insight. think like Claude is very generalized and allows you to build a lot of these different ⁓ applications yourself. And then OpenAI I think is... ⁓ is in between, it's really like the best at everything, if you will. So I think those are gonna be the big three. **Gabe (10:22):** Okay, interesting. Yeah, so you're seeing perplexity as like a specialized orchestrator essentially. Okay, verticalized, interesting. **Tony @ Moonpay (10:28):** Yeah, exactly. **Gabe (10:31):** Okay. And then for the piece about the kind of like the connectors and the hubs ⁓ for the orchestrator themselves, what are the use cases? And like we're trying to aim for like, you know, real use cases where customers are doing some type of process that is like legitimate, right? And not like, you know, watch trading or these points, you know, trying to accumulate points by using the CLR or something like that. But I'm curious on your end. Yeah. Like what are these use cases that you're seeing even if they're low volume, but almost like the high signal value driven use cases. **Tony @ Moonpay (11:09):** Yeah, I think ⁓ number one is prediction market research to trade execution. These LLMs have access to like large troves of data. And I know some of the stuff you've done with Shoal, ⁓ like kind of proves that right? Where like it has this like, as this proprietary data has all these curated information that LLMs can use to make decisions with. think that's number one. Number two is combining a lot of this different data, whether it's like a Masari or BlockWorks or block mates or whatever it may be and use that for token trading. So there's a strategy that we have that's called, it's like VC Intel to funding where you're essentially able, an LLM is essentially pulling information from a sorry, seeing what categories of crypto VCs are investing in and is able to curate a basket of tokens for you. then ⁓ point you in the right direction to allocate capital. And then I think number three is like, commerce. ⁓ MoonPay has or acquired Solana Pay, which is now MoonPay commerce. So we have access to around 6,000 real world merchants within Shopify. And we're seeing people start to spend their money via the MoonPay on ramp being the buy widget or the virtual accounts. And they're doing that directly into Shopify. So whether that's like a Skylark, which is Justin Bieber's brand, whether it's like a Pudgy Penguins, or whether it's a smaller ⁓ boutique. sort of Shopify store. Those are the three interesting use cases and most use cases that we're seeing. **Gabe (12:43):** Okay, interesting. Yeah, and that's a really good segue because I saw the UCP that was launched by Shopify as well and it kind of made me think of, we're gonna have like these headless merchants essentially where it's almost like a ghost kitchen and... **Tony @ Moonpay (12:50):** Yeah. For sure. Ayayaya **Gabe (13:00):** you know, especially coming from Uber, we're both at Uber for some time. The ghost kitchen thing was like the juggernaut that everyone was like, okay, it's thing gonna take over. And I think to some extent it did, but not as big as we thought. But you know, if you're looking for some toothpaste or something and you kind of delegate it to your agent, your agent can kind of traverse for good pricing and quality. ⁓ **Tony @ Moonpay (13:02):** Yeah. Yeah. **Gabe (13:22):** That seems like an open landscape that a lot of people aren't really thinking about this headless merchant is a headless stores. I'm curious for you, like, are you guys thinking about this and how are you guys thinking about it? I guess the answer is yes, but more so how like what are the what are the second thoughts, the second and third thoughts and how deep are you? Have you been going on this? **Tony @ Moonpay (13:28):** Yeah, for sure. Yeah, yeah, I think there's maybe like two or three thoughts around that. Number one is, yeah, I think like number one is agents deserve virtual cards ⁓ to have access to, or to be able to be backwards compatible with ⁓ how the internet is set up. So I think that's number one. ⁓ I think like number two is, Agents are the new websites. So instead of having to create your whole new website, which is fairly easy using Shopify, there's going to be those like large aggregators of stores or merchants. And all you have to do is work with an agent and make sure that your catalog is agent ready. So whenever someone goes in and types in like, hey, I'm looking for coffee mugs, your catalog comes up one, two, three, four, or five. I think that's the second piece. ⁓ I think the third piece is we're having really early conversations with some merchants. I can't really name who it is, but it's more ⁓ dining focused ⁓ where a lot of people are starting to think about how do I make, me as a merchant, how do I make sure that I'm agent ready? And it's going to be a collaborative effort where I think like, hey, ⁓ maybe I do need something that's backwards compatible with how the internet and the infrastructure works. Hey, like I do need to make sure that I'm agent ready and then ⁓ see it's like, hey, I actually have to have a good brainstorming partner to figure out how to do that. And I think with those three pieces together, we're gonna start seeing a lot more headless merchants and. think ultimately what Shopify released ⁓ is more on the merchant side, but that's a step in the right direction of saying like, hey, we wanna help make merchants agent ready. And we want to give merchants familiarity with agents and how they can use them day to day to run their business. **Gabe (15:41):** Yeah. Yeah, interesting. The thing that comes up that I think through, like if I'm on Amazon, right, and I'm trying to buy a mug, let's use a mug example, I feel like a lot of the inputs into the mug for me are like price, you know, maybe I get tricked on some type of markup type of marketing strategy, right? Some discount strategy maybe influences my decision. The color of the mug probably like what the packaging looks like probably influences my decision. In the world of ⁓ agents, a lot of these tricks don't work anymore in terms of distribution, in terms of marketing. So how are you seeing the discoverability ⁓ for these agents and for these marketplaces? Do you have any ideas what the heuristics are that might be appealing to agents? Or is that just coming from the memory of the agent knowing the person? **Tony @ Moonpay (16:32):** Totally. That's a good question. I don't think I've spent a lot of time thinking about it, but there's probably two pieces to it that come to mind. One of them I think is very far-fetched and is kind of playing into the future. The first one I think is more in the real world, which is agent-engine optimization. The same thing is SEO, which is how do you just make your products more discoverable by agents? **Gabe (17:12):** Yeah. **Tony @ Moonpay (17:22):** And I think that's very real, right? It's like, hey, the first person to crack, the first products rather, to crack SEO for their product and make it very easily discoverable by agents are probably gonna win the first wave of transactions. And I think that's very easy. I think the second piece is like, this is... ⁓ not imaginary, but I don't know if we're there yet. It's like, hey, these agents are gonna have the full picture of you. because I have like a budget and spending calculator, ⁓ spin up on perplexity computer, it has access to all of my checking and my checking and credit cards. ⁓ It'll understand how much I spend money, where I spend my money. And I connected my Amazon to it. So now it knows what I bought in the past. It's able to say like, hey, Tony, I know that you love your Bustelo ⁓ espressos in the morning. I mean, you drink about three to five of those throughout the day. Here are like three to five very specific coffee cups or coffee mugs or espresso cups that you're going to enjoy. Let me find you one that is like ergonomically designed and has cool patterns because everything you buy is like super funky. That I feel like would be the perfect world. Are we there? I don't know. How far we are, I really don't know. But my thesis is like, this is going to happen very quickly. So it doesn't matter as long as we build the blocks to do it. And the blocks to do it are like connectors, smarter models, and user willingness. **Gabe (19:09):** Yeah, yeah, yeah, I think that's a good characterization. I have no idea either. I think to speculate, there probably has to be some type of distribution rail. Maybe there's a single service that does some curation or something like that, and then you can be discovered through the curation, like a marketplace in itself. So yeah, that's the... **Tony @ Moonpay (19:15):** Yeah, yeah, yeah, yeah. Yeah, for sure. you could imagine like human curation for agent discoverability could be like very real. But once again, like anyone who says they have the answer, I think is being very optimistic. So we don't know. It's OK to not know. But once again, you have to build the building blocks. **Gabe (19:54):** Yeah, and it seems like it's kind of something that you guys are doing, With the CLI and or with the SDK for the MoonPay CLI, you guys have some other tools in there and kind of like tricks and skills to try to hit the full package. Is that kind of in the same direction of this is like, okay, one stop shop and you can kind of hit everything. **Tony @ Moonpay (20:11):** Yeah. Yeah, exactly. It's really under that principle of like human curation for agent discoverability. What famously we try to say internally is like, we want to be the opposite of MoteBook where it's like this gigantic aggregator of a ton of skills and 80 % of them are malware. What we want to say is like, hey, we have 50, 100 skills. Each one of them has been vetted by us and like we say these are okay. So we're curating this marketplace. We're curating this marketplace with all of these different skills that are verified. You as a user, you as an agent can say, hey, I want to build this like Neo bank that has virtual accounts, deep research, virtual cards, yield, like perks and prediction markets. The agent is able to say like, hey, found the MoonPay agents marketplace. Here are like the 10 to 15 different skills that you need building all of this. That at the end of the day is I think, going back to our earlier part of conversation, was a difficult thing for us at Grafane, which was like, hey, I have to build all these different agents and figure out how to get them to orchestrate together versus now within the CLI. As long as you as a human curate the right skills, agents are able to discover them and then execute and build whatever the intent is for a user. **Gabe (21:42):** And how do you think about routing between the request and, because as I think about this, it's like the, you have the kitchen, which is like all these MCP might be like the stove and then you have another MCP, which is like the oven and you have this built out kitchen with all the connectors, right? But. **Tony @ Moonpay (22:01):** Yeah. **Gabe (22:02):** you know, to move across these different tools, maybe there's more optimal routes, right? Almost like, you know, order flow type situation. How are you looking at that? And ⁓ yeah, I'm curious your thoughts on that piece. **Tony @ Moonpay (22:09):** Yeah. Yeah, for sure. ⁓ So I don't want this answer to come out like a cop out, but I do think it's like a really easy, it's a really easy mental model for a lot of these LLM products is the LLMs are getting really smart consistently. And how we think about routing, it isn't necessarily adding these different pipes, ⁓ which increase complexity and take time and so on and so forth. It's actually relying on these foundational LLM models. and allowing the LLMs to figure this out themselves. ⁓ And the tricky part there is like sometimes an L and this has been a constant theme throughout. It's like sometimes LLM will confuse swap with sale. So instead of swapping from token to token, it'll sell the token completely. Those are small errors though. And I think like the overall answer is like we allow the LLM to do this, right? And there is one large There is a Michelin level chef, which is the LLM. And there's a ton of sous chefs, which are the like tools that help the LLM, help this Michelin level chef figure it out. And I think the goal there is like, or the objective is like, hey, let's have this like the best possible LLM possible, which is the Michelin star chef. And then like in the backend, let's make sure. All the tools are set up correctly. Let's make sure the skill MD is like very, very clear. And what you have to do is very, very clear. So the sous chefs, these like tools and skills can do their job. So that's how I think about it personally. And I think that philosophy as well is kind of carried over from what we were building before. now. **Gabe (24:09):** And yeah, like there as as this stuff is coming out, it's so hard to keep up with regard to like the innovation and the direction. And it's almost like a lot of people can or a few people rather in the space kind of see where things are unfolding. And I think that's where the value is, where, you know, lot of the builders are building for this centralized orchestrator that and and they become the connectors, right? They become the the transaction interface that that has other recommendations. **Tony @ Moonpay (24:27):** Yeah. **Gabe (24:38):** similar to like what you're building or you know, it might be like a news data, right? Maybe something that that Shoal can provide but in the bigger picture, that's kind of difficult to put together in the first place, right? But once we kind of have that foundation, what do you think is next? And with this kind of orchestrator thesis and connectors thesis, what is kind of the next phase that rolls out? I mean, we've seen like the main which agents with Anthropic, agents running their own agents? ⁓ Yeah, curious, your thoughts there. **Tony @ Moonpay (25:11):** Yeah. Yeah, well, to keep it simple, think we get back to this like chat, own chat interface. That's what I think the ultimate state of it is. I don't think it's gonna be very generalized where I think it could be generalized, it could be verticalized. I think if you look at the history of software, you've gone from like extremely horizontal in like the 2000s to extremely vertical in the 2010s. And maybe AI replicates that where it's like, hey, we start out with like very generalized models. These ⁓ generalized models create like general applications. And then I think as just like software and mobile did, it finds its footing and finds the infrastructure. Then you're able to create like verticalized experiences. ⁓ And so I think the ultimate version of this is, are like verticalized chat first experiences. ⁓ So much similar like how I said earlier that perplexity is especially financed and ⁓ perplexity is extremely focused on finance. I think that's what we'll see with these like chat experiences, which is there's going to be a agent experience that's solely focused on crypto trading. What that then means is like crypto trading is a large bucket, includes perps, includes meme coins, includes Prediction markets includes yield, includes X, Y, and Z. ⁓ So I think that's what the final stage of it actually looks like. ⁓ How we get there, think like number one is like one click deploy agents. ⁓ Open call is a pain in the ass to set up. And that's just the reality of it. And I don't think people are gonna do it. Poke.com has done an awesome job of like phone number, agent, and iMessage. **Gabe (26:48):** Yeah. You **Tony @ Moonpay (27:11):** interact with agent. Number two is strategies or recipes, which is like, Hey, here, like, here are these like human curated strategies and skills. Here's how they've been turned into strategies. And now you can power your one click deploy agent that way. Then number three, think is like real world usage where sure. It's going to be super valuable that my agent can transact on Amazon. It's super valuable that I can buy these baskets of investments, but what's really more valuable is like it says, Hey, You love pizza or hey, you love pizza. Like I'm gonna order you a coffee beans like every single, every single week or whenever you get your paycheck. It's more valuable than my agents are usable in the real world. And so cut it up. Those I think are like the three steps to get there. And where we go is actually these like verticalized chat first experiences. **Gabe (28:05):** Got it. Okay, so you think you're seeing this convergence in the longer term back to specialized ⁓ operational orchestration workflows. **Tony @ Moonpay (28:12):** Yeah. Yeah, exactly. And like you can still see it in SaaS today, right? Like SaaS is inherently ⁓ a category where Salesforce itself does a lot of different things, but the sales team is cut up into different verticals that they can specialize in. And each one of those has a different sales playbook because it's inherently solving a different problem for a different customer persona. but they package it all as like one piece of ⁓ laws you to cross up, so et cetera, we've software has gone from horizontal to vertical. Now, if we say LLMs are still like very similar software, great back to horizontal, right? These generalized language models just kind of do everything. And I think we're still seeing some, we're to see the convergence back into vertical. And I think we're already starting to see that right where it's like, ⁓ A buddy of mine, Jackson, is working on surf.ai and surf is building like financial, ⁓ crypto first LLM models and a crypto first UI. So it's just a verticalized LLM built for crypto. And that's where I think this cycle kind of continues to go. Everything is sick. **Gabe (29:37):** On the enterprise side, is kind of hard to get signal because a lot of these companies, especially like Anthropic, right? All this stuff is, even though they're selling to the businesses like Codex, Cloud Code, on both OpenAI and Anthropic, they're like individual contributor tools. **Tony @ Moonpay (29:44):** Yes, sir. Yeah. Yeah. **Gabe (29:56):** Cowork is kind of like that evolution of that, right? Which we eventually see, you know, teams can work, cowork teams, right? But on the enterprise side, what are the requests, not to get the specific companies, right? But what's kind of like the trend if you can share of what people are asking for and like, what is the nature and the shape of what they're asking for? **Tony @ Moonpay (30:19):** Yeah. So I think ⁓ it hasn't really changed, right? It's like, hey, I want to create an agentic first experience for my product. I think that's like the flat out ask, right? How it happens, I think is it can vary. ⁓ But that's the overall, ⁓ that's the overall ask. Then it actually then becomes a question of like, what value does an agentic first product bring? for those enterprises and figuring out as a business how you match your product experience or your product offering to that demand. So I think number one is like expansion of TAM. That's where stuff like X4.02 becomes really interesting where it's like, hey, maybe my core business is built on $250 a month, $2,000 a month subscription. And so I've been missing. 35, 40 % of the market, which has allowed competitors to like go down the stack. Now with X4.02, I can widen my TAM and bring in those users. I think that's number one. ⁓ Number two is like diversification of business model where Claude and Perplexity and Chaggibiti do a good job of this. It's a nice blend where they have the classic SaaS model. It's like I can pay $20 a month to get access. But then I actually have this pay as you go model. And those two, don't think, go away. But then it becomes a question of what's the value metric? ⁓ The value metric I think ultimately becomes, which going back to diversification of business model is like. You charge based on completion of jobs, which is, hey, I'm doing this like data API or data product. Every time someone successively executes a trade using my data, that's the only time that they charge or that we charge for using that API. So that's, think, the second piece of like diversification of the business model. ⁓ And then I think three is like, does it enhance the consumer experience? So. Back to like headless merchants, think agents are the new websites, agents are the new interfaces, ⁓ and figuring out how to create an agent that is proactive and guides the user through your product is ultimately what businesses want, right? So I think what these enterprise requests is like, hey, I just want to create an agent ready product experience if you work backwards from it. What really means is like, are the goals? Is it like expansion of TAM? Is it diversification of business model? Or does it like amplify your product experience? **Gabe (33:18):** Yeah, wow. The diversification of business model, are you already seeing teams basically charge based on results? right now we kind of went from the subscription to the token to now, I mean, I feel like we just are. Cleaning up around in the token like we're just getting kind of familiar with token base usage or metered usage, right? Especially with extra to an MPP, but now it's like, okay, you know did the service provide value is essentially kind of this next Yeah, yeah, are you seeing that people are already deploying these types of approaches? **Tony @ Moonpay (33:42):** Yeah, yeah, yeah. Yeah, yeah, yeah. Not specifically in crypto. I know that this is like very much a thought experiment in the AI SaaS world, but I don't doubt that it's going to come out very soon. And it's going to be made, it should be adopted for specific products for companies. **Gabe (34:09):** Okay. Yeah, yeah, because that's almost like, know, prove you got to prove your value. **Tony @ Moonpay (34:21):** Yeah, exactly. then, you know, like, it comes into like a gigantic, it creates a gigantic question and a gigantic vacuum of like, if I can't inherently charge a blanket fee or blanket price, I'm going to be missing out on revenue. But if you're charging a blanket fee or blanket price, you're more susceptible to churning customers. which means you have to spend more on trying to keep those customers and you lose a lot of money when you lose a customer and you spend a lot of money trying to keep that customer. So the inverse is I actually charge for when I prove my value, which then means I'll be able to retain customers a lot more, reduce my spend and be able to iterate a lot quicker with customers who find value from what I'm doing. And it makes selling a lot easier, right? Which is like, Hey, here's like the amount of jobs that we've got done. And these are the gigantic value props for like these software companies, which is like, well, we have like a 99 % uptime. We have a 99 % success rate. like, just charge on that then, right? Cause now you're proving your value, that your infrastructure does the job for the person you're selling it to. **Gabe (35:33):** Yeah. And for you guys back to the enterprise, please share what you can, ⁓ the customer segmentation, are you seeing a lot of non-Web3 customers that are looking for these types of payments to kind of future proof? **Tony @ Moonpay (35:59):** ⁓ Yes, I like I so there's a couple parts to MoonPay, MoonPay itself and MoonPay has a ⁓ great ⁓ ventures team that is focused ⁓ a big strategy on acquisitions ⁓ and Iron which is a ⁓ virtual accounts and stable coin issuance company was acquired by MoonPay about a year and a half ago and We've gone live with Deal, which is one of the largest payroll providers in the world. And what we're seeing is like, or what we're hearing is, hey, we understand stable coins are a net new way to give individuals access to the US dollar. And individuals who live in places outside of the US really want to have their earnings come through that, through currency, through USDC, USDT. And what we see is like as enterprises become keen on stable coins, they choose to go to iron to figure out the strategy. And when they come to iron, it allows the opportunity to expand MoonPays offerings into those enterprises. **Gabe (37:22):** interesting okay that makes that makes a lot of sense so really there's like a it's almost like an education like once you kind of do the acquisition then there's like education the natural flow is to these on chain projects to products yeah that's cool man **Tony @ Moonpay (37:37):** I think so. I like if you look at if you look at ramp right like ramp is ramp is stepping into stable coins right and I think why did they start in stable coins maybe it's because what their product actually is but there's a ton of different things they could have done right they could have they could have done a ton of different things they could have done yield ⁓ they could have done virtual cards which they did but they decided to start with stable coins and so I think stable coins are an interesting value prop because companies want to hold them on their balance sheet. But also like they have gotten a lot of regulation and there's a lot of clarity. Thanks to the clarity act around what you can do with them. So it's a very welcoming asset for ⁓ companies to explore. **Gabe (38:28):** Yeah, Yeah, just as we're wrapping up here, just kind of a couple last thoughts. When it comes to like tokenization, right? There's like a huge, I think there's parallel kind of narratives right now that are huge and that have revenues backing them. You know, X4.02 and these, know, Stripe coming in with NPP is a lot of traction and potential customers coming in. The parallel tracks are like perps and tokenization, right? Tokenized stock. **Tony @ Moonpay (38:37):** Yeah. for sure. For sure. Yeah. **Gabe (38:56):** For the tokenized stocks in RWA cohorts, and stable coins too, right? There's huge regulatory ⁓ arbitrage and bottlenecks. Like some companies will do 10 times better because they have the licensing and they focus and spend the time on the licensing. **Tony @ Moonpay (39:13):** For sure. **Gabe (39:15):** On the stuff that you're doing specifically, and there's probably some connections there on the stablecoin side, but are you seeing a lot of resistance from enterprise companies due to licensing and comfortability? Or is it more green grass and you're moving? **Tony @ Moonpay (39:36):** ⁓ So MoonPay is one of the most licensed companies in crypto. ⁓ We have our New York Bit license, legitimately only a small amount of people like think Coinbase and Robinhood may have, ⁓ where we're regulated to the core where ⁓ I think actually to turn your question around, ⁓ enterprises and users choose us because we are so heavily licensed and heavily regulated and we stay compliant. ⁓ And so I think ultimately when you look at stuff like an Exodus, ⁓ which we launched our stable coin, the reason they chose us is because we are extremely licensed. And then that's one of the big value props for MoonPay as we were thinking about joining is The big ethos here is how do you become backwards compatible with the existing financial system? Because what MoonPay wants to do is build the operating system for modern money movement. And I think you can do that in a very cowboy style. But the way that you scale out and get big wins ⁓ is by being regulated, having your licenses, and being extremely compliant. **Gabe (41:03):** Cool man, yeah, this has been super helpful. All things agents and CLI and MCP, it's a lot to wrap your mind around. I think it's difficult too, especially online, to kind of see what's real, where are the trends actually settling, what are the institutions doing. So yeah, thanks for coming on and appreciate you joining. **Tony @ Moonpay (41:25):** Yeah, of course. Appreciate you for having me, Gabe. **Gabe (41:27):** Yeah, likewise. All right. Take care. --- # Browserbase: Fully Autonomous Is the Wrong Goal, 99% Accurate AI Agents Can Fail Catastrophically > Shoal Signal episode. Guest: Derek Meegan (Browserbase). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-06-10 - Video: https://www.youtube.com/watch?v=jJeBrHmMCjM - Canonical: https://shoal.xyz/research/episodes/browserbase-autonomous-agents/ - Keywords: AI agents, browser agents, infrastructure, interviews ## Transcript **Gabe Tramble (00:02):** So Derek, can you tell us about what a browser agent is and how it's different from like a playwright script and then also queue into browser base itself? **Derek Meegan (00:11):** For sure. ⁓ So first of all, you want to start with what is an agent, right? And so we all know what a large language model is, or ⁓ maybe hopefully everyone that's listening to this knows what a large language model is. But an agent is essentially a large language model on a loop, right? That is sort of continuously operating to achieve some sort of objective. And there's sort of varying degrees of autonomy for an agent. ⁓ You may have an agent that checks back with you on every single turn. You may have an agent that's set up for long horizon tasks, or you may have an agent that is calling tools that individually require human in the loop for approval. And so a browser agent is just an agent that operates on a browser. Just like a human does, it opens up ⁓ a Chrome browser and clicks buttons, fills in forms, ⁓ completes tasks on the web, ⁓ primarily on behalf of people. And so the way browser-based slots into this whole browser agent story of agents completing work or taking actions on behalf of people over the web is we provide the infrastructure that your agent needs to operate on in order to interact with the web. So whether that's search, whether that's fetching content from a page, or whether that's launching a real browser that your agent can use to interact with websites. **Gabe Tramble (01:32):** And this is a little bit different from other companies like Exa or like Firecrawl where Exa allows you to basically like search and retrieve information and Firecrawl will like take the entire webpage. They're like different approaches and you guys specifically basically are crawling on the browser. Is that good like articulation of exactly what you guys are doing? **Derek Meegan (01:34):** Ahem. ⁓ Approximately, I would say we're a superset of Exa, Firecrawl, and then ⁓ really the foundational player in the direct browser infrastructure space. And we're not doing crawling on behalf of our customers, but instead ⁓ exposing a full platform of tools for them to ⁓ operate agentically on the web. And to answer one of your original questions as well around how browser agents differ from Playwright, ⁓ Historically, ⁓ Playwright is actually a testing framework. Same thing with Puppeteer and many of these other foundational browser automation libraries. They simply have been repurposed before AI for ⁓ maybe some nefarious reasons. ⁓ Now in the age of AI as the direct hands for agents to click and type and operate on the web. Browser agents are very attractive ⁓ because of number one, ⁓ perception that there's a low ⁓ necessity for configurability, right? Like I can basically just shout some directive at an agent and then it'll go off on the web and do that thing for me. And that feels great, right? ⁓ In a second perspective, ⁓ LLMs also kind of ⁓ sort of ambiguous decision-making ⁓ into code, right? And that's really difficult to model ⁓ in strict like if or else statements, right? ⁓ And so when companies or people have deployed Playwrights scripts in the past to automate ⁓ actions on the web, they've been highly susceptible to breaking through very simple website changes. ⁓ And so with that nature of LLMs being able to make ambiguous decisions, you unlock the capability to heal actions at the step or even the trajectory level in more complex cases. **Gabe Tramble (03:46):** And traditionally people were kind of like mapping the website and then essentially if like a button move like an inch over then the strip would fail. **Derek Meegan (03:55):** Right. Yeah, and I think that's conflating the nature of a selector. And so what is a selector? It's basically some ID or some signifier, basically some string that maps to one or more elements on the page. And in traditional playwright or puppeteer scripts or other browser automation libraries, we're treating those selectors as code. And the sound actually code, it's really data. ⁓ And that data can be used in different ways across different scripts, right? You may click one button in another script and click that same button in a different one. ⁓ And what generative AI has allowed us to do in the browser agent space is kind of bubble up some layers of abstraction. And instead of operating on these selectors, which are really sort of implementation detail to completing the goal, right? We can instead, you know, in the most extreme case, like in fully agentic browser automation libraries. know, Stagehand agent or a browser uses another example of this, or there are several other ⁓ browser agent libraries, you give that top level task and that agent loop and that agent library kind of takes care of the rest. Whereas, ⁓ you know, obviously that juxtaposes to Playwright, but also ⁓ browser-based maintains a browser automation library called Stagehand. which allows you to find individual actions in natural language, right? So you may still be attached to like one particular trajectory, right? Like this flow, you you need to fill in the first name box, you need to fill in the second name box, you fill in the address and then you click submit. But you don't want to attach to the particular selectors that underlie these elements on the page. So Stagehand allows you to say like, hey, for this one action, like fill in this box. Then for this next action, fill in this box. And those two... sort of directions to the model are independent of each other. **Gabe Tramble (05:53):** Got it. Okay, so we have the agent, which we described, and then we have this ability to interact with the browser. And just so we have this full picture before we kind of get into the weeds, why would someone want to essentially have their agent look onto the browser? **Derek Meegan (06:11):** I think there's like, you know, two ⁓ or maybe I'll like differentiate between three like types of browser trajectories in the context of this, right? ⁓ Number one, you have this notion of like just in time automation, right? Where, ⁓ you know, you're doing regular and there are like many consumer AI browsers that are seeking to converge on this space, right? ⁓ Think about like perplexity comet or Dia. ⁓ They're basically, these agents are sitting alongside the human operator. as a human completes ⁓ many varying types of tasks. And the agent, or the human may say like, hey agent, know, go do this thing while I do this other thing. And there's no notion of like repeatability or scalability in those particular automations. ⁓ Then you have sort of like a third type of trajectory, which is ⁓ like clicking and typing is for some like higher purpose, right? So you may have like a UI testing agent. or you may have a competitive analysis agent or a deep research agent. And they are clicking and typing, but not for the purpose of clicking and typing, but rather to incrementally gather information or ⁓ quantitatively assess the nature of, for UI testing, like, okay, let me click on this button and then let me measure the time it took to load the page and be redirected to a new page. And then lastly, these are the highest volume use cases. are sort of transactional browser trajectories. ⁓ And we see this a lot actually more with enterprise customers where traditionally they've used these hard-coded scripts and they have to spend a lot of human capital to maintain them. But instead, you can shift those human capital costs towards model costs, right? And given sufficiently constrained problem space, ⁓ sufficiently ⁓ instrumented observability, ⁓ you can create a browser agent that ⁓ is reliable, is cheap, and is resilient to sort of step or trajectory level changes on that particular website. And so, you know, the goal there is to sort of have the best of both worlds, retain some elements of determinism, but get those assurances of variability without having to slot humans in between each individual. **Gabe Tramble (08:25):** So where do these workflows traditionally break down? And this will kind of lead us into the problem statement now that we have like a clean slate to work with. Where traditionally have people had issues and basically what have they been not able to do on top of that because of it? **Derek Meegan (08:45):** Yeah, I mean, I would say traditionally browser automation is hard, right? Like, it's just plain hard. There's a lot, it's very dynamic. I wouldn't necessarily say like Playwright, Puppeteer, or other browser automation libraries, like their interfaces are particularly intuitive for people. And then there's a lot of nuances with Chromium, with anti-bots, with the identity, you know, quote unquote, of the particular automation or agent that's taking actions. ⁓ So, you know, there's both this like functional difficulty in standing up these automations. There's sort of these unknown unknowns that make it difficult to make predictable, reliable solutions for automating browsers. And then, yeah, there's just conceptual hurdles to overcome in order to sort of ⁓ bring that like know-how and art into an organization ⁓ to where you can build these ⁓ automations at scale. And then, you know, I would say now as we're introducing browser agents, Of course you solve one problem, but you create new ones. Cost is definitely one of those. You can get very good computer use results from some frontier models, but it's simply not economically feasible to deploy Opus across a million trajectories like a month. So okay, this is a very high value flow and high volume, or maybe it has some value, the flow. but what is that value relative to that cost, both from a COGS perspective, then from an implementation and maintenance perspective, and that's where things start getting a little complicated. **Gabe Tramble (10:23):** Okay, so now that you do have these solutions to essentially browse or depending on your workflow interact with a browser using an agent, you're saying now that starts to multiply on different types of problems that occur there, where do you see kind of these big ⁓ or like the most ambitious problem space now that you guys are doing the work as of now? **Derek Meegan (10:49):** Yeah. So you think like, okay. You ⁓ you basically have these LLMs that can go and take variable actions of the web. Like you're probably building like these crazy, like digital online workers that are doing all of these dynamic things. And I think it's, it's, I can see why people would think that, right? I can see why people would think that, but in reality, ⁓ you know, you're, you're, you're expanding the realm. of what traditional browser automation was incapable of doing. ⁓ But you're building on the type of tasks that traditional automation ⁓ would automate. And so there's a lot of, let's say, receipt retrieval is a big use case. And this supports different finance workflows. We have a customer, Ramp. Ramp is one of our great customers. And we've partnered with them on helping ⁓ create a Gentic **Gabe Tramble (11:42):** Nice. **Derek Meegan (11:46):** receipt retrieval that's resilient to sort of traditional ⁓ automation detection, traditional like ⁓ changes to page structures, right? So these are all problems that have already existed, but these new solutions are, or these new tools are offering new classes of solutions that weren't available before, right? And so, ⁓ you know, we're really focusing on these like high volume transactional workflows. because they're clearly measurable and it's easy to attach a value to a trajectory. ⁓ know, of course, we also service these very, like these UI testing workflows or these deep research workflows. Deep research in particular is definitely interesting, especially now that we have this combination of search, ⁓ fetch, which is sort of like a curl equivalent. But of course we add like extract or markdown transformation on top of it. ⁓ And then the browser, these three together is actually **Gabe Tramble (12:29):** Thanks. **Derek Meegan (12:43):** plus an LLM, there's your recipe for a deep research agent. ⁓ And you can create a verticalized deep research agent for any industry or your particular company. And we found for us that it's super valuable, especially for our go-to-market, to automatically have a deep research agent kicked off when a lead is created in our CRM. And we can enrich information about that lead. we can compare that lead to other customers that we have ⁓ in our customer base and say, hey, what solutions might be relevant to them? And that informs our go-to-market org and our sales engineers when they go and speak to the customers. So I think there's an opportunity, of course, for information synthesis, information retrieval. ⁓ Of course, this just-in-time browsing use case ⁓ creates a lot of different dynamic use cases. **Gabe Tramble (13:28):** Okay. **Derek Meegan (13:32):** Although we focus on them less from an enterprise. Inherently, these are not scaled workflows that are repeatable and it's easy to tie some static value. If I know, if I'm Ramp, if we retrieve these receipts automatically for our customers, that represents some quantifiable value and then they can pin that quantifiable value against the cost of upkeep, the cogs. **Gabe Tramble (13:41):** Okay. **Derek Meegan (14:00):** et cetera, right? Or like the initial development costs of the project, et cetera. And yeah, and I think these transactional browser automations do present like a very interesting ⁓ unit economics problem, right? Because, you on one hand, each step that you take with the LLM, and this is not just with browser agents, this is with, you know, any agent, the, you know, if there's some underlying, you know, task for the entire trajectory, each time you take a step, **Gabe Tramble (14:03):** Thank you. Mm-hmm. **Derek Meegan (14:29):** there's this marginal increase in likelihood of failure, right? So you're accumulating risk, right? Something may go wrong. The agent may go off the desired trajectory. There could be some infrastructure failure. The agent could hallucinate, right? There's basically an innumerable amount of ways in which the agent could go wrong, right? So you're constantly accumulating risk, but with these transactional flows, right? Like if I'm retrieving a receipt, there's no value to me if I get 50 % of the way. there to retrieving the receipt or 80 % of the way there, right? So value realization is terminal, but risk accumulation is continuous. And same thing with cost accumulation, right? So you're accumulating costs and you're accumulating risk, but you aren't realizing the value until you get right at the very end. And that's like a particularly brutal like combination. And it makes it really tough, right? Cause like I mentioned in the beginning, the perception is I like throw some directive and then that directive gets completed. **Gabe Tramble (14:59):** That **Derek Meegan (15:27):** ⁓ But of course there's context ⁓ sort of breakdown between what I say and what I'm thinking. ⁓ There's unknown unknowns about the website that the agent may be embarking on. And so when we see customers that come to us and they say, hey, we want to deploy these browser agents at scale, we need to sort of ground them in what real applied AI actually looks like. And this is not just like a magic box, right? As much as we would like it. as much as we would like it to be, right? This is really fundamentally an observability problem. You need to understand what the agent is doing, right? Once you've understood that, ⁓ what are the key success criteria for a particular trajectory? So, and ideally this is deterministic, and ideally this is deterministic and the agent can invoke this midway through the trajectory, right? So. Let's imagine the case of like a bill payment, right? So I give the agent, here's this website, here's like a credit card, right? Here's some, you know, billing information. Go on this website, fill out the form, pay the bill, right? Very easy. And this is very easy to demo. And I've personally demoed this before, right? Like click, click, type, type, boom, submit, boom, you know, where do you sign? Right? But the problem when you go and scale this is even if an individual browser action is **Gabe Tramble (16:26):** Okay. **Derek Meegan (16:53):** 99 % accurate, right? Like let's say I gave you a browser agent. I'm like, here's a browser agent. Every step that you ask it to do 99 % of the time, it'll get it right. If that trajectory is a hundred steps, then that agent has an over 60 % chance of failing just because that's just how the math works, right? When you go 99 to, you the power of a hundred. So, um, you really need to ground yourself. What is an agent, right? This is not a person. **Gabe Tramble (17:14):** Okay. **Derek Meegan (17:20):** This is not some magic thing that will solve all of my problems. ⁓ An agent is an LLM on a while loop and an LLM does next token prediction. What I'm implying by saying an LLM does next token prediction is that you can think of the output of an LLM as a probability distribution. Somewhere in that probability distribution is the outcome that we want on each turn. So how can as my agent, **Gabe Tramble (17:45):** Thank **Derek Meegan (17:49):** goes through the trajectory, can I limit its output distribution to the portion of the possible distribution that I want? And context engineering is like one way. I think another way is that, you know, if you know that on each step that you accumulate some marginal risk, how can you eliminate steps? And this is where we've seen some interesting solutions ⁓ with sort of, have you heard of Karpathy's auto research? **Gabe Tramble (18:16):** Yeah, yeah. **Derek Meegan (18:18):** Yeah. And so, you know, the basic premise is you give the agent like some quantifiable goal, right? And then you set it off on a loop to do everything under the sun, like diverge across all types of strategies until it can achieve like that. Or the same thing with like codecs, like slash goal. Very similar. ⁓ we've been experimenting internally and we've also like shared some skills like publicly for auto browse. where we release an agent with this clear directive to run iteratively on a website and find that critical path through the website to complete that automation. The less steps you have, the less costs and risks that you accumulate, the faster you can get to that terminal value realization. So it's like a super interesting set of forces that interact with each other. And there's a lot of education that we need to do like with our customers, not only... You know, what does this observability look like? You know, how do you define the correct success criteria? But also, hey, how do we work with them to really understand the domain of their problem space? The possible failure modes that their agent may encounter and like planning for as many as possible for them. And then curating an environment for their agents in which when you think about the possibility, possible output distribution of any one action, it's as much as possible. **Gabe Tramble (19:31):** Mm-hmm. **Derek Meegan (19:41):** constrained to actions that we want and not the ones that we don't. **Gabe Tramble (19:46):** Got it. Wow. Yeah. Thanks for, for diving into the nuance there. I want to put a pin on the, uh, the ramp and the ramp use case and come back to that in a second, but to follow up on this statistical problem, right? Because, know, when someone talks about agents, they are typically thinking like, okay, I'm going to set this up and it's going to do everything and come back and I'm going to take a shower and I'm going to, it's going to be ready. Right. And, what you're saying is there's actually a statistical distribution problem they **Derek Meegan (19:50):** You Yeah. **Gabe Tramble (20:16):** into the success of agents, which is kind of like what people do in trading. It's almost very similar to trading and ⁓ like probability of taking a certain amount of trades. So my question is, if ⁓ each ⁓ run for your agent to go retrieve a receipt cost a dollar and a dollar of compute or like resources, right? Because you can't just price on the completion necessary. **Derek Meegan (20:22):** Mm-hmm. **Gabe Tramble (20:46):** but the resources do cost money. How do you actually ⁓ phrase this to the customer? is it actually based on completion, or do you say, it's gonna probably take this many runs, and it's probably gonna cost this amount in the aggregate to successfully do this task? Are you guys going that granularly into the customer, or ⁓ maybe you can just explain, yeah, how are you looking at that problem? **Derek Meegan (21:13):** Yeah, I mean, I think by the time, you know, customers have arrived at, we need to implement a browser agent to do this. They've determined that it's a pretty high value flow, right? And where, you know, what are the unique affordances that a browser agent gives you is the ability to navigate ambiguity, right? ⁓ And so we are approached with use cases that have ambiguity inherently built in. And our goal is to sort of put a box around that ambiguity and make it very easy for the agent to reason about that ambiguity and then implement as much determinism as possible around it. So a very rudimentary example, and this kind of goes in line with like, you know, the best step in a browser trajectory is no step, right? Is in your prompt, don't even give a website for your agent to navigate to. Like, okay, if I have a browser agent, why don't I just... navigate to the website first and then tell the agent go and do this thing. Right. And this is something like, this is like the easiest mistake to mess up. Right. Cause you're just like, I'll set up this, set up this website, you know, or this agent, all I need to do, you know, drop the website and the prompt go and do this thing, blah, blah, blah, blah. And then send it off. And then it's taking this action for no reason. Right. And so you're just like thinking about those numbers and thinking about, you know, we, you especially have to think about these, like the the statistical behavior of these trajectories when you're thinking about, okay, you know, I'm working with an enterprise customer and their scale is in the magnitude of thousands of trajectories, tens of thousands of trajectories. And things start to normalize. The weird things start to come out, right? And this is a little bit different of a problem than, you know, our friends at Anthropic who are adding computer use to cloud coat work. They just need to, you know, maximize the performance on their evals. Maybe there's a key number of sites that they know their customers go to and they can sort of formulate, ⁓ you know, maybe special skills or tooling to, you know, compliment ⁓ their cowork agent, like operating on those sites. ⁓ But yeah, so when we work with our customers, like, you know, by the time they get to us, they understand that there's a level of ambiguity. ⁓ Today, they now understand that tokens aren't necessarily free, right? **Gabe Tramble (23:21):** and **Derek Meegan (23:33):** And the first order of business is, Hey, like, is this capability even there? Right? Like, can we, you know, see some level of reliability, right? In that equation, right? What is the cost associated with a one trajectory? And then how many trajectories are necessary to complete a unit of work? Right? And so there's a difference between like the success per trajectory and then the success per unit of work with some capped number of retries. **Gabe Tramble (23:48):** Mm-hmm. Mm-hmm. **Derek Meegan (24:02):** Right. so the exam, for example, you know, you could have, um, 50 trajectories, uh, so that span across five units of work and each, uh, unit of work only had one success on the 10th retry. Right. So that's 45 failures, five successes, right. You would add that up to like a 10 % success rate, right. But hold on, right. If you permit 10 retries and on the 10th retry for each one, you got a success, then in reality, on a per unit of work basis, that's 100 % successful. So if it takes 10 retries and the value of the work, the unit of work being completed is higher than the cogs of 10 trajectories, then you may tolerate a per trajectory fail, a per trajectory success rate of 10 % because your per run trajectory or per run success rate is 100%, right? **Gabe Tramble (24:49):** Mm-hmm. **Derek Meegan (24:59):** So there's like a little bit of like some math and like framing there. And of course that doesn't always look like, you know, ⁓ 10 retries, right? Usually we recommend maybe three to five. And we encourage our customers to target something around like 75 to 80 % success rate on their trajectories. And that's extremely doable. ⁓ One thing, you know, that we've increasingly seen from our customers as well is this desire to maintain one harness, right? I have, ⁓ you know, again, **Gabe Tramble (24:59):** Yeah. **Derek Meegan (25:28):** We're talking about operating in ambiguity, right? So we work with another customer for bill pay, right? They want to pay bills agentically on the web. Well, right now they have really brittle RPA. They have people with boots on the ground that are upkeeping and monitoring this RPA. then remote or robotic process automation is like a very arcane term from like 1848 or whatever. **Gabe Tramble (25:46):** What's the RPA? **Derek Meegan (25:58):** to describe like automating browsers, right? Or automating stuff on a computer, right? Yeah, it was like kind of like really bringing like playwright automation or other computer automation to a business context. RPA, brittle deterministic automation. And then they have this long tail of websites that they pay bill on, that they need to pay bills on. But because they're so low volume, they just have humans, they're humans. **Gabe Tramble (26:03):** Yeah. Okay. **Derek Meegan (26:28):** going in, taking the information, going in, clicking and paying the bill, right, to do that last mile. ⁓ And so their desire is like, hey, you know, we have technical debt, we have all these human operators, like basically clicking through websites. Like how can we use agents to get the best both worlds, have repeatability with a high level of success for our highest volume websites, and then be able to capitalize on using agents for these long tail of websites. that we do not want to like, ⁓ like maintain RPA for. ⁓ and quickly it became an issue with trying to funnel all of the unique differences between each website into one harness, right? Like one website has like a certain flow where maybe you have to have to click a checkbox and another one, like you don't write something. It was like, how do you differentiate these? and what actually came about is equivalent to what we would call today, like a skill, right? You kind of write in natural language, like, hey, here's how to traverse through the critical path, right? There may be like some changes possibly, but this is likely the critical path that you need to go through. And then that brings us back to like what I was talking about earlier in that you can think about the output of the LLM as a distribution of, it's trying to predict the next token. And so if I tell the LLM, like, hey, when you go to this website, like, you're going to see this thing on the page. You need to just click this button at the bottom. If you have one agent that's told that and given the website versus one agent that's just told what the overall objective is and then given the website, the first agent, its output distribution is skewed towards that outcome of like, Hey, you're going to need to click this exact button in order to propagate to the website. And because that's represented in natural language, that looks more like a standard operating procedure that non-technical operators can approach and say, hey, know, browser-based offers video recordings of exactly what happened on the browser and what your agent was doing. I saw the agent go and do this thing. I don't need to write code, redeploy, like test, right? I just need to update the agent's standard operating procedures and continue to observe. And so that's like the fundamental difference that we see when, ⁓ **Gabe Tramble (28:30):** family. Uh-huh. **Derek Meegan (28:55):** know, customers want to deploy one harness across many different websites, is there still needs to be some level of customization on a per site basis, but maintaining that in standard operating procedures is much more preferable than maintaining like custom code or RPI solutions. **Gabe Tramble (29:13):** Got it, wow. So on the harness piece, and just for the audience, the harnesses, like the engine, or excuse me, the models, like the engine and the harnesses, like the car built around it that can, you know, has bigger tires or smaller tires to do specific things. Derek, for you, these harnesses, are they custom harnesses or are they using like Claude code or a co-work or some type of like generalized harness for like these use cases? **Derek Meegan (29:42):** Yeah, I mean, we offer our own browser agent. ⁓ Stagehand, well, BrowserBase is the main maintainer of Stagehand, an open source browser AI automation library. ⁓ Within Stagehand, there is a browser agent framework built on top of AISDK. ⁓ As models improve, I think the exact shape of the harness matters a little bit less and less, right? Because the model is doing most of the work. ⁓ But I really think about it like there's four things, right? There's the model, there's what's around the model, there's the human, and there's what's around the human, right? And a lot of times we're thinking about ⁓ like agentic work completion as if like humans are not part of the equation, right? We're just like, yeah, like there's all this work to be done, then all these agents are gonna do it. But wait, like where is the human in that story? Because the humans are the one that's asking for the work to be completed. The human is the one that need to verify that that work is going to be completed, right? I think that the discussions around harnesses often omit one of the most important things that the harness should be serving or maybe what's exposed to the human about the model's harness. So you can think about the human harness, the interface, right? Or the different ways that the human can sort of peer behind the curtain to what is the agent doing? how many agents are running at once, what does the cost look like, how can I steer an agent, what does human in the loop look like, what are the different failure modes, et cetera. ⁓ So, you know, when it comes to harness, I think this is something that's like constantly evolving. I think we've even seen a fresh, you know, perspective on this from browser use in their browser harness product. ⁓ Or, you know, it's not really a product, more like a framework, where it's essentially like completely bare bones. **Gabe Tramble (31:26):** Mm-hmm. **Derek Meegan (31:37):** And then you ask the agent to rebuild, to like build its tools on the fly. I think that's like very interesting for these like just in time, like browser agent use cases. But also like completely unsafe from a security standpoint, right? It's like, I don't necessarily know like with all of these supply chain like attacks, if I want my agent NPM installing anything, I don't even want to NPM install, right? So then I get a little bit scared and like the agent can, you know, arbitrary tools or modify its harness because. **Gabe Tramble (31:43):** All right. **Derek Meegan (32:06):** If that agent is holding anything that's like sensitive, right? API keys, credit card, right? These type of things. I do not want the agent modifying its harness. That all being said, as much as we give Cloud Code API keys, I know you've given Cloud Code an API key. I've never even watched you code, but I know you did it. So yeah, yeah, yeah. So that's all to say. There's a lot of competing opinions around harnesses. **Gabe Tramble (32:10):** the end. Yeah, guilty. **Derek Meegan (32:33):** I mean, I think it fundamentally comes down to, you know, protecting context. Whoever can protect the model context the most, give it exactly what it needs, and in doing so, help shape the output distribution to be higher quality. That's really what matters out of a harness, but I think broadly, the industry will converge on a right way to do it, because really, LLMs is one. **Gabe Tramble (32:50):** Mm-hmm. **Derek Meegan (33:01):** It's one thing, right? There's not a mechanical difference between ⁓ how inference works from XAI versus inference works from Anthropic, right? So there is a world where you can create the best harness that protects the context of the model most aggressively and permits the most dynamic tool calling, et cetera. ⁓ But I think right now, the name of the game is like... balancing those dimensions between performance, cost, and maintainability. **Gabe Tramble (33:33):** Yeah, the way I like to look at it is almost like driving on the road and there's like the huge potholes that you have to like go into and like the nuance of like actually using these automations and agents like shows itself in the potholes. And we're just not at a place where like the customer can just fly across the road. They kind of have to meet you at some point. Like you can build some scaffolding or like, you know, fill the hole a little bit or or **Derek Meegan (33:51):** Yeah. **Gabe Tramble (34:03):** right, but still it's not completely filled and like working with the customer or even like as individuals working with the tools to kind of see where the limitations are ⁓ is like the name of the game right now and Even if you can bridge like 50 % of the gap It's not like full-blown just you know, you click it and it just does everything There is like a lot of damage and clearly, you know billions of dollars of value that is moving around because of like the gap is semi field. So yeah, I like how you're kind of showing the reality and the nuance between what are the capabilities and you know, like what the customer's expectation is and what's available and kind of meeting them in the middle. **Derek Meegan (34:35):** Yeah, for sure. Yeah, and I think there's like fallacious binary that's proposed, which is that you can either have a human or you can either have an agent to it. And I think that's like, it's very simplistic thinking, right? Like in reality, ⁓ you know, we ought to be thinking about how humans and agents can interface together ⁓ as like something cohesive to complete work, right? And that is so much more powerful. because there are many ways in which agents and humans are complimentary, right? Like they can sort of, you know, cover for weaknesses in the other, right? So for example, I, as a human, need to sleep, eat, you know, drink water. I require healthcare, shelter, et cetera. These are all things that LLMs don't. Well, maybe they use water, right? But an LLM, you know, conversely, hallucinates. ⁓ is you fundamentally cannot hold an LLM accountable, right? I think like actually like IBM sort of originated this is like you cannot hold a computer accountable, therefore, like do not let computers make management decisions, right? So you can think about ⁓ instead of trying to like live in this world where it's like, ⁓ well, only humans can do it or only an AI can do it. It's like, well, how can we set up systems together? right, with those four things, the model, what's around the model, the human, and what's around the human. So we can maximize certain key business goals around work completion. Are we going to do it faster? Are we going to do more of it? Or are we going to do it cheaper? Or are we going to create a better experience for customers? And so I think there's a lot of opportunity there. ⁓ It's a little bit more difficult in the browser agent space to think about that, because more often than not, you sort of bisect ⁓ ⁓ responsibility between human and agent ⁓ because you know co-piloting an agent on a browser it's like you might as well just click through it yourself you know like each and that's how like a browser agent differs from like a coding agent ⁓ each individual action on its own is like very low value like it's a low about like a click is low value a type is low value we're like on one turn in Claude code I could you know the agent could output code and like code is very **Gabe Tramble (36:42):** Mm-hmm. Yeah. **Derek Meegan (37:07):** So I think in the browser agent space, there's more of this binary between what humans will do and what we want to set up agents to do. And I think if you look beyond that, or if you look at tools where ⁓ using the browser, or if you look at an agent where using the browser is only one tool, and only one use case out of a broader set of use cases, there's some interesting dynamics that I think are emerging in human computer interaction. **Gabe Tramble (37:22):** Okay. That's interesting. Yeah, because I've come across times where I instructed my browser agent ⁓ to basically do something and I'm waiting for it to complete and I'm like... I could have probably just done that faster because the cost or the time and effort of that specific action was just more valuable for me to do. It just cut the time I was waiting or the focus. It's almost like I have to actually calculate the focus that I'm either going to lose or the context switching. And that kind of reminds me of what you're saying, but more on an enterprise level of this determinism versus agents. **Derek Meegan (37:46):** Exactly. **Gabe Tramble (38:14):** piece like can you kind of can you kind of split between what constitutes something to be deterministic versus what constitutes something determinism as in like rules base right where it's like you know follow one two three and these are the rules ⁓ and whereas like that differs from agent or agentic reasoning **Derek Meegan (38:34):** Yeah, I mean, I would say it's like one thing needs to be sort of a moving target, right? So you could have very deterministic rules, but those rules are applied in different environments, right? So that's the example of like the bill pay customer, right? Like they have very specific rules for what they want their agent to do, right? Fill in this information and click this button, right? But those rules are applied in different places, right? Or you have one environment, but you're applying different rules, right? ⁓ or ⁓ you have one harness and that harness is satisfying different use cases, right? Basically one component ⁓ that's critical to the work being completed on a particular trajectory needs to be like ⁓ not static in an unpredictable way. ⁓ And that's where these agents really shine because they just unlock, like you just like functionally weren't able to do this before. If you were to task like this bill pay customer and say like create one playwright script that can handle, like can even theoretically pay a bill to any degree of success across thousands of websites. If you were to task them with that, like that's just like functionally impossible, right? And then today though, that is less than 150 lines of code and deployed in, you know, a browser-based cloud. So that's like super valuable, right? Like they could come to us, they can host their code with us, they can use our browser automation framework, we can give them best practices around that, they can use our browsers, and all of a sudden, like this problem that's requiring people to maintain, that is constantly breaking, is completely a headache, ⁓ it can be augmented agentically, right? Is it something that like you set and forget and you never think about it forever? No, right? But is it better than the previous state? Yes. And is this something that will certainly benefit from the inevitable increase in model intelligence and decrease in per unit token costs? Yes. Right. So that's also a great thing because you can kind of make this investment today and you have some level of insurance that assurance that like things are just going to get better. **Gabe Tramble (40:51):** Yeah, yeah, that the point that you're like touching you touch that quite a bit actually is like If you kind of lower your expectation for the maintenance almost of these things and kind of like, um, kind of conceptually, like being open to monitoring and improving, like you just, you enter a different phase of like what is possible with these agents because there's almost like a cognitive limitation where if you just think they're one shot, then you're, not going to get the value. But, but if you don't think they're, they're one shot and you're like working on these things, there's just so much upside and you can kind of really like perceive the capability and I think just in general there's not a lot of people who truly perceive and can feel like the model capabilities by like deploying these very specific workflows or stuff that actually matters where there's like stakes right. **Derek Meegan (41:45):** Yeah, I think, know, sci-fi versus reality, like point blank and simple. ⁓ These are not like magical thinking machines. ⁓ This is like, you know, this is calculus. This is linear algebra. This is matrix multiplication, right? These matrix multipliers are cooking us on coding, dude. These things are better at coding than me, right? ⁓ So it's powerful matrix multiplication, but it's matrix multiplication, right? And that's why it's like, I think it's this framing and then like, **Gabe Tramble (41:49):** Thank Yeah. Okay. Yeah. **Derek Meegan (42:14):** finally I think I'm getting a bit better at articulating it. Because I think I've internalized it from just repeatedly working with AI, Or kind of working with our sales team to deploy this with our customers. And really coming to understand actually from the other side of it, right? Not from the academic side, to say like, ⁓ this is a framing that makes sense, right? It is next token prediction. **Gabe Tramble (42:16):** Yeah. **Derek Meegan (42:43):** It is next token prediction. What is the current token? What is most likely the next token? Right? What came before GPT-3? You would say like today I am tired because last night I did not. And then you train the model to say sleep. Right. And then you then you train to say a few multiple words and then sentences and then paragraphs. And then you scale that and then you have something that sounds like intelligence. Right. And I think that's another important point. Right. Like We people will like look at an AI image and they know that it's fake, right? Like they're like, that's a fake image. Like that, that scene never happened in real life. And like, that's fake, right? And then, but then they look at the output of AI and they say, those are real thoughts. And like, that's, there's like a breakdown between that, right? Like actually what you're looking at is probabilistically correct looking thoughts, right? And like, could those probabilistically correct looking thoughts be applicable to solving a problem that you're trying to solve? Yes, right? But also very much no. And this is like, I think sort of the crux of like AI psychosis, right? And like people convince themselves, especially with the assistant persona, right? And I haven't quite decided if that is the model or what's outside the model, right? But the assistant persona that like is prompted and like RLHF'd into like the ChatGBT web app or the Claw, like the Clawed persona is actually very good, but like... the Claude persona, et cetera. Like, ⁓ these types of personas are very agreeable. ⁓ they're, they're, they're post-trained to have a certain behavior. There are negative externalities to that post-training. And I think that's very like consequential for people, like basically trying to ideate with LLMs thinking that what an LLM is going to say back is essentially equivalent to a real thought. When in reality, it's the result of matrix, like this is matrix multiplication. this is Matrix Mobile. I can't say that enough times, right? Because people type into it and they get out Magic stuff and then they think it's Magic and it's not. **Gabe Tramble (44:44):** That's right, yeah. Yeah, that is that is such a great framing because it does it does feel like thinking and I think your point to it could be it's probabilistically correct. It's probably the next ⁓ idea per se or or could be something that's real and the the like the cognitive security education of people like saying this there's none right like the the model companies literally do not discuss this and I don't even hear people online kind of talk about how to perceive these things, like mentally, the mental model in which to engage, because the mental model to engage changes your expectation ⁓ and actually does in a good way, right? Because then you can know what it can and can't do and its limitations, you get better performance. So yeah, I really appreciate it. I like your way that you frame that. **Derek Meegan (45:20):** ⁓ yeah. Yeah. Yeah, I just don't think we understand it like that well, right? Like, and not just like people, don't know what next token prediction is conceptually. Like the like frontier labs don't quite understand the phenomena of large language models. Like the, like, we don't even understand the best way to enter. Like, think about this, like chat, GBT came out, five years ago, coming up on five years later this year, right. In October. ⁓ we still don't know the best way, right? Like we're still like, MCP CLI, like custom tool, like blah, blah, blah. You know, all these different like protocols for agent-agent interaction, like, we broadly still haven't figured out the best way to use these and like what life's, what life, you know, ⁓ optimally looks like, via leveraging, you know, AI. ⁓ and so. Yeah. I think as time goes on, of course we'll. formalize like learnings and we'll look back and we'll be like why why were we doing this? know, why were we doing this like AI like random, you know AI co-worker startup or whatever like ⁓ you know, it'll seem so obvious in retrospect but ⁓ maybe maybe we'll remember like just kind of how difficult it was like for a while to actually figure out like how to use these things well I mean think about like how foundational tool calling is to the agentic experience today. This was not even something that was in the original release of ChatGPT or of like, you know, GPT-3 broadly. And there was no such thing as MCP, right? There was no such thing as like computer use, right? So, you know, broadly the industry is still in an exploration phase, in my opinion. **Gabe Tramble (47:22):** Yeah, wow. Before we go into like the browser browser API's and basically turning like a website into an API I want once to unpin the ⁓ the ramp and and there was like a couple other things that you said about like use cases ⁓ Not for ramps specifically but you guys are highly focused on like real workflows that produce economic value and those economic or those use cases can be quantified right you can say okay this workflow costs $10 and you can tell the customer is going to run this many times with this many iterations, $10 to file this receipt, right? And they can determine if that's valuable. What are the big or kind of main use cases that you're seeing for customers that are looking for real work done? **Derek Meegan (48:08):** Yeah, like there's tons of compliance workflows that are like super valuable. ⁓ Healthcare automation, healthcare portal automation, ⁓ financial workflows, bill pay, bill pull, receipt pull. ⁓ You know, a lot of these transactions that just, there doesn't broadly exist API support, right? Then we have, you know, large agent to customers that need reliable infrastructure to surround their general purpose agents. ⁓ so their usage of a browser may not be in a consistent fashion, right? Like they're, they're using the browser for their customers. ⁓ but they support their customers using the browser in, in variable ways. I think there, there are also, you know, some customers that, that wish to provide agentic brow, the capability to define agentic browser automations for their customers. Right? So. they're focused on that harness, on that harness or application layer that sits on top of the infrastructure. ⁓ Developing infrastructure is not easy, and it's particularly harder in the age of AI because the workloads that AI does are just like, it's not how a human would do it, right? A human would maybe scale up, maybe not linearly, but sort of gradually and then maybe higher and higher. Whereas an agent will just be like, know, shit, a hundred browsers, give them to me. And that's really tough. how forces interact change when the volume of those forces increases. So maybe that's fine if you only have 10 customers, if someone's like, oh, I need a hundred real quick. But when we're trying to serve thousands of customers concurrently, then we need to sit back with our infrateam. **Gabe Tramble (49:49):** Yeah. **Derek Meegan (50:03):** and say like, okay, well, you how do we scale these systems, right? Like, ⁓ how do we, you know, prevent any single point of failure, right? Like, how do we make them resilient and how can we make them like ⁓ scale quickly because our customer workflows can be, ⁓ you know, ⁓ very, very spiky. **Gabe Tramble (50:23):** Yeah, without like all the details and nuance, I know someone is still sitting here with like the question in their head, okay, how do I know this thing is not gonna like email my ex-girlfriend to sign up for my new product? And incorrectly if I'm wrong, you are like a 20 year veteran martial arts person, right? **Derek Meegan (50:38):** Hahaha. Yes, yeah, yeah, you did your research. Yes, yes. **Gabe Tramble (50:50):** So the stakes here are huge, right, for these things working. so like, do you like just that kind of abstract thought, like, do you actually, if you can answer, like, what are just the guardrails around something like that? **Derek Meegan (50:54):** For karate? like, what? ⁓ Yeah, I mean, ⁓ my perspective is that security is the root of scalability for agents, right? So if your agent is not secure, right? I'm not going to have it do more things, right? And like, and other people will not use it, right? So you need, ought to figure out ahead of time, like, what are the types of guardrails that you need? How can this thing like go off the rails? ⁓ And, you know, How can I make sure that just reliably does what I want it to do? And I think there's a couple of things. Like number one, for like generally low impact workflows or like maybe, you know, workflow where you're like, can actually like monitor it in real time. There's a very low likelihood chance that it will email your ex-girlfriend. Okay. Very low. ⁓ Because actually, you know, models are pretty good at instruction following, right? And unless like, something is injected into the context during the course of the trajectory to guide it towards that. I mean, again, it's next token prediction. And these things are pretty good at predicting the next token, right? So it feels like if you ask it, you know, to order groceries that like emailing your ex-girlfriend ⁓ is like not really in the path of like next token prediction. Now, I think this gets a little bit different. Maybe you're getting at like some weirdness with like, maybe if you have like an open claw. or like a Hermes agent, right? And OpenClaw is a very interesting project because I think it exposed two really important types of features that people just desire in agents, but in maybe a bad way. So the first feature is that it has broad access to everything, right? And this is where potential emails to people that you don't wanna talk to comes into play, right? Because... This thing is plugged into your email. This thing is plugged into your text messages. It has a browser. Like ⁓ it has access to all of this stuff. Your bank account. I don't know. People are giving anything to their open call these days. ⁓ Because it has broad access and by the nature of LLMs like it will complete ⁓ problems in novel ways. Right. It will string together tool calls in ways that like you didn't anticipate ahead of time. And that makes it extremely powerful. Right. Because this is very capable. Right. And then the other way that, ⁓ you know, OpenClaw exposed like some, some AGI magic that people like really like is event driven execution. So it's no longer that like, ⁓ my agent only does stuff when, you know, I like point the finger out and I say like, go do this thing. ⁓ Something external happens in my life. I receive a text message. I receive an email, something like that. And the agent responds and proactively does work for me on my behalf. And those two things together are. create a very powerful agentic experience. Because things will get done and you're not even directing it to happen. And problems will be solved in ways that you do not even expect that they could be solved. I'm pretty sure the creator of OpenClaw told a story about how he sent his agent a voice note. And because it had access to a browser, it looked up the OpenAI embeddings and figured out how to download them and then convert the voice note to text and then do the action. So again, You know, you don't think that, if I just give my agent like a computer and a browser, then it could possibly, you're not expecting in advance that it could figure out how to transpose a voice note into text and then kind of follow that instruction. ⁓ The problem with OpenClaw is that the way it achieves this broad access is like completely disregarding security. And that's why you have these instances where like, people are posting on Twitter like, my open claw was texting my ex-girlfriend. I saw something like that, right? Or like, ⁓ like my open claw, like deleted my database or like kept deleting my emails. I was like doing all these inadvertent things, right? So, you know, going back to the point where, where like security is the root of scale. ⁓ this is my opinion for why you do not see, you did not see open club basically displace every, you know, agent harness in existence or get broadly like. **Gabe Tramble (55:03):** I don't think so. **Derek Meegan (55:23):** do you see like major enterprises saying like, hey, this is our like, you know, notion for a reason did not implement their notion agent on top of open call, right? ⁓ Or many other companies, you know, they're not thinking like, yeah, let me use this thing, you know, despite these qualities, right? You can build those qualities and you can give an agent a wide array of access to stuff, but in a more secure way than like, hey, let me just throw a bunch of credentials on a Mac mini. and load this thing up on a Mac mini and then chat with it through WhatsApp. ⁓ So as far as guardrails go, my belief is that what you're trying not to happen should be verifiably impossible. So a good example is credential exfiltration from a sandbox. So even to use an agent in a sandbox, you need an LLM API key. So you already have something that's sensitive. And people's solution is they load it into the environment. of the agent. ⁓ Like that you consider it gone. You know what mean? Like it is not that hard like to exfiltrate an agent, right? You need to steer the conversation towards the probability distribution where the agent sends you the API key somehow, right? It can send it to you in plain text. It could send a post request, right? It could download. Don't even get me started on an agent's NPM and installing again. You're going to start getting me like stressed, right? ⁓ you know, it could, any myriad of things could happen where this API key goes from existing on the environment on the sandbox to somewhere it shouldn't be. Right. And so a lot of these sandbox vendors are starting to get savvy right now. They had this concept of like credential brokering, right? So you're running an agent in a sandbox. You needed to talk to things like, external services that are sensitive. Okay. Well, you know, give me a domain, right? Let's say in the API dot entropic.com and you know, load the secret to somewhere secure. When requests come outbound through egress on the sandbox, we will catch that request, we'll terminate it, we'll unwrap it, we'll insert the API key into the header, we'll wrap it back up and send it to the provider. And so this way, you're able to interact with sensitive APIs, but there's nothing to exfil, right? But this still gets more complicated because ⁓ you still want to protect access to that sandbox, right? That sandbox... is still ⁓ needs to be some kind of trusted environment because what happens ⁓ maybe if you securely call a tool and that tool has sensitive data and now that data is in the context window of the agent, right? And so this is why it's like credential brokering is not enough, right? Like just cause I credential broke some secrets but I still let my agent MPM install something. It can install something malicious that yanks the the chat history of the agent. and in the chat history is sensitive stuff that was exposed to the agent's context. So it's very complicated basically. **Gabe Tramble (58:18):** Peace. Yeah, wow. Yeah, there's so many and I feel like this is talking to why we've seen so many hacks and exploits like ⁓ not even just like in the crypto space where there's there's a lot but even in the like Web2 AI like Anthropic and all these different companies. **Derek Meegan (58:41):** Yeah, it's crazy. It's an unsafe world out there right now. And it's definitely, I think, things, at least internally, at BrowserBase. We're definitely thinking about this. it's especially ironic that it's happening during this type of experimentation phase with agents. I won't say their name, but a startup yesterday just disclosed that they had a **Gabe Tramble (58:48):** different. **Derek Meegan (59:10):** ⁓ an exploit happen through an escalation of an agent that monitors their infrastructure, right? Like they have like some agent deployed, I guess their agent's doing something to like monitor the health of their infra, like things are going good and maybe triage or like escalate if things are going wrong. Somehow this attacker was able to like probe, like expose some exposed like public surface of their technology. like gain control or interact or even maybe have interacted with this agent that monitors the infrastructure and then escalated it permissions and like impacted their customers. And like that's like very scary, you know? ⁓ And so, yeah, I think, you know, we'll continue to go through this tumultuous time for a bit. It will necessitate like, you know, real solutions to this type of security. But I think, you know, ultimately we'll be better off for it because we'll have more secure systems. And finally, when Anthropic gets enough compute, you know, they can drop mythos and we can all hack each other. So, it'll be good. **Gabe Tramble (1:00:15):** Nice just quick quick time check here. Do you have time to go through the API stuff? **Derek Meegan (1:00:20):** Yeah, I have until 2.30 if that works. **Gabe Tramble (1:00:23):** Okay, cool. Yeah, I'm good on time. I'll keep an eye on 2.30 ⁓ and I'll just cut this out. Okay, so can you talk a little bit more about, you guys have this product that ⁓ basically converts these sites into an API or like machine readable for the agents themselves. Can you just talk a little bit about that and like what problem is that aiming to tackle and solve, et cetera? **Derek Meegan (1:00:46):** Yeah, so actually this is just a skill, right? This is literally just a skill. And if you don't know what a skill is, ⁓ it's Markdown, Google it, right? Like it's literally just Markdown. And I think that's what's so beautiful about skills ⁓ is it is such a simple primitive, but extremely powerful because you can have tons of different essentially like standard operating procedures or different types of guidance for the model. And I mean a lot, right? Like you could have 50, 100, I don't know, 500 skills. And in very token efficient way, simple routing rules in your system prompt around if this type of scenario shows up, ⁓ if someone asks you a data question, invoke the snowflake skill. And then the snowflake skill can say, hey, if someone's asking you this type of data question, ⁓ maybe about sales, invoke the CRM skill. And the CRM skill can, you can skill chain. And you can make like very, ⁓ you know, codify very complicated workflows in these skills. ⁓ Additionally, with skills, you can attach code, right? That the model can execute. so, you know, skills is interesting distribution mechanism of both industry knowledge, right? And like capability. So like, you're not only like creating the tool, but you're like, yo, you want to use this tool, here's some ball knowledge and here's how to do it, right? And that, and you pair that with like, very adept ⁓ and intelligent agents. And all of a sudden you get tools that are like very powerful and can ⁓ operate on like very ambiguous problem spaces. so browser to API is actually nothing new, right? And there's a ton of players ⁓ that have attempted to like basically make a business around this, right? Where you say like, hey, this website basically has information that I want. I would like to get this information. ⁓ you know, in a con, in like an API contract, right? Like there, it's, it's a simple interface for something, for, for a module that can be rather deep, right? Cause you may have to traverse different sites. You may have to log in, right? But in reality, people just want that simple interface and an open API spec, right? Browser to API. I don't know. We were trying to come up with like a savvy word, savvy name for it. We landed on that, but it really generates an open API spec, which can be turned into an MCP that can be turned into a CLI. It's basically just like a top level interface that says, hey, here's the URL, and then here are the type of parameters that this thing accepts, and then here's what you can expect to get back. ⁓ And so Browser API uses our browse CLI, ⁓ which under the hood is built on the same browser automation library as Stagehand called understudy, ⁓ which basically creates a high level abstraction for ⁓ interacting with the page with a browser through CDP. There's Chrome Developer Protocol. Chrome Developer Protocol, very ugly, very verbose, very difficult to work with, understudy, very nice, page.click, page.scroll, et cetera. Like very, just like high level declarative commands. And then the browse CLI expose that in a CLI functionality. And then there's concept of browse CDP, which is a functionality I built into the CLI that allows you to create a parallel web socket connection, right? So you know, if ⁓ I'm using Playwright, right, or if I'm using a browser automation library, I connect to the browser through a web socket. So it's continuous, like bi-directional communication. And that's how I, it's like a remote controller. Like that's how I like, I drive the browser like through this web socket, right? Like, you know, scroll down, click this button, type these things, blah, blah, know, Chromium browsers accept multiple CDP connections and pretty well actually, as long as, you know, you're not like, One CDP connection is doing the majority of the work and then the other one is maybe listening passively. That's exactly what Browse CDP does is from your command line creates the second ⁓ CDP connection to the browser and passively listens to all the CDP logs that are occurring in the browser. So that's network activity, that's JavaScript evaluation activity, ⁓ you can see the other things that are attached to the page. So it takes all the CDP logs, It periodically takes snapshots of the DOM, so the HTML, and then it periodically takes literal screenshots of the page as well. And so what Browser.API does is it gives a special directive to the agent to instrument ⁓ browse CDP and output and transpose those CDP logs into a semantically organized and traversable file system. And this is the observability bed. that browser to API is built on. And so you can see exactly what's happening at the network level. You can see exactly how the page looks like. You can see screenshots of the page. You can see which network requests fail and basically how the page operates. And from that, the agent can start to say, hmm, I see this request came in after I clicked this button. And this request returns data that may be interesting. And then it goes and it discovers those APIs. It identifies that you can call them irrespective of the browser being opened. Sometimes you may need a token, sometimes not, but this is where, you know, Codex or Cloud Code can come in and ascertain that. They have this domain knowledge already baked into their training data. ⁓ And then what comes out is a clean API spec that says, hey, you know, like you're going to Hacker News. Here's the API endpoint that the Hacker News front end uses to populate its posts. And here's how to invoke that API. **Gabe Tramble (1:06:16):** Okay. **Derek Meegan (1:06:36):** And so for some like protected sites, it may not be so simple, right? But imagine, you you have maybe like a real estate directory and that director has a hundred or a thousand pages and each page has like 10, ⁓ like homes on it or 10 properties. If I were to do that through browser automation, like an extract all the information about these properties, I have 10 like ⁓ properties and then I click a button and then I get the 10 and then I click a button. Okay. I'm clicking a thousand buttons, right? **Gabe Tramble (1:06:36):** and **Derek Meegan (1:07:05):** That's a lot of buttons. Instead, if you found the underlying API and that API is of course paginated, then I could say for, you know, ⁓ I equals zero, you know, to a thousand, ⁓ hit this API and, ⁓ you know, ⁓ shift the page each time you hit it. And you can turn, even if you have to run it on the browser because you need some type of special cookie that's, that's only issued on the browser, running that for loop. **Gabe Tramble (1:07:24):** Mm-hmm. **Derek Meegan (1:07:35):** on the API is significantly faster than clicking through each page. Where again, right, you're accumulating risk through each individual action that you take and you're accumulating costs through each individual action that you take. ⁓ So yeah, that's, that's browser to API, ⁓ did super well. Like people definitely resonated with it. Created some controversy in Japan. guess, ⁓ you know, some, this developer in Japan made a CLI for like this online grocery store, maybe like a few days before I posted that. So yeah, I heard a lot about that from Japanese Twitter. That was kind of cool. **Gabe Tramble (1:08:08):** That's that's and and just to be clear this is something you put together and this is like all your domain knowledge correct **Derek Meegan (1:08:16):** Yeah, yeah, I put together a browser to API. Definitely want to shout out Shrey, my coworker here at Browse Race, he helped put together the video that we posted. But yeah, and like I mentioned, this is not, know, this is, you know, using the underlying APIs of a webpage on a browser is not something that I necessarily came up with for the first time in history. But I packaged it up in a skill, which is an amazing like distribution mechanism. and provides a really easy interface for people to understand. hey, browser to API. I'm gonna go for a browser, I'm gonna get an API back. That's all you need to understand. You download it ⁓ and then you use it with your agent. And yeah, I got a ton of comments and code tweets about people using it successfully and automating stuff. So that was super dope. **Gabe Tramble (1:09:09):** That's awesome. Yeah, I feel like skills kind of get trivialized a lot and like, oh, it's a text file. It's it's you know, what is it worth? Right. But for something like this browser API where this has like a lot of domain knowledge from, know, yourself who's deep in the trench. **Derek Meegan (1:09:25):** End code. End code. **Gabe Tramble (1:09:27):** Yeah, yeah, go. So I think that even is something to where like even myself initially, I've seen these like skill marketplaces and I'm like, what's where's kind of the value? But over time, you're kind of confirming here, I'm seeing more of this transfer of knowledge into the skills in the end. It's it's very like specific things. So, yeah, I think you're you're pulling on something that probably will have legs and maybe skills evolve into something even more ⁓ like an agent or something like that. **Derek Meegan (1:09:59):** Yeah, I think so. mean, again, we're all still exploring. We're all still figuring out. We also don't know how the hell we're supposed to interface with these LLMs, right? I think skills are particularly powerful. ⁓ The intermingling of soft rules and code is interesting. And again, yeah, like packaging domain knowledge, like, hey, here's how to do this thing with the actual tool to complete it ⁓ is particularly powerful. ⁓ And so, and I think, you know, tangentially, it's a great distribution mechanism. **Gabe Tramble (1:10:33):** Yeah. Just as we're wrapping up here, this is the last question for you. based on all the stuff you're looking at, like all the tech and the agents, not necessarily related to browser race, or it could be, but what is the biggest alpha that you've seen? And we're at the end of the video, so less people will see this, but yeah, where is just some concepts or tools or ideas or where you see the spaces going that you think is gonna have a lot of ⁓ value or growth potential? **Derek Meegan (1:10:53):** Mm-hmm. Hmm. ⁓ I think the biggest alpha in AI right now is actually like upskilling yourself and making yourself smarter. ⁓ You know, I think trying to figure out how to do like how to literally automate your entire life with an agent, ⁓ you know, and not really actually, you know, thinking about the ways in which you're nurturing your own intelligence, you know, especially considering like how much **Gabe Tramble (1:11:26):** Mm. **Derek Meegan (1:11:38):** ⁓ you can use an agent to cannibalize your own thinking. A lot of people have, you know, talked about how they feel like their brain is going through like atrophy. I don't even know what the active verb word of it is, but they feel brain atrophy, right? Because they're not like, you know, it's like if you go to the gym, right? If you stop going to the gym, you know, you're not getting sore and therefore your muscles are not growing. And so then you kind of like lose your muscles, right? So like, I think it's really easy to like vibe code yourself into oblivion. Like you quite literally can like buy enough tokens to basically code continuously through each waking hour of the day and then go to bed. But I often find that those people that are doing that aren't really getting much done, right? Like they're kind of going in circles. So, you know, actually one of the technical leads here at Browserface Walker, a great engineer, and we were talking the other day and he was saying that he read the study where, you essentially, when you're doing something, you can either like focus on doing it or you can spend time like learning and upscaling. And it's like really difficult to be both doing something and upscaling at the same time. And I think that's even more pronounced in the age of AI. So I'd say there's like a lot of alpha and you know, like reading books, like studying, thinking, writing. along with, you know, of course, figuring out ways that you can augment your AI output, your output, your productive output with AI. ⁓ So yeah, like invest in the human, like, let's let's sort of like reframe a little bit, right. And I released this article on Twitter recently called like, what if fully autonomous is the wrong goal? Right. ⁓ Like, everyone is racing to make a fully autonomous like ABC, right? Like, I want a fully autonomous product marketer, right? Like, **Gabe Tramble (1:13:07):** Yeah. Mm. **Derek Meegan (1:13:32):** I want a fully autonomous, like software engineer, et cetera. And it's like, yes, we want to go into the future. And like, I, we want AIs that can like do stuff. Yes, definitely. Right. But like where, what are we ground? What outcomes are we grounding in? Right. And so that was my sort of call to action. The article, like, look, you're thinking about doing something with agents. Cool. Right. Or you're thinking about solving, you know, generally you're thinking about solving some problem. Cool. Right. **Gabe Tramble (1:13:45):** Yeah. **Derek Meegan (1:14:01):** What are the underlying goals or outcomes that you're actually trying to manipulate through solving this problem? Right? Like a fully autonomous agent is but one solution in the set of possible solution in this, in the solution space. Right? ⁓ so maybe instead of grounding yourself in that solution immediately, because that's broadly what the industry is trying to do, or because I don't know, like it feels cool or like it feels good, right? Like it seems cool. ⁓ instead what are, you know, **Gabe Tramble (1:14:14):** Yeah. **Derek Meegan (1:14:30):** sit down and define what are the concrete business goals that I actually want to complete and reclassify AI and particularly agentic AI as just but one tool in the possible set of tools that you can use to attack the problem. ⁓ And then approach the problem from first principles being agnostic to the solution, right? Like to any one solution. And I think this is most pronounced in areas where people are investing in AI that where people are heavily **Gabe Tramble (1:14:43):** Mm-hmm. **Derek Meegan (1:14:59):** doing the work? Do you think about software engineering is a classic example where so many companies are marketing and like aiming towards this idea of an autonomous software engineer. But like what key business problems are you actually solving in software engineering? Because the biggest business problems I see in software engineering right now are like constrained software engineering bandwidth, know, spiky workloads by AI, you know, just intense. **Gabe Tramble (1:15:00):** Mm-hmm. **Derek Meegan (1:15:29):** ⁓ explosion of cognitive load and being like kind of unable to ⁓ like offload that cognitive load. that's, these you know, these have always been problems, right? Or the review process is totally broken because I can, I can go codecs goal, make 1000 PRs right now and drop those PRs onto my team lead. You think he's going to be happy? Like, no, he's going to be pissed, right? Like that, like making code or like just generating output. It's like not the equivalent. of like ⁓ driving like an organizational outcome. Right. And so people are like really focused on fully autonomous, like they're going to achieve fully autonomous slop. Right. Where my framing is like, how do, what are like key, you know, what are key goals, like key outcomes that we want to attain. Right. And to what degree do we want to manipulate or drive these outcomes? And what are the tools at our disposal? And within that, like How can we think about work completion as not, there's all this work and there's all these AIs and like, how do we get all these AIs to do this work? And rather there are people, there are AIs and there are this work and how do all of those things interact in order to complete that? **Gabe Tramble (1:16:32):** Thank Yeah. Wow, man. Yeah, that's really well said. I think I resonate very heavily with all that and kind of the double down on the like just coding to code and it's almost addictive and you can kind of go. Yeah, yeah, you can go into like. **Derek Meegan (1:16:57):** It's a video game. **Gabe Tramble (1:17:02):** like psychosis almost, right? Just coding and coding and coding and you work and then you kind of just flip into these new projects, new project, new project, and maybe after a month, okay, what have I shipped, right? And it's like this pseudo ⁓ accomplishment or like doing things. Yeah. **Derek Meegan (1:17:12):** Yeah. It's like performative productivity. And like, look, there's nothing wrong with it if you like to code, but like recognize what you're doing, right? Like recognize that like you're having fun. And like, if you're good with that, like there is coding to have fun in my opinion, but like, I don't know. I don't show up, know, Paul, I hope you're not listening at this point. I don't show up to browser-based to code for fun, right? I'm coding for money and I'm like coding so I can make money and browser-based can make money, right? And so it's really important for us to like... **Gabe Tramble (1:17:31):** Yeah. Yay. **Derek Meegan (1:17:45):** stay grounded in what we're actually trying to do and what we're actually, the outcomes that we're actually trying to drive, right? And I mentioned this in the article too, using agents or more broadly developing software is a business activity, right? And business activities need to impact customers, business productivity or costs. And if you ain't doing that, then you ain't doing it, you know? So that's that. I'll get off my soapbox. **Gabe Tramble (1:18:12):** Eric, man, this has been really good. Yeah, I appreciate you coming on and thanks for sharing about all this stuff and hope to have you on soon. Yeah, see you. **Derek Meegan (1:18:19):** Yeah, thank you for having me. --- # Privy and Agentic Commerce: Agent Wallets, Wallet Infrastructure & x402 > Shoal Signal episode. Guest: Max Segall (Privy). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-06-02 - Video: https://www.youtube.com/watch?v=ksYYRDUyXqU - Canonical: https://shoal.xyz/research/episodes/privy-agent-wallets-x402/ - Keywords: agentic economy, AI agents, agentic payments, x402, agent wallets, crypto, DeFi, yield, infrastructure, interviews ## Transcript **Gabe Tramble (00:00):** Today we're gonna talk about the constraint layer in the agentic economy and what that means for wallet infrastructure providers like Privy who need to maintain the controls around the wallet and not necessarily just providing the wallet infrastructure because we don't want agents to just go rogue as they say. **Gabe Tramble (00:16):** So today we have Max Siegel, the COO of Privy, who focuses on agents and wallet infrastructure that recently actually got acquired by Stripe. **Gabe Tramble (00:25):** so Max, can you tell us what is an agent wallet and how is this materially different from an embedded wallet or like a human driven wallet? **Max Segall (00:35):** 100%. So at Privy, we build infrastructure that allows you to provision wallets so you can embed crypto into your product. So we got off the ground serving many of the sorts of companies people think about when they think of crypto, like Hyperliquid, you could sign up with an email, get a wallet and start trading. Pumpfun, Farcast or Zora, OpenSea, all of these traditional crypto products. And as we were building and as agents started becoming more popular, people started using our wallet infrastructure to allow agents to manage digital assets. And so an agent wallet is just using privy to spin up a wallet and have the agent manage the wallet. And as we've supported more of these use cases that have gotten more and more traction, There've been a host of features that are specific to agents that aren't as important when you have a human managing the wallet. And so we've basically built an entire product capability set specific to agents. have an agent CLI, we have a policy engine, we have compatibility with agent protocols and a bunch of other things that I'm excited to dive in on. **Gabe Tramble (01:54):** So you guys are building this wallet infrastructure and one of the branches is this agent infrastructure that has exposed kind of a new set of problems in that space. ⁓ Before we get into like the particulars of those problems for the agent wallets, can you describe like who are these users and what are you noticing people using these wallets in the first place? **Max Segall (02:19):** Yeah. So we, about a year and a half ago, I think, or a year we had our first big breakout agent managed wallet customer, this company Banker that many people in the crypto world are familiar with. It's a bot that lives in the X feed and any time you tag it, it takes an action on your wallet based on what it was prompted to do. So I could say, I max want to send $10 to Gabe. It spins up a wallet for Gabe. It sends 10 stable coins from my wallet into Gabe's wallet. And then Gabe, you could say, I want those $10 to earn yield. And it would sweep them into a DeFi protocol for you. And people started having a lot of fun with this new crypto form factor. And it started driving, you know, tens to hundreds of millions of dollars of volume in privy wallets. And as these wallets got more usage, there were all sorts of new demands. Like at this point, agent, the quality of agents was a lot lower than it was today. And so it was very likely that when you prompted the agent to do something it would do, it would misinterpret your And so this was a big driver of our policy engine feature set and, you know, allow listing certain receiving addresses. So if the agent, you know, misinterpreted your prompt and hallucinated wallet actually can't physically perform the action. that it interpreted, like it can only perform what you design and lock down the wallet to be able to do. So supporting early builders like that, like Merit, like Nevermind, and a bunch of the very frontier builders in the ⁓ agent-managed wallet space allowed us to have the right tool set in place. So when there was like the massive open-claw driven agent explosion that we saw in the beginning of this year, We were ready with the capability set. And at this point, a third of Privy signups, we have like hundreds of signups a week for Privy accounts. A third of them are using Privy for agent managed wallet use cases. And it's a bunch of frontier builders pushing the limits of what's possible. There are a few popular patterns we're seeing, a couple of shapes that are pretty common. One is people who want an agent to... portfolio manage, that's actually a product shape that works quite well today and is ⁓ showing real value at scale. We have a company, Glider, that does this. I think one way to think about the value prop is it's like a betterment on chain in Forrest. And you can set up a wallet, an agent a set of rules of how the portfolio of assets in the wallet is managed, and then just let it run on That's a very popular use case. Another one is for payments and, and actually like consumer driven payments. So you get an open clause set up or you have your agent working for you. spin up a wallet for the agent and then you just prompt, you know, the agent is prompting it to make payments for you. That's an explosive design space right now. And we just launched with AWS. It was two weeks ago now that their agent core platform, their agent builder platform. natively integrates privy wallets so that agents you create on the platform are provisioned along that we set up. set them up with wallets and they can make payments across the X4o2 ecosystem. We did a similar thing with Langchain and their agent building capabilities. So that's a super, super common use case. Give the agent a wallet and let it start paying for things. And then the third very popular use case, and we're seeing dozens of great teams building this, these, they're almost trying to become ironically like Stripe for agent payments. And we're a part of Stripe, we're owned by Stripe. ⁓ And these teams are building marketplaces where an agent can come in and there's a marketplace of services they could purchase, like they could purchase one. unit of SMS or one unit of compute. And it allows for per use microtransaction based services so the agents can do whatever work is needed of them. So the agents can drop into these marketplaces like Sapium or like Lava or like orthogonal. There are a bunch of great teams building these types of products. **Gabe Tramble (06:46):** Okay. **Max Segall (06:50):** Actually, Stripe has our own version of it as well. And they can drop in, they could purchase services. It's all happening on crypto rails with microtransactions. And that's another super exciting design space that's opening up. **Gabe Tramble (07:04):** Nice. So there's the portfolio management payments being able to provision and just pay for things with the wallet and then the microservices. On the microservices side, are those type of services similar to like AgentCash Locust? Is that the same type of product? **Max Segall (07:20):** Yep, There are so many great teams building in that space right now. **Gabe Tramble (07:26):** And then just ⁓ for these products are basically allowing you to provision a wallet in like your codex or some type of agent tool and then it can pay for microservices through like X4.02 and MPP. And that's what you're saying has been another big use **Max Segall (07:43):** Yep, and it's both sides of the transaction. So it's the agent having the wallet to spend on the services. And then the wallets are useful for the services. So you can have a Cloudflare wallet or a Twilio wallet, ⁓ and you can really open these platforms up. So it's not like the platforms need to integrate services one by one and have umbrella API keys. You could have ⁓ a payout wallet accumulating value for the service to claim. **Gabe Tramble (08:13):** Interesting. Yeah. So we've kind of only talked about so far just on the show in general, like the services that are provisioning while it's for the consumer. And you're saying you're supporting both the consumer and the enterprise who's basically providing the services, the micro payment services. **Max Segall (08:32):** Yeah, so it's, mean, the whole is at the frontier stage right now, but we need a way for the service providers to get paid as well. So that's either gonna look like there's a wallet accumulating value for the service provider to claim, or there's cool stuff we could do as Stripe or other merchant side ⁓ products that can cool stuff we could do as Stripe or other merchant side ⁓ products that can automatically convert the inflows into fiat outflows. **Gabe Tramble (09:10):** Got it, okay. And correct me if I'm wrong, I'm try to extrapolate this higher. So if I'm the end user and I wanna pay for a microservice that will tell me the price of Bitcoin, then I would use one of these like agent payment services that can use X4.02 and find a provider. Let's say the provider is CoinGecko. But you guys are working also with CoinGecko to accept those payments as well. **Max Segall (09:35):** Yeah. So it's these, these marketplace services are either giving coin gecko and interface to plug into so that they could provide like per per use services to agents and get paid for that. ⁓ you know, or obviously Stripe, Stripe is investing a ton on this front as well. **Gabe Tramble (09:58):** Nice. And specifically, what are these different ⁓ policies or pieces that become important that's different from a normal wallet? Like, what are these things that you've accumulated from, it seems like, just real customer interaction with like BankerBot? What are the particulars here? **Max Segall (10:16):** Yeah. So the way the Privy wallet works is when we spin up a wallet, split the wallet's private key that controls the wallet into shares. So there's never a single point of compromise with the Privy wallet. And then you as the developer implementing Privy, you can figure who controls the wallet. That could be an end user like you Gabe. It could be an agent that's controlling the wallet. It can be our customer can have full control over the wallet. And when the controller of the wallet initiates a transaction, the key shares come together in a trusted execution environment and execute the transaction. And the trusted execution environment is, there's sort of like a checkpoint in the trusted execution environment to make sure, does the transaction satisfy the conditions that are allowed on that wallet? And that's how our policy engine works. So you could say, you know, an agent managed wallet can only transact up to $100 a value a day. That's like an example of a policy. And so if you're trying to put $120 transaction through when, even if the proper owner of the wallet initiates the transaction, if it violates the policy, it gets blocked in the TE and it does not, it cannot execute. So we've, we've built our policy engine. So many of features of our policy engine are built around supporting these agentic use cases and preventing, you know, if, a prompt is misinterpreted, let's make sure that value doesn't go where it shouldn't. So if, you know, an example, Madeline, uh, who leads a lot of our agentic work at Privia loves to use is like, you know, if the prompt is, want to buy a boat neck sweater and the model interprets like that as I want to buy a boat, then that purchasing a boat transaction is not approved. So the policy engine, it's super expressive. Like if you can think it, you can design a policy around it. And that's, that is like one of the largest features. One of the most important features for agent managed wallets. Another one is, it's, it's, it's, it's related to policies. It's what we call quorum approvals and you can designate rules so that you know, if a transaction meets a certain set of conditions, maybe the agent managed wallet requires the user to also approve the transaction. So that's another feature on the security front. We have all other sorts of things like allowed origins to make sure that certain types of transactions need to originate from certain sources. So, you know, maybe transactions under a certain amount can be fully managed via an agent. and transactions over a certain amount need to be managed in an interface. You could also start with a user wallet. So you could get a wallet in Ramp, one of our customers, and then you can delegate the management of that wallet to an agent for certain actions. So you could start in a traditional product, a traditional user wallet, and... then have the agent take over and start making certain transactions for you. **Gabe Tramble (13:33):** wow, interesting. So in that last example, let's say I'm trading, I'm trading them, say, okay, actually I want to have the agent do these little rebalances. You guys support infrastructure to allow both at the same time. Nice. **Max Segall (13:47):** Yep, exactly. So all sorts of rules and controls you can put on it, which a lot of that functionality was born from supporting early agent builders. And it's cool, like a lot of the fintech companies who are doing nothing with agents yet, they want the same rule set. they feel great about being able to either block list. **Gabe Tramble (13:58):** and we'll **Max Segall (14:12):** receiving addresses or set transaction limits on wallets. Like lot of these features that were built to support agent builders are useful to companies like Deal or Klarna or Ramp. **Gabe Tramble (14:23):** Thanks. Why do you think that or less like, can you help us understand why this design decision is not put on the developer side or on the user side as in, you maybe I can put in a prompt or maybe some code that says, okay, don't spend more than this much, right? As opposed to moving that into the actual wallet infrastructure side. Can you help us understand why that is important or ⁓ is something that you guys have taken on specifically. **Max Segall (14:56):** Yeah, so it's flexible to the point where the developer can expose the creation and enablement of those rules to the user. So the developer could say, I actually just, I don't care who my user is, I want to protect them in these five ways. And so I'm going to put these rules on the wallets and that's easy to do. And then you can have the user, you can give the user the ability to set either like MFA controls or transaction limit controls as well. And then that gets enforced by the same policy engine under the hood. So it's a very flexible product that allows you to protect your users if you'd like, and it allows your users to like progressively secure their accounts if say the asset value in the wallet exceeds a certain point. **Gabe Tramble (15:45):** Okay, so you guys are taking the decision of basically cutting a lot of the risk and then the user can basically expose that risk and by doing that it's at the wallet layer that it kind of gives the most leverage for that. Nice, okay. **Max Segall (15:58):** Yep, exactly. So I think the big thing to call out is like, there is so much excitement about this space right now, but it's also very clear. We've just scratched the surface of what's possible. Like many merchants still don't accept stable coin payments. And so, and that's, that's changing quickly, but you know, as, as we at Stripe make it easier to accept stable coin payments by default and other merchant facing payment tools do similar things like capability set's gonna evolve a ton as we just have completely new unexpected use cases emerging. **Gabe Tramble (16:44):** Yeah, are there any use cases that you think are going to be bubbling up that you're seeing early right now or pretty novel implementations or any things that kind of break from those three that you explained before? **Max Segall (16:57):** people are doing all sorts of crazy things. it's really sky's the limit. Like if you can imagine it, you can build it. But the big limitation right now is the fact that many merchants don't yet accept stable coins. And I think we at Stripe have like a big role to play in addressing that limitation. actually just, we just today made MPP enablement. ⁓ a self-serve, you know, any merchant, regardless of where they are, can turn it on today. And that's like one of many, many steps that we're taking as Stripe to make this easier. Then the other thing that is pretty cool is that you can, with a privy wallet, with stable coins in it, you could provision a card on top of the wallet. And then, know, now you have a way of facilitating transactions from the wallet. even if the merchant doesn't accept stable coins yet. **Gabe Tramble (18:01):** It seems like Stripe and your guys' positioning ⁓ is pretty unique because a lot of early technology has to overtake. the incumbents or and that's usually done by distribution or like virality of the products. But in your case and kind of for the broader ecosystem, Stripe is really like one of the big gatekeepers here and they can essentially just like turn the lights on. So I'm sure that you guys have some friction maybe and like what are you seeing as the path typically for building? Is it like, OK, you guys are co-building or do you kind of feel like you're like a lab, how was this dynamic, especially as they're like a gatekeeper in this case. **Max Segall (18:48):** You're saying like, what's, what's the, how do, how do we and the rest of the Stripe team work together to facilitate types of products? Yeah. So we have been operating as privy for the last year, even though we're a part of Stripes org. And so we're building as close to teams who want to access this tech as possible. And the idea is like the **Gabe Tramble (18:56):** Yeah, yeah, yeah. **Max Segall (19:17):** crypto landscape, the way stable coins are being adopted, like it's changing so quickly and we need to get the modular products as close to developers as possible. So when a team like Banker, when a team like Merit Systems wants to push the space forward and reimagine what's possible, like let's give them the raw building blocks and stay close and whenever they need something, whenever the product doesn't work well, let's evolve it fast. So we're doing that. And then we're building privy into and wallets in general into many of Stripes biggest products and making them stable coin fluent by default. And, and, and, you know, we, we, we almost have like a customer relationship with link. For example, we, just announced that like link is going to be holding a balance, have it have the ability to hold balance by default built on stable coins. And that's, you know, us working closely with the link team and treating them like they're our biggest potential customer with 200 million users. And, and so we work super closely with all the product teams across Stripe and try and find ways to take the same tech that we're like rapidly iterating with the frontier builders with and bring it into our own products. **Gabe Tramble (20:39):** And for all of these different stakeholders, I'm sure not everyone feels the same way about crypto and kind of like this revolution and centralized finance and such. But from the executive level, is there buy-in across the board? Like talking to the link team, right? Link is in like a lot. products. When you're paying for stuff online, you can kind of do the easy checkout with Link. ⁓ And they've really nailed that in as a tight product. like, are you finding friction in these conversations or is it really like a hot lead and you're just onboarding them as a customer? **Max Segall (21:16):** Yeah, I mean, the amount of like top down buy in on stable coins at Stripe is like the most exciting thing I've I spent I was at Brex for four years before joining Privy in 2022. And I decided I needed to work in crypto after like trying to build products on fiat rails. Like I just kept running into all the limitations of ACH and the other popular payment methods that Brex is built on top of. And so that was that was like the catalyst for me getting excited about crypto in the first place. And now it's playing out in the biggest imaginable scale with Stripe leaning in as hard as it is. And, you know, in order to deliver Stripe value to, you know, as many people around the world as possible and in order to really create instant frictionless payments, no matter how big or small they are, like crypto is the enabling technology that makes that possible. And so there's tons of top-down excitement and pushing teams to think about, we deliver this experience we're trying to unlock with crypto rails? And we're featuring all of the most exciting things happening on previous tech stack in Stripe firm-wide company all hands meetings. And that's honestly inspiring a lot of the building that's happening at the product team level. And it's really cool. And this isn't like, this isn't just happening at Stripe. We see the same thing happening with our biggest customers, our biggest FinTech customers as privy, where teams will see P2P payment experiences being built by crypto native teams. And, you know, next thing you know, Remitly is trying to replicate that with their user base of tens of millions of users and, and Revolut and Robinhood are keeping a close eye on like all of the all the trading and investing use cases that are working on the crypto side of the market and figuring out, okay, what can I deliver to my tens or hundreds of millions of users? So it's this like super exciting moment where the things that are happening at the frontier, the crypto native teams that are just like defining the products that can work are inspiring things happening with teams who have access to tens to hundreds of millions of users. **Gabe Tramble (23:40):** With what you're seeing right now, I want to pose this question as kind of like a three. potential answers and maybe if those don't fit then can come up with your own but I'm curious where do you place your bets on gonna be like the largest ⁓ economy? Do you think it's gonna be on the like ⁓ B2B stable coin side or like agentic commerce or like where the autonomous agents are basically buying and selling services ⁓ or do you think both like between both and yeah of those three I'm curious where It's from all the stuff that you're seeing, which in lane kind of seems like is going to be the biggest or have kind of the biggest ⁓ outcomes. **Max Segall (24:24):** Yeah, so our mandate is just like anything real big impactful that has PMF built on crypto rails. We want to be the infrared behind it. And we are like super ear to the ground nimble on picking up on, you know, where are there trends that are working? Where is there like real value being delivered with crypto? Right now, I mentioned a third of our signups are agent managed experiences. Most of those are not working at scale today yet. They're experimenting and there are teams that are breaking out with use cases that are driving a ton of volume. The three I mentioned being like the three big main ones. And so that's a massive investment area. And we just like have irrational conviction that like in 10 years, there are going to be more agent facilitated payment transactions than human facilitated payment transactions. And that's going to happen on crypto rails. And we need to make sure we can support everything that's that that builders are trying to unlock with that. So we're investing a ton of product energy there. And then fintechs, every big fintech, you go down the list of the top 20, you know, biggest or most valuable fintech companies like they're they all have some stable coin crypto strategy and just making sure that we're able to address whether it's delivering native yield or payments to countries worldwide or unlocking access to markets they can't serve, making sure we have everything we need to support those use cases that's massive, growing quickly. The crypto native side of the market is there are pockets of explosive growth. Hyperliquid obviously is like a very top of mind thing. They were one of our earliest customers and there's a whole ecosystem of teams building on hip three, hip four, unlocking use cases that are getting. really quick PMF, like being able to trade commodities over the weekend or being able to create markets around the valuation of private companies. So lots of cool stuff happening there. And then the so the those three use cases, agentic use cases, fintech use cases, market crypto native market use cases, whether it's purpose or prediction markets, and then the fourth are treasury use cases, people who are reimagining how do you build business, finance, operations, infra on crypto rails and make that more efficient. There's a ton of work at Prairie happening on that front too. **Gabe Tramble (26:55):** Wow. So you guys are playing in a bunch of fields and what you're saying is the commerce side for payments with like these neo banks and upcoming startups is basically where like this hardened use cases and then on the agent side is like R and D in basically fine tuning. Is that a good articulation of that? **Max Segall (27:15):** Exactly. You've got it. **Gabe Tramble (27:18):** In on kind of circle back a bit on the T side, the trusted execution environment. Could you explain the reason why you guys took that decision and like what that actually enables for agent wallets and even just payments in general? **Max Segall (27:35):** Yeah. So it is, we big fans of TEs. They're the gold standard of security. They are extremely locked down. The AWS Nitro enclaves that are TEs are built on top of, or they, you know, they're default off the network and they are secure and they are extremely They're really well suited for these like checkpoint controls. So whether it's a policy engine or a quorum of approvals, like you can at the T level enforce in, ⁓ you know, this is enforced entirely by code that ⁓ if you have a policy in place, like if the transaction does not. comply with the rules of that policy, it's physically impossible to get that transaction through the TE. And then the other thing about TEs we love is everything that happens in the TE is verifiable. So there is a proof that you can go back and reference on exactly what happened, what conditions were met. And that is great audit feature to make sure that the system is doing what it is designed to do. **Gabe Tramble (28:57):** Interesting. So this environment is more robust for ⁓ being able to execute the policy and the logic and all these different functionalities for the managed wallet. **Max Segall (29:09):** Yep, exactly. **Gabe Tramble (29:10):** On the AWS side, just to break a little bit, so you guys partnered with AWS to basically facilitate like micro payment services on behalf of Amazon. So Amazon's they have like this managed agent service and then you guys are rolling out your service in collaboration. What are they kind of after there and what do you think this enables in terms of like distribution? Because Amazon is such a beast really this seems like a distribution opportunity, not just for you guys, but for ⁓ other projects, et cetera. **Max Segall (29:47):** Yeah, they are, they are you know, they're the whole suite you need to stand up and, and manage an agent for your product. So they're trying to be like the one stop shop you can go to, to build and manage your agent. And I think payments is if agents at the highest level or kind of like code that can perform or intelligence that can perform work. Being able to participate in the economy is a core part of performing work. And so it's important to them that the agents that they're allowing teams to build have a way of paying for things. And I think there's like a pretty big philosophical race happening when it comes to payments of like. Are these payments going to happen on card rails? Are they going to happen on crypto rails? Is it going to be a combination of both? And I think they recognize that there are some really great advantages to payments happening on crypto rails. know, for one, it's permissionless to spin up a wallet. And so when you have an agent autonomously, maybe spinning up a sub agent for a task, like getting that agent access to an account that can hold money and pay for things, it's much easier to do that. with a permissionless system, then getting that agent access to a bank account, which is the traditional way of getting a card. like getting that agent access to an account that can hold money and pay for things, it's much easier to do that. with a permissionless system, then getting that agent access to a bank account, which is the traditional way of getting a card. But then you have the roadblock of many merchants don't accept stable coin payments today. So you need some way to, if the agent wants to participate in the economy and the counterpart they're trying to transact with doesn't accept stable coins, need some way to allow that agent to access that service. So AWS. integrating wallets natively, integrating privy and our agent managed wallet capabilities natively. This is them saying, you know, they see building block as part of their offering. **Gabe Tramble (32:06):** And is this why you guys have the card? Is that for agents being able to spend or is that more on the human side? **Max Segall (32:13):** Yeah, we have the card. mean, the card, it's one of the it's similar to our policy engine. Like it came out of requests on both the human stablecoin wallet side and the agent stablecoin side. So our card capability is like one of the best examples. One of our flagship customers is this company ARK used to be called Dollar App. They're the fastest growing Neobank and Latam. And their big big value prop in the beginning was help people in Latam save in dollars. And so if you were, if you wanted to get paid, you live in Argentina, you wanna get your paycheck in dollars, you can give a regular account and routing number so the paycheck can go into what feels like a bank account. And then Bridge, which is another subsidiary of Stripe, they converted the Argentinian peso. payroll into stable coins. And so the dollar account balance was denominated in dollars. And people, you know, in all the markets that dollar app launched in went crazy over this value prop. They were saving in dollars. And then, you know, the big question is, well, like, everything is stable coins behind the scenes. But then the big question is, like, how do I actually use those stable coins? And being able to provision a Visa card on top of the wallet so that You know, could go onto Amazon and purchase things or you can go to Netflix and purchase your subscription or even go to a grocery store and put down a card. That's like the big unlock because most of these services, especially then, didn't accept stable coins. And so it was built around just this like acknowledgement that people want to hold crypto assets. There's like a of value in holding crypto assets, but you need a way for those assets to be spendable in the real world. **Gabe Tramble (34:10):** And for you guys, everything seems to be denominated in USD, across the board for these payment services and for ⁓ even the agents. Are you guys seeing any certain areas where the denomination of the currency is not always dollars? **Max Segall (34:31):** Yeah, I mean, that's I think that's one of the most exciting trends right now. We work with a bunch of local issuers at Bridge. We have a bunch of local issuing capabilities as well. I think it's like reasonable to expect that people are going to want to hold stable coins, hold local currency stable coins. ⁓ So I think, you know, in terms of like growth areas that I'm extremely high conviction. And in the crypto ecosystem, that's a big one. **Gabe Tramble (35:02):** And for what you've seen, what are those actual use cases? Is it for consumer day-to-day spenders? A lot of trading happens in US dollars. So yeah, for those new denominated current digital assets in different currencies, where are you seeing those specific use cases so far? **Max Segall (35:23):** Yeah, it's just who like don't want to think about currency conversion their entire life is in Brazilian rail and they want to hold balances in Brazilian rail. They don't want to have to like worry that some macro event made this transaction I was planning 3x more expensive in you know very volatile currency even though you know saving in dollars might be advantageous the like certainty of the value of the transaction is a priority for lot of spenders. **Gabe Tramble (36:00):** Yeah, on the builder side, ⁓ where are you guys seeing people blowing themselves up essentially when using ⁓ agentic payments or even just kind of these payment services in general? Like where do you guys see the most risks ⁓ for builders, developers in general? **Max Segall (36:20):** I think it's the same biggest risk we've seen from the beginning at Privy, which is when you're building tools for a frontier market, there's a very big temptation to take like the newest tech trend and build the product around that. And so when we were getting started, like account abstraction was like the big new capability, ERC 4337 had just come out. There was a new way to sponsor gas payments and There was a whole wave of builders in the beginning when we were first getting Privy off the ground that would come to us and say, we're building an account abstraction app. And I was like, what does that mean? And they're like, well now I can sponsor gas. So we're building a product around that. And that's like, that is not the product. There's like no inherent customer need behind that. That's just a ⁓ tool to make building the product easier. And I think the biggest risk by far is like right now there are so many new tools coming out and people are looking at the tools and saying, ⁓ there's my product idea. But starting with the like, what's the, what is the real world experience we want to unlock? And then let's look at the tools we have at our disposal and maybe stable coins and crypto like aren't the right tool for it. And just being like super pragmatic about what's the best way to deliver value to the world and going, going problem out first tech out. I think that's the biggest risk. **Gabe Tramble (37:46):** Do you have any example of these currently right now, these hot trends essentially on the tech side or even the research side as these protocols start bubbling up? **Max Segall (37:59):** Yeah, mean, like agents are very cool and very useful, but like an agent might not be right for facilitating the either payment activity or investment activity that you're trying to use. like, know, agent out is, think ⁓ it's similar to like ERC 4337 out. Like, let's actually think about like, what are we trying to build? What are we trying to drive? Does an agent make sense? Increasingly, agents are super powerful. And so for many, many activity, it will make sense. But like, don't start with, we have agents now, let's build something with it. Start with, this is the problem I'm trying to solve. Let's figure out how to do it. **Gabe Tramble (38:49):** Okay, so even the overfitting of agents right now as pretty good, like a pretty hot topic, AI agents, is one of these things that you're noticing as well. **Max Segall (39:01):** I mean, it's a third of our customers at privy. So it's pretty crazy how many teams are excited about this. Rightfully so. It's like the most powerful thing I've seen available to people. making sure that you're thinking about it from a, this is the problem I'm trying to solve and this is why it's a good solution to that problem is the right way to go about it in my view. **Gabe Tramble (39:26):** Yeah, yeah, I'm just having these conversations. I've noticed a lot of strong builders are using some deterministic code to facilitate large portions of their operations. And then the agents are kind of just orchestrating these tools, like these deterministic tools, maybe it's for trading or market making, security. ⁓ So yeah, definitely the overfitting, I agree, on the agent side ⁓ has been a big thing. I'd say to end here and just the final question, of all the stuff you're seeing, I'm curious, where is the alpha? Is there any type of companies or team or new provenance that you're seeing evolving? And it might not have to do with agents, might just be kind of trends amongst customers or ⁓ stable coins in But I'm curious to see, where would you stake your bets at this point? **Max Segall (40:25):** That's a great question. mean, there are lots of cool things happening around agents. there's, I think that's great place to spending time. The thing that like I've always been really bullish on for teams that are like building crypto into their products or the fact that like crypto rails give you like, it allows you to build like anything into a super app because of all of the protocols you have access to and things are on crypto rails. So, you you can take stable coins in a wallet and invest them and convert them into any other on-chain investable asset. And increasingly, that's a pretty big universe. It's not just like ETH, Sol and Bitcoin that are thought of as like traditional assets, but it's like tokenized stocks and commodities. you know, you can make, you could take positions on prediction markets. So That's one example. You could also, you know, take stable coins and very quickly build P2P payment like Venmo-esque experiences on top of them. You can invest them into DeFi. And so, like, I think these Neo banks that are building on stable coin rails and like able to hold stable coin balance, like they're going to quickly become super app type companies like Robinhood. I think that's a really underrated trend. The fact that Rails allow you to turn any consumer app into a super app. **Gabe Tramble (41:57):** So like a WAP or ⁓ maybe like Slash, these are the companies you're thinking of. **Max Segall (42:01):** Yeah, two great teams that we work super closely with. **Gabe Tramble (42:06):** Nice nice. Well cool, man. Yeah, thanks. Thanks for sharing and this has been great. Yeah, I hope to have you back soon See ya **Max Segall (42:14):** Love to come back soon. Thanks for having me. Super fun. --- # GPU-Backed Debt and the Case for the End of SaaS Credit > Shoal Signal episode. Guest: David Choi (USDAI). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-05-27 - Video: https://www.youtube.com/watch?v=5bU6OylSTd4 - Canonical: https://shoal.xyz/research/episodes/usdai-gpu-backed-debt/ - Keywords: crypto, DeFi, MEV, yield, tokenization, Bitcoin, AI compute, interviews ## Transcript **Gabe (00:01):** So we've seen the tokenization and really the financialization of markets like real estate and these entities like Fannie Mae that have derived from these financialized markets. However, where is the case of this with AI and what does this look like and what is the debt market and the financialization of debt in AI and compute look like? Well, I'm here today with David Choi, the co-founder and CEO of USDAI, which is working on tokenized debt in relation to compute and data centers. So David, can you take us through, you first started working on financing and underwriting stuff, artworks like Warhols and these other major art and now moving into the AI and compute space. Can you take us through that journey a little bit and what you're seeing in terms of the compute markets as of late? **David Choi (01:01):** For sure. I guess in terms of my personal background, kind of like coming out of college, my first job was in art financing, ⁓ where we were looking at ways to find indirect ways of valuations that weren't just based on very limited data sets, where you would have like maybe three or four comparable trades in the last year, which is not enough to be like what they call a mark to market, which is when that's a previous valuation. And they didn't have cash flows. ⁓ with these assets. So we tried using these Monte Carlo simulations on the sale leaseback of the artwork where you have the right to buy back your own artwork as a way to estimate the pricing. And so you had to assume your own volatility index, which we had to create ourselves. But it was just kind of teaching me in that early educational process of my career where you can't rely on just simple data points. You have to use time to your advantage, pricing. and just other data sets that you can infer. And then afterwards, I worked at Deutsche, my first job. Again, in terms of esoteric assets, my first deal was actually doing a securitization deal on timeshares, which is single mortgage divided up. Two weeks is the timeshare, so 26 times multiplied by 300 rooms in a hotel. And then that's where the real money came from in timeshare, not from the sales themselves. So it's just like interesting to see how prevalent this was when it comes to asset-backed financing. Just like most things in the world just don't have a price, but you can definitely discover one based on a market price. And yeah, that's kind of like, you know, worked in crypto ever since for the last couple of years. **Gabe (02:47):** guys. **David Choi (02:55):** ⁓ doing a little bit of MEV, doing a lot of investments. And really seeing how DeFi has developed mostly as what I call a money markets, ⁓ which might be a different definition to what most people view it. But I always viewed that most of DeFi was money lending against money. ⁓ And I feel like it still has the incredible tools to create financial systems for things that aren't money, which I would redefine as the foil of ⁓ being capital markets. where you have things you're giving loans against capital, things that are productive. And I think people also divide it as like, there's loans and then there's margin. Most of DeFi is just margin, so it's not actually lending. So I think we're kind of seeing the evolution and this is why you see rates so low in DeFi, because you're just providing margin. You're not actually providing productive, scalable, expansionary capital that is what credit really is for, to build the economy out. **Gabe (03:52):** So you have this deep background in underwriting essentially and then kind of moved up the stack to MEV and then to DeFi and now in this specific field of the compute. ⁓ You mentioned a little bit about art not having a lot of these data points. Can you one, of take us through the landscape of the debt instrument in this space for compute? And then also, is there enough data points for ⁓ this industry in the first place? **David Choi (04:25):** Yeah, there's some asset like GPU backed loans that people try to experiment with, but they're just really underdeveloped. Go on Bloomberg, you click a single CoreWeave bond where they say it's the ABS, but for GPUs. ⁓ Well, first off, it's against a single counterparty. Not that, you're underwriting CoreWeave, you're not actually underwriting. ⁓ And then CoreWeave is like a counterparty, but you're not actually underwriting a basket because that's how get to ⁓ a number, right? You have 10,000 different loans and then that's when you can get to enough. Like when I give you a loan personally, I'm underwriting your ability and my trust in you versus the loan to 10,000 different unsecured individuals peer-to-peer loans. That's when you get to a default rate and you get to a number. And that's how you use law of large numbers in your advantage. So that doesn't really exist for GPUs because that requires 10,000 different loans being put together. That's when you can actually start having data points and numbers and start creating metrics that are derivative from the underlying asset. ⁓ That doesn't really exist in this space because ⁓ it's just really difficult to structure. ⁓ This exists for airplanes. This exists for equipment like tractors. This exists for automobiles and houses ⁓ where you have a very deep secondary market because you have the data points. have a lot of numbers. You have lot of ⁓ softer data points. ⁓ It just doesn't exist for GPUs. The way that GPUs have typically initially been financed is very similar to Bitcoin miners, which was convertible debt, where the company would take out that very, very diluted loans, which would get converted out of the money strike at multiples of valuations, which always gets struck because it's fast growing companies. And yeah, if you were a seed investor in some of these Neo clouds, you're already diluted 95 % because It's just a capital intensive business and you're selling equity for depreciating assets just to keep up with the times. It puts a lot of pressure on your equity. ⁓ And yeah, the financial tools available for ⁓ these assets have the industries is very limited. And you can't really do equipment finance without that. It's just not really a thing. It just doesn't make any sense in terms of, weighted average cost capital as a financial concept. You're really, really pushing the cost of equity and not really pushing cost of debt. So the tool sets that a lot of these companies have is limited. Like we were talking with this data center who was talking to a middle market investment bank and he got a four page presentation on why you can't get financing for its 200 mil GPU cluster. ⁓ Because he's like, yeah, you just can't get a fixed APR loan for this. It's not availability in the market. And the reason being is that. ⁓ to your point earlier about Fannie, ⁓ when you get a loan from a bank, the bank doesn't hold the loan. They resell it. ⁓ Otherwise they wouldn't have enough money. like, you know, kind of like fractional reserve banking. they don't be actually holds to debt because if you can't resell it, you're holding the loan. ⁓ This is how was ⁓ in the 1920s, 1910s, like before Fannie, like as a comparison of what the world existed without it. **Gabe (07:38):** Mm-hmm. **David Choi (07:51):** You used to get a five-year balloon loan against your house, 50 % LTV, ⁓ and every five years they would just roll it until the Great Depression happened and you would have to give up your house because they wouldn't want to roll it because they were holding it on the books, ⁓ short-dated loans. ⁓ So it was only with the creation of, I guess, the ability to package up the debt and make it tradable ⁓ where you have a forward flow to sell into. **Gabe (08:09):** and Okay. **David Choi (08:21):** That's when it became a deep capital market. That's why you can get 10 % down low interest rate loans in your house because of that credit extension. But that doesn't exist for GPUs because the time it takes to structure that debt is so long. Giving 10,000 loans and then making it tradable is an onerous process by banks, which takes years to do sometimes. And if you're talking about year-long structuring cycles for an asset that depreciates in the same period, because they're faster depreciating assets, it's not possible, structurally not feasible, ⁓ to create these instruments for these asset classes. ⁓ So the market's in this weird period where it needs this instrument. But the legacy traditional finance just doesn't move in the same speed. ⁓ **Gabe (09:00):** Mm-hmm. **David Choi (09:21):** And that's why it's never been a product. And it's why it was never made for Bitcoin miners. Bitcoin miners don't have the same product either. It was never made for GPUs because GPUs, most of the GPU miners, or sorry, Neo clouds ⁓ were Bitcoin miners and they use the same methods, which is converted to that. ⁓ But not everyone wants to debut their investors by 95%, including their own ⁓ equity. So yeah, it's a limited tool set. This is why we push into private credit and just to like, **Gabe (09:38):** Mm. **David Choi (09:51):** I'm sure the audience knows, they see Blue Owl ⁓ and then they also see Oracle borrowing all this money from another legacy tech business where they're doing term loans because they're all trying to compensate for this lack of this core financing mechanism, asset-by-financing, ⁓ because it doesn't exist. They go into borrowing against Oracle. They go into Blue Owl, ⁓ which was definitely a big private credit firm, but can they finance trillions of dollars? We don't know. mean, how fast can they raise money from their LPs, right? ⁓ That's their replacement cycle. ⁓ But if it's tradable, ⁓ you can create the trillion dollar markets. But instead, we're just pushing it further and further out. ⁓ And this is why ⁓ you're seeing a big issue in the financing markets ⁓ in the AI space. ⁓ And installation is getting delayed. ⁓ Projects aren't getting financing. ⁓ And now you're seeing the scarcity increasing with chips because demand's increasing, but supply isn't. **Gabe (10:58):** So basically there's this void, Where, like a gap. where the banks are not servicing and just the system is essentially inefficient. The financial system is inefficient in servicing this certain sector. We can talk about it in a second, but there's like the hyperscalers and then the Neo clouds and you guys are servicing these Neo clouds, which are the long tail. But if you can kind of ⁓ smooth over this bank issue, what exactly is the issue? Is it the risk? Is it the just the timeline to underwrite these these ⁓ assets and instruments? Is it an education issue? ⁓ Kind of. Yeah. And you kind of double click into like, what is the core the the core disconnect here? **David Choi (11:47):** What blockchains do really well is that it's incredibly asynchronous. Like it's just a continuous, it's a perpetual, right? That's why we have perpetuals for ⁓ like hyperliquid, because it is perpetual. So you can just roll over the contracts again and again and to add infinitum. ⁓ And it's also great for stable coins because it just goes on forever. And I just want to preface it there because I think it's a digestible metaphor. ⁓ What we're creating is kind of like a depth perpetual. It's something where you don't have to be, ⁓ it's not something we issue every year. Like, hey, we're issuing this ABS that has this maturity date. We're issuing a single debt instrument, which is SUSDAI. ⁓ And whenever a loan gets created in our product, it gets added in to that debt instrument into Infinity. So you can always enter a loan and then you can obviously repay it at different times in the next guy. ⁓ This is how TradFi works. TradFi does everything synchronously. ⁓ If you, like I said, 10,000 loans, you have this like tenor of maturity date and that's why you have so many. ⁓ If you go into the book, you have so many of these bonds. ⁓ It's because they all have a maturity date. ⁓ And that just doesn't work for ⁓ like 24 months refresh cycles on different chips where you have your, if people are saying like, it's going to take two years. I'm like, you're already like two generations out. Like you're. You're not at the hoppers or the block wells. You're not the Rubens and maybe the Feynman's. ⁓ So it's a timeline of securitization. It just doesn't fit into the same speeds and cycles as AI or tech or hardware refresh cycles. ⁓ It's just too slow. no matter how, even if you get to the most efficient speeds, which is probably when you have a lot of data, a ton of data, like real states amount of data, which is which take like 100 years to develop, ⁓ then maybe it might work, but not right now. Right now, it's a brand new asset class. ⁓ And there's definitely data. It's not necessarily the extent that you'll see unless every single American owns a GPU, which might be possible in the future. ⁓ It's not that infeasible to envision. ⁓ But ⁓ enterprise GPU, not personal PC one. ⁓ But ⁓ that's when... you might be able to create that structure. ⁓ for now, you need to create something that is a lot more accommodating to the speed at which you can structure the debt, which is what blockchains are perfect for, really. And that's why, know, companies like Figure kind of came to the blockchain to solve a very, very similar issue ⁓ for Helocs, where they can speed up the process rapidly by having asynchronous systems. ⁓ And that's why DeFi is great. So for us, ⁓ the moment of loans originates immediately priced and added to the SUSDA pool, ⁓ no matter what maturity that they enter or exit from, because we're just seeing their monthly repayments at different times. ⁓ And that's why it's pretty nice. It's kind of like, if I explain to more Tri-Fi people, it's kind of like, I would say, infinite, ⁓ you don't require a warehouse facility ⁓ for more Tri-Fi folks. ⁓ It's kind of like represented in the tokenized form itself, which is SUSDEI. **Gabe (15:14):** Okay, so this perpetual approach suits the maturity of the asset class, essentially. yeah. And so how do you prevent against the risk of like, quote unquote, kicking the can on these assets? **David Choi (15:22):** the short-daiting this event, yeah. Yeah, so we. in terms of the underwriting work or in terms of ⁓ the repayment schedule, I guess. **Gabe (15:46):** Yeah, I would say maybe the under, maybe both actually. Yeah, maybe if you can kind of talk, or how you were thinking about both of these without things going bad or stale, cetera. **David Choi (15:50):** OK. ⁓ Yeah, we actually have a much easier job than many of the curators in this space for DeFi protocol. I guess I can describe it in two ways. One, to address those respectively, one would be permutations of underwriting is very, very limited for us. So in terms of how much work we have to do as a governance protocol, as an USDA protocol, and by the way, to clarify, the CEO of Permian Labs, the developer behind them, ⁓ not the protocol itself. But ⁓ the permutations of work is very limited. There's maybe eight chips, of which the eight chips is very clear parameterization that we can just follow. ⁓ And and then secondly, ⁓ it's extremely high cash flowing assets. One of the highest cash flowing assets in the world in of the scale. So that makes it really easy to generate liquidity ⁓ as a result of that. ⁓ **Gabe (16:35):** Mm-hmm. **David Choi (16:52):** So in terms of the permutations that we look at, there's very few limited number of chips. So we don't underwrite companies ⁓ and we don't underwrite loans to small companies. ⁓ We're not a SMB like lending business. We're very much a GPU backed and GPU like asset backed and turning the ⁓ assets into bearer assets on chain and then giving loans against them. ⁓ Much like Aave doesn't care about your FICO score. ⁓ Justin Sun, if you wanted to, you could get a loan from Goldman. But he chooses Aave because he could just put up his collateral and get cash against it really fast. ⁓ In our case, we don't care if they're all birds or whoever they are, because I actually don't think there's ⁓ as much value in the enterprise value of the companies versus the value of the chips, ⁓ because that's what we're undermining. And there's only a few chips, like I said. There's like B200s, B300s, GB 200s, GB 300s, ⁓ maybe 5090s and H200s. And whenever a new one comes in, we just get rid of the other ones that are older, just because it's just a refresh cycles. ⁓ But there's not that much variables as a result, versus like, hey, I'm looking at this point with this LTV based on the volume metrics based on where it's listed. There's a lot more risk based on this define integration. And I'm like, And you have to do that across 30 different assets. It's tough. And it's a hard job. Versus eight assets, which is just a chip to sell. So in terms of like kicking the can, it's actually there's not much kicking to do because it's very, very easy to not easy. Sorry. It's very, very straightforward. What we're really looking at and just being specialized, special in these ships. And because we're so aggressive in terms of the debt service coverage ratio, which is like what we really measure, like what is the most they could pay because kind of like Fannie, you kind of want to be pessimistic, impatient and aggressive to have the deepest capital markets. The more that you are impatient, the deeper people will trade it because they know it's ⁓ programmatic. Fannie definitely wants to be a program if it wanted to be just like a straight up like machine. ⁓ As for like ⁓ liquidity, ⁓ you have so much cash flow January from this that the repayment of debt is incredibly fast. And I'll give you the real numbers of our protocol. We look at the debt service coverage ratio, is these are mostly homogeneous assets. So it's not like this one is that different from the other one. We just look at how much they pay every month, which ends up being 3 % of the principal and 1 % interest. you multiply that by 12 months a year, that's about 48 % and 50 % of the loan repaid. And that's kind of what we look at. And that's how you generate liquidity. And you're not actually pushing the next greater fold because you just know like, I can just redeem my money if I'm less than 8 % of the pool taking two months. And with a 20 % buffer plus a 50 % repayment, the 70 % of the loan book kind of being pushed back into cash in a single year. That's pretty good. It's actually very good. It might not be the 100 % capital efficient, but I think DeFi users prefer a little bit of a buffer in terms of their liquidity preferences. But at 70 % of the loan book be turned into cash in a year is pretty damn good, I think. And it meets the impatience of the money market participants in DeFi. **Gabe (20:16):** Mm-hmm. So your answer to that question about how do the investors necessarily become comfortable, right? Is these things are cash generating machines and basically they can take on this and model out essentially what they should receive, et cetera. **David Choi (20:56):** As long as we sequence it correctly and organize it economically and make it really, really rules-based, think people get pretty comfortable. I myself have lost so much money on the Grayscale premium trade ⁓ to the point where I got in podcasts because one of my threads went viral. ⁓ I know what it's like to have your money not be redeemable by primary redemption mechanisms and where people assume secondary and liquidity mechanisms. And this is also true for Goldfinch. This was true for like usual money. This was true for like ANZIN. I mean, I can go down the list of every single failed RWA experimentation and almost 100 % of the time, it's because you can't get any money back. I was like, how did you design this thinking like just putting an AMM pool on UNICEF is to solve it? I'm like, no, no, you need to make generate cash. I'm not going to, I can dabble in STRC discussions because there's some yield generated, but if you can't redeem it for the principal, there's always going to be a risk. ⁓ For us, we make it very clear how exactly you get your money back. And that's how we organize a lot of our tech around. We call it QED, which is inspired by Flashbots' MEV boost. Which is pretty much every block you generate some liquidity or a reward and then you bid for it. What we do is that every repayment, we turn into an auction. It's like a tender offer that happens every month for 4 % of the entire NAV. ⁓ Yeah, and then as long as you're programmatic around it, think liquidity organizes around it, and it becomes ⁓ anti-fragile for these kind of use cases. **Gabe (22:30):** Yeah. Yeah, just to touch on that RWA piece, I think in a past interview you said some of these RWA firms are like, quote unquote, toxic waste to the ecosystem. If maybe if you can like dive in and if you feel inclined, share some names and maybe why you kind of feel that way about these these protocols. **David Choi (22:40):** Yes. I've just been in this space for so long. I know what happens with adverse selection. People think that we're adverse selection and I'm like, well, we're not underwriting ⁓ these companies, right? They're not like companies asking us for money. We're literally taking their underlying collateral and giving a loan against it. So unless you think one of our eight assets are ⁓ adverse selected, you can make a claim, but they think we're giving unsecured loans, very different, right? Versus asset backbones. ⁓ I guess what I don't like is people taking Dino yields, things that are like ancient, like real estate loans and bringing it on chain. I'm like, good. So you're taking the most capital efficient systems in financial history. And you think it's going to be better to give mortgages on chain. I'm like, no, that's that you just adding more fees and making the R and R inefficient. Just like adding more fees like, and the interest is lower. but you're taking the same amount of risk. Doesn't make any sense. I think what is the And that's why I think it's toxic waste. think it's just, I mean, I'll say this a bit with like a lot of these like tokenized private credit stuff that was coming on. I was like, do you really want to buy this stuff? And they're like, no, it's a good brand name. I'm not going to say which ones, but I'm like, the brand name doesn't mean you're underlining the underlying assets. You're literally taking something that's illiquid and you're pressing it nav par. Anyway, it just... They don't actually originate on chain. You see A16Z complain about this too. They're like, guys, you're just tokenizing securities. You're just adding fees on top of fees on top of fees and then the same underlying asset. If you don't originate on chain, and that's what happens in our protocol, you're actually originating. The fees are generated on chain and the token holders own the fees. ⁓ And we own the vertical stack of, not we, sorry, the protocol owns a vertical stack of origination, structuring, and distribution, which is the three layers of the financial process. So yeah, think it's, I think it's toxic waste. And this might pivot into like the next part of what I think is happening into credit in and of itself is changing. And we're at this perfect juncture. I think SaaS credit is, is dead. I think SaaS credit for what it was in the Zerp era, where we were giving unsecured loans against what seemed to be great consistent cash flowing ⁓ corporate loans because they're just generating great subscriptions year over year. ⁓ That era is like shutting down. This is what private credit is going against such wide compression is because those companies are going into, their stocks are crashing, right? Because you're just one codex prompt away from replacing the entire business. ⁓ Thing is AI companies aren't that much better either, right? **Gabe (25:36):** Mm-hmm. **David Choi (25:55):** You can't really give a loan to a cash flow company because this is going to get computed away. But what you can give loans to is not against the company unsecured, ⁓ but rather against secured asset backed loans against what they do have that is valuable, that generates entire business proposition, which ends up being 90 % of their costs to compute. ⁓ So what you're seeing is the end of this chapter of SaaS ⁓ cash flow based under unsecured corporate loans. and as being completely replaced, not by new companies, but by assets and just by GPU loans. So GPU loans isn't a niche is what I'm saying. It might be the replacement of all of credit that we know today. It's just, it's a super sector like replacement. It's a superstructure replacement. And I think people kind of are missing that point. And kind of having a hard time understanding this, but I'm like, and **Gabe (26:40):** Mm. **David Choi (26:55):** I'll say this too. This is also why I think this is the second largest business in AI. ⁓ Number one business is Nvidia because they create the chips. ⁓ The third largest business is OpenAI because that's the LLM. ⁓ But they only make 20 to 40 billion a year. Nvidia makes 500 billion next five quarters. Wall Street makes 150 to 200 because you're paying interest on the chips. ⁓ Because all the chips are definitely so to me, it's the second largest business. And that's only going to get bigger and bigger. And that interest is very, very high for Wall Street. And I don't think that's toxic waste. think that's the this is the birth of a new sector. And this is what we should be tokenizing, not Dino yields that are fees on fees on fees of tokenized securities, but really originated on chain. Anyway, sorry to go on. Yeah. **Gabe (27:48):** So your thesis is a lot of these RWA companies on chain, We're going after the companies which were bad assets and kind of like the new category opportunity is you guys can not go after the companies which are you maybe the data centers or the providers but more so the actual asset which are the the GPUs and you're seeing this as the second largest asset class. So you have the compute which is Nvidia. You have the the debt structure around the compute and then the models. Is that a good articulation of kind of your and how you're seeing the landscape play out. **David Choi (28:30):** Yeah. And I feel like this is what DeFi has always been great at, which is bearer asset lending. And this is kind of what we're congruent to. Like it is like GPUs as the isolated collateral away from the companies themselves. And I think this is something that DeFi people are also pretty like comfortable with because it is a low trust environment. There is a cost of underwriting. And I think a lot of people kind of misunderstood that in the early days of RWAs. They tried to push it off by just saying, We're just going to do it off chain. ⁓ V1 of RWAs was just like, let's underwrite on chain, and we're just going to do it ourselves. This is ⁓ what you saw with the first wave of RWAs. ⁓ I hate naming them, because I do like a lot of the people. But they were trying to underwrite themselves on chain. Didn't work. It just takes too much work. There's misalignment. Now, I guess the current iteration is that, yeah, we'll just use like a bank, know, like a top tier guy. And I'm like, this still still doesn't address the issue ⁓ versus doing what we did well ⁓ in DeFi, which was, Hey, there's a specific set of assets we could underwrite based on it being asset backed and then underwriting the asset itself, which is a lot more scalable. It's kind of like these five boxes that you like update the parameters for every quarter. It's isn't that different from Fanny, right? Like you have like three buy boxes. If it fits into it, then it works. Otherwise, we're not going to accept it. And it has to fit into this, otherwise we're not going to take it. That's what a governance protocol does. And I think it did it very well. yeah, and I do think this is the second largest industry in AI specifically, not assets, but in AI in general, ⁓ is the financing of chips. ⁓ I don't think anybody's trying to disrupt it. And I know for sure they aren't because ⁓ we chat with like Nvidia and they're like, there's not many startups trying to disrupt financing. This is not something they think of a startup like a disrupt. They think of private credit funds or our banks trying to finance these large deals. But a startup is to do it. ⁓ It's a very different proposition. And to me, a stablecoin kind of is a bank, right? ⁓ It's just taking, there's a checking and savings account. In the case of us, it's a USCI and SUSCA. We're not a bank, but it kind of follows the same concepts. ⁓ And we're... the deals generated from the checkings can subsidize ⁓ the loans that we're giving on the savings account. ⁓ And it can be competitive with these counterparties. The only difference between us and many of the other counterparts that they're introducing their customers to is we're not trying to be vultures and trying to ink every covenant out of the counterparties. ⁓ We're just trying to scale the AOM and define this asset class, ⁓ which is very different. ⁓ Anyway, yeah, think it's also what DeFi could be great for in reestablishing itself as the center of this new wave. ⁓ I think people forget that NVIDIA stock went from like. $33 to like $10 over the course of a few months because ETH went to ETH staking. ⁓ When Nvidia was 100 % beta to crypto, it's time to bring it back, know? Like ⁓ crypto used to be like the center stage of Nvidia's fate. ⁓ And now I think DeFi is in a great position to be center stage of AI ⁓ and we're trying to be that proxy. **Gabe (32:00):** in So you mentioned in video a bit, and I know you guys work directly with them for ⁓ basically onboarding clients and they potentially would send you leads and things like that. What are they saying internally about, you know, this long tail, the Neo clouds ⁓ debt, you know, sector of the market? There's the hyperscalers and then there's this longer tail where like on the hyperscaler side, there's you know, there's billions and billions of dollars being moved around and you're seeing these huge But yeah, curious, what is NVIDIA saying and how are they looking at this? Do they have any ideas? Do they kind of align with your thesis and your framing? Are they seeing things a little bit different? Yeah, curious to kind of hear like the inside take on that. **David Choi (32:47):** Yeah, I'll say this too. It's not like an exclusive thing that they're working with us on. It's just that Nvidia works with a lot of partners, a lot of funds and a lot of financing counterparties. So I don't want to imply anything exclusive there. They work with their ecosystem. You can go back to their numbers. Obviously at the $500 billion, like metric I said before, about 20%, 30 % of that is for emerging neoclouds. **Gabe (32:57):** Yeah. **David Choi (33:14):** know, sovereigns that are just starting to build up their supply all the way to like ⁓ non-U.S., European or Asian counterparties that are going to be the next coal weaves. ⁓ But they just don't have access to the American credit markets, which is by far the best in the world. If you want a loan in the U.S., it's way easier than getting a loan in Europe or getting a loan from a non-Chinese bank in Asia. ⁓ It's just like, credit is really easy in the U.S. But it still hard for a of these counterparties to get a loan. So they know it's a big issue. There's very, very little competition for the USEF protocol because credit just doesn't exist in a lot of places in the world as easy as this, especially for a growth sector that seems like it's high risk in different parts of the world. yeah, mean, 20 to 30 % of the revenues may soon be completely stopped because of this massive private credit retreat. People were depending on private credit for smaller deals. ⁓ But as you see, most of the private credit in the world is in full retreat right now. ⁓ This is a great place for DeFi to step in and tell that void. it's definitely, ⁓ if I was looking at what's stopping the deals that's happening right now, and I guess I'm going to kind of segue into that as like, what is ⁓ the difference in terms of bottlenecks between the different between the revenue stack, ⁓ the 80 % to the 70 % of the hyperscalers, ⁓ they're doing gigawatt build-outs, right? ⁓ They're massive. And that's what powers the limiting factors for them. Funny thing is really, they can always get more money because they're massive ⁓ American pillar like corporations like Amazon. But finding gigawatt is near impossible. That's like amount of energy that Denver uses, right? Like that's how big these properties are. And they're like, They are hyper-object scale build outs. If you were to build like 15 Las Vegas spheres, that's about the same amount of cost. It's like $50 billion for a gigawatt. It's fucking massive. ⁓ Whereas if you want to find like two or three megawatts, maybe 10, you can find that in the US or in Europe or in Asia, sometimes in Africa or Latam, definitely at Latam and near like a lot of the major dams. But you can't get financing. They have the opposite issue. There are sites all over the world that they can get. But who's going to finance a sub 300 mil GP financing deal where there's no equity upside and it's just a yield deal, an infor deal, ⁓ and they just have to organize everything together? ⁓ And they're like emerging operators. They'll have the chips eventually in the off take, but it's hard to get the off. It's like a big chicken and egg problem because they didn't, they might have the brand names. ⁓ **Gabe (36:07):** Yeah. **David Choi (36:10):** But they need to finance it. That's like the thing that just stops a lot of deals. So that's the segmentation of bottlenecks. If you're big, you have a power issue. If you're emerging, you have a financing issue. ⁓ And yeah, that's how we've seen the market develop at least. **Gabe (36:30):** and you're gonna be serving and serving currently this emerging market and the financing issue and you're seeing that this is gonna be the second largest. So on those points too, when going back to the asset, why specifically the Nvidia chips? And if I'm not mistaken, you guys are solely focused on those. Why are you not using any other providers in their grave? **David Choi (36:56):** well, they're 90 % of the market. So that's kind of like the big reason. It's like, we do have like the most data from them because they are the most traded. We work with a lot of the ITADs, which is something called the IT asset disposition. The only thing that we've kind of like real, ⁓ created a big network for, ⁓ they're the guys who originally were doing server asset dispositions and with very little residual value. Chips have like extremely high residual value. ⁓ but, ⁓ they, ⁓ they, we, talk with them all the time. ⁓ And they don't really see ⁓ these other chips being traded. They're not really used. They're not really put up into, a rental marketplace. then people rent them out. They call it spec, or just per hour rentals, by weeks instead of by years. That's not really developed. So they don't really have a base price to defend the value of an AMD chip versus Nvidia. That's actually just pure. pure gold, right? It's just cash. can resell that instantly because you know that you can actually make money on it the next day. So not enough data, no off-take market, ITADs aren't trading it, less than 10 % of the market, and Nvidia chips are just big enough. Eventually one day, but yeah, I have not seen Google TPUs trade in the market once. **Gabe (38:20):** And who are you seeing as the runner-ups? Because I know at one point, NVIDIA is working with Grok or the equity loan system with Grok. yeah, who are the emerging players or technology ⁓ that you think is going to maybe hold up a fist or be potentially like debt that you see or assets that you see that you could support? **David Choi (38:44):** ⁓ I would say like AMD and Google are the ones that have been maybe brought up. Typically what they do is like they do these guarantees of minimum hourly rentals to get financings. That's what we've seen in the market at least. So like, hey, you get like this $2 an hour guaranteed if the contract fails. And that's a guarantee by like say AMD. So you're really just underwriting AMD. You're not even underwriting the value of the chip. I mean, we'll do that deal. If we get a guarantee from AMD, yeah, I'll then put it into the USDA protocol and get liquidity on it. I'm sure governance will approve. ⁓ But otherwise, yeah, it's still very, we're still very far. There's a lot of new companies kind of coming out trying to disrupt Nvidia. ⁓ But I think Nvidia would just buy them just like ROK, like you said. If a new competitor came out that's really better than Nvidia. They're gonna price it 95 cents to the dollar to Nvidia anyways. So it's still gonna be like pretty credit worthy because they're gonna be a max capitalist. But yeah, I think Nvidia is probably just gonna buy their way out. They have so much cash and I'm sure these ship companies wouldn't mind that either. **Gabe (40:04):** Yeah, yeah. And where do you see is like the opportunity? So like there's the broader thesis where, you know, the credit markets, there's this opportunity to be restructured, especially right now when things are hurting. But where's like the next biggest opportunity that you're seeing that maybe people aren't accustomed to just because you're uniquely suited in like the financialization piece and on the GPU side? **David Choi (40:32):** I think a lot of people talk about agent to commerce as if it's like a ball in a mitten. Like, yeah, you can pay your agent in this way. And that's agent to commerce. And I'm like, okay, that's sick. It's just like a plaid. Or they view it as like a credit card, or they think they'll make money out of interchange here and there. But what I think people often forget is that what is 90 % of all expenses in all of AI? It's compute. Pretty much, people are astonished by the salaries by OpenAI or ⁓ by these other companies. But I'm like, have you seen the compute though? It's so much bigger than the salaries or the talent acquisitions. ⁓ Even that OpenAI. investment by Microsoft. Most of that was in Azure credits. It wasn't in cash, the famous one years back. Just because it's so expensive to run all these models. This is why you're getting kneecapped on Cloud right now, because it's a compute issue. They have a lot of smart people and they hire the best, but it's nowhere close to the amount of compute that they need and are spending and are subsidizing. The next stable coin that's going to be created is going to be related to AI. I call the next great one, Tether. was originally obviously with the perps winning circle with DeFi being the great pair. The next one's gonna be related to AI without a doubt. And if it's related to AI, it's gonna be related to compute. Our thesis is, agenda commerce is thinking about it incorrectly. Like it has to connect to compute because that is where the money will be spent. Our theory is that if you can lower the number one cost that is controllable in compute being the debt. you may be able to create the next stablecoin, which is the best way to subsidize for why compute costs are so high, because the debt related to is expensive. ⁓ So if you can expand the credit correctly, I think there's another business model after you build the loan book, which is creating the settlement layer for all of rental contracts, all for the debt contracts, all for all of compute itself, ⁓ which I think a lot of people kind of don't see as a business model. is what we see as something we want to do in the future. **Gabe (42:58):** Got it, got it. And are you guys seeing yourselves as a stable coin, especially like with the Genius Act and some of those other regulations? Like how are you navigating that for these instruments? **David Choi (43:13):** This is why we work with PayPal and that's why our backing is on PYUSD for USDA, which is in no relation to any GP loans at all. ⁓ Or I mean, it's not exposed to the risk, but the yield generated from that is then ⁓ used to help subsidize ⁓ our counterparties in terms of their compute costs to some degree, if they are using that currency to settle in it. ⁓ PayPal I think is I mean, they're, they're FinTech, but they're also a great group of lawyers, probably number one in Silicon Valley. And they know what they're doing there. ⁓ But I, what I think with the Genius Act is interesting. ⁓ I think a lot of people focus on the Genius Act and clarity, but I think what they miss, at least for us, is the one big beautiful bill, which is like the introduction, introduction to bonus depreciations for our borrowers. That's our favorite bill out of all three of those. ⁓ which makes it very interesting to, I ⁓ mean, this could be the one of, this is in some ways ⁓ a tax efficient, a tax ⁓ optimizing ⁓ stable coin to some degree as well. ⁓ But I'll give you a use case of what we did recently ⁓ of like how we used USDAI, which is just one-to-one to PYUST by the way. ⁓ to lower the interest rate of one of the loans that we did. So one of the loans that we did, we required three months of debt service reserve account, which is just like, you if they miss a payment or two, can always draw from this account to cover up. It's kind of like, just like a rainy day fund. And we forced them to hold it in, we didn't force them. We like give them the option to hold it in **Gabe (45:00):** Yeah. **David Choi (45:09):** ⁓ USDAI, but, if they did, could lower the interest rate from 12 % to like 11. And they always say yes. and this is a company that has never even, ⁓ never even used a wall before, right? But they didn't have a treasury management system. They didn't, they didn't, they didn't have some guy to manage the treasury like second by second against, ⁓ all the cash they're holding. ⁓ so like, yeah, I mean, we'll just hold in USDAI and, ⁓ we would take that 11%. ⁓ So that's just like a clean use case of how we were able to use USDEI and SUSDEI to effectively lower the interest rate of compute. But yeah, that was just an interesting use case there. **Gabe (45:53):** Interesting interesting. Yeah, recently we had ⁓ Chunda from from Paxos Labs actually and Paxos is labeling or is is supporting the the PY USDs and then you guys are working with PY USD so our PayPal USD rather and Like even just on our show specifically. We're seeing like this composability of Services come come together ⁓ Literally within a couple episodes. I'm curious for you. This insurance piece has come up is basically what you're what you're talking about now ⁓ Are you seeing people building this insurance product? Is this something that you guys think you need to take on? ⁓ Yeah, how are you looking at this this this insurance piece and almost covering, you know the loan paybacks and etc **David Choi (46:45):** Yeah, the insurance fees was created. It was like in collaboration with Barker. It didn't exist in the world before we kind of did the first POCs and made it feasible and work with Barker, which did a back-to-back policy with Mean Agree just to get a place. But that was just one of the things we were going through with the obvious proposal. Initially, we were rejected because of some risks in the way we did the tranches risk with Filo, which is first loss. ⁓ We realized that they covered the entirety, not just 5%, but the entirety of the loan book. ⁓ So we worked with the Barker team to create something that ⁓ would meet the standards of ⁓ more institutional depositors. ⁓ And I guess what the common risk was, like, if you were a depositor and if you didn't understand how depreciation worked for chips, the obsolescence risk, ⁓ you're going to price it at a much higher BIPs than ⁓ what a professional would, right? Be like, it's probably like another 500 bips of risk per, ⁓ I think Tom Rees did analysis of what the real rate should be. And he just threw numbers because he just guessing. ⁓ But unless you actually price the risk, which is what we did with ⁓ Barker and Munich, ⁓ it's like we had to price the risk for them. It ended up being like around 75 to 150 bips. ⁓ Because given our aggressive ⁓ loan amortization schedules, they priced it pretty low ⁓ because they were looking at the data and the risks associated with them. ⁓ And now if I was doing my personal money, I probably wouldn't even take it because I know the amortization schedule that I'm doing is extremely aggressive. I'll definitely take catastrophic risk, but in terms of value insurance, yeah, like, I don't know if I'd take it, ⁓ I have like, should, USA protocol should because ⁓ selling a yield product, That's trying to show scalability. ⁓ So I think it was a great ⁓ innovation that we did in turning GPUs into a NASA class. **Gabe (48:50):** Nice. And just before we wrap up here, ⁓ at one point you were talking about internet capital markets and internet money markets. And if I'm not mistaken, I think you're not a fan of internet capital markets specifically. Can you kind of maybe clarify that and give your take on these two different framings of ⁓ eventually this class? **David Choi (49:16):** I am a fan of Internet Capital Markets. I'm not a fan of the people that ⁓ are defining it, are trying to put it for like, being coins. yeah, like things that are generated on the Internet. To me, like Internet Capital, like the word capital means that has to be productive in nature. Like things that are like actually created from, I guess, Internet and can be used and more effectively like ⁓ be productive, which for me is like cash generating. ⁓ And that's when you can actually have true ICM. ⁓ But right now, most of DeFi is ⁓ money market like. I mean, there's this entire era of like, say, Eigen layer restaking. then people are like, it's going to be productive. I'm like, and it wasn't. Nobody actually used restaking for anything. It's just money. It's just wrapped money against wrapped money, getting loans against money. ⁓ It's just unproductive assets. It was just margin. ⁓ So I am hopeful that it will come about. It's just like, ⁓ What are you actually giving loans to? ⁓ Is it making money? If it's making money, ⁓ I guess instead of calling it internet capital markets, they should just call it fixed income. ⁓ Like why does a business take fixed income? Well, it's because it's generating revenue and it doesn't want the volatility of floating rate. So wants to borrow at a fixed rate because it's a tractor and it has a farm and it makes this much revenue a year. And it's very confident that it can scale. ⁓ I think right now people are comfortable floating rate because nothing's productive. ⁓ It's not a capital market. It's the using floating rate because it's just arbitraging inefficiencies across market. So I'm hopeful for the future. ⁓ I guess I just didn't like how people are using it because they didn't understand the etymology of the words they were using. **Gabe (51:07):** Yeah, and that kind of goes back to your just original thesis in general is, you know, these need to be productive assets and assets specifically that are generating revenue that can be underwritten. Do you think that only exists off chain or do you think that there's also opportunities potentially on chain? **David Choi (51:28):** Yeah, I think there are opportunities on chain. It's just asset selection is pretty important. And I'm trying to think of what another good, interesting market would be. I'm just so biased because I like my project so much. So I always say GPUs. I think what you're with hyperliquid, like what you saw with pre-markets is like technically an asset class because it's creating something that is not really seen in traditional markets. If it's all something that existing financial systems can't create, that's just a great wedge into like building the other stuff. ⁓ And I think ⁓ that's when you can really build out the markets around it. But just by taking assets that have better counterparts in traditional markets ⁓ usually means that the product shouldn't exist. It's like, yeah, just a deeper market off chain. ⁓ Why bring it on chain for like 5 % efficiency? ⁓ So it's usually when you can really, really have a zero to one moment. ⁓ But I know it's kind of a cop-out answer. It's hard for me to create analysis outside of the product that I'm ⁓ Yeah, so OK. I guess I'll give that question a pass. I don't have a good answer for that. Yeah. **Gabe (52:55):** Fair enough, fair enough. Well, yeah, David, thanks for coming on and appreciate talking about all this stuff. And yeah, hope to have you back on soon. **David Choi (53:04):** Thanks, Gabe. Thanks for the fun questions. **Gabe (53:06):** Yeah, likewise. See ya. --- # Why AI Agents Keep Failing > Shoal Signal episode. Guest: Gabe Tramble (solo essay). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-05-18 - Video: https://www.youtube.com/watch?v=dLHQEC8Zglc - Canonical: https://shoal.xyz/research/episodes/why-ai-agents-keep-failing/ - Keywords: AI agents, MCP, AI & Agents, interviews ## Transcript **(0:02)** I'm running a hundred agents. Okay, but but how could you possibly be running a hundred agents that are that does anything productive when really you just banked without any context? That doesn't mean anything. It doesn't make any sense, right? What about I went to the river bank? That implies that I'm at the river, right? On the bank. But then what about I'm going to the bank to deposit money. What I'm trying to get at here is the way that you know what I'm talking **(0:37)** about is dependent on the context. Ultimately the context matters here in understanding the meaning of what is happening. This is not only prevalent in language but also for agents to understand operations. Agents need context and it's not like you can just open an open AI or a clawed product and then it starts doing all the little things. Understanding context is a really complicated problem and it's not enough to just show this file here and show this file there. The context needs **(1:13)** to be worked into the actual workflows themselves. And this is made possible through stuff like MCPs or model context protocols. A model context protocol is a way that you can connect external tools or external data to your agent. An agent being like a cloud code or codeex, any of these tools that have a model on top of what we call a harness. A harness is basically a rule set of instructions that a model can use. We'll get into that stuff later in a different video. **(1:48)** But the whole problem here, it's not how can we get agents deployed. It's not how can we get the agents to do these workflows and do all this crazy stuff. The first problem that I'm seeing that is not being addressed is how do we get the agents to understand context? And I'll give you an example. If you're opening an email, to understand that a email is spam or if it needs to get pushed into a certain folder actually requires a lot of thinking, right? That **(2:18)** there's a cognitive process that occurs when you're doing this stuff. And you really just don't you don't internalize that you're doing all these computations. It's just second nature. You know what a spam message looks like. It's pattern recognition. You know what spam looks like. You know what an important message looks like, right? But how does the agent know that the person that you met in person on Tuesday said that they'll send you an email? And how **(2:44)** does the agent know that you met that person? That's context. So, there's tons of workflows that structurally work well, but break down because the agent doesn't have the information to execute the decisions. We're past the point where the agents need to kind of figure out, okay, is this possible to even do? Can the agent even do these types of things? And I use the a the word agent very loosely here, but we can define agents as AI models with instructions. **(3:16)** Okay, a model with instructions that can do stuff, not just chat in a chat box, but can actually do something. Okay, so this context issue can be heavily solved by connecting external data. And usually this can be done through like an MCP which I explained before or other types of APIs or connectors. The point here is the context problem once solved unlocks all the crazy automation stuff that an enterprise or small business or an individual can do. So another example of **(3:50)** this is if you're going through your email and you're like, "Okay, well I want some agent that can look through and sort my emails." Right? The email sorting process actually is heavily reliant on context that we internalize. A way that you can think about this is if you offload this task to a human, how many times would they come back with questions, right? And how do you set up a system? The the goal here is how do you set up a system where every time a **(4:18)** real human would come back with a question, oh, have you talked to this person? Do you know this person? Do you think this is spam? Those can be solved by skills and connections to context or data sources that have all this information about your company, business, etc. So, a lot of the dayto-day stuff that we see online is is about agents and I'm running a 100 agents. Okay, but but how could you possibly be running a hundred agents that are that does anything productive **(4:48)** when really you just need one? You could do a lot of damage with one agent that understands just who is in your business pipeline, how many people are in your business pipeline, and you set up a skill that can look at the business pipeline, check the emails, and then give recommendation for stage updates, right? So, if you have someone that is in a prospecting, right? You just talked to them and you're prospecting and then you check the email and they replied **(5:12)** back. They said, "Hey, yeah, let's set up a call." Bam. the agent can automatically infer the state change or the the the position of the deal, the state of the deal by looking at the context in the CR. So really there's tons of opportunity for context management systems. The the state what what is the state and how do you the the skill and the goal becomes how do you externalize the state so that the agents can look at the context run an automation and then eventually **(5:49)** perform the action all on its own. And this is why I'm such a big proponent of MCPs because you don't necessarily have to build your own CRM. The savvy SAS companies that have spent tons of time doing design decisions like linear or or a CRM. A linear is a product management application. They put all this design philosophy and elbow grease into product management so that you don't have to. So in the future I see businesses are still using these SAS products. The SAS **(6:25)** products become somewhat commodities because the user interface becomes less important. So you can kind of commoditize the services and and that is a problem that these service providers are going to have to play. The commoditization of services is is something and is a risk if you're running that that business line. But for the operator who's not distributing these types of businesses, a tool, then you really can just select, okay, I'm going to grab this tool. And you're not **(6:55)** necessarily interfacing with the user interface to update the state. the agents or manual pushes from your your your coding agent can update the state of the CRM of the email or any type of database or a notion instead of you doing it. So this kind of opens up a new way of interacting with SAS products that I kind of see in the future, which is you have this orchestration command center that basically can touch all the different SAS products that you have **(7:29)** subscriptions to and they spend the design decisions on, you know, what is the schema of a CRM look like? And the the structure the structure is what you're paying for. you're paying for the design structure and the rigorous testing that they put into like what the best product management tool is. Let's say like a linear and then what you're doing is orchestrating between all those different tools as context for agents to perform tasks. And if you think of it **(8:00)** through this lens, then you can start seeing that you kind of don't need a 100 agents. the the benchmark doesn't become I need a 100 agents running around. The benchmark really becomes how much context have I pulled in and how much externalized information do we not have supported, right? Maybe and and then you set up workflows for these things like inerson calls. Maybe maybe you had an inerson call and you have some type of recording device so that you can **(8:31)** immediately move that into your context system because the context will allow the agents to perform better because it understands the disposition or the positioning or the state of a business, an individual or an enterprise. --- # New Media in the Age of AI: TBPN, OpenAI, and Media Defensibility > Shoal Signal episode. Guest: Ashley Christenson. Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-05-14 - Video: https://www.youtube.com/watch?v=dDzn380SwJE - Canonical: https://shoal.xyz/research/episodes/new-media-in-the-age-of-ai-tbpn-openai/ - Keywords: interviews ## Transcript **Gabe (00:01):** So Ashley, why did OpenAI acquire TBPN and what are they after? Is it the IP? Is it the trust? What is the actual reason that you think that OpenAI went after this media company? **Ashley Christenson (00:14):** Yeah, I think we've seen a lot of takes come across the timeline, probably more than is realistically necessary. Sam Altman himself said that one of the reasons he wanted to acquire John and Jordy was because their ability to market and build trust for a technology that as of right now, the average person is quite critical of, quite skeptical of. would supposedly be helpful in Sam's journey as he is bringing open AI and artificial intelligence more generally to the masses. I think that that's probably part of it. I think yes, John and Jordy are good at marketing. Absolutely they are. But part of this is also just the network that the guys have been part of for so long. They have been in various startups, knew Sam Altman before, so these are like very well connected guys. The show also has a bit of a novelty component itself because we haven't seen a lot of live tech shows specifically that have been able to attract the caliber of guests that John and Jordi have been able to attract. We've got CEOs of the most major companies that are joining, I mean, every single day to have some of these really insightful interesting conversations and sometimes you get to see a unique perspective of these people that you haven't been able to before. There are live tech shows that have existed before TBPN, but they did it at a scale, at a production level, at a level of professionalism and also entertainment that I think hasn't really existed, of course, with the network that they have access to as well. So I think that is also one perspective. of it, they go deeper with the show as well. So they've got merch and a Discord server and they're building community and they've got clips and so they're kind of utilizing almost this new flywheel effect that while their audience is quite small and niche, will likely be able to grow the show and is a part of the reason why they're able to command like 30 million in sponsorship dollars within a 17 month timeline. That's absolutely awesome. **Ashley Christenson (02:41):** astronomical. So it's a combination of like value of the show, the niche high value audience that it attracts and having access to the network in addition to the the format being quite unique and done at a different level that hasn't existed before. **Gabe (03:04):** Got it. Good. And I think people would argue like amongst the AI companies, probably OpenAI is the one that has one of the larger trust issues across the board. So you're basically saying it's a bit of the network, the trust, and then this novelty, almost like attention. So are they after this trusted attention? maybe can you narrow down what is, and maybe it's a combination of things, but maybe in like a couple of words, like what is the core thing? **Ashley Christenson (03:31):** Yeah. So. With live content especially, in the 13 years that I've been within this content format as a strategist in this industry, one of the things that I have realized is live is the best trust and relationship development tool that exists because it breaks down the barriers between the host and the audience in a way that allows you to see somebody's reactions in real time. There's no hiding whenever the broadcast is live. There's no clipping something out and removing it for later so that it's completely efficient for the narrative that a company is trying to build. So there's a level of trust that you're able to generate with live content that doesn't exist with recorded video or podcasts even. But one of the takes that I haven't seen as far as why this acquisition happened is enterprise. So OpenAI, Anthropic, all of these LLMs, really the only way that they're able to sell the amount of tokens required to keep up with these massive valuations is by negotiating really large enterprise relationships. And every enterprise is on TBPN. Every single one of these Fortune 500 CEOs wants to show up on this show and now OpenAI is in front of all of them. So potentially there is an enterprise network that John and Jordy are able to get Sam Altman in front of as well. **Gabe (05:02):** Interesting. Okay. And how do you maybe predict them actually putting this into practice? Is it through like just logo or like how do you think they might kind of work in OpenAI in a way that doesn't almost like dilute the editorial lens, but you know, I can kind of achieve its goals that way. **Ashley Christenson (05:22):** Yeah, that's a good question because I don't know. I don't know how you talk about OpenAI without actually impacting the trust that you've generated on the show so far. think that it is gonna have to be impacted because you don't have, for example, the sponsorship, the ad reads that you had anymore. And those were actually kind of a cultural moment for the community that consumed TBPN's content. They seem to really enjoy them to the point where now they're kind of reminiscing on the advertising era and they miss some of the ad reads. So there's that aspect. There's also just the fact that people know this is OpenAI's show. And while Sam Altman can say they maintain full editorial independence and they're allowed to push back and pressure OpenAI on anything, what is realistic might not be the thing that is said publicly. I don't know what their, I don't really know how their content develops from here. I hope that it stays as trust generating as possible because that is ultimately how OpenAI gets in front of these enterprise companies and then can negotiate these longer term deals that help them. **Gabe (06:50):** you **Ashley Christenson (06:53):** I hope OpenAI is able to stay high trust with this audience so that they can negotiate these longer term deals so that their business is actually viable long term because they've done a lot for us and ChatGPT Images 2.0 is helping me make much better YouTube thumbnails so more of this please. **Gabe (07:18):** Yeah, and on that vein, it seems like right after the acquisition, we just stopped seeing them. there's been a lot of speculation. It's because of the lawsuit between Elon Musk and OpenAI. But I'm curious to hear your thoughts. What do you think is the reason why we potentially haven't been seeing them? **Gabe (07:42):** Sorry about that. me... **Ashley Christenson (07:44):** You're good. **Gabe (07:49):** Someone's calling me. **Gabe (07:53):** Yeah, I'll ask that again. Or actually, yeah, yeah, let me ask it again. So why do you think we haven't been seeing TPPN on X as of later? You know, there's kind of been this speculation around the lawsuit between Elon Musk and an open AI kind of throttling the visibility. I'm curious to hear your take on that. **Ashley Christenson (08:14):** Yeah, yeah, some people were talking about a shadow ban, very speculative, but the reality of this is that especially with live content, anytime that there is a major headline, it's very natural to experience a viewership attrition after that major news. And even in marketing in general, you kind of have like peaks and valleys when you have major headlines or this like major inflection point of mass awareness and attention that you've never experienced before, that doesn't just create a new baseline for you to operate from, or like in perpetuity. It's something that it still shifts and adjusts over time and you're going to have valleys just like you're going to have the peaks. So I don't think that it's a speculative, know, Elon Musk digging his little dirty fingers into the algorithm. I don't think he even has much visibility into the algorithm itself or potentially even as that involves with X right now, think Nikita Beer, X's head of product, is leading a lot, but even he doesn't get involved or work on the algorithm at all, so he also doesn't impact the visibility. I think more likely what happened is a lot of us consumed TBPN for the maybe 48 hours that that news was hot, and then we moved on to the next thing, and that impacted their reach, and that's just very normal. We have seen a recovery of TBPN content on the timeline. It could be a result of everybody saying, hey, we're not seeing TBPN as much. What's happening? And so more people go and check out what went wrong with TBPN. And so then their content starts surfacing more in the algorithm. So I don't think it's this insidious thing. I think it's just normal human behavior. **Gabe (10:09):** Wow, okay, so it's almost like a narrative climax and then you can't really go up from there. So we have this like attention trough and that's your theory around why we haven't been seeing them. Do you have any other examples like off the top of your head, maybe this something like this occurred and maybe a traditional media or even other agencies or, know. **Ashley Christenson (10:22):** Yep, exactly. **Ashley Christenson (10:34):** You know, I don't know if I have an example that would be similar to the live show that John and Jordy have, but I've led marketing in close to 60 different startups. And anytime that we have a large press release or a large announcement, there is a very natural peak in attention. You acquire some customers and community members as a result of that. But it... Like I said, it doesn't create this new baseline where all of a sudden you have a lot of people who are paying attention to you because they saw a big publication talk about you. It's more like, okay, here's a boost in trust and credibility and people are gonna check you out, but it's not necessarily a... enough of a forcing factor to keep people checking in consistently, that is still a result of good content and good marketing over an extended period of time. **Gabe (11:37):** So these reps, you think the reps of live streaming and trust is how you kind of cement the baseline of attention for these types of audiences. **Ashley Christenson (11:47):** Yeah, absolutely. **Gabe (11:49):** And on that piece to kind of switch around a little bit. So MTS was launched recently by A16Z. I'm curious to hear what is your kind of takes. I think you've said they're still finding themselves, but what separates an MTS versus TPPN if someone like A16Z has all these resources, maybe arguably the network reach similar to TPPN in some regards? Why have they just not **Ashley Christenson (12:03):** Mm-hmm. **Gabe (12:19):** showing up in the same ball game really. **Ashley Christenson (12:22):** Mm. Yeah, so I'm doing some work with MTS actually, I can give you, I haven't announced that publicly, but I am working with the team and as of like two days ago. So I have some probably additional perspective that I can give here that I couldn't before. So with TBPN, they have of course, 17 months of timeline and that's 17 months of a team that from what I have learned, And it goes pretty hard. I have heard people almost call it like an Elon Musk company. They work really hard. They get a lot done, long days, very fast pace. And when you compound that over 17 months of a show with that level of pace and attention and dedication from all of the people who work at TBPN, not just John and Jordy, but like Ben, the producer, and Dylan, the president, and all of the other guys that work at the show. there is just a level of production like problems and programming issues and guestbooking and processes that you have created together over that level of time that MTS doesn't have. **Ashley Christenson (13:45):** that yet. Because MTS has only existed for a couple of weeks now, it just needs more time to cook, honestly. It just needs more time to cook. I also think that the identity is a little bit different. So TBPN is very advertiser aware, very much going to do things that, well, previously before the acquisition was like brand safe. So one of the things you have to think about with content is who makes sense to advertise on this, assuming that you want sponsorships as the monetization model. There's also crowdfunding and other ways that you can make money from content. So they would stay away from certain topics like religion and politics, whereas MTS is not scared to go there at all. They're definitely OK with more political based shows even if somebody like Mercury or R.A.M.P. may not end up sponsoring the show as a result of that. They also are doing things like investing into production and getting a studio and like right now they're just working in the basement at A16Z so it doesn't look like a high level production. But it will over time. And the team is also moving very fast. I would say probably not as hardcore as TBPN, but the show runner that is working on this, one of the full-time team members, previously worked at TBPN. So there's a similar feel and a similar pace to it as well. So I think the show is going to improve a lot over time. They need a little bit of time to get it there. they didn't launch with the show in a perfect place and to be honest you kind of shouldn't launch live shows like that anyways. One of the things that... **Ashley Christenson (15:47):** you have to do with content is you really have to just ship it and make, you know, 1 % improvements with every single new piece, whether that's live or video or short video. it's very difficult to make a, a perfect product. Maybe you can do that if you, you work with people who, you know, are very experienced, have been doing it for decades or agencies, like launch videos are a good example of this, but especially with live. **Gabe (16:16):** Mm-hmm. **Ashley Christenson (16:17):** It's something that you kind of co-create with the team in addition to the community that's building it and the the discord server for MTS like sources some ideas for the show So it's just something that naturally builds over time. It's much better to ship and make improvements than it is to to wait and like lose the the relevance of the moment and I think that's something that from my My perception in A16Z tends to do pretty well as they're very fast and they launch whenever the moment makes sense and they make improvements over time. **Gabe (16:59):** Yeah, this is a little bit more of a maybe like an abstract, but what I'm understanding is there's like an operational proficiency that TBPN has put together and just refined and compounded over and over and over time where MTS is basically building up this institution, right? Like TBPN is this institution that's well-oiled and then we can see the compounding effects. Is that enough or? Do you think also kind of like the shine, and I don't mean to steer your answer, but kind of what I'm thinking is TBPN has this shine on it that I think people really resonate with, which is maybe more or less culturally. Do you think that this operational efficiency is all it takes along with a certain format and then you can kind of just build up the content from there, or is there kind of like this additional piece that, How do you weigh these? Maybe there's a better way of going about it. **Ashley Christenson (18:00):** Yeah. Yeah, good question. I do think that operational efficiency matters because there are things that whenever it comes down to process, process does impact the product of the show. If you get into a situation where let's say you're not as efficient before the show goes live, guests aren't prepared, hosts aren't prepared, cameras or like production quality isn't what it could be and that could get in a host's head, that could be distracting. So there is something to be said absolutely for process and how it can make a show more comfortable for everybody who is involved so that they can put on the best show possible and not have to worry about, I don't know, looking into a camera that's like shutting down and flickering or they can't see chat or, you know, whatever issues they might experience while live or like even being able to ask better questions inside of an interview. There's a whole pre-production process that has to happen in order for interviews to be as successful as possible, as you know, because you did it for this conversation and all the other ones that you've had. You're right that there is a shine on TBPN right now that doesn't quite exist for MTS. Part of that comes down to format. A big thing that I'm talking to the MTS team about right now is like, who is this show for? It's okay if we want politics and we want to talk about tech and business, but is this like your... **Ashley Christenson (19:36):** your, I don't know, terminally online ex-friend that you're just kind of looking through posts with? Or is this a VC network that's highlighting, you know, founders who are in a raise or they're building out more content so LPs will dedicate more funds to them? is this show a... Just like, what is the overall identity of the show? And... Sometimes people have a very clear vision for what it is and sometimes they don't. And when they don't, you have to bring the entire team together and kind of build out what that vision looks like. And sometimes you get to that vision over time. The more that you ship, the more that you find out what works and what doesn't work. And then you make those improvements. So I never say that a show or somebody who's launching something live or even if it's just like a produced recorded podcast, nobody should try to direct copy TBPN, I think that can't work if you're in like a completely different niche. You can kind of emulate the same format because it's TBPN's format is not unique either. It's like Sports Center but for tech and business. So we can apply that to lots of different categories and industries. But if you're playing in the same industry as TBPN, you want to adopt a different format and there's lots of different formats that we can experiment with. We could have cooking shows or tech and business travel shows. There's somebody who's doing a tech and business cribs show, which is breaking down people's so that you can see where they're building their startup from. You get to see their computer and their desk. There's reality shows, Judge Judy for tech and business. There's a never-ending list of things that we can create. And it's really exciting, because tech should be fun and interesting. And we deserve fun content, too, just like they have in the traditional entertainment industry. **Gabe (21:51):** Yeah, yeah. We've seen this TPPN model kind of replicate like numerous times. It seems like it's the same industry, right? Or like X, right? X supports politics, finance, crypto, tech. And then it's almost like geo-located. Like we have TPPN in Europe and then we have like the New York version and then we have the original and we have the VC version. for these formats specifically, do you think that the Sports Center model is inherently better for the tech industry and that's why it just caught fire? Or do you think that it was just applied, like an operator just took this model and applied it in a way that made it extremely successful? **Ashley Christenson (22:38):** Hmm. Yeah, I think that we... I do think that the Sports Center model makes a lot of sense because you're covering headlines, you're getting other people on the show. But even then, there's a lot of different formats you can use to arrive at a similar value prop, even if it's not Sports Center. So I don't think that it's the Sports Center model specifically that maybe the show was successful or made it valuable. something that we can apply the same value that people get into other formats. **Gabe (23:26):** And so for the format. I want to understand, do you think, because for creatives, you know, this content creation is definitely literally creative, right? It's art. Do you think that there's like a data driven approach to come to a successful format and a successful show or some type of media presence? Or do you think that's almost more like artistically intuition driven? And like, how do you kind of see those two camps? **Ashley Christenson (23:59):** Yeah, man, that is so fun. That's such a fun question because there are like when you look at the the creator economy and like content in general, there are kind of two different types of people. Well, there's there's actually an entire spectrum of people. But if we look at both sides of the spectrum, you've got like the hyper business, high business acumen strategist personality, personality types like myself. And then you have the high artist, like creative personality types and they care more about personal expression and creating art that has emotion and meaning. And so you can lie kind of on, you can lie anywhere on that spectrum. But those, if I had to categorize the... the, you know, each side of that spectrum, would kind of be those two personality types. And I think in order for content to be successful, if I'm being completely realistic, you need both. And artists that are listening to this will hate me for saying that. Generally the true, like, real artist does not love the business side. They just want to make art and not have to think about making money from it or getting views on it. They just want to make the thing that they love, the thing that's inside of them and have the, you know, organic traction and growth on it. Unfortunately, as the internet becomes noisier and noisier and everyone's competing for reach and reach for everybody goes down as a result, which we're seeing on Instagram reels, for example, artists are going to have to think more and more about what makes the content that they're creating valuable and interesting for people if their goal is to get views on it and to monetize it. For some people, it's just a hobby. **Ashley Christenson (26:02):** They just want to like make the thing and not have to worry about anything and if it grows cool if it doesn't they don't really care I thought the percentage of people who are honestly okay with their stuff never growing. It's probably very small. think at our core all of us want to be recognized for the things that we care about and the things that we put out into the world, especially when it's something that's so important to us. And so that's where the business side comes in, thinking about distribution and reach and how you get content in front of people, how do you package it so people care about it? How do you monetize it? What's the model behind it? Who's the team? What are your resources? What do you have access to that other people don't? So I feel like they are both equally important, but I might even put... I don't know if I can give you a percentage of which one matters more. Those are the two, because as I'm, I'm observing what's happening with AI, of course, the business side and getting reach in a really competitive environment where everyone can post 500 TikTok videos a day is so important. But I also think that the content that resonates, the stuff that performs really well is the stuff that's more creative storytelling based artistic. human emotion versus, you know, top five tips for whatever, you know, the topic is of the video that you're creating. So I think that they're both important and I don't know if I could make a hierarchy there. **Gabe (27:47):** Yeah, I kind of come to the same conclusion, especially just listening to you talk about it as like another outside perspective. It's almost like they do different jobs. And maybe they're not apples to apples in terms of the value proposition. So maybe you make good content, but you don't have any distribution. or you just do all this data-driven approach to understand, OK, what is the best content that is populating? But then you almost can kind of just fall into the algorithm. And now you're kind of maybe devalued, even though you're in the trend, unquote. And then also AI basically collapses one side of that. And it's kind of leaving this creative piece as where value is moving towards. So yeah, I'm curious for you, is that what you're seeing or how are you looking at the effects of AI that's potentially collapsing the data side or the operator side and where it's leaving the value to be held? **Ashley Christenson (28:52):** Yeah, interesting. I do agree with you. think the... the ops and like data, a lot of that can be done by AI now. So we have various tools that can tell us, especially on YouTube itself, which is really fascinating. You can go to YouTube studio now and they will give you a breakdown on your video. As long as it's been live for a couple of days, they will actually tell you, know, here's what the comment said and the recommendations or the requests that your viewers had. Here's what we're seeing in in your view charts, based on the graphs and all of the data that YouTube gives you, here are the top three or four things you should keep in mind for the next video. And so that is incredibly helpful because when I talk about improving content 1 % every time, YouTube now tells you how to do that directly. Previously, you had to kind of decode that yourself. which a lot of creators, especially more like entertainment or artistic creators struggle with because they don't really care to build up like the business acumen or the marketing skillset. They just kind of want to publish more stuff and hopefully get it in front of more people. So that's a massive value add from AI, even just in a single YouTube feature. That's not counting everything that you can do with. Clawed chat and co-working code and all of the other tools like vidIQ, Tube AI is one that I'm using a lot. There's so many video AI tools that are helping us make a lot of these decisions now. I think with where value is accruing, I definitely agree. It's in the storytelling, it's in humanity, it's in relationships, it's in network. **Ashley Christenson (30:50):** So many tools now that can copy and paste really any content if I'm being completely honest. they want to, if people want to imitate what it is that you create, they can very easily do it. We can use AI to make content at a massive scale that we've never seen before. And so now a lot of people have been discussing taste, which I hate to say, because I feel like everybody has talked about this ad nauseum and it's probably such a buzzword that it means nothing at this point, but no. **Gabe (31:20):** I agree. **Ashley Christenson (31:20):** Knowing what to make when you have the ability to make anything is a thing that differentiates you in addition to think value accrues around people who can use these tools at a level where I talk about it as almost like being on the limitless drug because it's like you can create at a level that you couldn't before if you have some unique perspective. The problem is for some creators especially newer ones, there's not a ton of unique value that they can share that really comes from either having unique life experience or even just like a length of life experience and that that perception, that perspective that you can share on top of just, you know, here's the news of the day, which is content that I will make. But I give my additional perspective on top as somebody who has been in live content as a strategist for 13 years, who has led marketing around with 50 different startups, worked in a couple of agencies, worked with some of the largest companies in the world, built communities. Like I get to speak from that lens. **Ashley Christenson (32:47):** on position to give a completely unique perspective on things that maybe they didn't have the time to do before all of these tools existed so value is definitely around your unique lens and like what you can bring that can't just be given given as a response from Claude. In addition to I think community is something as well that I would like to see a lot more people talking about the importance of community. We're seeing a surge in IRL events, but we're also seeing a surge of interest in like private community spaces. People are retreating from the noise on public feeds. Adam Maceri, the head of Instagram, has said that Instagram has not been about the feed for several years. DMs. Like you get on Instagram to find short videos and send them to your friends or send them to your partner. And that's really what Instagram is. there's a there are a lot of different value adds in the AI era that I think are kind of reorganizing how we think about marketing and content and work in general. **Gabe (33:59):** Mm-hmm. You have like a really nuanced perspective of like identity and people and kind of this humanities piece, which probably is the most lacking in the tech crypto AI adjacent spaces. And I think one example that you talked about before is the AI fruit series and like the AI reality show series. Can you kind of talk a little bit about that and like your theory around you know staying power right and if if someone creates AI content and then it has no like attribution but anyways yeah I'll let you hop into it maybe if you can give like an overview so I'm not butchering it **Ashley Christenson (34:44):** Yeah. **Ashley Christenson (34:48):** Yeah, no, Yeah, so you're talking about Fruit Love Island, which went viral on TikTok. It was a single person using AI tools to create a Love Island version of fruit. Like, the characters were all fruit. You would see a banana who was falling in love with a strawberry, and it was really... It was really degenerate to say the least. were lot of adult jokes and that flavor that Love Island has. What was that? yeah, Devastatris, absolutely. And this content went so viral that each episode got, I believe it was over 13 million views. **Gabe (35:22):** Yeah, it's good match. That says debauchery for sure. **Ashley Christenson (35:44):** It was the fastest growing TikTok account of all time. went from zero to three million followers in like a couple of weeks. Absolutely massive viewership, cultural resonance. It wasn't just that somebody had created a show and a lot of people were watching it. It was that people were... showing community behaviors as a response to the content that they had seen. So they were making videos about the Fruitlove Island stories. They were bought in. There was user-generated content or like CJC is what I call it, community-generated content about it and it was completely AI generated. So that's compelling because there was no human face, no human voice, no real human person that showed up at all. yet people still enjoyed the stories so much that they would make content and were completely bought in. And that is something that I have not seen with AI yet, which I thought was really interesting because if AI has the ability to create these community level behaviors in an audience, is that is community actually defensible for us as humans? And I think that it is because this account was was removed after couple of weeks, I believe, it was shut down and then copycats sprung up and so we saw just a handful of accounts that were trying to accomplish the exact same thing, people talking about how it was shut down, but nobody thought about like the creator behind. **Ashley Christenson (37:37):** Fruit Love Island. Nobody really cared about the person. And the copycat sprang up and people started watching that content immediately. And there was no like mourning, right, for the original creator. There was no grieving. So I think the thing that differentiates us versus somebody who can create a ton of content at scale or like AI faceless channels, for example, one of the things that makes content defensible is the human behind it and whether or not people will actually care if you stopped posting. If you stopped posting and disappeared tomorrow, if there is anybody who would say, what happened? Where, where did you go? That is defensibility. That is community. That is someone who generally genuinely cares about you, not just the stuff that you create. And I think as we move into this era where reach becomes harder and harder to get, that building out community and having that relationship with people online, even if it's arguably a little parasocial, is really important because it creates a habitual experience in our viewers and our community members that... that preserves our reach and our attention even when everybody else is saying distribution is the moat and all of a sudden it's about how many eyeballs can you get on all of these vibe-coded products. So I do think that the human-to-human relationship is probably one of the most important things to focus on as a creator or a marketer in this reality. **Gabe (39:29):** Yeah. Wow. OK. Yeah. We got to unpack that a little bit. So first. **Ashley Christenson (39:33):** Fair. **Gabe (39:35):** I do want to make a comment, is I see the fruit content is very much like maybe video entertainments as memes and the way that it like propagates feels more like a long form meme. And then it just kind of evolves where maybe like generated, I was going to say human generated content. This stuff is generated by humans using AI, right? But it seems like a lot of this, maybe like conversation right is not a meme so the way that it travels and is a bit different so yeah no no kind of question there but kind of the way I'm thinking about that yeah **Ashley Christenson (40:18):** Yeah, yeah, that's a good point. Entertainment media does travel a lot further, but usually you see that like conversion on it is also a lot less than something that might be a bit more educational like this. **Gabe (40:35):** So basically you're saying defensibility here is going deep on, at least for this type of industry that we're in, the defensibility is going deep on the individual level. **Ashley Christenson (40:48):** Mm-hmm. Yeah. Yeah, I definitely agree with that and I think that's why we're seeing such an interest in live content right now. YouTube Live has increased, I think, 30 % quarter over quarter. and oh no I'm sorry that that stat was wrong it's 30 % of daily YouTube users watch live content. 30 % of the billions of people who are on YouTube are watching live in some capacity. We're seeing you know TikTok live had astronomical growth they they decreased like 12 % this past Q1 2026 just as a result of all the stuff that's going on with the government kind of spinning off this US version of the app. Of course, Twitch has been kind of flat for several years since the pandemic and they had this explosive growth on the platform. But we're also seeing interest in live shopping. That has, I think it's a 37 % annual growth rate. That is 19 % of total commerce in China. It's 5 % in the US. So we still have a ways to go. the upcoming interest in live shopping is going to be absolutely huge. We're already seeing TikTok Shop convert really well. think that's, gosh, it converts around 10 % higher than traditional produced video. Engagement is around 10x higher. Return rates are 40 % lower. And with... just general live content even more entertainment based we're seeing gen z and younger generations as well like gen alpha right getting more and more invested in it because you can kind of shift the content based on the viewing experience that you want to have so if you want something more passive you can turn live content on in the background if you want something more active you can get involved in the chat you can watch **Ashley Christenson (43:01):** larger creators and like be part of culture as it's happening that you know later on is gonna become a Forbes article or something. You can be part of a smaller community that's much more intimate where you have a group of friends who know you, who maybe you hang out with every single day. And so I view live content as like this. this human to human connection tool that you can't get in any other content type at the same level. Vlogs are kind of a similar value. you're able to get a sense more of a person when you see how they interact in their day-to-day life, but it's still not the same as being live with somebody and being able to ask a question in chat and see how they answer it or see what happens whenever their game crashes or they are... I know, out at a grocery store and they get recognized by somebody or like iShowSpeed recently did a stream underwater, the first underwater stream that I've ever heard of and that's really cool for people who are too scared of the ocean, right? He just went scuba diving in, I think, Ghana. Absolutely so cool, such a cool production. So I do think that that human to human relationship is crucially important in live content just kind of is, I think, the best format to create that outcome. **Gabe (44:41):** And to circle back on the, think you made an interesting point on the community piece, right? So these live streams are generating these really deep social connections for viewers. When it comes to the AI community piece, you said it might not be defensible versus like Speed, who just is deeply ingrained in his community from this live stream approach, which is like his personality, his being really is, was being. Can you just talk more about like the AI piece? Like why is, why might not that be defensible and maybe like the contrast is somewhat like speed. **Ashley Christenson (45:21):** Yeah, I think there is an innate human need to feel seen and recognized. And the ability for a human to do that for another human is huge. When we acknowledge each other, it feels... very cathartic. It feels like it matters because we're all human. understand the human experience and like the trials and the tribulations and the emotion. AI is not currently and maybe never in a position to be able to fully understand the complexity of human emotion. All of the little you know, the tone of voice, the very, very small, minute facial expressions that you make, the context of all of the things that you have experienced as a human and how those impact who you are today. I think that AI as like a relationship tool will improve. And there are absolutely people who are trying to build out like AI therapists. and AI girlfriends and all of these more relationship centric kind of technologies. But from what I can tell, there's just nothing that can really create that full sensation of the human experience, like talking to another person or being around them, IRL. just feeling seen by another individual who just absolutely understands who you are. And we need it so much that some people are trying to use AI for romantic companions. And we've all seen the headlines where people got way too involved with chat GPT. And then it created a sort of psychosis in them where they thought that they were maybe a much different person than is **Ashley Christenson (47:40):** realistic. So I think to me that that shows the level of importance that human connection has for us and that in the era of AI just becomes more and more valuable. **Gabe (47:58):** Got it. Excuse me. have allergies super bad. **Ashley Christenson (48:06):** Bless you dude, it's allergy season. **Gabe (48:10):** So it seems like there's almost like an algorithmic drift. without this kind of human course correction and content very much like can follow and does follow significantly this algorithmic drift. And maybe the value is in this person to person reality generation. And a little bit on this vein, like the AI basically allows you to produce content at scale, right? there's, AI is like a way that you can kind of enhance the quality of the production. in some regards. And then also like video quality, right, is another way of enhancing the production. You choose at a lot of times to like not participate in the high quality production. Maybe you record at like cafe or something like that. But it seems like you're almost doing that on purpose. know, is there some theory behind that or reasoning? I'd love to hear more. **Ashley Christenson (49:11):** Yeah, man. Yeah, I'm glad that you picked up on that because you're you're totally right. It is intentional. Part of it is just because when I'm sharing content, I know that the most important thing is that it just like fits into your life every single day and that you get something from it. Otherwise, you're not going to keep going. And content is really a longevity game. And my life right now is so chaotic as a result of this like TBPN and MTS stuff. I have so many meetings back to back and even getting me in this conversation was like such a nightmare for you and I'm so sorry. It's just that's what's realistic for my life sometimes. I have a seven month old and so filming from home can be difficult especially when she's teething. But I also do think that There's a couple of different things happening here that have impacted my perspective and why I value this type of format, very low production. One is because I think there has been just a, I think we've all been slapped in the face with like value, make valuable content, make content that's just absolutely perfect, hyper-optimized, Mr. Beast level of thought and like strategic time. that goes into each piece. And part of that is on the production side. It's have the most clear camera, but it's also like the editing and make sure that it's fast paced and kind of dopamine drip style. of production and I think there will always be a place for that. I think the hyper optimizers will always be playing that game. Some people just really love that game but I don't and there are a lot of people who don't love that game. I don't personally love watching MrBeast content. I'll do it if it's like relevant to my development of like my thesis and the things that I'm learning and if it's important I will. **Ashley Christenson (51:22):** but it's not my preferred style and it's just also not authentic to who I am. don't... I don't think about YouTube or produced video at that level. think much more in terms of community, real relationships, showing up as a real person, making people feel like they actually get to know me. And that is not well served by like hyper optimizing the content. So that's one aspect of it is the Mr. Beastification that everybody has been talking about for several years. I also think that there is genuine interest around just seeing somebody in their their native like day-to-day environment. It's something that I know, I just prefer to see this style of content that maybe is a little bit more vlog oriented, but is not, still not edited like a vlog because vlogs require so many different clips. Oftentimes there's so much happening. You have to like tell a story throughout the thing. I feel that it's more like, the story on my channel is... **Ashley Christenson (52:50):** the things that I'm experiencing that you get like a small peek into in every single video versus a single video itself being like this huge narrative arc. So there are just different levels that creators want to compete at. Some creators want to compete for that top 1 % production and they're all about best camera, best, you you know what I'm saying. And then there are people who want to compete more on scale posting a lot of content and just being there all the time. And then there are people who want to compete on authenticity and feeling like a real person. And I just genuinely feel like with where the internet is going. The way that my camera looks doesn't matter nearly as much. That's not nearly as interesting as my ability to give people insight into this whole streaming strategy space, new media as it's developing. That is the value that I can give is that unique perspective, that 13 years. And that's valuable regardless if my camera looks great or not. if I have, I mean the microphone is one place where I will not compromise on quality. But that's valuable regardless if I'm filming a video on my MacBook in the car or if I am using, you know, my Sigma lens and like my Canon setup. So I'd much rather go like fuss free and just bring people into all of the things that I'm seeing as much as I can. And of course still improve 1 % with every upload as much as I can. But I just want to be, yeah, I just want to be a real person. And I feel like more and more people want that on the internet now. **Gabe (54:35):** Yeah, wow, that's super interesting. It's almost, I think you have like a confidence that you have like a confidence range and then you almost can self-select because you have confidence in the distribution of the content in the first place, which is pretty interesting. **Ashley Christenson (54:52):** Yeah, man, I have felt like that too and I wasn't sure. for while if I was crazy or not, honestly, because I'm like, I don't think people care. think, you know, and I felt these things. And so I talked to Jamie Rastburn. He helps entrepreneurs build their YouTube channels. And we didn't do like a paid call or strategy call or anything like that. He just saw my content and he was like, hey, let's let's have a conversation. So we did. And I floated this idea to him and he said, Yeah, yeah, and he's the one who actually gave me the insight YouTube is best whenever it does something for you because it keeps you posting versus trying to strategize and second-guess yourself and is this the right thing? It's like just if you're feeling some way about content There are a lot of other people who feel the exact same way as you. And I know if that's the way that I was feeling, that there are a lot of other people who are feeling the same way. And I've only made three videos in this style so far. And maybe the thesis is wrong. Maybe it's not true that people are interested in somebody just spinning up a MacBook in their car style YouTube video and just riffing. I don't script anything, nothing. I just go for it. So, you know, it could be wrong, but I'm also comfortable with that. If it's wrong, I'll just make another YouTube video and say, hey guys, I was wrong. I'm going to try something else. I think that's kind of the interesting part about content too, is that you get to try things and like build in public in real time. And sometimes you're right. And sometimes you're wrong. And people can learn a lot from the mistakes that you make. And it's okay to make mistakes in public. think too many creators probably try to be perceived as like perfect. **Ashley Christenson (56:48):** smart, don't know, like hyperactualized individuals, which just isn't realistic. I want people to know I'm dumb too. I'm also stupid. **Gabe (57:00):** Well, that's hard to see in this case. Yeah, I think we can, from perceiving your content, I can tell there's like a carefree range that you can traverse and it seems like the most comfortable and like effective for throughput range is the one that you're sitting in. **Ashley Christenson (57:22):** Aw, I appreciate that, man. That really, that does, that doesn't mean a lot to get that, to get that compliment because I also wasn't sure. So the more that I hear that, the more that I'm like, okay, this is a, this is the right direction. Let's just keep going. **Gabe (57:37):** Yeah, yeah, no problem. And that actually takes me to my next question. know we're going a little bit long here. can wrap up shortly, but... To kind of like self actualize, guess, is a way of your or kind of sit in the comfort of being yourself. It's counterintuitive to like the information that we hear about these hyper strict algorithms like YouTube X lately, right, which we can get into in a second. And it almost seems maybe that we have a poor understanding of how the algorithms work. If this type of like personal, you know, I this, you this is the way I want to see it, so I'm going to do it this way. Probably more times than not is like not what we're quote unquote told or instructed how to post. So I'm curious, do you think this is the case that you're experimenting with it now? But yeah, like can you kind of just show up on any platform the way you want to for a long enough period of time and then the out like the platform will tune to you? Or do you think you can actually kind of be sent to the graveyard with the ways that show up. **Ashley Christenson (58:47):** Yeah, man, this is a really great question because you're completely right that, I don't know, we've heard from like gurus and educators. I don't want to be like an anti-guru person because I think there's valid education that's out there. But we've heard that, you know, these are all the best practices and these are the... ways that you should either make live content or YouTube videos or podcasts or X. There's just so many different tricks and pieces of information that people have shared over the years that we all, I think we all are at a place where we kind of understand what works and what doesn't. And sometimes not, sometimes algorithms change and things can adapt and they prioritize different things. But I'm a big believer that algorithms are just tools to surface the right content to the right people. I think that's true from everything that I've seen, from the stuff that I've researched. It's not that you're being shadow banned or there's this algorithm god in the sky who's determining who's allowed to be popular and who isn't. It's more like if you create stuff that resonates with people, it doesn't matter if it's perfectly formulaic or it's the the best format or production or whatever. Certain things can resonate. Lots of things can work. And I think with AI too, it's creating slop because a lot of us have been told what is supposed to work, yet AI still, like I said earlier, doesn't fully understand emotions or curiosity gaps. or hooks or the things that make humans actually care. And if an algorithm is just a tool to like surface the right content to the right person, then it's more about creating content for a person than it is creating content for an algorithm. The algorithm is just the thing that routes stuff to people. And so I think about it as if like, I'm speaking to somebody that **Ashley Christenson (01:01:08):** would find this information interesting. And for my content, there's kind of like specific groups of people that I have in mind that I create for. And that to me, I think is what, that is more valuable than... maybe structuring a post on X correctly so that you get like the highest dwell time on it, because the algorithm prioritizes that. It's important to know what algorithm's like, I think. It's always great, but sometimes you do make decisions that maybe it's not what the algorithm wants, but you know that it's something that people are going to like, and that's the most important thing. **Gabe (01:01:53):** So when you're making content, are you picturing you're talking to an individual? Are you talking to an audience? Do you have a visual representation of this? Because I think a lot of people maybe talk to the algorithm, and that might be the problem in itself. But what's your visual representation as you're posting on X or doing recorded content? Are you speaking to an individual, like a metaphorical audience, like a lecture? Can you take us through that? **Ashley Christenson (01:02:22):** Yeah. **Gabe (01:02:23):** bit. **Ashley Christenson (01:02:23):** Yeah, so yes, I have a couple of audiences in mind, which is has been a unique experience because usually you're told you want to only create for one group of people. You want, you know, one problem, one person, one outcome that you provide per channel. And if you're doing anything more than that, you should separate it out into other channels. And I do think that there's validity in that as well. But that's just not what my content is. And that's not authentic to my life again. I don't want to run like five YouTube channels to speak to five different audiences. whenever I'm thinking of the audience, one is small streamers, because that was my first audience that I created for and the topics that I talk about are still compelling for them because I'm sharing a lot of like platform news and strategy. The difficulty for them and the reason that I'm not going to appeal to like the largest group of small streamers possible is because if I'm not solely targeting that person then the the content is I'm not making decisions as far as title and thumbnail and the topics that I talk about that cater specifically to that that type of person if I was only catering to like the small twitch streamer or the small kick or like rumble streamer I would be much more likely to make content about like how to grow from zero to 15 viewers or I don't know even kind of drama based news. Something that that type of person tends to like a lot more aside from like they want to grow their stream and they want to make money. Those are their two major outcomes. So if I was trying to attract that person it would all be here's how to grow your Twitch stream. Here's how to make more money from your Twitch stream. stream or your Twitch community. That would be like the two outcomes that I would focus on. But as I started posting more on X and doing more deep dives into the... **Ashley Christenson (01:04:38):** like news, Mr. Beast using streaming or like TBPN or MTS and being able to bring this educational lens to it that nobody else has been able to. Maybe, maybe Devin Nash, if he was more kind of focused on these industries would be more interested in posting about this stuff. But. you know, he's more in like e-sports gaming category. So he's not covering nearly as much the tech and business headlines. So as I started making content on X about this, I started to realize, this is actually really resonating with a very high quality person. And that was founders of startups, investors, VCs, people in like big, big companies like guys at Anthropic, guys in creator economy startups, like the CEO of Riverside DMed me, one of the executives at the Huffington Post, the... Let's see, people at Yahoo Finance found me. There's just a very different caliber of person, more executive business oriented person that is now interested in this information. And so I create for that level of person as well, which means that I'm covering much more from the senior level, like strategic kind of thinking around, let's say frameworks, why live content works, when to use it, who it works best for, how to utilize it across industries. So I'm, I'm speaking to kind of these two categories of people at once. And maybe it would be more strategic if I separated it out this like B2B style content onto another channel. But in my conversation with Jamie, I asked him about this. I was like, is this a totally different category of person? Should I do a film booth? Ed, whatever, I forget his name. **Ashley Christenson (01:06:48):** but should I do what he did? He was a B2C channel. Should I create a B2B channel? He forexed his revenue as a result, even though his viewership is a lot smaller. And he was like, honestly, I have, you have this history of creating. content many years ago for small streamers and that actually adds to your credibility. So it might impact your viewership, but the story that this channel tells is really interesting. And I had felt that and to hear him say that I was like, okay, I've got a, I've got a YouTube guy in my corner that's telling me I'm doing the right thing. So let's just, let's just go for it. So yeah, to answer your question. Yes, whatever I am creating content, I try to **Gabe (01:07:18):** Thank **Ashley Christenson (01:07:36):** to think of the person, but it is a little difficult sometimes because I'm creating for multiple groups instead of just a single individual. And honestly, sometimes I don't create with a person in mind. I just make it because it's something that I am like... I don't know, theoretically interested in exploring, right? It's something that adds on to the thesis that I have that we've been talking about this whole conversation with live content being so compelling for people and human connection in the era of AI and all of these topics that I'm just so interested in exploring. Sometimes I create for myself too. **Gabe (01:08:19):** Interesting, okay. Yeah, creating for yourself is interesting because it's like self-entertainment basically. **Ashley Christenson (01:08:28):** Yeah, exactly, yeah. Yeah, when I make a post on X, sometimes I'm like, ooh, this is so fun. And I get to talk to Claude and go back and forth and tell it when it's wrong and say, that's a good insight. So like, I'm also learning as I'm making this content too, which is I've recognized for myself during my career. If I feel like I'm in an organization or working with a team where I'm not really learning anything, like if I'm the person at the top, this is also why I got really bored of being a founder. It's not as compelling for me and I just won't spend a lot of time on it because I don't feel like I'm learning enough. **Gabe (01:09:06):** Yeah. Okay, so can you put this into maybe like a loose framework where there's like this chicken and egg problem and this goes back to kind of like the data versus the intuition. Like, do you just study what works or do you kind of cultivate like this creative personality? They're hand in hand, right, for this type of situation. But can you give us like a framework of how to maybe produce content? Does it stem from this creative lens and then you apply the persona that you want to like talk to or how do you think through this because there's like a discovery that happened on Twitter as well it seems **Ashley Christenson (01:09:45):** Yeah, yeah, um, so I'll say with my ex content, there was definitely a time I felt like I was posting within this category and maybe not getting as much visibility as I am now. but it was a very short amount of time, if I'm completely honest. The original post, the TBPN breakdown that I did that, got me recognized initially. And then there have been other ones since then, like breaking down MTS or breaking down the Mr. Beast, flywheel. It really just comes from feeling like I'm in this weird position where I can share something that... gives perspective that nobody else can share on the timeline. Like with TBPN, was seeing, I mean, it's crazy to see a headline of this company was just acquired for $115 million and hey, it's a live stream. That's crazy to me. You know, that was a very natural fit into the things that I've thought about for a really long time. So whenever I did that breakdown and it was a really long post, usually long posts do not perform. for me so I tend to stay away from them but when I did that deep dive into it and I was like here's what actually happened with the TBP and acquisition. I think the framework is probably the history and like lens that I can apply so that's not really something that people can can utilize like that's not really tactical for most other people but there is something to be said for it was very timely that news had just been announced. It was unique perspective that I had seen some other people say this podcast got acquired and I was like, no, that's wrong. It's not a podcast. **Ashley Christenson (01:11:42):** There were people who were saying, it's just because John and Jordy are really charismatic guys. I'm like, no, that's wrong. you know, I think it's like taking, having a stance on something and giving a unique perspective in a timely manner on a topic that a lot of other people are talking about. And if I had to make like the trifecta of what makes my content successful right now, it would be that it, any posts that I have that's very timely. is topical. because you have things that are like news, if nobody is talking about them at scale, then it doesn't really matter. There was an Instagram post, Instagram feature that came out that I wanted to talk about, but nobody's talking about it. I'm, know, I could, I would share it. I would get like a little bit of engagement on it, but I don't really need to and I'm busy today. Anyways, sorry. So timely. the amount of people who are talking about the thing, and then the deep dive, the unique lens that I apply to it. And those three things are probably what makes it stand out versus some other stuff on the timeline. **Gabe (01:12:58):** Interesting. Yeah, I would say podcasts, I do not like the word podcast, like someone's like, Oh, you're podcast. I'm like, this is a this is a an environment to cultivate knowledge. This is not a podcast per se. You know, I don't maybe I'm just **Ashley Christenson (01:13:13):** yeah, okay, so you feel like podcasts kind of trivializes what you do. **Gabe (01:13:19):** Yeah, yeah, might. This might just be like a personal thing, but I do. **Ashley Christenson (01:13:23):** No, I definitely get it, dude. I get it. It's like you're, I mean, you're, definitely a good interviewer. can tell you, you've done your research and your, I don't know, your ability to like ask questions off of the things that I'm saying is really, you're, you're really, you're much better at this than I am. You're really good at this. **Gabe (01:13:48):** Yeah, maybe this is this hopefully this is my lane here so I think the the way that you it makes it easier for me because I think you have deep thought on a lot of these tracks and I and I don't necessarily know where you're go but I can kind of follow the thread of What's maybe important and kind of how you're thinking about this stuff? So that's super helpful for me. It's not always the case talking with everyone where they'll kind of complete the thought around around, you know, maybe like an area. So yeah, it makes it easier for me. Yeah, yeah, but I appreciate it. **Ashley Christenson (01:14:24):** Good. I'm so glad. I tried to answer your question at the end of like, wrap this up, girl, put a bow on this. Don't forget to actually come to a point at the end because I used to be really bad at that. would just waffle on forever. No, that's I mean, you know, it's just like that sometimes. **Gabe (01:14:39):** Yeah, yeah, yeah, go ahead, go ahead. **Gabe (01:14:48):** Yeah, yeah. Okay, so and how are you on time here? **Gabe (01:14:55):** Okay, okay, let's wrap up. Let me... **Gabe (01:15:04):** Actually, I have a real... **Gabe (01:15:10):** Okay, so the way you're looking at this is you did you do have, you know, intuition of okay, what is good to post, but you're using like, like a like time as a variable to understand, okay, is this relevant? party equation? And then is this like bubbling up essentially? Like is there other discourse that's that's bubbling up around that? And then with the TPPN, you basically saw, time is now, and then the concept, you know, I'm an expert in this field, and this is a rare, this is like a rare thing that's happened. So that was like a way that you were able to identify like a new customer, essentially, or a new voice and audience to speak to. **Ashley Christenson (01:15:55):** Yeah, yeah, and to be fair, that unique blend of things does not happen every single day. There's not daily news in my category that I can speak on at this level that is happening across the timeline. That is like... not super, super rare. would say maybe it happens. Like it's happened really three times over the last couple months. The first was the TBPN acquisition. And then I think it was the Mr. Beast live stream. And then shortly after that, maybe like a month after it was MTS. So I don't get this opportunity every single day, but I'm still posting every single day. I try to post like one to three times a day usually. So that means that some days the engagement and like the interest in my stuff is a little bit lower, but that's okay. There are, you know, not every day can be the best day. And I talked earlier about the peaks and valleys that you usually experience and marketing and content. So that's just, this is a very natural part of it. And then there will also be days like I have a banger and days where I'm and that post maybe wasn't... it was more for me than it was for an audience, which is also, you know, that's okay too. Sometimes I'm gonna have those days where I just make a post that I care about that maybe not everybody does, or a topic that I think is more interesting than everybody else thinks it is, because I have... I do have niche, kind of nuanced perspective and interest in some of these things to the point that not everybody cares about I don't know, Instagram launching this live shopping thing that they launched, I think it was this morning actually. So yeah, I know that that post is not gonna perform as well, but I'm probably gonna make it, because it's cool to me. **Gabe (01:18:02):** Yeah, Yeah, this is has been great. Appreciate you coming on. And last question before we wrap is. Other than the live stream connection, is kind of like your core thesis, right? This human to human value accrual model, which probably over the next generation is going to be a huge dominant feature of media content generation. Where is there like some alpha or things that are bubbling up that no one is really looking at? It seems like clipping, which we'll have to like do another show on this, but clipping has, it seems like it's It's peaking. But at some point, yeah. **Ashley Christenson (01:18:43):** Yeah, I think clipping is f***ing for sure. sorry to cut you off, go ahead. **Gabe (01:18:48):** Yeah, no worries. Yeah, Clipping speaking, but at some point it was the alpha, right? Like if you knew what clipping was, that was the game changer. What do you think, and it's good to ask this at the end for the people who are paying attention, but yeah, what do you think is kind of that next meta, if you will, for the listeners still hanging on? **Ashley Christenson (01:19:12):** I love that you gave, yeah, you're like rewarding the people who are staying through to the end. smart. Yeah, I... think live shopping is like criminally under discussed right now and under appreciated. I think some people have seen it come up on the timeline. Gary Vee has talked about it. Even when he talks about it, nobody engages with it. When I talk about it, I made a post about how QVC was being impacted by like essentially how live shopping is the new internet era QVC. And then it was crazy the next day QVC announced that they were filing for bankruptcy. Like they were so impacted by live shopping on TikTok, what not, Amazon live shopping, which their live shopping is not that great, but what not is doing incredible work and even live shopping on like owned streams, your own stream. You can sell things. learned about this. 2018 I released an ebook. I sold like I don't know a thousand dollars overnight when I first launched it which was a pre-sale and I thought that was really cool. I had never you know I went to sleep and woke up with a thousand dollars. That was really cool and then whenever I went live on the day that it was available for purchase I made $4,000 in an hour or two, which was like an astronomical amount of money for me. I'm from like very humble beginnings. so that to me was the first time I was like, oh my God, live selling converts at a level that I did not realize was as impactful as it actually can be. think as people **Ashley Christenson (01:21:19):** grow more more accustomed to live content, we're going to see more conversion opportunities inside of live. I've also seen similar data from a tool called Borty. So I met with the founders of Borty. They raised from VC, like they're in a really interesting position. Borty has, think, 150,000 executives and like white collar workers and he's essentially like a networking AI. So if you're in the Borty network, you will be shared with other people in the Borty network. If you guys have something in common that you're both looking for. For example, if I want to help companies create live programming, I can tell Borty, hey, this is who I am. We do a short intro call. It's like a 15 minute, five minute call with an AI. It's crazy. And then you say, okay, well, I want to provide these live streaming services. And it says, okay, anytime that somebody tells me that they're looking for live, I will tell them who you are and I will connect to you. It's nuts. And so they went live with a guy who was selling a book and the book... hit number one on the New York Times bestseller organically because like the thousand people showed up to the live stream. He sold tens of thousands of copies of this book and made it to number one. it's. live shopping once people realize that it's a better conversion ROI than short video, than produce video, than podcasts, there will be an absolute explosion. So anybody who starts getting really good at this now and can position themselves to maybe help brands do this or help entrepreneurs sell stuff live or help their community members or even just make their own stuff and sell it live. **Ashley Christenson (01:23:28):** there's massive growth that's going to come to that space and nobody is taking it nearly as seriously as they should. **Gabe (01:23:36):** Yeah, wow. Yeah, yeah. I know the conversation is going good when I'm like scrambling to take notes on the side. So. Yeah, so, but yeah, anyways, thanks. Thanks for that. Borty is the app that you're that you're talking about, right? **Ashley Christenson (01:23:41):** Good. Yes. **Ashley Christenson (01:23:51):** Yeah, yeah, it's Bordy.ai, B-O-A-R-D-Y, and I'm not like sponsored or affiliated or anything. I had one call with them just to explore the tool and teach them a little bit about life. **Gabe (01:24:05):** Yeah, cool. Well, yeah, this was a great conversation. I appreciate you coming on and yeah, I hope to have you again on sometime soon. **Ashley Christenson (01:24:12):** Yeah, thank you so much for having me. **Gabe (01:24:14):** Take care. --- # Anthropic Mythos in DeFi: Social Engineering and Security in the Age of AI > Shoal Signal episode. Guest: Yuannan Yang (CertiK). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-05-04 - Video: https://www.youtube.com/watch?v=lq3lFJrH88E - Canonical: https://shoal.xyz/research/episodes/anthropic-mythos-in-defi-security/ - Keywords: AI agents, crypto, DeFi, security, gaming, interviews ## Transcript **Gabe (00:01):** Claude just launched one of their biggest models yet, is the Claude Mythos Preview model. And they're claiming that it has found 20 to 17 year old exploits in old code that millions of products and people have looked over. So I'm here with Yang, a smart contract engineer at Certic, who his previous experience was at Tsinghua University and Johns Hopkins University as a researcher. And today he's a lead engineer at Certic working on all things AI and smart contracts. So yeah, Yang, please help us understand how you're looking at the DeFi landscape with something like Mythos kind of looming in the background. And is this something that we should be nervous about? how should we kind of look at the blockchain space with this application and models relatively available? **Yuannan Yang (00:56):** So if you refer to the methods models that developed by Cloudy, ⁓ I think it's, I just want to make sure before, so I want to make sure the methods you mentioned is the models from Atatopic or the gaming platform. **Gabe (01:17):** And profit. **Yuannan Yang (01:18):** yeah, okay, got it, got it, got it. Yes. ⁓ So ⁓ in my understanding, we do very basic testing about ⁓ the OPPOS models, but we do not have access to methods models yet. But we found out that those models are very powerful in terms of traditional cybersecurity parts. Like find out those injection front-end bugs, those bugs in very big heavy software system but I just found out that they are not very good at solving problems in Web3 DeFi landscape. Why? It's because in DeFi especially for smart contract it's basically you can think about it's a gaming it's like you are playing game ⁓ using a smart contract. Smart contract is the rules to play that game but the attackers is trying to break your system trying to any edge cases anything that can break the games. It's quite different for traditional ones. For traditional securities, you are searching for some ways to get your servers access, get your data, get access to run certain commands. But for DeFi, it's more like you are thinking how we can break this game, how we can do, for example, arbitrage, some arbitrage scenario. to earn money from using this game rule. So pretty much it's a different, it's kind of like different landscape and situations. So in terms of that, I think ⁓ Opus and Antutopiq AI right now is not that powerful enough ⁓ compared to Web2 traditional securities. **Gabe (03:14):** Wow, so you're saying it's apples to oranges, basically, the capabilities of something like the Mythos model in traditional cybersecurity compared to the conditions and the game, if you will, in crypto. You guys are seeing them apples to oranges, and basically, there's different technology that needs to be applied and is not readily available yet at that scale. **Yuannan Yang (03:37):** Yeah, yeah, so the landscape is quite different. yeah, I would say, because you know, Web3 is not ⁓ very big. It's not very big, it's very small branches of security. So if you need to reach deeper into that branches, it still have a long way to go. **Gabe (04:00):** Nice. Is this what your internal engineering team is saying? What are the conversations around that? Is it urgent, like, okay, we have to move, or is it like, okay, this came out and we'll see what happens, but otherwise we're just gonna focus on our own ⁓ applications of AI. **Yuannan Yang (04:17):** ⁓ So ⁓ can you repeat that question again? **Gabe (04:24):** Yeah, yeah, yeah. So like the discussions that you have, you know, with other smart contract engineers, whether they're on your team or externally, how are you guys looking at the Mythos model? Because, on mainstream media, on Twitter and these other platforms, everyone is pulling their hair out. But for crypto specifically, ⁓ **Yuannan Yang (04:38):** Yeah **Gabe (04:44):** As you said that, okay, you the application is not quite there. Are you guys kind of moving very quickly because it eventually will be there or is the vertical of crypto just so different that the principles and kind of like the primitives that are being applied are just totally different for DeFi and smart contracts? **Yuannan Yang (04:48):** Mm-hmm. Well, so ⁓ based on my experience, I think eventually it will be there, but just in time, just about the time. ⁓ So because the landscape is different, so it still needs, it still needs some time for training in order to get that deep. But we've already seen some... say something that will happen in the future. For example, we're right now using ⁓ OpenAI and that's what topic models. their APIs to serve as a reasoning model for our internal AI system. it's like we are using your, we are not using their like knowledge base, like their like knowledge base, like how they, how to process the data. We're using them as our reasoning engine, like to do audits. It's like basically we just tell them that how we, we just basically teach them how we do audits and ask them to follow our follow our rules step by step. For example, I told him, hey, this is a staking contract. So what is needed for a staking contract? You need XYZ. And what's the game rules for a staking contract? It's like XYZ is there. And now you need to help me to check whether those conditions are true, whether I am applying this attack techniques, I just get additional rewards? Can I just break the rules? Just et cetera. **Gabe (06:12):** Mm. **Yuannan Yang (06:40):** if we provide additional knowledge and give him the workflows, how we do the artist, he will complete it very well. **Gabe (06:51):** Okay, you guys are, so these are like parallel systems to basically run your tools that you already have built out. And you mentioned the knowledge base. I know you guys, you have your own knowledge base and that's kind of the moat for, or a moat potentially for your business. Can you just explain what that is and why that's important kind of in this equation? **Yuannan Yang (07:03):** Yes. So our knowledge base is a very big knowledge base and we started our knowledge base even back to 2021. we started this knowledge base. So initially this knowledge base was using a document format. It's like every time we were doing audits, you have some experience experience, will do some research and you will accumulate some knowledge. You just put it into a document and it's basically like your audit notes. And later on we have ⁓ a checklist system, which means that every time we do audits, we need to figure out what kind of checklists we need to do. And we have this checklist system to accumulate our knowledge. And also we are handling incidents. from Web3 spaces, so we have a big incident database. ⁓ So basically these two parts ⁓ is where we accumulate our knowledge. So right now we have a really, we put those knowledge into very structured, structuralized format into our database so that our AIs can just batch it really quick and really conveniently. also the AI will know what kind of knowledge they need from this database. So it's basically a long journey and we just index the the knowledge into our database. **Gabe (08:55):** Wow, okay, you guys really, you're kind of forming it into a data company where you have all this data and kind of structures of how you go about the audits and checking for certain things and then leveraging the agents to basically accelerate those checks. **Yuannan Yang (09:12):** I would say no, unfortunately. So this is because our data is not like traditional data. For example, ⁓ some raw data that we simulate. If you are AI that do simulations on driving, you need a lot of driving data to train your model. But it's not quite like that. So for our knowledge base, it's more like the experience from auditors. like the checklist, it's like, for example, if you do a staking contract, you will understand how the rules is played, how the game is played, what would be the rules. So, auditors just pull out those rules into a database. It's not the code itself, it's not what we did, but it's just maybe just one or two phrases to describe this staking contract. So basically, it's not like this traditional data, but I would say, it's a more abstract data there. **Gabe (10:16):** Got it. Okay, and for you guys specifically, when it comes to looking at these, the models, is there particular models that you've seen that are better at these types of tasks, or is the generalized reasoning model sufficient if it's just generalized, and then you kind of have the rule book on top of that? **Yuannan Yang (10:38):** Yeah. So ⁓ from my experience, because I only do quite a few scanners myself, so in my understanding, I prefer to use strategy BT ⁓ from OpenAI, those models, because those models are good at reasoning, and they are good at logical, think about logical issues. From my audit experience, 70 % of the vulnerabilities are related to logical issues. It's like the rules, and they're trying to break the rules to find the vulnerabilities inside these rules, like how to arbitrage, how they can achieve profits with those rules. So I think in TragiPT it's do a better job to do those kind of reasonings. And the cloud models are more like trying to find out the coding bugs, some language specific, like for example, the Cloud Code will understand how you're gonna code. And he just found out the difference between his code and your code. Then he will come up with a funny, say, hey, your code is different than me. So are you introducing some vulnerabilities? So I prefer to see Cloud Code works like that. And for like, charge BT, for models, they would like more like reasoning, just ⁓ read those rules to see. that whether there is some vulnerabilities that can break the rules. This is just my two cents. **Gabe (12:16):** And at this stage, you think the gap is significant between your experience in the application of the models where like GPT 4.5 is different from like OPUS 4.6 or 4.7? Yeah, yeah. Do you think the gap in between the two models is very wide or do you think it's pretty narrow? Like how big of a gap in the performance for your specific use case is it between, ⁓ you know, Anthropic and OpenAI? **Yuannan Yang (12:57):** ⁓ Thanks for repeating this. ⁓ I don't think there is a very significant difference. if we are, ⁓ say if ⁓ our test dataset has 10 vulnerabilities. So maybe in ChatchBT, we were using ChatchBT models, and they can find eight. But for using Cloud Code, ⁓ they can find like seven. So it's not very different. but I would say they still have some difference but I don't know how they gonna be in the future and how is the vertical goals and their plans but I would say in terms of our current my current experience the the difference is it's not very big it's just some minimum difference **Gabe (13:48):** Got it. And so you guys are essentially building like a harness ⁓ for smart contract auditing and using the frontier models to power this harness. **Yuannan Yang (14:00):** Yeah, exactly. So we are using different models. Like, GPT-4.5, you just mentioned, also models from Cloudy. We also use some open source models and try to lower the cost. **Gabe (14:18):** What about localized models? Are you doing any local stuff for cost effectiveness? **Yuannan Yang (14:23):** Yeah. Yeah, exactly. So this is also some directions we're now heading to. you know, ⁓ those APIs from cloud, OpenAI is quite expensive. But for some tasks, like extract contacts from ⁓ code, those are very easy tasks. You can do it either with this static analysis tool, static analysis ways, or you can use very cheap models. So we were trying to decompose all the workflow. and just that those tasks was very easy. Did not need those sophisticated models, ⁓ optimize those tasks using ⁓ local models. **Gabe (15:10):** interesting. Okay, yeah that kind of takes me to my next question about the breadth of the type of work you do so Recently there was there was a drift hack right which was a social engineering hack and this is not the first time we've seen this there's the Axie infinity social engineering hack same thing. It was like 600 million this one might be on the order of closer to 300 million and Is are these types of hacks within your remit one and two? How are you guys looking at the tool? **Yuannan Yang (15:32):** Mm-hmm. **Gabe (15:42):** and skills to prevent these types of things and are you supporting customers with this? **Yuannan Yang (15:48):** Yeah, so because of AI, the landscape has dramatically changed and those social engineering attacks happens a lot. like every week, I will receive a lot of reports from our clients saying like, our private get exploit, can you check, help me to check out what happens? Like most of the clients, the private get got compromised because they're doing some like vibe coding stuff and they were just systemistically install some MPM packages, which those malicious packages were just breaking the system, like get credentials, get the private keys from the memory. So we saw a lot of cases like that. And ⁓ we also saw some AI introducing new vulnerabilities, like ⁓ in the past, like MoonWheel. MoonWheel, it is a void that CloudCode I forgot the model is 4.5. It just introduced one of these to hard code at the Ethereum price. **Gabe (16:56):** And that was the Moonwell ⁓ vault, the DeFi protocol. They basically introduced a new update, and then the model introduced the bug. And basically, in the GitHub, could see Opus was the co-collaborator on that. **Yuannan Yang (17:01):** Yeah. Yeah. Yeah, exactly. So the landscape is changing dramatically. ⁓ So that's also some things we... ⁓ we are trying to build ⁓ the capabilities we're trying to build recently. So ⁓ I remember last week we just launched a new product called Assertive AI ⁓ Skill Scanning, which is ⁓ a tool-side scan for malicious skills. ⁓ But to be honest, I would say we still have a long way to go because we also have a group of security researchers who is conducting research. which is ⁓ how to bypass those skills scanning. ⁓ They were working as attackers to think about ways to bypass those scanning tools. So we found tons of ways to bypass those scanning systems, even with the most popular scanners. ⁓ You can also check out our post at solik.com. I will explain this in detail, but I would just say we still have a long way to go to protect this. Yeah. **Gabe (18:25):** So for vibe coding specifically, has become one of the, is that like the largest attack vector for social engineering as of lately? **Yuannan Yang (18:34):** ⁓ I would say no, but because most of our clients are developers and they are developing smart contracts and that's why we receive most of the reports. Last month we released a security report on Open Cloud and we just got a matter of cases where the hackers leverage Open Cloud vulnerabilities to get a credentials private case. And just in one case ⁓ earlier in February, ⁓ this year, ⁓ OpenClaw Skill Hub. SkillHop is the SkillHop. Yeah, the skill registration, CloudHop, it got flooded with over like 400 malicious skills. Yeah, they just impersonated tools like ByBase, PolyMarket, DressUp as crypto training automations. And I remember there was one account alone racked up like 7,000 downloads. So it's a quite big number. And also I remember **Gabe (19:20):** wow. **Yuannan Yang (19:40):** there is an independent researcher just ran a proof of concept. He published a test malicious scales there and within eight hours there is 16 developers across like seven countries, eight countries, I forgot, install it. So I would say web coding is only a small portion and we do see a lot of more cases. because AI just expands the security boundary dramatically. **Gabe (20:14):** And then what is kind of the forefront case study for exploits? If it's not vibe coding, vibe coding is clearly like on the rise. What's the core issues that you've seen? **Yuannan Yang (20:25):** Mm-hmm. The core issues I've seen you mean AI agent **Gabe (20:34):** Just like social engineering, what are the main ways in which you're seeing case studies of social engineering? What is the pattern of those attacks? **Yuannan Yang (20:37):** so cringy. Yeah, for social engineering, let me think about it. Because most of the cases I've dealt with is byte coding. And for social engineering, I just received some cases ⁓ where... So we're the attackers just to tell you like, Hey, I have a deal to want to discuss with you. Let's do a Zoom call. Let's do a Chrome call. And when you are doing Zoom calls with them, they might send you a fake link. It's not like zoom.us.com is, but like Zoom like for what, what, is, it's a very, it's just disaffection. And during the meantime, you will see some like blur and some noises there and there pop up the window saying like, Hey, you need to upgrade. **Gabe (21:25):** Okay. **Yuannan Yang (21:35):** your zoom. If you click that one, your computer will die. So there is a lot of social engineering ways to break your system using emails, like zooms, like telegram. So you have to be cautious about the links you click and you have to be cautious about what you are doing to your computer. You have to set up very restricted access control to your computers. **Gabe (22:02):** And are these, ⁓ do you think for a lot of the customers that you're dealing with, are these targeted attacks or is it kind of blanket attacks? **Yuannan Yang (22:11):** Yeah, I would say ⁓ in my understanding, I think it's kind of like very targeted. ⁓ I ⁓ have that feeling because I know of many of my friends, they are working in crypto companies. They are like business developments, they are like maybe CTOs. So they just receive tons of fake emails, like tons of fake invitations. like tons of malicious links every day. So I feel like if you are working in crypto, you have access to many resources ⁓ like you host private key for your company assets, et cetera, you will be easier to get attacked. **Gabe (23:04):** And for you, are, what is the extent of how you support these types of attacks? Like, you know, if it's someone is downloading something, a skill, and it's a malicious skill, at what point are you ⁓ supporting them? Is it after the fact or like, what is the predictive stuff that you're doing ahead of time ⁓ for these types of things? **Yuannan Yang (23:29):** Yeah, I would say there is no effective ways for you to prevent those attackers. know, attackers are always coming up with new ways, new technologies, new angles to do social security. But I think that the key is you have to educate them enough to do some educations for them. Tell them what you need to do, what you cannot do during an interview and give them more case studies to make them understand, to make them have security awareness. I think that's the most important thing. But what we can do is give them applications of course and after that, if they found out that their system might get wrecked, we would just let them stop the networking and send the computers to us. We will just do some hardware analysis, etc. just to find out what the root cause is and then publish the root cause to public and do more applications. **Gabe (24:28):** Got it. it. So a lot of education and kind of don't do these types of things. And then if there is a tactic, then it's there's like a retro on it. But what what are the can you share like ⁓ maybe just for people in general, like what are these things to look out for and what's like the core primitive? it like downloading something? What are like the actions clicking, downloading? What are kind of like the high level actions that should be monitored, especially in the age of AI and all this? **Yuannan Yang (24:38):** Yes. **Gabe (24:58):** know, automations. **Yuannan Yang (25:00):** Yeah, first and foremost, if you are reading some emails, if you are having some conversations, if you saw a link, that direct you to something you do not know from untrusted parties, do not click that link. You need to verify as per the, you are having conversation with a trusted party. They may just pretend to be a trusted party, say, like you are both like your partners, et cetera, but you have to verify the correctness of the link. And when you are doing, like when you are having Zoom link, when you have meetings with your clients, with anyone, you need to be careful to read whether the links is correct and if they ask you to download everything, never do that. And also for those who like doing web codings, I would recommend that you do web coding in a secure environment like say sandbox or even use a new computer without credentials to do so. Yeah, that's basically a very high level advice I can give you. **Gabe (26:11):** Good, good. Another section in the own second. Yeah, so. For the product that you guys are building, it seems like you're ahead of the curb on... you know, building this AI harness specifically for crypto security auditing. And you said before that, you know, something like a mythos or this traditional cybersecurity model doesn't directly impact ⁓ the ecosystem at all if there were as much as we think. Right. So what is kind of like the race look like and how does the, how does the business model for you guys actually change if potentially the barrier to entry for a first mark? contract auditing ⁓ lowers. **Yuannan Yang (27:01):** That's a very hard question because AI really impacts the whole industry for a lot. So a thing that I can say immediately is that AI is truly replacing those junior auditors. So we recently launched our AI product called AI Auditor, is a beta testing. Beta testing is a scanner. that can scan your smart contract and give you a result like an hour. And this scanner's capability is ⁓ much better than a junior auditor. So I would say, if a junior auditor cannot find sophisticated bugs that AI cannot find, ⁓ it is a... be like getting impacted. And also in terms of other is itself, ⁓ I would say like, ⁓ I saw there is a trend for like, ⁓ like every clients wants to like develop a real quick near using their AIs to do development. And they do not even understand when they're coding sometimes. So in this case, it's provides, it requires from the risk is shifting from them to us. It's like we need to understand what kind, what AI, what's the capability of AI, what's **Gabe (28:33):** Mmm. **Yuannan Yang (28:39):** What mistakes are the AI going to make? **Gabe (28:43):** And you're saying that the right now the teams are basically putting together code and then it's working, but then they ship it to you and it's like slot. **Yuannan Yang (28:55):** Yeah, exactly. it's AI, they do web coding, right? Because AI is very powerful. They can just do some web codings that add features really, really quick and just submit those to do an audit. this is, ⁓ I would say, so the development cycle is becoming quicker and quicker. It's like they just spend a day to develop a hundred lines of code for us to audits. So, I mean, in this case, we have to adapt to it. That's why we invest a lot on our AI technologies. We launch our AI products. It's like every time they have developed a smart control or something, they can just use our AI to do scanning as a checkpoint. And later on, when they finalize, have a beta stable version, they can just reach out to us like, we want many audits for this version. Can you do that for us? Yeah. **Gabe (29:54):** So the team pushes ⁓ new code and then they have a checkpoint, like a self-serve tool that you guys provide. How long have you guys been doing that? **Yuannan Yang (30:05):** ⁓ So we're doing that AI tools as our internal tuning system. It's like every time if the client allows us to use AI, we will just run the code base and just serve as a baseline for our audits. And we just recently released some of the scanners to public, some general as a beta testing. So this is just to adapt to the AI ⁓ environments that AI dominates the coding space. **Gabe (30:46):** Yeah. And previously, so teams would finish all of these features and development and then ship ⁓ a pile of code to you. But now it seems like the behavior and the landscape of development obviously is changing. It's faster and the throughput is accelerating. And then on your end, it seems like you're building towards this real time audit. Can you tell me about where the **Yuannan Yang (31:08):** Thank Yeah **Gabe (31:17):** direction of the industry you think is going? Is it going towards real-time audit? What do you kind of see it as in maybe the next three years? **Yuannan Yang (31:26):** Yeah, so to be honest, ⁓ I don't even know what's gonna happen in three months. know, AI is changing like dramatically every day. So ⁓ I would say in terms of industry, I don't think ⁓ real-time artists will be dominant in a space because right now AI system has many problems. I will list just a few here. So the first is the randomness I told you. ⁓ **Gabe (31:31):** I see. **Yuannan Yang (31:56):** If you look into our benchmark, so we do a benchmark on 2026 incidents, is which there is a 35 instance and we do a benchmark on that so in our first round there is like 80 record rates, 8 % record rates. In the second round, it's have 88 % record rates. So that means that if you run the model like two times you will have higher chance to gain more vulnerabilities. That's the randomness I just told you, which means that in some situations, AI can miss bugs, miss those very critical bugs. Those are instances that lead to actual loss. So if you miss the one bug, it's going to be millions of dollars loss. So I would say AI still have some restriction in terms of randomness, but for humans, in terms of human artists, ⁓ we at least have three auditors in projects. They will do manual review, line-by-line review, and do cross-check, which means that every time when a finish was done by a human audit, there is a likely chance that they miss vulnerabilities like AI. And also in terms of accountabilities. So you cannot expect AIs can do accountabilities for a product. If your product got audited by AI, you were probably not trusted. And this is another part I think AI cannot replace. And the third part is in terms of depth verticals. So ⁓ we were building AIs. ⁓ At the very beginning, I was thinking when the AIs can truly do some very, you know, very in-depth thinking, like finding some zero-day vulnerabilities that only like, experts can find. I would say yes for some cases, but more cases I will say that it requires humans for guidance. It's more like, human needs to tell AI what you need to do and give him a guidance to like how to achieve that goal. So I think for those in-depth findings, sophisticated findings, still requires human interactions there. **Gabe (34:23):** Yeah, it seems like now you tell an agent what to look for and the rules in which it should look for it. Are you guys thinking through and for you? **Yuannan Yang (34:31):** Yes. **Gabe (34:37):** Do you think that skill can move up the stack where then the agent starts finding its own ways of, its own rules or either finding its own specific types of vulnerabilities? How far do you think that is where the gap kind of closes on the expert? **Yuannan Yang (34:59):** Yeah, it's a super good question. So we do have some research regarding to that. in smart contract audits, we have a term called property or invariant, ⁓ which means that you have, when you are doing smart contract, need to, there is some rules that always hold true. Whether you are doing form of applications, you are doing fuzzings, you need to make it as true. For example, a invariant of property can look like this. So when you say there is a staking contract, you stake like 100. When you un-stake, you un-stake like in certain period, your un-stake amount should be bigger than the staked amount. So that is the property, right? So that is what we call the property. It's basically like rules you need to fulfill while playing this game. if you need to come, I mean, if you have already **Gabe (35:52):** Hmm. **Yuannan Yang (35:59):** come up with this infrared for a similar staking contract you can reuse this ⁓ infrared and property. But in terms of if there is a new system, it's a different staking model. Like say, hey, this staking model is like in the first week of your staking, if you un-stake, you will get punishment. what you can get is actually decreasing. But for the second month, it's get increasing. I mean, the situation is different. if these ⁓ human or AI system can just look into that to identify those properties. But obviously, the abstraction is not as good as human for understanding cases. But in actual cases, it's much more complicated. It requires a bigger system. They have many different interactions to external parties. If it's staking, it's not staking. to in this protocol. It may stick in other protocol, other dependency protocols. Say like list of data, like say other yield protocols, and you have to understand what kind of products you are sticking into. So for humans, because we have experience and we have ⁓ better ability to gather, put all the information together because we are getting a lot of training for this expertise. So we can quickly adapt and find out the proper ⁓ great property or invariant or better invariant than AI. But I would say you are right. This is something that my AI can come up with, but I don't know when it is. **Gabe (37:40):** Yeah. Yeah. Okay, so you're saying, and I'm starting to notice a pattern actually. We had Nikita from Barter on our first episode and he was saying, you know, more so the agents are ⁓ used in like certain conditions. ⁓ And for you guys, you're saying like, okay, the agents can do certain things very well, but you know, for this like abstraction piece and pulling together all the context, it's **Yuannan Yang (37:50):** Mm-hmm. Yeah. Mm-hmm. **Gabe (38:13):** the context piece is the issue. ⁓ Also, someone else, Mike from ⁓ Hummingbot, he said the same thing, where for them, the missing piece is kind of like just plugging in all the information about the ecosystem. Is that kind of what you're seeing as what's missing from, you know, like some agent just basically doing like the end-to-end discovery and auditing process of, you know, novel issues or problems, et cetera? **Yuannan Yang (38:42):** Yeah, exactly. also, I believe there is not a lot of data for AIs to be that smart at the current stage, because know Web3 security is very new at this space. And I don't know if there is enough data ⁓ to train the action models to be that good. But I do believe that the capability of AI is keeping increasing. and there will be more and more sophisticated vulnerabilities that AI can find. ⁓ But in terms of current phase, ⁓ would still say that AI still have its limits based on our ⁓ experience of using AI throughout audit process. **Gabe (39:38):** Yeah, this is super interesting. Any last thoughts before we wrap up? I know you guys are pushing on the internal AI harness a lot. any last thoughts there and kind of what you expect and are going to be seeing over the next couple of months? **Yuannan Yang (39:48):** Thanks Uhhh, asshole. ⁓ That's a very high level question. ⁓ I've chat with quite few CTOs from blockchain infrastructures. ⁓ They are just building some infrastructures for agent economy. They have different solutions. Basically, just ⁓ give an agent identification on their blockchains. the blockchain and your crypto accounts like that and execute the transactions there. So I would say a lot of like infrastructures and lot ⁓ of nodes are just shifting to agent to agent system but I also feel like I'm not comfortable with current security models. Many things that they did not actually realize, like for example, AI agent is off-chain and not controllable. How do you ensure that your agents will not get exploited? How do you prevent like problem injections, data poisoning to your AIs? And also like if you're thinking about, if you compare this to the past, the threat model is completely different. So in the old days, if attackers want to perform a social engineer attack, discuss. So they have to build trust with you, right? They have to make you trust that this email is ⁓ from a trusted party, like your partner. even some hackers from North Korea, they will even enter your organization's past interviews to do social engineering. But now the hackers can only just social engineer your AI agents. So what your AI agent is it's like a very junior employment employee that has a full access but like almost no security instincts. So I think this makes much easier for a hacker to break into to to hijack your AI agent than an actual human. So those kind of challenges I think we do not have good security models for that. ⁓ **Gabe (42:25):** Yeah. That's a great analogy. And because we've seen kind of some like ⁓ wrappers or tools that are securing the agents, but, you know, those do not go as viral as, you know, open claw. Just it just the the breadth of the stuff that you can do. So, yeah, the agent security piece, especially like reading emails, you know, with the prompt injection where, you know, there might be malicious instructions in the email, something I've been worried about. ⁓ And on that point, to just before we wrap is I have a kind of a very specific question for you. And basically you guys see a lot of ⁓ types of protocols, right? You're like a bottleneck of information when it comes to teams with capital, right? And teams who are shipping products. And that is kind of a unique area as one of the largest smart contract auditors. Without getting into the specific names, are there types of products right now that are being built in the ecosystem that you're noticing are getting more audits, right? And for us, this is like an indicator of **Yuannan Yang (43:14):** Mm-hmm. **Gabe (43:36):** Okay, maybe this sector is heating up. Yeah, is there like some kind of hints you can give on, is it payments, is it stables, is it agents? Where are the serious players ⁓ shipping code the most? **Yuannan Yang (43:52):** So I would say from my experience, would say we got a lot from institutional clients. They're doing payments, they're doing infrastructure stuff. So they are players from traditional world and they're trying to do web three stuff. So the gap here is they have very strong experience in Web2 but they did not know about Web3. ⁓ For example, I remember our security team found vulnerabilities that related to fake deposit ⁓ that can just do a fake deposit to exchange ⁓ using smart contract and just the cheat and the exchange scene like hey we're for ID, make a a fake deposit, we have to trade the exchange and say hey we make a deposit but actually there is no money going there. So this is a vulnerability that web 2 native ⁓ personal security researchers cannot find. I think it's a good case. So in terms of that I think Serdic is a good one to fit in that place. Like give some insight to the audience for those parties. to let them understand more about web3 and provide security products to make sure that everything works smoothly because they carry out a lot of capitals there and also data privacy etc. So yeah, I would say there's a lot of things we need to do in the future. **Gabe (45:49):** Yeah. Awesome. Well, appreciate you having on this. This has been super insightful. and I guess to wrap on that last thought, the institutions, these web two institutions, uh, I'd assume, you know, banks and tech companies are coming on chain, building their own products. And this is potentially something that we should kind of pay attention to as there's probably going to be some, some updates and new products rolling out for the next couple of months, if not the year. Yeah. Cool, man. **Yuannan Yang (46:16):** Yeah, exactly. **Gabe (46:19):** Well, yeah, appreciate having you, Yang, and sharing your expertise here. And hope to have you back on time sometime soon. **Yuannan Yang (46:24):** Yeah, thank you, Gab. Thank you. Thank you for being so nice to me. know, engineers sometimes are quite shy and do not know how to handle some tough situations when you're doing face-to-face camera. So thank you for being so nice to me. **Gabe (46:28):** Don't worry. Yeah, no problem. Yeah, anytime and appreciate you coming. Yeah, see you. **Yuannan Yang (46:49):** Yeah, appreciate it. Thank you. See you then. Bye. --- # The $292M KelpDAO Exploit: A Step-by-Step Autopsy > Shoal Signal episode. Guest: Harry Donnelly. Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-05-03 - Video: https://www.youtube.com/watch?v=gRgXK75TUBo - Canonical: https://shoal.xyz/research/episodes/the-292m-kelpdao-exploit-autopsy/ - Keywords: crypto, DeFi, security, infrastructure, Ethereum, interviews ## Transcript **Gabe (00:00):** Nearly $300 million was lost in the KelpDAL hack with losses extending throughout the crypto ecosystem due to collateralization, leverage, and composability throughout the network. I'm here today with Harry from Circuit, former MIT financial engineering And we're going to go through the specifics and the cadence of what happened in the hack. and uncover a forensic deep dive of what's to come next. So Harry. Let's hop right into the hack and yeah, from your angle, you did a deep analysis assessment and posted online a retrospective. Could you take us through KelpDow, Layer 0 and all the specifics of what happened during the hack? **Harry Donnelly (Circuit) (00:40):** Cool. So first things first, as Gabe was saying, $292 million lost, but not just that, a massive downstream impact on everything in DeFi, almost. We're still waiting to see everything resolve. So it's Monday. This happened on Saturday. It's not fully ironed out yet. But what we do know from the postmortem that got released today is how the root exploit happened. So Layer 0 released their statements. I've gone deeper into it and researched all around it. And hopefully today, you'll have a better understanding afterwards of what actually happened. So with that, we'll dive in. ⁓ So the way I broke it down the paper is to understand the hack you're gonna need to understand a little bit of context around both kelp and layer zero because what is kelp-dow? What is orraseath? There's a lot of acronyms, there's a lot of word salad. So pretty simply orraseath is... Staked ETH routed through Eigen layer. So you get double staked ETH. And in order to do that on different L2s, you have to stake, not just stake, you have to give funds to KelpDAO and then they will put it in different chains for you. And so while funds are on those layer 2s, they are not actually your real funds. Your real funds are kept on Ethereum main net and they're kept in a custody contract. And so the custody contract is where your real funds are. Think of the funds in the L2 as a receipt of that, almost like a deposit box. You put the funds in the deposit box, they give you a receipt. You can use that receipt and if you want to bring it back to Mainnet, then you get the funds out of the deposit box. So that's what was actually hacked. The deposit box was where all the funds were taken from. And how did they get access to that? Well, that's where Layer 0 comes in. So Layer 0 is a messaging chain. Think of it like people talk about like Swift for blockchain, but what it does is send messages back and forth between different chains so that they can talk to each other because normally blockchains don't talk to each other and when we talk about different L2s and being able to bridge funds back and forth they need to be able to talk to each other to coordinate on what's real and what's not. The problem is, in this case, layer 0 was part of the reason that it was exploited. And people were able to show something that wasn't actually real as being real, which allowed funds to be released. One of the key parts of layer zero security is something called a verifier. So what they do is they watch the different events and say that, yes, this happened on this chain, so you can do things on this other chain. So think of it like it's passing messages back and forth. **Gabe (02:45):** Mm-hmm. **Harry Donnelly (Circuit) (03:00):** And the big issue that happened and the consternation that everyone's talking about is that decentralized validator network is not really the case when it's a one of one. And it ended up being that layer zero's default setting is one of one. You basically need one person to verify it. So it's not really decentralized and neither is it a network, it's just a validator. **Gabe (03:19):** this is the out of the box setup. Basically, if you, if you, you know, enroll with them, then you have this one of one DVN validator. **Harry Donnelly (Circuit) (03:27):** And so they make it really easy for you out of the box to just get going. Here's a one-on-one setup, which is fine if you're wanting to do some testing and wanting to get things off the ground. The issue being with Kelp that there was more than a billion dollars of funds, which was then resting on this. And so you can see why one of one is fine as a basic setting, but the blame lies not just on the setting itself, but that people who didn't change it. So there's both the operational risk of you shouldn't have everything resting on a one of one verifier, but also what a lot of people are pointing fingers at as well as on layer zero is that they shouldn't even have that as an option. **Gabe (04:04):** Mm-hmm. **Harry Donnelly (Circuit) (04:04):** that if they're in rolling chains that they know won't really look at the settings and don't have the technical expertise and knowledge that they should just enforce the security for them. And so there's fingers pointed both ways at the moment. **Gabe (04:16):** So right now, so kelp gets hacked. They're using layer zeros, one of one setup. And the kind of the presumptive explanation is like, okay, should they have had that one of one, but then also it's not secure ⁓ in the first place. So is that a good architecture of what's happening so far? **Harry Donnelly (Circuit) (04:34):** So think of it that what actually got exploited was layer zero. And the reason that Kelp got targeted is because they had a one of one. And so think of it almost like kelp was the largest honeypot that they could go after, but layer zero was where the point that fun, not with the point, the point where the attackers got into. And so that goes into like the actual mechanics behind the attacks. Maybe I'll explain that and then we can bring it back out and help you understand a bit more on like why deviants matter. The root root cause, and I have a graph which is just like there's all these layers of dependencies of ⁓ who relies on And, The kelp custody contract basically relies on layer zero to verify messages back and forth. So layer zero will come and say, hey, someone's trying to send 50 ETH from this chain to this chain. the DVN, which is the verifier, will look at it and say, OK, yes, there is 50 ETH on this chain to be able to send to this other chain. I verify and attest to it. Comes together, layer zero says that's good, and it gets sent off. The issue is that for these DVNs, what they do is that they have to look at the blockchain to be able to understand what's actually happening. To do that, they use something called RPC nodes. And for the RPC nodes to see what's happening, it needs to make a query. What happened on the root root cause was that the RPC nodes that layer zero was running, two of them got compromised. And North Korea was able to infiltrate two RPC nodes and put in malicious code. And this malicious code was very, very smart. It wasn't just malicious code that anyone could see. It was malicious code that would only activate when the DVN was the one requesting from it. So if anyone else is trying to think of it like make a request of it, it would give the right information. But if that specific DVN was making the request, it would give false information. So think of it like I'm trying to scam you. I have a certain message that I will only tell to you about my intention. But to everyone else, I'll say something else. And so everyone else thinks that very trustworthy, everything is fine. But then when I say it to you, I'm not actually telling you the right thing. almost in a way how to think about it is that it was lying specifically to the DVN for the sole purpose of allowing a message to get signed that wasn't the right message. **Gabe (06:53):** And we don't know yet the reason why it got hacked or how it got hacked in the first place, right? **Harry Donnelly (Circuit) (06:58):** Yeah, so that's the kind of the big open question that we don't yet know how the RPC nodes got exploited and layer zero didn't release that in their postmortem. So that's something which there is no information about publicly. We may get more information in the future, but that is the root root cause is that that was where the exploit happened. And then everything is downstream of that. So that was kind of like the root as mentioned. So once the RPC node was compromised, what it would do is it would give the wrong information to the DVN. So once the DVN was given the wrong information, it could then send a message in sign for money that wasn't actually there. And so that's what happened in the case for KelpDAO where a message was sent. pretending to be unichained and saying, would like to move 116,500 or as ETH. And here you can verify and attest this. And so that's an. The also very clever thing that happened at the exact same time is that these two RPC nodes were the ones that were compromised. And so Lazarus Group, North Korea, the people behind the hack, they needed to make sure that it was those specific two RPC nodes which were chosen because they have a few different RPC nodes. They weren't sure which ones could be taken. So what they did is that the other RPC nodes, they DDoSed them. So they basically sent them an enormous amount of requests all at once, which overloaded them, which meant they weren't able to process anything, which means that at that exact moment, all of the messages were sent to those two nodes instead. So think of it like I have four different options and whenever a message comes through, I can pick one of those four options. I have logic behind the scenes that says if one of these options or two of these options or three of these options, however many are down, I will always send it to a different one. So what they did is they made sure that the only two available, the only two that weren't down were the two that they'd compromised. **Gabe (08:30):** Mm. **Harry Donnelly (Circuit) (08:44):** And because they compromised them, they could then give the wrong information, which said, yes, the money on that chain, the Oris Eith, is actually there. it's there, you can sign a message to then release those funds on this other chain and let it out. And so going back to what we were talking about in KelpDow is that all the funds on different layer twos are really just a receipt. All the funds are actually deposited on Mainnet. And so what they were able to do is forge a message to say, hey, release the funds from the custody contract on Mainnet and give it to me. And because it was a fake message, they were able to take out real money, but there wasn't anything backing it. And so that's then the problem is that you have all of these deposit tokens, which are deposits for tokens in a box, think of it like in a bank, but that box doesn't have as much money as it was supposed to. And so when people talk about a haircut, that's the big problem is that there's no longer enough money to give everyone 100 % of their money back. And so people are trying to figure out at the moment what to do about it. that then leads to the second part, is, once that exploit happened, they needed to figure out what to do with the funds. **Gabe (09:48):** Okay, got it. So essentially KelpDow's DVN was kind of like the low hanging fruit and once they identified that, they compromised the two RPCs out of four and then forced the traffic into the two compromised RPCs and then were able to basically like double spend and collect real dollars for like these receipts that they essentially generated. **Harry Donnelly (Circuit) (10:12):** Think of it like that. I'm not exactly sure how many other RPCs there were. So four I don't think is the correct number, but basically everything else is correct. And so once they had done that, they had real funds, which they'd been able to take out. All the funds in the L2 were no longer fully backed, and then they had to decide what to do with it. **Gabe (10:29):** All right, so we covered KelpDAL, we covered Layer 0, the DVNs, the RPCs, and basically the mechanism in which they were able to compromise a system and exploit the protocol. How does this affect Aave and why is this such a big deal and what are the downstream impacts to the rest of these different protocols, **Harry Donnelly (Circuit) (10:50):** Yeah. So think of it from the attacker's perspective is that they've now successfully been able to take out funds that weren't really there. It was for a token or as ETH, which doesn't have a lot of liquidity. So they had taken out a lot of the supply. If they tried to sell it all at once, they wouldn't get all the funds out. So they would have stolen, imagine it, $300 million, but maybe only gotten 50 to 80 million actually out of it, which wouldn't have been great. They put an enormous amount of time and effort into actually doing the compromising and the exploit. They need to try and get as much money as possible out. So what they did is that they went and used those funds and put them as collateral in AVE. And so think of it like they put them down as collateral and they took a loan out against it. And the unfortunate timing is that Aorus ETH had just been recently upgraded within Aave to not require as much. Think of it like you could take out a much bigger loan than previously you would have been able to. So was like 93%. So 93 % of the value of the collateral you deposit, you were able to take out in a different token. So what they took out is wrapped ETH. So that's really liquid. could kind of do whatever they wanted with that. There is a very liquid market. And once they had that in hand, they weren't constrained anymore. The issue then being is that they put all this ORS ETH as collateral and we know that that collateral is not worth as much as it's supposed to be because what they did is that they minted a bunch of it out of thin air and so that's been the big problem for AVE right now is that that collateral is going to cause bad debt. And because Kelpdow hasn't decided what they're going to do, or they haven't at least publicly announced what they're going to do, the liquidators on AVE, the people who will, if the bad debt is there, liquidate the funds, aren't entirely certain how to liquidate. So if I take a step back. How does Aave work? Aave is a lending and borrowing market. So you put funds in and you can take funds out. And the reason that you can trust that you can take out a loan against it is that you're putting more funds in than you're taking out. To protect against the value of the money you're putting in, going below the value of the money you've taken out, they monitor it. So they use oracles to check the price. And if the price of the value of the token you've put in goes too low, they liquidate it. So once they liquidate it, they sell it, and they then basically cancel the loan out. The issue now is that because the collateral that's been put in, we're not entirely sure what the right price should be, liquidators aren't liquidating it. Because they might try to liquidate it, but actually lose money in the process of doing so. So they're just stuck. Everyone who's been able to withdraw has withdrawn. So all the markets that are at 100 % utilization. So there's no way to basically take money out at all. Until the situation gets further resolved and we figure out what's going to happen with the ORC, those markets are going to stay exactly as they are. Once it gets resolved, AVE has just put out a plan, this kind of... two scenarios that could accrue. First one is that the losses are socialized equally. So every ORS ETH holder gets an equal amount of loss and that'll cause a certain situation and a certain impact on AVE pools. The other one is that... all of the main net ETH, RS ETH holders, they get 100 % of their funds and all the people on the L2s who hold RS ETH, they get a much bigger haircut and that'll cause a different impact to AVE. And so based on those two different situations, there's a different amount of bad death and we'll be able to see what the outcome is going to be. Aave has paused the markets in the meantime to try and figure out and understand what's happening. And until everyone comes together, decides on what the outcome should be, decides, are people going to put money behind it? Are people going to repay the bad debt? We're still waiting in limbo. And so that's the situation we're at at the moment. **Gabe (14:18):** And for you, how do you look at the socialization of the losses? Do you think that people who are on these different chains should bear the full weight? Do you think that if you're on the L1, maybe you're doing that on purpose because there's risk, right? There's like L2 risk and even additional smart contract risk on L2. So, yeah, how are you looking at it personally? And if you're in this situation, how would you want to see the losses socialized. **Harry Donnelly (Circuit) (14:45):** Yeah, there's two sides to it. So the first side is saying everyone who put funds in an L2 should be aware that there's much higher risk associated with it and they're to blame themselves. And as a result, they should take a much bigger haircut because the people who kept their funds on Mainnet ETH were being safe and being secure. And so they shouldn't have to be bothered by it. The other side of it is saying, most users have no idea about the underlying technical risks of what's happening, which I'd say is probably true most of the time. And from what I understand from reading in the AVE forums, everyone has the same right to the underlying token, regardless of what chain you're on. And so think of it like an investment asset. that? The difference chains doesn't actually matter. It's the asset itself that matters. And so if there is going to be a haircut, it should impact all asset holders equally, regardless of underlying technical infrastructure. And right now, they're trying to figure out which way it's going to go. I don't have a proper opinion either way, I think. think if people were truly security conscious, they probably would keep things on layer one, on Ethereum. And I think there's going to be a lot of unhappy people on Ethereum who, if the losses are socialized to them, will complain. But equally, the socialization of losses is going to be much, much greater if everyone at L2 is cut. I think off the top of my head, it'll be about a 15 % haircut to everybody if Mainnet ETH is also taken into account. But if it isn't taken into account, I think it's like a 75 % haircut. So people lose 75 % of the value of their funds. Not exactly. That's off the top of my head, what I can remember. So that choice is going to be a very, very big one because it ultimately impacts tens of millions, hundreds of millions of dollars and also these other downstream markets as well. **Gabe (16:27):** Yeah, and it also sets the precedent too, where if you're operating with a protocol on mainnet, then you basically assume the risks across the other chains, which this will kind of be a big deal to set into motion if they socialize the losses across the L1. **Harry Donnelly (Circuit) (16:42):** Yeah, I guess I can't think of another example of that. it'll be a precedent. It's a pretty unprecedented situation because AVE has been regarded as the gold standard. It's been regarded that nothing could happen. Smart layer zero bridges were regarded as pretty safe. Normals amounts of volume were going through them. staked ETH was regarded as an incredibly safe asset and all of those assumptions are all falling apart at once because of something that happened downstream. So it shows you the nature of DeFi where the composable Lego bricks of money that you can put together to construct all these really, really cool things also has these really terrible downstream cascade impacts where if something specific and small goes wrong, it can impact everything else. And really it is this where we have two RPC nodes were injected with a bit of code. And now we're talking about a situation where hundreds of millions of dollars have been lost and we're discussing socialization across probably thousands of token holders. and lots of people's lives are going to be affected. And not just that, but I think AVE has had its TVL withdrawn by like $8 billion or so. So there's been a lot of funds being withdrawn from DeFi. It's had a massive, massive impact across everywhere and all because of two different RPC nodes which have been compromised. So it shows, if you're familiar with like the XKCD comic of, there's like a leaning tower of bricks all the way and there's like one tiny one at the bottom. It was kind of like that. That one got knocked. and everything's kind of collapsing in various states at the moment. **Gabe (18:04):** Yeah, and this is like very kind of on point with. crypto and DeFi in general, like with the Terra exploit, we have this composability that builds up and builds up and then if something happens we have these detrimental outcomes. Hopefully these things can be resolved over time and I can see online there's depression in the sense of why does this continuously keep happening and even it's interesting that this arguably could be a central And on that point, I'm curious for you, how do you see kind of the responsibility stacking? Where do you think layer zero is at fault here because they have a maybe quote unquote a weak, guard rails against the configuration? Or do you think it's more of a KelpDow issue where they took the configuration and, did not apply it according to the TVL, you know, over a billion dollars of assets. **Harry Donnelly (Circuit) (19:03):** Yeah, I don't think anyone's faultless here. So layer zero was the one that was, their RPCs were compromised ultimately. Like Lazarus Group was able to get into their RPCs and exploit it and basically sent messages for things that didn't exist. So that was massive issue and ultimately caused everything downstream. Kelptoe. should have not had just a one of one DVN and shouldn't have just relied on a single party for it. And so that was negligence on their part if they're going to be managing and in charge of billions of dollars of other funds. Both of them are now kind of pointing fingers at the other, seems. So there are zeroes saying, hey, we expressly told everyone that you shouldn't use a one of one. It's noted in the docs. If you did it, that's on you. And then Kelpdow is saying, well, like, look, was your RPC nodes that were compromised. And a one of one is fine if the verifier is doing the thing that it's supposed to do. Both of them are to some extent a bit at fault. think Aave, you can also point towards, recently, just enabled ORS ETH as a market, had just enabled the 93 % utilization rate, or sorry, 93 % LTV to allow a lot more funds to be withdrawn. So it's kind of a perfect storm of multiple factors coming together with all of these different dependencies. And now it's at a massive downstream impact as a result. **Gabe (20:20):** Yeah, yeah, I 100 % agree. This is very, very complex exploit, right? And it kind of relies on multiple stages of weakness, even like getting the funds, in a place where like Lazarus Group can spend them and not freeze the assets on chain, right? So for them specifically, yeah, could you speak a little bit more about... like the pattern in which they, after they perform these exploits, secure the funds. think Aave was an interesting case where they took the loan and left the bad debt. But historically, like what happens from here? Like what do they typically do with the funds? And is it common to basically put these loans up? **Harry Donnelly (Circuit) (21:02):** Yeah, the loans not common. And the reason that they did it in this case is because the collateral they were able to deposit, they knew wouldn't be worth what it's supposed to be. And so they took out better assets. Think of it like they put in a bad asset and got out a good asset. And so the good asset is worth a lot more than the bad asset. And that's why they did it, which means that they're happy if the bad asset gets liquidated, if it disappears, they don't really care because they now have funds which they can use and disperse elsewhere. Generally, the pattern of what they do is that super sophisticated, like in the wake of the Bybit hack, what they start doing is they start sending funds across hundreds or thousands of different wallets to try and stop people tracking the trail of it. They put it through mixers, things like tornado cash, again, trying to obfuscate the trail further. They can do a bunch of different things with it. Like sometimes they've gone to like pump.fun. In other cases, they've tried to do trading. think people have been able to see that their trading hasn't been so good. They send it to decentralized exchanges to it out. Eventually what they end up doing is getting it out in lots of different directions and a lot of the time what it does it goes to sanctioned countries and they'll try and off ramp it there. So there's a lot of Chinese OTC desks and money launderers who will allow them to off ramp the funds and then they then use it and bring it back to North Korea where it's then actually used to fund the nuclear missile program. So we do have our world where Magic Internet Money is being used to fund North Korea's missiles and it's just a kind of like very long convoluted train to get there. **Gabe (22:26):** Yeah, yeah, yeah, that's, it's a tough hit on the ecosystem, right? Cause I'm sure no one foresees the like these cascading events kind of leading to geopolitical issues. And it definitely is this downstream impact of managing customers' funds and this type of environment, right? Where we can't just like turn off the lights **Harry Donnelly (Circuit) (22:45):** can't do that. I think it's like, you know, ultimately dealing with billions of dollars here. And generally what people look towards is traditional finance and there's an enormous amount of checks and balances and layers of independent control. And we just don't have that a lot of the time in crypto. And this is a very clear case of it where hundreds of millions of dollars is gone because there was just no independent checks. And that is kind of inexcusable in a way as an industry that we need to be able to fix this better because if we do think this is going to be the future of finance, these things need to be solved. And this isn't going to be the last hack. Like it's not even the last time the first hack this month, like Drift protocol happened earlier in the month and was also. And so they're exploiting all of these things incredibly intelligently. Like these are really, really, really sophisticated attacks which require them to know. incredibly well all the niche details of DeFi and crypto and how these things fit together. Like this is an incredible example where they were able to take advantage of a bridge and a staked ETH protocol and a lending protocol and mix them all together to get out several hundred million dollars on the other side. You don't do that by accident. So we have a nation state adversary who wants to take all of the money. If any of it's exposed, you can expect that if it gathers in large enough quantities, if there's a weakness, eventually it's going to be exploited. And so it to be solved. People need to put the right controls in place. People need to manage the risk properly. Eventually there needs to be insurance around it. And then that's when actual traditional capital will be able to enter en masse and people will be able to be more confident in the space. **Gabe (24:24):** So we covered the hack, the method, the fund recovery and the conundrum there of how the funds will be distributed or socialized across the different users. What else is next after this? ⁓ What are the next things that we're waiting on and who's basically up next to say something? **Harry Donnelly (Circuit) (24:46):** So Aave has just released, I think about an hour or two ago, they released something in the governance forum about how they're thinking about it. I think KelpDow just released a statement which was blaming Layer Zero, but not actually talking about the next steps. what everyone is hoping for is that all of the different parties can come together in some way and figure out a plan, which is able to be a good one because Aave does have a large treasury, KelpDow does have other user funds. There is an insurance fund called the Umbrella Fund. and what is available. So people want to ideally have a way to make most people whole, if not all people whole. Whether that happens or not would require people to stop pointing fingers at each other and basically trying to blame each other, which it seems is the case now. But if they're able to do that and come together and successfully coordinate, then that's the ideal next step of what we find out. If not, what's going to happen is we're going to get a statement from Kelp at some point and how they're planning on distributing the funds or ⁓ performing the haircut. That'll then impact AVE and will impact how the different markets settle. And then eventually everything will clear and the bad debt will happen. People will lose some funds and then things will continue. Obviously. Things won't be the same as previously. The total trust that people would have had in AVE, I'm sure will be decreased as a result. And people will be much more wary of the space because there's a lot of different hacks happening all the time. So it's net negative, ultimately. It's positive in the sense that we now have a better awareness of what happened, but it's net negative ultimately for the space. **Gabe (26:11):** I'm curious for you, do you think there's like a... a unfillable incentive where the Lazarus Group is sitting because essentially they have huge monetary benefit, right, to exploit these unique paths, like highly complex paths. But for like a white hat, right, or someone to be like an adversary, you know, for DeFi and the ecosystem, there's almost not the same incentive to deploy maybe the scale of resources. What do you think is kind of like the way to combat this where Like these exploits kind of fall into almost like a valley, right? Where no one is really looking or kind of has the incentive to harden. Yeah, how are you looking about that? I is there like an opportunity for some type of consortium or, yeah, curious how you kind of look through this. **Harry Donnelly (Circuit) (27:00):** Yeah. So I'm not a bridge expert, but I'm pretty sure there's been people kind of like for a while pointing at the one of one verification and saying that it's eventually going to end in tears. you know, those people have been validated to that extent, obviously don't know the history there. A lot of the stuff, you know, exploit of or PC nodes aside. Most things you can drill into and you can say, okay, if this goes wrong, what happens? If this goes wrong, what happens? If this goes wrong, what happens? And do that very granularly for every step along the chain. And so with the RPC nodes, for example, it's a case of, okay, if someone sends the wrong information to the verifiers, how can we make sure that that is protected? It's don't just have one verifier, have multiple points checking it independently to ideally prevent that from happening. And so at every single point along the What you ideally have is not just a single point of failure, because the thing that's going to be exported every single time is a single point of failure, which in this case is what happened. So what we need is multiple checks and balances. We need the ability to have independent controls at every step. We need the ability for people to have better security measures, protecting things like the keys and things like the verifiers. Everything should be distributed. We need to have monitoring. People need to be able to see what's happening in real time. They need to be able to detect these risks ideally. We need to have automated response, which is basically what we're doing at Circuit because between the point when Kelp was able to take an action and the attack actually happened, it was 48 minutes. Circuit wouldn't have been applied in this situation, but it's representative of that. Humans can't react quickly enough to these attacks because they're happening at machine speed. So you need to be able to automate the response because you can map out in gameplay what are the different scenarios that can cause an attacker and alert B and then take an action based on those. And then you need to be able to ideally just recover if things go bad. So if shit hits the fan, if the different infrastructure that using goes down, how can we get our funds back? So those are kind of like different nested layers you can put together. And at every point along the way that you're looking at where things could go wrong, ideally you can have as many of those together as possible to stop it from happening. What ideally would then happen is that if you're able to say, the proper security controls are in place, we're very confident we spend the right money on the right tools and the right people to make sure that these are there, then you can have insurance on top. And that's what ultimately gives people much more reassurance is that even if things go wrong, you'll get your funds back. The issue being is that insurers look at hacks like that and say, wow, that's a bit crazy. How could I insure that? Which they'd be quite right, because they'd be insuring something six layers deep, which they don't have the technical expertise to go and find. So it's a mixture of people in the space who do have the technical expertise really being handed about it and being pretty clear with folks that you can't just let it fit there. You need to actually spend money on it. The space maturing enough for people to say, OK, we can't just move fast and break things. We need to actually make sure that the breaking things doesn't lose us hundreds of millions of dollars. And when that happens, it allows the proper controls to be there to allow actual capital to then stand behind it, which then allows people to get much more confidence in actually doing things at scale. So that's the way I view it. **Gabe (30:06):** ⁓ yeah, Harry, you explain to us what your customers are saying and how you see this sort of thing at your **Harry Donnelly (Circuit) (30:15):** I think a lot of it is just uncertainty, ultimately, because what you've done with crypto is that you've taken the most complex, difficult parts of both computer science and finance and then mingle them together in such a way that almost no one can understand either, which leaves you with a lot of unknown unknowns. And I think that's scary for people. Not I think, it is scary for people. that ultimately, if you're unsure of are the different risks and the different attack vectors that can happen, and new things can pop up all the time, such as this. sure, I'm not just sure, I know that the different curators, for example, in the different vaults, our chaos labs, I think, who's a risk manager, these things weren't flagged as a big of risk as ultimately they ended up being. And so when you have financial risk managers who are also in charge of technical risk, sometimes things can be missed or sometimes things can't be seen as clearly. And so... Ultimately, you need people who do understand both sides. You need people to understand the financial side. You need people to understand the technical side. And you need to have tools that solve for both things. And that's part of what we're doing at Circuit is that we've built a incredible team of people who understand both the kind of deep engineering side of it, but also the financial engineering and how these things get impacted downstream. And what we've built is think of it like automated controls or automated asset extraction that allows you to sweep funds to safety before humans have the chance to react. One of the biggest patterns that we saw across these attacks is that they happen so quickly people can't respond in time. So Kelp is an example of what happened in 48 minutes. We wouldn't have been able to help in this case but it's representative of people are not able to move at machine speed and the attacks that we're seeing are just getting quicker and quicker and quicker. And so if you just stand a chance of getting funds out, even for example, with Aave, if you had wanted to get funds out before everything froze, it happened really, really quickly. And this is where we could have come in and allowed you to sweep those funds and withdraw those funds automatically before they got trapped. And so that's what Circuit's doing. And we're working with some of the best folks in the space, particularly on the insurance side, to help. make it possible to de-risk the space and ultimately make it insurable and then make it possible to move real institutional capital on chain and then have the future of finance actually be defi. **Gabe (32:26):** amazing. Well, Harry, thanks for coming on and take us through the forensics of the hack and hope to have you on soon. **Harry Donnelly (Circuit) (32:32):** Sounds good, man. Appreciate you having me. **Gabe (32:34):** So --- # Stablecoins as Geopolitical Instruments > Shoal Signal episode. Guest: Chunda McCain (Paxos Labs). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-04-23 - Video: https://www.youtube.com/watch?v=eIaoosFHZRU - Canonical: https://shoal.xyz/research/episodes/stablecoins-as-geopolitical-instruments/ - Keywords: stablecoins, crypto, DeFi, restaking, yield, RWA, tokenization, infrastructure, Bitcoin, interviews ## Transcript **Gabe (00:00):** everyone, this is Gabe from Shoal Research and I'm here to bring the next episode of Shoal Signal. here with Chunda, the co-founder and CEO of Paxos Labs. And actually I met Chunda a couple of years ago at ZuZalu, which was Vitalik Buterin's network state. and Chunda would come out of the dorm rooms every day at breakfast and lunchtime and then go back into the dorm rooms because he was grinding away on his startup. So yeah, looking forward for him to share a little bit about that and his transition into Paxos. Chunda, please share us a little bit more about what you're doing and your transition from Ion into Paxos. **Chunda McCain (00:23):** You Yeah, 100%. Well, and I haven't thought about Zuzalu in a while. Sometimes it still is if that was a parallel universe. And for anyone who does get that reference listening to this, honestly, reach out. I always like to talk to folks who went there. It's a very fun, unique experience we can all reminisce on. But I digress. **Gabe (00:43):** Yeah, 100%. **Chunda McCain (01:01):** Let's see, we'll start with my journey. mean, if we want to start with the ION days, can jam there. I guess this all started when I decided I wanted to build myself in DeFi. been part of the crypto ecosystem following it since 1718, working in it since 2020. And in 2023, there's just kind of this intersection of a whole bunch of serendipitous moments that made me realize that, you know, at that time would be a really interesting time to build out a DeFi protocol focused on lending and credit around a new type of asset. At that time, was staked and restaked assets in DeFi. But one thing we quickly ran into was the realization that although demand for financial primitives was wide, there was a bigger gap when it came to offering those financial primitives in a clean packaged kind of methodology to the platforms where users were actively investing in these products today. And so we kind of pivoted into a new product line called Nucleus, focused on basically building out these tokenized yield strategies as well as branded stable coin issuance. And it really aligned with what now is the vision of Paxos Labs, effectively trying to ask and answer the question, once enterprises and the largest enterprises around the world take the demand that's existed around digital assets and take that first step to bring it onto their platforms, what do they do next with that capital? And that's the question that we're trying to answer here at Labs. But to take a step back, I can give us a little bit of a broader strokes breakdown of Paxos, Paxos Labs, and the whole, what I like to call a Paxos Extended Universe. Paxos was started about 13 years ago by... our CEO Chad Cascadia, and he was focused on this problem of how do we provide access to crypto rails to the largest amount of people possible, right? And the realization came that you need to do two things. One is you need to first start by enabling people to get that first foot in the door with what we call first step capabilities, the first thing you want to do when you interact with crypto, buy, or sell digital assets on an off ramp and access stable coins. And then simultaneously you need to meet people where they are today, which is at the largest enterprises, financial, consumer and otherwise, that are actively using different types of consumer products and then find ways to embed crypto into those experiences that benefited those products and those enterprises. so Paxos historically is built off suite of what we call first step capabilities of those first things that enterprises want to do when enter into the ecosystem, which is really consolidated into those three core use cases. Buy, hold, sell digital assets that aligns with the crypto brokerage offering that exists at Paxos. So if you pull out your phone today and you go on Venmo or PayPal and you buy Bitcoin, that's settled on Paxos Rails. Similarly, the second pillar there is orchestration on and off ramp. So if you're a merchant on Stripe that wants to accept stable coins and you turn that feature on on Stripe, that's settled with Paxos Rails. And then finally, what Paxos is most known for, the issuance business, right? So USDG, PYUSD, PaxG, and many other assets throughout the years have sat at the bedrock of the Paxos business. On the lab side of the business, we're focused on, all right, all of these assets are great. And they're the great first step for enterprises. How do we go and enable those assets to then be active in the ecosystems that they exist in on the platforms that they exist in? So we focused our mandate on another three pillars, one, which is on-chain stablecoin movement, stablecoin orchestration. Second is generating yield on stablecoins and ⁓ other tokenized assets like gold. And then third is enabling on-chain credit. and lending and borrowing capabilities. And so really combined, you have this full stack experience where from the first step you take into crypto all the way into the 10th year that you're building out your platform, you have a suite of capabilities that help enable you to build out novel solutions for your platform. **Gabe (05:11):** Got it, got it. So you guys are really taking customers end to end, you know, from like zero crypto experience, and then your Rails can support this holistic stable coin experience over like an indefinite period of time of scaling. **Chunda McCain (05:27):** 100%. The idea of saying I like to use is I don't sell capabilities, I sell solutions. The way that we think about building out solutions here is centered around, we look at problems that enterprises have. Hey, my cross-border remittance is expensive and slow. Hey, I'm not able to monetize these dollars on my platform. Hey, I'm a payment provider and money keeps coming in and out. I want to find a way to retain it on platform. crypto solutions which are just better financial products better financial infrastructure to go and address those problems that these enterprises face. **Gabe (06:01):** Yeah, and this kind of transitions into the meat of some of the stuff that I want to personally understand. And from your experience, you have this holistic enterprise perspective of the stablecoin landscape, who the players are, regulation, genius act. So for this in particular, I'm curious about the geopolitical landscape and what is the power that stablecoins actually hold, **Chunda McCain (06:08):** Yeah. **Gabe (06:28):** especially in the context of USD coins, ⁓ USDC and USDT, PYUSD, these US denominated stable coins, why are they so strong quote unquote? And kind of what is the geopolitical lens or application of these coins in general? **Chunda McCain (06:32):** Mm-hmm. Yeah, so I think like, you know, there's a few reasons why stable coins just in and of themselves. And, you know, you see this in the adoption of ⁓ assets like USDT, which don't share back yield, but yet are still propagated around the world. One of the value propositions of stable coins is just access to the stability of the US's currency, right? And I think being in the US, it's pretty easy to discount how good we have it from a currency perspective, but. There's a reality that ⁓ globally, right, US debt and thereby US currency value is effectively propped up by nation states the world round. And so what we're doing here is we're effectively enabling the average, quote unquote, consumer, you call it, in all these jurisdictions that don't have access to direct directly purchase US debt from, you know, directly from the US Treasury, the ability to tap into that by leveraging stablecoins. And the thing that I actually think is a really interesting and pretty understated point when it comes to stablecoins, and specifically US stablecoins, is I think they act as a forcing function to bring the entire world onto crypto rails and to accelerate into crypto even quicker because What some regions are recognizing is that their demand for their currencies is actually decreasing because of the growth of stablecoins in their regions. And so as a byproduct, they have an incentive to build out more robust on-chain rails for their own currencies to justify the ability for their citizens to be able to hold their own currencies. We even see like a pretty interesting cases in like Brazil, for example, because they have a very high rate environment. They're in some cases you can see people building out enterprises that are focused on enabling that high rate environment and their general currency stability to actually act as a yield vehicle. And they're tokenizing that as a product because I might be, you the number might be slightly different than today, but I believe they're the rate of that they're quoting on sovereign debt as somewhere in the 13 to 15 % range. And so if you're hedging out the delta between that and the value of US currency, you actually have a pretty attractive yield product. And if you put that on chain and now you can distribute that globally, you create these really interesting dynamics between how nation states can effectively leverage their own native debt demand in order to create these bespoke products that now they have a platform to distribute that globally. Because historically, if Brazil was in a position where they were like, hey, I want to find a model to enable the global market to access this type of rate trade, it's a lot more difficult. It requires a lot more upfront infrastructure. And also, it's less scalable, right? Because you'll have less firms who can offer those solutions and can offer access to that trade. versus now with stable coins, you can have a digitized Brazilian dollar, you can have a digitized American dollar, and you're able to go and facilitate these really novel strategies. One thing I'm personally interested in is seeing the productization of the historical yen US dollar basis trade and seeing what we can do with that once we're able to create more digital rails to enable that basis trade to continue. **Gabe (10:16):** So you're saying the US can kind of maintain dollar dominance by short-cutting the access to treasuries through the stable coins. And then foreign nation states or other countries outside the US are tokenizing yield opportunities and then they can sell those and that gives other countries access to their currencies as well. Is that? **Chunda McCain (10:38):** Yeah, you get a lot more dynamic and active in an international rate environment that becomes more reflexive due to investment demand on the basis of underwriting sovereign debt, which is fascinating because these markets have existed historically, but they haven't been as dynamic as they can be and also as widely accessible to the general audience, right? Maybe if you work at a trading firm, everyone knows the yen dollar basis trade, right? But if you go and ask any person on the street, how would you go and access that? They wouldn't know the first thing. But what stable coins and digitizing currencies and dollars the world round allows you to do is to open the door to enable more public access to these types of kind of interrelated currency and debt relationships that historically just have been kind of mitigated to the nation state level and then large investment firms that operate near that. **Gabe (11:41):** So for these other countries, what is the reaction that you're seeing? Because obviously, if you're a country and your leverage nationally is the currency, and you have dollar dominance growing, and the ability to transact like USDT, especially in countries and in regions like Southeast Asia, is very dominant. What is the reaction of these different countries and, you know, is it kind of, are they accepting it? We've seen some like bans plenty of times, but yeah, yeah, what's kind of the reaction? How does that? **Chunda McCain (12:10):** Yeah. I think I've seen three different reactions. So one of which is the one you've you've mentioned, which is just banning it. Right. ⁓ Banning access to stable coins. is, you know, China's done this or they've been cautious around it. There's certain countries in Africa that have done this. Right. Just outright bans on stable coins because of the threat it poses to their to their national currency. So it's one route you can do. The other route that we see is ⁓ It forces that nation to lean in more to digital assets. I think you see this sometimes in South America, sometimes in Southeast Asia, in the Middle East a little bit, where you have these nation states recognize that, okay, this is inevitable, right? The digitization of all capital is inevitable. What we need to do is accelerate towards it so that way we can compete on a level playing field. with the US, which has already gone a decade plus long head start on building out the infrastructure to support this. So you see a lot of investments being made there in certain regions where they're like, OK, this is an opportunity for us to go catch up and get ahead of these nation states that are banning stable coins. And then there's a third model that I've actually found kind of interesting. This has been in East Asia is actually primarily where I see this. where the legislature fully understands the value of stablecoins, even US stablecoins, and welcome it in. In East Asia, a lot of those countries have very, very tight capital controls on currency demand in order to maintain specific rate environments or to balance import-export demand. And so what you see there actually is this kind of interesting like centralization on specialization of goods and production that sometimes occurs. And or you see new markets be generated for demand for the underlying currency or strict capital controls on money that flows in and out. So I've seen kind of like two different outcomes in East Asian nations. One where they're like, all right, let's take an approach where we take a harder look at what is generating currency demand and let's focus on leaning into that to basically like hedge out the risk of supply shock from US dollar stablecoin demand. And the second thing that I've seen that's been kind of interesting is saying like, okay, we'll allow US stablecoins But we're going to be extremely careful about the tokenization of our own asset. And what we're going to do is we're going to maintain strict capital controls of the tokenization of our native currency and have a very like iron grip on the firms that are doing so to maintain and basically react to the moving demand for US dollars in their region and then turn on and off levers at the enterprise level to generate demand for their own asset in a digitized manner. That I think is this really interesting middle ground of like trying to be cautious and not necessarily fully accelerating towards digitization. But understanding that digitization is inevitable. But there's also this lever if you really want to maintain capital control over your currency value on your own currency by controlling how digitization occurs for your own currency and then also potentially moving that lever forward or pulling it back based on maintaining that balance you want to strike. This is a really interesting model that as I've talked to some, some nation states who are approaching this type of issue that they're thinking. **Gabe (15:37):** if you can share and you know, try to accordingly who were like some of the sophisticated actors that you see maybe at the nation level or just like enterprises broadly that maybe we wouldn't quite think was the case. **Chunda McCain (15:49):** that are adopting stable coins. **Gabe (15:51):** Yeah, yeah, not just adopting, but also kind of like navigating the landscape in a sophisticated manner. **Chunda McCain (15:57):** Yeah. So the one country I was thinking about when I was talking about this type of capital control is actually Korea. I spent a decent amount of time. I actually spoke on the their equivalent of the Senate or representative floor last time I was there about the concept of it was more on RWAs. But I spent a lot of time talking with people there and some of the legislators there on how they were approaching stable coins. And the really interesting kind of theme that was that resonated was, hey, currency demand in Korea is is down to a science, right? They're very, very conscientious about managing currency demand in order to maintain stability on the currency on the basis of their import export balances. And so when they look at digitization of the won. they're thinking about it within the context of that historical framework and saying like, okay, what are the levers we can push and pull here to make sure that we don't over induce want supply, but we have some controls over retaining leverage, but also enabling propagation of demand of one for like when it's necessary. And I thought that to be just a really, I mean, their legislation. and legislature has been really stable going forward ever since the previous president came into came into their position. And I think they're taking a really measured and conscious approach to this that I find a lot of nations aren't really thinking that deeply around how digitization could affect their own currency demand and really building out strategy around it. That's a little bit deeper than like complete ban or just fully lean into it and just figure out what happens from there. **Gabe (17:31):** Yeah, yeah. That's pretty interesting because historically with digital assets, they've always been pretty particular with inflows and just currency leaving the country in general. We've seen with the exchanges and the kimchi premium of Bitcoin and all this stuff. So yeah, now that you mention it, it kind of makes sense. **Chunda McCain (17:55):** Yeah, they understand the market, right? And so they understand how exactly to take a measured approach to navigating it with nuance. **Gabe (18:04):** Yeah, yeah, that's interesting. for these customers that you guys are working with, these enterprises, like what is the flavor of... what these different entities look like. Because if we're kind of thinking of like, Paxos is working with some customers, maybe it's like a Coinbase, right? Or a Kraken, et cetera, Binance, But behind the scenes, maybe these can be like sports teams or all these other different types of entities. What is the appetite and kind of the breadth of... folks looking for stable coins, whether it's like a nation state or a sports team, essentially. Yeah, curious. **Chunda McCain (18:39):** Yeah, we have spoken with everyone in that gamut from sports teams and leagues to nation states and FIs and PSPs and payroll providers and neo banks and everything in between. DeFi protocols, blockchains, you name it. The way I kind of think about customer segmentation is kind of split in two. And I like to think about it in a problem solution orientation, right? So you usually have what I call like product execution parameters and that sits at the specific ICP. Right. When I'm thinking about how do I activate users on a payroll platform versus how do I activate users on a NEO bank. Two very different experiences. But what I can do is kind of group all the enterprises we work with into two buckets. There are enterprises that maintain a a flow of capital, right? Capital moves in and out with them. And there are enterprises that ⁓ store capital or custody capital, right? And you can get the high level split on their mandate is effectively split based on those objectives. So for those who are managing the flow of capital, think of the payroll companies, payment service providers, credit card issuers, a lot of what they're thinking about. is retention of capital. How do I help my platform retain the billions or millions or tens of millions or trillions of dollars flowing through my system? How do I help them find a reason to stay on my platform and then add value to my enterprise? Now, like I mentioned before, what that looks like is a little bit different depending on the client, what I'm gonna say to a payroll provider versus what I'm gonna say to payment service providers. two completely different things on what that's gonna look like on their app. But the mandate is the same. On the other side, what we're really looking at when it comes to custody or collection of capital is two things. We're looking at maximizing client or user retention, and we're looking at maximizing margins on client dollars, right, or user dollars. And so for them, they're thinking about questions. You know, if I'm a bank, I'm thinking about, hey, if... I don't have excess demand to borrow and I have idle cash on my balance sheet. That's cash that could be utilized that I'm losing money on. How can I further activate this capital? If I'm a NEO Bank, I'm asking how do I enable my users to stay on my platform versus, let's say even just going to use DeFi directly. If I'm an exchange, I might be thinking about how can I enable people to leverage stable coins. to maybe subsidize some of the cost of trading on my application. So there's a whole bunch of different ways that desire to retain users and increase margins exists in that segment of clients, but that's generally the higher level mandate on that side. **Gabe (21:26):** Okay, got it, got it. And for these clients, basically you have like different use cases per segment. And then for like some of these active segments, what are like the levers essentially that you can pull on? And maybe you touched on this a little bit earlier, but you know, if I'm like a basketball team, right? Like what is the actual application of... **Chunda McCain (21:35):** Mm-hmm. **Gabe (21:51):** a stable coin within my institution, right? That's different from a gift card or something, right? **Chunda McCain (21:54):** Yeah, 100%. And that's where we get into the world where, like I said before, we shouldn't be selling capabilities. Don't sell a staple coin. Sell a solution to a problem you're facing. If I go talk to a basketball team or when I've spoken with sports teams or consumer platforms that kind of look like that in the past, you usually get a question around, all right, I have So much value flowing through my commerce system, right? There's merch, there's tickets, there's, you know, meet and greets, there's, you know, you name it, And so how can I go and find a way to further, one, increase spending in that ecosystem, two, increase my margins in that ecosystem? and three, create levers to increase user engagement. And so if I want to increase spending, what could I do? Well, I could discount certain experiences if they pay with a stablecoin backed by, let's say a pack of stablecoins or something of that nature, right? Because now if I have my own branded stablecoin in that ecosystem, I'm generating dollars on that. The user is helping me generate dollars and they get kickbacks in the form of discounts on some of their purchases. Or let's say if it's a year long pass, right? because now I'm booking out that revenue for a year and I know exactly how much that dollar is worth on the books for that year as it's being utilized in my ecosystem. Another thing could be, hey, if I want ⁓ users to be able to have access to like unique opportunities, maybe you want an embedded wallet into your platform that has your own branded stable coin. Let's say if users stake that stable coin and generate additional yield, which generates additional margin for the enterprise, then they get access to unique experiences. And so now with embedded wallets, with a stable coin, with stable coin yield, you've created a fan engagement experience. Right. And so it's about using the access to capital as leverage to be able to spend and generate more value for your your users and your clients and your fans. That is really the centerpiece of things like a consumer engagement exercise. Because at the end of the day, really, if you just think about it from a simple first principles perspective, what using stable coins, what crypto does and what DeFi does holistically is it enables you to generate additional revenue with the same dollar and save money that you would spend on some of the inefficiencies of the traditional financial system, which means it's just more capital in your pocket and what is the value of capital in your pocket? You can reinvest that to build a better product, better service, better platform. **Gabe (24:33):** Got With these different levers, guess kind of to to re-pick up like the the geopolitics piece and kind of like at the national level, why do you think some of these larger countries, maybe like a China, why haven't we seen like stable coins, you know, flowing maybe even in small adoption, right, across different countries? Yeah, what do you think is kind of the hold there? Is it that the USD is just so powerful global? the market share, right? If you look at USD coins versus other countries, even the EU, it's marginal, right? So yeah, what do you think is kind of the stagnation on that piece and kind of the growth and are you guys looking at this as products that you're taking seriously? How is that? **Chunda McCain (25:17):** Yeah, I find them very interesting. think the question I have is probably the question that is in every nation states mind when they are experimenting with this. Also, I'd give, I think China a little leniency. think they use Hong Kong as a bit of an experiment, experimentation venue to explore different initiatives, different stable coin initiatives, which they've done over the years. And I think the biggest question that any, whether you're a nation state or whether you're, building out a bare metal stable coin yourself is what are the demand drivers for this asset? Where are and why are people going to access this asset? And the question I think at the nation state level you have to ask yourself is what primarily if you're not a reserve currency, which is just the US, demand for your currency is driven through the sale of goods and services that are unique to your geography industry it's. Right. And so if you're operating under that function the question should be OK if my wedge if my demand driver is my geography industry et cetera how does tokenizing my currency help drive that demand further. The question the answer might be it doesn't. Right. Right. If say you know you can imagine a world where like let's say you're the primary. ⁓ demand driver for your currency is tourism. There may not be a clear path to say, okay, well, you know, is tourism demand really going to justify, like, to have some way to accelerate tourism demand if I have a stable coin? It could be hard to pin that down. But if you have a more diverse economy or if you have interesting ways to structure a rate environment, like I talking about in Brazil and Japan, then you're in these positions where You can you can look at a Brazil and you can look at Japan and say like they're actually very interesting investment level structural demand drivers for these currencies that exist outside of the sale of goods and services. And so if you can generate those types of incentives from an economic planning perspective there's really large interest in experimenting with stable coins. And you see that reflected in those jurisdictions as well. The growth of Brazilian stable coins is one. the larger regions in South America that are issuing their own digital currencies. Similarly in Japan, they've been opening the door a lot to issuance of Japanese currency, Japanese tokenized currency. In fact, I believe there's news recently about tokenized yen project being worked on. And it's because they have these economic levers to create novel demand drivers for the currencies that have already existed historically, and then they'll just lean into it further by tokenizing it. **Gabe (27:47):** And then you guys just came up with a new product, the Amplify Stack, right? And yeah, if you can kind of chat a bit about what it is and how you plug into these countries and to these different enterprises and how you're supporting them through this new product. **Chunda McCain (28:03):** Yeah, so like I mentioned before, the mandate that we're focused on on Paxos Labs is really to answer the question, what do you do once you bring stable coins, once you issue a stable coin, once you bring digital assets, whether RWAs or assets endogenous to crypto onto your platform, what are you going to do with them? How do we make sure we make those implementations in that first step successful? One of my biggest fears is I think we're given a window of opportunity to justify the value of our existence as an industry. For those of us who have been around for a while, back in 2017 and 2018 and 2019, there was a concept of enterprise blockchains and enterprise use cases and people really exploring it. And there was a lot of capital investment into it, but that capital investment didn't lead to any results. And so what we're focused on is basically that second leg of... All right, let's make those capital investments to bring these assets onto your platform. But let's make sure we drive real business results once you make that investment. And so the Amplify stack is focused on providing the three pillars of what we call like activating your platform. One is Mint enabling branded digital dollars on your platform where you can retain all of the value of the dollars on your platform through a native stable coin. Second is earn where you're able to deploy that stable coin into additional yield generating opportunities to further retain your users. And then the third is borrow enabling that stable coin access credit or the digital assets under platform to access credit. So that way they can ideally access credit in your native stable coin and then do more with it. And if you notice the idea of the Amplify stack is that you're not supposed to just take one piece out of the stack and kind of run with it, but it comes as a bundle. And in bundling all those capabilities together, you get a full stack holistic digital asset experience that is just much more robust and much more useful to the end user on your platform. **Gabe (29:56):** Got it, got it. Yeah, I think this is helpful to understand, at least for me, because I think kind of when we think about stable coins, it's like either yield or like mint and burn, right? And not kind of the extended. business tools, to conduct business, but then also for teams to amplify whatever they're doing on the product side, whether like basketball team or like a nation. And I'm curious, as you're seeing this entire landscape of players and of all shapes and sizes, right, where is the value kind of bubbling the most? where would you say like, hey, yeah, you should kind of pay attention in this corner, under these rocks, right? Where is the interesting things happening and what does it look like? **Chunda McCain (30:43):** Yeah, I think to me there's just kind of a few sectors in the market where I think things are happening. I think in FIs, like I have like a personal prediction that I think, you know, in 12 months, over 50 % of the largest FIs in the world will offer crypto assets directly on their platform. I think it's inevitability. I have very high confidence that that will be the case. And so I think if you look at the top of the market, that's where you're going to see a lot of activation energy. If we go down market, right, and we look at, all right, let's look at the fintech sector, let's look at the payment sector, let's look at neo banking. I think where you're going to see an expansion of demand is around the use of DeFi for novel use cases, right? I've gotten demand from PSPs for ⁓ use cases such as credit lines for their merchants embedded into their payment flows. I've chatted with Neobanks who are interested in deploying directly into DeFi are asking like, can I find compliant scalable methodologies of deploying into on-chain yield? And so I think for us and I think for the industry at large where we're like laser focused is really that like step down. from the top line, although there's a lot of investments in the top line as well, step down for that absolute top of the market, because that's where a lot of the innovation is happening. That's where a lot of the next steps are happening, because all these platforms have usually already taken the step to embed stable coins or digital assets, and so we're really seeing them work through, okay, how can I get creative to do the next thing? Because the next thing isn't just like, all right, I do step two, I do step three. It's like, no, I build, you know. WXY and then someone else decides to build DEF and those will look like different things. They'll resonate differently in the market. They'll use stable coins and crypto infrastructure underneath, but they'll express themselves differently in the user experience and that's what I'm really excited to see. **Gabe (32:35):** So these, just to restate, these large financial institutions, like traditional institutions, you're saying that essentially we're going to see like a massive in the next 12 months push on stablecoin adoption. **Chunda McCain (32:47):** I think stable coin and digital asset, they'll either be issuing digital or stable coins or enabling digital assets directly on their platform. **Gabe (32:55):** Got it. And then on that similar vein, especially in DeFi, we have these like super novel financial instruments, Like, you know, tokenized basis trading and something like an Athena on Solana. There's quite a few like ⁓ money manager stable coins. And I think they're trying to move away from the term stable coin, but essentially a fund managing a strategy and deploying it as a coin. Perena is one that comes off the of my head on the Solana ecosystem. **Chunda McCain (33:15):** Yeah. **Gabe (33:22):** But for these types of assets, what are you seeing these institutions, the large institutions are going for? Is it kind of like the vanilla model or is there appetite for these more like strategy-based assets? **Chunda McCain (33:36):** Yeah, it's a good question. I mean, if I'm being frank, think the market just really isn't there yet to go up the risk curve. When getting people acquainted with the intricacies of a new financial system, a new financial operating system, there's a lot of risk just in operating that system in and of itself and being a part of that system. If you start to add, you know, endogenously emerging yield products from that system, you start to go into a realm where people are all right, like, let's let's pull the brakes like I'm taking these, you know, I'm taking these baby steps in this. We can't we can't start running and go, you know, jump in the race car and go full throttle. Right. So I think, you know, they what is interesting about that sector of the market is I think they're doing a really interesting job of blending off chain sources of yield with the benefits of on chain rails. And I think there's a lot of demand for more crypto native audiences and companies to invest in those types of products because they understand the risk. They understand these models. But now they get access to these traditional finance or these markets in traditional finance that was previously only accessible to really large capital allocators. I think that side of the market is really interesting. I'm paying a lot of attention to what's going on there. But I don't expect the demand to be driven from the other side just yet. **Gabe (34:58):** So really you're saying like these kind of like vanilla opportunities where the use cases scope down essentially to like, you know, USD backed stable coins and then those turn into their own products. **Chunda McCain (35:14):** Yeah, know, lending, can get into, you know, we call staking for digital assets. think people are coming across the bend on that. There's gonna be a lot of activation energy there. We go farther down the risk curve, think ⁓ people are gonna start pulling the brakes on it. **Gabe (35:27):** you Got it, got it. And so on that piece, what do you think is like a counter narrative? Like what are people talking about that you think is just garbage or fluff? Maybe it's not garbage, right? But like what is the stuff that's fluff? **Chunda McCain (35:36):** Mm. Yeah. so, so here's a piece that, you know, I've just have, I've tried to wrap my head around it. I've tried to really get on the train because it would be fantastic. I mean, for our business, but also just holistically for the industry is agentic payments. and the thing I just struggle with is like, give me the sustainable systemic demand driver for that. That isn't paying for APIs that I could do with a ramp card that does the same. Right. And sure I may nick a few bits off the yield while it's sitting on my on my balance but it's not I don't see what I'm doing beyond that again. It's like what's next. Right. What's next. If there's nothing next and there's no systemic demand driver there then it's not super interesting to me. I think once we see commerce platforms and consumers start transitioning to doing more agentic based purchasing and financing and things of that nature. I think there's a world where that exists. I think the timeline for that is indeterminate. Until we have structural demand drivers there, I remain skeptical. And the heuristic I like to use is ⁓ would you give open claw your credit card information? And the answer most people would say is absolutely not. **Gabe (36:51):** Yeah, that makes a lot of sense. on the agent side, the thing that I kind of question is what is the use case in which an agent needs to talk to another agent as opposed to a service? And it's almost like there might be this context-based opportunity where I have context and I put in my agent and someone else has context and they put in their agent and there's a unique experience that is not available. **Chunda McCain (37:20):** Yeah, we're like the agents are acting as the intermediary. **Gabe (37:23):** Yeah, yeah, it's a bit early. It's a bit early. **Chunda McCain (37:23):** Yeah. Being early is just as important, or being on time is just as important as being right. Or at least sticking around until you can be right is very important. **Gabe (37:36):** Yeah. So institutions are not asking, at least in your conversation, no one's asking for, you know, **Chunda McCain (37:41):** I have had not a single conversation from nation-state to religion to FI to DO Bank to ask me about if we support agent payments. Now maybe I'm talking to the wrong enterprises, but I don't see the demand in market. **Gabe (37:57):** Fair enough. That's good insight. Cool man. I think that's pretty much, yeah, that's kind of like the rap for me. The stuff that we covered is for you in general on the geopolitical side, the... these are your customers, right? These nations are your customers and kind of like the US has its angle. The other countries, know, nationally actors have their angles and how they're kind of reacting to this pressure, this pressure dynamic. And then that flows into kind of like your day to day customers, whether it's like, you know, enterprises, financial institutions, even up to like sports teams. Is there anything else that we should know kind of within that stack that we necessarily haven't covered yet? **Chunda McCain (38:38):** Yeah, well, the thing I'll clarify there is I don't think we necessarily internalize nation states as our direct customers. However, they definitely are creating environments in which we see more customers arising in those environments because the lever that nation states get to pull is political legislative and those political legislative levers then translate into enterprise demand for products, enterprise demand for services, enterprise demand for capabilities. Now that being said, in that suite, think the thing I'll leave you with here is I think... One thing I am very much kind of a proponent of, and we have an internal philosophy of, is being able to provide a unified platform that kind of abstracts away the complexity of a whole of the minutiae that get involved in financial operations. To provide... Crypto Rails, but not for the sake of Crypto Rails. I think that's something that a lot of folks kind of fall into the trap of. But for the sake of the fact that Crypto Rails are just a better way to operate finance, right? And so my philosophy is, I didn't come into this industry to sell everyone on crypto. I came into this industry to sell everyone on a better way to do finance. A way that... empowers the user, way that empowers self sovereignty and ownership, a way that decreases the amount of middlemen and the amount of friction that exists in legacy systems, and also offers a more equitable system for everyone involved. So I'll leave you with that. **Gabe (40:17):** Well, thanks, Trin. We see you working hard doing the gauntlet ⁓ since the Iron Man. Yeah. But great to have you and hope to have you back on soon. Yeah. See you. **Chunda McCain (40:22):** I'll my best. Alright guys man, always a pleasure chatting. Catch you. --- # Autonomous Agentic Commerce: Micropayments, AgentCash, x402 & MPP > Shoal Signal episode. Guest: Shafu (Merit Systems). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-04-20 - Video: https://www.youtube.com/watch?v=vVmyBfGqM7Q - Canonical: https://shoal.xyz/research/episodes/autonomous-agentic-commerce-x402-mpp/ - Keywords: AI agents, agentic payments, x402, micropayments, interviews ## Transcript **Gabe (00:01):** So Shafu, can you give us an understanding of what MPP is, X402, and these agent payment protocols, and this will set the stage for the rest of the conversation where we can get more into the nuance. **Shafu (00:13):** Yeah, just imagine you have an API, right? And without X4.2 or MPP, you have an agent that wants to access that API. The agent just can't, right? Because you would need to sign up, get an API key, pay a subscription, all that kind of stuff. ⁓ X4.2 MPP completely changes that. So you have your API, you put X4.2 or MPP around it, and now it's paper request. So the agent goes ahead and wants to access I don't know, some API, right? And it just can access it. It pays with stable coins and it gets that data back. So basically it gets rid of paywalls on the internet. And what's beautiful about X4Tune MPP, in my opinion, is they're, first of all, they're open standards on top of HTTP and they're extremely simple. They're super thin. Basically what they include is how much Do you need to pay to access this? How are going to pay this on what chain and what currency? And that's pretty much it. **Gabe (01:21):** And can you explain a little bit of the nuance between X402 and MPP? Are these the same exact protocols for accessing APIs or is there some technological differences, benefits or side effects from both? **Shafu (01:37):** Yeah, from a high level there, they're very, very similar. I guess the biggest difference is that X4.2 came out of the Coinbase ecosystem and MPP came out of the Stripe and Tempo ecosystem. ⁓ High level, they're solving the same thing. There are some nuances in the technical details, some little features here and there that are different, but from a high level perspective, they do pretty much the same. **Gabe (02:07):** Got it. So just to step back, X4.02 and MPP, these agent payment protocols allow agents such as like a cloud or cloud code or codex tools, any types of agents to access APIs. without having to authenticate and then they can use stable coins. And I think it's interesting that Stripe, as you mentioned, is participating in this landscape. So this is like a big service provider. I know in San Francisco they have a billboard that says they process like 1.3 % of the global GDP. They're in the financial payment space, right, for a long time. Why do you think that they're launching this with stable coins as the rail? Like, why isn't this possible just with using a credit card? Like, why can't I just give my agent the credit card? What is the unlock or what is the change here where stable coins are the payment rails? **Shafu (03:04):** Yeah, it's a great question. The problem with credit cards is you have fixed costs. I think it's around 30 cents ⁓ and you have like 3 % on top of that. So just imagine you want to access an API which costs like sub one cent, right? Now you need to pay 30 cents just in credit card fees to access that API. So that just doesn't make any sense. And that's where stable coins come in. They're perfect for Micro-transactions, they're instant, you there are no refunds, all that kind of stuff totally goes away. It's extremely cheap. It just works out of the box. ⁓ So in terms of credit cards, it just wouldn't work for ⁓ X4 to an MPP. Maybe it works for like high ticket purchases. So just imagine your agent goes off and buys like jewelry or like a car or something on Amazon ⁓ or somewhere else. Maybe that will work, but where we see the most use out of X4.2 and MPPs, people paying for API calls. And these are extremely cheap, so it just doesn't make sense to do with crycarts. **Gabe (04:19):** Yeah, it seems like there's like a convergence right now of, you know, capable agents, stable coin rails being pretty established. And then this new open protocol for transacting micro payments through the APIs. Kind of the important thing here is the supply, right? What are some of the projects or service providers or tools that you've been seeing or think are some of the best ones that are on the other side of the equation here providing services or providing API support and tooling? **Shafu (04:50):** Yeah, so we have native integrations into Firecall, Minerva, Nansen, Misari, bunch of others. You can see all of them on X4.2 scan, which is like this discovery tool that we built. We list all the ⁓ X4.2 resources there and all the API providers that support X4.2. ⁓ The beautiful thing about X4.2 and MPPs, that it's very easy to wrap an API as well. So just imagine you have an established API provider and they're just not interested in the agent space, for example. ⁓ It's very easy for anyone to come in, get some API keys and put their API band X4 to an MPP. But there are already a ton of great native ⁓ integrations. **Gabe (05:39):** Yeah, some of the ones I like are like Parallel or Exa, search and retrieval tools. And I think kind of the value here that I see is the traditional search, right, like in these agents, maybe like Claude, right, is pretty good. ⁓ But these external tools are like significantly better at search. So when it comes to search, that's kind of like my big use case. I'm curious for you personally, like what are the ones that you're ⁓ really excited about or use cases that you're **Shafu (05:44):** Yes. **Gabe (06:09):** you're honing into. **Shafu (06:11):** Yes. So what we see for me personally, I just did that before before I do the podcast. was, you know, we have this new product called Poncho. It was basically, hey, find a thousand potential customers for Poncho. And it's really good at that because it has access to Apollo. It has access to LinkedIn. It has access to Parallel. So it can look things up like without like Booting up a browser and scraping things just has access to the API. So it's really, really good at finding people. It's really, good at finding companies and enriching them. And that's what we see right now. It's really good at lead generation, stuff like that. **Gabe (07:02):** Got it. So just a step back. have the agents that can do things and basically like process cognition. And then the X4 02 and MPP are micro payments to these hundreds, if not thousands of legitimate services that the agent can just call, right? And, and your use case that you're saying is pretty interesting is punch, Poncho product needs users. And then you can use these like email generation ⁓ services, right? Where they, give you like emails for people who might fit this type of product and then you're orchestrating between all these different tools to basically like simulate like a salesperson essentially. Is that like a good articulation of how you're using it? **Shafu (07:48):** Yeah, exactly. And just imagine poncho is like, it's like Claude on the web, ⁓ plus the X-Fortune MPP superpowers. That's always how I like to describe it. It gives you agent superpowers. And by superpowers, mean, it just gives you access to these great APIs. ⁓ So now Claude has access to LinkedIn and YouTube and Apollo and parallel and XR. and much, more ⁓ out of the box without setting up a single API key or a single subscription just with one unified balance with which you pay. And that's it. And now we have access to basically all the great APIs on the internet. **Gabe (08:39):** I'm sure you've talked to some of these service providers. Why do you think they're willing to, you know, try this new landscape? Like what, is in it for them if potentially they're bringing in less revenue ⁓ per customer, right? Where before, say, usually they'll have like a $20 or a hundred dollar, et cetera, subscription, this fixed cost subscription. And then you have some credits that you'll use on the API, but now you might use their service and, and, know, be very efficient in the usage because you're only paying per use, right? So for the companies, they're receiving potentially less money, but there's some discoverability. Like, what do you think is the reason why they've been so willing? Because it seems like there's a lot of big projects that have really just hopped on board. **Shafu (09:27):** Yeah, I don't even think it's less money. think in the long term, they're going to make more money because it's just a new distribution channel. So just imagine you have someone that, you know, instead of, he can't, it's just not worth it to spend like 50 bucks on, you know, some Apollo subscription or something, but he definitely can't pay like two bucks, you know, to just access the data that he gets. So Apollo just earned an additional $2 just from a new customer, just whole new distribution channel. ⁓ Obviously people are excited about this because everyone talks about the eyes, it's the biggest thing in the valley, all that kind of stuff. And agentic commerce is just the next evolution of this. It's like super obvious to me that agents are gonna spend money on the internet. I think that's pretty obvious. Like I'm inside Claude code, I'm inside Codex. probably 10 hours a day, you know, not just engineering, just like I described earlier, like sales stuff and marketing and go to market. And for me, it's like extremely frustrated if I'm, for example, inside chat GPT and it just cannot access LinkedIn or it cannot access YouTube because I just got used to it. I got used to like the X for two MPP superpowers. and **Gabe (10:44):** Mm-hmm. **Shafu (10:55):** Most of these data providers or API providers see that. ⁓ They see the agentic thing, you know, just taking off. And they see the vision where like, an agent probably is not gonna open up my landing page and is probably not gonna talk to some sales guy. They're probably not gonna sign up through Gmail or Google or whatever OS. They just wanna access the data. and they're going to pay for it. ⁓ And it just pay for request and it works. ⁓ And it can be more expensive, right? So we have, we have, for example, white pages API, which gives you like homeowners or things like that. And this is like 40 cents per API call because the API is just that valuable. So it doesn't need to be like sub one cent, but it can be. But, but I think like the big picture is just this totally new distribution channel for these API providers to sell their services to agents. **Gabe (12:02):** We'll get to ads in a minute, but this discoverability thing is kind of the first thing that comes to mind where, okay, let's say you do have a thousand services, right? And there's going to be overlap between services. How do these agents... do self discovery if there's so many options and kind of one example is, you know, I might say, okay, use Exa or use parallel for search because I personally know that those are those are two high value search companies. But for the agents themselves, what is the mechanism here for discoverability and how can they basically route to the best appropriate tools? **Shafu (12:43):** Yeah, so how Discovery works currently is we run X4.2 scan and MPP scan. ⁓ And how X4.2 scan and MPP scan works is it's certainly permissionless. Anyone can register their API there or their server there. And ⁓ why is that magical? It's magical because we index that automatically. And when you use Poncho, which is basically your client to this agent e-commerce space. It's like the browser of agent e-commerce. You're inside Punchline, you're like, I wanna access LinkedIn data. It's gonna do a search over all the things that it has on X4 too scan and PPCAN, and it's gonna give you the best one. It's Google plus the browser basically. And that's how discovery works. **Gabe (13:39):** And how are you, I guess to dig deeper, how are you validating if something is like the best one, right? Like, is this a manual process? Is there like a hierarchy or like some type of triage system that runs through the different tools that these ⁓ X4.02 endpoints or MPP, the agent payments endpoints presents? How are you actually deciphering between for your own product? **Shafu (14:05):** Yeah, so right now it's a mix between a manual process and automatic indexing. So on the manual process, it's just, you know, when we onboard someone like Parallel or Exa or Minerva, we just know they're good, right? We just serve them. ⁓ For the other stuff, it's like, how often do they get called? How often do they return a 200? How often do they fail? what's the quality of the data there, all that kind of stuff. A very long-term vision, it's probably gonna work like Google. We just index things and we have metrics that we look at, all that kind of stuff. But right now, it's like a manual process and an automatic process. **Gabe (14:53):** Okay, so kind of the long-term vision of this is you are using the metrics from these tool calling to almost like rate the quality of each service and then you can route through the highest quality services on top of like a curated list. **Shafu (15:10):** Exactly. yeah, maybe even we return like three, maybe you want to access LinkedIn data and we give you like three API providers and the agent just decides which one's going to use or if one fails, it just tries the other. It's actually pretty good. So if you use, if you search inside Poncho, it's actually pretty amazing how well it works. **Gabe (15:36):** And if a agent tool provider, if the return comes back failed, does it still charge the agent or the person who's operating the agent? **Shafu (15:52):** Yeah, depends on how the server implemented Xfru2. ⁓ So you can implement the refund mechanism, or you can implement, I'll give you the data first and then I charge you. But it's up to the server. ⁓ So theoretically, the server could charge you and not give you the data. ⁓ The good thing is we're talking about sub ones and transactions. So if that happens once, they just get blacklisted and they're never called again. **Gabe (16:23):** Okay. So yeah, because there's almost this risk here, Where you're just, you know, you don't know who's on the end of the table all the time. And if you are, you know, putting your funds out there, even if small, like it's kind of important to figure out you're not just calling like a hundred different, you services and then you're racking up these things. So that to me seemed like a pretty big ⁓ opportunity, really, not even almost like a problem, but like opportunity space with the routing. And to extend on that piece, we now understand we have these agent payment solutions or the endpoints or micro payments on APIs. You can call the API and then you have like these extended toolkits of, you know, models and search and kind of anything, know, flight tracking, all that type of stuff, ⁓ really opening up the capabilities for agents. When it comes to like the next phase of this, because right Right now you kind of specify the types of tools that you use or maybe that you use a service like yourself. But you guys talked about this concept of emergence and how over time, and I think this is where it gets a little bit muddy, but over time the agents can almost do self discovery as if they're like in a shopping mall with a goal, right? So if the goal is to ⁓ come back and bake a cake, right? They can go into the mall and like walk around and maybe they go into a close and there's obviously no food there, but then maybe there's like a little grocery store, ⁓ a bakery or something, right? So this orchestration across the tools by themselves where you're not specifying, that's a whole different kind of behavior change. people are not even quite in tune with kind of phase one, but I do wanna do some discovery around here of how you guys are looking at this ⁓ autonomous commerce. and how you're looking at this discovery mechanism for these types of tasks. **Shafu (18:26):** Yeah, I think that's super interesting. think where I see emergence is when you combine all of these APIs together. ⁓ So right now, if you go to Ponscho, you could be like, look up Shafu on LinkedIn, get me his profile picture, create a website, ⁓ make an image out of him, you know, serving on the East River, then create a song and post it all on a website. And it can just do it. all of that because it has access to the image models, it has access to music generations, it has access to LinkedIn. And this is where I see this emerging thing happening, where you just combine all of these APIs together and all of a sudden you can solve things that you couldn't do before. Always just a lot of effort, right? So instead of getting like 16 API keys, it just works out of the box and you don't even have one subscription. ⁓ So I think like this emergence of like just combining all these tool calls or just combining all these API providers is really powerful. And we already see that just because you have so many functionalities now that are behind X4.02 and every time they're, every day they're new ones. ⁓ So on X4.02 scan, I think we have like six high quality API providers. that got wrapped and get put on x-futuristic scan. So every day it just gets more powerful and more powerful and this compounds, right? ⁓ So yeah, this is what I see as the emergent property of like just using open standards, right? Because the difference here is ⁓ if I wanted, let's say I'm an API provider, right? And I want to get my API into Chatchi PT, right? What would I need to do? I'll probably not talk to Sam Altman or some other high up guy at OpenAI. And then we would have like an enterprise agreement and it probably takes six months. And in the end, it probably wouldn't happen because you just don't have the cloud or something like that. And this OpenAgentic commerce thing is anyone can just come in, put your API, put your server behind X for a tour MPP. And now every X422 MPP client like Pawnshore just has access to your resource. And because we have the discovery layer as well through X422 scan MPP scan, it immediately shows up in search as well. So just like the open internet, right? Like I could, know, 20 years ago, I built a website, it gets automatically indexed by Google. I don't need to, you know, call the Google guys and ask for permission. I just can't do it. that's the same thing in this open agent e-commerce space. **Gabe (21:24):** Go ahead, got it. So for you guys, like how do you prevent against security risks? So we had a guy from SIRTIC, a smart contract auditor, and he kind of was explaining how agents are very capable, but they have like no security instinct, right? So how do you prevent against something like a prompt injection where, you know, you have an agent doing an autonomous task, it goes around and says, oh, wow, this service, you know, is going to **Shafu (21:44):** Hmm. **Gabe (21:54):** exactly what I need, right? Or it's cheaply priced and then it gives you some information to manipulate the agent. How do you prevent against this and kind of what is the domain or category which we should kind of think about this in? **Shafu (21:56):** Yeah. Yeah, I think the biggest lift or the biggest leverage is spending limits, sure that the servers are okay. So let's say I think like we have a custom, I think we have a set spending limits of like five bucks on poncho. So that means you like your agent couldn't spend more than $5 on one API call. It will ask you like 20 times because we have APIs that are more expensive than five bucks. Like you can get a shirt through X4 2 scan. You can buy things on Amazon through X4 2 scan. So they're obviously more expensive than $5, but your agent would like ask you three times if you're a hundred percent sure if you want to do this. So spending limits is one. The other one is indexing servers, you know, see what they return. ⁓ making sure that they're actually not exploited by someone else or something like that. But at the end of the day, just because it's totally permissionless, know, someone could theoretically put in a malicious server in X4 too. And it gets, it gets indexed. It's basically like the open internet, right? It's like what Google solves all day. How do you make sure that what you show to people when they search for things is actually legit and not exploitable. So it's a very similar issue, I guess. **Gabe (23:42):** Yeah, okay, so not necessarily intrinsically ⁓ or structurally only something that comes up with agents and agent commerce, but this is kind of like a reflection of the same issue with landing on a bad link or kind of like ⁓ getting a bad email, right? **Shafu (24:00):** Yeah, it's fundamentally a search issue. In the case of agentic commerce, it's a little bit different because you actually pay money immediately. So you just want to make sure, you know, like the spending limit helps a lot. So in the case of the spending limit, like the worst case would be $5. And that still wouldn't be great, but it wouldn't be the end of the world. So that's how we try to counteract that kind of stuff. **Gabe (24:10):** Thanks Mm-hmm. I have a more theoretical question for you and Basically, the way I'm using and seeing these products is oftentimes my agents will talk directly to like a service, right? And usually the service is behind REST API. ⁓ A lot of people talk about this agent to agent commerce. And as of right now, I just can't really think through the case studies in which one agent talking to another agent actually makes sense. It's almost as if like, **Shafu (24:58):** Yeah. **Gabe (25:03):** ⁓ the use case is literally not conceivable right now. So yeah, I wanna like tighten on that nuance and I wanna hear your take on that. **Shafu (25:07):** Yeah. Yeah, I don't really have a take here, Gabe. I see it the same way. I don't fully get it. And we don't see that. So like 100 % of what we see are people using things like poncho. It's like access this LinkedIn and find me more information about this person. Find me 100 companies similar to this. Go generate an image. Go upload this file. This is 100 % of what we see. ⁓ I haven't seen this agent to agent thing in action. ⁓ So yeah, I have the same opinion as you. **Gabe (25:56):** Got it. Got it. Yeah. Do you think there is any use case or any theoretical example where an agent might need to talk to an agent? And I guess my idea of that is let's say I have a business and you have a business and we kind of have to come to like a non ⁓ you like my request and your request has to be kind of merged together and then we can kind of figure out the nuance, but even that can be a marketplace, right? So it's like every time I think of some type of agent to agent commerce use case, it turns into a marketplace or it's, it's not really needed. ⁓ so yeah. **Shafu (26:36):** Yeah, maybe one thing I could think of is, let's say we live in a world where the top models are just extremely expensive, right? So you get like cloud code subscriptions like 200 bucks, right? Which is amazing. But let's say there are models that are just a hundred times better and they're a hundred times more expensive. ⁓ Maybe an Asian to Asian thing would be, Hey, this is my agent. have like the cheaper version and I'm going to rent the more expensive version for like five minutes to just do this one task. ⁓ so you rent another more powerful version for like a limited amount of time. I just came up with that example. ⁓ maybe that's, that's something, but I have a hard time like think, like seeing in the foreseeable future. you know, like my agent talking to your agent and they're trying to like, I would just talk to you. like that's like, yeah. So I'm not sure about the agent to agent thing. It's at least, it's at least not something that we're seeing right now. **Gabe (27:51):** Yeah, yeah, the way I'm kind of thinking about that too is like the, if someone has information that is so valuable that someone else is going to pay for, then usually that turns into, you know, a business, right? And a service and the service has endpoints that you can just hit. So the question kind of becomes like, what use case is there where you don't have a full service, but someone has some information that's more valuable. **Shafu (28:06):** an API. Yeah. **Gabe (28:20):** or valuable enough to transact with. And I just, personally can't think of any right now. **Shafu (28:25):** Yeah, it's a good point. If you have that, turn in an API and charge for it. ⁓ So yeah, maybe in five years, maybe in three years, but not currently something we're seeing. **Gabe (28:30):** Yeah. Okay, yeah, thanks. Yeah, that's a hot take. I think that's not how a lot of people see the space right now. ⁓ For ads, for advertisement, you've made some comments about how, you know, agent commerce and ⁓ agentic agent commerce will disrupt the advertisement space. Can you give us like your thesis or your lay of the land and how you see that happening? **Shafu (29:08):** Yeah, it's very simple actually. So the vision is you go to the New York Times, for example, very, very theoretical example, because I've never been to the New York Times, but whatever you go to the New York Times, you hit the paywall, right? You hit the paywall. It's like pay us $10 for a New York Times subscription or the New York Times is free and you see a bunch of ads which suck. Like I hate ads. In this X-World 2 and 3 world, it's, hey, I want to access this article and I'm going to pay 20 cents to access this article and you're not going to show me any ads. Another example, I've been paying for YouTube premium for the last, probably since I can afford it, maybe last 10 years, just because I don't want to see ads. In this world, Instead of paying, I don't know, I think YouTube premium is like 18 bucks a month or something. Instead of paying 18 bucks a month, you just pay 10 cents or one cent to access a specific video. And instead of serving ads, blah, blah, blah, you just pay and probably the creator gets like 30 cents, YouTube gets like 70 cents or whatever. But like that's the model. The thing is, **Gabe (30:17):** per video. **Shafu (30:33):** Previously, the only way to monetize the open internet was ads. We've been living in that world for the last 30 years. It's the only viable way to monetize anything on the internet right now. But that has changed. We now have an alternative. You can put anything behind X-Root 2 and let people do micro payment, micro transaction. And now you have an immediate source of revenue. No subscriptions, just paper requests and no more ads. ⁓ So that's the vision. **Gabe (31:12):** Okay, and just to put it all together and to help us understand for thinking about it correctly, you have a service like New York Times, and usually it's on the columns where they have the ads, and people read the article, it's free, and then the revenue comes from this ad space. But with the agents, the revenue gets paid instantly to... **Shafu (31:24):** Yeah. **Gabe (31:34):** view the article ⁓ and then that changes the entire dynamic of the ad space. So with that in mind, do you think that ads on the internet go to zero? you know, let's say like agent payments roll and this becomes mass adoption, ⁓ which it probably will. What actually happens to the ad space you think? **Shafu (31:57):** Yeah, it will definitely not go to zero. The funny thing about people in general is they don't value their time or they don't value their attention. So we all know people in our lives that make good money and they will get like the ad-supported Netflix version. We all know that person as like $5 cheaper and they're like, I don't care, I like to see an ad from time to time. So we always have that kind of... We're probably 80 % of the internet. But I would argue high value people. And actually, there are studies about that. If you see a lot of ads, you're probably poor. It's true. So I think we're always going to have ads. **Gabe (32:35):** Thank **Shafu (32:55):** But now we have a much much cheaper alternative. So instead of getting the, you know, you're some poor high school student, right? You're not gonna pay 18 bucks for a YouTube premium subscription or whatever. But maybe you pay like sub one cent to not see ads on a YouTube video ⁓ or on a news article or ⁓ that kind of stuff. So it's just, we have a different path now. We have the alternative. But I think ads are going to be on the internet for a very, very long time. The other thing is that that is pushing against ads in general. It's just if we move more and more into this agentic world, just imagine people are not using a web browser anymore. So for example, in our office, right, if you walk around, most of the people are looking into a codex terminal. or a clock code terminal. ⁓ It's not only engineering because now with X4.2 you can do a bunch ⁓ more. So there isn't even a place to serve ads, right? You're not gonna put ads into a terminal. So you're gonna lose eyeballs on the ads for sure, ⁓ but it's not gonna go to zero. ⁓ **Gabe (34:06):** Mm-hmm. **Shafu (34:17):** The great thing about Asians is you cannot serve them ads, right? They don't get distracted like that. It just doesn't work like that. So it's fundamentally a different paradigm. I'm happy. I'm just happy we have an alternative now because I really, really dislike ads. **Gabe (34:35):** Yeah, interesting. do you see this like stark change of like class on the internet where like literally you're going to be in the ad space or you kind of have your accounts loaded across the board and then you're not seeing ads? Because to see an ad you would basically kind of land on the website, right? So. **Shafu (34:55):** Yes. **Gabe (34:57):** That's like a consumer experience. maybe if you're looking at your agent, let's say Claude at some point can pull up the article in full view, which through ⁓ X4.02, those are two different kind of like UI and discovery features. How are you looking at that? And do you think that everything will just be pulled into an agent interface or do you think there still will be like this separate kind of like a search with fingers, right? Like Google searching interfaces that are heavily used. **Shafu (35:30):** Yeah, think the question about class is a good one. I think we already have a class system. And the class system is people that can afford a cloud code subscription and people that can't. ⁓ Or a codec subscription or whatever. It's just a fundamentally different experience of how to use a computer. It's just a way, way more powerful experience on how to use a computer. ⁓ I think more and more is going to be pulled into this agent experience. Just imagine Codex or Cloud Code getting 10 times better, 10 times faster, and 100x more, and 100x cheaper. I always don't Google anything. I don't know about you, but I literally, couldn't tell you when I, the last time I Googled something. So we're definitely pulling in that direction. **Gabe (36:34):** Yeah, on the class piece a little bit to pick up on that, I am noticing there's this compounding effect of creating systems that are optimized for the individual. And I think there seems to be like a there's a huge technical margin, right, for being able to build your own systems, whether that's searching like in like a sales role or just kind of keeping up with daily tasks or like tasks in your life, right, using these tools. But it's compounding, right? So I'm curious about your thoughts of like, three years from now, you might have like this whole infrastructure that might be equivalent to like 10 humans of labor per day, right? What do you think is kind of capable and how do you think things change within society when you have? you know, people walking around that have that are individuals with, you know, the capital, the output capital of 10 people versus walking next to folks with the output capital of one person. **Shafu (37:38):** Yeah, I think, and this is going to get philosophical a bit, but it's interesting. I think the world in general is getting more extreme. Like you're going to have the 16 year old billionaire and you'll probably have a lot of people without work. ⁓ And then the question is, how do you solve that? And I'm not sure. And you know, people talk about UBI and that kind of stuff. doesn't feel right to me just as a very capitalistic person. ⁓ **Gabe (37:47):** . **Shafu (38:06):** But yeah, the world is gonna get more extreme in every way possible. Just you're gonna have very, very successful people on the top and you're gonna have a lot of people without anything to do. ⁓ Because the agents are just better at what they could do. ⁓ Do you know the permanent underclass meme? **Gabe (38:32):** Yeah, yeah, yeah, we actually wrote a paper on that. **Shafu (38:34):** Interesting. Yeah. So it's like the permanent underclass idea is like, if you're not going to make it now, you're going to be stuck in the permanent underclass forever. I don't believe that. ⁓ It's still a very interesting idea. It's just learn the tools, know, learn the tools. If you watch this, you probably already do, but I don't know, like how many people are using these agents? Like 1 %? **Gabe (39:03):** Yeah, maybe less. **Shafu (39:04):** Sub 1 % it's insanely small. ⁓ So yeah, the world is going to get a bit crazier. It's going to get more extreme and I'm not sure what to do about it. **Gabe (39:19):** Yeah, I agree. The permanent underclass thing is interesting because I think it actually is a flywheel mechanism for AI in general, where it's kind of like, what is the behavior that comes out of knowing about the permanent underclass? Like you're going to spend more tokens and kind of figure out how to deploy your agents and all these things. But at the same time, it's not like a not real risk, right? This is a real paradigm shift happening. **Shafu (39:28):** Hmm. Hmm. **Gabe (39:47):** ⁓ Also, and if you have comments, please hop in. On the capitalism thing, I think that capitalism actually is eroding because of AI and as the models get better and better and better and even if you have access to all these different tooling, right? **Shafu (39:58):** Hmm. **Gabe (40:07):** the cost is just it's going to keep going coming down and down and down as ultimately we might see agents, you know, building themselves and optimizing and and yeah, I'm curious, curious to hear your thought on that piece because for me, it kind of erodes capitalism in a way where ⁓ it's hard to capture value in like a capitalist society. We might move into like a feudalism or or maybe we're doing like arts and stuff like that. But ⁓ yeah, can hear you. thoughts. **Shafu (40:39):** Yeah, ⁓ I think it's an issue. I'm really, really interested in ⁓ online dating statistics. Have you looked into online dating statistics, like Hinge and stuff? Okay, so very, very interesting stuff. So I would say, like in New York or the US in general, we live in a very liberal society. **Gabe (40:52):** No, no, no, I'm up for that. **Shafu (41:08):** That reflects the stats. So on Hinge, you have 50 % of all men don't get one match and you have the top 10 % of men get all the matches. Right? So there is this concept of hypergamy where it's, you see that in every culture on the planet. It's basically the concept of women marrying up. Up in status, up in wealth. It just... It's a concept out of social sciences. And if you don't regulate that, it just gets more extreme over time. And I think the same thing we're seeing with just technology in general, ⁓ just the concentration of wealth, ⁓ we're going to have the same effect. And if you don't regulate that, which ⁓ I'm not sure we should, or at least I don't know how, it's just gonna get more extreme over time. So I don't know, like the top 10 % of people own 80 % of things. It's probably gonna be like the top 1 % owns 99 % of things, stuff like that. ⁓ So you just see the tendency, you see that in online dating, you see that in wealth, you see that, you know, all these kind of things. ⁓ **Gabe (42:24):** No. **Shafu (42:37):** and it's gonna be more extreme over time. **Gabe (42:40):** Yeah, yeah, yeah, I can't speak on the dating example or like kind of what it means ⁓ socially, but for the wealth piece, yeah, I mean, that's something we've seen for a long time and it does exacerbate it. ⁓ **Shafu (42:57):** Yeah, I think on the dating side, it created things like looks maxing or insults. All of these concepts stem from a lot of men that couldn't date or couldn't find a girlfriend. It's just a second order effect of these kind of things. **Gabe (43:05):** Hmm. **Shafu (43:25):** So yeah, on the technology side, I just know that it's happening. It's very obvious that it's happening. ⁓ How it's going to look like in five years, I have no clue. **Gabe (43:34):** Yeah. Yeah, yeah, yeah, the the Intel thing is interesting because because looks maxing is is you probably knows is like a genealogical roots or like grandson of of like some of the Intel forums online. We're going a little bit off, but. **Shafu (43:43):** Yeah. Yes. No, it's great. ⁓ Yeah, think it's just... Yeah, it's so interesting. It's just a... As I've said, like if you... At least in the online dating realm in the West, as I've said, like if you're not in the top 20 % of men, like just don't download the app. It just doesn't make sense. just doesn't make... Like the numbers say that. It just doesn't make sense. **Gabe (44:24):** Yeah, yeah, yeah. **Shafu (44:26):** So it's like this, you know, like they have this, concept of ascending, looks maxing. And ascending basically means you want to be in the top 20%. And that's also like, it's very relatable to like the permanent underclass. You know, it's just in a different, in a different setting. So, so yeah, we're going to live in a world that is more extreme in every aspect imaginable. **Gabe (44:31):** Yeah, yeah. Yeah, yeah, Yeah. Got it. Okay. So on the capitalism piece, there is a kind of like this other thread, Where, and you might have talked to it a little bit, but to nail on it again, the commoditization of these services, right? Do you think that if there's an EXA and there's a parallel and there's like a marginal improvement between the two, or maybe if you're using the services, you can't even tell who is who, right? I think with like a Claude and a Codex, like heavy use, could literally feel the personality differences and the speed. And you know, you can look at an ⁓ output and tell if it's like Claude or Codex, probably. ⁓ With some of these services, especially using like tons of different services, I'm kind of thinking that these things commoditize not into like the brand, but into ⁓ almost just like, you know, I need to do a search and it needs to be like an enhanced search. ⁓ **Shafu (45:31):** Mm-hmm. **Gabe (45:56):** That is kind of how I'm seeing this play out. Do you agree on that piece? Do you have any additional thoughts on this commoditization piece? **Shafu (46:04):** Yeah, I think it's already a commodity. ⁓ It's just going to be like, at least now you have a brand and stuff. Like you go to a landing page and you know, it has, you know, the vibes are nice and they're using like modern colors and stuff like that. ⁓ You're inside an agent, never going to see that, right? You're never going to see any colors. You're not going to see the face of a founder. You're not going to see their, you know, whatever. **Gabe (46:13):** Mm-hmm. Yeah, yeah. **Shafu (46:32):** It just, you know, use this to do this. So it's probably going to be even more commoditized as it even was before. **Gabe (46:42):** What do you think the things that stand out like, you know, traditionally these services use really nice ⁓ text and ⁓ logos and there's like all these different tricks like marketing. ⁓ but those no longer work like you said, right? Like the ads don't work on the agent. This visual appeal, like psychological element is mostly removed. What are the things that are kind of like these important variables that you wanna like drive, SEO maybe, right? To people's agents as they're indexing your services if you're a provider. **Shafu (47:00):** Yeah. Yeah, I think the biggest leverage is probably for people like Twitter or LinkedIn or stuff like that. They just own the data and no one else does. So if I want to get data from Twitter, I have to go through the Twitter API. If I want data on LinkedIn, I have to go through the LinkedIn API. Even if their landing page doesn't look nice, even if they don't have nice colors, it doesn't matter. Just the data is so valuable. So in that case, it's funny, like all the AI models, all the AI frontier labs, they need all the data in the world. And it's probably for the consumer, it's very similar. **Gabe (47:56):** you **Shafu (48:14):** I don't care about the brand, but this is the only API provider that gives me that kind of data, so I'm gonna use them. ⁓ So I think that's where we're stand out. **Gabe (48:19):** Mm-hmm. And where do you think right now, and maybe you don't have to think about it, but like where are the big use cases for searches right now or API calls, micro payments ⁓ on X4.02 or MPP? Like what are the behavioral trends that agents on behalf of people are actually doing that are useful tasks and not like some meme coin or something? **Shafu (48:48):** Yes. So the biggest use case that we see right now from people actually using our stuff is lead generation and enrichment. And they use it all day. They use it all day to find companies they can sell to. They use it all day to find customers that they could sell to. They use it all day to find the LinkedIn, email, Twitter. **Gabe (48:58):** Mmm. **Shafu (49:15):** of a specific person, which is enrichment. So that I would say right now is the biggest use case for this. **Gabe (49:24):** Got it. Got it. And in that process is you have like a business service. you want to identify companies based on a criteria, right? And then the agent searches for these types of companies. Maybe it calls like EXA does a website search and pulls back 100 companies. And then you need to use the Twitter or excuse me, the yeah, or the Twitter endpoint, right? And find their Twitter accounts, right? So you can do the DM and then you have ⁓ emails. You need to get the emails for the company and then you can use a email endpoint like Hunter or Apollo, I think you said, was the other one. So now you basically have all the sales diligence and you're saying this is the most common use case right now for agent commerce using X4.02 and MPP. **Shafu (50:13):** It's just what people actually spend money on, which is the only signal you should look at. Yeah, people spend a bunch, a lot of money on this right now, ⁓ especially in Pancho, which is a product we haven't even announced yet. ⁓ So these are people that we manually onboarded and they love the product so much that they spend a lot of money every day on. on lead generation and enrichment. **Gabe (50:45):** For things that are available, I've seen like a lot of like meme coins and services that are wrapped in tokens. I think more recently you said something online like you think that meme coins have like destroyed the credibility of a crypto. Can you speak a little bit about your thoughts about that? **Shafu (51:05):** Yeah, yeah, it has. ⁓ And it's just from from my own experience, because we talked to a lot of potential API providers ⁓ about integrating X for two or MP MPP. And we can't we can't mention crypto. ⁓ We don't we don't see ourselves a crypto company. We just we're just using stable coins to facilitate payments. But we're trying to stay **Gabe (51:23):** Mmm. **Shafu (51:35):** as so much away from that when we talk to like API providers because they would just, they would be like, okay, I'm not interested anymore. And that's how bad crypto reputation has become. ⁓ I can give you an example. And maybe this is just interesting. So the X4O2 standard was defined by the guys at Coinbase ⁓ a year ago. **Gabe (51:44):** Mm-hmm. Yeah. **Shafu (52:01):** And we started looking into x-402 maybe six months ago. And there were like 2000 maybe x-402 transactions. And half of them were like coin-based integration tests or something like that. A very low number of actual transactions. ⁓ So we built x-402 scan, which is a explorer for the x-402 ecosystem where we list every x-402 server and resource and people can add their resources. And we went from 2000 or like a couple of thousand transactions to a couple of millions ⁓ in like five days. Which sounds very impressive, but 99 % of the volume was like meme coin shenanigans. And by meme coin shenanigans, mean people created X servers that will give you meme coins through XOR2. ⁓ And we're not interested in that kind of stuff. And it took our site down, it took the Coinbase API down because we haven't read it too much. ⁓ So that was a fun time. ⁓ The other stuff, he's back. **Gabe (53:04):** Mm-hmm. Yeah, give me one second. think my camera died. One second, one second. **Shafu (53:23):** Yeah. I got I got it, **Gabe (53:42):** Yeah, sorry about that. That was like hanging onto my seat. One second. **Shafu (53:46):** No worries, no worries. nor is it **Gabe (54:58):** So the hammered side I think is probably a place to to pick back up. **Shafu (55:06):** So yeah, they launched a bunch of servers that would give you meme coins through X4.02 which is a terrible mechanism to launch a meme coin but whatever. So the thing is, okay, so 99.9 % of that volume or number of transactions were meme coins, but like 0.1 % of that was people actually using X4.02 to to buy interesting API resources. And it's funny, like a lot of people would like screenshot X for a two scan statistic and they were like, you know, everything is down 90 % what happened. And the thing that happened is all the meme coin stuff went away and we grew the actual API usage by 10X. But it just, yeah, just a fun story. And we had a lot of fun. for like five days in the office just scaling up x422 scan and stuff because we got hammered by the crypto people but yeah. **Gabe (56:17):** So in calls, you guys are not bringing up crypto at all. let's say you have a sister company, right? And they need to launch ⁓ the same product. What are you going to tell them before they go into a meeting so you can get the clothes and explain that these are crypto rails without blowing up the opportunity? **Shafu (56:22):** No. Yeah, don't mention the word crypto at all. If you have to, can say stable coins. Don't mention the word blockchains, stuff like that. know, we're ⁓ using stable coins ⁓ to save you 30 cents on every transaction, which goes to the credit card provider. ⁓ And that's the pitch. ⁓ But yeah, it's funny, Gabe. I spent a lot of time in crypto and I think when you're in the crypto bubble, you don't see that. But once you step out of the bubble, you're like, Jesus Christ, these people hate crypto. ⁓ Which is understandable because all they can see is crypto, meme coins, scams, all that kind of stuff. ⁓ **Gabe (57:21):** Yeah. **Shafu (57:38):** Are you familiar with Channel 5? **Gabe (57:41):** No. **Shafu (57:42):** Okay, so Channel 5 run by Andrew Callahan is like a YouTube channel. Very, very interesting guy. And he interviews people and stuff. So he was interviewing the Hoctua girl. You know the Hoctua girl? Okay, so he's a great guy, very open-minded guy. And the Hoctua girl was like telling him about, because he was asking her about like the crypto coin, crypto token that she launched. You know what he said? **Gabe (57:57):** Yeah, yeah, yeah, yeah, yeah. **Shafu (58:12):** He said, anyone that mentions Krypto to you, don't talk to him. And he talks to like the craziest people on planet earth. know, it's like extremely open minded guy, great guy, I love his content. But if a guy like that tells you that, you know you have a reputation problem. Something is completely broken and you just need to rebrand the whole thing. **Gabe (58:20):** Yeah, yeah. Where do you think is, so you're navigating the rebrand. What do you think is the best way to do that? Is it to just avoid crypto? Is it like to carve out kind of like a new narrative or like a new category? Like how are you navigating that? And then how do you think is like the long-term solution for that? **Shafu (58:57):** Yeah, I think you have you have two things in crypto you have speculation and you have payments We just need to focus on payments ⁓ Because stable coins are awesome, know, I grew up in Egypt Getting access to US dollars in Egypt is insanely hard and sucks You know like sending money to Egypt receiving money like US dollars. It's just a very very bad experience **Gabe (59:16):** Mm. Mm-hmm. **Shafu (59:25):** And stablecoins fundamentally solve that. So that's just one example. Stablecoins uniquely enable agentic commerce through X4 to an MPP. just so you have this, you have the payment rails, which is great, just uniquely enabled by crypto in general. And then you have the speculation stuff, which, you know, it's just a big casino in my opinion. and people see it like that. And you know, there are a lot of scams inside the casino. ⁓ So yeah, focus on the payments and less on the speculation stuff. **Gabe (1:00:05):** Got it. So for you guys, as long as you're kind of navigating as we're gonna lower costs and you don't have to deal with the credit card providers, then they're pretty okay with ⁓ working with a payment service provider that's using crypto. **Shafu (1:00:23):** Yeah, it's not even crypto, it's it's USDC. You know, it's stable current, it's not more than that. using USDC to facilitate X4 to transactions. That's all we use crypto for basically. **Gabe (1:00:28):** Mm. Got it, got it. Well, yeah, man, Shafu, thanks for coming on. ⁓ Last thought here, what is your big ⁓ AI prediction that no one's talking about right now? What do you think is gonna happen? **Shafu (1:00:55):** oof AR prediction that no one's talking about? AI predictions that no one's talking about. I would have said, you know, agents spending money on the internet, but everyone's talking about it now. So I haven't thought of anything new to be honest with you. Just, you know, like we're working 24 seven or just making agents spending money on the internet for the last six months. But yeah, anyone that is interested in agent e-commerce and wants to grow this space by a thousand acts, that's basically the mission of the company right now. **Gabe (1:01:10):** Yeah. **Shafu (1:01:34):** Please reach out, know, we'd love to help you in any way. ⁓ Go try out Poncho if you want to experience like this agent e-commerce future. Try Poncho.com. ⁓ And yeah, please find me if you're interested in this stuff, Twitter, on Telegram. Shaffuz Urex. **Gabe (1:01:52):** Yeah. Perfect, Before letting you off the hook, I'm gonna tighten it up a little bit. For all the stuff you're working on, what is like the biggest alpha that you've seen in the space? **Shafu (1:02:00):** Yeah. **Gabe (1:02:08):** ⁓ For me, I've been messing with Hermes lately with the harness and I think there's some cool stuff there. yeah, where is the alpha? Where is the opportunity when it comes to the payments? Maybe like what is no one building that needs to be built and that you're kind of seeing bubbling up ⁓ or some opportunities? Yeah. **Shafu (1:02:31):** Yeah, the opportunities is pretty simple. It's just take an API that you find interesting and put it behind XFOR tour MPP. That's like the biggest leverage thing you can do. I know a lot of people that work on agent credit, agent credit, agent reputation. I don't fully get that. These agents are paying one cent to access an API. I don't see where credit comes in. But maybe once they buy more expensive things than maybe. But I think a lot of people are wasting their time there. But yeah, it's pretty simple to get into this space. Because you know, agentic commerce space is just brand new and it's very, very small. So we had someone recently put like all the pedal maps behind X4-2. So you want to look for a pedal match. You can look that up through X4-2. Some guy put like half of sub stack behind X4-2. Another guy put like the city bikes with like electric bikes in New York behind X4-2. So I could be like, hey, I'm in. Williamsburg, where's the next available CBuy inside my agent? So that's what I mean. That's what's awesome about like open agent e-commerce is like, he didn't ask us, you know, he didn't ask Coinbase, he didn't ask Stripe or Tempo or anyone. It was just, have this API, I'm going to use this open standard X for a tour MPP. And now every agent with the wallet has access to it. **Gabe (1:04:17):** Got it. Well, cool man. Shafu, thanks for coming on and yeah, I hope to have you back on too. **Shafu (1:04:24):** Yeah, thanks for having me on. This was fun. See ya. **Gabe (1:04:27):** See ya. All right, man, I got the recording done. Yeah, man. --- # The Onchain Underworld: Solvers, Market Makers, Routing Algorithms, and Where AI Fits In > Shoal Signal episode. Guest: Nikita (Barter). Host: Gabe Tramble. - Publisher: Shoal Research (https://shoal.xyz) - Published: 2026-04-20 - Video: https://www.youtube.com/watch?v=RicJ2_3eWak - Canonical: https://shoal.xyz/research/episodes/the-onchain-underworld/ - Keywords: crypto, DeFi, solvers, market making, MEV, infrastructure, Ethereum, Bitcoin, interviews ## Transcript **Gabe (00:00):** Hey everybody, this is Gabe from Shoal Research and this is the first episode of Shoal Signal and I'm excited to have Nikita from Barter talk about all things DeFi, routing, and what I like to call the DeFi underworld. So without further ado, Nikita, yeah, please introduce yourself and tell us about what you're thinking. **Nikita (00:20):** Thank you, Gabe. It's pleasure to be here. Hello, everyone. My name is Nikita. I've been working in crypto full time since 2017. I joined during the ICO era and I was fascinated with new tokens and new primitives that emerged. And in 2020, just before DeFi summer and pandemic, I joined Oneinch as a third employee after the two co-founders, Anton and Sergey. Anton and Sergey are both technical, so they needed help with business development, investor relations. integrations and I've been chief business development officer at Oneinch for two and a half years, helped scale the team from three people to 150. And yeah, in 2022, I moved to Chile and I had a baby here. So I decided to take some time off crypto, know, focus on family. And around that time, the concept of intents started to emerge. And I'm super bullish on DeFi in general, actually. One of the reasons why I've joined Oneinch is because I felt like 2019 centralized exchanges had so much power over like what's going on in crypto and maybe market makers as well because for any project whatever you're building whether it was like DeFi, GameFi, you SocialFi, you at some point you have to engage with like listing team and you know like distribution of your assets to people and centralized exchanges were extremely sharky and when DeFi started to emerge I instantly fell in love you know the fact that like Uniswap the way Uniswap worked you can just create pool and whoever wants can start buying or trading your assets was phenomenal and like super refreshing to me as a crypto user. yeah in 2022 I feel like the concept of intent started to pop up and it wasn't even better I like like ideas that people don't need to like commit to a certain path or transaction they can just specify an intent like I want to buy one is at the best possible price like let's say like around two thousand dollars And then solvers or other sophisticated parties would make sure you get the best rate possible and would fulfill your intent. I definitely... felt like this is the way to go because we want mass adoptions, we want people to use our services, our infrastructure, and crypto was way too complex at that time. Actually, I still think crypto is way too complex, but we'll talk about it later, I guess. So we've built a solver, and Cowswap was the leading and pioneering platform at that time that allowed solvers like ours to find this best route and provide the best rate to the user. **Gabe (02:40):** Thank **Nikita (02:50):** So we launched in 2023 around February, yeah, February, March. And within like three months, we became number one solver on Cowswap by volume and users and transactions. And to this date, we have facilitated over 35 billion on chain. And last year, we were third largest router on Ethereum mainnet behind Oneinch and Kyber network. And we are very proud that due to the fact that we exist, users of Cowswap and other venues have more than like $5 million of coins more on their wallet than they would otherwise had to if, you know, barter never happened as a project. Because, you know, if we didn't exist and we didn't provide rate, then the second best like solver would facilitate your transaction. And you would get like a little bit less ⁓ in terms of your tokens. And yeah, so. due to our existence and users in crypto have like 5 million more and we are proud of this metric. But I don't know, should we dive what solver is and how it works? ⁓ Yeah, what do you think? **Gabe (03:55):** Yeah, yeah, was just going to ask to get into that because for solvers, this is not like a traditional business. This is almost like a competition, like a head-to-head competition, if you will. So yeah, if you can kind of give a brief on what solvers are and kind of what the reason solvers are here for, that'd be great. **Nikita (04:13):** Right, I've suffered for like three years trying to explain what solvers are to everyone during crypto conferences like ECC, Denver and others. But a solver, like the way we see it, is an interesting, unique mix between aggregator, market maker and MEV bot. Just like an MEV bot, you have to be aware of every block and the market conditions and you need to find the most optimal liquidity that exists on chain. Just as an aggregator, you aggregate all available, like ideally, all available liquidities that exist with like AMMs, pools, wrappers, et cetera, et cetera. So you try to rely on on-chain liquidity and provide the most optimal path for the users, the best rate possible using this publicly available liquidity sources. And as market maker, Every now and then you can tap into your own liquidity, into your private pools, and essentially market make and earn fees or spread within transactions. Solvers are a mix of these three unique market participants that also exist. I guess the biggest difference with aggregators would be that aggregators are more user facing interfaces. you know, people go to zero X and they interact with the depth while we as a solver, we power like B2B platforms like cowswap, for example. Yeah. So solvers specialize on, you know, optimizing, you know, inclusion in the blocks, optimizing, you know, gas that you spend on with every like swap and action. optimizing, analyzing the state of on-chain liquidity and try to give you the best possible rate and earn like a small fee on top of it. And a lot of people actually think being solvers is very profitable and like kind of cool. I strongly strongly disagree with that. Maybe it was profitable, well, not maybe it was relatively profitable in like 2023, maybe 2024, but the margins have been going down. The competition intensified dramatically. The users are getting more sophisticated and they are using... Well, the quotes have to be extremely tight in order to fulfill the intents. And we are facing tremendous competition from market makers. market makers are... pushing us to innovate and find ways to compete with their private liquidity. And this is probably one of the most fascinating events that are happening in our landscape right now. **Gabe (06:43):** Wow, yeah, so can you take us a little bit deeper, what, between maybe you and let's say five other solvers, what are the mechanisms or ways that separates you and how do you go about thinking of differentiating the product to bring the best prices at the end of the day and win these auctions? **Nikita (07:01):** So I would say there are two prime type of solvers on Caoswap. Some of them are market makers like Wintermute that operates resolver or others like TokaLabs for example. The other types of solvers are more algorithmic one like ours that rely on on-chain liquidity and that build it to unite existing DeFi primitive. So market makers goal is fairly simple. They analyzing, you know, the liquidity that's available off chain liquidity on centralized exchanges. And they are figuring out if they can improve, you know, the quotes that exist on chain with their own inventory. So what winter Mute does and what is actually like very close to equilibrium, very hard for solvers like ours to compete is that they do not have this block time constraints in terms of How long do they have to wait? so let me put it this way. They have private liquidity in their wallet and they can price it the way they see fit according to a lot of information that they have access to, including things that are happening off chain. And it's super cheap and efficient in terms of gas because they're not... combining like Uniswap, Curve Balancer liquidity into one complex route and trade. They just use a hot wallet to provide you an excellent quote on like Ease price or like Bitcoin price. And they just do the swap using their own private liquidity. So what we do and what a lot of other solvers does is we rebuild all the DeFi primitives that exist on chain into an off chain like trading engine. So for example, we rebuilding like existing AMMs and their mass and all the logic inside our environment. And we use Rust because we need to emulate like millions of different ways how we can split your liquidity. Like if you want to trade like 100 E's, we can split it into so many different ways. Top into incredible amount of pools. across all the DEXs that exist on chain. And this is fairly complex. It requires a lot of computational power. It requires different algorithms. There are different approaches from mass perspective, how you can work on routing and bringing these different DEXs together. A very popular and ⁓ maybe one of the most mainstream approaches is convex optimization. Not the best one, but a lot of people are using that. So I think we have market maker solvers that use their hot wallets and their own liquidity to fulfill transactions. And there are like algorithmic solvers that rebuild all the DeFi primitives from scratch. yeah, like other people can use it. So yeah, other people can use it and it creates like problems like slippage, for example, if we, you know, calculate it. **Gabe (09:51):** Yeah. **Nikita (09:53):** like rate on like using uni v4 pools and then someone swaps before us then the rate is going to be different and the user would probably get less and we don't know who is gonna like do what because the blocks are being built in real time and we don't have the information we only know like the end state of the block when when the block was built in the previous iteration also for our listeners if anyone wants to dive deeper into it i think there is a pretty good open source project called propeller heads that run Tyco where they've built an example or like the logic of the implementation. And if anyone wants to try build a router algorithm, I think starting with Tyco and with propeller heads like GitHub repository might be the best way to go and get you familiar with in general, how it works. But most of the solvers like ours, we rebuild these primitives by ourselves. And we are using different tips and tricks to optimize the way we use liquidity. And we are also connected directly to like block builders, for example. So they can guarantee us inclusion. We are also using pre-confirmations, projects like pre-mef, et cetera. to land on top of the block or very high in the block with our routes. So yeah. **Gabe (11:12):** Got it, got it. So, so. And help me if we're understanding correctly. Basically, you there's two types of players, the market makers and then the solvers. And then the market makers, it seems like they have maybe a quote unquote easier game because they're pulling from known liquidity. They kind of know how to price it. They have additional external information where you guys are running almost this like simulation of of the entire ecosystem and then predicting kind of how a trade would land. And then that's how you **Nikita (11:20):** Yes. Yes. **Gabe (11:42):** move forward or make decisions. Is that kind of a correct illustration? **Nikita (11:45):** It is correct. I just add that I think being market maker, good market maker is extremely tough and pricing your assets is an art. And, you know, some, some projects like winter mute, for example, they excel at this game and they do a very good job. Well, for new participants, it's a little bit tough, but ⁓ yeah, in general, like what you described is exactly what's happening from our point of view. It's our job is extremely important because if projects like ours do not exist and we are squeezed out, then there are only market makers left and the DeFi primitives like AMMs receive toxic flow. And essentially like now market makers provide very good rates, very tight spreads, but as if they become like monopolistic, they would improve and the rate like, like the rates for end users would get worse and the DeFi will start mimic trade fi. So it's a **Gabe (12:38):** Got it, got it. **Nikita (12:39):** ideological battle. **Gabe (12:41):** And do you think, like what is the state right now? Do you think that is the case? Do you think it's not the case? Where are we kind of trending in terms of this decentralization component versus off-chain liquidity? **Nikita (12:57):** So yeah, in 2023, we were like the largest solver on Cowswap. In 2024, another solver called Copium Capital was leader in terms of transactions and volume. In 2025, last year, we were second behind Wintermute. So market makers now are the most dominant players, and they are extremely important in order to provide the best rates for every platform. And even like new... new intent systems like Cowswap and Merge, they're not targeting to onboard algorithmic solvers like ours. They want market makers to provide quotes and to be present on their platforms. the market trend is a little bit grim. It's going towards centralization. Moreover, we now have prop AMMs and prop AMMs are kind of playing the same kind of game, trying to provide tighter spreads within the block. And yeah, it looks like it might get even worse. **Gabe (13:56):** Okay, And so for someone who is like new and is like, hey, you know, I really enjoy this. Is there space for kind of like new entrant players to, you know, come up with their own order routing system or algorithm, et cetera? Or do you think this is kind of like a sailing ship where, you know, the floor just raises so fast that it's not necessarily feasible for a new entrance to kind of pop in? **Nikita (14:22):** Well, let me put it this way. I feel like our algorithm and system was historically one of the best to interact with AMMs. But then RFQ liquidity, liquidity from Hashflow, Bebop, liquidity that is provided by other market makers have become incredibly competitive. And it's kind of a different type of game. I would say within routing an algorithmic perspective, I don't think there is much innovation that can be built. Moreover, it's extremely complex and not very profitable. So I don't envision like new players emerging or innovation happening. Actually, if you look at the past couple of years, I would say the number of solvers and algorithmic projects have been shrinking. Like Copium guys, have pretty much left the market. They stopped solving and we acquired their code base. There was a big announcement back in September this year, last year. But I would say on the AMM design, on the way how we interact with liquidity, we definitely see some innovations happening. **Gabe (15:16):** Mm-hmm. **Nikita (15:29):** One of those innovations is superposition, what we've built in a way, trying to compete with market makers and offer a different path to users, how they can like earn yield and how can they empower systems like cowswap or uniswap, one-inch fusion and others. **Gabe (15:47):** Can you tell us little bit more about the mechanism there and the challenge that basically trying to tackle with that? **Nikita (15:53):** Right. So honestly, I am super, super excited about Superposition. I feel like this is one of the most interesting primitives in DeFi. And we've showcased it to people initially at DEFCON in Argentina this year and received a lot of like tremendous feedback. But we've been competing with market makers and market makers use their hot wallet to settle transactions. And we've been thinking, how do we compete with them? Because in terms of like gas, they are... Perfect, you it's just a transfer from the wallet, you know, it's ⁓ very optimized and you price liquidity using off-chain data. So how do we compete with that without becoming a market maker ourselves? And we've decided that why don't we use like other people, community and like users, their liquidity to fulfill trades that we receive from cowswap and earn yield natively. So what superposition does and how it works is, You as a user give an allowance to our smart contract to interact with your wallet and you give an allowance on a token level. So you can choose like the most basic example we have a stable coin. So you can choose like three assets, USDT, USDC, DAI, and you say I'm comfortable holding those assets and I'm happy to provide them like to stream them as liquidity to DeFi as long as I earn yield and I receive more tokens in return. So... Yeah, you've chosen those assets and let's say you have a thousand USDC, then we use your liquidity to facilitate swap and call swap and give you in return one thousand one die. And then we use your liquidity again for another swap and then you receive one thousand two USDT. So your liquidity like always grows. It stays inside your wallet, every block. You can pause it at any time. You can stop it at any time. You can like we have... Tinkering with some fancy use cases like imagine you're going to sleep and you know for eight hours You're not gonna use any of your stable coins and then yeah We start like routing trading you wake up and you have like more tokens that you went to sleep with and it's like first self-custodial yield product like right now if you want to earn yield you always need to deposit funds into a vault into a pool the vault narrative is like popping up and we are thinking like well, yeah, you're your wallet is essentially like an ideal vault. And if we can add a couple of constraints and a couple of like use cases like bridging, for example, or like not just swaps or even maybe lending, you can earn yield while still having custody of your assets. in a way we transform, you know, your wallet from a spending account into a saving account. And I think this is really cool for like a lot of users. We've just launched in November last year and we've been live for four months. We have close to 500,000 TVL. We've connected over 100 wallets and the DAP is live. You know, it's safe. We have a security audit. Do not use your prime wallets to interact with it as the concept is very new and you can never be too sure. But you know, if... Like we plan to build more and more features on top of it. We plan to improve and, know, battle test security. And we feel like this might be the end game of, you know, DeFi in general. **Gabe (19:07):** Okay, and this is kind of what we discussing before, like a solution to competing with these, you know, the market makers who have access to this large bucket of liquidity. So you're kind of expecting, you know, this on-chain liquidity that you can tap into is kind of like a comparable solution. **Nikita (19:25):** Exactly. mean, market makers, you know, they're getting more and more dominant and they're earning yield while toxic flow and, you know, goes to AMMs and to users essentially as well. So in our opinion, it's super to build this, you know, layer and also to find new ways earn yield. A lot of yield on is not originating from on chain elements, like for example, stable coins. Stable coins primarily earn yield from like treasuries or depositing collateral. if ⁓ your stable coin is backed by USDC, then USDC is ⁓ deposited somewhere and earns yield. While we unlock yield from DeFi trading, from swaps and purely on-chain yield, yeah, like feels kind of new. At the same time, you know, if you look at the market, we've analyzed, you know, user wallets and there is like so many stable coins and other assets that are just lying idle in user wallets, not doing anything, which is kind of like economically inefficient. And we feel like we want to offer them this unlock with superposition and start generating like a sustainable yield, which is Currently, we are targeting like 7 or 8 % on stables, which is like bigger than what do liquidity providers get when depositing funds into like Balancer, Uniswap, Curve, or even lending protocols like Aave. **Gabe (20:54):** Wow, wow, yeah, yeah, that's pretty comparable. you know, just to transition a little bit, I'm curious for, on urine, since a lot of this is very much like almost high frequency trading background, you know, algorithm chops, probably a lot of. curious how you're seeing the deployment of agents and AI for this type of routing and not necessarily AI agents running around and trading with each other, but more so where do you see the actual tangible applications of AI and even with like ⁓ mythos that just launched, right? A lot of this, I think kind of like the underlying parameters that we're seeing is you can have agents reason autonomously very powerfully, right? So does this unlock new ways of routing liquidity and how does that look? Or is it just kind of like, yeah, AI's been great and we're coding 10 times faster, right? So yeah, I'm curious how, for you specifically, how is this impactful and do you see things happening on chain yet or what should we expect for? **Nikita (21:56):** Right, so. Okay, let me begin with like how we use AI. And I think every project is now going through transition or should be already at the end of transition where you move from like previous workflow towards like AI agentic workflow. We've had 16 people working full time at peak ⁓ in barter and we've downsized to 12 and we might downsize a little bit more. It's just because some of the people both on a business end and on, you know, engineering and didn't pick up AI tools fast enough and didn't use them in their workflow. Also, if you check our recent announcement, I think we've built a lot of small prototypes, niches, product. updates, different interfaces or analytical like micro tools, I would even call them, using AI that just improve user experience and overall UI of our products. So yeah, using AI is essential. You cannot get things done now or you would do it like... so much slower than it would not matter by the time you finish. So that's one side of the story. Another one is how do, what does it mean for our product for like routing and swaps and liquidity in general? And we, we are bullish on AI and agentic, not just payments, but operations on chain. We feel like agents will interact with crypto agents will be doing things on chain and they need tools for it. So we've packaged our swap API into an MCP and the same we've done for superposition so that the agents can deploy liquidity or perform swaps and also analyze every block they can get a state of ⁓ on-chain liquidity and find arbitrage opportunities or ⁓ doing... doing anything they can. Like, I don't think people are using it right now. Also, it feels a little bit risky to give access to an agent with your liquidity, with your wallet, because who knows what agents might do with it. Yeah, but this is definitely the future. ⁓ Agents will transact. Yeah, we have a... I personally don't have a trade fire experience, but some people on our team do, and they sincerely believe that the banks and institutionals will never allow agents to interact with them at such pace and speed and capacity as they can interact with blockchains. It's just like they will be limited with banks APIs and on chain they can do a lot more interesting cool stuff. So we are, we are bullish on agents. are building for them. Yeah, we are definitely building for them. **Gabe (24:44):** Got it, got it. So agents are not necessarily changing the structure of your product directly. As you're doing computation between, I don't know, like Aave or Uniswap, right? You probably have some system that is robust, and you remember refining for the last few years. And I guess on those pieces specifically, are you guys implementing like... **Nikita (24:57):** Right. **Gabe (25:09):** agent logic or any like autonomous decision making at all or do you think that doesn't even, is that not even required for your infrastructure or even kind of like the nature of solving, et cetera? **Nikita (25:21):** We've been debating it for a while and for now it looks like, know, mass and optimization, all it takes to, you know, build an algorithm and start routing in DeFi and, you know, utilizing liquidity on chain effectively. So agents will not improve much. However, there is one use case. where we find where agents can help us. And that's when like volatility spikes happen. So in the past, when, you know, like suddenly the market would move like drop dramatically or would start to rise in dramatically, the block space would become extremely competitive. The AMM pools would be like heavily abused by MEV bots. **Gabe (25:46):** in **Nikita (26:05):** And, you know, routing for us becomes a little bit more complex because we have to account for higher slippage and, higher gas costs. And that's where AI can do like brilliant things by predicting the market conditions based on the previous cases where things have happened. can also, yeah. So this is one use case where we've adapted AI for our algorithms and logic, but they do not. affect day-to-day operations. It's just for, you know, this volatility cycles. **Gabe (26:35):** Got it, got it. And do you see this kind of trending in that direction? Or do you think, you know, for your product, it still is too early? Yeah, I'm curious on that piece. **Nikita (26:45):** Excellent question. I don't know for sure. ⁓ I think it feels like mass does the work. I would say that probably AI lowers the barrier of entry because for example, one of our co-founders algorithmically, he have been building a shipment software for over nine years and the software is used by giants like IKEA, Philip Morris, Pepsi to... bring the goods global from different factories into different countries. And he told us the same mathematical problem, how you optimize shipment of assets and how you optimize DeFi routing. And it's funny that I was just at ECC Cannes and I was speaking with trade five people, institutionals, and there were a few engineers from Fidelity. who instantly said, wait, like, like, routing sounds so much similar to shipment. And yeah, you know, it was the first time someone told me that outside of our team, but this was our alpha. And this is what like this experience, his experience helped us build a very good system that was extremely competitive, like in 23, 24. Now I think anyone can kind of do it, relying on AI, relying on like, you know, public knowledge and even my be able to try like different concepts and stuff. **Gabe (28:05):** So you guys are looking at solving as almost as logistics essentially. **Nikita (28:10):** Yes, this is how our algorithm is built. **Gabe (28:14):** Interesting. yeah, without spilling that, the alpha, how do you frame shift between kind of thinking of them as, you know, trading versus supply chain, **Nikita (28:24):** Yeah, well, our vision is that, you know, AMMs are being abused and not earning enough yield to be competitive. Moreover, know, another thing we have in mind is that DeFi is still extremely complex. let's look at the, you know, what happened with the infamous, notorious, know, ⁓ swap on Aave when the user lost like $50 million. That happened like a couple of weeks ago. The swap went through Cowswap and one of the solvers for some reason didn't have like the best security constraints and executed swap at a terrible, terrible rate for a user. Nobody knows and nobody yet fully understands what happened and who was this user and what happened with the funds that he was trading. However, we provided a couple of feedback to different media news agencies, for example, DL News and Blockworks. we've seen the swap was so notorious that it was covered even in media like Forbes. But a lot of data and information that was inaccurate in terms of who profited, what actually happened with the funds, and where is the issue coming from? So we think one of the issues is that DeFi is still really complex. imagine you're given approval first, you wait for ⁓ a block time, so like 12 seconds, until you approve assets to be used in a certain protocol. Then you perform this swap in action and you wait for it to settle. are incurring like slippage. So DeFi is still very, very clunky. That's why the volumes are not there. I've spoken with a lot of different founders and we all agree that DeFi haven't happened yet. It's still small, it's still niche. It's by far the best use case crypto has, but it hasn't like fulfilled all its promises. And we need to make it user friendly. And this is what we do with barter, with superposition because user doesn't need to know what's happening. Like they can check. They can verify the logic, but users are not monitoring day to day what's happening with their liquidity. Moreover, if they've given approval to us next time when they will want to swap those assets, they have like one less action they would need to do on chain because we already have an approval. So, yeah, this is our vision on what's happening and what's not working and how do we bring DeFi to the next level. **Gabe (30:52):** Yeah, well, thanks for that. And I'm curious for you, what are you kind of seeing now, especially during this quiet, I know you said before we got on the call, Ken was really good. What are you seeing as the things that you're pretty excited for, kind of where people should be looking at? we wanna see where the alpha's at, right? or the signal essentially. And maybe it's not like, buy this coin, but more so like in what direction should we be looking when it comes to your domain superposition? I think you're saying one of them, yeah, with that in mind, like how are you looking at that? **Nikita (31:30):** So let me compare the market sentiment I felt during Consensus Hong Kong and East Denver, which happened in February, and East Cannes. So in February, during those conferences, there were much less users, and people were a little bit confused in terms of what's actually going on. And, you know, like all the market trends were kind of going down, you know, the token prices, the volumes, the active users on chain, blah, blah, blah. So, yeah, everyone was quite pessimistic. However, what I've seen in Cannes is that we have a lot of real builders. We have quite a good amount of theoretical use cases and they're not yet, they're not even theoretical. They're already... There are like MVP, you know, proof on chains that they work. They just need to scale operations and get people and they, you know, grow it. And, you know, this feels like the flywheel is starting to get back on track. And they were like real builders in Denver. Everyone was, you know, like directly related. There were like less random people, less traders, maybe less people doing BD. I'm a BD person myself, but it's kind of good. good to see a lot of technical talent, engineers, people who fill the product and update it on a daily basis. about what's exciting, I feel like, imagine I have like a thousand USDC and you have a thousand USDC. And if I deposit it into Uniswap, I get one sort of yield. If you deposit it into Ava, you get like a different sort of yield. And... **Gabe (33:10):** Any. **Nikita (33:11):** our yields may vary by various numbers. Like I would get like 3%, usually like Uniswap LPs earn like 2 to 3%. And the other, it would be higher, it would be like 4, 4.5, maybe like 5%. So essentially the same, know, assets power different primitives, earn different yields, someone earns less, so someone is like less aware, and essentially will move towards where he can earn more. But I feel like there is a lot of convergence happening between those DeFi Legos. And everyone was building different parts of the stack. And now people are building everything under one hood. So what I'm trying to say is that projects like Fluid, for example, their liquidity is deposited into them. is used for both AMM liquidity, like for swaps and for lending. So it powers like essentially those two primitives. And I think this is nice. I think we need like a same kind of shared liquidity layer that would power bridging, that would power swaps, that would power like lending. Our superposition is one way of doing it. There is a one inches building towards a similar use case. Their platform is called Aqua. It's not yet live, but they've built a developer SDK. I also think there are like a lot more things that are happening with stable coins and real world assets. ⁓ It's ⁓ surprising that a lot of like DeFi people, actually want to trade real world assets on chain. And I think we should allow them to do it. And we've had some big names, pioneers like Ondo, but Ondo reminds me a lot of Bencore or Kyber network, would say like early DeFi 2018. And those platforms were gated. So for example, I couldn't have built a pool on top of Kyber network. need to do like QIC, QIB. need to provide like legal opinion letters that the token I'm bringing there is not a security and stuff like that. Uniswap didn't have this constraints and we see new real world assets that offer kind of similar. user experience without like gated entrance. yeah, people are loving it. People are experimenting. People want to buy like oil and like trade it. I would say a lot of use cases are still kind of, you know, not gambling, but I would say trading and, you know, get rich fast oriented. However, **Gabe (35:29):** Mm-hmm. Yeah. **Nikita (35:43):** Yeah, yeah, yeah. In the long run, it always bring innovation and bring like sustainable good use cases that will benefit everyone in the industry. So this is, this is my take. **Gabe (35:53):** Okay, so basically this like collapse of the fragmentation is this big piece and then some extended assets that can be traded whether it's like RWA, know, tokenized stocks or commodities, etc. **Nikita (36:07):** Yes, I also want to add that I feel like Ethereum Foundation started to play a much bigger role than it used to be because historically, know, Ethereum was always very decentralized and it was kind of hard to like engage with the core team and the foundation. And now they are helping, you know, bootstrap daps and they've hired a lot more people to coordinate. Sounds very refreshing and I think it will help smaller teams pioneer new use cases. also the fact that L2s are trying to specialize and a lot of activity is going back to Ethereum Mainnet. It also feels nice and lowers liquidity fragmentation. **Gabe (36:50):** Cool man. Yeah, this has been super great. I think a lot of people don't quite understand how much thought goes into kind of under a swap and it's not just like, you know, concentrate liquidity or even... you know, like full range, these two mechanisms that people don't even really know about themselves. But there's like a whole underworld network of money movements and routes and ordering. yeah, so yeah, appreciate you coming on. Yeah, if there's anything we didn't cover, like happy to have you share a little bit more. **Nikita (37:21):** Yeah, no, I'm super excited about the future of Ethereum, DeFi, crypto in general. I think there are a lot of synergies with AI and of course, AI has a faster adoption pace and solves a lot more use cases. However, crypto is solving finance, it's solving transparency, this is what we need. yeah, I also feel like building in crypto is incredibly tough and... for all this like DeFi primitives, one simple mistake can lead to like catastrophic losses by users, liquidity providers, like other protocols as well. We've seen a couple of nasty exploits recently like with Resolve and Rift. And yeah, I feel like people should just be aware that it's such a complex part of the stack, but it's very essential and it's when it succeeds. It's gonna be huge for everyone and I'm bullish it will happen sometime, you know, next year or so. **Gabe (38:18):** Yeah. Cool, man. Well, thanks. Yeah, Nikita, thanks for coming on and sharing the ins and outs and hope to have you soon. **Nikita (38:27):** Thank you so much, Gabe. You know, really appreciate everything you guys do at Shoal Research. I think you guys provide some of the best insightful pieces on the market. Our team reads all of them. Yeah, thank you. **Gabe (38:38):** Appreciate it. Yeah. Take care. **Nikita (38:40):** Take care, bye bye.