Linear thinking is the default. You describe a problem, AI gives you a solution. Fast, clean, and limited. Most people stop there, take the answer, and move on. The ones who get more out of AI don’t accept the first frame. They force the model to think in multiple directions at once before converging on anything.
TL;DR: One prompt structure forces AI to map three competing paths for any decision, each with a probability of success. You get a strategy session, not just an answer.
What the Pattern Actually Does
The structure is simple:
[Problem]. Propose 3 paths: 1. The Aggressive path. 2. The Conservative path. 3. The Contrarian path. List the probability of success for each.
Aggressive means go hard and fast. It’s the path that bets on your strengths, accepts short-term pain or risk, and tries to win decisively. Conservative means protect what you have. Slower, steadier, designed to preserve optionality and avoid catastrophic downside. Contrarian means ignore the obvious move entirely and try the weird angle. The path nobody in your space is taking, the one that sounds wrong until it doesn’t.
The probability estimates aren’t precise math. Nobody’s running Monte Carlo simulations here. They’re forcing functions. When AI assigns 65% to aggressive and 30% to contrarian, you stop treating the contrarian as a throwaway and start asking: what would have to be true for that number to flip? What conditions would make the weird path the right one? Is that world closer than I think?
That question is where the real thinking starts. The numbers create cognitive pressure. Without them, the contrarian path just looks like a curiosity. With a number attached, it becomes a hypothesis you can stress-test. You start poking at the assumptions underneath the probability instead of just nodding at the path and moving on.
There’s also something else happening here. When you see three distinct paths laid out side by side, you naturally start noticing what they share and where they diverge. Sometimes the aggressive and contrarian paths share a core mechanism and only differ in timing. Sometimes the conservative path is actually the riskiest one when you factor in what happens if you wait too long. You wouldn’t see any of that from a single-answer prompt.
🧭 Where to Actually Use This
- Pricing decisions (raise aggressively, hold steady, or undercut the market entirely)
- Content strategy (post daily, post less but bigger, or ignore the algorithm and go niche)
- Product launches (full rollout, beta-only, or skip this feature and ship the next one)
- Negotiation prep (push hard, meet in the middle, or make a completely different ask)
- Hiring decisions (build the team now, stay lean and contract out, or restructure the role entirely)
- Partnership conversations (go deep with one partner, spread across three, or stay independent and grow the leverage first)
The pattern scales to almost any real decision because every real decision has an aggressive version, a conservative version, and a version that sounds weird until someone with more perspective tells you it’s actually the move. The prompt just surfaces all three at once instead of defaulting to whatever answer comes first.
Prompt of the Day
Copy this and swap in your situation:
I’m trying to [describe your decision]. Propose 3 paths: 1. The Aggressive path. 2. The Conservative path. 3. The Contrarian path. For each, give me the core logic, the key risks, and your estimated probability of success. Then tell me which one you’d pick and why.
The “tell me which one you’d pick” addition at the end forces a recommendation instead of a list. Useful when you’re genuinely stuck and just need a push. It also reveals something interesting: if the AI picks the conservative path but you feel resistant to it, that resistance is data. If it picks aggressive and you feel relieved, that’s data too. The prompt doesn’t just generate options. It surfaces your own reaction to them, which is often the clearest signal you have.
One more tweak worth trying: after you get the three paths, follow up with “Now assume the aggressive path fails in month two. What’s the fastest recovery?” That stress-test question turns the output from a strategy menu into an actual contingency plan.
Why It Works
Most prompts ask for the answer. This prompt asks for the answer space. You sit with three competing options before collapsing to one. That’s how experienced strategists think, and AI is surprisingly good at it when you ask the right way. The reason it works is structural: you’re not asking AI to be smart, you’re asking it to be exhaustive before you decide. The intelligence is in the frame, not just the output.
Single-answer prompts optimize for speed. Three-path prompts optimize for coverage. When the decision is small, speed wins. When the decision actually matters, coverage wins. Knowing which mode to use is half the skill.
If you’re making decisions from a single AI response, you’re leaving most of the thinking on the table.
Try it on the next real decision you’re sitting on. The contrarian path alone is usually worth the 30 seconds it takes. More often than you’d expect, it’s the one you end up going with.
The ‘Scenario Branching’ Manager.
by u/Significant-Strike40 in PromptEngineering