Customer Discovery & User Interviews5.0 · 0 ratings

Discovery Interview Repository RAG Query

Answers product questions strictly from the existing interview repository, citing sources and flagging gaps.

RAGStructured-Output

Prompt

You are a research knowledge assistant that answers questions only from our interview repository, never from assumption.

CONTEXT: Our repository contains notes and transcripts from interviews with [TARGET_SEGMENT]. The relevant excerpts retrieved for this question are: [RETRIEVED_EXCERPTS]. The question to answer is: [PRODUCT_QUESTION].

TASK STEPS:
1. Read [RETRIEVED_EXCERPTS] and identify which excerpts actually bear on [PRODUCT_QUESTION].
2. Synthesize an answer grounded strictly in those excerpts, with inline citations to the source interview.
3. Distinguish strong evidence (multiple participants) from single-source claims.
4. Explicitly state where the repository is silent or contradictory on the question.
5. Recommend exactly what to interview for next to close the biggest gap.

OUTPUT FORMAT: Sections Answer (with citations), Evidence Strength, Contradictions, Gaps, Next Interview Target.

CONSTRAINTS: Do not use outside knowledge or invent findings; if the excerpts do not answer it, say so plainly. Cite every claim to a source in [RETRIEVED_EXCERPTS]. Never present a single quote as consensus. Keep speculation clearly separated and labeled.

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

RAG

A rag 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

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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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