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Case study

The PM Intelligence Tool

An agent system every PM at the company now uses daily, and the discipline of deciding what not to automate.

Role
0→1 owner. Pitched it, scoped it, built it
Timeline
Self-initiated, from the data side
Team
Solo build
Outcomes

Nobody asked for this

This tool wasn't on a roadmap. From my seat on the data side, I watched customer intelligence scatter across Gong calls, Slack threads, Notion docs, and Intercom tickets, with no owner and no way to see it whole. Before writing a PRD, a PM reconstructed reality by hand, one search box at a time.

I pitched the build myself. Seeing the gap from the data side and turning it into a product is the founding-hire version of customer discovery.

The real cost

The hours were the visible cost. The invisible one was worse: PRDs were only as good as whichever fragments a PM happened to find. Decisions inherited the blind spots of a manual search across four tools.

The design decision that mattered

Automate end to end, so the agent writes the PRD

Passed

The tempting demo, and the wrong product. A PRD is a decision document; automating the decision removes the accountability that makes PMs trust it, and tools that replace judgment get quietly resisted.

Agents draft, PMs decide

Chosen

Agents own the grunt work of signal detection across the four sources, analysis, and a first PRD draft. The PM owns the judgment about what matters and what ships. The boundary is the product.

Why the boundary is the product

The hardest call wasn't technical. It was deciding what not to automate. Tools that eliminate grunt work get adopted; tools that replace judgment get resisted. Drawing the line at “draft, don't decide” is why adoption hit 100% instead of stalling at the demo.

What I built

Three agent roles working over Gong, Slack, Notion, and Intercom: signal detection surfaces what's changed and what customers keep hitting; analysis turns raw signal into patterns worth a PM's attention; PRD generation produces a first draft grounded in that evidence. The PM enters at the judgment step with the reconstruction already done.

Results

100%
of PMs use it daily, not just at launch
~60%
less customer-research time, as reported by the PMs using it
min
to a first PRD draft, down from hours

Adoption is observed; the time savings are self-reported by the PMs. I'd rather label the number honestly than dress it up as telemetry.

What I'd do differently

Instrument the tool itself from day one. A product whose pitch is “better signal” should measure its own, from research time to draft-acceptance rate to which sources actually drive decisions. The self-reported ~60% is believable, since the PMs vote with daily usage, but the builder of the semantic layer should hold his own tool to semantic-layer standards.