USV’s New $900M Fund: Fred Wilson, Rebecca Kaden & Mike Mignano

We raised $900M in new funds for USV, which is by far the most USV has ever raised in a new fund cycle.

I don't think $1 trillion is what we need to underwrite to at USV. I think if our biggest winners are in the single-digit billions, given our fund size and our ownership, we can produce really, really healthy returns for our partners.

You know, there have been some outliers at $50 billion or $100 billion, but a lot of our biggest winners are in the $10 billion range, and that's produced enormous returns for us.

It's also a bigger number than we've raised before, somewhat significantly, and marks a new strategy for us. The market has evolved; the outcomes are bigger, the swings are bigger. I was a little surprised how many of them said, "Are you seriously raising?"

We are here at Union Square Ventures, USV, in New York City with Mike Mignano, and we're about to go on a bit of an office tour. After that, there's more. We're going to do a sit-down with Fred Wilson, Rebecca Kaden, and Mike to go over what we're about to announce.

We just raised a new fund. We raised $900M in new funds for USV, which is, I would say, by far the most USV has ever raised in a new fund cycle, but there's a reason for that, and I think we will get into that in a little bit.

So why not $1 billion?

Oh, well, you know, we're— I would say with USV, we have always been extremely intentional about fund strategy. Not just fund size, but fund composition, how many companies, roughly what size checks do we plan to write, stages, number of companies.

And so the $900M really comes from that strategy and that model. We don't raise funds as vanity metrics. You know, it's not like, "We got to hit $1 billion," or, "We got to hit $2 billion."

I want to be a unicorn fund.

The $900M really comes from the strategy, bottoms up, which, again, I think we'll probably get into,right?

Yeah. Okay, so maybe we can do what you do best, and we can walk backwards to hide all the equipment.

Okay.

And then we can pick it up around the corner.

Sure, let's do it.

Allright, so we are here at Union Square. We're going to walk into the kitchen. These are some main areas. It's very active today.

Lots of people here today. Yeah, this is, I don't know, a bit of a seating living room area. Obviously, we've got the kitchen. My favorite feature of this kitchen is this Xbloom pour-over machine. Have you seen this thing?

No, what is this?

It's basically a pour-over robot. So if you like pour-over coffee, this is a robot that makes that for you.

Is this an investment?

I don't know. I don't know.

Okay.

But it's really cool. I've seen these in a few offices, a couple startup offices, a couple VC offices. So it's not like USV is the only place that has this, but if you like coffee, it's pretty good.

That's cool. I've never seen that.

Yeah, we've got our little bit of a dining room table here. We've got a board, one of our portfolio companies, Board. Do you know Board?

No, what is this?

Board is the world's first tabletop gaming console.

Oh.

Founded by Bryn Putnam, who founded Mirror.

Oh, yeah.

This is an amazing product. Every game comes with its own set of pieces, unique pieces.

Oh, cool.

That the screen reacts to. And they also have a platform to make it really, really easy for developers to build games for this. It's really— it's an awesome product that we definitely recommend.

Do you play chess on this?

They don't have chess.

They don't? Okay.

They have all their own games.

Yeah, you got to make it square.

Games that developers are...right. Well, I guess you could do chess where you sort of, like, shave off the edges and stuff.

Smaller. Yeah.

Or something.

Okay.

But it's awesome. Highly recommend. This is what we call the pit.

The pit.

So the pit is where we all work and we all hang out. This is my desk. It's very cluttered. I hope you don't get a shot of it.

Hopefully there's nothing bad on the screen.

We talk about deals.

No bubbles.

We talk about whatever might be going on on X that day. There's also a group chat for the pit. So the conversation that happens here very actively every day just continuesright when we leave here.

So no one has an office, or are they?

No, no one has an office, except— well, actually, Tierney and Carrie and Christine have offices.

This is special ops.

Because they don't want to deal with the madness of the pit, which I don't blame them. This is where a lot of board meetings happen, some of our full partnership meetings. We also have another room in here that we use for these types of meetings.

One of my favorite things about this office is pretty much every room has really epic views.

Yeah.

So you've got great views all the way to the Hudson River over here. You've got views uptown over here. There's a really, really cool view from here where you can see straight up Park Avenue, which I really love.

Actually, at my desk in the pit, if I turn to my left, it's literally like a perfect vertical view of Park Ave, which I think is really cool.

Yeah, it's...

I mean, this represents New York pretty well, if you can see all of it, if you're coming as a founder from, I don't know.

Totally. And I'll take you up to the roof in a minute, where we have literally like 360 panoramic views of pretty much all of Manhattan, which is really cool.

So you guys have invested in 263 companies?

That number soundsright, yes.

Okay. And how many do you expect to invest in with this fund?

You know, I think we try not to be too strict and specific about the number, but I think generally speaking, you know, probably somewhere 30-ish, maybe 30 to 40, a mixture of both seeds and A's. I think we'll do probably a lot more seeds than we've typically done in the past.

And, you know, we can get into a little bit of the fund strategy later with Rebecca and Fred, but, you know, going earlier, we believe, is becoming more and more important, just given how many startups are emerging as a result of AI and how competitive the market is.

Yeah.

Yeah, this is the library. So this room is great. It's beautiful. And we use this for a variety of reasons. We host events here with our founders and different people within the community. As you can see, we also have these desks here where we often host portfolio companies or companies that aren't in the portfolio that need a place to work.

It also actually is a library and has lots of books on the shelf here that many of us have read.

Do you have a favorite?

Let's see. Do I have a favorite? You know, one of my favorites is The Messy Middle. Shout out USV product advisory partner Scott Belsky. This is his book. This is about sort of the middle of the startup journey.

There are many books written about the early days and the formations. There's also obviously lots of books written about the success stories, what happens at the end. But I believe Scott's vision with The Messy Middle was really about what happens in the middle, which is the hardest part, as most startups are not straight lines.

So that's a great book. Let's see, what else? Shoe Dogs, obviously a classic. I mean, there are a lot of good books on this bookshelf, so.

Well, speaking to your point of going earlier with this fund, you guys are also incubating companies. You just released one that you incubated yourself, Supertake.

Yes. Yeah, so, you know, one of the things I'm sure we'll talk about is it's getting easier and easier to build products and get them to market quickly and test them quickly. One of the things that we've been talking as a partnership for a long time now is this idea that it's never been easier as a result of AI for people to take control of their own financial independence,right?

We're coming out of a world in which, you know, huge, huge companies and a huge market has been built on paying people for financial expertise and financial services. With Supertake, we believe that regular consumers should be able just to invest in their ideas without having to know anything about the stock market, anything about picking stocks or building a portfolio or what it means to rebalance or actively manage a portfolio.

And so with Supertake, it literally does all that for you through an agent. You just give it an idea or a belief you have in the world, and Supertake will go and invest in that idea directly through your Robinhood or Coinbase accounts or brokerages, and then it will actively manage it for you.

So it will tell you how it's doing. It'll check the news for you regularly. If something's broken in the portfolio, it'll automatically rebalance it for you. And it really speaks to the types of companies that we look for in the theme of obliterate, don't automate, which, you know, we can talk about when we talk about our theses.

We just think that AI companies are not only making it easier and faster to achieve existing processes in the market, but literally restructuring markets completely because humans now have access to intelligence and expertise that previously they had to pay a lot of money for.

So Supertake is a great example of that and something that we were able to, at least for the initial product, just build ourselves.

That's awesome. Did you build it in this room?

We did not build it in this room. We built it in lots of other rooms, though.

So if it's becoming so much easier to start companies and you can do it with just one person, why do we need venture capital?

So, I mean, it's still expensive for a startup to operate and scale a business. Obviously, things like inference are becoming more and more of a line item for startups,right? Great products are getting built, but to subsidize those products and make sure that customers can actually use them, maybe without having to pay themselves at first, more and more startups are subsidizing inference on behalf of customers.

The other thing I would say is, as it is becoming easier and easier to start a company, there are so many more companies, and therefore it's probably harder than ever to actually stand out and break out from the pack.

And so, you know, we're seeing startups getting more and more aggressive about their go-to-market and about their marketing strategies and making sure that they can really break through the noise. And so I think startups are always going to be expensive to maintain, to operate, to build, to break out.

It's just building the actual product, I would say, is arguably easier than ever before.

So we just walked through the entire floor. This is like the main floor,right?

Yeah. Yeah, this is the main floor.

What are your favorite parts about this office? You've worked at different offices not too far away.

Yes.

So what's your favorite, like, vibe about this space?

I'd say, like, one of the things I really love about the USV office is there are lots of different vibes in the office,right? You come in, it's very comfortable, it's very homey, obviously, like beautiful furniture and chairs and couches.

And then as you get further in, it's more of like a co-working space. Obviously, people working, talking. As you go in the back, you have a little bit more of like an introspective place in the library. You can get some quiet.

And then, as we'll see in a bit, the roof offers a whole different element. So, you know, whereas I feel like most New York City offices, especially small offices, it just feels like you're in a room.

Right.

There really are, like, actual different.

Thank God.

Personalities to this office.

Light here, yeah.

And we have light. Yeah. Pretty much, like I said from earlier, pretty much every corner of this office gives you a different view of New York City, which I think is really cool because it's my favorite city.

Do you have a good window cleaner? What's the...

It's a good question. I'm not sure who cleans the windows, but they clearly do a great job.

We've made it to the rooftop. What goes on up here?

This is just a really great place to work when the weather's nice. We'll come up here. You know, I'll take some calls. People do lunch up here. We also, you know, occasionally have different get-togethers and, you know, meetups with founders.

There's a party that we often do here every fall that people really like. And, you know, much like downstairs, as I mentioned, the nice thing about being upstairs on the roof is you have an amazing view from pretty much everywhere.

I mean,right through this archway here, again, you can see a perfect view straight up Park Avenue, which I think is incredible. You can see the Empire State Building. If you walk over this way, you can see all the way across the Hudson River to New Jersey.

Also, on really nice days, the sunsets on this side of the roof are really spectacular. So it's a great roof. It's a great feature of the office, and it's something that I think we all really appreciate.

We're experiencing some good fall weather today. Okay. What is your hottest takeright now?

My hottest take? I would say the user interface is not going away. I think one of the things we're seeing all over X, people love to say that the user interface is dead. Everything is being collapsed and folded into a chatbot.

I don't believe that to be true. I think the user interface is where people build trust with a product, where they gain comfort and know how to navigate different experiences. I think that the user interface is how products convey different concepts and ideas visually.

And I have a hard time imagining that we're just going to be delegating all of our computing away to agents. Yes, I think agents will do many things for us, especially the things we don't want to do. They might go shopping for us.

They might file our taxes for us, but they're not going to watch Netflix for us. They're not going to watch YouTube for us. They might not even scroll X or Instagram for us,right? I think we're going to want to do those things.

And so I have a hard time imagining that the user interface is just going to turn into a chatbot everywhere.

Okay. Pretty good hot take.

Thanks.

Allright, so next we're going to go and do a sit-down with Fred, Rebecca, and Mike. So stay tuned. Okay. Do I start with USV? Welcome to Sourcery.

Thank you.

Thanks for having us.

Thanks for having us, Molly.

So we have Fred, Rebecca, Mike. How are you guys doing?

We're great. Yeah.

We're doing great.

Feeling really good.

Allright, so we have a huge announcement we need to discuss. Who wants to take it away?

I think you should take it.

Allright. Yeah, well, we're excited. We closed our most recent set of funds, raised $900M. You know, in many ways, it's a continuation of what USV has now been doing for many decades of, you know, thesis-driven, great partnership with founders, backing businesses that we think are going to be leaders of their markets over the next decade.

But it's also a bigger number than we've raised before, somewhat significantly, and marks a new strategy for us. The market has evolved. We think the outcomes are bigger, the swings are bigger. The opportunity to leverage the new technology in the market and the applications that will be built on top is super, super significant, and the rounds are bigger and more expensive and faster.

And we are evolving our strategy to keep up with that and really be able to attack that market. Amazing. So maybe we go back to the 2004 LP letter. So what were you talking about then, and how is it different today?

Well, that was

early on in the internet era. Commercial internet had arrived in '95, and by 2003, a lot of the underlying infrastructure had been built. Not very different from where we are with AI. You know, a lot of the AI infrastructure has been built, but we're still waiting to see what the big applications will be,right, that will get built on top of it.

And that's where we were in 2003. The infrastructure was there. We had Google, we had Amazon, we had Yahoo, we had eBay, but we didn't yet have Facebook. We didn't yet have Twitter. We didn't yet have YouTube. We didn't yet have iPhone.

And so we imagined that there were going to be all these new applications that would be built on top of what we now think of as the web. And I think the moment we're inright now reminds me a lot of that, except now it's AI.

Couldn't agree more. I think we feel like Fred said, you know, the AI infrastructure has been built. Obviously, it's still getting built. There's going to be more and more opportunity, but we're at this moment where we're starting to see the beginnings of what feels like an explosion of the application layer of AI.

Obviously, there are products that we've all now been using for the past couple of years, like, you know, Granola and Suno and things like that. But, you know, just over these past weeks, obviously, everyone's been talking about a whole new type of application layer with Instinct and Muse and Grokbot.

And so it feels like we're entering a new phase where agents will be powering a lot of new experiences, both for enterprises and consumers. And that's really, really exciting for us.

So I'm curious, how do you justify the round size increases if models are, if it's preferred now to go to open source and it's cheaper? Like, where does all that capital go to?

Yeah, I think, you know, something we talk about often is how it is getting dramatically easier to build a product. You know, we recently announced that we incubated a product that we built very, very quickly and very, very cheaply.

And lots of other builders are doing the same thing. But what that means is that there are so many more startups that you have to stand out from and break through the noise from. And so, you know, one area that a lot of the capital is going is doing just that, breaking out, you know, marketing, messaging, positioning.

I think we're seeing a lot more investment, especially in consumer for startups trying to break through the noise.

We're excited about open source models, and we see the trend moving in that direction. And there's kind of a lot of promise there. If you look at the fundamental costs that companies are spending on compute, it's in a totally different hemisphere than it's ever been, even if you take something like Instinct,right?

Like the numbers that they're talking about on what they're going to have to spend on compute to service their needs is pretty wild. And so that's a really different cost base. There's a bunch of big questions out there.

How much does that go down? And I think we're in this time, and we feel like we've been in this time where we don't know the asymptotes of things,right? We don't know when models stall. We don't know how low compute goes.

And so one of the challenging and maybe exciting things is you're playing a little bit against an unknown field, but there's a fundamental cost of compute that is part of the conversation and kind of cost block of companies that really wasn't really there before.

I think the other thing going on is that the types of companies we are investing in and that are scaling in the market are different and more varied than probably in any other time in USV history,right? So we have software applications that are emerging that we believe are going to leverage this new technology that's been built to totally transform how we live and how we work and how we are productive and all these kind of things.

But we also have a robust energy portfolio,right? And we believe that programmable, cheaper, faster energy is the horizontal undercurrent of everything being built on top. And the cost structures of those energy companies are totally different or our investments in physical AI and the physical world,right?

Where we're investing in things that are really full-stack robotics companies that are building their own models and also the deployment on top sensor businesses. And so they have different cost structures that are requiring both different levels of capital and sometimes different types of capital than previous eras have justified.

You know, one thing on the inference, it actually reminds me of kind of an earlier era of technology, maybe the mobile era or even, you know, sort of the post-internet era where, you know, you had these great consumer products and businesses subsidized the usage to make sure these products could get as adopted as far and as wide as possible before customers are forced to pay.

I thinkright now, you know, we're coming out of a period where I think, you know, AI applications in the enterprise and consumer have been more paid for by customers. We're coming out of a lot of subscription businesses, but now products like agents, you know, to your point about the inference, we're seeing that startups actually want to subsidize the inference and pay for it on behalf of customers to reach that critical mass of adoption.

So I do think it's actually going to be pretty expensive to build large-scale consumer businesses if you don't want your customers to pay subscriptions.

OpenAI and Anthropic are still subsidizing their core chat offerings,right? I mean, you know, Claude will ask you to start paying at some point, but, you know, this is ChatGPT has been free for how long? Gemini is still free,right?

A startup can't come in and charge for something that their competitor is giving for free. And so I think you'reright that inference or compute is going to be an expensive subsidy for fast-growing apps for a while.

Yeah, I have a question. In the early days of Twitter or Facebook,right, they offered something for free to the market. And I think one of the things that USV believed in those days is that giving away a lot of value for free in order to back into an opportunity to create a network was a very, very good strategy.

Did it feel like they needed more money than other companies had ever needed because they were doing that?

They did need a lot of money. I mean, Twitter, the original financing was $5 million, and then a year later, it was $25 million, and then a year later, it was $100 million. At that time, those would be numbers.

Yeah, relative.

Right? Like we could multiply by 10 and you'd get to $50, $250, and a billion. And that's kind of what we're seeing now,right? And that was also, you know, 2007, so that's 20 years ago. Just pure inflation is going to give you a multiple too.

I think what's also interesting about that era compared to this one, I think a lot of these products people have pointed out are not that retentive,right? Because there aren't things like network effects. But back then, with a Twitter, with a Facebook, I have to imagine that you all were seeing these and saying, we need to scale these things as quickly as possible because once we do, we're going to have this incredible network effect and there's going to be this incredible lock-in.

It feels like it.

Well, what was different then that I don't think is true anymore was that not every VC saw that.

The network effect.

Yeah. In the early days of Facebook and Twitter, there were venture capitalists who were arguing, we need to monetize this. You know, we need to, you know, have a subscription so we can, you know, have a revenue line that will allow us to finance the company.

And there were others, we were in the other camp who were arguing that, you know, if we can get 10 million, 50 million, 100 million users, we will be able to finance the company. We ended up, you know, winning that argument and we wereright about that.

And that's really how that model emerged that companies use, you know, even to this day to get to network effect.

I wonder if one analogous thing is there's the beliefright now that if you look at these kind of emerging consumer agents, the answer is scale,right? That functionality is not all that different among them, but that if you hit breaking points of scale or maybe distribution, that you can win markets.

And so it's a race to see if you can have theright compute and have theright distribution to get there. There's another strategy, which is one that we've been talking a lot about, which is maybe more analogous to the Twitter era, which is you actually may still need a network effect in order to maintain longevity and have retentive behavior.

And that network effect is going to come with who can really be the first and best at multiplayer behavior and taking these kind of new single-player behaviors and figuring out how to make them truly multiplayer. And it's not that we don't need network effects anymore.

It's just that we need to get there.

We haven't seen them yet.

We haven't really seen them yet.

I want to push back on the agent-like economy so much because it's kind of obvious every single company is going to have an agent of some sort. You'll probably have more securitized boxing within those. I mean, we were joking about this earlier, but it's kind of true.

You, like, input all of your sensitive data and it kind of roams free. But it's clear with Facebook and Muse. I mean, Deel even launched theirs for most of, like, management work and that kind of thing. Like, every company will have an agent of some sort.

Obviously, it's one of the most cost-intensive things because it's running so many different programs at once and nodes and that kind of thing. But I just have to push back on that. So, like, do you think that's a viable long-term category?

Like, how does that compress versus years ago?

We do. We do. We think that Amazon will have an agent. So I'll have my Amazon agent and I'll have my Shopify agent and I'll have my Etsy agent. But I think I'll also want to have my shopping agent or maybe just my agent that will talk to my Amazon agent and my Etsy agent and my Shopify agent so that I don't actually have to be managing conversations with each and every one of those agents.

I can just have my agent go off and do a task. Today, what's happening is the agents, as you point out, are logging into these services and kind of pretending to be me. Amazon doesn't like that. I think last week they said to Facebook, we're not going to let Muse access Amazon,right?

We'll see more of that. But I think eventually what will happen is there will be some standard or some way of agents connecting to the agents that each service offers you and making it easier. So I think we're in the early innings of how this plays out, but we do believe that people will want their own agents that represent them as opposed to my Amazon only having my Amazon agent.

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Before we go too far, let's talk about USV's strategic positioning, where you guys are investing, and what your typical check size is.

Yeah. So, you know, USV has always been, you know, for its history, really been focused on the early stage, mainly Series A, sometimes some seeds, sometimes a little bit more than that. I think we're going to continue to play the same game and invest in the same stages for the most part.

But to Rebecca's point from earlier, we're going to be doing it with a slightly larger capital base. Not so that we can do many more deals or fewer deals, but more because, as we talked about earlier, the shape of the market and the shape of the deals has changed as it's gotten easier to build.

You know, there's also much, much more demand flowing in in the form of capital, and startups are raising more. And so for a fund like ours to stick to our strategy, to stick to our various ownership targets and make the fund math work, we need to write slightly larger checks.

It doesn't necessarily change the way we think about deals or the way we think about companies or our thesis-driven investing. It's more of a reflection of where the market is today.

And what was the pitch to LPs? Was it an easy one?

You know, I think USV has a long history with a group of LPs that have been very, very loyal to USV, and I think USV has been loyal and good to them as well. And so there's a lot of trust established there.

And we added some new ones. And I, you know, what was interesting to me was LPs see the same thing we're seeing.

Yeah.

We're not living in different worlds. They see it too. And so I think, you know, maybe a few years ago this would have been an edgier push than it wasright now because the market has pretty clearly moved in a direction.

And I don't know, one thing that I feel like I've kept saying to myself is you cannot like things about the market, but you're unlikely to change the things about the market. And so, you know, we believe that it's a pretty unique time to be on the field investing, and we want to be on the field in theright way.

And we have four areas that, you know, we talk a lot about, you know, in conversations like this, on our website, with our LPs, with founders. Rebecca mentioned them, physical AI, AI applications, AI infrastructure, and energy. And so those are the areas that we're investing in, and we're consistent about that everywhere.

Our LPs understand that. So there are other areas out there. Founders who are working in those areas have lots of places to go to, but they don't come to us because we're not loud about those things. But the things that we are loud about, founders find their way to us.

And I think that's what we mean when we say, like, you know, the strategy is kind of the same as it's always been at USV. We're thesis-driven. There are things we like. There are things we don't like. You know, $900M may represent a big jump up for us, but relatively speaking, it's still maybe considered small relative to a bunch of other funds.

And I think that size and this thesis-driven approach is what enables us to play the game that we want to play relative to the rest of the market.

Well, to that point, I was an LP at one point in my day. And there are very, like, there are very few funds to invest in. You typically know which ones you're going to invest in, like, a year before you invest.

It's all long-dated and, like, very much organized. Were they waiting for you to raise larger? Did you have pressure for that over the years?

One thing that I think USV has always done quite well, and I think, you know, Fred and Brad said at this, is we're very, very communicative with our LPs. We talk to them a lot. We don't take it for granted.

They're support. We do quarterly calls. We update them on our strategy. We update them on our portfolio. We tell them what's working. We tell them what's not working. We tell them what we're thinking and where our heads are.

So by the time we come and say, okay, we're going to shift the fund size from X to Y, they've known it's coming. This is part of a conversation that's been going on for a long time. I was a little surprised how many of them said, are you sure you shouldn't raise more?

Really?

Yeah. Again, because we're not living in a bubble,right? They're seeing the same things in the world, you know, that we are, and they're seeing the landscape of what's advantage, but also that they appreciate that we... So why have a small, relative in any world, a small fund?

I think there's a bunch of reasons. One, you can return it easier and get into carry and have the dynamics of the fund work the way you want it to. Two, you can be pickier,right? We always want to manage a fund in a bottom-up way.

And when I say that, what I mean is there's a universe of companies. We don't want to say we need to be an X percent of them for this math to work. We want to say we have strong hypotheses and ideas about what we want to do.

And if we'reright enough about the ones we do aligned with us, this fund is going to be a big success. And so we don't want to get bigger than that strategy allows for. But that number has shifted. And so that was an ongoing conversation with the LPs.

It also aligns interests,right? Like when the funds are small, it kind of focuses the results on the performance of the portfolio companies, and everyone rallies around that. When the funds are really big, it potentially distorts the incentives a bit.

And that's one thing that I've really appreciated about USV's small fund strategy.

When you started USV, did you want it to stay a small fund? Did you ever want it to be a really big fund?

I liked the earlier stage of investing and so the ability. When we started it, you know, we were thinking of writing like a $3 million Series A check. Obviously, that number's changed a lot over the years, but that's how, that's where we wanted to be, and that's where we still want to be.

What is a typical Series A today?

I'd say it starts with 10.

Like, I think 10 is now on the small side.

That's why I say it starts with 10.

Yes, 10. You know, you're obviously seeing some Series A's that are 100 or.

A billion.

A billion,right? Like, we also know what's not in our zone,right? That's not in our zone. We want to overall, and there will be exceptions to every rule, we want to lead our co-lean investments. We want to make real bets on things and stand behind them.

There might be a time where we break that and write a, you know, strategic check into something in a different way. But overall, that's really our strategy. The checks that we believe in, the Series A checks in this fund, will probably be 10 to 30 in order to do that.

They don't have to be the whole round, so the rounds could be bigger than that. But that's probably what we're looking at. And then we'll do a lot of seeds. And we'll even do some earlier than seeds. Maybe Mike can talk a little bit about that too.

Yeah. We, you know, one of the things that we've been thinking a lot about at the seed stage is, you know, what are some new and different strategies that we can pursue as a partnership that maybe USV hasn't traditionally pursued to get real ownership at the seed stage,right?

One thing could be taking more pure founder bets, which as a thesis-driven firm, like, we haven't done a ton of that in the past. Another thing could be, you know, earlier we talked about how much easier it is to build something than ever before, how much cheaper, how much faster.

We have a lot of strong opinions about different categories and theses. And so in some cases, we feel like it might make sense to actually build something inside the partnership as a bit of an incubation.

Yeah. And there's another slant on that. We have a couple of venture partners, Jared Heck and Scott Belsky, who are really accomplished entrepreneurs and product thinkers and builders. And working with them and Mike, who is also very much in that camp, we can do things that aren't really an incubation, but we have an idea.

We go find somebody who maybe wants to start something, and we kind of partner with them to get it off the ground. So we're not the founder per se, but it's a situation where we have, like, full ball control, if you will, and we'll provide maybe the first two checks into it before it goes out to market.

And so this is all kind of, I think, a continuum between real incubation and founder bets and maybe what I can call, like, proprietary seeds. And I think maybe those will make up as much as a third to a half of all the seed investments we make.

Because, as Mike said, it's getting easier and easier to prototype something and take it to a small group of users and actually get real feedback and see if you've got something or not.

That's a good point. So how has the measurement at which you diligence these companies and the milestones and the success metrics changed over time? What do you look for now, or what do you overlook now that you might have looked at before?

I think one of the things that I've been really excited by coming in as USV's newest partner is how much this team cares about products. You know, it feels like the deals that we've dug in on sort of always require, not requires, there's not a hard requirement, but it feels like there needs to be somebody on the team that's, like, really excited about the product.

Now, obviously, that can't always work, especially in today's market where, as we just mentioned, you know, some cases we want to go earlier and earlier and just bet on a founder or maybe somebody that's in our network that we really trust, but.

Or we're betting on micronuclear reactors, you know.

Right, exactly. So it can't always be about that.

That's a little different. So in the energy side of our business, it's different. But I would say in anything that touches the consumer, it's a combination of what Mike said, which is using the product and getting kind of an instinctive feel for whether the product is good or not.

And when you combine that with retention data and cohort data, the magic is when you can start to, the thing you feel is the thing you see in the data, either the retentiveness of it that you feel and you see, or maybe you're like, you know, I might churn off of this because of X, Y, Z, and you see that in the data and you're like, oh, you know, they're going to have a churn problem.

And so it's, I think it's a combination of using product and sort of a product-native mindset combined with a lot of data and really looking at cohorts and understanding what real users are doing.

I think the other thing, though, is that teamright now is playing, team is always the most important thing,right? No great company can be built or started without an A+++ team. We actually debate that sometimes because sometimes there are these examples of crazy runaway network effect businesses where the momentum of the network can carry it far enough that maybe team matters left.

But I think in today's world, team is playing, you know, it always plays an important role. I would argue it's playing in a more important role than ever for really a bunch of reasons. One is that I think great hiring is harder than it's ever been.

There's massive, massive talent competition. And so the ability to pull people away who are excellent from really, really strong other opportunities, sometimes where they're getting paid a lot of money by large labs or incumbents or whatever it is, or startups that have raised billions of dollars.

You need theright founders that can really kind of mobilize a world around that. The other reason is I think narratives and market narratives are aggregating faster than they ever have. So the market is designating winners,right? And telling these stories in a way where value aggregates, often in a way that way, way, way precedes where the business is.

And so the ability to be the founder that drives that story and gathers that attention and breaks through the noise and designates themselves as the owner of a market very early is super important,right? Both for investors and raising money, for team, for customers.

That narrative piece and storytelling, I think we are paying way more attention to now than we probably have in other markets.

Also, if it's easier than ever to build a product, you know, we want to back founders that we believe can really go the distance,right? And that's, I think that's more rare than ever.

I know this is like, you know, we're talking early stage, but the company's mature. Like, you guys are sophisticated investors. Like, you are actually looking at performance metrics. Like, it is clear, and it's also clear which ones end up becoming scams because they're really good at marketing themselves.

And then which ones, like, actually have performance and revenue and that kind of traction. So I'm kind of trying to get below the layer of like, yes, it's a great product, yes, it's a great team, yes, it's a great founder.

Like, what do you want that team to be focused on? Is it retention? Like, is it revenue? Like, what do you care about?

The last time I was on Sourcery, there's a clip now that I see on X all the time from that interview where I guess I said ARR is a fake metric. I said something like that. I see this.

I think ARR has become, you know, a metric that a lot of investors pay attention to given how fast the revenue rate has ramped for so many of these companies. But, you know, I think one thing that we care a lot about is kind of clicking a layer deeper than that.

You know, so many of these products now, because so many are subscription-based,right? We talked a little bit earlier about how so many products are subscription-based. I think it's easier than ever before to get somebody to pay for a product via subscription without knowing if they actually like that product,right?

A lot of the subscription plans are annual. A lot of the time you have to pay just to try the thing. And so we try to look often more at the true usage retention of the product. Like, how often are people actually coming back to this product and using it?

Are they coming back every day? Are they coming back every week? Do they turn out after a month? I think that's probably a more telling thing to look at than just revenue retention. Yes, great. If the company can hold onto that revenue for a year or two years or three years, obviously that's going to show up in the business.

But if the product isn't good, at some point they're going to churn and the business is going to fall apart. So I think people should be paying more attention to that. Like we used to, I'd say in an earlier era of investing.

I think it's user retention and product innovation. I think we're in a moment in the market on the consumer application side where trial behavior is at an absolute high.

Totally.

And engagement behavior is at an absolute low. And that makes sense,right? We're getting thrown so many new things all the time in the market.

And you have to pay to try them.

You have to pay to try them. And we want to. It's on the news. It's the main discourse in the world. Everyone's like, are you up to speed? Have you tried Instinct? Have you tried Muse? Have you tried Robin Hood?

Like, we want to try them all. We're going to stick with very few. So the trial behavior is a little bit of a fake out,right? Because we know you can get people to try, but it's only really going to have long-term value if you can get it to integrate into someone's life.

Totally.

And so figuring out how to tell that is, I think, the whole thing. And part of that is watching how someone iterates on product,right? I don't only think it's like great product insight. It's what are the little hooks and things they do and changes they make that keep that product going and fresh and different?

Because realistically, the idea that we get, you know, full insight into retentive product behavior before we get to make a decision is not really true,right? Like, if we really needed that, we'd be having to write way, way bigger checks than we would like to write here.

So we're going to have to make an inference about that with less data than, you know, maybe we would like. And so I think you're looking for proxies for that, both on the team and on the data side that give you the sense that that's to come.

But a lot of this that we've just been talking about, I think of as like seed, Series A, Series B kind of conversation. One of the hallmarks of USV is that we are very long-term investors. We still, all of us are still working on companies that, you know, we funded over a decade ago.

And so as these companies grow, what you want to see is that the team can launch new products and new lines of business. We had all of our CEOs together last week at our annual CEO Summit. And one of the stars of our 2016 fund is this company called Abridge, which is an AI for healthcare company.

And Shiv was telling a bunch of us just in a casual conversation that they had made all of their money for the last five or six years on a single product. And he's most proud of the fact that in the last 12 months, they've launched two new products, really two new lines of business.

So now it's a three-legged stool instead of a one-legged stool. It's going to be a much more stable business. And the three products are very synergistic. So when a customer adopts one, they're kind of locked in. When they adopt the second one, they're more locked in.

When they lock in, when they adopt the third, they're kind of all in on Abridge. So that, to me, is the evolution of a company that's going from being, you know, a great company to being potentially a fantastic company.

And the thing about venture capital is anybody who studies it, and you've been an LP, so you know, is that it's usually two or three, maybe four companies per fund end up being the stars of that fund. And to be one of those companies, one of two or three things has to happen.

And what's happening at Abridge is probably my favorite example of a company that can make something, can make a company that could be like 100X.

Well, one of the things I like about that, that I think, is that if you think about Abridge or like a bunch of the winners that have emerged, including Twitter, they're often not straight lines. It's not like they popped immediately and like it was obvious,right?

Abridge is in 2016, you know.

And we're seeing a lot of companies now that feel like they are straight lines.

It feels like it's obvious and it's unlikely that that's the story.

That's a good point. So to dig into, I guess, this pattern, if there is one over time, like, is it obvious to see that in a company? Is it a straight line to Rebecca's point?

If we go back, USV has probably now had over 10 early-stage funds in the life of USV. And every single one of them have produced two to three really great companies. And if you, you know, you just sit there and you list them.

In our first fund, we had Twitter, we had Etsy, we had Indeed.com. Indeed.com, you know, we still see ads on TV. We haven't been an investor in that company in 15 years, but I suspect that company is like 50 or 100 times bigger than when we sold it a decade or more ago.

And then in our second fund, we had MongoDB and we had Twilio, you know, which were, you know, products that developers use. And then we had Stripe, and then we had Coinbase, and then we had Duolingo. And then now we're getting into the more recent era, like Abridge is a 2016 company.

And I've left off a few,

but there are probably 20 or 25 companies that, you know, we've invested in over the last 20 years that I would, you know, consider to be extraordinary companies in terms of not just the investment that we made, but like what they become.

I mean, Indeed's really interesting. Like, you know, we were there at the very beginning. It was Paul and Ronnie and a couple of engineers, and they had this idea. Today, it's like probably the largest job hiring system in the world,right?

You know, and it just came out of nowhere to become that,right? And you watch these things emerge that way. It's remarkable. I mean, Twitter, you know, well, now we know, you know, what it is. It's one of the most important, you know, pieces of media infrastructure in the world.

And, you know, when we invested, it was like five or six people,right? So that's pretty interesting. And one of the things that we can give founders, and we're not alone in this, by the way, is that there are plenty of people here at USV who have that kind of perspective on what it takes to really build a generational type of company.

And

the fact that it's not a straight line,right? Like Coinbase was like, you know, you know, like it was like a series of like little moves and then flat for a long time, then a little move, flat for a long time.

The couple big breakouts in '17 and '19 that led to it becoming a public company. So it's never a straight line to the top. And sometimes there's management changes. Twitter's sort of famous for having kind of a revolving door of CEOs for a long time.

So that's its own set of things that you have to work through sometimes.

But if you take Abridge, for instance, like Abridge, the idea of the product was very similar, but it went down a very different go-to-market road for years that didn't get them anywhere and turned out to not be the go-to-market road,right?

That made sense for that product at that time.

What was it?

Consumer.

The idea was you would walk into a doctor's office and record the appointment. Well, it turns out it's actually the doctor who wants to record the appointment.

And so like you think you back a whole business,right? You think you back, you know, you get conviction on this idea that patients want to record themselves, you know, in their medical appointments for X, Y, Z reasons, and your backing this team to go after that.

What you learn your backing is not that. You're backing kind of a team, a product sense, and a direction,right? And what you backed was the idea that Shiv could build the team that took this like kernel of an idea that was directionallyright and kind of wrong in the details to start and navigate it to the place where theright product and then, as Fred talked about, eventually theright series of products met theright go-to-market at theright time.

And that sometimes happensright away and sometimes takes a while. And you need the teams that are going to be able to kind of go on that journey and fight that out.

It's usually an extraordinary founder, though. Not always, but Shiv's an extraordinary founder. And the other startup that we backed in Pittsburgh, Duolingo, again, an extraordinary founder.

More of a straight line.

No, no. The first product was, no, the first product had nothing to do with what they ultimately.

What was the first product of Duolingo?

It was like translating, you know, like foreign language documents. No, it had nothing to do with, I mean, but.

He's amazing.

Founders, Rebecca said this earlier, founders who can combine a vision for something that they want to exist in the world with the ability to tell that story and galvanize theright people and theright investors and theright product. That's, we've all seen it.

We know when we look at it, we're like, oh, that's a great founder. But it's easier to see it when they're, you know, the CEO of a public company than, you know, when they're just walking in our door with an idea.

And we get that wrong more than we get itright.

How do you get it wrong?

Well, we think somebody can be a Louise or a Shiv, but it turns out that they can't get out of their own way. They overthink things. They struggle recruiting. They struggle retaining. They're a micromanager.

They struggle making hard decisions to make the big changes early enough,right? To say, this go-to-market's not working, let's try something really different. It's hard to burn boats as startups.

Mike's been a founder, so he has a lot of empathy for this.

Not a straight line. Yeah, it's never a straight line. But, you know, everything these two are talking aboutright now is what I love about USV being thesis-driven,right? You know, all of the examples that they both just cited, if you think about them in the context of when the bets were made, it's extremely early,right?

Like the Coinbase bet was very, very early on in the history of crypto. The Abridge bet was very, very, very early on in the history of AI and data capture.

Particularly AI and healthcare.

And I think, you know, Rebecca's framework that she just laid out a few minutes ago about a great team and a direction of an idea, I think, is so, so important and so key. And I think that's how USV has been successful at these bets early.

Another one that, you know, we've been talking a lot about is Radiant, which, you know, Fred is on the board of. You know, that bet was made before it was obvious to everyone in the world that energy was going to need to be so abundant for AI.

But, you know, this team had a thesis and had a point of view about the importance of energy, which was what led to that investment. And now, sure enough, how many years later, five, six years later.

We invested in Radiant in '21, so we're five years into that one.

So, I mean, anyway, it just speaks to the power of, I think, thesis-driven investments. But I think to your point and, you know, to your answer, Fred, we don't always get itright. And sometimes not only is the team wrong or the person, but sometimes the thesis is wrong.

Sometimes the benefit of thesis-driven investing is you can, I think, a few things. One, you can bet on spaces that are more on the come or less obvious because you have a prepared mind and perspective that you're bringing to it of something you believe.

You're not just seeing a company and seeing what they believe. You have a belief. You can also start the conversation with a founder in a different place,right? Because you're saying, I have a set of hypotheses on something and you have a set of hypotheses on something.

Where do we align,right? Which I think is actually a lot more fun and probably sets you up for a relationship in a different way, but also I think tends to get us to a better outcome than otherwise. The risk is like there's a lot of ways you can be wrong and be wrong on people.

You can be wrong on the whole thesis,right? You can go down a road that isn't, you know, theright road to go down, but when you go down theright one, it's worth it.

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Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deel.com/sourcery. That's D-E-E-L.com/sourcery. I guess to distill this theme down, what are the key behaviors or actions that successful companies make that win each technological shift?

Like we're in a major technological shiftright now. How have you seen that throughout time of what the key behaviors are of those teams or of those founders and maybe the key traits of those types?

It's getting the idearight. What I mean by that is

everybody knows that we're all going to have personal agents. But if you look at each of the products that are out there, they're all a little different in terms of how they feel, how they work. Getting itright is theright set of features kind of stitched together in theright way and delivered with theright business model.

And then also with a team who has the ability to access capital and scale against the opportunity if they actually catch fire. So that, I think, it's not just the ability to raise capital. There's lots of people who are great at raising capital, but they can't build a product that really wins.

And there are people who build a product that really wins, but they can't galvanize a team or money, and so they get beat. It's the ones who can do both that ultimately really win.

Was identifying that aspect of fundraising ability as important maybe 10 years ago? Was it as obviously important 10 years ago?

The interesting thing, and Rebecca alluded to this earlier, sometimes if a product really catches fire, it can raise money even without theright team around it. And then you have to kind of scramble, you being the founding team and the board, kind of have to scramble to figure out how to fix the team and get itright so that all the things can come together.

And I would say that was true at Twitter. That was also true at Etsy. So it isn't always the case that

theright product emerges from a team who has maybe theright stuff to make it a lasting business.

Why is one of the categories called Rebel Alliance?

Well, rebel just in the sense that there are now the sort of established winners in AI, which would be OpenAI, Anthropic, Grok, Gemini, I guess, although that's Google. And then there's this sort of open source world out there of open source models, open weight models, open source harnesses, and all this other infrastructure that you can stitch together to build something that looks like Claude or looks like Cursor or some sort of full stack product.

We call it the Rebel Alliance because a lot of developers out there, they don't want to build on like a closed stack. They're worried that if they build on top of Claude, for example, just to pick on Anthropic, that somehow Anthropic will ultimately compete with them and then they'll get cut out.

And this famously sort of happened in the early days of social media. People built lots of businesses on top of Facebook, and Facebook ultimately decided they wanted to be in those businesses themselves, and they got cut out,right? And so developers out there have this concern, I need a stack that I can control and I can trust.

And so we call it the Rebel Alliance because there are people who are kind of rebelling against the leading emerging stacks and trying to construct their own.

And it turns out like that stack is actually very, very large, and there are lots of layers to it for not only opportunity, but for the different needs of the developers,right? There's things like alignment with the models and making sure that the models are aligned with the needs of the enterprise or the customer.

There's things like memory, there's things like routing, there's things like the models themselves and making sure that they're open weight and you know a developer can actually manipulate them the way they need to. And so we feel like not only is there this, I don't know if we want to call it like uprising of developers wanting to not be beholden to this one sort of player ecosystem, but it's also very, very, very large with lots of layers, which is why it represents an entire thesis for us.

I mean, we had a moment on stage last week at the USV CEO Summit where I was interviewing the CTO of Coinbase about some of the changes that they've made organizationally to be more AI-centric and how they do the work.

And he just casually mentioned that they moved away from Claude and they built their own harness, their own coding agent harness on an open source product called Pi. Well, we're an investor in this company, Arendel, who put Pi out into the market.

I didn't even know that this had happened. I was just like, yes.

That's great.

And that's, you know.

Tons of developers.

Well, so a company like Coinbase and Shopify has done the same. They were, you know, pretty loud about it. And I imagine many other companies too, where the CTO and the engineering leaders look at it and say, oh, we can't just build everything on top of Claude,right?

We have to have something that's more flexible that we can evolve with our needs. And all of this is really getting built up in these open source tools. We're very excited about that area. It's an area that we feel like we have a lot of conviction around that maybe other venture capitalists aren't as excited about as we are, which is something we like because the founders feel a kindred sort of spirit with us.

And so we tend to be really competitive in those environments.

Any other areas?

Well, I think energy in general was an area that, you know, I think we staked out early. And, you know, we basically said, look, if you really want just a simple way to bet on AI and not have to think about all this other stuff, just bet on energy.

Energy, yeah.

Now, we're not just doing that, by the way. It's 20, 30% of our portfolio, but we feel like it's a very levered bet on AI.

That's a good one.

We talk a lot about obliterate, don't automate, which is kind of another phrase for the investments we're making at the application layer of AI. The way we think about that is it's the idea that a new.

AI is going to kill us all?

No.

No, no. Opposite.

But that it may obliterate an existing market,right? There was an era of software, you know, over the past decade, SaaS, enterprise, that was really about automating businesses and automating markets that already existed. But with AI, you know, businesses and consumers can tap into intelligence that was previously gatekept by really large organizations or really large institutions at a fraction of the cost.

And we believe that through that, literally entire markets can be restructured through that democratization of intelligence. So a great example of this is something like healthcare. We have an investment in a company called Doctronic, where they're leveraging AI not to just make the existing healthcare system more efficient or more practical, but to literally give consumers a doctor in their pocket in the form of AI.

That can actually write prescriptions in some states.

Really?

Yeah.

Utahright now. What kind of prescriptions?

You name it. What do you need?

Oh, no.

Probably not. Probably not controlled substances.

It's not controlled substances. Right now it's largely refills.

But you can see.

Anything you want.

But you can see that if everyone had access to a doctor, literally on demand, immediate for virtually no cost, what that would do to the existing healthcare market in this country.

One of the things that I love about obliterate, don't automate is that it's perfectly applicable to this moment in time, but it's probably the best articulation of the thesis USV has always had.

Sure.

Fred actually wrote a blog post in 2014 called Obliterate, Don't Automate about the USV thesis. We've always believed in the opportunity to restructure markets and drive the value back to the end user away from the centers of power in the middle.

You just can do that with a whole new toolsetright now. So the opportunity to restructure healthcare, restructure education, or restructure manufacturing or whatever gives this opportunity to drive the value out of the middle to that end user in a totally different way because of the toolsets at hand.

A simple way to think about this is don't hire a lawyer, use an AI lawyer. Don't hire an accountant, use an AI accountant. Don't hire a doctor, use an AI doctor. No human whatsoever in the loop. It's not about selling AI to doctors or AI to lawyers or AI to accountants.

It's like, I'm not going to have an accountant. I'm literally going to tell my AI to prepare my tax return. I'm going to give it access to my bank and it'll just do the numbers and send the IRS my.

You know, I don't need a human. I don't need to pay a human. I would say 20 to 30% of the legal work that we do here at USV does not get touched by a human lawyer anymore. Now, we know what our AI lawyer can do and what our AI lawyer shouldn't do.

That's increasing over time, but we're not careless about it. But there's certain things like issuing a term sheet we do not need a lawyer to do anymore.

No. How many of those have you issued?

Right.

Many.

So we can train a model on all of our previous term sheets and issue them,right? And so, and the thing that is exciting now isn't where everything is, it's the slope,right? And if you just play out that slope, it covers a lot of that.

Your AI lawyer is as bad as it's ever going to be.

It will never be as bad as it is today.

The company that we recently announced that, you know, we talked about as sort of an incubation super take. I mean, this is another great example of this. The whole idea of that company is you don't need expertise around the stock market or you don't even need to pay a financial manager to come up with a portfolio strategy for you and then deploy it.

You can just have the AI do that. And so that's another example of sort of breaking down the barriers of sort of gatekept institutional knowledge via AI.

The age-old question to this would be, why can't incumbents do that?

They won't do it. They have people. I mean, lawyers are a perfect example of it,right? We say to our lawyer, you know, you can issue the term sheet, we're just not going to pay you to do it. And they're like, well, why would I do that?

You know, I have people to pay. Okay, fine. Then I'll just use an AI lawyer to do it. Like.

And their business model depends on the people.

The incumbents cannot, and I think it's particularly powerful in people-based businesses. The incumbents cannot offer something for free.

Our partner Brad is, I think, always says this the best, but his line is always the best time to bet against an incumbent is when them doing what you want to do fundamentally threatens their current business. It is very, very hard for major incumbents to burn their own boats and to take that kind of risk.

So if you think about, you know, there's plenty of news out there about certain law firms,right? Hiring engineers and machine learning. Morgan and Morgan is going into AI. Did you see that? Yes, exactly. And trying to build the models.

And some of them will do it and some of them will try, but overall, it will cannibalize their own business.

Right. I mean, Google has done, I think, an admirable job. They know that Gemini is going to cannibalize Google Search. And the numbers are staggering. I saw last week, Search is way, way down. It's dramatic. They are doing it, but they have all these other businesses.

They've got YouTube, they've got Waymo, they've got, you know, Gmail, they've got Android. Like, they can literally kill the thing that funded all those other businesses because now they have all the other businesses. If all they had was Search and they never built those other businesses, they'd be in a world of hurtright now.

Yeah, a lot of publicly traded incumbents are going to have a really hard time doing this because they have to answer to their shareholders and keep revenues going up and to theright.

But I think your fundamental question is the one we're thinking about all the time. It's not only why can't incumbents do it, it's why can't anyone do it. Right? It's why can't I build that agent to do my taxes or why can't I train my, we trained our own, you know, legal model.

We didn't buy it. And so what is going to create advantage in this moment in time when the building is faster and more efficient than ever, you know, and that is something we're thinking about. And that goes back to network effects and speed and team and product decisions that are going to make these abstractions the ones that people rely on.

And also some of these other categories like physical AI and data at the edge and, you know, energy and things that operate in a little bit of a different way than software. So an area where all of this is directing, it's part of Rebel Alliance is trust and security.

And so how are you thinking about cybersecurity and all of those types of things as we obliterate and automate everything?

It's definitely an area that I think is about to change. I think a lot of cyber focus over the past few decades has been focused on the enterprise. It's probably going to undergo a lot of change at the consumer layer now just because of how many consumers are going to be, I think you said earlier, just like handing over everything to their agent, whether it's Instinct or Grokbot or Muse.

I mean, one of the things I was thinking about just this morning was the concept of password reset is going to have to change. If you give your agent access to your email, which is where all your password reset emails go, they just automatically will be able to access literally every account you own.

So it's definitely an area we're thinking about. You know, we haven't traditionally made a ton of investments there, especially at the enterprise, as we mentioned, but it's an area that's going to change dramatically.

We have a portfolio company, they call themselves Common Fabric now. They just announced,right?

Yes, Common Fabric.

And it's a sandbox that's focused on this very issue about how do you give users the security that they want, but also the power that they need. They have a particular approach. I think it will be interesting to see whether that approach or a different approach will emerge, but we have a lot of conviction that users are going to need some new help in security around this stuff.

I mean, I think about my mom who's 96, she's not prepared for this world. Like she's not going to be able to know what's real and what's not real. I'm not sure I know what's real and what's not real.

People get spooked by or spoofed by those AI videos all the time.

All the time.

Well, we've always been interested in this idea of security and privacy and control with the user versus the platform. And we've done that to kind of more and less success over time in terms of how much the end user actually cares about it.

There have been companies like DuckDuckGo that had enough of an audience that really cared about privacy and search that created a really, really strong business around it. And there have been plenty where we may want them to care about privacy and security, but there's not enough of an incentive system for the end user to really care about it.

That may be changing.

Yeah.

Right? It may be part of the conversation in a big enough way where things like on-device and private models and these kind of personal security and more consumer-oriented products may have a moment that in previous iterations it didn't have because of the awareness and the scale and all those kind of things.

I also think things like biometrics may have a different kind of moment in terms of proving humanity. And so I think we may be entering a time where things that previously struggled to get attention have this moment to grow.

The other thing to think about is if you can run models locally on a secure device like an iPhone, then you can give a lot of this secure information to your local model and have it do the work locally as opposed to out there in the cloud.

We're not there yet, but I don't think we're very far from some pretty powerful models being able to run locally.

Nikhil and I saw a company this weekend that's doing local models on your phone.

So we're there.

Yeah, I think we're there. Wow. Surprise. Well, Fred, you know, of all people, though, it doesn't just stop at that. Even in crypto, like you can click a link and your whole wallet will be erased.

I've done it.

You've done it. Oh, wow. Do you have anything left?

No, no.

We should be worried.

What stops your agent from clicking the link? So I have owned crypto assets for 15 years and I've been hacked four times.

Oh my God.

But I still have like 99% of all my crypto.

Oh, not bad.

So, but I've been stupid and done things I shouldn't have done and not had my crypto as secure as it needed to be. And I've learned the hard way, as most people in crypto have. I think if you talk to most people who have been in crypto for as long as I've been, they will tell you something similar to that.

Hopefully, the ratio of losses to what they've kept is the same as mine, because I feel good about that. There are some stories out there that are horrible where people lost everything, but I think most people, you know, got hacked and it scared them enough to kind of take the proper measures.

I almost lost all my crypto once. I got very close to being scammed. I was on the phone with a scammer for like 15 minutes thinking they were legit.

You were on the phone?

Yeah, it was bad. And my wife, she was like, you need to hang up the phoneright now. And sure enough, she wasright. But I came very close to losing all of my crypto.

Damn.

I mean, Coinbase, you know, a company that I'm still on the board of and was, you know, one of our really great investments over the years here at USV. That's a big part of what they do. You know, they have cold storage where they store assets super securely for their customers.

And there's a lot of, you know, there's two-factor and there's like delayed withdrawals and there's all these things that they do to protect those assets and literally protect their customers from their own stupidity, which I'm guilty of, by the way.

Yeah, in many ways, it's a security company more than anything else,right?

Yeah. I mean.

Well, that's an interesting analogy because like people wanted to get into crypto and were interested in it, but it was, it felt dangerous because you'd get scammed all the time and there was a big privacy risk. And Coinbase came along and said, just give it to us and we're going to handle that part of it for you.

And it'll be secure.

They're the most trusted brand of legislation.

And it's just a trusted brand.

No offense.

Yeah, exactly.

Mortgage.

Yeah. They're the most trusted brand in the sketchiest industry ever.

That should be their tagline.

No, they make it literally seem so normal. Like it's awesome. I've talked to them about it. Even Cat, they're like, they do a great job marketing.

And most people don't know how exactly they're keeping it safe,right?

Well, that's on purpose.

Yeah. Totally. Probably telling anyone. Yeah. And also they don't really care as long as you trust that it's safe. You don't really, and I wonder if we're kind of at that tipping point or moment in AI as well where like everyone's interested, we know it's going to provide a lot of utility, but we're looking for these kind of trusted brands and platforms that can kind of give the comfort that things are in good hands.

I went to their last system update product launch in New York, just a couple blocks away. And that was one of the questions that I asked both Cat and Brian. It's like, you guys built the most trusted brand in one of the toughest markets.

Like, what do you think all these AI companies are getting wrong?

What they say.

Well, I mean, like they're telling people they're going to lose their jobs and die. So that doesn't help. It definitely doesn't help.

It's a good way to destroy trust.

Yeah. Okay. So I hope you don't mind. I went over a bit because this like dynamic just works really well. It's awesome. So we might not have that much time for solos, but I just figured this might be fine.

This is just awesome.

Maybe we just do like the quick office thing.

I think.

I think that's fine.

You have to go in a few minutes. What time is it?

It's like 10:00.

9:52. I got eight more minutes. Okay, cool. So I figure just like two or three more questions, but like this is awesome.

Great. So then maybe we're good.

You guys are so fun to talk to. And like the vibe and the dynamic is great. This is the vibe. I mean, what you're seeing is the vibe among our partnership and frankly, the entire team. I don't mean to make it just about the partners.

It's a very conversational kind of back and forth, wanting to hear what the other person thinks and collectively kind of coming to ideas together. That's how we work. Okay. So I'm going to ask you the hard question now.

Sure.

Do you expect every company to become a trillion-dollar company?

No, of course not. You know, if you expect, if you expected every company to become a trillion-dollar company, you would not, somehow you would not be taking enough risk,right? Like venture is based on an outlier mechanic, but we don't invest in companies that we don't see the opportunity ahead of us.

Do you think it's realistic to think that like these companiesright now will become, I mean, obviously Anthropic's not that old. We have ChatGPT, that's a little bit older, OpenAI, but like.

I have kind of two takes on the question. Part of your question is, does every market have to be a trillion dollars,right? Can you get into a market that you don't see it today? I think one of the things that USV has done quite well historically is be willing to bet on markets that aren't yet there, but are on the come.

Crypto being maybe the best example of it. Energyright now as well. Education. These markets where if you were underwriting exactly the dollars spent in crypto at the moment of a Coinbase investment, you would never get close to being able to underwrite the value of what that became, nor what that market became.

So you need to bet on markets that you are excited about today, but even more excited about where they're going. We're certainly doing thatright now. We've been talking about things like robotics, like what can happen because of a sensor proliferation.

None of that is that interesting today in what is live in the market. But do we think when we look at 2030 or 2040 or 2050, those can be trillion-dollar markets? Absolutely. Radiant nuclear,right? The market for nuclear energy today is almost zero,right?

It doesn't really exist, but we believe it's going to be one of the most essential energy sources that are out there. So we have an interest and ability to write forward on markets, on what we think markets can become versus only what they are today, which I think is really important to our strategy.

I think there was a time where we could underwrite businesses of different scale. Part of it was fund size, part of it was market dynamic. There was a time where like number three, four, five in the market could still actually accrue a lot of value.

I am not as sure that that's where we are today. Others may disagree, but I actually think value is aggregating to top players faster than they ever have before. And interest isn't really existing in the longer tail. So we are less interested in saying, well, we're not in the one or two player, but maybe this three or four player can get enough value that it's a great investment.

I think there was a time that worked. I'm not sure that time is now.

Yeah, in many ways, every USV investment has to, you almost have to believe that it's a TAM expansion opportunity. If you're sort of evaluating the size of the TAM as a fixed TAM when you make the investment, it's probably not going to make sense.

But I also think that if there was a time when we felt if a company could be worth a half a billion dollars, we could make an investment, then I think the number, you know, kind of grew to a billion.

I don't think a trillion is what we need to underwrite to at USV. I think if our biggest winners are in the single-digit billions, given our fund size and our ownership, we can produce really, really healthy returns for our partners.

And that's where it's been. You know, there've been some outliers at 50 billion or, you know, a hundred billion, but, you know, a lot of our biggest winners are in the $10 billion range, and that's produced enormous returns for us.

I ask this also because I just came from bending spoons. And so, you know, they're obviously buying up a lot of companies. They're doing it in the low $1 billion range. They did some earlier ones and that kind of thing, but it was, you know, markably like the ZERP era of funded companies that were at $11 billion, $15 billion, and they got written down to around $1 billion or $2 billion, that kind of thing.

But how do you think about that valuation sensitivity today and where does it get irrational?

I mean, if we get into companies early enough, the earliest stages and with theright ownership size, as Fred just said, even exits in the single-digit billions can still be enormous for us, given the small fund size of our strategy.

This will always happen. There will be some companies that overshoot what they're really worth, and they'll come back to Earth. Not all companies, some companies just are rocket ship going, but some companies, they have a moment where the world thinks they're worth five or $10 billion, but they really are worth a billion.

And that's perfect for a bending spoons,right? Like their model's really interesting. They can, you know, pick things up, you know, when the venture journey's over and grow those businesses, you know, with a different, you know, kind of capital structure.

So as we close out, this is my partner question, but my partner, my favorite partner, I don't know where my camera is. There's like 500 cameras here. Sourcery is sponsored by Brex. And so they think a lot about performance, spending spotter moving faster.

I think about this, you've gotten this question before, in terms of who you surround yourselves with. And, you know, performance is like a measure of like maybe the five closest people to you. Without pumping your book too much, I will try to get you to think outward of that.

It could be an author, it could be like a historical figure, it could be just a longtime mentor of yours. Who are the people that really keep you inspired or keep you challenging yourself?

Founders.

I know that was it. Yeah.

I mean, it really is founders at our CEO summit last week. We all went around the room and said, who inspires us the most? And our partner Brad got up and said, entrepreneurs. And I thought to myself, damn, he did it again.

That's why it's great to be a venture capitalist. Every day someone walks in and you're like, oh wow, that person is thinking about things in a completely different way and changes the way you think about something. So I have to say, most venture capitalists will probably tell you the same thing, that founders are the real inspiration for us.

And our.

When you see an outlier founder start to kind of chug,right? And like hire that talent.

Are there any particular names that you guys have?

Yeah, I've been thinking a lot about like, okay, I have a founder I work with named Zach Kanter. He's the founder of a company called Steady. He sent this email out, an update yesterday. He's been at this for 10 years,right?

It's a long time. The business is cranking. That really happened in the last three years. And he fought that out for seven years, and then he got there and he knew exactly how to take advantage of the moment when the stars aligned for him.

Some of it was external market, some of it was a really high bar of team, even through really hard times. Some of it was just like getting the product at the exactright place that when it was useful, it was there.

And that kind of like intensity and lining up the puzzle pieces is so hard. And I think about the kind of haves and haves and nots in the portfolios I work with. And a lot of it is that, of like, can you make these things line up so you're really ready at really theright time and you just keep that intensity at full charge, even when it's like the wind's not at your back?

And that I find really inspiring to work with.

A thing I always say about like the best founders, at a certain point, you know, they reach this level where it's almost like they see the matrix and they can just, they can do anything. You know, a great example, you know, you and I know that we've talked in the past about Suno, Mikey Schulman, which is a, you know, Suno's a USV portfolio company.

You know, when they just started out, they were so, you know, obviously so excited about the opportunity ahead of them, music, but they had never founded a company before and they had never operated in music before, which is such a challenging market to operate in.

And after now going through the paces for a couple of years and obviously having a tremendous amount of success, I mean, Mikey is just operating at an insane level that, you know, if you met him when he had just started, it's just a world of difference.

And we learn a lot from him and from all of our founders.

Thank you very much, Fred, Rebecca, Mike, really appreciate it. And congratulations.

Thank you so much.

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