Discovery isn't call stacking; it's a ranked deliberation. At Upcore we ran 20+ prospect interviews across 12 verticals, distilled them into an opportunity brief, and surfaced the top-3 agentic-AI use cases by severity, ROI, and buildability. The scoring frame is the deliverable, not the call logs.
An enterprise PM's superpower isn't the meeting you run; it's the decision stack you enforce. In discovery-heavy projects the meeting is almost the vacuous part — the discipline is in turning raw interviews into a honest committee.
The interview phase
- 20+ structured calls with would-be buyers across 12 verticals
- Each tracked: pain, budget signal, who "wins", priority phrasing
- Are interview notes signal-rich — each one lands as a claim, not a story
Synthesis out of interviews
- Severity — how sore is this pain?
- ROI — "would they pay to make it go away?"
- Buildability — can we ship this without rebuilding the factory?
The top-3 use cases by this triple are what a roadmap should be allowed to defend. Everything else is a tasteful "not yet."
What the brief said
- 20+ interviews produced a target pulse ("agentic AI for sees, order, dispatch")
- 12 verticals surfaced cross-functional flow, not a shadow play
- Top-3 opportunity brief survived, and both a pricing and an intel play leaned on it
The slides that survived
- One slide: pain, out, budget, buildability, for each of the top 3
- One ranking: "what we'd do 0-6 months"
- No "insight" deck with a hundred bullet points
What I'd do differently
- Run quant after qual. Interviews raised questions; a scorecard would verify them at 5x reach.
- Design the interview with scoring baked. Asking "how bad is this, 1-10" per pain earlier beats post-hoc coding.
For the mechanics I keep alive, the deep-dive method covers evidence; for the agentic side, how I build with agents is the same discipline.