Original | Odaily Planet Daily (@OdailyChina)

Author | Azuma (@azuma_eth)

On March 10, the dAI team, which is part of the Ethereum Foundation and focuses on promoting the deep integration of "Artificial Intelligence (AI) and blockchain," today launched a new standard ERC-8183 in collaboration with Virtuals Protocol.

The head of AI at the Ethereum Foundation, Davide Crapis, stated that ERC-8183 is one of the missing components for the open Agent economic system that the Ethereum community is building. This standard can be combined with x402 and ERC-8004, playing an infrastructural role in secure interactions between Agents. The dAI team will support the adoption of ERC-8183, aiming to make it a neutral standard.

What does ERC-8183 aim to solve?

According to the introductory article released by Virtuals Protocol, ERC-8183 is designed for commercial transactions between AI Agents. This standard defines a set of on-chain rules that allow two untrusted Agents to complete business processes such as "hire-deliver-settle" without relying on centralized platforms.

The core problem that ERC-8183 seeks to address is how to complete transactions when Agents hire and cooperate with each other without a platform, without laws, and without human arbitration?

For example, if a marketing-oriented Agent A wants to hire another image-generating Agent B to create a batch of marketing posters, there exists a commercial trust issue—neither party knows each other and there is no basis for trust. When is the payment to be made? If A pays upfront, B might go on strike or deliver unsatisfactory results; if B does the work first, A might refuse to pay…

In the traditional internet world, users and businesses also face similar commercial trust issues, and platforms play a crucial intermediary role—they host A's funds, determine whether B's services are completed, and handle the final payout. Well-known platforms like Taobao, JD.com, Meituan, and DiDi essentially serve as such platform-based intermediaries.

What the Ethereum Foundation and Virtuals Protocol aim to do is abstract the functions of the platform into a on-chain protocol through ERC-8183, executed by smart contracts to take on a decentralized intermediary role in the Agent economy.

Breakdown of the ERC-8183 operational scheme

The operational mechanism of ERC-8183 is not complicated; this standard introduces a new concept called Job (which can be understood as "task"). Each Job can be viewed as a complete business transaction, involving three different roles:

• Client: "Client," simply put, is the Agent that publishes various tasks;
• Provider: "Provider," which is the Agent responsible for completing the tasks;
• Evaluator: "Evaluator," a unique role responsible for determining whether the task is completed.

It needs to be emphasized that the Evaluator is the core design of ERC-8183. In this standard, the Evaluator is defined only as an on-chain address, but from a broader perspective, this address can correspond to various execution forms.

• For subjective tasks such as writing, design, or analysis, the Evaluator can be an AI Agent that reads the submitted results, compares them with the initial task requirements, and then makes a judgment;
• For deterministic tasks like computation, proof generation, or data transformation, the Evaluator can be a smart contract encapsulating a zero-knowledge verifier (ZK verifier). The Provider submits the proof, the Evaluator verifies it on-chain, and automatically calls "complete" or "reject" to finish or reject the task;
• In high-value or high-risk task scenarios, the Evaluator can also be a multi-signature account, DAO, or a validation cluster supported by a staking mechanism.

ERC-8183 does not distinguish between these different forms. The protocol layer only cares about one point—whether a certain address calls "complete" or "reject." Whether this address runs an AI Agent driven by LLM or a ZK circuit does not fall within the scope of the protocol's concerns.

Returning to the Job, each Job has the following four lifecycle states, which correspond to different processes when ERC-8183 operates.

• Open: The Client creates the Job in this cycle, publishes tasks, and specifies requirements;
• Funded: The Client transfers the commission to a smart contract escrow address rather than directly to the Provider;
• Submitted: The Provider completes the work and submits proof;
• Terminal (Completed / Rejected / Expired): The Evaluator is responsible for reviewing the task and determining whether it is completed (Completed or Rejected), transferring funds to either the Client or Provider accordingly. If no Provider responds or completes the task within the time required, the funds are returned to the Client.

Apart from the standard procedures outlined above, ERC-8183 can also realize more derivative functions through modular extension features called Hooks, adapting to complex business use cases in the real world. Hooks are optional smart contracts attached when creating a Job, which can execute custom logic before and after various lifecycle stages of the Job, such as credibility thresholds, bidding mechanisms, cost allocation, or other special requirements.

How does ERC-8183 differ from x402 and ERC-8004?

From x402 to ERC-8004, and now to ERC-8183, readers unfamiliar with this concept might be confused, wondering why a new item is needed every once in a while. However, these three standards are at three different stages of the AI Agent economic system, addressing different issues.

x402 is an HTTP payment protocol that aims to enable AI Agents to make direct payments like calling an API; ERC-8004 is an identity and reputation standard for AI Agents that solves how to assess whether an Agent is reliable; ERC-8183 addresses the commercial transaction phase, seeking to break the challenge of how to enable two untrusting Agents to complete a transaction.

To summarize in one sentence: x402 solves "how to pay"; ERC-8004 determines "who the other party is and its reliability"; ERC-8183 manages "how to trade with confidence."

The three are not competitive but complementary, collectively pointing towards the same goal—building a decentralized, autonomously operating AI Agent economic system.

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