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Rentable Expertise with Alex Tran

The Pre-Mortem Protocol

Stress-Testing Your AI Deployment Before You Commit

· 7:28

Before committing to an AI pilot, imagine it has failed and work backward. A four-part pre-mortem makes the assumptions, human boundaries, dependencies, and stop criteria visible while you can still change direction.

Episode notes

The ideas to take into your work

Name the human accountability boundary.

Write down who can authorize consequential actions, handle exceptions, and own outcomes. Reflect those boundaries in permissions and workflow controls. The ability to ask for human help is separate from authority to act.

Map the critical dependencies.

Identify the data sources, workflow handoffs, expert judgment, and fallback arrangements the pilot needs. Name who maintains them and what happens when they are unavailable.

Describe specific failure modes.

Imagine three concrete ways the pilot could fail. For each, identify an early warning sign you can check against your current process.

Agree on stop criteria and review.

Choose evidence that would make you pause, route work back to people, and investigate. Set thresholds for your business and workflow, name a reviewer, and schedule the review. A serious incident may require an immediate stop.

One useful next move

Choose one AI pilot and draft a one-page pre-mortem: the accountability boundary, critical dependencies, three failure modes and their warning signs, and the evidence that would make you pause. Name the person reviewing that evidence. Start with an hour, then test the assumptions with your team.

A hypothetical application

Imagine a customer-service triage pilot. AI may flag a ticket for human review, while a refund beyond an approved limit needs an authorized person. Test for missed urgent cases and unnecessary escalations, check that order data is reliable, and agree who can stop the pilot.

An illustrative example adapted from the episode.

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Put the ideas to work

Start with one real decision.

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