The article discusses real-world examples of AI-generated tech debt in a TypeScript codebase co-maintained by an AI agent and human developer. It highlights issues like knowledge loss between sessions, lessons not becoming permanent code changes, ineffective metrics, and insufficient verification methods. The key takeaway is the importance of making decision trails and rationale easily accessible through files to prevent hidden tech debt.
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