ThinkWithPrompt by SynotticThinkWithPrompt

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.

Thinking & DecisionsFew-ShotAdvancedLegalPlanFill-in Template

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.

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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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