Intelligence is Free, Now What? Data Systems for, of, and by Agents

智能免费，然后呢？--Data Systems for， of， and by Agents

UC Berkeley's BAIR Lab argues that as inference costs approach zero, data systems face three shifts. First, systems for agents: a single user request can spawn thousands of SQL queries, but 80–90% of sub-queries are duplicates, so reusing results or returning approximate answers can speed things up. Second, systems of agents: thousands of agents need a new substrate to manage state, coordinate, and handle failures. Third, systems by agents: agents can now synthesize entire data systems, but verifying correctness remains an open problem. The post is a research roadmap and does not provide a deployment timeline.

Why it matters: Berkeley BAIR dropped a roadmap with a real thesis and hard numbers, not a vague trend piece. The core insight — when inference is nearly free, database systems get rebuilt for, of, and by agents — is sharp, and the 80-90% duplicate subquery stat gives engineers a concrete tar...