Learning from Failure

Failure is data. When you treat it that way, you can improve faster and take smarter risks next time.

Run a short post-mortem. What was the original aim? What actually happened? List 3–5 contributing factors—both choices and conditions. Separate facts from guesses.

Extract one lesson per factor. Turn each factor into a practical rule: “Validate with three users before building,” or “Time-box research to 60 minutes.”

Design safer experiments. Shrink scope, shorten timelines, or cap budgets so the next attempt has lower downside and faster feedback.

Update your checklist. Capture new rules where you’ll see them—prep docs, templates, or a pre-launch checklist—to prevent repeat mistakes.

Normalize the loop. Review outcomes weekly: what worked, what didn’t, and what you’ll try differently. Progress compounds when reflection is routine.