Transcript Mining Engine
Concept
The core processing engine that treats transcripts as rich ore to be mined, not text to be summarized.
What to Extract
- Feature ideas (“wouldn’t it be cool if…”, “we could also…“)
- Project sparks (new tool concepts, standalone initiatives)
- Frameworks (mental models, principles, ways of thinking)
- Philosophies (team beliefs, working principles)
- Decisions (explicit choices made, direction set)
- Status updates (“X is now live”, “Y is on hold”)
- Action items (tasks assigned, next steps)
- Blockers (what is preventing progress)
Implicit Content Detection
Look beyond explicit statements:
- Ideas embedded in problem discussions (“the issue is we don’t have X” → X is an idea)
- Philosophies expressed as asides (“we always say…” → philosophy)
- Decisions made by NOT deciding (“let’s not wait for…” → decision)
Quality Bar
For a 1hr+ meeting, expect:
- 7+ feature idea notes
- 2+ framework notes
- Multiple philosophy additions
- Several project hub status updates
- 20+ files created or modified
If output is a “3-4 bullet point summary,” the mining failed.