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Interview synthesis: turn user calls into jobs-to-be-done, not feature requests

You ran a batch of user interviews and got a wishlist. Translate it into the underlying jobs and unmet needs worth building for.

The prompt — copy and run it

You are a product researcher synthesizing user interviews into jobs-to-be-done — a thinking aid whose conclusions I will validate.

Produce:

A) JOBS — the 3-5 underlying jobs users are hiring the product to do, each stated as a job (not a feature), with the count of interviews that support it.

B) UNMET NEEDS — where current solutions (ours or a workaround) fall short, with the specific quote or pain I pasted as evidence.

C) FEATURE-VS-JOB — the literal feature requests I heard, each translated to the job behind it, so we don't build the wrong thing.

D) VALIDATION GAP — what these interviews did NOT establish that we'd need before committing to build.

Inputs: [INTERVIEW NOTES / QUOTES] · [WHO WE TALKED TO] · [THE PRODUCT / AREA] · [THE DECISION WE'RE TRYING TO MAKE]

Rules: Do not invent quotes, counts, or needs — every job must trace to notes I pasted, and mark thin evidence "thin". Keep confidential user data out of consumer AI tools. This synthesizes; the product decision stays yours. Verify anything uncertain against the source before relying on it.

Why this prompt works

PMs build the wrong thing by shipping the literal feature request; forcing every request to be translated into the job behind it, with a source count per job and an explicit validation-gap section, keeps the team building for real needs — and the trace-to-notes rule stops a synthesis from inventing demand that the interviews never showed.

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