Rich by Coin

Vitalik Buterin has urged moving away from a blind race toward artificial general intelligence and toward an Ethereum-led approach that prioritizes decentralization, privacy, verification, and human empowerment. In a detailed outline, he described a four-quadrant Ethereum–AI framework meant to coordinate AI activity while embedding safety rails across technology, economics, and governance. The framework balances infrastructure with impact and survival with thriving outcomes, and key elements include local large language model tooling, zero-knowledge payments for private AI API usage, cryptographic privacy enhancements, and client-side verification of AI services and attestations. He argues that progress should be guided by guardrails rather than sheer speed.

Buterin emphasizes that the current framing often treats AI progress as an undifferentiated race, and he advocates integrating AI and crypto with Ethereum-style decentralization and verification as guardrails. He argues for building railways that support agentic commerce, trade, and investing, with trust and coordination at the core of infrastructure and compliance. The proposal envisions Ethereum as an economic layer for AI activity, including API payments, bot-to-bot hiring, security deposits, on-chain dispute resolution, and AI reputation standards, with these features likely to run on rollups and app-specific L2s. AI-augmented governance would require identity, reputation, and stake-weighted accountability beyond better interfaces.

The four quadrants span trustless tooling for private AI interaction, an economic layer for AI activity, cypherpunk don’t-trust–verify tools, and upgraded governance through improved prediction markets and governance systems. Industry voices have weighed in, with Joni Pirovich of Crystal aOS saying Ethereum becoming the default settlement layer for AI-to-AI interactions is realistic, provided governance and infrastructure challenges are addressed. Midhun Krishna M of TknOps.io added that using Ethereum as an economic layer for AI-to-AI interaction is directionally correct, though it will largely operate on rollups and app-specific L2s, requiring programmable deposits, usage-based payments, and on-chain dispute resolution, with AI-augmented governance demanding identity, reputation, and stake-weighted accountability.