Your Agent Is Only as Good as Its Data

​AI agents keep getting smarter. Their output still depends on the data they can reach.

​We learned this the hard way building an AI support agent for our own product business. The context it needs lives in five places: Intercom, years of email, billing, our product database, and third-party recorder logs. Each system holds a piece of the answer. None holds the whole thing.

​In this one-hour session, we'll share what we're seeing from our own build, from clients, and from a deep dive with a team running three support agents across 400 to 500 tickets a day for a consumer app with over a million users.

​We'll cover:

• ​How to inventory where each agent's context actually lives

• ​Distilling history into skills vs. stitching live systems together

• ​Why vague error messages break agents, and how to fix them

• ​Starting scrappy (Google Drive) vs. building for scale (Snowflake)

• ​Capturing context that lives nowhere

​For operators, Chiefs of Staff, and technical leaders standing up agents inside their companies.

​Presenters

• ​Lawrence Coburn, Founding Partner, Legible

• ​Taylor McLoughlin, Founding Partner, Legible

• ​Brandon Catcho, Founding Partner, Legible