Pivot Decision Framework
Distinguishes a failing execution from a failing thesis, since the two need opposite responses.
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Running it, start to finish
- State the original thesis in its four parts.
- Identify which part is failing and whether it was executed well.
- Look hard at whatever worked unexpectedly.
What you get back
The output this produces, every time.
- Tests problem, solution, pricing and distribution independently rather than as one failure.
- Asks whether the thesis was executed properly before it is abandoned.
- Looks for the anomaly, which is where pivots usually find their direction.
Getting better results
Where this usually goes wrong, and how to avoid it.
- Check distribution before blaming the product. A good product nobody encounters is indistinguishable from a bad one, and this is the most common misdiagnosis.
- Follow the thing that unexpectedly worked. The segment that retained or the use case people invented is usually the direction, and it is easy to dismiss as noise.
- Check the runway supports the pivot. Pivoting without enough time to test the new direction produces a second failure with no evidence from either.
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Written for The AI University. Every prompt in this library is original work — authored, tested and revised here, not collected from elsewhere. 365 of them, free with an account.