Managing Partner at Y Combinator
Check size: YC's live standard deal is $500K per accepted company: $125K on a post-money SAFE for 7% plus $375K on an uncapped MFN SAFE, with a participation right. This is YC's standardized program deal, not Diana's personal check range.
Diana works with technical founders building frontier AI, robotics and hard technology. Her Escher Reality and Niantic experience combines zero-to-one infrastructure with deployment at consumer scale, producing a lens that looks for a real engineering unlock, a specific high-value workflow, fast technical iteration and a product path that turns research capability into something users can adopt.
Apply through YC and lead with a working demo. Explain the technical insight, why it became possible now, target workflow and user, performance versus alternatives, data and systems architecture, reliability, iteration speed, early usage and the founders' unique ability to build it. For robotics or hardware, include deployment cycles, unit cost and field learning.
Deeply technical founders, a genuine engineering unlock, demos that work, ambitious markets, proprietary systems insight, rapid iteration, vertical AI tied to a valuable workflow, hardware-software co-design, strong user contact and a credible route from prototype to reliable deployment.
No exhaustive personal pass list is published. Her public focus implies weak fit for generic AI wrappers, impressive research without a user, hard-tech roadmaps with no iteration path, teams unable to explain their technical edge and products that ignore deployment reliability, data, hardware constraints or customer workflow.
Identify the technical result newly possible, the prior limiting constraint and measured performance that changes product feasibility.
Move from demo to field use through reliability, data collection, user feedback, cost, safety and iteration cadence.
Map the full expert workflow, required tools and data, human approval points and economic value an agent can own end to end.
Explain complex systems simply enough to show what is novel, defensible and useful without hiding behind jargon.
Diana's combination of founder experience, scaled AR deployment and deep ML expertise underpins her work with frontier AI, robotics and hard-tech founders.
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