AI and Automation for VC Platform Teams

Most VC platform teams are one person. At HV Capital, that person supports more than 150 portfolio companies. At Earlybird, platform sits inside a cross-functional team that also covers comms, events, and operations. Neither firm plans to hire to keep pace. So the question stops being how to adopt AI and starts being which parts of the job can run without the person in the middle.

This roundtable with Data Driven VC covers what three platform leaders have actually put into production. Anna built a knowledge base from portfolio conversations, then layered a skill on top that handles the architecture questions she used to answer by hand: comp policy, onboarding, performance management. A second skill takes a founder's bare list of job titles and returns competitor hiring patterns, market size, candidate archetypes, lead times, and a feasibility read she can take straight into the conversation. Earlybird is consolidating comms and portfolio content into a single source of truth so the team can surface patterns instead of re-deriving them each time.

Where the group disagrees is more interesting. Measurement is contested — one speaker argues against OKRs for platform work entirely, on the grounds that the value sits in crises that never surfaced. The buy versus build question gets a sharper answer than usual: buy reliable data at scale, build only where the firm holds context no vendor can assemble.