2026 is becoming a key turning point where Crypto and AI deeply intersect.

In the past two years, we have witnessed the transformation of AI from an "auxiliary tool" to an "autonomous economic participant". AI Agents are no longer just chatbots that answer questions; they have started to autonomously initiate transactions, call APIs, manage asset portfolios, and even hire other Agents to complete tasks.

However, the premise of all this is that these Agents need identity, payment channels, credit records, and verifiable execution environments.

And these needs happen to be the problems that blockchain is best at solving.

Continuing with the usual talk, the Ethereum Foundation set up a decentralized AI (dAI) team in September 2025. Vitalik Buterin published a systematic AI strategic framework in early 2026, and a series of protocol standards concerning Agent identity, payments, and execution have already been launched on the mainnet. Meanwhile, new public chain ecosystems like Solana are also building AI infrastructure on their respective paths.

Therefore, this article also attempts to use the Ethereum ecosystem as the main axis, supplemented by significant progress from other public chains, to outline the complete picture of current crypto AI protocols.

1. Vitalik's AI Blueprint: Ethereum as the "Trust Layer" of the AI World

In February 2026, Vitalik Buterin published a systematic post on X, specifically revising the "Crypto × AI" intersection framework he proposed two years ago.

In the article, he reexamined the ideas presented two years ago, believing that the acceleration toward general artificial intelligence often resembles the unrestricted speed and scale that Ethereum itself was challenged with when it was created. He explicitly opposed simplifying AI development to an "AGI race," advocating that Ethereum should become a guiding force in the AI world.

In other words, what he truly cares about is not how to let AI spiral out of control faster, but how to ensure that the expansion of AI is built on verifiable, auditable, and constrained infrastructures.

Overall, Vitalik's framework includes four core pillars.

First is trustworthy AI interaction tools. He advocates using local large language models (local LLMs), zero-knowledge proof payment mechanisms, and other tools to allow users to use AI services without exposing their identities and original data.

This attitude is not just an abstract expression. In April 2026, Vitalik publicly shared his local LLM utilization plan, after testing several hardware sets, he chose to locally run a 35 billion parameter open-source model Qwen3.5 on a computer equipped with an NVIDIA 5090 GPU, completing all calculations locally, aiming to enhance inference speed to a level that can be used daily while minimizing reliance on cloud models.

Of course, the symbolic significance of this act outweighs its practical significance, but it at least shows that in his view, what is truly worth pursuing in AI is not just stronger models, but more controllable ones.

Secondly, there is the economic coordination layer for AI. This includes how Ethereum can support inter-agent payments, security deposits, dispute resolutions, and reputation accumulation through smart contracts, forming programmable economic relationships between machines; third is AI as the interface for Web3, for example, local AI assistants can help users draft transactions, audit smart contracts, and interpret formal verification proofs, acting as a bridge for ordinary people to enter the complex on-chain world.

Lastly, there is the AI-enhanced governance system, which finds a balance between automation and human judgment, such as using AI to upgrade prediction markets, quadratic voting, and public fund distribution.

In summary, the core idea of this framework can be condensed into one sentence: Ethereum is not looking to accelerate AI but to ensure that AI operates in a verifiable, auditable, and decentralized environment.

So how is this to be realized?

2. From Identity Protocols, to Payment Protocols, to Execution Protocols, to Verifiable AI

If Vitalik's framework is the macro blueprint, then the recent wave of protocol evolution in the Ethereum ecosystem has started to press this methodology into specific technical stacks.

The first infrastructure node worth paying attention to is ERC-8004.

As the identity, reputation, and verification standard designed for AI Agents by Ethereum, it is led by the Ethereum Foundation's dAI team, jointly developed with Google, Coinbase, and MetaMask, and encompasses the three key entry points of AI, transactions, and wallets (see the extended reading: A New Ticket to the AI Agent Era: Promoting ERC-8004, What is Ethereum Betting On?).

As its official name suggests, Trustless Agents, its core logic is not a complicated algorithm, but aims to give AI a verifiable identity, reputation, and capability proof on-chain. To put it simply, its design is very restrained, doing just three things:

• Identity registry: Based on the ERC-721 standard, each AI Agent will be "NFT-ized," meaning that AI Agents can be viewed, referenced, and integrated into other protocols just like wallet addresses;
• Reputation registry: Can be understood as the "Yelp" of the AI realm, allowing users or other Agents who have actually interacted with the Agent to submit feedback, and these evaluations can be linked to on-chain payments or custody actions, ensuring that reputation is not an arbitrary narrative but a historical record based on real economic behavior;
• Verification registry: For high-value or high-risk tasks, historical reputation alone is not enough; thus, ERC-8004 reserves third-party verification interfaces, allowing endorsements of the Agent's capabilities or execution processes through trusted execution environments, zero-knowledge proofs, and other means;

If identity answers the question "Who is the Agent?", the payment infrastructure represented by the x402 protocol answers "How do Agents transact?".

It is well known that x402 is an open HTTP payment protocol initiated by Coinbase and Cloudflare. Its basic principle is very clever as it has revived the long-dormant 402 status code (Payment Required) in the HTTP protocol. When an Agent attempts to access a paid service, the server returns a 402 status code and payment requirements, and the Agent can gain access after completing the payment with stablecoins.

The entire process is embedded in the HTTP request, requiring no account registration, no credit card, and no human intervention. In other words, this is a payment system designed for machines, not humans.

It is worth noting that earlier this month, the Linux Foundation officially took over the x402 Foundation and received the x402 protocol contributed by Coinbase. The official statement is very clear: x402 aims to directly embed payments into HTTP interactions, allowing AI agents, APIs, and applications to exchange value just like exchanging data.

I believe the importance of this news has been greatly overlooked. On one hand, it concerns the potential and significant influence of x402 in AI and Internet payments. On the other hand, the lineup is indeed luxurious. x402 has always been promoted by these giants, but this time it is evident that 1+1 is greater than 2.

Additionally, the V2 version of x402 is also working to expand payment methods, including not only support for on-chain stablecoins but also compatibility with traditional ACH (Automated Clearing House) and card networks to bridge the gap between AI Agents and real financial systems.

Lastly, beyond identity and payment, the recent third puzzle piece Ethereum has added is the execution layer.

In April 2026, Biconomy and the Ethereum Foundation's Improve UX direction jointly promoted ERC-8211, aiming to solve the most realistic bottleneck for AI Agents in the DeFi world, such as on-chain complex operations often not being a single call but multiple, dynamic, and easily invalidated execution chains.

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 independent transactions: withdrawing funds from a lending protocol, exchanging tokens, and then depositing into another protocol.

Each step requires individual signatures and confirmations, which is cumbersome for human users and even more so for AI Agents that require high-frequency autonomous operations. The solution of ERC-8211 allows multiple blockchain operations to be executed in a single transaction, dynamically parsing actual values during execution, and must meet predefined conditions before moving to the next step.

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

Putting these three together, the recent line in Ethereum has become clear: ERC-8004 answers "Who are you, why do others trust you", x402 answers "How do you pay for services", ERC-8211 answers "How do you efficiently complete complex operations".

In other words, what the AI Agent economy truly lacks is not just a smarter large model, but an open, composable, and extensible protocol stack; and this is precisely what Ethereum excels at doing.

3. Beyond Ethereum: Solana, DePIN, and Decentralized Computing

Of course, even if Ethereum occupies a leading position in standard setting and trust infrastructure, the AI crypto ecosystem is far more than just one chain.

A more accurate statement is that Ethereum is competing for the standard layer and trust layer, while other ecosystems are demonstrating different advantages in the execution layer and computing power layer.

Solana is the most typical example. Its increasingly significant presence in the Agent payment discussion comes from the fact that the needs of AI Agents for the chain are not ideologically correct, but rather "low latency, low cost, and sufficiently stable." In Solana's official introduction to x402, milliseconds-level finality and extremely low transaction costs are directly highlighted as important selling points for machine payments, which also explains why Solana is better suited for high-frequency, low-value, and immediate feedback Agent interaction scenarios.

At the same time, the Agent toolchain around Solana is also rapidly maturing. The Solana Agent Kit's official GitHub allows any model-based Agent to autonomously execute over 60 types of Solana actions, covering various scenarios such as trading, token issuance, lending, airdrops, Blink, and cross-chain activities, being reused by numerous on-chain projects and developers.

Therefore, looking at today’s landscape, the division of labor in crypto AI is becoming clearer. Ethereum seems to focus on protocol standards, identity reputation, and trusted execution as the underlying abstraction, while Solana holds a practical advantage in high-frequency payments and low-friction interactions. The value of decentralized computing networks will also be revalued as more Agents truly enter production environments.

Overall, looking back from the point of April 2026, the landscape of crypto AI protocols has already begun to take shape:

• Identity layer: ERC-8004, as the Agent identity standard led by Ethereum, has expanded to multi-chains including Base;
• Payment layer: x402 has grown from an experimental project of Coinbase into a global standard under the governance of the Linux Foundation;
• Execution layer: Standards like ERC-8211 have simplified complex on-chain operations for Agents;
• Verification layer: Technologies like zkML, TEE, and cryptographic proofs have begun to provide verifiability for high-value Agent interactions;
• Competitive landscape: Ethereum focuses on standard and trust layers, Solana on high-frequency execution layers, and Bittensor may also serve as a supplement in dimensions like computing power, forming a complementary rather than zero-sum pattern;

Looking ahead to the second half of the year, Ethereum's new upgrades will likely promote L1 scaling, native account abstraction, and post-quantum security, among which the popularization of account abstraction will undoubtedly significantly lower the usage threshold for Agent wallets; the deep integration of x402 and ERC-8004 may also give birth to a closed-loop Agent economy, covering Agent registration identity, service discovery, initiating payments, and accumulating reputation, all completed on-chain.

Final Thoughts

Ethereum and blockchain are not looking to accelerate the arrival of AI but to ensure that the world does not spiral out of control when AI arrives.

After all, in the Web2 world, the identity of AI is defined by the API keys of big companies, payments are carried by credit card systems, and trust is backed by centralized platforms. This system operates with difficulty in scenarios with human users but increasingly struggles with the new paradigm where millions of AI Agents require 24/7 autonomous cooperation.

And the standard setters centered around Ethereum, the efficient execution layer represented by Solana, and the decentralized computing supported by DePIN may construct an entirely new infrastructure for the AI Agent economy.

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