The Pre-Mortem Protocol: Stress-Testing Your AI Deployment Before You Commit

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The Pre-Mortem Protocol: Stress-Testing Your AI Deployment Before You Commit

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Most owner-CEOs adopt AI the way they adopt a new hire: they write the job description, pick a tool, and hope. But the highest-leverage decision isn't which AI to use — it's whether you've honestly stress-tested the deployment before it touches real work. In this episode, Alex Tran introduces the Pre-Mortem Protocol, a four-part framework that forces you to imagine your AI initiative has already failed and then work backward to identify the specific conditions that would cause that failure. You'll learn how to name the human-accountability boundary before you configure a single prompt, how to identify the data and workflow dependencies that will quietly kill your rollout, and how to turn the pre-mortem into a one-page decision document that your whole team can use. This isn't about pessimism — it's about making your AI bets more honest, more governable, and more likely to survive contact with reality. If you've ever deployed a tool that looked great in a demo and then died in your operations, this episode is for you.

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