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Invitation only 15 seats Approval required
For founders of fast-growing Series A+ startups, with a limited number of investor seats.
Some of the investors in the room:
Merck Global Health Innovation Fund (GHI Fund)
Presidio Ventures (Sumitomo Corporation)
Morgan Stanley Ventures Lab
Description:
When AI compresses engineering cycles from months to days, the scarcest thing in a startup is no longer the ability to build.
It's knowing what to build, for whom, and how to win when everyone can ship.
That shift rewrites the founder's job. Moats move from code to data, distribution, and judgment. Team shapes change. Capital efficiency changes what "venture scale" even means.
The playbooks most of us learned are quietly going out of date, and the new ones are being written right now, by the people in rooms like this one.
The evening:
Dinner and conversation with a curated table of ~15 founders, operators, and investors. A handful of invited voices will anchor the discussion including heads of CVCs and later stage AI founders. This is a roundtable, not a panel: everyone at the table is expected to bring opinions.
What we'll get into:
What's newly easy, what's suddenly hard, and what that does to the first 18 months of a company
Where defensibility actually lives when software is cheap
How team composition and hiring change when one builder does the work of five
What the next generation of founder playbooks will look like
House rules:
Off the record. No slides, no pitches, no recording. Come with a point of view.
ORGANIZED BY
Elpis Labs
We work with the government sector and international trade agencies to help their startups find corporate partners in the U.S.
The Vertical
An online publication, community platform, and event series focusing on international venture ecosystem.
Trinovation Partners: The "Scale AI" of Venture Backed Startups
We are an AI data operations partner for venture-backed teams building computer vision and AI products. We build and run dedicated annotation pods: named, trained teams assigned to your product, not an anonymous crowd. Covering image and video annotation, gold-set calibration, human-in-the-loop QA, and edge-case review. Pods launch in 1-2 weeks, scale with your deployments, and deliver quality you can audit: 500+ annotators deployed, 95%+ QA accuracy, and a 30% model accuracy lift for our clients. Independent and New York-based.
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