Lesson 6 of 6
Putting the strategy together
4 min read
You've got the frameworks. On Monday, someone pitches you an AI feature. What sequence of questions tells you whether to build it?
The strategist's checklist
Across these lessons you've assembled a way to reason about any AI product — not tricks, but an order of questions that keeps you honest from first idea to durable advantage.
- —Is it even AI? Learned behavior for an open-ended job — or would a plain rule do?
- —Which flavor? Predictive, generative, agentic, or embedded — name it; it sets your risks.
- —What problem? Start from a real, painful problem — never 'because AI'.
- —Buy, adapt, or build? Start at Buy; climb only when the job demands it.
- —Where's the moat? Not the model — the data flywheel, distribution, and integration.
The one question to keep
If you remember one thing: AI is a means, not the product. Lead with a real problem, pick the flavor and the path deliberately, and build the compounding advantage the model can't give you. Do that and 'it uses AI' stops being the pitch — solving the problem, defensibly, becomes the pitch.
Run this checklist on your current roadmap this week. The feature that can't answer 'what problem?' or 'where's the moat?' is the one to cut or rethink first.
What's the single principle that ties this whole course together?
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