05 State Persistence

This video addresses the challenge of managing long-running, multi-session tasks with AI coding agents. It explores why expanding context windows alone cannot solve cross-session memory loss, detailing how finite context triggers "context anxiety"—a phenomenon where an agent rushes, cuts corners, or skips verification as memory runs out. Viewers will learn how to prevent knowledge drift and costly session-start discovery by implementing a State Persistence Toolkit consisting of progress trackers, decision logs (recording the "why" behind architecture), and structured "clock-in / clock-out" routines. Created using Gemini Notebook using materials from https://walkinglabs.github.io/learn-h....