Build a self-improvement loop for your coding agents

​A poorly written agent Skill can burn through hundreds of unnecessary tool calls, and still produce code that falls short of your team’s standards.

​Agents need a feedback loop for continuous improvement. In this hands-on workshop, we’ll show you how to build one: a system that evaluates agent runs, identifies weaknesses, and turns those findings into concrete Skill improvements.

​An evaluator scans your team’s conversation logs, delegates each run to scorer agents, and grades the results against criteria you define, such as code quality, efficiency, and task compliance. A self-improvement agent then uses those scores to propose Skill updates for your team to review and merge.

​We’ll share real self-improvement results from our own repositories, including the Skill changes we shipped and how they improved the code produced by our agents.

​Plus: how to run the full evaluation and improvement loop with Warp Factories, so agent quality improves continuously as your team works.

​Who it’s for: Engineers and engineering leaders deploying coding agents who want a repeatable, measurable process for improving code quality over time.