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How to ThinkIn the Age of AI
Principlev1PR-1367

Catalog your actual output history to identify recurring…

Catalog your actual output history to identify recurring error patterns, then build checklist items and quality standards around the errors you demonstrably make rather than hypothetical failures.

Why This Is a Principle

This derives from the axiom that raw experience without reflection doesn't produce learning (Raw experience, without reflection, does not produce…) and that calibration develops from domain-specific feedback (Domain-Specific Calibration Development). The principle prescribes using your error history as the data source for quality systems.