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VC: Former NEA Partner Starts New Fund, Runs it Like a Startup (Memos, KPIs, R&D)

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You can also watch/listen to the entire episode on X.

Who you’ll learn from

Vanessa Larco spent nearly a decade as a Partner at NEA. Then she walked away to start a fund built on one bet: the companies OpenAI won’t kill.

OpenAI deprecated Sora and quietly killed checkout inside ChatGPT within months of launching them. Not everything the frontier labs touch wins, which leaves far more room for startups than the doom narrative suggests. Vanessa invests in the teams that live in that gap: founders who out-ship everyone chasing them long enough to build the durable moats underneath.

At NEA, she backed Robinhood through its 2021 IPO and led the firm’s investment in Greenlight, with board seats spanning Mejuri, Assembled, and Cleo. Before venture she was a product leader at Box, Microsoft, and Twilio, and a founder who raised and sold her own startup. She’s now co-founder of Premise, a new fund backing technical founding teams building the next category-defining companies.

Discussed in this episode

  • The “OpenAI won’t kill it” framework for spotting durable AI companies (and why not everything OpenAI ships actually wins)

  • Why the “it’s just a wrapper” dismissal cost VCs real deals, and the kayak/AWS parallels that explain why

  • Why Premise only backs technical founding teams, and the shipping speed that becomes the real early moat

  • How the old go-to-market playbook is breaking, especially in DevTools, and what replaces it

  • Why someone on the founding team has to “nerd out” on distribution, and why no-playbook moments are where you growth hack

  • How to run a conviction-based investment committee, and why big funds drift toward consensus whether they like it or not

  • Why running a fund is just running a startup: fundraising, product, and customer success by another name

  • The unanswered question Vanessa keeps circling: how to give experienced GTM talent space to rewrite the playbook

Episode Highlights

1:51 – Technical vs. non-technical AI founders

4:37 – The bottleneck of hiring AI talent

5:15 – Do old moats still exist?

6:36 – Cloud era lessons vs. today’s AI layer

9:18 – The shift to the distribution era

11:38 – Interview: Vanessa Larco (Premise VC)

12:40 – Companies OpenAI won’t kill

13:37 – Consumer habits vs. enterprise AI

15:05 – Moving beyond the “wrapper” stigma

17:39 – Thesis building vs. founder curiosities

20:11 – Sourcing & the “Surreal” community

22:26 – Learnings from NEA & Lightspeed

24:06 – Rethinking the investment memo

26:43 – Consensus vs. conviction investing

31:26 – Running a VC fund like a startup

35:04 – Building internal automation tools

37:35 – Distribution moats & DevTools

39:38 – Sourcing new GTM playbooks

41:12 – Parallel to the AWS boom

43:55 – Human psychology vs. AI tools

47:06 – SF’s best cookie spots

Thank you to our sponsor partner: AngelList

GTMfund’s LP base spans from individual operators to institutional allocators, and AngelList has been instrumental in supporting all of them. They handle everything from investor onboarding and accreditation to distribution and tax documentation, creating a seamless experience across geographies and fund types. Plus, all of this is available on a single, modern platform.

For an LP-base like ours, with over 350 C-suite and VP-level operators, this kind of white glove service and seamless workflows is so important. It’s also instrumental that we support our institutional LPs that we’re fortunate to work with, and AngelList is able to do so every step of the way.

If you’re looking for a platform that can support any type of LP investing in your fund, learn more at www.angellist.com/gtmfund.

Key takeaways

1. “Companies OpenAI won’t kill” is less contrarian than it sounds.
The fear that OpenAI will build and crush everything is fading. In the last few months they deprecated Sora and quietly killed checkout inside ChatGPT after the partnerships turned out harder than expected. Not everything they ship wins. That leaves a lot more room for startups than most people assume.

2. Product velocity is the only edge that matters early.
If you built it in a month, someone will copy it in a month. Vanessa isn’t betting on the feature, she’s betting the team can keep shipping better and faster than everyone chasing them. Perplexity and 11Labs won because they out-shipped the field. The old moats still apply, network effects, proprietary data, integrations, change management, they just take time to build, and your job is to stay ahead until they do.

3. Only back technical founding teams.
At least one co-founder has to be highly technical and accomplished. Those are the people staying current on the latest AI frameworks and rewiring the roadmap the moment new capabilities ship. Teams without a strong technical founder lag on exactly the thing you can’t afford to lag on.

4. Distribution is where the new playbooks get written.
The old go-to-market motion is breaking, especially in dev tools. “Launch a video on X/Twitter and go viral” is not the only way, and CMOs hired off the old playbook often don’t know the new one. Someone on the founding team has to nerd out on distribution the way the technical founder nerds out on the product. When there’s no playbook yet, you can growth hack your way to a breakout. Once there’s a playbook, you just spend your way there.

5. A two-person fund is a startup.
Vanessa and her co-founder Mercedes built Premise as a company. The product IS the fund. Fundraising is fundraising, deploying is shipping features, portfolio support is customer success. They run KPIs, treat management fees as an R&D budget, and are mapping CAC to LTV. Both are former founders, and they say they wouldn’t have partnered with anyone who wasn’t.

6. Conviction gets harder as the room gets bigger.
Every fund wants to be conviction-based, but put 20 people around a table and humans drift to consensus. When the most senior partner says “I don’t get it,” conviction is hard to hold, especially when your career sits with those same people. The fix isn’t agreeing on every deal, it’s agreeing on the process and how you grade it, then disagree and commit.

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