The Rubber Duck Prompt: Debug AI Output by Making It Explain Every Decision

You know the trick — explain your code to a rubber duck and the bug reveals itself. Turns out it works on AI too, except you make the AI be the duck. The Problem Your AI assistant returns code that looks right. It runs. But something about it feels off — maybe it picked a weird data structure, ignored an edge case, or used a pattern you didn\'t expect. You can\'t tell if it\'s wrong or just different. Most people either accept it or start over. There\'s a better move. The Rubber Duck Prompt After the AI generates code, hit it with this: Before I review this, walk me through your decisions: 1. Why did you choose this data structure? 2. What alternatives did you consider and reject? 3. What edge cases did you think about? 4. What assumptions are you making about the input? 5. What would break first if requirements change? That\'s it. Five questions. The AI is forced to justify every choice. Why This Works When an LLM generates code, it\'s pattern-matching from training data. It doesn\'t