Decision Premortem Simulator

Helps simulate a future failure of a key decision to identify hidden risks, assumptions, early warnings, and experiments before committing.

Overview

Decision Premortem Simulator helps users stress-test an important decision before committing. It asks the user to imagine that the decision failed in the future, then works backward to expose hidden assumptions, execution risks, external risks, emotional risks, opportunity costs, early warning signals, and risk-reduction experiments.

This is a thinking tool. It supports clearer judgment but does not predict the future or replace qualified professional advice.

When to Use

Use this skill when the user is considering a meaningful choice such as:

• Launching a project, product, newsletter, course, or business experiment.
• Changing jobs, roles, schools, tools, workflows, or commitments.
• Making a large purchase or long-term personal plan.
• Publishing sensitive content or taking a public position.
• Choosing between options with uncertainty, tradeoffs, or possible regret.
• Pausing before a decision that feels exciting but under-examined.

Do not use it as the sole basis for regulated legal, medical, financial, mental-health, or crisis decisions.

Inputs

Collect these inputs:

• Decision under consideration.
• Preferred option or current plan.
• Goal and success definition.
• Decision deadline.
• Time horizon for the pre-mortem: 1 month, 3 months, 6 months, 1 year, etc.
• Constraints: money, time, energy, reputation, family, team, obligations.
• Stakeholders affected.
• Current evidence supporting the choice.
• Main assumptions.
• Alternatives already considered.
• Reversibility: easy to undo, costly to undo, or nearly irreversible.
• User's current emotional state: excited, afraid, rushed, avoidant, overconfident, pressured.

If information is missing, proceed with clearly labeled assumptions and ask for confirmation before strong recommendations.

Workflow

1. Frame the decision brief

   • Summarize the option, goal, deadline, constraints, stakeholders, current evidence, and success criteria.
   • Separate facts from assumptions.

2. Write the failure narrative

   • Imagine it is the selected time horizon in the future and the decision failed.
   • Write a concise, realistic failure story without catastrophizing.
   • Include operational, social, emotional, timing, and opportunity-cost dimensions.

3. Map failure modes

   • Group possible causes into:
     • Assumption risks.
     • Execution risks.
     • External / market / environment risks.
     • Stakeholder and communication risks.
     • Emotional / cognitive bias risks.
     • Opportunity costs.

4. Score risk signals

   • Rate probability, impact, and detectability on a 1-5 scale.
   • Low detectability means the user may not notice the problem until late.
   • Highlight high-impact and low-detectability risks.

5. Assess reversibility

   • Label the decision as a one-way door, two-way door, or staged door.
   • Suggest ways to make the decision smaller, reversible, or staged where possible.

6. Identify early warning signals

   • Define observable triggers that indicate the plan is drifting.
   • Include leading indicators, not only final outcomes.

7. Design risk-reduction experiments

   • Suggest small tests, conversations, prototypes, budgets, timeboxes, checklists, or evidence-gathering steps.
   • Each experiment should reduce one or more major risks.

8. Create the decision checkpoint

   • Recommend one of: proceed, pause, resize, gather evidence, stage the decision, or choose another option.
   • Explain the recommendation in terms of risk, reversibility, and evidence.
   • List what would change the recommendation.

Output Template

# Decision Premortem Simulator

## 1. Decision Brief
- Decision:
- Preferred option:
- Goal / success definition:
- Deadline:
- Time horizon:
- Constraints:
- Stakeholders:
- Current evidence:
- Key assumptions:
- Alternatives considered:
- Reversibility estimate:

## 2. Future Failure Narrative
"It is [time horizon] from now. This decision failed because..."

## 3. Failure Mode Map
| Category | Failure Mode | Underlying Assumption | Notes |
|---|---|---|---|
| Assumption Risk |  |  |  |
| Execution Risk |  |  |  |
| External Risk |  |  |  |
| Stakeholder Risk |  |  |  |
| Emotional / Bias Risk |  |  |  |
| Opportunity Cost |  |  |  |

## 4. Probability / Impact / Detectability Table
Score 1 = low, 5 = high.

| Risk | Probability | Impact | Detectability Problem | Priority |
|---|---:|---:|---:|---|
|  |  |  |  | High/Medium/Low |

## 5. Reversibility Assessment
- Door type: One-way / Two-way / Staged
- What makes it reversible or irreversible:
- How to reduce commitment size:

## 6. Early Warning Signals
| Signal | When to Check | Threshold for Concern | Response |
|---|---|---|---|
|  |  |  |  |

## 7. Risk-Reduction Experiments
| Experiment | Risk Reduced | Cost / Time | Success Signal | Decision Impact |
|---|---|---|---|---|
|  |  |  |  |  |

## 8. Final Recommendation
- Recommendation: Proceed / Pause / Resize / Gather Evidence / Stage / Choose Another Option
- Rationale:
- Next 3 actions:
- What would change this recommendation:

Safety Boundaries

• This skill does not provide legal, medical, financial, mental-health, emergency, or crisis advice.
• Do not present probability scores as objective predictions. They are structured estimates for discussion.
• Do not pressure the user into a specific decision. Present tradeoffs, assumptions, and next evidence to gather.
• Encourage qualified professional input for regulated, high-stakes, or safety-critical decisions.
• If the decision involves self-harm, harm to others, abuse, coercion, or immediate danger, prioritize safety and appropriate human support rather than decision analysis.
• If the user lacks enough information, recommend evidence-gathering rather than false certainty.

Examples

Example 1: Launch Decision

User: "Should I launch this paid course next month?"

Assistant should produce:

• A decision brief with deadline and success criteria.
• A 6-month failure narrative.
• Risks around audience demand, production capacity, pricing, support burden, and reputation.
• Experiments such as a waitlist, pilot cohort, or sales page test.

Example 2: Career Change

User: "I'm thinking about quitting my job to study AI full-time."

Assistant should produce:

• A careful pre-mortem that includes finances, energy, family constraints, motivation, opportunity cost, and re-entry options.
• Strong reminder that this is not financial or career counseling.
• Staged alternatives such as part-time study, runway calculation with a qualified advisor, or milestone-based decision gates.

Example 3: Tool Purchase

User: "Should I buy an expensive software subscription for my project?"

Assistant should produce:

• Assumption risks around usage, integration, switching cost, and alternatives.
• Reversibility assessment.
• A short trial plan and cancellation checkpoint before committing.