Harness engineering: Preparing TypeScript codebases for coding agents

The approach you've outlined for managing AI-generated "slop" in your codebase is quite comprehensive and well thought out. Here are some key points and additional suggestions to further enhance this system:

Key Points

1. Self-Documenting Development:

   • You're instructing the coding agent (Claude) to update Notion documentation as part of its development process, which is a smart way to ensure that documentation stays up-to-date with code changes.

2. AI Coding Rules Enforcement:

   • Enforcing rules like "minimal changes" and avoiding unnecessary abstractions helps in maintaining clean and concise code.
   • The rule against speculative error handling (relying on internal callers and framework guarantees) is particularly important to avoid bloated and redundant error-checking logic.

3. Quality Gates:

   • Ensuring that tests, linters, and type checkers pass before committing is a standard practice that helps maintain code quality.

4. Garbage Collection for Slop:

   • Periodic audits of the codebase to remove dead code, outdated documentation, and other forms of slop are crucial.

Additional Suggestions

1. Automated Code Quality Checks:
   • In addition to

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