Split a decision into reversible and irreversible parts
Separates the one-way-door parts of a decision from the two-way-door parts, so you can move fast on one and slow down on the other.
The prompt
Help me split a decision into the parts we can easily undo and the parts we can't.
The decision: [WHAT WE'RE CONSIDERING - e.g. "switch our CRM", "open a second office", "restructure the team"]
What it involves: [CONTRACTS, MONEY, PEOPLE, SYSTEMS, CUSTOMER COMMITMENTS, PUBLIC ANNOUNCEMENTS]
Timeline and pressure to decide: [DATES]
What worries me most: [CONCERNS]
Steps:
1. Break the decision into its component choices and commitments.
2. Classify each one:
- Two-way door: easy and cheap to reverse.
- Costly to reverse: possible, but with real cost in money, time, trust, or morale.
- One-way door: practically irreversible (e.g. layoffs, public commitments, signed long-term contracts, deleted data, lost reputation).
3. For each, estimate the cost of reversing it and how long it stays reversible (some doors close after a date).
4. Suggest ways to make one-way parts more reversible: pilots, phased rollouts, break clauses, keeping the old system running, delaying the announcement.
5. Recommend how much analysis and sign-off each part deserves: decide fast on two-way doors, slow down on one-way doors.
Return:
1. A table: Part of the decision | Type (two-way / costly / one-way) | Cost to reverse | Window to reverse | How to make it more reversible.
2. What we can decide and start now.
3. What needs more evidence or senior sign-off, and what evidence.
4. A suggested sequence that keeps options open as long as possible.
Don't invent costs or contract terms; mark them [CHECK]. Contract and employment points may need legal or HR review.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Thinking & Decisions prompts
What to fill in
- DATES
- CONCERNS
- CHECK
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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