3 Rules for De-Slopping AI-Generated TypeScript Code

Mike Cann candidly shares his experience of dealing with "AI slop," referring to the messy and tangled TypeScript code generated by AI tools, which initially led to a lack of understanding of the code's intricacies. This realization prompted him to embark on a de-slopping journey, where he learned the importance of breaking down large, unwieldy functions into smaller, more manageable ones, clearly segregating queries from commands, and naming functions accurately to reflect their purpose. His approach involved reorganizing a monolithic codebase into smaller files to gain a better understanding of the code structure, which ultimately improved readability and maintainability. Mike emphasizes the need for clear separation of responsibilities within code to ensure that both humans and AI can comprehend and modify the code efficiently. He also introduces a skill designed to automate this de-slopping process, encouraging others to test and provide feedback, highlighting the potential for AI to rectify problems it initially created.

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