Work
Specific examples and outcomes.
Vibe Capital: Building a fund from scratch
The situation
Building a deep tech and AI infrastructure fund 18 months before ChatGPT launched, when most LPs weren't interested in the thesis.
What I did
- Developed the thesis: conviction before consensus. Back founders who manipulate matter, bend energy, or rewrite biology.
- Sourced and underwrote 40+ investments across AI infrastructure, advanced manufacturing, biotech, and space.
- Portfolio markups at 24x and 12x on positions that haven't exited. Co-investors on various deals include Sam Altman, Alex Wang, and operators from Meta and Scale AI.
- Hands-on strategic work with founders through high-stakes decisions - operational focus, capitalization structure, when to hold and when to move. The kind of calls where five investors give five different answers and only one is right.
A real portfolio with real markups, built on a thesis that's now consensus.
Example: Pipedream
2021 pre-seed on underground autonomous delivery networks when most people thought it was science fiction. Built conviction around the constraint: last-mile delivery economics break if you can eliminate surface traffic and weather. Worked closely on strategy as they moved from concept to real infrastructure, and helped position the company to land anchor tenants representing tens of billions in network demand.
First node launching in Austin with sub-2-minute fulfillment from underground RFC to surface portals. Next: 125+ mile DFW network.
Example: Shapes
2021 investment in AI companions - over a year before ChatGPT launched. Cold inbound from founders, stayed in contact, invested when AI friends sounded like a toy. Lightspeed led the seed round.
Facebook | 2007–2017
What I did
Product operations for Search, from Graph Search launch through 2B daily queries. Cross-functional coordination across engineering, legal, PR, and safety. Employee #180.
How I work
Messy, high-stakes questions - "Is this real or nonsense?" and "What would it take to get there without lying to ourselves?"
What you get back: a map of the system, the constraints that matter, and a sequence of moves.