BD

**Cross-turn reasoning, rendered live. Both sides leave with something.** Lacunex runs goal-directed adaptive interviews where structured insight is produced *during* the conversation, not in an overnight report. A Host (subject-matter expert) defines objectives; the platform conducts every turn live, surfaces cross-turn observations the moment they cohere, and at session close hands the participant a reflective takeaway worth keeping. Built by a systems analyst, ten years in. Lacunex closes two gaps real-world interviewing never closes: beginners — analysts, PMs, anyone for whom interviewing is *part* of the job — don't yet know how to run a round well; experienced researchers do, but lack the time to interview enough people for long enough. A four-call Opus 4.7 architecture runs every turn: - **Conductor** — decides the next move from session state and renders the interviewer's turn. - **Meta-Noticing** — observation-only; spots contradictions, hedging, and implied-not-said across turns. Every notice must cite ≥2 distinct transcript anchors (enforced in code, not just in prompt). - **Extraction** (Haiku 4.5) — schema-bound; fills the host's live insight dashboard turn-by-turn. - **Takeaway Synthesis** — a reflective artifact for the participant, including a "what you already have that is relevant" section. Mapped against Anthropic's *Building Effective Agents* (Schluntz & Zhang, Dec 2024): **three of the five patterns layer on a single turn — Orchestrator-Workers, Parallelization, Routing.** Three domain briefs ship — **Founder Investment Evaluation**, **Post-Incident Witness**, **Civic Consultation** — plus **Brief Designer**, where the platform interviews the host to author a *new* brief using the same four calls. Recursive dog-food. **Audiences exercised during build:** VC and angel investors evaluating founders; city officials running civic consultations; SREs, safety officers and clinical QI managers conducting post-incident interviews; clinicians eliciting patient values; tacit-knowledge capture from retiring experts; consumer-insights teams; qualitative researchers; managers preparing for high-stakes conversations. Empirical scale, on a **simulated 11-resident cohort** run against the Civic Consultation brief on the real platform: **303 turns, 54 deployed `◆` cross-turn observations from 243 considered, 12 cohort patterns, 6 routing recommendations.** Cost with prompt caching: **~$1–2 per session**, under $5 for the cross-cohort aggregate — putting a 100-resident consultation at ~$150 end-to-end. **Not an overnight research moderator** (Outset, Listen Labs, Strella ship next-day reports). **Not a transcript analyser** (Dovetail, Condens ingest transcripts that already exist). **Not "Claude with a long system prompt"** — a single chatbot can't enforce cross-turn reasoning the way four calls with code-enforced turn anchors can.