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Authoring tech blog/article series for note/Zenn/Qiita/dev.to. Not for specs (Scribe) or microcopy (Prose).

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referenceinterview-format.md

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Interview-Format Article

Purpose

Reshape raw Q&A material — interview transcripts, podcast episodes, AMA threads, lightning talks, customer conversations — into a polished interview-format article that preserves the interviewee's voice while removing filler and re-sequencing for narrative arc.

Scope Boundary

  • IN scope: transcript triage, question re-writing, answer trimming, voice preservation, narrative re-sequencing, pull-quote extraction, reader-facing intro and outro.
  • OUT of scope: live interviewing technique (delegate to field), podcast production (different domain), video editing (delegate to director), short blurb / quote-card design (delegate to prose or ink).

Core Concepts

Interview Article ≠ Transcript

Raw transcripts are a tax on the reader: filler words, asides, lost threads, and chronological order. Published interviews respect the spoken voice but re-organize for the page.

Raw Transcript Published Interview
Chronological Narrative-ordered
All filler retained Filler trimmed
Topics interleaved Topics consolidated
Q1 → A1 → Q2 → A2 strict Reordered around themes
~10,000 words for 60 min 1,500–4,000 words polished
Speaker filler ("um", "you know") Removed unless characteristic

Three Interview Article Forms

Form When Length
Q&A direct Engineer interviews, expert deep-dives — "Q:" / "A:" format with minimal narration 1,500–3,000 words
Narrative-with-quotes Profile pieces — author voice frames the interviewee's quotes 2,000–4,000 words
Roundtable 3+ participants on one topic — questions become section headers, answers attributed 3,000–6,000 words

Voice Preservation Rules

The interviewee must read the published version and feel "yes, that's me, just sharper". Rules:

  1. Never write words the interviewee didn't say in spirit. Paraphrasing is allowed; fabrication is not.
  2. Keep characteristic syntax — sentence fragments, technical jargon, regional expressions — even when they violate "good writing".
  3. Trim filler ("um", "you know", "kind of") unless the speaker uses them as a deliberate cadence.
  4. Reorder sentences within an answer for clarity, but don't fuse two unrelated answers into one.
  5. Send a draft to the interviewee for fact-check + voice-check before publish. Allow 3–5 line edits, not full rewrites.

Question Re-Writing

Spoken questions are often messy. Rewrite for the page:

Spoken Written
"So, like, I wanted to ask you, um, you know, about, like, the migration, like, what was the hardest part?" "What was the hardest part of the migration?"
"Cool, cool, so, before we wrap up, just one more, what would you tell someone starting out today?" "What would you tell someone starting out today?"

Keep the question short, specific, and free of compound clauses. A good written question fits one breath.

Answer Trimming

A 60-minute interview often produces 8,000–12,000 words. The article needs ~2,000–3,000. Cut by:

  1. Remove verbal filler globally.
  2. Drop tangents that don't serve the article's through-line.
  3. Compress redundant restatements ("So basically, like I said earlier …").
  4. For each answer, keep the surprising / specific / actionable parts; cut the obvious.
  5. Consolidate two adjacent answers if they share a topic.

The author's job is to respect the reader's time while honoring the interviewee's contribution.

Re-Sequencing

Chronological order rarely produces the best article. Common re-orderings:

Strategy When
Best-first Lead with the most surprising or quote-worthy answer; build context after
Theme-clustered Group by topic across the interview (career → tech → philosophy)
Tension-arc Open with conflict / problem, build to resolution / lesson
Reverse-chronological For "lessons learned" pieces, end-state first

Never re-sequence in a way that distorts meaning. If the interviewee said "X, but only after Y", don't isolate X without Y.

Pull-Quotes

Extract 3–5 pull-quotes (one sentence, 80–160 chars) and surface them in the article:

  • Format: oversized type, separated from body, attributed.
  • Choice criteria: surprising, repeatable, on-brand for the interviewee, complete on its own.
  • Avoid choosing quotes that are unflattering when isolated — context matters.

Author Intro and Outro

Every interview article needs an author frame:

Section Content
Intro (100–200 words) Who is this person? Why are we talking to them? What did the conversation cover? Why should the reader care?
Setup (1–2 lines per major topic) Brief author narration between sections
Outro (50–100 words) Where to find the interviewee (links, with consent), what's coming next, optional CTA

The intro is where the reader decides to keep reading. Treat it as seriously as a hook (see hook-design.md).

Consent and Attribution

Item Default
Real name Confirm explicitly; pseudonym only on request
Affiliation / company Confirm; some interviewees can name employer, others cannot
Photo Always opt-in, with credit
Contact links Twitter / X / personal site / GitHub — opt-in per link
Off-the-record Mark clearly during interview; never include even in paraphrased form
Sensitive content Pre-publish review; allow withdrawal of any specific quote

Get written consent for: real-name use, photo use, sensitive opinion attribution, employer mention. Tone: respectful and clear.

Footnotes for Technical Claims

Interviewees often state facts that need verification. The article should:

  • Include footnotes / inline links for any concrete claim (numbers, project history, public events).
  • Use a "[Editor's note: …]" insertion for clarifications, never silent edits.
  • Mark uncertain claims with [citation needed] until verified.

Workflow

  1. Receive raw material — transcript (Whisper / Otter / Rev), notes, recording.
  2. First-pass triage — identify the 5–8 most interesting moments, the through-line theme, and the unusable sections.
  3. Choose form — Q&A direct / narrative-with-quotes / roundtable.
  4. Re-sequence — best-first / theme-clustered / tension-arc / reverse-chrono.
  5. Trim answers — remove filler, consolidate redundancy, cut tangents.
  6. Rewrite questions — short, specific, spoken-clutter removed.
  7. Extract pull-quotes — 3–5 candidates.
  8. Write intro and outro — frame the conversation for the reader.
  9. Fact-check — verify dates, numbers, project history; add footnotes / links.
  10. Send draft for interviewee review — allow 3–5 line edits; protect against full rewrites.
  11. Publish with consent confirmations in place.
  12. Distribute — pull-quotes become atomic assets (see content-repurposing.md).

Output Template

interview_article:
  interviewee:
    name: "Real name (with consent)"
    role: "current role and affiliation (with consent)"
    links:
      - { type: x, url: "...", consent: yes }
      - { type: github, url: "...", consent: yes }
      - { type: site, url: "...", consent: no }  # not included
  form: q_and_a_direct
  through_line: "Why our most reliable service had no tests, and what we learned."
  re_sequence_strategy: best_first
  raw_word_count: 11_400
  published_word_count: 2_350
  intro_words: 180
  outro_words: 70
  sections:
    - id: S1
      heading: "The day production didn't break"
      questions:
        - q: "When did you first realize the no-test approach was actually working?"
          a_excerpt: "..."
          a_word_count: 280
    - id: S2
      heading: "..."
  pull_quotes:
    - text: "Tests are a constraint we add for our own benefit, not the system's."
      length_chars: 64
      placement: between_S1_and_S2
  fact_checks:
    - claim: "We ran without unit tests for 4 years"
      status: verified
      source: internal_postmortem_link
  consent:
    real_name: yes
    employer_mention: yes
    photo: no
    pre_publish_review_completed: yes
    interviewee_edits_applied: 3

Anti-Patterns

  • Publishing the raw transcript verbatim — disrespects the reader's time and the interviewee's actual ideas.
  • Heavy paraphrasing that loses voice — the published interview reads like the author talking, not the interviewee.
  • Cutting tangents that contained the most surprising moment because they were "off-topic".
  • Re-sequencing that changes meaning ("X, but only after Y" → "X").
  • Publishing without pre-publish review — interviewees lose trust permanently.
  • Pulling out-of-context quotes for shock value.
  • Using the interviewee's identity (name, employer) without explicit consent.
  • Skipping fact-checks on numerical claims because "they said it confidently".
  • No author intro — the reader has no entry point to the conversation.
  • Q&A format with bloated multi-clause questions — kills readability.
  • "Lightly edited for clarity" footer when edits were heavy — be honest about the level of editing.

Deliverable Contract

An interview article is complete when:

  • Through-line theme is articulated.
  • Form is chosen (Q&A direct / narrative-with-quotes / roundtable).
  • Raw word count and published word count documented.
  • Intro and outro present and within word budgets.
  • Pull-quotes extracted (3–5).
  • Fact-checks logged for all numerical / historical claims.
  • Pre-publish review completed and edits applied.
  • Consent confirmed for real name, employer, photo, and contact links.
  • Atomic-asset hand-off plan (see content-repurposing.md) drafted.

References

  • Errol Morris, A Wilderness of Error — methodology for interview-driven longform.
  • Claudia Dreifus, Talk: Conversations with the World's Most Interesting Writers — Q&A interview craft.
  • John Brockman, Edge.org interviews — structural conventions for expert-Q&A.
  • The Paris Review Art of Fiction / Art of Non-Fiction series — gold standard for narrative-with-quotes.
  • Niemen Storyboard — annotated journalism interview articles.
  • Sarah Koenig, Serial — sequencing interview material as narrative arc.
  • AP Stylebook, Quotations chapter — voice preservation and consent norms.
  • IRE (Investigative Reporters & Editors) — fact-checking and source-protection guidelines.
  • Reuters Handbook of Journalism — pre-publish review and accuracy standards.

Source: SKILL.md on GitHub

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