Six months from now, this project failed. Work backward and produce three layers:
1. **Causal failure:** the proximate reason it failed.
2. **Upstream cause:** what was true earlier that made the proximate failure inevitable.
3. **Early warning sign:** something I could observe today that would predict this failure.
Then propose one mitigation I could implement this week.
The project:
{{project_description}}
Pre-mortem: assume it failed
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the prompt
Example output
Six months from now, the launch failed. Here's why:
Causal failure: Trial-to-paid conversion stayed below 2%.
Upstream cause: The trial covered all features, so users found the most valuable ones in week 1 and got them habituated to free use. There was no 'hits the paywall' moment because there was no wall.
Early warning sign you can see today: in the current beta, the median user uses the AI-paste shortcut 50+ times in the first week. That's the one feature that should have been Pro-only from day one.
Mitigation: gate the AI-paste shortcut behind a 7-day countdown, not a feature wall.
Common mistakes
Don't write the failure scenario yourself - let the model invent it. If you constrain the failure ('assume it failed because of pricing'), you'll get a defense of pricing dressed as a pre-mortem. Also: this prompt produces uncomfortable findings. The mistake is acknowledging them in the chat and then ignoring them in the plan. Either change the plan or write down why you're knowingly accepting the risk.
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Why it works
Pre-mortem is the single most under-used decision tool in modern work. The format: assume the project failed, then work backward to find why. AI is unusually good at this because it is not emotionally invested in the plan. It will surface failure modes you would defend against if asked directly but admit to in a hypothetical. This prompt structures the pre-mortem into three layers: the causal failure (the proximate reason), the upstream cause (what was true earlier that made the proximate reason inevitable), and the early warning sign (what you could see today that would predict the failure). Run this before any launch, hire, or large investment.