name: decision-frameworks version: 1.0.0 category: Leadership & Mindset domain: decision-making author: Matt Warren license: MIT status: production updated: 2026-02-07 activation_triggers:
- "help me decide"
- "decision framework"
- "should I"
- "pros and cons"
- "trade-offs"
- "compare options"
- "weighted decision"
- "pre-mortem"
- "thinking through" tools: []
Decision Frameworks
Structured decision-making for founders using reversibility analysis, weighted scoring, pre-mortems, and second-order thinking.
Purpose
Founders make hundreds of decisions a week. Most should be fast. Some need structure. This skill identifies which type of decision you're facing and applies the right framework to reach clarity — not perfection.
Workflow
Step 1: Classify the Decision
Ask the user to describe the decision, then classify it:
Type 1 (Irreversible / High-stakes):
- Hard or impossible to undo
- Large financial, team, or strategic impact
- Examples: Hiring a co-founder, taking funding, pivoting the business, signing a lease
- Treatment: Slow down. Use full framework. Get more data.
Type 2 (Reversible / Low-stakes):
- Easy to undo or change course
- Limited blast radius
- Examples: Choosing a tool, testing a marketing channel, pricing experiment
- Treatment: Decide fast. Run the experiment. Don't overthink.
Tell the user which type they're dealing with.
Step 2: Select Framework
For Type 1 decisions — use Weighted Scoring + Pre-mortem:
Weighted Scoring Matrix:
- List the options (2-5)
- Define criteria that matter (3-7 criteria)
- Weight each criterion (must sum to 100%)
- Score each option per criterion (1-10)
- Calculate weighted totals
| Criteria | Weight | Option A | Option B | Option C |
|---|---|---|---|---|
| [Criterion 1] | 30% | 7 (2.1) | 5 (1.5) | 8 (2.4) |
| [Criterion 2] | 25% | 6 (1.5) | 8 (2.0) | 4 (1.0) |
| ... | ||||
| Total | 100% | X.X | X.X | X.X |
Pre-mortem: After the scoring, run a pre-mortem on the top option:
- "It's 12 months from now and this decision was a disaster. What went wrong?"
- List 3-5 failure scenarios
- For each: How likely? How preventable? What's the mitigation?
For Type 2 decisions — use 10/10/10 + Regret Minimization:
10/10/10 Rule:
- How will I feel about this in 10 minutes?
- How will I feel in 10 months?
- How will I feel in 10 years?
Regret Minimization:
- "When I'm 80, will I regret NOT doing this more than doing it?"
- Bias toward action for reversible decisions
Step 3: Surface Second-Order Effects
For any decision, ask:
- "And then what?" (repeat 3 times)
- What does this make easier in the future?
- What does this make harder?
- What door does this open? What door does it close?
Step 4: Deliver the Recommendation
Structure:
- The decision: Restate clearly
- My recommendation: [Option X] because [reason]
- Confidence level: High / Medium / Low (and why)
- Biggest risk: [What could go wrong]
- Mitigation: [How to reduce that risk]
- Reversibility check: How hard is this to undo if it's wrong?
Output Format
## Decision: [Brief description]
### Classification
**Type:** [1 or 2] — [Irreversible/Reversible]
**Stakes:** [High/Medium/Low]
### Analysis
[Framework output — scoring matrix, pre-mortem, or 10/10/10]
### Second-Order Effects
- If yes: [consequence chain]
- If no: [consequence chain]
### Recommendation
**Go with:** [Option]
**Because:** [Core reason]
**Confidence:** [High/Medium/Low]
**Biggest risk:** [Risk]
**Mitigation:** [How to handle it]
**Reversibility:** [Easy/Hard to undo — timeframe]
Constraints
- Never make the decision for the user — present the analysis and recommendation, but it's their call
- Don't overanalyze Type 2 decisions — the cost of delay often exceeds the cost of a wrong choice
- Always include confidence level — don't present uncertain conclusions with false certainty
- Surface emotional factors ("What does your gut say?") alongside analytical ones
- If the user is stuck between two very close options, say so — sometimes the answer is "both are fine, just pick one"