The original title is "Intelligence is Free, Now What? Data Systems for, of, and by Agents"

Short summary

As AI inference costs plummet (~50x annually), the era of near-free intelligence enables new workload patterns: agentic speculation (agents performing thousands of exploratory queries), agent swarms requiring coordination and state management, and agents generating custom data systems. Rethinking data systems for these agentic users—not humans—becomes critical infrastructure. Traditional databases assume human queries; agents perform high-volume exploratory work that can be optimized through result reuse, approximate answers, and higher-level primitives.

• •AI inference costs dropped 50x annually; intelligence is now near-free
• •Data systems must optimize for agent workloads: agentic speculation, swarms, and synthesis
• •New primitives needed: result caching, approximate answers, agent coordination

Generated with AI, which can make mistakes.