Meta research shows coding agents perform better using compact summaries of past attempts rather than raw execution logs, signaling a shift toward memory-efficient AI design.

A practical model for AI coding agents that need to remember projects, tasks, executions, and runtime sessions separately.

Meta research shows coding agents perform better using compact summaries of past attempts rather than raw execution logs, signaling a shift toward memory-efficient AI design.

TL;DR: AI coding agent memory should live in the repository, not the chat window. Bigger context...