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UI/UX & Agent-Experience Design · Playbook · Core · ~4 min read
UI/UX & AGENT-EXPERIENCE DESIGN · PLAYBOOK · CORE

Synthesize Interviews with Quote-Level Citations

AI can synthesize six interview transcripts into themes in minutes — and it can also fabricate a perfectly plausible quote and attribute it to a participant who never said it. This playbook runs the synthesis with quote-level citations and timestamps required on every theme, then spot-verifies each against source. Hallucinated quotes are the failure mode you're hunting.

Workflow area: Research & Synthesis · Tier: Core · Hands-on time: ~35 minutes

Manual synthesis is the most honest work in research and the reason it doesn't happen: six transcripts is two days of highlighting, and under deadline the team "remembers" the interviews instead. AI collapses two days to an afternoon — but a synthesis model's failure mode is uniquely poisonous for research. It doesn't fail loudly; it produces a clean quote, in the participant's voice, supporting a plausible theme, that was never said. A fabricated quote in a themes report is worse than no research at all, because it carries research's authority. The citation-and-verification discipline is not overhead on this recipe; it is the recipe.

When to use — and when not to

  • Use it for any multi-transcript synthesis3+ interviews, usability sessions, or the mixed pile from pb-01's calls; the discipline is identical, the gain scales with volume.
  • Use it when stakeholders will act on the outputroadmap-influencing findings need the citation trail precisely because they'll be challenged.
  • Use it to reprocess old studieslast year's transcripts, synthesized with today's discipline, often answer this quarter's questions for free.
  • Skip it below three transcriptsread two interviews yourself; the model's leverage is breadth, and at n=2 you are the better instrument.
  • Skip it when transcripts can't leave your tenantsensitive-domain research (health, finance, minors) runs only in approved tools, or by hand.

The recipe

  1. Prepare transcripts with stable timestamps and IDs. Each transcript needs participant ID (anonymized — P1, P2…), and timestamps throughout (your notetaker's export has them). The timestamp is what makes every claim checkable in seconds instead of minutes — it's the load-bearing part of the whole discipline.

  2. Run the synthesis with citations made mandatory. In Claude (long transcripts favor large context windows):

    You are synthesizing user interviews into themes. The citation
    rules below are absolute.
    
    Research question: [e.g. "How do finance approvers decide what to
    scrutinize vs. rubber-stamp?"]
    Transcripts: [PASTE ALL, EACH LABELED P1, P2, ... WITH TIMESTAMPS]
    
    Produce themes, for each:
    - THEME — one sentence, in plain language
    - STRENGTH — how many participants evidence it (list IDs)
    - EVIDENCE — 2-4 VERBATIM quotes, each with participant ID and
      timestamp, exactly as spoken. Never paraphrase inside quotation
      marks. Never merge statements from different moments into one
      quote.
    - COUNTER-EVIDENCE — quotes that cut against the theme, same
      citation rules. If none, write "none found".
    Then: SURPRISES (contradicts our assumptions), and TENSIONS
    (participants who disagree with each other).
    Rules: a theme with fewer than 2 quote citations does not appear.
    If you are not certain a quote is verbatim, mark it [CHECK].
    
  3. Spot-verify every theme against source — the hallucination hunt. For each theme, take at least one cited quote per participant, open the transcript at the timestamp, and compare word-for-word. You're hunting four specific frauds:

    VERIFICATION LOG
    Theme 1 / P3 @ 14:22 — VERBATIM ✓
    Theme 2 / P1 @ 08:15 — CLEANED: model dropped "I guess maybe" —
    hedge matters, restored original
    Theme 2 / P5 @ 21:40 — MERGED: two statements 4 min apart joined
    into one "quote" — split and re-cited
    Theme 4 / P2 @ 11:03 — FABRICATED: nothing like this at 11:03 or
    anywhere in P2 — quote deleted, theme re-evaluated (now n=1,
    theme demoted to open question)
    

    A fabricated or unfindable quote kills itself and puts its theme on trial. Every [CHECK] flag gets resolved. Keep the verification log — it's the report's warrant.

  4. Weigh the themes yourself. Counts are not importance: a theme with two quotes from your exact target segment can outweigh one with six from adjacent users. Re-order the verified themes by decision relevance, and write one line per theme on what it means for the product — the model synthesized what was said; deciding what it implies is the researcher's half of the job.

  5. Publish with citations intact and link the sources. The report keeps every quote's ID and timestamp; file it in Dovetail (or your repo) with links from each theme to its source transcripts — this is what pb-03's persona sweeps and pb-18's repository queries will consume. A stakeholder who can click from claim to quote to recording extends trust; one who can't, shouldn't.

Make it yours

  • Dovetail-native version: if transcripts already live in Dovetail with highlights, run its AI synthesis for the first pass and apply steps 3–5 unchanged — platform AI hallucinates too; the verification discipline transfers whole.
  • Notably for the visual-canvas pass: teams that synthesize spatially can auto-cluster highlights in Notably, then enforce the same rule — no cluster graduates to "theme" until its quotes pass the timestamp check.
  • Claude Projects for longitudinal synthesis: accumulate verified themes reports (not raw transcripts) in a Project per product area and ask cross-study questions — "what has changed about approval anxiety since Q1?" — with citations inherited from the underlying verified reports.

Quality check

  • Every quote traced or diedthe verification log covers at least one quote per participant per theme; anything unfindable at its timestamp was deleted, not shrugged at.
  • Hedges and mess survivedparticipants say "I guess" and contradict themselves; over-clean quotes mean the model polished the humans out of the data.
  • Counter-evidence sections have content sometimesa synthesis where every theme is unopposed is a synthesis that wasn't looking; real data argues with itself.
  • Theme strength matches citation realitya theme claiming five participants cites five distinct IDs; check the IDs, not the claim.
  • Surprises made it to the topthe finding that contradicts the roadmap belongs in the summary, not paragraph nine; coherence bias buries exactly what you paid for.
  • The report links to sourcesclaim → quote → transcript → recording, every link live, or the citation discipline was cosplay.
Warning

Interview transcripts are personal data — anonymize before synthesis, process only in tools your organization has approved for research data, honor each study's consent and retention terms, and never let a convenience tool become the place raw participant voices quietly accumulate.

Key Takeaway:

The synthesis is only as trustworthy as its worst quote — require citations, verify against source, and let any fabricated quote put its whole theme on trial.

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