I had a decent story ready but I front-loaded too much on the mistake itself and ran out of time explaining what actually changed in my thinking afterward.
Choose a real, consequential decision where you missed something important, then show how you diagnosed the root cause and changed your decision-making process. Focus on the learning loop and the concrete, better outcome in a later decision, not on the mistake itself.
Pro tip: Amazon values Earn Trust and Learn and Be Curious, so pick a mistake that was significant but not a values violation, and explicitly name the mechanism you added to your process (e.g., a pre-mortem or a lightweight experiment) that prevented a repeat.
Briefly describe the project, your role, and the specific decision you made, including the constraints and information you had at the time. Keep it concise so you can spend most of the answer on the learning and the later decision.
State clearly what you decided, why it was wrong, and the measurable impact (e.g., delayed launch, wasted engineering cycles, missed customer metric). Avoid blaming others or external factors.
Explain what you missed—such as an unvalidated assumption, a biased data source, or skipping a stakeholder—and what you learned about your decision-making process. Show self-awareness and curiosity.
Introduce a subsequent, similar decision where you applied the lesson. Detail the specific steps you took differently (e.g., ran a pre-mortem, built a prototype, consulted a different team) and the better outcome.
Tie the learning to Amazon Leadership Principles like Customer Obsession or Bias for Action, and note how you have institutionalized the improvement (e.g., a checklist, a review ritual) to benefit your team.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.