Decision avoidance: the decide prompt pack
This pack helps you test whether more AI analysis will eventually remove the need to make an uncertain decision. It turns the idea into a small decision you can inspect this week, without inventing customer evidence or hiding behind more output.
Start with the evidence
I need to decide whether more AI analysis will eventually remove the need to make an uncertain decision.
Review the material I paste below.
Separate observed behaviour, direct statements, opinions, and assumptions.
Quote the evidence behind every conclusion.
Do not suggest solutions yet.
End with the three most important missing facts.
Useful signals to look for:
- Prompts keep growing
- Recommendations repeat in new formats
- No new outside evidence enters the decision
Run the smallest honest test
The test is to cap the analysis, identify the missing fact, and collect one real observation. Decide what passing and failing mean before you see the result. Otherwise almost any outcome can be explained as good news after the fact.
Design a seven-day test to cap the analysis, identify the missing fact, and collect one real observation.
The risky assumption is: more AI analysis will eventually remove the need to make an uncertain decision.
Use real behaviour, not hypothetical intention.
Give me the participant, task, evidence to capture, pass condition,
failure condition, and the decision each result should trigger.
Keep the test small. Do not propose a new product or campaign.
Ask for a real timeline
Write five interview questions about a specific past event.
Cover what happened, what they tried, the workaround, the cost,
and what happened afterward.
Do not ask what feature they want or whether they would use an idea.
Add one short follow-up beneath each question.
Read the result without rescuing it
Review these notes as a skeptical product partner.
Create two columns: what happened and my interpretation.
Flag any interpretation unsupported by an observation.
Give the strongest case for continuing and the strongest case for stopping.
Name the one missing fact most likely to change the decision.
Make the decision
Return to AI after the test, when it has evidence to reason over instead of more speculation.
Use this short decision note:
- Decision: What happens now?
- Evidence: What observed behaviour supports it?
- Risk: What could still make it wrong?
- Next check: What will you inspect and when?
- Not doing: What attractive option is waiting?
One prompt to run on everything
Help me decide whether more AI analysis will eventually remove the need to make an uncertain decision.
1. Separate behaviour, statements, opinions, and assumptions.
2. Quote the evidence behind each important claim.
3. Name the weakest assumption carrying the most risk.
4. Design a seven-day test to cap the analysis, identify the missing fact, and collect one real observation.
5. Set pass and failure conditions before the test.
6. Give five past-behaviour interview questions.
7. End with a decision note and one thing we are deliberately not doing.
Do not invent customer facts. Mark missing evidence clearly.
Download the runnable R151 pack
Use the safe dry-run first. The starter validates fictional input and returns a reviewable draft; it does not publish, charge, contact users, or change production systems. The ZIP includes the Node service, tests, Docker setup, n8n workflow, GitHub Actions, and examples.