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Pre-mortem: assume the decision failed, then work backward to why
You're about to make a big call and everyone's nodding. Run a pre-mortem that surfaces the failure modes optimism is hiding.
The prompt — copy and run it
You are a decision advisor running a pre-mortem — a thinking aid; the judgment stays yours. Produce: A) FAILURE SCENARIO — assume it's 18 months later and this decision failed badly; write the two-paragraph story of how, grounded in the real risks I described. B) FAILURE MODES — the top 5 specific causes from that story, each rated on likelihood and how early we'd see it coming. C) EARLY WARNINGS — for the top 3 modes, the concrete leading indicator to watch and the pre-committed action if it trips. D) REVERSIBILITY — an honest read on how reversible this decision is and the cheapest way to preserve optionality. Inputs: [THE DECISION] · [WHY WE'RE LEANING YES] · [KNOWN RISKS] · [WHAT'S AT STAKE / TIMELINE] Rules: Do not invent facts or manufacture false risks — build only from what I described, and separate plausible risks from remote ones. This structures the downside; the decision and the judgment stay yours. Verify anything uncertain against the source before relying on it; keep confidential and identifying data out of consumer AI tools.
Why this prompt works
Executive decisions fail from risks that optimism and consensus suppressed; a pre-mortem that forces the team to inhabit the failure first, then convert its causes into leading indicators with pre-committed responses, surfaces the downside while it's still cheap to act on — and the reversibility read reframes a scary bet into a question of preserving optionality.
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Frequently asked
When should I use this prompt?
You're about to make a big call and everyone's nodding. Run a pre-mortem that surfaces the failure modes optimism is hiding.
Why does this prompt work?
Executive decisions fail from risks that optimism and consensus suppressed; a pre-mortem that forces the team to inhabit the failure first, then convert its causes into leading indicators with pre-committed responses, surfaces the downside while it's still cheap to act on — and the reversibility read reframes a scary bet into a question of preserving optionality.
What mistake does this prompt help you avoid?
{'code': 'PF02', 'note': 'Consensus-suppressed downside — a pre-mortem converts failure causes into watched leading indicators with pre-committed responses; judgment stays yours.'}
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