deep-interview

Extract tacit knowledge through an adaptive interview by running a guided questioning loop that surfaces core ideas with targeted questions, then incrementally writes responses into a structured knowledge base with topic folders and themed files.

Structure interview answers into a knowledge base by using real-time writing to automatically generate an _interview-index.md, create topic folders, and organize responses into themed files as the session progresses.

Control adaptive interview depth by selecting shallow, medium, or deep modes, which balances the breadth and depth of topic elicitation to match your specific knowledge extraction goals.

Adaptive interviews handle real-time synthesis by progressively deepening questions per theme and generating a final summary alongside a browsable knowledge base once the session concludes.

Yes, this structured interview approach works for any subject domain, applying its adaptive questioning loop to elicit topics, extract knowledge, and build theme-based files regardless of the input topic.

Limitations when building a knowledge base from elicited interview topics include reliance on the interviewee's responses for depth, as the adaptive questioning loop only progressively deepens questions based on the answers provided during the session.