Premise VC investment thesis puts founder priority ahead of mega-fund scale

The Premise VC investment thesis is built around a blunt read on early-stage venture: Vanessa Larco says founders increasingly want investors for whom a seed check is a material commitment, not a side bet. Larco, a former New Enterprise Associates partner, co-founded Premise VC with Mercedes Bent in early 2025 to back technical founders at pre-seed and seed with checks ranging from $500,000 to $3 million.

Larco spent nearly eight years at NEA, where she served on the investment committee and led deals across enterprise software, developer tools and consumer technology. Her investments included Evident, Kindred, Cleo, Greenlight and Mejuri, and she was a board observer at Robinhood before its 2021 IPO.

In an interview with Crunchbase News, Larco said the math of multi-billion-dollar funds makes small checks harder to prioritize. A fund trying to put several billion dollars to work cannot build its model around $2 million commitments, she said, even if it still participates in those rounds.

Premise VC has not disclosed its fund size in the material reviewed. Its stated focus is narrower: early technical founders building software companies with high growth potential and enough durability to survive beyond the current AI funding cycle.

Why did Vanessa Larco start Premise VC?

Larco tied the launch partly to a change in founder behavior after the Silicon Valley Bank collapse. She told Crunchbase News that when companies were worried about making payroll, founders learned quickly where they ranked inside each investor’s portfolio.

That experience, according to Larco, made specialized early-stage funds more attractive, including to first-time founders. She said emerging managers have been winning competitive lead positions in pre-seed and seed rounds against larger firms, a shift she sees as a response to founders wanting more attention from investors with fewer conflicting priorities.

Larco said Premise interviewed its target founders before shaping the firm’s own offering, treating the fund like a startup whose product is capital plus support. The firm focuses on market assessment, product-market fit and team scaling, according to Crunchbase News.

How does Vanessa Larco evaluate AI startups?

Larco said Premise spends several days in concentrated diligence with founders, sometimes speaking with them one to three times a day while also running reference and back-channel checks. Because that process depends on trusted networks, she said many of the firm’s investments are in cities where the partners have strong reach, including San Francisco, New York and Atlanta.

Premise evaluates founders against seven internal attributes, Larco told Crunchbase News. She did not list all seven, but said the firm wants founders who are world-class in at least two of them. One trait she named is “urgently dissatisfied,” which she described as a high-standard, impatient operating style that can be difficult but is distinct from ego.

At pre-seed and seed, Larco said the original pitch is less predictive than the founder’s ability to find the right market and product over time. That view is practical: very early companies often change materially before they reach scale.

On AI, Larco’s filter is whether a product is meaningfully faster, cheaper or easier than what customers use now. She said a small discount is unlikely to move a market, while cutting a large manual task from hours to minutes, or turning an expensive service into a much cheaper software product, is more compelling.

Larco is not categorically against companies built on existing models or APIs. Her concern, she said, is whether founders understand the technical trade-offs well enough to shift work across open-source, closed and other models when cost or quality changes. She compared today’s criticism of AI wrappers to early skepticism of startups built on Amazon Web Services.

She also said she remains interested in consumer software and fintech despite broader investor pullbacks, arguing that AI is changing consumer behavior. For AI agents, Larco said users still tend to want help with research and filtering rather than fully delegated decisions with no visibility into the process.

This story draws on original reporting from Crunchbase News.