Berkeley researchers outline how data systems must change as agents take over knowledge work
Original titleIntelligence is Free, Now What? Data Systems for, of, and by Agents
Berkeley AI Research authors argue that near-free inference will make agents the dominant workload for data systems, requiring redesign for agentic speculation, agent-run state and coordination, and agent-synthesized systems.
The post cites inference prices falling 9x to 900x per year with a median near 50x, and reports that about 80-90% of sub-queries in a text-to-SQL benchmark were duplicates. It frames the three directions as data systems for, of, and by agents.
The piece maps three concrete data-system challenges posed by near-free inference, useful for anyone designing infrastructure for agent workloads and memory.
Source: Berkeley AI Research · bair.berkeley.edu