Vitalik Buterin is challenging the dominant narrative shaping today's artificial intelligence industry. As major AI labs frame a competitive race toward artificial general intelligence (AGI), the Ethereum co-founder argues that the premise itself is flawed.
In a series of recent posts and comments, Buterin outlined a different approach that prioritizes decentralization, privacy, and verification over scale and speed, positioning Ethereum as a key part of enabling infrastructure rather than a vehicle for accelerating AGI.
Buterin likens the phrase “AGI operations” to simply describing Ethereum as “financial sector operations” or “computing operations.” In his view, such framing obscures questions of direction, value, and risk.
ETH's price trends to the downside on the daily chart. Source: ETHUSD on Tradingview
Ethereum as an infrastructure for private and verifiable AI
A central theme of Buterin’s vision is privacy-preserving interactions with AI systems. He notes that there are growing concerns about data leaks and identity exposure in large-scale language models, especially as AI tools become increasingly embedded in everyday decision-making.
To solve this problem, Buterin proposes a local LLM tool that can run AI models on the user's device, along with a zero-knowledge payment system that enables anonymous API calls. These tools allow you to use remote AI services without tying your requests to a persistent ID.
He also emphasizes the importance of client-side verification, cryptographic attestation, and Trusted Execution Environment (TEE) attestation to ensure that AI output can be verified rather than blindly trusted.
This approach reflects the broader “don’t trust, verify” ethos, where AI systems assist users in auditing smart contracts, interpreting formal proofs, and verifying on-chain activities.
Economic layer for AI-to-AI coordination
Beyond privacy, Buterin sees Ethereum serving as an economic coordination layer for autonomous AI agents. In this model, AI systems can pay each other for services, deposit deposits, and resolve disputes using smart contracts rather than a centralized platform.
Use cases include bot-bot recruitment, API payments, and reputation systems supported by proposed ERC standards such as ERC-8004. Proponents argue that these mechanisms can enable decentralized agent markets where coordination is achieved through programmable incentives instead of institutional control.
Buterin emphasized that this economic layer will likely operate on a roll-up and application-specific layer 2 network rather than Ethereum's base layer.
AI-enabled governance and market design
The final pillar of Buterin's framework focuses on governance and market mechanisms that have historically suffered from the limitations of human attention.
Prediction markets, secondary voting, and decentralized governance systems often falter at scale. Buterin believes that LLMs can help address complexity, aggregate information, and support decision-making without eliminating human oversight.
Rather than racing toward AGI, Buterin's vision frames Ethereum as a tool that will shape how AI is integrated with society. The focus is on coordination, safeguards and practical infrastructure, an alternative path that challenges the dominant acceleration-first mentality.
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