When wallets begin to embed AI Agents: Why is the new interaction paradigm ERC-8211 worth paying attention to?

Starting in 2025, many people may gradually become accustomed to a new way of interaction: telling GPT or Gemini, “Help me plan my trip to Hong Kong next week and recommend suitable flights and hotels,” and it will silently perform information searches, filter conditions, route selection, price comparisons, and a series of steps in the background, finally only presenting you with the results for confirmation.

However, bringing the same expectation onto the blockchain, the story completely changes.

For example, if you give a DeFi Agent the command: “Swap ETH in the wallet for USDC, cross to the Base chain, and deposit the full amount into Aave,” objectively speaking, from the perspectives of “understanding the need” and “planning the path,” today’s Agent may not necessarily be incapable. The real disconnect appears in the execution phase:

You still likely need to complete steps like signing, authorization, swapping, cross-chain transfer, and deposit one by one, each exposed to risks such as slippage fluctuations, Gas volatility, bridge delays, and on-chain state changes. This also means that if any step deviates from expectations, the previous actions may not be reversible, and subsequent steps might not connect properly, leaving only an incomplete process on-chain.

The problem isn’t that AI isn’t smart enough; it’s that the execution layer on-chain still lacks a truly suitable expression method for Agents.

For this reason, in early April 2026, Biconomy and the Ethereum Foundation jointly released ERC-8211, aiming to address the current “static constraints” in smart contract execution, providing a more expressive execution layer for AI agents and complex DeFi workflows, attempting to fill this missing piece.

1. The “Final Disconnect” of AI Agent Integration on Chain

Over the past one or two years, the focus of the crypto industry has shifted from L2 scaling and RWA liquidity to a more disruptive topic: how AI Agents can truly take over on-chain operations.

Objectively, from “issuing multi-step DeFi strategies via natural language” to “letting autonomous Agents manage entire cross-chain portfolios,” we’ve seen many practical implementations recently. Most concepts are already mature at the demo level, including generating multi-step DeFi strategies via natural language, autonomous rebalancing, automatic yield migration, cross-chain position adjustments, and even more complex portfolio management.

From reasoning and orchestration perspectives, AI capabilities have advanced rapidly. However, when truly deploying into production environments, the shortcomings of execution layers become increasingly apparent.

In production, this shortcoming can be summarized in one sentence: DeFi is dynamic, but most current batch processes are static.

The official website and discussion posts for ERC-8211 clearly state this issue: existing standards like ERC-4337 and EIP-5792 have indeed advanced from the old model of “one signature corresponds to one call” to a new stage where “one signature can pack multiple calls,” but the parameters within these calls are still largely frozen at the moment of signing.

In other words, the amounts, target values, and expected outputs filled in at signing time do not automatically adjust based on on-chain state changes during execution.

But DeFi itself is full of uncertainties. The actual output of a swap depends on slippage and liquidity in the block being executed; the arrival time and final amount of a cross-chain transfer depend on the bridge’s mechanism and fees; the share-to-asset ratio in lending protocols or vaults also constantly changes.

After all, the values users or Agents see at signing are often just current estimates, not the actual results at execution time.

To understand what ERC-8211 solves, consider a typical example: suppose an Agent wants to do something seemingly simple—swap ETH for USDC in the account, then deposit the full amount into Spark to earn interest.

Under the current static batch processing model, the Agent must estimate how much USDC it will receive after the swap before signing, often forcing you to hardcode the input amount for the second step at signing time. If the estimate is too high and the actual amount received is insufficient, the entire batch rolls back; if too low, some funds remain idle in the wallet and can’t be used.

In other words, it falls into a dilemma: either bear the risk of failure or accept opportunity costs. This is why many seemingly straightforward on-chain processes become fragile once steps extend to 5, 8, or even cross two chains—not because the strategies are too complex to describe, but because the current execution paradigm relies heavily on pre-written, static parameters.

In short, the upper limit of static batch processing essentially determines the maximum safe strategy an Agent can execute.

From this perspective, ERC-8211 aims not to decide how AI Agents make decisions, but to provide a more natural, stable, and secure way to execute decisions once made. It seeks to give on-chain execution a native expression format designed specifically for AI Agents.

2. What Exactly Has ERC-8211 Changed?

The core breakthrough of ERC-8211 isn’t about packing more steps into a single signature, but about upgrading batch processing from a sequence of parameters hardcoded into a transaction to a “program that evaluates parameters dynamically at execution time.”

It sounds abstract, but it’s not hard to understand. The official description is: From transactions to programs.

This means ERC-8211 no longer treats batch as a list of actions to be executed sequentially. Instead, it views it as a runtime-evaluated, condition-checked execution program. Specifically, it achieves this through three combinable primitives:

• Fetchers: Define where to get the value for a parameter. It could be a query of the current balance of a specific address, making the parameter no longer a snapshot at signing but a real-time read from the chain’s state during execution;
• Constraints: After a parameter is derived, it must pass inline constraint checks—e.g., “USDC received must be ≥ 2500,” or “slippage cannot exceed 0.5%.” These constraints are verified before routing the value into the next call. If any check fails, the entire batch immediately reverts;
• Predicates: Act as gatekeepers between steps, responsible for deciding whether to continue. They do not produce values but judge whether to proceed. For example, in a cross-chain scenario, the batch on Ethereum can be guarded by a predicate that waits until “WETH transferred from cross-chain has arrived” before submitting.

In this design, each parameter must answer two questions: first, where does this value come from at execution; second, what conditions must be satisfied before it is used in a call. The combination of these three makes a batch no longer just a sequence of transactions but a program embedded with safety checks.

Ultimately, the mental model of static batch processing is a checklist—execute A, then B, then C in order. ERC-8211’s mental model is a conditional program—after executing A, take its real output as input for B; only proceed if B satisfies constraints; if any step deviates, roll back the entire batch.

We can simply understand it as a “smart batch processing” mechanism designed specifically for AI Agents and complex DeFi operations, because in traditional on-chain operations, completing a complex DeFi strategy often requires multiple separate transactions: withdrawing funds from lending protocols, swapping tokens, then depositing into another protocol (see also “The Panorama of Crypto AI Protocols: How to Build a New Operating System for AI Agents Starting from Ethereum’s Main Battlefield”).

Each step requires individual signatures and confirmations, which is already cumbersome for human users and a bottleneck for high-frequency autonomous AI Agents. ERC-8211’s solution is to allow multiple blockchain operations to be combined into a single transaction, with each step dynamically parsing actual values at execution and only proceeding if predefined conditions are met.

For example, an Agent can complete atomically in one signed transaction: withdraw funds from Aave → swap the received amount on Uniswap → deposit the swap result into Compound—all in one atomic execution, without writing new smart contracts.

3. Why Is It More Related to Wallets, Especially Smart Wallets?

ERC-8211 is worth the attention of the wallet industry not only because it suits Agents but also because it will redefine the wallet’s role in the interaction chain.

Traditional wallets are more like secure signers: their job is to hold private keys, display transactions, get user confirmation, and then send signatures. This role was crucial in the EOA era and remains so in the account abstraction era. But if more on-chain operations are performed by Agents in the future, the wallet’s role will become even more central and significant.

The reason is simple: when users no longer control each on-chain action step-by-step but instead authorize an Agent to execute a whole set of goals, the wallet must be capable of handling this higher-level interaction. It needs to display not just a contract address and calldata but an entire “intent—value retrieval logic—condition checks—final outcome” execution program.

Therefore, future wallets need to understand not just transactions but programs. ERC-8211 provides a clearer handle for wallets because it explicitly encodes these execution semantics: where parameters come from, what conditions must be met, when to continue, when to revert. These are no longer hidden black boxes in backend logic but objects that wallets can interpret, simulate, and display.

From the wallet’s perspective, this entire mechanism ultimately points to the same goal: users no longer sign a string of low-level calls they can’t fully read, but a result-oriented, clearly bounded, condition-verifiable execution program:

• AI Agents can interpret user intent and generate paths;
• Wallets can display these paths more clearly for user review;
• Relayers only submit when conditions are met, without the ability to tamper with the outcome;

This is precisely why non-custodial execution is considered a prerequisite for Agentic DeFi: because the agent can participate, but sovereignty, constraints, and final settlement still reside on-chain. This is also where ERC-8211 aligns with smart wallets—by embedding “expressing complex safety-critical intents” into the protocol standard.

It’s worth noting that ERC-8211 is fully compatible with account abstraction standards like ERC-4337, EIP-7702, and ERC-7579. It doesn’t replace account abstraction but adds a layer of programmable execution semantics on top of it.

If ERC-4337 solves “who can initiate transactions on my behalf,” and EIP-7702 addresses “how EOA can temporarily gain smart contract capabilities,” then ERC-8211 addresses the question: Once an Agent starts acting on my behalf, can it complete an entire decision chain in a single signature?

Looking back at the evolution of on-chain interaction paradigms on Ethereum over the past decade:

• First phase: One signature = one function call (EOA era)
• Second phase: One signature = a static batch of calls (ERC-4337, EIP-5792 era)
• Third phase: One signature = a dynamically evaluated intent program (ERC-8211 era)

Each transition means users (or their Agents) can express more complex goals with less friction.

Although ERC-8211 is still in draft and ongoing discussions, and large-scale protocol integration will take time, its direction is already clear: when AI Agents truly start making on-chain decisions for humans, the chain needs a native execution syntax that matches this capability.