Pre-mortem
A preparation technique in which you assume the budget was rejected and work backward to the most likely causes, so you can fix them before the meeting rather than diagnose them after it. Distinct from a post-mortem, which happens after the failure. Once you have listed the possible causes, do not treat them as equally urgent; rank them by how likely each is and how much damage it would do if it happened, and spend your remaining preparation time on the top of that list, not spread evenly across every cause you can imagine.
Defined in 5 GAGE programs, which carry 15 distinct definitions of it. The wording above is taught in AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A preparation technique in which you assume the budget was rejected and work backward to the most likely causes, so you can fix them before the meeting rather than diagnose them after it. Distinct from a post-mortem, which happens after the failure. Once you have listed the possible causes, do not treat them as equally urgent; rank them by how likely each is and how much damage it would do if it happened, and spend your remaining preparation time on the top of that list, not spread evenly across every cause you can imagine.
An exercise, borrowed from decision-science practice, in which an engineer assumes a decision has already failed at some point in the future and works backward to generate the most plausible reasons why, in order to surface real weaknesses before a live review does. Used in this topic as a structured method for anticipating objections and guarding against confirmation bias.
A decision-science technique in which, before committing to a high-stakes call, a team imagines the decision has already failed a year later and works backward to name why. It surfaces doubts that a confident room otherwise suppresses, turning them into candidate failure conditions and guardrails; it is the practical antidote to the Zillow failure mode.
The general practice, applied throughout Section 3I's worked walkthrough, of deliberately imagining a failure has already happened and working backward through what each kind of reviewer would ask about it, rather than waiting for a real incident or a real examiner to ask those questions for the first time.
A decision technique in which one assumes a plan has already failed and writes the story of why, to surface the assumptions and risks that optimism hides; pairs naturally with a predictive model's blind spots.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Crafting Prompts for Business Scenarios · Practical AI Workflow Design and Prompt Engineering, AI Literacy & Professional Conduct
- AI for Innovation: Predictive Analytics Applications · Advanced AI Literacy, AI Literacy & Professional Conduct
- Know Your Attacker · The Capstone: Deploy and Defend, Agentic AI Governance: Applied Mastery
- Scoping the deployment: what your organization actually needs versus what the demo showed · Shipping AI and Surviving the Incident, AI Governance: Applied Mastery
- The hostile board: defending your AI budget to directors who interrupt · The Money: Budgets, ROI, and Risk, AI Governance: Applied Mastery
- Building Personal Authority and Credibility Without a Technical Background · Own the AI Transformation Mandate, Business AI Transformation
- Capstone Phase 1 - The Organizational Assessment · Capstone: Your Transformation Blueprint, Business AI Transformation
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.