All right, everybody. Welcome back to This Week in Startups, our venture capital roundtable. We do it every Wednesday live. We ship it later that night on Wednesday, sometimes Thursday morning. Really excited for our panel. D.A. Wallach is back for the third week in a row, becoming my partner in crime here. He's from Time BioVentures. You can check out more about them at timebioventures.com. I'm an LP and things are going well, D.A.
Thank you, Jason. This fund is going to do well, and I'm saving a slot for you in LAUNCH Five so we can round-trip our LP interest in each other.
Jenny Fielding is here. She's been on the program many times. Everywhere Ventures co-founder and managing partner. Tell us a little bit about Everywhere Ventures.
Yeah, early-stage pre-seed fund, investing across many health and work areas, and we've invested in 300 companies. So pretty active.
Yeah, that is active. I'm assuming pre-seed and seed is the focus.
No, seed, just first money in. And honestly, it's a rare breed these days. So you do it, Jason, and a couple other people. But...
So you're trying to do what First Round's original value prop was: put the first 250K into the seed rounds and have conviction.
In the pre-seed, yeah. So typically the rounds are a million dollars. Sometimes they're, you know, just a bunch of angels or a couple of micro funds get together, but these are almost like angel rounds, but we're institutionalizing that.
You know, it's very important that we have this in the market because everybody's a coward, Jenny. Everybody is like lemmings in our business, especially at the early stage. 'Oh, who's in? Who's leading? Yeah, let us know how the round develops' is what a lot of VCs like to tell people. You tell them the opposite: 'Hey, this is a fit. We're putting the 250 in. We don't care who else is in, or we're not in.' Am I correct in summarizing candidly?
Yeah. And especially, you know, in this stage, if you think about, you know, some of the deep tech or the futuristic stuff, it seems like science experiments. And if we don't have people, you know, really at the earliest stages, like how are these founders going to come to be? Because most folks, they want to see a lot of traction. And the very famous Ben Lerer of Lerer Hippeau, managing partner. You know them. And they did Warby Parker back in the day, Venmo back in the day, Zipline. Not sure when you got into that. We did the more recent last two rounds ourselves.
First check, baby. First check.
Many, many moons ago. I was just a boy.
It's crazy because I, you know, met Keller and he pitched me that same round. The guy said, 'You're doing fixed-wing drones on a slingshot in Africa to deliver blood. Hardware is hard. This technology doesn't work. I don't understand the consumer base. We invest in American companies operating in America. I would love to donate to this, but it doesn't feel like a venture investment. I don't know how I'd explain it to my LPs.' But you had the courage of your conviction. Not even — we invested when it was a company building toy robots for kids, pre becoming a fixed-wing blood delivery platform in Africa. So we were even stupider.
Right, and that's the key lesson here, D.A. — it's a key lesson for all of us. Better to be dumb and lucky than to actually try to figure out what great founders are capable of. You knew he was a great founder.
He was always very special. I'm sure you felt that when you talked to him. And I think, much like Jenny, we are also early-stage focused and believe that, you know, we're wrong more than we're right. But, you know, you do this long enough and you get a feel for when you're sitting across the table from someone who's nuts and maybe going to do things.
Yes, that is a key to what we do as investors at the earliest stage. We're betting on a team, and I don't know, it feels like maybe half of my companies pivot in a significant way because we are pre-seed investors as well. That tracks, Jenny, for you too?
100%. In fact, like, I wish there was more data around it. It's hard to get, but I'd say in our portfolio at least a third, and some of our biggest companies have pivoted.
Yeah. It's basically the successful ones are the ones that pivot. Explain why you think this is, Ben.
Well, I think actually, interestingly, I'm making this up as I go, but I think you may see even more of it now because the ground is just moving beneath our feet in ways that it only does during a real sort of reshuffling and, you know, revolutionary moment in technology. And, you know, with what the foundation models are doing and the spaces they go into and how they move, it's just not clear what the enduring models and moats are going to be. And so you bet on brilliant people early, and they have a notion and they start building. And it turns out, you know, I would say that Zipline is an interesting one because hardware companies doing wholesale pivots is obviously very difficult. Yeah, you sort of have to start truly from scratch. Whereas software companies, with the pace of development right now, you can do something for six months, decide it's not the thing. You know, Cursor is like a pretty good example of this, right? I mean, we have lots of recent examples of things that ended up being very valuable very quickly and started as something else entirely. And I think you're going to see more of that.
Yeah. D.A., does this happen in bioscience and biotech?
Well, yeah, biotech is a little tough to pivot, right? For some of the same reasons that hardware is that maybe Ben was alluding to. And I think the reason for that is the fixed costs of taking things, particularly into clinical trials, are just extreme by comparison. And so once you start down a path, in particular once you've selected the indication or the disease you want to go after, you're kind of locked in at least through that first human trial. And so we do see quite a bit less pivoting at the later stages, but we see a lot of exploration in the early stages as companies try to take a technology or even a specific molecule and figure out where they can apply it with the greatest impact.
You know, I always tell founders when we invest, keep your eyes in the peripheral vision. Like if you see something off to the side and you're interested, it's okay with me if you go explore it for a week or two weeks, you make an MVP, because man, I see that happen all the time. Founders like, 'Wait, there's something over there.' Our best-returning investment in our fourth fund, Micro One, started — crazy founder, Ali, I knew would be successful at something in life — was just using AI to figure out who was the best developer, who's in the 0.1% of developers. And then he's like, 'Yeah, and by the way, I have friends over at this large language model company and they need data.' So we took the developer data, we kind of packaged it up and we sold it to them, and they want more data. So I think I'm going to try to build them, you know, a way to get data to put into LLMs. I mean, they're at a billion dollars in revenue right now.
And we invested at a $12 million valuation.
I mean, a full-scale pivot. I'm going to take a moment before it gets too late to put on my Plaud device. Plaud device. I'm going to hit record and then I don't miss a moment here. Plaud is an amazing hardware solution. You put a pin on it, you put it on the back of your computer, you record everything. It uses amazing software to summarize it with hundreds of templates, and then you can connect it to all your AIs and do your to-do list, action items, all that great stuff. Check out Plaud at plaud.ai/twist. Use the promo code twist and they know we sent you and they'll give you 10% off. Not that you guys need it, but you can get that. Hey, D.A.
You know, you're very good at finding interesting stories. I think you're a curator amongst curators.
Might come from... I saw something this morning in particular that I wanted to throw to this group.
The managing partner, founder of Dragonfly Ventures, smart guy — Haseeb, or what is it? How does he spell his name? Haseeb Qureshi.
This tweet here. Haseeb Qureshi. Look at what he said. He said founders are now sending them markdown files, company.md files that they can open up with their LLM of choice and utilize to basically grok everything about the company. So rather than a pitch deck or a video or doing a phone call, you can just pull up that markdown file and start asking it questions about the business. And I thought, wow, this is a new thing. I have not yet encountered this. And curious, Ben and Jenny, if either of you has.
Yeah, I'll jump in here. So about a year ago, at Everywhere, we have a full-time engineer on our team. We started thinking about, like, how do we optimize, you know, a small VC so that, you know, we show up in all the searches and founders know about us. And so we did a little bit of research and we saw that actually almost no — it was like 99% of the websites that we looked at of other VC firms weren't optimized for the agentic world, meaning that they didn't have FAQs, they didn't have glossary pages, and basically agents couldn't discover it because the way that they described their firm wasn't agent-friendly. So we were, I think, among the first to kind of do that, and we actually saw the results, which was pretty interesting, of just how that was surfaced about us being a pre-seed fund and all of that. So we kind of jumped in early, and I think that, you know, this was the second manifestation of it. If venture funds are going to do it, obviously startups are going to do it as well. And like, what a cool way to be able to prepare for a meeting before and kind of like self-serve as you're getting to know founders and industries without having to set up a call and do all these things. So I think this is the next evolution of, you know, agentic venture, and I'm all for it.
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By the way, this seems just like a natural evolution. Everyone is clearly feeding all of these materials into some version of off-the-shelf or, you know, internally trained or whatever. Like, everyone's got their own way that they're using AI to help them make decisions and help them get through work. And like, if you want to skip some steps and help us, fabulous. I don't know that we need it. I think we've, you know, built enough AI skills internally where we can, you know, ingest files that are not expressly built to be ingested and we're doing just fine. But I think I most agree with number three here and number four as being the thing that, like, I don't think you're saving me a lot of time. But like, you're clearly expressing that you're leaning in. That will be gone in like six weeks when everyone starts doing it because they know that it's a signal that says something. But I think the neutral read is actually really the key to it, which is like you're going to be a company that is going to — you're comfortable trading on your merits and like what you really are versus some like weird manufactured, like, you know, don't look in that room story. And so like, I think this is a good thing. I don't think it's like changing the world, but I'm all for it.
And Ben, there's an interesting thing that I know Josh Wolf has said in the past from Lux Capital, great investor, very successful firm. Josh has said their biggest success stories historically have been companies that were highly contested among the partners in the investment committee meetings. In other words, you know, one or two people really wanted to do it and others absolutely hated it. And by contrast, the sort of consensus, 'yeah, this is an obvious bet' ones have disappointed, relatively speaking. Now, if we're all going to be feeding presentation materials into our AI and respecting to some extent its opinion, I'm curious for you guys, like, how far are you willing to go against the AI? Are you at a point where you fed stuff in and it said this is a terrible investment, never do it? Are you ever going to supersede it?
So, two things. One is we've all heard that adage about the contested deals or the great deals. I think Sequoia has also talked a lot about this in the past. If that's the case, then we should be concerned about this vintage for late-stage companies, because, you know, the companies that are getting access to the real late-stage capital are all these like highly, highly consensus deals. Now, I can't speak to what actually happens in the partner meetings of these megafunds, but right now we're operating in a market where there's this belief that things are obvious. And so that's just like an interesting little tidbit around the edges of that. As far as the advice AI gives, we get really great analysis and good market mapping and good work. We actually find that the recommendations from AI are, no matter what we do, really disappointingly low conviction. And so we have a scoring system that we sort of play with internally where we like to score deals on a one through nine, no fives.
And one through nine, no fives because cowards pick fives. I do one through ten, no eights.
Because cowards pick eights. Normally it's a world of no sevens, but we could talk about this separately, Jason. But I do think that there is — so we go and we put it in and we get scores between three, four, six, and seven almost 100% of the time, which is just like a pretty weak-willed, you know, it's like a yes but with reservations or no but we could flip it if... And so I find the work to be very high quality. I find the actual answers to be not even particular.
What are the variables? Give us a little hint. Don't give us the whole algorithm. I know it's proprietary. Do you have some variables? Because I'll give up a couple of variables from us.
We have actually a number of variables that I couldn't even like — we're scoring the founder's domain expertise. We're scoring the founder's willingness to be — like how they deal with being challenged in the meeting. We score the quality.
Wait, let's unpack that one. Do you want somebody who is brash or do you want somebody who listens thoughtfully and answers the question, or both of those things? What do you...
We continue to play with these and have multiple agents running that treat these a little bit differently. I mean, this is an imperfect world where we're screwing with this constantly. I think the idea is you want — I mean, I guess the cliche is, you know, strong convictions loosely held or whatever, but you want people who you can have real challenging conversations with, who address those challenges head-on, who don't skirt the subject, who are willing to acknowledge what they don't know. I think that, like, I don't know that we have a different formula than anybody else in terms of talking to somebody who feels substantive and who feels, you know, at the same time passionate and not so insane and stubborn that, like, we're never going to be able to work with them because they have no interest in hearing anyone else's voice.
Yeah, but it's a bunch of these things that we score all at once to try to come out with some overall metric. And then of course we also plug it into our fund model and how many positions we try to get, and it's gone back and studied all of our prior funds and where we find fund returners to try to pull out not just is this a good deal, but does the math or the ownership work for us.
This is a key one, D.A. and Jenny. I have become cutthroat in my later years with the team who are like, 'This is a great thing and there's 100k available at this $20 million valuation.' I'm like, 'So we own 50 basis points. Do the math. That's a $45 million fund. What does the outcome need to be for us if we get diluted 50% along the way? What does the outcome need to be?' And it's like, 'Oh, it has to be Uber. It has to be $140 billion.' And I'm like, 'Okay, not too many of those. So let's move on to the next deal and stay in touch with this founder.' And they're like, 'Oh, but can we put in a little?' I'm like, 'If we put in a little, then I have to go back to the LPs and explain why we did this bet and didn't put in a lot.' And it was a waste of our time because then we put the same amount of work into every founder, the same amount of work into every founder whether it could be a fund returner or not. So you really need to keep that sort of discipline in mind.
I like the signal here. I don't like giving too much of my playbook away, Jenny. You know why? Because then people game it because they listen to the pods and they're like, ask their agents, 'Hey, how can I get through JCal's screening process? How can I get Sequoia's B?' And that's what I realized when I started this podcast over 15 years ago, because every time I explain this stuff, six months later it would be incorporated into people's pitches. And the gamesmanship became crazy. Now I just look for the indatigable — indagable. How do you pronounce that word?
Yes, that's what I was going to say. I think the...
The number one thing we look for is resilience, and how do you gain resilience, right? That's through a series of interactions, and I mean, you can call them tests, but it's really about how that person responds, right? And I think to Ben's point, right, you know, the challenges, the tip on the shoulder, these are all things that you evaluate. So I think resilience is a hard one to gain. I just gave everybody on the team...
Jal, Jal, right? You don't respond to the first 30 emails, right? I wait for 31 now because you just want to make sure they've got that hustle. But I mean, I want to just like stick on this for a second because...
We can't, on the one hand, be perpetuating this story that AI is going to solve everything, going to solve incredibly hard problems in the physical sciences, in biotech, in finance, and at the same time believe that it's not going to be capable of rigorously evaluating companies and ultimately giving us a score other than four, five, or six. I mean, why do you guys — I mean, do you believe, and if so, why do you believe that we should have jobs past six months from now or a year from now? Because it seems like what we do as an analytical and risk-taking endeavor should not be beyond the reach of these AI projects if they really can fulfill the capacities.
I have the answer. Yeah. Remember Chamath started Capital as a Service? Put in all your SaaS metrics, we tell you if you're funded, we just give you the funding based on your metrics.
Yeah, and if in music you'd be like, 'Well, this is a banger. It's got a great hook and, you know, I like the solo here.' If it was that easy, then it would be science, and then on the other side you have art. And I always tell people what we do is alchemy. It's some mystery in between those two things that takes a bit of instinct. And then once you're on the cap table, are you relentlessly supporting the founder and being the guide on the side, the, you know, warm ear who gives them encouragement depending on what they need or helps them problem-solve? So I think that function of just being a human who is enthusiastically on the cap table rooting for you — like if you can get really five or ten really great humans on your cap table who are like, 'Yeah, we can do this, this is insurmountable odds, you can do this, how can we be helpful' — I feel like that part of the job is the most human. But the analyst part, you're probably right.
Look, I agree with you. There's, as we all know, there's the picking them and there's the working them.
And I agree with you, the work them is...
You're right. The analysis should be — you should be able to get great analysis that's better than most of the people on your team, but then maybe the conversation on top of that analysis then becomes the higher-order bid, like, 'Hey, my algorithm says this, your algorithm says that' in the partner meeting, right?
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When we think about how we're using AI internally, it is in service of protecting the, like, real atomic unit of value, which for us is like a minute spent face-to-face with a founder, having like building a real trusted relationship. And so how do we automate away all the rest of our job in order to actually make those human relationships matter and productive? And you know, look, there is some like very grim future where founders would prefer an algorithm to be their investor in some way, I guess. But and I, by the way, I'm not afraid of the algorithm being a better picker. I actually embrace the idea that the algorithm is a better picker. I still don't think the algorithm is going to be able to build the relationships and build the trust. And you know, the role that I like to fill, even though it's a little bit — it can be painful, is I want to be your first call on your worst day. And I don't think that AI is ever going to replace that. And I think that not every founder wants it, but the founders that do are going to pick an investor that they want to have that sort of camaraderie with.
Yeah. I don't think venture capitalists are a profession of the future. Like, I don't think that this job will really exist. But I do think, you know, to Ben's point and yours, Jason, like the cheerleader, the coach, the psychiatrist when you need one. I think these are things that are, you know, very basic to humanity, kind of going back to D.A.'s original topic, and I'm not sure those are going to go away, but I do think our job is going to change.
That's very interesting to me because I totally agree with your points about these services that are provided by really great investors like the three of you. I won't include myself in that, but...
I don't believe in services. I think that's all total BS. And I don't — I mean, the Twitter and LinkedIn and all these founders saying like, you know, 'I want my investor to help me with introductions and products and all this stuff,' and like, no, you just literally at the early stage, at like the pre-seed and seed, you need someone that's not going to be destructive and who's going to be your total cheerleader. I think that's...
So I'm talking about the service that Ben mentioned, which is being your first call on the worst day, you know, serving a governance function as things go further along and you need to make tough decisions, navigate the capital market. You could argue though that all of those very human services, for lack of a better term, or value adds that VCs bring to the table...
Meat-based. They're meat-based, D.A.
These meat services are arguably highly overpaid by founders of successful companies. I mean, it's not unheard of for that early investor who's getting the first call on the worst day to make over a billion dollars if the company goes really well, right? And, you know, you can go hire the greatest performance coach in the world for much less than that. So if we sort of...
But that person also puts their reputation on the line. I think it's a good challenge, D.A., but that person puts their reputation on the line and gives up decades of their life to match capital with talent, and that is a very unique position in the world and is well worth the 20 or 25% that LPs pay for it, and it's well worth the 20, 30, 40% of the company that winds up being given to those LPs and that little sliver of carry that people make, until such time as there's another funding source that does it better, that balances the LP need to deal with chaos. I mean, if you really think of what we do, LPs do not want to go into the muck and the chaotic nature of years one through five of these companies. If they did and they had to deal with the BS we have to deal with on the margins and the chaos and the fraud and the insanity, they would be like, 'Yeah, that's way too gnarly for me.' It's kind of like people who invest in movies or movie studios. There's some studio head and Bob Iger says, 'It's all going to be okay.' Well, I read in the paper that this director just beat somebody up on set, did this crazy thing. 'Nope, it's fine. We got 10 movies. This one gets delayed. It's okay. It's all going to work out in the wash.' I think that plays a role in society.
And then you would ask the same question, D.A.: What's the point of these CEOs? What's the point of these founders? Like, can't we just put everything on autopilot and let somebody just... And I got pitched by a VC, very well known. He said, 'I want you to invest in this company.' I said, 'Okay, here's the founder.' He says, 'The founder is my partner.' I said, 'What?' He said, 'The founder vibe-coded a startup and we're just building it in-house.' So that was my first example of a VC finding a market, going after it doggedly, and just writing the code themselves and being like, 'We don't have a founder for this, so we're just gonna have one of the GPs be the founder.'
Well, I think — I mean, this, look...
Well, this is the next topic. I'm going to tell you about the company that we're spinning out of Everywhere.
What? Okay, it's a segue. I'll allow it. We'll call an audible here. Jenny, over to you.
Well, it was such a good...
And by the way, it wasn't you who did this.
No, I know. I know, but I'm not asking anyone to — I'm not thinking — I'm not asking anyone to invest.
I think the guys are gonna maybe pull up a visual, but here we go.
All right. So as an early-stage investor, a pre-seed investor, what do I spend most of my time doing with 300 portfolio companies? Making introductions to later-stage capital, helping my startups, you know, research who, you know, should — you know, who would be good investors, etc. So, you know, we spend so much time trying to do this, we actually put together a little platform. We built it in-house for ourselves, and then some of our friends wanted this. And basically, we have to beg, borrow, and steal to get this data. As a small emerging manager, PitchBook is about $20,000 a seat, and wow, if you want the API integration, throw in another 15K.
You know, then layer on, you know, things like Harmonic. I mean, these are all great products, but it gets to be quite expensive.
So we built some of this in-house, and now we've started to — we call it Jelly — and we've started open-sourcing it and actually, you know, providing it to other managers and potentially selling it. So we have a beta. We announced it last week. We had got a thousand people on the list, and it gives you some of the things that PitchBook doesn't give you, like insights into what investors are talking about and thinking. Just if you look at this screen right here, you know, what is Jason talking about on Twitter, what's important to him. So as a founder, if you go pitch him, if you want to get in touch with LAUNCH, you kind of know what's relevant. So we tried to synthesize things that we thought were relevant for us and our peers. So this is our first attempt at Everywhere as a venture fund to spin out a product. We are not raising money externally or hitting up, you know, our friends for money. But we will be, you know, selling this product soon. We're having a ton of fun. Obviously, us like everyone, it sounds like, yeah, we're going to sell it. I mean, you know, 20,000 versus — I don't know, you guys can tell me how much we should charge, like 50 bucks a month...
We're taking some input.
Yeah, this is like a very interesting moment in time. I don't know if you saw a similar thing, Ben, but let me replace this one. My friend Kevin Rose, who did Digg many years ago, decided, 'I would like to have a better version of Slack,' and he started building it, and he just gave it for free to the world on GitHub. And I said, 'How long did this take?' He said, 'Four to five hours a day for about a month.' And I was like... And I said, 'How long would it take with Claude 2.0?' Which obviously the answer is half as much. But I talked to him, I was like, 'Are you going to make this into a company?' Because I kind of like the idea. At the same time, Jack from Square launched his own version of Slack for developers. So Ben, what does this say about the future of incubation of ideas and startups and technology?
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Well, I think it says more than just incubation. It says something about more than just incubation. I think this is the great challenge of the market right now, is somebody can go and build something that feels like it is in some way, shape, or form at feature parity with Slack on nights and weekends. Now, I would say sort of a few things. One is obviously the sort of network effect and the distribution remains this important thing, and the distribution providing a user base that then creates a data advantage. And so without a distribution or a data advantage, you know, you're really just vibe-coding. I think there's another layer to this, which is the hardening of that system and building it so that it can really truly support the sort of nuanced needs and the security concerns and the SOC 2 compliance and all the things that you need to build to go around a product that's actually enterprise-ready. I think people understate that. I can go vibe-code this thing quickly, and actually building something that truly does what Slack does is not — like, Kevin did not build that yet, but I'm sure he built something that's good enough for plenty of people. And look, the reality is this is the great challenge of this space right now, and I think it's one of the reasons that you...
The late stage consolidates around companies that appear to have cracked the distribution and data moat, because they go, 'It's going to be hard to compete with this, and I don't want to make a bet on this other new team maybe figuring it out when there's going to be 40 teams or a hundred teams or a thousand teams that can all go build the same thing.' And so this is why Instinct — like, Instinct has gotten into the zeitgeist and has the user pull, and as a result is now worth $30 billion. It doesn't matter what you think it's worth. Like, to someone it's worth — I'm not — to somebody, to somebody it's worth $30 billion. And I think that that is, like, you know, you fall into the too-big-to-fail category or whatever it is, even while Kevin goes and builds that. Slack continues to perform exquisitely well, is probably the best buy that Salesforce has ever made. And so, you know, the SaaS apocalypse of it all hasn't happened yet. Is it going to happen in some categories? It may, but Slack also knows what AI is.
Yes, and probably use some of it.
But don't you think it's cool to be able to serve niche communities? And I think that's what we're trying to do. We're not building this for all of private equity. We built Jelly for our peers, for people in venture capital specifically who can't pay for, you know, this. And I feel like Kevin probably the same. He's not trying necessarily to kill Slack. Like, he's trying to provide something for the people that need something like this who are his peers, right? So I think, you know, the vibe-coding — and I agree, you know, the security levels aren't there — but how exciting that we can all, you know, serve like specific needs as opposed to generalized software for these niche communities.
Yeah. But Jenny, what happens if you sell a thousand seats for $600 a year and you're sitting there and you're like, 'Huh,' and you have 20 more feature ideas and you have four people working on this? You're going to want to add a zero, right? You're going to want to add a zero. And I think that's the danger for the incumbents, is that people are going to come to this. And there was that famous expression, 'Your margins are our opportunity,' D.A. Like...
I'm kind of looking at this going, well, if everything, you know, becomes free, and then people basically — they're restarting the game of Slack. They're restarting the game of Figma and design. It's like, you know what, I can put something out there that my peers use, I get 1% market share, and let's start the game over. Right.
Well, I just think it's an embodiment of the, you know, century-long trend of personalization in every industry. And to Jenny's point, she can make a version of a data platform that is really narrowcast to the needs of a venture capitalist that she knows as well as any of her peers or prospective customers. And then for us on the other side of the Zoom, the question becomes, is she trying to charge us more than would lead us to just build it ourselves, right? I mean, because that's now the new game that everyone is playing, is someone comes to you and says, 'Look, I've taken a month for four hours a day to build this thing.' And it's basically like, do you two want to spend four hours a day for the next month, or would you rather just give me $20 a month? And right, I mean...
I think I'm trying... I literally — you took the word out of my mouth. D.A., Ben, is this literally just we're going to have to rethink pricing of products? If a version of Slack can be made, you know, and be offered at a flat rate instead of per seat, and then some startups are like, 'Yeah, I want to save that money.' It's kind of like free capital.
We announced a deal yesterday in a category where there's going to be multiple players. It's an AI-first law firm where you pay for the work, not for the time.
It's called Black Letter.
They're, you know, sort of Crosby was the first mover. We think that this is a fascinating team out of Cohere that we think is going to do this in a really wonderful way and is building, you know, the best technology in the space. I don't need to give too much of a...
Valuation $12 billion. They have three people.
At least, at least. I mean, you know...
But this is an example of a model where you rethink the model of an industry that's been around forever. We paid for people's time, now we pay for the work. You want to go get a Series B done? I'm going to charge you this much regardless of what — you know, I can guarantee you a quality product with a fixed price. People would prefer that. People would...
And look, I think one of the reasons that you have seen this move in the early stage that I'm sure everyone here who invests is seeing, which is this preference for younger founders — younger and younger and younger and younger founders — because there is now such an emphasis on speed.
And the idea being, if, as you said, D.A., it's like, well, you know, maybe I just want to go build this thing that Jenny's building. If Jenny wants to charge me 20 and I can do it for 19, what's the point? I'll just build it myself. I think now we are favoring teams that we think are going to move faster and faster and faster and faster, and be more and more AI-pilled, and have more like fleets of agents deployed, and cover more ground more quickly, because that is the advantage. That, like, the advantage is that the moats are smaller, and so we favor teams that are going to move faster, and younger people tend to have less distractions in their life and need to sleep less and use more AI and all the things.
All right, let's talk SPVs. SPVs versus funds. I think, Jenny, you found this one.
Set it up for everybody here, and part of being a great panelist is to pick the person you want to pass it to. So...
Okay. Well, I think both of these guys have a great perspective on this. So, family offices put 34% of VC commitments into SPVs, up from 9% in 2019. So in other words, instead of putting money necessarily into their funds, we can extrapolate, they put that money into single-purpose vehicles, which was kind...
of interesting. So I saw this on Twitter, Beezer Clarkson, so she's an LP, she was at Sapphire for many years and has a fund of funds, and she's very active, you know, in kind of talking about the inside baseball of what's happening on the LP front. She's great, you should go follow her. So she asked if the fundraising slowdown, which we're all experiencing and seeing, is capital leaving venture, basically just saying, you know, it's an underperforming asset or, you know, we're going to put our money elsewhere, or just changing how it's invested, meaning into these single-purpose vehicles where the LPs are investing directly into individual deals as opposed to spreading it into a fund. So super interesting. And the thread argues that limited distributions, you know, by LPs towards picking individual companies instead of making, you know, another 10-year fund commitment is kind of the trend of the market. So I looked in my own LP base and we do have, you know, a number of family offices, and I would say this does actually track for us, where our LPs are even more interested in our later-stage deals, right? So these deals are more derisked and, you know, less interested in putting money directly into funds. And so we've felt that as a small manager, where they've kind of rebalanced where they're putting their money, and I think other emerging managers are feeling it as well. So I'd love to hear from Ben, actually, because I imagine when you started, you know, all those years ago, your fund, it was smaller and you had kind of maybe less institutions and kind of smaller folks, and if you've seen anything like this.
Yeah. So first of all, I think like the misleading thing about this is the percentage of that money that went into SPVs and OpenAI and Anthropic is enormous. And so this overstates that trend because you have two companies that in four years consumed more venture money than any companies in the history of humanity. And so that's one. And so I think it's really important to note that, like, I don't think, by the way, I think this is a real trend. I just think that it's a little misleading when you have two companies. Usually the biggest and best companies don't just need constant infusions of tens and tens and tens of billions of dollars.
