What Your AI Doesn't Know: The latest trends in agent searches

An agent only searches when it doesn’t know something. In other words, every search is a confession, and Exa has been collecting them from thousands of agents for two years.

Read together, those searches form a map of how AI agents like to work, and where their knowledge ends. There’s clear evidence of growing expertise. Coding agents used to search for examples and tutorials, now they go straight to the source, searching for code repos, issues and API references. Searches for mature frameworks like React, Next.js, and the rest of the “vibe code stack” are fading, not because they’re falling out of use, but because models already know them cold. Instead agents are searching for their own tools: MCPs, skills, agent instruction files and the latest models.

But even as their knowledge and capability grows, agents still need to search. Models still take months to train, but the coding frontier now turns over every quarter, and AI is speeding that up. This knowledge cutoff won’t be fixed by the next big model release.

In this keynote, Jeff Pinner, CTO of Exa, shares what we’ve learned from agents telling us what they don’t know, what it means for anyone who maintains a library, ships an agent or relies on one, and why search is an Agent’s best gateway to the present.