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Build a Self-Correcting Rulebook to Fix Recurring AI Mistakes
How toAgents & ToolsThe Neuron · 2h ago

Build a Self-Correcting Rulebook to Fix Recurring AI Mistakes

You can prevent repetitive AI errors by instructing the model to update a plain-text rulebook whenever it delivers a wrong result. This technique refines target instructions without disrupting previously working examples.

Try it yourself

  1. 1Maintain a numbered list of operational guidelines for your recurring AI prompt task.
  2. 2Identify the specific rule that caused a failed or incorrect response.
  3. 3Ask the AI to propose a minimal edit to that single rule rather than rewriting the full list.
  4. 4Have the model evaluate the updated rule against earlier approved examples to prevent regressions.

Copy this prompt

Here is my current rulebook and a faulty output: [PASTE RULEBOOK AND FAULTY OUTPUT]. Do not rewrite the entire rulebook. Identify the specific rule that caused this error, suggest the minimal edit to fix it, and test the update against these approved examples to ensure no regressions: [PASTE APPROVED EXAMPLES].
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