5 Rules for Building AI Agents That Work in Production | Nan Yu & Jacob Shumway

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About this video

Nan and Jacob built Linear Agent, which has transformed how the $1.25B company gets work done.

In this episode, they took me from the initial memo to launch, showing how to give an agent tools to find the context it needs, use evals to improve reliability, and more.

This episode is a must-watch if you want a concrete, behind-the-scenes example of how to build a production agent end to end.

We talked about: (00:00) What’s holding AI agents back as models improve? (00:51) Three things every good agent needs (03:00) Demo: The internal memo that started Linear Agent (09:50) The biggest mistake to avoid when building agents (11:29) Demo: From Slack to code in 6 minutes with the agent (17:01) When prototyping, “use the biggest model until it works” (24:02) Give agents tools to find context, not more context (34:07) The first thing to do before building an agent

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