While AI can generate code, the stakes on blockchain are too high for bugs, as they lead to direct financial loss. The solution is formal verification, using mathematical proofs to guarantee smart contract correctness. This provides a safety net, enabling users and AI to confidently build and interact with financial applications.

As consumers use AI to analyze contracts and diagnose problems, sellers will deploy their own AI counter-tools. This will escalate negotiations from a battle between people to a battle between bots, potentially requiring third-party AI arbitrators to resolve disputes.

As anonymous AI agents proliferate globally, traditional KYC and national legal systems become inadequate. It will be impossible to know who or what is behind an agent, creating a need for a new global, trustless infrastructure for agent identity verification and cross-border dispute resolution to prevent abuse by bad actors.

Unlike simple "Ctrl+F" searches, modern language models analyze and attribute semantic meaning to legal phrases. This allows platforms to track a single legal concept (like a "J.Crew blocker") even when it's phrased a thousand different ways across complex documents, enabling true market-wide quantification for the first time.

For complex cases like "friendly fraud," traditional ground truth labels are often missing. Stripe uses an LLM to act as a judge, evaluating the quality of AI-generated labels for suspicious payments. This creates a proxy for ground truth, enabling faster model iteration.

As AI capabilities accelerate toward an "oracle that trends to a god," its actions will have serious consequences. A blockchain-based trust layer can provide verifiable, unchangeable records of AI interactions, establishing guardrails and a clear line of fault when things go wrong.

Block's CTO believes the key to building complex applications with AI isn't a single, powerful model. Instead, he predicts a future of "swarm intelligence"—where hundreds of smaller, cheaper, open-source agents work collaboratively, with their collective capability surpassing any individual large model.

For AI agents to be truly autonomous and valuable, they must participate in the economy. Traditional finance is built for humans. Crypto provides the missing infrastructure: internet-native money, a way for AI to have a verifiable identity, and a trustless system for proving provenance, making it the essential economic network for AI.

The primary danger of mass AI agent adoption isn't just individual mistakes, but the systemic stress on our legal infrastructure. Billions of agents transacting and disputing at light speed will create a volume of legal conflicts that the human-based justice system cannot possibly handle, leading to a breakdown in commercial trust and enforcement.