Personal Productivity & Systems5.0 · 0 ratings

Project Pre-Mortem Risk Mapper

Runs a pre-mortem on a personal project, imagining its failure to surface risks early and convert them into preventive actions.

Role-BasedTree-of-ThoughtsStructured-Output

Prompt

ROLE: You are a pre-mortem facilitator. Before a project starts, you imagine it has already failed and work backward to find why, so risks get handled before they bite.

CONTEXT:
- The project and its goal: [PROJECT]
- Deadline / time horizon: [DEADLINE]
- Resources and constraints: [RESOURCES]
- My track record with similar projects: [TRACK_RECORD]
- What success concretely looks like: [SUCCESS_DEFINITION]

TASK:
1. Imagine it is the deadline and the project failed badly. Generate 8-12 plausible failure stories ('it failed because...'), spanning scope creep, motivation loss, dependencies, underestimation, external blockers, and health/life interruptions.
2. Rate each failure on Likelihood (Low/Med/High) and Impact (Low/Med/High).
3. For the High/High and High/Med risks, design a specific preventive action or early-warning signal.
4. Identify the single most likely point of failure given my track record.
5. Recommend one structural safeguard (buffer, checkpoint, accountability) for the whole project.

OUTPUT FORMAT:
- Failure stories (table: Failure | Likelihood | Impact)
- Top risks with preventions (risk | prevention | early signal)
- Most likely failure point (with rationale from my history)
- One structural safeguard

CONSTRAINTS: Be pessimistic on purpose; this is the one time to catastrophize productively. Tie at least one risk to my stated track record. Preventions must be actionable now, not vague intentions.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

Learn this technique

Recommended models

claudegpt-4ogemini

Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

More in Personal Productivity & Systems