Thinking Partner: Using AI for Decisions and Strategy

Everyone talks about AI saving time. Writing faster, summarizing faster, analyzing faster. And that's real. But the use case nobody talks about enough is this: AI can help you think better.

Not think for you. Think better.

Here's what I mean. Last week I was stuck on a pricing decision. Two options, both defensible, and I kept going back and forth. I wasn't missing information. I was missing structure.

So I opened Claude and typed: "I'm deciding between a per-seat pricing model and a usage-based pricing model for a B2B SaaS product. Here's the context..." and I laid out the situation. Customer profile, average deal size, competitive landscape, our cost structure. Then I said: "Give me a framework for making this decision. What are the key variables I should weigh?"

In about ten seconds I had a clear decision matrix I hadn't thought to build myself. Not because I couldn't build it. Because when you're deep in a decision, you skip the step of structuring the problem. You just churn.

AI doesn't churn. It structures. And that's incredibly useful.

Here are four ways to use AI as a thinking partner. Try at least one this week.

The framework request. "I'm deciding between X and Y. Here's the context. Give me a framework for evaluating this." Works for hiring decisions, strategic bets, vendor selections, market entry. You're not asking for the answer. You're asking for the right way to think about the question.

The red team. "Here's my plan for Q3. Argue against it. What could go wrong? What am I underweighting?" This is the chain-of-thought technique from Week 2 applied to strategy. You're asking AI to think through the counter-argument step by step. It will find holes you missed, not because it's smarter than you, but because it has no ego invested in your plan.

The brainstorm with teeth. Don't just ask for ideas. Ask for ranked ideas. "Give me 10 ways to reduce customer churn for a B2B product with an average contract value of $50K. Then rank them by feasibility for a team of 5." The ranking forces AI to apply constraints, which gives you ideas you can actually execute.

The pre-mortem. This one comes from behavioral psychology. "Assume this project failed in six months. What were the three most likely reasons?" It's a mental trick that works on humans and it works just as well when you ask AI. You'll get risks you hadn't considered because you were focused on making the plan work, not imagining it failing.

The persona trick from Week 2 makes all of these more powerful. Try: "You're a skeptical board member reviewing this plan" or "You're a competitor's strategist looking at our market position." Different perspectives surface different blind spots.

A word of caution. AI is good at structure, frameworks, and generating possibilities. It's not good at knowing your market, your team, or your gut feel. The output is a starting point for your thinking, not a replacement for it. If AI gives you a framework with five criteria and one of them feels irrelevant to your situation, throw it out. You still make the call.

The people who get the most out of AI aren't using it to avoid thinking. They're using it to think more clearly, more quickly, and from more angles.

The most underrated use of AI: not asking it to do work, but asking it to help you think.