Metacognitive Debugging

I ran a focused explainability week to analyze my own reasoning. Each day, I documented a recent decision, described the evidence that supported it, and asked an AI to restate my logic, flag assumptions, and surface likely biases. Patterns emerged quickly: places where I over-weighted recency, collapsed ambiguity into false precision, or trusted familiarity over fit. That time‑bounded practice improved the way I think, not just what I think.

Key moves I kept using afterward:

• Ask for a restatement of my reasoning in plain language.
• Request a list of assumptions and where evidence is thin.
• Name one bias likely at play and a counter-move I can try next.