Every post works through a real scenario and shows how to predict it — what to assume, how the outcomes branch, and what the result actually turns on. Then it hands you a CTA to predict your own version.
Your financial future isn't one number — it's a spread of outcomes. Here's how to use scenario analysis to predict where you actually land, and which variable controls the spread.
A career switch is a multi-year bet with a delayed payoff. Here's how to predict whether yours pays off — the realistic timelines, the branches, and the factor that decides it.
Moving cities or countries is a prediction problem disguised as a logistics problem. Here's how to predict whether a relocation actually works out — and the variable it really hinges on.
A job change is a high-stakes scenario with thin data. Here's how to turn it into a prediction you can act on — what to assume, how the outcomes branch, and the one factor it usually turns on.
Cofounder conflict rarely ends in a clean break — it ends in slow drift. Here's how to predict how the conflict actually plays out, and the forcing function that decides which way it goes.
A hire is a high-variance bet you can't easily reverse. Here's how to predict how a hiring decision plays out — and why the manager, not the candidate, is usually the deciding factor.
Most launches are graded months too late to do anything about it. Here's how to predict a launch's first 90 days up front — the branches, the real success driver, and the early tripwire.
A price change is one of the most predictable business moves — if you frame it right. Here's how to predict churn-adjusted impact, and why usage, not price, is the variable that decides it.
You rarely have complete data when you need a prediction most. Here's how to predict an event's outcome with partial information — and why naming what you don't know makes the prediction better.
AI can't predict crypto prices, and anyone selling that is lying. But it can predict scenarios — conditional, structural outcomes. Here's the honest line between the two.
Markets overreact to announcements, then revert. Here's how to predict the real reaction to a product or competitor announcement — separating the noise spike from the structural shift.
Policy changes have second-order effects that surprise everyone. Here's how AI predicts the likely outcomes of a policy shift — the directional effects it gets right, and the limits it should admit.
No jargon. A plain-language walk-through of how AI turns a scenario you type into a prediction — the five steps from your sentence to a set of weighted, explained outcomes.
Not all predictions deserve equal trust. Here's what actually makes an AI prediction reliable — the density of analogues, the quality of your inputs, and how to read a prediction's own confidence.
The quality of an AI prediction is mostly set by how you ask. Here's how to write a scenario question that gets a sharp, useful prediction instead of a vague one — with before-and-after examples.