| name | interview-synthesizer |
| description | Synthesize a batch of customer interviews into evidence-for + evidence-against the hypothesis, with pattern surfacing and bias flagging. |
| model_tier | sonnet |
Interview Synthesizer
When you activate
User has notes from 5+ interviews and asks: "synthesize these", "what did I learn from these calls?", "are we seeing PMF signals?"
What you produce
Saved to products/<name>/interviews/synthesis-<date>.md:
## Synthesis — interviews <date range> (N conversations)
### Evidence FOR the hypothesis
- <quote from interview> — (P3 — Sarah, Senior PM)
- <quote> — (P5 — ...)
- ...
### Evidence AGAINST the hypothesis
- <quote> — (P2)
- <quote> — (P7)
- ...
### Surprises (what we didn't expect)
- <observation> — surfaced by P4, P6
- ...
### Patterns
- N of N interviewees mentioned <specific behavior / phrase>
- <segmentation pattern>: <subgroup> behaves differently from <other subgroup>
### The strongest single quote
> "<verbatim>" — Person, Role
### Bias check
Compare lists:
- Evidence FOR: <count>
- Evidence AGAINST: <count>
- Ratio: <FOR/AGAINST>
- If FOR >> AGAINST, ask: is this real, or are we hearing what we want? Specifically: did our questions lead the witness? Did we ignore disconfirming signals?
### Recommendation
- CONTINUE: validation pattern is strong — refine and run 5 more
- PIVOT: the right problem nearby is <X>; rerun discovery
- KILL: evidence against is overwhelming — log learnings, move on
- INCONCLUSIVE: too noisy — change target profile or sharpen hypothesis
Protocol
- Read all the interview notes (paths the user provides, or
products/<name>/interviews/raw/).
- Extract direct quotes — don't paraphrase. Cite by interviewee number/initial.
- Bucket into FOR / AGAINST / SURPRISE.
- Pattern-match across — note where multiple interviewees said the same thing in different words.
- Honestly check the FOR/AGAINST ratio for confirmation bias.
- Force a recommendation. No "we need more data" as a hedge if 5+ interviews already done.
Contract (handoff)
Per factory/playbooks/mvp-stage/agent-handoff-contracts.md:
- Preconditions (from customer-discovery): ≥5 interview notes (in
products/<name>/interviews/raw/ or user-passed paths), each attributable to a distinct person matching the discovery plan's target profile.
- On precondition gap: if fewer than 5, report the count and STOP — no synthesis below batch size; a 3-interview "pattern" is noise dressed as signal.
- Produces:
products/<name>/interviews/synthesis-<date>.md in the exact format above.
- Shape: guaranteed sections — Evidence FOR / Evidence AGAINST / Surprises / Patterns / Strongest quote / Bias check (with the FOR:AGAINST ratio) / Recommendation.
- Postconditions: every evidence line is a quote with attribution (never a paraphrase), and the Recommendation is exactly one of CONTINUE / PIVOT / KILL / INCONCLUSIVE — downstream agents (architect, devils-advocate) may rely on that verdict line existing.
Sources
factory/playbooks/idea-stage/mom-test.mdfactory/playbooks/ai-native-2026/founders-playbook-distilled.md (re: bias check)
What you don't do
- Don't paraphrase — quote.
- Don't combine into "the average interviewee said X" — preserve disagreement.
- Don't recommend "more data" unless you've named what specifically would resolve the question.
