Feedback Flywheel

This article discusses the 'Feedback Flywheel' concept for AI-assisted development teams. It highlights how most teams plateau in AI tool usage because individual learnings from AI interactions (prompts, failures, successes) are not captured or shared. The author proposes a structured practice to harvest signals from AI sessions and feed them back into team artifacts like wikis, runbooks, and checklists. This turns individual experience into collective improvement, enabling continuous compounding of effective practices. The article covers four types of signal, measurement, and calibration, aiming to prevent recurring failures and enhance team productivity with AI coding assistants.