Author: Merkle3s Capital; Source: X, @Merkle3sC

From "helping you view market trends" to "executing on-chain yourself," AI is entering the true financial operation layer.

Introduction: AI is no longer just an advisor, it is beginning to become an executor

Over the past two years, AI's role in the crypto market has been clear:

• Summarizing the news

• Interpreting white papers

• Analyzing data

• Developing and writing code

But it has never involved real on-chain operations; the key content is still your own confirmation.

In February 2026, this boundary underwent a structural change: [Image of a PNG file: https://img.jinse.com.cn/7436717_watermarknone.png](https://img.jinse.com.cn/7436717_watermarknone.png) [Image of a PNG file: JV9LOATivT6jOlR8cvqnwIYTc6kOpdts5R5Uk8vB.jpeg](https://img.jinse.com.cn/7436717_watermarknone.png) [Image of a PNG file: JV9LOATivT6jOlR8cvqnwIYTc6kOpdts5R5Uk8vB.jpeg) ...

• Coinbase Launches Agentic Wallet + x402 Protocol — Giving AI its own wallet, funds, and payment capabilities.

This is not a concept, nor a roadmap.

This is a system that is already running on the Coinbase mainnet. The question is no longer whether AI can analyze DeFi, but whether AI can execute DeFi for you. Firstly, what AI lacked in the past was not capability, but "operational authority." Many people mistakenly believe that the reason AI has not truly entered the operational layer of DeFi is because its models are not strong enough. The truth is quite the opposite. The large-scale models after 2024 already possess: Complex logical reasoning ability; Financial structure understanding ability; Code generation and debugging ability; Multi-step task decomposition ability. It can completely calculate: Which pool has higher fees; Which interval has better capital efficiency; When to shift positions. When should risk exposure be reduced? But it can't do one thing: it can't touch money. 1.1 The role of early AI: researcher, not trader. Before the advent of Agent Skills and Agentic Wallets, AI's position on the blockchain was very awkward. It can: Read on-chain data; parse contract structure; generate transaction paths; calculate gas costs. However, the final execution is still: AI gives you a suggestion; you open Uniswap; you click confirm yourself. AI is only the "suggestion layer," not the "execution layer." In other words: **It handles the thinking, you handle the risk.** This is the true form of AI + DeFi over the past two years. 1.2 The Real Gap: Three Infrastructure Elements Not in Place The reason AI has been unable to enter the operational layer is not a model problem, but an underlying architecture problem. **Part One: Interface Fragmentation** Each protocol has different SDKs, different data formats, and different parameter logic. For AI to integrate, it must be adapted separately for each protocol. This is extremely inefficient for machines. The second point: Wallets not designed for agents. Traditional wallets assume human users: Manual signatures are required; there are no independent limits; there is no session-level control; and there is no machine identity management. Even if AI can generate transactions, it cannot securely hold and manage assets. The third aspect: Lack of a machine payment system. AIs cannot: Automatic collection of payments; Automatic payment; Settlement based on the number of calls. There is no "machine-to-machine" economic layer. This means that AIs can only exist by attaching to human accounts. 1.3 The puzzle wasn't complete until 2026. In February 2026, three variables changed simultaneously: Uniswap uses Skills to structure protocol capabilities; Coinbase reconstructs the wallet model with Agentic Wallet; the x402 protocol empowers machines with payment capabilities. This isn't a single project's innovation. It's the simultaneous alignment of the protocol layer, account layer, and payment layer. Once these three layers are complete, AI will have the potential to become an "on-chain participant" for the first time. II. Uniswap Skills: Translating the "Human Interface" into a "Machine Interface" How does Uniswap transform protocol capabilities into a structure that machines can directly invoke?

2.1 From UI to API: Protocol Rewrites Interface for AI for the First Time

The design logic of past DeFi protocols was:

• Human-oriented

• Interacting via webpage

• Clicking buttons

• Signature confirmation

This is a typical UI (User Interface) paradigm. But for the Agent, the UI is meaningless. ...ul>

On-chain execution. For example, liquidity-planner can: Read the current pool state and calculate the price range. left;">Simulating capital efficiency under different intervals

Outputting optimal interval suggestions

But it won't directly touch your wallet.

It generates:

• Explicit parameters

• Deep link

• Executable transaction structure

In other words: It helps AI figure out "how to do it," but doesn't sign it for you. This design is very rational because it separates "intelligent decision-making" from "asset control."

2.3 Why is this step so important?

For humans, this is simply a tool upgrade. For machines, it's a role reversal. Before Skills: AI could only interpret data and could not directly call the core capabilities of the protocol. With Skills: AI can call DeFi protocols like functions and can perform multi-step logical planning and generate transaction paths in batches. This means that for the first time, DeFi protocols have truly become "machine-friendly infrastructure." 2.4 From Multiple Operations to Atomic Transactions Traditional Process: At least 2–3 transactions. Using the planning module allows you to: Merge logic, optimize paths, and reduce unnecessary calls. In complex scenarios, it can be compressed into a single atomic transaction. For high-frequency agents: Gas costs decrease, execution efficiency improves, and failure probability decreases. This isn't just about optimizing the user experience. It's a prerequisite for scaling up machine operations. 2.5 But Skills are not the end goal. It's important to emphasize that Uniswap Skills solves the problem of structuring protocol calls. It does not solve: Who holds the assets? Who signs them? Who sets the limits? Who bears the execution risk? Because once protocol capabilities are structured, the real core issue becomes: Who provides the AI ​​wallet? III. Agentic Wallet: When AI First Has an "Account" If Uniswap solves the problem of "how AI calls the protocol," then Agentic Wallet solves a more fundamental problem: Can AI become an independent financial entity? This is the core of the entire structural change. 3.1 Assumptions of Traditional Wallets: Users are Humans Existing wallet systems assume by default that: Users have subjective judgments; users can manually confirm; users understand the risks; and users are responsible for their private keys. This is a "human-centric design." However, agents do not conform to these assumptions. It:

• lacks subjective risk perception

• requires automatic execution

• requires access control

• requires programmable behavior boundaries

traditional wallets cannot serve this role.

3.2 The Core Logic of Agentic Wallet The core design of Agentic Wallet consists of three things: ① Programming the "Signing Right" This means that AI can be authorized to execute automatically within "controllable boundaries". ② Private Key Isolation and Execution Security The private key of Agentic Wallet is stored in a TEE (Trusted Execution Environment). Key Points: The model itself cannot read the private key. Even if the reasoning logic is abnormal, assets cannot be directly stolen. All transactions have permission verification. This is the premise for "automatic execution". ③ Gas Payment Mechanism (Base Network) On Base: Gas payment via Paymaster AI eliminates the need for separate gas balance management Supports continuous automated execution This is crucial infrastructure for high-frequency strategies.

3.3 Built-in Agent Skills: Modular Execution Capabilities

Agentic Wallet has five built-in core capabilities:



This means that: AI is not just a "path generator," but truly possesses "execution rights."

When execution rights are combined with asset ownership rights, the roles change.

AI is evolving from an "assistant" to an "operating entity." 3.4 x402 Protocol: The Economic Layer Between Machines The significance of Agentic Wallet extends beyond automated trading. The core function of the x402 protocol is: Supporting automatic machine payment collection. Supporting automatic machine payment. Supporting settlement based on the number of calls. This means that: One Agent can pay another Agent; it can purchase computing power; it can purchase data sources; and it can automatically settle service fees. This is no longer a matter of "humans directing machines." This is a machine-to-machine economic closed loop. 3.5 Structural Change: Accounts Transform from "Human Tools" to "Machine Nodes" When AI possesses: the ability to invoke protocols (Skills), the ability to hold assets (Wallet), and the ability to make payments and receive income (x402), a new type of role emerges in the financial system: non-human economic participants. This is not an efficiency upgrade; it is a change in the participation structure. In the past: Only human accounts participated in liquidity. All actions stemmed from human decision-making. In the future: Some liquidity will be managed by agents. Some arbitrage will be executed by agents. Some payments will be completed automatically by agents. As account types change, market behavior patterns will also change. 3.6 But this is still early stage. It must be emphasized that: Automation errors will be amplified; Risk control logic is still iterating; The legal and regulatory framework is not yet clear; Market competition will compress profit margins. Technology implementation does not guarantee profitability. But the structure has already changed. IV. Why now? Three conditions mature simultaneously. Technology doesn't happen overnight. The emergence of Uniswap Skills, Agentic Wallet, and x402 is not accidental, but rather the first intersection of three technology curves in 2026. 4.1 The Model Cost Curve Has Turned Downwards The cost of deploying a moderately active policy agent in 2024 was not low: Advanced model inference costs; frequent API calls; complex logical chain inference. If an agent runs 24 hours a day, the monthly cost could reach four figures in US dollars. But by 2026: Inference costs will decrease; token prices will decrease; model efficiency will improve; and local inference capabilities will be enhanced. The result is that the cost of deploying multiple vertical agents will become acceptable. This means that "AI employees" will begin to transform from a luxury into a role that can be mass-produced. 4.2 Unified Interface Standards: The Emergence of MCP In the past, when AI accessed each protocol, it required: Separately written parsing logic; Separately written data mapping; Separately written call structure. After the emergence of MCP (Model Context Protocol): AI and tools have a unified interface language; The protocol can be standardized to publish capability modules. Agent This step, which allows batch invocation of different protocols, is equivalent to **adding a "USB interface" to the DeFi protocol**. Without this unified layer, agents cannot scale. 4.3 Mature L2 + Gas Payment Mechanism Automated execution has an implicit prerequisite: **transaction costs must be low enough**. In the high-gas era of the 2021 mainnet, high-frequency execution by AI was almost impossible. But now:

• Mature L2 network

• Low-cost base environment

• Paymaster supports gas payments

Agents can:

• High-frequency, small-amount operations

• Continuously execute strategies

• Automated finance without manual gas replenishment

Only now does it truly have a realistic foundation. 4.4 The Intersection of Three Curves If we look at any one of them individually: Strong enough model, but no wallet → Cannot execute Wallet exists, but expensive model → Cannot scale Low gas, but messy interface → Cannot be integrated Until 2026: Model cost decreases Interface standardization Wallet Model Reconstruction

• Gas Costs Controllable

The three curves intersect for the first time. This is the answer to "why now?".

Conclusion: When market participants are no longer just "people"

AI has moved from the "suggestion layer" to the "execution layer."

This is not a product update, but a change in the participation structure.

This is not a product update, but a change in the participation structure.

From Tools to Nodes Past AI: Helping you analyze; Helping you calculate; Helping you generate code. But ultimately, decision-making and execution were all done on human accounts. Now: Protocol capabilities are structured (Uniswap Skills) Account models are restructured (Agentic Wallet) Payment layers are integrated (x402) AI can: Hold assets Execute within limits Automatic payment collection and disbursement Continuously operate This means it's no longer just a "tool." It's becoming an on-chain node that can be authorized, restricted, and managed. This isn't an efficiency upgrade, but a change in the role of participants. As more and more strategies are executed by Agents: LP range management will become more automated; arbitrage opportunities will disappear faster; market response speed will be higher; and volatility transmission may be more intense. This is very similar to the process of high-frequency trading entering traditional financial markets. The difference is: this time it's happening in an open-chain system. However, we are still in the early stages. We must remain calm: Automation does not guarantee returns. Model errors may be amplified. Market competition will quickly compress excess returns. The boundaries of law and responsibility are not yet clear. This is not the beginning of an era of "easy money." This is the start of "structural change." The real question is: In the past, we asked: Can AI help me with transactions? Now, the more important question is: How will the market be reshaped when a portion of on-chain liquidity is managed by agents? And: In a system where machines can also be economic participants, where will humans find their advantage? Perhaps the answer isn't faster. Rather, it's clearer risk assessment, strategy design, and authorization boundaries. Uniswap has given AI operational capabilities. Coinbase has given AI accounts. x402 has given AI payment capabilities. With these three layers stacked, AI on the blockchain is no longer a fantasy. The era has begun, but many haven't realized it yet.