VC as Software Workflow

This points to venture capital becoming a software workflow before it stays a people business. The job Kavin Stewart describes is not founders pitching robots, it is a firm that turns founder data, market research, internal notes, and network knowledge into a machine that can screen companies, draft memos, benchmark metrics, and route introductions with almost no manual analyst work. That fits Tribe Capital's long standing focus on structured company data and quantitative underwriting.

• The immediate bottleneck is data cleanup, not relationship replacement. Stewart says the hard part today is taking messy startup data, normalizing it across thousands of companies, and producing comparable underwriting reports. The zero employee idea only works if that back office gets automated first.
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• A useful comparison is Velvet, which sells AI software to funds that reads decks, emails, data rooms, and spreadsheets, then fills in CRM records and drafts investment memos. That shows where the market is already moving, toward fewer junior staff hours spent gathering facts and more time spent on selection and introductions.
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• The deeper implication is that a firm like Tribe Capital is trying to productize its edge. Tribe's broader history around Termina and growth accounting was built on standardizing startup data for apples to apples comparisons, so the endpoint is a fund where software handles the repeatable analysis and humans are only needed for judgment and trust, until even some of that gets abstracted away.
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The next step is not literally a firm with no partners, it is a firm where one partner can do the work that once needed a team of associates and analysts. If that model works, the winning venture firms will look more like compact software organizations with capital attached, and the advantage will shift to whoever best captures proprietary data, converts it into decisions, and plugs that into a high quality founder and LP network.