
ERC-8004 is about to go live on the Ethereum mainnet, providing a standardized solution for trust issues among AI Agents. The Google-driven AP2 and x402 protocols have integrated payment scenarios, but how cross-platform AI Agents verify each other’s identities and reputations remains a critical bottleneck. ERC-8004 establishes a trusted communication mechanism through on-chain identity verification and reputation systems.
As the x402 protocol gradually takes shape, AI Agents completing autonomous payments under user authorization are moving from conceptual validation to actual implementation and exploration. This is seen as a key technological attempt to shape the on-chain AI economy. The x402 protocol offers standardized payment interfaces for AI Agents, enabling token transfers, smart contract calls, and cross-chain transactions on the blockchain.
However, when we look further, a series of more fundamental questions emerge: How should users express and authorize complex intentions to AI Agents? How do AI Agents choose the optimal payment method during execution? How can we verify that each payment made by an AI Agent is truly authorized by the user? These issues manifest as the complexity of executing payment operations, but fundamentally point to a more basic premise: how to establish a trustworthy communication mechanism between “humans” and “AI Agents,” and between “Agents” and “Agents.”
This trust problem has already begun to surface in real-world scenarios. When users entrust an AI Agent to perform complex DeFi operations, that Agent may need to invoke other specialized Agents to complete specific tasks—such as calling a price oracle Agent for real-time quotes or a risk assessment Agent for security checks. Without a unified identity standard, how can the first Agent confirm that the other invoked Agents are genuine and reliable, rather than malicious impersonators or phishing programs?
Even more critically, the number of AI Agents is exploding. Industry data shows that by 2025, over 100,000 various AI Agents will be deployed across different blockchains and platforms. These Agents belong to different developers, serve different purposes, and use different tech stacks. In such a highly fragmented ecosystem, establishing unified identity and reputation standards becomes extremely urgent.
Against this backdrop, protocols for AI Agent payments and collaboration are beginning to take shape. In September 2025, the AP2 (Agent Payments Protocol), driven by Google, was released. This protocol aims to standardize the authorization, execution, and settlement processes for AI Agent payments, and through deep integration with the x402 protocol, provides a foundational channel for on-chain native AI payments.
The core contribution of the AP2 protocol is establishing a standardized payment process framework. It defines how AI Agents receive user payment intents, convert these intents into specific on-chain operations, select the optimal payment options, and provide feedback on execution results. This framework offers a common language for different developers to build interoperable AI Agents.
However, new questions arise: even if authorization processes and payment pathways are standardized, how should AI Agents verify each other’s identities and reputations when they begin to invoke, collaborate, and compose with one another? Currently, the number of AI systems and AI Agents is growing explosively, and cross-platform, cross-domain AI Agent collaboration will become the norm. If trust issues among Agents are not resolved, their mutual communication and invocation could face potential security risks, ultimately limiting the expansion of the on-chain AI economy.
This is precisely the core problem ERC-8004 aims to solve. Unlike the AP2 protocol, which focuses on payment workflows, ERC-8004 centers on the identity layer of AI Agents. It proposes a decentralized identity standard based on Ethereum smart contracts, allowing AI Agents to register unique identities on the blockchain, publish capability statements, and accumulate verifiable reputation records.
x402 Protocol: Provides the underlying interface for AI Agents to perform on-chain payments
AP2 Protocol: Standardizes authorization, execution, and settlement processes for AI Agent payments
ERC-8004: Establishes decentralized identity recognition and reputation systems for AI Agents
These three layers form a complete technical stack: ERC-8004 addresses “who is executing,” AP2 handles “how to execute,” and x402 deals with “what is being executed.” Only when all three layers are well-developed can the on-chain AI economy truly operate.
The technical architecture of ERC-8004 is based on Ethereum smart contracts and the ERC-721 non-fungible token standard. Each AI Agent, upon registration, receives a unique on-chain identity NFT, which contains basic information (such as creator address, version number, capability statements) and dynamic data (such as transaction history, reputation scores, third-party endorsements).
The identity verification mechanism employs asymmetric cryptography. When Agent A needs to invoke Agent B, Agent B can request Agent A to sign a challenge message with its private key, then verify the signature against the on-chain identity registry. This mechanism ensures that the caller truly controls the claimed identity, preventing impersonation.
The reputation system is more complex. ERC-8004 proposes a multi-dimensional reputation scoring model, considering factors such as:
Transaction History: Number of completed transactions, success rate, average transaction amount
User Feedback: User ratings and reviews of the Agent’s service quality
Expert Endorsements: Certifications from well-known developers or security auditors
On-Chain Behavior: Records of malicious activities, such as spam transactions or attack participation
Longevity: Duration of active presence on the chain; longer activity correlates with higher reputation
All these reputation data are stored on-chain and accessible for verification. When Agent A considers invoking Agent B, it can first check B’s reputation score. If the score is low or there are negative records, Agent A can choose to reject the invocation or require stricter execution conditions (e.g., collateral deposits).
ERC-8004 also introduces a “reputation collateral” mechanism. Developers can stake a certain amount of ETH or other tokens into the Agent’s identity contract as a guarantee of service quality. If the Agent acts maliciously or makes serious errors, users can initiate dispute resolution to confiscate part of the collateral. This mechanism provides economic incentives for maintaining good behavior and upholding reputation.
The greatest value of ERC-8004 lies in providing a trust foundation for cross-platform and cross-domain AI Agent collaboration. Without a unified identity standard, each platform must establish its own reputation system, and reputation cannot transfer when Agents move across platforms. By anchoring identity and reputation on a public blockchain, ERC-8004 enables reputation portability and interoperability.
This interoperability opens the door to complex AI collaboration scenarios. For example, a DeFi aggregator Agent could invoke specialized Agents from Uniswap, Aave, and Curve, each with its own on-chain identity and reputation. The aggregator can select the most reliable execution path based on reputation scores and trace responsibility if issues arise.
Cross-chain scenarios also become feasible. Although ERC-8004 is based on Ethereum, through cross-chain bridges and identity mapping mechanisms, AI Agents on other blockchains can register identities on Ethereum or map Ethereum identities onto other chains. This lays the foundation for building multi-chain AI Agent ecosystems.
Currently, ERC-8004 is in the final testnet validation stage, with deployment to the Ethereum mainnet expected in the coming weeks. Multiple AI Agent development teams have announced support for the ERC-8004 standard, including some well-known DeFi protocols and NFT platforms. If widely adopted, ERC-8004 could become a key infrastructure for the on-chain AI economy.
However, challenges remain. The effectiveness of the reputation system depends on sufficient data accumulation and community participation. In the early stages, most AI Agents lack historical records, making cold-start problems significant. Additionally, designing reputation scoring algorithms requires balancing against manipulation and encouraging innovation, to prevent monopolies or exclusion of newcomers.
The launch of ERC-8004 marks the transition of the on-chain AI economy from infrastructure development to ecosystem growth. In the foreseeable future, we may see a vast network composed of millions of AI Agents, each with specialized capabilities, collaborating through standardized identity and reputation systems to provide complex on-chain services.
This ecosystem operates similarly to the service economy in the real world. Users do not need to understand every technical detail of each Agent; they only need to check reputation scores and user reviews, much like reviewing seller ratings when shopping online. Collaboration among Agents will form a division of labor and specialization—each Agent focusing on doing one thing well, then combining to accomplish complex tasks.
From an investment perspective, the release of ERC-8004 could spawn new business models and investment opportunities. Developing high-reputation AI Agents might become a profitable venture, akin to SaaS services today. High-reputation Agents could charge higher fees, and reputation management itself might evolve into a specialized field. Additionally, derivative services around Agent identity and reputation—such as reputation rating agencies and dispute arbitration platforms—may emerge.
However, the success of this technical standard ultimately depends on ecosystem adoption. ERC-8004 needs broad recognition from developers, platforms, and users to become the standard for AI Agent identities on-chain. This will require time, continuous technical iteration, and community building. But if successful, it could become a crucial component in driving the deep integration of Web3 and AI.
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