Frame a choice like a conversation: if this feature ships, what percent of trials convert, at what price, and how quickly? Estimate a realistic downside, a plausible middle, and a stretch result. Multiply by probabilities you are willing to say out loud. Now compare against build time and opportunity cost. If you can explain the math plainly to a customer or friend, you probably understand it well enough to trust it.
Adopt a weekly ritual: make five binary forecasts with stated probabilities—will churn drop this week, will three demos book, will CAC stay under target? After outcomes arrive, score them using Brier scores to quantify calibration. Pair this with a confidence ladder—30%, 50%, 70%, 85%, 95%—and write why you chose each rung. Over weeks, patterns emerge: perhaps you overrate marketing timelines or underrate user friction. Adjust rungs accordingly and watch stability improve.
A good process can yield a bad outcome, and a sloppy process can get lucky. Preserve confidence by grading decisions at the moment they are made, documenting assumptions, data sources, and alternatives considered. Later, when reality lands, separate luck from craft. This practice inoculates you against shame spirals, protects curiosity, and builds institutional memory—even if the institution is just you, a notebook, and an honest scoreboard.





