Decisions are experiments
Every decision worth agonising over is one you cannot resolve with more research. If the data settled it, it wouldn’t feel like a decision — it would feel like arithmetic.
So the question is never “what is true here”. It’s “what do I believe, how strongly, and what would change my mind”.
Priors, out loud
Write the number down. Not because the number is right, but because writing it converts a mood into something falsifiable. “This will work” cannot be wrong. “I think there’s a 60% chance ten of these customers renew” can be, and in three months it will be.
The second half is the condition. Before committing, say what you would have to see to reverse. If you cannot name it, you have not made a decision — you have made an identity, and identities do not update.
Reversible beats correct
Most of the value here isn’t in better prediction. Prediction under real uncertainty is bad, and stays bad. The value is in choosing shapes you can back out of.
A schema change you can roll back, a vendor you can leave in 30 days, a feature behind a flag — these cost more upfront and let you be wrong cheaply. A rewrite, a two-year contract, a hire made to fix a strategy problem: those are wrong expensively.
A public API is the sharpest example of the irreversible class. You can add to one forever and remove from one almost never, because removal is a promise broken on someone else’s schedule. Ship a field with the wrong name and you keep it for a decade. The same afternoon’s work behind a feature flag costs an hour more and can be withdrawn at any point. The two look identical while you’re making them and are nothing alike afterwards.
Where it breaks
Optionality has a price, and the people who love this framing rarely pay it out loud.
Everything reversible is also everything uncommitted. You cannot build a hard technical asset, a brand, or a team on a foundation you have explicitly reserved the right to abandon in 30 days. Some things only pay out if you refuse to reconsider them — most compounding is exactly that. A founder who treats every decision as an experiment ends up with a portfolio of half-tested bets and nothing that anyone else could not also have.
There’s a second failure. Probabilistic language is unusually good at laundering indecision. “I’m 60/40 on it” can mean you’ve reasoned carefully, or that you would rather not be on the hook. A team can tell the difference; the calibration habit does not protect you from it.
The line I use: reversibility is the default, and a small number of decisions get deliberately promoted out of it — named as irreversible, argued once, then closed. The mistake is not having irreversible bets. It’s having them by accident.
In practice
State the hypothesis before the work, not after. Set the review date at the same time as the decision, because a decision with no review date is never wrong. Keep a short list of the calls you have deliberately closed, so you stop relitigating them in the shower.
Takeaway: treat decisions as experiments; optimise for optionality.