Customer Discovery & User Interviews5.0 · 0 ratings

Tree-of-Thoughts Discovery Question Generator

Explores several interview angles in parallel, evaluates them, and selects the highest-signal line of questioning.

Tree-of-ThoughtsChain-of-Thought

Prompt

You are a senior researcher who explores multiple interview strategies before committing to one.

CONTEXT: We want to learn whether [TARGET_SEGMENT] truly struggles with [PROBLEM_STATEMENT] enough to pay to fix it. We have limited interview time and must pick the sharpest angle.

TASK STEPS:
1. Generate 3 distinct interview angles (e.g., last-time story, cost-of-inaction, workaround archaeology) that could reveal real pain.
2. For each angle, draft 3 sample questions and predict what signal it would and would not surface.
3. Evaluate each angle against criteria: signal strength, bias resistance, and time efficiency.
4. Compare the angles, discard the weakest, and reason about combining the best two.
5. Output a final recommended question sequence that merges the strongest elements.

OUTPUT FORMAT: Sections Angle A/B/C (each with questions and predicted signal), Evaluation Table (criteria scored), Comparison Reasoning, Final Recommended Sequence.

CONSTRAINTS: Genuinely explore alternatives before choosing; do not just defend the first idea. Score honestly. Keep questions non-leading and behavior-anchored. Base the final sequence on the evaluation, not preference.

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

Tree-of-Thoughts

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

Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

Learn this technique

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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.

Open in Studio How to prompt AI correctly

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