小蓝视频色情网页版

In early 2025, teamed up with to found , a firm focused on backing early-stage technical founders building durable, high-growth software.

Before that, Larco had spent nearly eight years as a partner at (NEA), one of the world’s largest venture capital firms.聽

There, she served on the firm’s investment committee and led investments across enterprise software, developer tools, and consumer technology, including , , , , and . She also served as a board observer at leading up to its 2021 IPO.聽

Known for her sharp product intuition and hands-on operational experience, Larco focuses heavily on helping founders evaluate market dynamics, navigate product-market fit and scale resilient teams.

Before transitioning to venture capital, she built a career as a product leader and founder. After earning a degree in computer science with honors from the , she began her career at working on and , before leading core product teams at companies like and . She also founded an app development startup that she successfully ran and sold before joining NEA.

小蓝视频色情网页版 News recently sat down with Larco to discuss how changing founder preferences and the (SVB) collapse drove her to launch a specialized pre-seed and seed fund designed to make early-stage founders a top priority.聽

Among other topics, we also discussed how she evaluates startups based on founder potential rather than initial ideas, looking for teams that leverage AI to make products dramatically faster, cheaper, or easier to use while avoiding rigid, single-model wrappers.

This interview has been edited for clarity and brevity.

小蓝视频色情网页版 News: You were at New Enterprise Associates for nearly a decade before branching out on your own. What led you to start your own firm? Was there a specific gap in the market, or was there a premise you felt couldn’t necessarily be fulfilled at a fund that size?聽

Larco: There were a lot of things. At a multi-billion-dollar fund, writing $2 million checks is never going to be a top priority. They invest across all stages, but when you have to deploy between $3 billion and $6 billion depending on how you look at it, it鈥檚 impossible to do that $2 million at a time with standard team sizes.

Even if you still write those checks, founders have gotten wiser to what it feels like when they are a top priority versus when they aren’t. One founder put it to me this way: 鈥淚 want my investor at every round to feel like the check size hurt 鈥� that it’s a big percentage of their fund 鈥� because that鈥檚 how I know I鈥檓 going to be a top priority when push comes to shove.鈥�

So, for a pre-seed round, they want a pre-seed fund where the check size hurts. For a seed round, they want a seed fund where the check size hurts. For a Series A, they want a mid-sized fund where the check size hurts.

That frank conversation put a lot into perspective. Founder preferences have shifted over the past few years. Emerging funds over the last three to four years are winning very competitive deals, securing lead slots against more established, bigger firms. This was virtually unheard of before.

How has that happened?

A side, unintended consequence of the SVB collapse was this change in founder preference. When SVB was going under, every single founder called everyone on their cap table saying, 鈥淚 can’t make payroll on Wednesday. Can you help me?鈥�

Every VC was getting dozens to hundreds of calls. Depending on portfolio size, you can’t help everybody or be on the phone with every single company. Everyone had to prioritize. If firms scraped together money to help cover payroll, they couldn’t cover everyone across the entire portfolio. Very quickly, founders got to see where they sat on the priority list.

That’s interesting. As I cover rounds lately, I鈥檝e noticed the lead investors aren’t as often the big mega-funds.

Not at pre-seed or seed.

Even Series A. You’re seeing less of it happening.

Part of it is that fund sizes got really big, so they are writing bigger checks, which inevitably leads to more calculated ROI risk and moving to later stages. Part of it is that founders want to be a top priority, and they saw what happens in a crisis.

Founders are on WhatsApp channels, hacker houses, and communities, so one bad story spreads faster than ever. It used to be just repeat founders who wanted specialized, focused firms at the earliest stage for signaling risk and other reasons. Now, even first-time founders hear those stories and want a specialized investor.

When customer preferences change in any market, you realize there’s an opportunity. We asked ourselves: 鈥淐an we capitalize on this shift? If you were to build something from the ground up targeting this specific ICP, what would you build?鈥�

We did what we tell our founders to do: a listening tour. We interviewed people in our ICP and asked: What do you wish you had? What works, what doesn’t, what taglines are you skeptical of, and what is tangibly helpful? We doubled down on what we could provide well and cut out things people assume are best practices that founders don’t actually value.

We think of Premise as a startup, and our product happens to be a fund, so it still has to be something people want.

Do you invest strictly at those very early stages, or across other stages?

Strictly pre-seed and seed. Check sizes range from $500,000 to $3 million.

It鈥檚 noisy out there. How are you able to cut through that noise to identify real potential versus people riding the AI bandwagon? As a journalist, I struggle with that, so I imagine investors do, too.

We spend a lot of time with founders before backing them. During diligence, we talk one to three times a day for three to five days, alongside extensive reference and back-channel checks. Because of that, most of our investments are in cities where we have strong networks, like SF, New York, and Atlanta.

We try to get a deep sense of who the person is, what motivates them, and what key attributes they possess. Mercedes and I looked across all the best founders we saw at our previous firms and identified seven core attributes. There isn’t one single persona; founders have different strengths and weaknesses. We look for founders who are world-class in at least two of those seven attributes. In our investment memos, we justify those choices with anecdotes and reference feedback. Nobody is the best at all seven 鈥� some attributes even contradict each other.

At the pre-seed and seed stages, whatever idea you pitch 鈥� while we want it to be a good idea because it shows your ability to plan and generate ideas 鈥� the likelihood that it’s what the company looks like in five to ten years is very slim. A lot of it is gauging the potential of the person to find the right market and product fit to build an iconic company.

It is tough, but it’s not that different from the crypto, Web3, or early AI waves. Tailwinds always attract fair-weather founders. The core tactics to figure out who really wants to build something interesting, who has unique insight, and who is tenacious enough to endure the ups and downs haven’t changed in the last decade.

I’ve seen you discuss AI as a concierge service, shifting from “do-it-yourself” tools to “do-it-for-me” agents. You’ve also mentioned that an AI agent shouldn’t just be a wrapper; it needs to significantly re-architect the cost structure. When looking at a seed-stage deck today, what stands out as evidence that a team actually knows how to fundamentally change that cost structure?

Those can actually be two separate things. If a traditional wedding planning concierge service costs $20,000, and you offer it for $1,000, you’ve blown the cost structure out of the water 鈥� even if you’re just a wrapper using $100 in API credits. You can be a wrapper, pay for APIs, and still charge a fraction of traditional costs because the legacy price anchor is so high.

What I look for in any company to be competitive is whether it is faster, cheaper, or easier than existing options. A 10% discount isn’t enough, but at 50% off, people will switch. If a tool reduces a weekly five-hour administrative task to five minutes, sign me up. The bar now is enabling people to do things they couldn’t do before or lacked the confidence to do. For instance, I can build a cap table in Excel, but it takes me forever. If a tool makes that effortless, I’m in.

So ideally, a startup delivers on at least two of those three pillars: faster, cheaper, or easier.

I’m not against wrappers, but founders must understand the underlying mechanics. If you scale and the wrapper gets too expensive, or the model degrades, you need to know how to split tasks across open-source, closed, Google, or other models to deliver the best product at the best price.

Technical founders obsessively optimize models for specific features across their product. Less technical founders often use a single model for everything, which doesn’t guarantee the best price or performance. My hesitation with wrappers isn’t that a team launched quickly; it’s when they don’t know how to continue innovating because they’re wedded to a single model.

The counter-argument to my own point is (AWS). When AWS came out, critics said, 鈥淎nyone can start a company over a weekend on AWS; it’s not defensible, there’s no moat, you don’t own servers.鈥澛�

Yet many great companies were built on it. It鈥檚 the same argument. People said the same things about the cloud and mobile waves 鈥� that mobile was a toy and no one would buy a $1,000 phone or pay for subscriptions. Looking back, those criticisms sound funny.

You mentioned you look for seven distinct founder attributes, and that a founder needs to be world-class in at least two or three. Without giving away the whole secret sauce, what is one attribute on that list that would surprise people?

The one that catches people off guard is what we call 鈥渦rgently dissatisfied.鈥� These founders can come across as disagreeable: they’re more focused on the goal than on making people feel good, and their standards can be genuinely difficult to work around.聽

But the people who’ve worked with them tend to say the same thing: that the founder pushed me to accomplish things I didn’t think were possible. This shouldn鈥檛 be confused with ego. It’s about managing hustler, relentless energy and pointing it at the right problems. The best founders I’ve backed have this quality. They have a high bar for themselves and their teams 鈥� as in everything should have been done yesterday, and they should have acted accordingly.

On the flip side, given how fast the tech landscape is shifting right now, is there an attribute that used to be a ‘must-have’ for a Series A founder five years ago that you now consider a nice-to-have at the seed stage?

The attributes themselves are pretty universal truths about what makes a great founder. What’s changed is the intensity and pace at which they have to show up. Five years ago, shipping an exceptional product, not just features, every six to twelve months was the bar. Now it’s every three to four months.聽

So being a decisive execution machine still matters enormously, but what we’re evaluating is whether a founder can operate at this new compressed pace without sacrificing quality. That’s a harder thing to assess early, but it’s become one of the most important signals.

Right now, a huge portion of the VC ecosystem has completely retreated from consumer tech to chase B2B enterprise AI. Are you still actively looking at consumer behavior change as an investor? Do you think the rest of the market is miscalculating the size of the consumer AI market, and if so, why?

I think the retreat is short-sighted. Consumer software has historically produced some of the most important companies ever built, and it doesn’t make sense to vacate that entirely because the sector has been in a lull the past few years.聽

The first principles of what makes a disruptive consumer company are exciting again because consumer behavior is rapidly changing with AI. We price in that risk. Fintech is another space where I’ve seen a meaningful pullback, and we’re still active there for the same reason. If everyone is running from a category, that’s usually worth paying attention to in case new tailwinds emerge.

You spent years as a product leader at places like and . We鈥檙e hearing a lot of talk about how AI will automate the tedious parts of product management 鈥� writing tickets, reviewing specs, tracking bugs. If AI absorbs the execution workload of a PM, what does a top product leader actually do day-to-day in 2026?

The job of a PM has always been consumer empathy: understanding what someone is trying to accomplish and why, and then making sure the product actually gets them there.聽

AI only changes the artifacts you produce. A few years ago, you were writing specs. Now the best PMs I talk to are writing evals to define what 鈥済reat鈥� looks like for the agents they’re building and testing whether the agents actually deliver it.聽

Someone somewhere still has to care deeply about the end user, ask the hard questions about what success means, and hold the bar. That’s still a human job.聽

I love the analogy that AI wrappers are just the new AWS. But with AWS, the 鈥渕oat鈥� eventually became workflow stickiness and data accumulation. In a world where technical founders are constantly swapping models to optimize cost and performance, what does a 鈥渕oat鈥� actually look like for an early-stage company? If it’s not the underlying model, then what is it?聽

I think it鈥檚 still workflows and data accumulation. I don鈥檛 think the moats changed much. The real question is how you retain your customers when competitors can clone you in three days. There are small non-durable moats you can lean on before you build out the data/workflows/network effects/integrations/etc moats.聽

You made an interesting distinction between how technical and non-technical founders approach model selection. Given that, are you leaning heavily toward funding purely technical, AI-native architectures right now, or can a world-class product-and-distribution founder still win you over if they hire the right engineering talent?聽

Never say never, but I am heavily biased towards a founder or founding team that has exceptional AI talent. I find that these folks enjoy being at the cutting edge, staying up to speed on the latest breakthroughs, and don鈥檛 mind blowing up their roadmap to move fast on a new functionality that enables them to build better products for their customers.聽

You talked about AI shifting from ‘Do It Yourself’ to ‘Do It For Me,’ like giving everyone a concierge wedding planner or a financial analyst. When an agent moves from just giving advice to actually executing transactions and making decisions on behalf of a user, what is the biggest hurdle you see startups face? Is it a trust problem with the user, or is it an execution infrastructure problem?

Few people want 鈥淒o it entirely for me, and I have no idea what you did or how you did it鈥� right now. Most concierge services do the research, ask you questions to personalize the recommendations, and then filter down the options they present. If you have questions, you can dig into their reasoning, what they ruled out, etc. If you don鈥檛 like the options, they can go and find a new set. Rarely do wedding planners, travel agents, etc just go off and book everything for you without your input. I think that鈥檚 where we are with agents. It鈥檚 not just a trust problem, but more that people still want to make the decisions themselves 鈥� just not do all the research.聽

Related 小蓝视频色情网页版 query:

Illustration: