product-interviewer

Extract tacit product knowledge for AI agent onboarding by conducting a structured interview that prompts subject matter experts one question at a time and records their literal answers verbatim into a raw markdown log.

Creating RAG-ready product documentation from expert interviews involves a seven-axis structured elicitation process that captures verbatim responses and generates thematic markdown files organized by vision, architecture, features, and data.

Structure a domain knowledge capture interview by dividing the session into seven axes: vision, business domain, architecture, features, data, operation, and history, asking one to three focused questions per axis.

Yes, you can generate markdown context files directly from SME interview responses by logging literal answers during the session and then consolidating them into per-axis thematic files for downstream RAG-ready context.

Structured product knowledge extraction requires no external frameworks or dependencies, operating entirely through progressive, one-question-at-a-time prompting to ensure strict literal logging of expert responses.

When a product documentation interview leaves open questions, the structured elicitation process generates a dedicated list of open questions for follow-up alongside the verbatim raw interview log and thematic markdown files.