Starting in 2025, many people may gradually begin to get used to a new way of interaction: saying to GPT or Gemini, "Help me plan a trip to Hong Kong next week and recommend suitable flights and hotels," and it will silently complete a series of steps in the background such as information search, condition filtering, route selection, and price comparison, finally just handing you the results for confirmation.

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

For example, if you give a DeFi Agent the command: "Convert ETH in the wallet to USDC, cross to the Base chain, and deposit the full amount into Aave," objectively speaking, from the perspectives of "understanding demand" and "planning a path," today's Agent may not necessarily be unable to achieve this; the real gap appears in the execution phase:

You will still likely have to gradually complete operations such as signing, authorization, conversion, cross-chain transfer, and deposit, and each step is exposed to risks such as slippage changes, gas fluctuations, bridging delays, and on-chain state changes, which also means that as long as one link deviates from expectations, the previous actions may not be reversible, and the subsequent actions may not connect, leaving on-chain what often amounts to an incomplete, half-finished process.

The problem is not that the AI is not smart enough, but that the blockchain execution layer still lacks a truly suitable expression method for Agents.

For this reason, in early April 2026, Biconomy, in collaboration with the Ethereum Foundation, released the ERC-8211, aimed at solving the "static limitations" in current smart contract execution, providing a more expressive execution layer for AI agents and complex DeFi workflows, attempting to fill this missing piece of the puzzle.

1. The "Last Gap" for AI Agents on the Blockchain

In the past one to two years, the focus of attention in the crypto industry has clearly shifted from L2 scaling and RWA liquidity to the disruptive topic of how AI Agents can truly take over on-chain operations.

Objectively speaking, we have seen many practices recently, from "issuing multi-step DeFi strategies in natural language" to "allowing autonomous Agents to manage entire cross-chain investment portfolios," with most concepts already matured at the demo level, whether it’s natural language generation of multi-step DeFi strategies, autonomous execution of rebalancing, automated yield migration, cross-chain position adjustments, or even more complex portfolio management.

From the perspective of reasoning and orchestration, AI capabilities have made significant strides; however, when it comes to placing it in a production environment, the shortcomings of the execution layer become increasingly apparent.

When it comes to production environments, this shortcoming can be summarized in one sentence: DeFi is dynamic, but today most batch processes are still static.

The ERC-8211 website and discussion posts clearly articulate this issue, stating that the existing ERC-4337 and EIP-5792 have indeed advanced the old model of "one signature corresponds to one call" to a new stage of "one signature can bundle multiple calls," but the parameters in these calls are essentially still mostly frozen at the moment of signing.

In other words, the amounts, target values, and expected outputs that users enter at the time of signing do not automatically adjust due to on-chain state changes when it comes time to execute.

Yet, DeFi itself is filled with uncertainty. The actual output of a swap depends on the slippage and liquidity of that block; the arrival time and final amount of a bridge depends on the mechanism and fees of the bridge itself; and the share-to-asset ratio of lending agreements or vaults also constantly changes.

After all, the values that users or Agents see at the time of signing are often just an estimate at that moment, not the actual results during execution.

To understand what ERC-8211 solves, let's look at a typical example, assuming the Agent wants to do something that seems very ordinary - exchange ETH in the account for USDC and then fully deposit it into Spark to earn interest.

Under the existing static batch processing model, the Agent must estimate how much USDC it will receive after the swap before signing, often forcing you to hard-code the input amount of the second step during signing, leading to estimates that are too high resulting in insufficient actual incoming amounts, causing the entire batch to roll back; estimate too low, leaving some funds idle in the wallet unable to be used.

In other words, it gets you stuck in the so-called dilemma: either accept the risk of failure or incur opportunity costs. This is why many on-chain processes that seem not complicated, once extended to 5 steps, 8 steps, or even across two chains, quickly become fragile; this isn’t because the strategy itself is too complex to describe, but because the existing execution paradigm relies too heavily on hard-coded parameters.

In simple terms, the capacity limit of static batches actually determines the upper limit of strategies that Agents can truly execute safely.

From this perspective, what ERC-8211 aims to address is not the decisions made by AI Agents but whether there is a more natural, stable, and safe way to execute once the Agent has made a decision. Thus allowing on-chain execution to possess an expression form designed specifically for AI Agents.

2. What Exactly Changed with ERC-8211?

The core breakthrough of ERC-8211 lies not in cramming more steps into a single signature, but in upgrading batch processing from a sequence of transactions with frozen parameters to a program that dynamically evaluates parameters at runtime.

This might sound abstract, but it’s not difficult to understand; the official description uses one sentence: From transactions to programs.

This means ERC-8211 no longer views batches as a checklist of actions executed in order but rather sees them as a program executed under conditions and evaluated at runtime. To break this down, it achieves this through three combinable primitives:

• Fetchers: These define where a parameter fetches its value from. It can be a query of the current balance of a specific address, making the parameter no longer a snapshot at signing but a real-time reading taken from the on-chain state at the moment of execution;
• Constraints: Once a parameter is resolved, it must also pass inline constraints—such as "the received USDC must be ≥ 2500," or "slippage cannot exceed 0.5%." These constraints are verified before the value is routed to the next call, and if any of these fail, the entire batch rolls back immediately;
• Predicates: These can be understood as gatekeepers between steps, not responsible for generating values but for determining whether to continue execution. For example, in a cross-chain scenario, the batch on the Ethereum side can wait at the predicate ensuring "the WETH from cross-chain has already arrived," continuing only after the arrival;

In this design, each parameter must answer two questions: First, where does this value come from at execution; second, what conditions must it satisfy before being used in the call, leading to a combination that turns a batch from merely a transaction sequence into an embedded safe-checking program.

Ultimately, the mental model of static batch processing is a checklist—executing A, B, C in order; whereas ERC-8211's mental model is a conditioned program—A executes, the real output of A is used as the input for B; B proceeds to C only if it meets constraints; and if any step does not meet expectations, the entire batch rolls back.

We can simply understand it as a "smart batch processing" mechanism designed specifically for AI Agents and complex DeFi operations, as traditionally, completing a complex DeFi strategy on-chain often requires multiple independent transactions: pulling funds from lending protocols, exchanging tokens, and depositing into another protocol (see the extended reading "A Comprehensive Overview of Crypto AI Protocols: How to Build a New Operating System for AI Agents Starting from Ethereum's Main Battlefield?").

Each step requires separate signing and confirmation, which is cumbersome for human users and even more so a bottleneck for AI Agents requiring high-frequency autonomous operations, while ERC-8211's solution allows multiple blockchain operations to be combined and executed in a single transaction, with each step dynamically parsing the actual values during execution and continuing to the next step only after predefined conditions are met.

For example, an Agent can complete in one signed transaction: withdrawing funds from Aave → converting the actual received amount on Uniswap → depositing the conversion result into Compound—all atomically executed without needing to write a new smart contract.

3. Why It Has a Greater Relationship with Wallets, Especially Smart Wallets

ERC-8211 is worth the attention of the wallet industry not only because it is suitable for Agents but also because it will redefine the wallet’s position in the interactive link.

Previous wallets resembled secure signers, with the responsibility of safeguarding private keys, displaying transactions for user confirmation, and then sending the signatures. This role has already been significant in the EOA era and continues in the account abstraction era. However, if more and more on-chain operations are carried out by Agents in the future, the role of the wallet will become even more central and heavy.

The reason is simple: when users no longer control on-chain actions one by one but instead authorize an Agent to execute a whole set of objectives, the wallet must have the capability to handle this higher-level interactive object; it needs to represent not just some contract address and a segment of calldata, but an entire "intention—value logic—condition judgment—final result" execution program.

Thus, the future wallet needs to understand not only transactions but also programs. ERC-8211 provides a clearer grasp for wallets because it explicitly writes these execution semantics into the encoding structure, detailing where parameters come from, what conditions must be met, when to continue, and when to roll back, all of which are not hidden in backend logic but are transparent objects that wallets can interpret, simulate, and display.

From a wallet perspective, this whole mechanism ultimately points to one thing: Users no longer sign a string of underlying calls that are hard to fully understand, but sign an execution program that is results-oriented, clearly defined, and verifiable by conditions:

• AI Agents can be responsible for understanding user intent and generating paths;
• Wallets are responsible for clearly presenting this path for user review;
• While relayers are only responsible for submitting when conditions are fulfilled, without the authority to alter results;

This is precisely why non-custodial execution is seen as a prerequisite for Agentic DeFi, as agents can participate, but sovereignty, constraints, and ultimate settlement remain on-chain. This is also where ERC-8211 truly aligns with smart wallets, writing the task of "securely expressing complex intentions" into the protocol standard.

It is worth mentioning that ERC-8211 is completely compatible with account abstraction frameworks such as ERC-4337, EIP-7702, and ERC-7579; it does not replace account abstraction but adds a layer of programmatic execution semantics on top of it for Agents.

If ERC-4337 solves "who can initiate transactions on my behalf," and EIP-7702 addresses "how an EOA can temporarily gain smart contract capabilities," then what ERC-8211 solves is once an Agent begins to operate on my behalf, can it complete an entire decision chain in one signature.

Looking back at the evolution of Ethereum’s on-chain interaction paradigms over the last decade:

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

Each leap signifies that users (or Agents acting on behalf of users) can express more complex goals with less friction.

While ERC-8211 is still in draft stage with technical discussions ongoing, large-scale protocol integration will also take time, its intended direction is sufficiently clear; when AI Agents genuinely begin making on-chain decisions for people, there will be a need for a native execution syntax that matches this.

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