It sounds like you've encountered some interesting challenges and benefits while experimenting with "specsmaxxing" for AI agents. Here are a few key points to consider:
Benefits of Specsmaxxing
- Consistency in Naming and Architecture: By providing clear, structured specifications, you can ensure that the agent adheres to consistent naming conventions and architectural patterns.
- Reduced Review Time: The agent's adherence to your specified guidelines reduces the time you need to spend reviewing and correcting its work.
- Clarity of Intent: A well-defined spec helps prevent misunderstandings and ensures that the agent understands exactly what is expected.
Challenges and Pitfalls
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Ambiguity in Specifications:
- Example Needed: "Typed errors, never throw strings" can be interpreted differently by different agents or even at different times. Providing concrete examples or limits (e.g., "up to 3 distinct error types") helps mitigate this.
-
Negative Constraints Are Harder to Audit:
- Verification Difficulty: It's easier for an agent to avoid introducing something than to ensure it doesn't exist in existing code. You need clear, verifiable rules and possibly automated checks.
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**Stale
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