Building a skill optimization loop

The post explores the concept of creating automated feedback loops to enhance the performance of Skills, using a specific example of replatforming websites from WYSIWYG platforms to self-hosted code on Vercel. It introduces an "observer" Skill that evaluates the effectiveness of the replatforming process by running tests, identifying behavioral and visual differences, and suggesting improvements based on structured data and state-of-the-art models. The observer Skill is designed to optimize costs while maintaining quality by analyzing patterns and proposing updates to the underlying "inner" Skill, thus continuously improving it through iterative loops. The process is facilitated by tools like Warp and Oz, which support orchestration of multiple agents, and the entire approach is open-sourced for broader application. Although the method is not flawless and has limitations like the risk of finding local maxima, it offers a practical way to ensure Skills operate efficiently by continually refining them. The post also mentions a new podcast called Talking Slop, along with related articles discussing broader applications of Skills and loops in software development.

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