Building Search for AI Agents with Exa CEO Will Bryk

Search is shifting from a human-centric keyword model to an agent-centric paradigm, where AI systems require comprehensive, deep, and highly controllable data retrieval. Unlike traditional search engines optimized for consumer clicks, agent-focused platforms like Exa prioritize raw information density and semantic complexity to support autonomous workflows. This transition enables a more efficient "agentic economy," where smaller, specialized models leverage targeted retrieval to perform tasks accurately while reducing token consumption and compute costs. By treating search as a foundational infrastructure rather than a mere service, this approach addresses critical bottlenecks in knowledge work, such as go-to-market intelligence and technical coding assistance. Ultimately, perfecting information retrieval serves as a gateway to solving complex societal challenges, ranging from political polarization to social isolation, by ensuring that accurate, high-quality knowledge is accessible to both human and machine users.