Sequoia & the Hewlett Foundation on VCs NOT raising funds, Cisco's $1B AI fund, and more! | E1973

Is there an advantage to being AI native architecture versus traditional software SaaS architecture with an AI feature? In other words, are we disrupting a generation of SaaS with AI native applications? That, to me is the critical thing. The hyperscalers will have a business model like you say, whether it's inference, as a service, workload as a service, they will figure it out. But it's everything else that the venture ecosystem is funding and has funded over the last six years. That is where I'm trying to figure out the technical assistance and that is what Konstantin and I talk about this.

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Off@Devsquad.Com twist welcome back to this week's Liquidity Podcast. With me today I have Konstantin Buehler from Sequoia. Next we have Anna Marshall from the Hewlett Foundation. Of course we have Jason Calacanis from the Launch Fund. I'm your moderator, David Weisberg, co founder of 10X Capital. Today we have several great topics to discuss. The number of VCs who have decided not to raise another fund has doubled from the same time last year. Cisco is investing $1 billion into the AI startup ecosystem. And we'll finish with the latest three investments from Konstantin and Jason. Before we dive in here, I'd love to hear a little bit about Sequoia's relationship with the Hewlett foundation. And how did you and Konstantine meet?

I met Konstantin at an annual meeting many years ago. Hewlett has been part of the Sequoia family for over the 20 years that I've been there. It was a relationship that preceded me since I got to the foundation, and my job at every annual meeting is, yes, to hang out with the managing partners, but it's also to go and develop relationships with all the new talent. And at one annual meeting, Konstantin and I struck up our conversation and I am very deep in the weeds in tech and so I love having my conversations with Konstantin on whatever the newest thing is in tech and we go deep, deep, deep on things like AI or crypto or any other subject.

Great.

Well, let's get started. According to Pitchbook, the number of VCs who don't plan to raise another fund next year doubled from 6% for the first half last year to 13% for the first half this year, though likely to be double from last year. This number is likely underreported given that 38% of VCs disappeared from deal making. With only 2,725 active firms in the market right now, considerably down. Konstantin, obviously Sequoia doesn't have much issues fundraising, but you are affected by this weaker venture market. Is this reflected in the pricing and valuations you're able to achieve today?

So first, David, you pulled up the chart. This is canceled or pulled in, it looks like. And I imagine how much of that is being pulled in. I mean, people are taking a longer time to deploy. I don't know how much of that is actually we're not going to go. People are not going to go raise another venture fund versus they're extending the length at which their current venture fund is going to be deployed. And frankly, that's a responsible thing to do. And I can speak to the value of time diversity and I think that's probably good for the industry. You asked me about valuations. It's a little bit of tale of two cities right now. Now, we have not seen a correction in valuations across AI world. Those valuations remain very high, 20, 21, 22 type levels. We have seen a production in valuations on traditional software as a service businesses, consumer businesses and the like. Those are a lot more involved fundraising processes for companies and the valuations reflect it.

I would just add that from an LP perspective, because of AI, there is a lot of sort of the pacing of new investments, whether they are in AI or not AI, which is how the world seems to be sorted these days. In the Valley, I would say that we're seeing great companies being funded by our partners in non AI sectors at reasonable valuations. And I think we also have to take into consideration it looks slow versus the last three or four years, but it's not slow. When you look at sort of the last 20 years of venture fundraising, I would say that we're probably going back to a normal pace as opposed to the frenetic pace that we were at. So I would just put it in context.

Jason, your thoughts?

You know, I speak to a lot of fund managers. We created something this year Inside of our company called the Whisper Network. I'm always trying to productize what we do as a high scale investor. We do 100 new investments a year through our different programs, founder, university launch, accelerator like Y Combinator or techstar. So we really want to meet a lot of other funds so that we can share with them the early stage companies, year zero, year one companies we're investing in so that they can pull through and raise a seed fund or a series A from, from other great funds. And there are a lot of emails not getting returned. And I think there's a lot of VCs who are out of market, they're not actively investing, they're managing their existing funds. And I would say these numbers, you know, 6%, 12% are probably low. A lot of people aren't clearing market. And I think there's going to be some capitulation where people realize, man, venture is too hard. It's really hard. You have to wait 10 years. You could hit these storms like we just went through for the past two years. LPs are racing expectations, they're sharpening their pencils. Everybody's getting very focused on exits. And it feels broken right now. The venture ecosystem feels a bit broken. When you have, you know, SaaS, companies trading at 5, 6, 7 multiples in the public market and then 100x or 50x in the private markets, how does that gap get closed? And it's really, you have to have a lot of faith that these companies are going to break out. And the power law, man, unless you've experienced the power law yourself with a bet, it can be very hard to wait for your moment in time to hit one. And I think that's what's happening right now. People who maybe started funds in the past five years, started investing at the peak of the cycle. Now they're seeing all those markdowns, seeing shutdowns and maybe they're realizing, I'm not going to hit an outlier, I'm not going to be part of the power law. This is too hard, I quit. Which, you know what, it's probably a good thing. We probably got a little bit too big. It's a boutique industry. It probably shouldn't have as many people marking up investments, you know, at 50x or 100x revenue. And if you have too many people doing that and fighting for too few strong deals, then your entry price gets screwed up. And the exit price we know because of public market. So I think the industry still has a lot of indigestion to work through. And people shutting down their funds and not raising another one is part of that. It's part of that capitulation. Just like sometimes founders have a hard time shutting down their companies, I think some of these funds are having a hard time shutting down. And yeah, it's a moment of reckoning for a lot of them.

Constantine, Jason mentioned the power laws. When funds like Sequoia and you focus on the early stage as funds get larger, are you still looking for every investment to return the fund, or is there some other calculus that you're going through?

Yes, I work on the early stage teams, seed series A efforts, and for those, we absolutely need that type of power law return on every potential investment. We do look for companies that have the potential to be so big that they can return the fund or more. I want to just double click on something that Jason said a moment ago, though. He was talking about how this total disconnect between public markets and private markets and paying 100 times ARR and what companies are actually at today is bad for fund managers. I just want to point out it's also really bad for founders. I mean, working with founders the past 10 years, when you can raise at a high valuation, generally that's directionally good if you're one of those power law businesses, because it means less dilution and you're on a path that has same type of outcome with more ownership for the founders. But in all the other cases, it's actually a ton of money that goes onto a preference stack and the preference stack gets thicker and thicker and thicker. And that's actually really rough for a lot of these founders. You know, as the audience probably knows, a preference stack needs to be paid back in an acquisition first. So it actually operates somewhere between debt and equity. And that's not good for founders who are not on the right side of the power law. And then also they end up operating companies for years more than they really should because they still have capital to burn or to at least see how they're able to build the company with the amount of capital remaining. And they've got a bunch of investors who, to Jason's point, want to see it through or want to see if they can see it through. And it is just as big of a problem to the founders as it is to all these venture funds right now. And it's going to take years to play. Jason, you've seen a couple more of these. Anna, you've seen a couple more of these. How long did it play for this to actually work out of the system? I was kind of hopeful. 2022 correction comes along. 2024, we'd have it worked out of the system, but it's still working through the pipes.

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And you see a lot of these startups raise massive amounts of capital and sometimes they literally end up being roadkill for some of these disruptions like AI. How does that play out? When you see these startups that have hundreds of millions of dollars on their balance sheet and no real exit plan, what happens in those cases?

So it depends on why they have the hundreds of millions of dollars. So if they have hundreds of millions of dollars because they were opportunistic founders and they saw that in 2021, it was very easy to raise capital. But what we really focus on is what are they doing with this capital? So what is the return on that dollar of capital that they have in place? If they're investing it for a future market share gain, if they're investing it for, you know, market dominance, new ideas, new pipeline, new products, that's a very different thing than if they are doing ping pong tables and giving it to their employees. Like, honestly, like we look at the return on capital employed and try to understand why it is and what is the end product of those dollars. So you can't make a blanket statement like, you know, a company that just has a couple hundred million dollars on their balance sheet, that could be to do good, to really make, you know, grow and invest in their business for five years from now. Or should the best thing for that 500, $500 million be that they can't see their way out of the box and therefore they should actually return it down to, through what Constantine was talking about, through the waterfall, and actually try to fold this, recoup as much money as possible, move on and move on to their next startup. Like not every startup in the old days, a venture, 25 to 40% of startups failed. So like not every venture idea has to work. And I think we've forgotten what that's about. I mean venture was one of these industries where yes, it's a power law, that one, you have to underwrite everything for that one thing to, to deliver the fund, but you also have to be realistic about your chances. And just being like left for dead on the side of the road with like 15% growth is not what venture's about. Sometimes it's better to take your $300 million that you've got in the bank and put it down the waterfall and let people move on to the next thing so that the return on invested capital can actually change.

Yeah. And if you look at it like a poker hand, sometimes your starting hand looks really great. It's a great team, it's a great market. And then you get the product out there and the product's not very good or it doesn't connect with customers. And sometimes you got to fold the hand, right. Like you could have ace, king and pre flop and you get 3, 4, 5 comes out on the board and you're like, gosh, I think I'm going to be barbecue sauce here. I should just let this hand go if somebody's shoving all their chips in. And I think that's really hard work for Managers, especially these new managers. So to dovetail that experience of the founders with the managers, we've gone through our portfolio recently. We're doing this, like, summer of, you know, assessment of the portfolio. And we just basically said, one, two, three, One, we've got companies that are clearly growing. Three, we've got companies that are in the process of accepting that this is going to be shut down or sold or merged or whatever it is. And the founders have kind of made that clear to us that, you know, they're in their last hurrah and they're doing that. And then there's this big open number two section, which is, hey, we're figuring it out, right? And so at the scale that we invest, you know, when we have those number ones, we know what we have to do. Put as much money into them as possible, get good dollars into those companies. With number three, you know, we're trying to encourage the founders to, hey, wrap it up if you don't think it's going to work out. And let's talk about your next company. Let's talk about the next adventure. What did you learn here? Because a lot of times our second investment with the founder is the big winner. Superhuman comes to mind. We had invested in. When I was a Sequoia scout, Raul's first company, Rapportive, sold it to LinkedIn. It did fine. We tripled our money. It was a 50k investment. We got back 200k or something, quadrupled our money. And I just said, hey, Raul, promise me I'll be the first investor in the next company. And we put 500k into superhuman when it was just a tiny little company, was an idea, actually. And so we really want them to move on and wrap it up. And then I think some funds are having that same experience. They just, they didn't hit it. So what are you going to do? You know, you're probably either going to shut the fund down or you're going to try to raise a fund with no performance. It's really hard. And LPs now are cutting their commitments while they wait to get dpi. So I think some people are being realist now and it takes, you know, driven humans. Sometimes they hold out hope. They're holding out that, like, 5% chance that they hit that last ace in the deck or whatever card they need, whatever magical card on the river. It's a magical. It's called the magical card. And a one or two outer for a reason. It's probably not going to happen. So you got to be realistic about it. And I think people are figuring that out this year.

Constantine, how do you look at a lot of emerging managers bring you investments for, for the Series A and for seed as well. What do you see in the emerging manager space today?

Look, the emergency manager space is, is still very active because they raised all these funds, you know, one, two, three years ago. And I think that the quality of companies that they're bringing at the seed and Series A are, are really high. We partner with a bunch of early stage funds or seed stage funds that find businesses in a particular vertical, a couple that come to mind virtue which is specifically focused in the health care vertical or working with the folks at GG1 who focuses in going global. So products that actually can go global and those specialized funds are really interesting to us because you're able to hey, understand this person is exceptional at seeing everything in the market under this area and sharing the things that are most promising with us. At the same time, I do think it's been pretty challenging to be an emerging fund manager. It's not easy to show dpi. It's not even easy to show TVPI with your new funds. And by the way, that's by far the easier of the two to show. And I do wonder how it's going to play out for a lot of emerging managers. I'm optimistic that if you put in great work, you'll get great outcomes and we have a lot of friends in the emerging manager space. We have a whole ecosystem fund which is all about helping emerging managers. It really came out of the structure that you were describing earlier, Jason, where we had the successful scout fund, helped launch amazing scouts like you, Jason, over the past decade. Plus how do we actually grow with them more actively? We weren't able to do that as effectively, you know, 10 years ago. Let's have an ecosystem fund that's going to help managers grow beyond an initial scout and into more and more of an emerging manager. We also partner with a variety of funds through that and then also even a fund, a fund in Sendana Capital which is a LP in early stage seed funds. And so we see a lot of activity there, a lot of companies coming out of these emerging managers and frankly a thousand flowers blooming is really great for the entire ecosystem and what we're hopeful for.

Yeah, it's a great time I think to have programs like we have. Thank God we have our accelerator and then we created this pre accelerator founding university I talked about a bunch of times where just two or three developers, creatives who aren't even incorporated yet, can work with us for 12 weeks to kind of polish their idea and then perhaps get incorporated. If they think it's a business, and if they don't, that's fine. And we offered them 25k checks and we've done 80 of those 25k checks already. Everybody thought in my internal team, hey, this is crazy to put 25k in for 2.5%. And I was like, is it? Because that would be like, right before techstars, right before our accelerator, right before Y Combinator, we've got 20,000 people applying for funding and half of them fall into this category. Let's see if we can capture that. And I'm really excited that we have, because trying to compete at the Series A, space where these things are all overvalued and it's super competitive, is really hard. So as a manager, you have to kind of find a place to be super helpful to founders. If you find a place where you can be really, really helpful to founders and you love it, I think you'll be fine. If you're trying to compete with Sequoia and Benchmark and, you know, Founders Fund on a Series A, I think you're going to get your butt kicked. I'll be totally honest. And I think that's where a lot of the emerging managers tried to compete and it did not work out well for them. I think they overpaid for companies that maybe weren't great or maybe weren't the right teams.

This is one of the things we respect a ton about you, is the innovation there. I mean, going further upstream, if you view it as a stream, where the top of the absolute source of the stream is all these great individuals who come up with an idea or might not even have an idea, and they end up saying, hey, do I take this risk or do I not take this risk? Well, historically, you've waited for accelerators to have the idea and the person and have the person already and have a pitch and an application. And so I love what you're doing of finding people even earlier, risking less capital, but enough to actually contribute time and effort and say, hey, you know what, I'm actually going to spend a few weeks or months developing this idea, seeing if it turns into something. And by the way, the person who makes that first bet on you, you are so loyal to them. So to all the managers listening, the amount of loyalty to someone who makes the first bet, I know the person who made the first bet on me as a investor when I was in grad school. And I was a AI engineer grad student who had some interest in investing. And Kevin Hartz was a top speaker. And he said, hey, I'll give you couple hundred thousand dollars to start investing. And that turned into a great multiple for him. That was huge for me. I still think about it to this day. I'm still grateful to him to this day. That was more than 10 years ago. And so finding those people super early, top of funnel, less competition, more distributed, more local, and the way to win in the long term. Could not agree more with you, Jason.

And you know, to just give you a little story there, little story time. In the early days of the Scouts program, I started something called Open Angel Forum. I would just bring five or ten angel investors together to look at new ide. And one of those was Uber who came to it. Another one was Jonathan and Marco from Thumbtack. We put a small check in. We were the first investors in Thumbtack through the Scouts program. People don't know this. I introduced them to Ruloff, to Michael, to Daglioni, everybody. And they passed on the Series A. Jed Katz did it over at Javelin. And then Marco and Jonathan figured it out and Sequoia did the Series B in Thumbtack, famously. And Jonathan contacted me about a year ago, six months ago, and said, hey, I got a new company. I need you to be the first investor in my new company. I was like, jonathan, you're rich. You know, you're doing fine. Why do you need me? He's like, oh, well, we've got like millions of dollars in ARR. But I. You're my good luck charm. I need you to be my first investor in Athena. And I said, tell me what Athena is. We had dinner. And so if you go to Athena, wow.com. now, it's the first time I've ever endorsed a company as like their spokesperson. I'm the spokesperson for it. When we did this whole big marketing push for them and I put the first million dollars into the company outside of the founders, and they raised a huge round. It added like $10 million in ARR. And so this can go full circle where you can really be helpful to these founders and they'll remember and give you that opportunity to be the first investor in their next company. And so your reputation is built by how helpful you are. And yeah, thank you for the kudos.

Absolutely.

And Anna, is that the secret to success? I know we can't talk about all your funds you've invested in, but you're pretty much in every great Fund is it just being earlier? How have you been able to build your relationships with VCs?

So I would say that the VC firms, like every other company, is like a living organism. And so you have to look at what a firm is doing and how it's evolving, how it's developing its bench, how it's. What are the principles, what are the people who are doing the deals, how networked are they? And so that changes over time. And our job is to have, you know, we have a venture portfolio where we only have 10 managers. Like, we really have 10 core managers. If you're a Hewlett venture manager, it's because our bar is so high. We've been fortunate to be on Sandhill. We've been fortunate to have these great relationships. And there are some firms where we will hire every once in a while, every couple of years, we find a new firm to back and we will do a check and we will just sort of take that flyer on a new fund. But it's very much of a portfolio where we believe that in venture at least, the access and the reputation of a firm still attract the founders. And it is that competitive advantage is unlike any other asset class in my portfolio. And that hasn't eroded.

So you are looking at Anna, does that manager connect with founders?

Does the manager connect with founders? And does the manager have the network to be able to access the best founders, be able to get on those cap tables, be able to get the ownership interest that we desire? Because we know by the time the company goes public, we will be diluted enough to where we need to really have really good ownership interest at the beginning. And more than anything else, do we think that the partnership thinks so far ahead that they're able to have the right team in place to have that technical expertise? And so that's why I spent so much time with sort of with Konstantin and with people like Konstantin's peers across these firms, because I learned so much from them about what they're seeing in the marketplace. And that informs not just my opinion about their firms, but my opinion about what we should do with our venture portfolio, how this ripples through our public equity portfolio, how it ripples through the buyout portfolio. I mean, it has implications for capital allocation across the entire web.

So I want to kind of bring this full loop here because Jason and I were just talking about the importance of being there early, the loyalty of being there early, the value of actually being a true partner to a company from start to finish, and then how that compounds over time and how you get the call in the next one, et cetera. Anna, you have a repeating game. And you are one of the most legendary and prestigious foundations and LPs there is, full stop. And I want to kind of connect these two because you also get to know people really early. I've been at Sequoia five years now, first LP meeting, first one that I was ever invited to. After joining Sequoia, I was going around doing my best job, trying to engage with the limited partners, and you tracked me down, Anna. You said, hey, can we sit and have some breakfast? You'd done all this research on me, asked me all these excellent questions about artificial intelligence and my grad work in IT and all the technologies that I was looking into and the recent investments in the portfolio, and you'd done the research on all of that. And that left such an impression on me early on because at that first meeting years ago, no one else had done that kind of work or research to understand so early. And I think that's the connection. The relationship has really grown still because you said, hey, I understand where this person is expert, where he can add value. I want to connect early on. Even though as one of the best LPs in the world, you don't have to do that, Jason. You don't have to find people when it's 25k and not even an idea and help develop it with them. And by the way, Sequoia doesn't have to do that with legendary founders from Idea from Inception as well. But, but that's how you become excellent. You find people early on, you invest early, you do the extra work. And I certainly feel an extra closeness because of that to you, Anna. And so I'm grateful for you, for you doing that as well.

It's very much a part of the Hewlett culture, which is these long standing partnerships. I mean, we do projects like in Western conservation, where we literally have spent 20 years restoring the Klamath River. So part and parcel of the culture of the foundation is to be long term partners and to help partners become the best version of themselves. And when I was saying firms evolve, firms evolve. Like the managing partners leave, you can get the next generation. I mean, in some of the firms we're with, we're on the third generation of investors. And you have to be able to identify what it is that that next generation brings, how you can help them become the best version of themselves. Because when the firm does their best work, you as an lp, get the best returns. And so it is very much of.

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Speaking of partnerships, Cisco is getting into the corporate AI game by launching a billion dollar fund to invest into AI startups. The fund has already committed into Cohere, mistral and scale AI and has already deployed $200 million out of their fund. Konstantin, you not only invest in AI, you actually have a master's in AI from Stanford. How do you look at the AI ecosystem today and where do you see the large AI players positioning themselves?

Only a billion. I'm kidding. That's a huge amount. The number of people that have raised AI funds or strategic AI funds or the rounds. The rounds in AI space are shocking frankly. And I don't see how in aggregate they're sustainable. Like individually, there will be exceptional investments. Without a doubt, this is a transformative technology that's decades in the making and will have decades of run. However, I don't see how the aggregate dollars invested are going to create the kinds of returns that the Annas of the world and the Hewlett's of the world and Jason's LPs and your LPs David expect. I really wonder how these mega rounds play out in aggregate. Things that I'm interested in that Sequoia is interested at this point. There's been a lot of build out in the infrastructure layer. Things are going well there. There's been a lot of spend actually in the infrastructure layer. I think that's actually become, I wouldn't say mature, but that's developed probably as we would expect it, where a lot of innovation budgets are spending on inference or training and that's moving into production and that's yielding some nice revenue growth. Now I think we're starting the application era and that's what I'm super focused on and we're super focused on is finding great application layer companies in artificial intelligence. How do you build a great application layer company in artificial intelligence? Well, it's all about the human. I think AI actually makes it more about the human, not less about the human, because your moats and your barriers of entry are actually going to be less about the technology because AI can actually do much more of that technological work and much more about how you make something sticky to a person, how you make it something that they engage with and that one person is going to be able to do a lot more work. So we're looking at AI applications that do that effectively and we'll talk about a couple of them. And in the recent investments at the end of the, at the end of.

The show, I would just add that I think part of what you're seeing is we literally have team meetings where we start every week with like this week in AI, like the speed at which things change. And so you see your man, you know, some of these rounds and you're like, wow, that's a lot of conviction for a technology that is changing faster than anything we've ever seen. And that to me is just, I'm not sure. I'm not here to make a judgment of whether that's hubris or whether that's great. But I do think you need to consider the evolution of business models as you're doing this. We saw this a little bit during crypto, where all of a sudden our brains had to get around. Are there different business models? And I'm not sure we know what the business models will look like in The AI app world, is this going to be like an inference as a service? Are we going to do discrete workloads? Are we going to do edge AI? There's a lot of things that I think we don't know. And so going slow and steady and trying to figure out, is transformer technology here to stay forever or are we moving to something else? All of these things, I think, merit a prudent judgment in deployment of capital as we see this wave take off.

Yeah, I wouldn't read too much into the tea leaves of Cisco with 20 billion or whatever they've got and in cash laying around and a profitable business throwing $1 billion into the space because it might be their hope is to get BD deals out of this. Right. We've seen a lot of round tripping or boomerang revenue. We've talked about it a bunch on the different podcasts. And so maybe they just feel like we have to have a little AI pixie dust here. Maybe that's their way of educating their team and looking. They've always been a very acquisitive company. They were known for M and A over the decades. So, you know what's really interesting is the application level that is emerging and we're in a little bit of like a trough of despair. You had this like massive hype when people are like, wow, this thing can do anything. And then they were like, oh, I just checked the facts. Two thirds of the facts are wrong. And now we're in the put up or shut up phase. I think Anna sort of alluding to that is like, how does this thing actually make money? And are you going to pay an extra 10 bucks a month per person per seat on Slack for AI? I'm not. We, you know, I just saw that pop up and I was like, yeah, I don't think I need this, but we do pay for a Corporate account for ChatGPT4O. I've been, you know, paying for Claude and some of these things and I'm watching the results and I'm like, this is saving a really large amount of time. So everybody's had the moment where research or some job was done by these AIs in verticals where it saved a ton of time. So it's definitely here to stay. And it's going to be subscription model, it's going to be infrastructure payments, it's going to be all of that. And the founders tend to figure this out. It reminds me a lot of what happened in the app space where entrepreneurs got really excited because it Was like a new format with some new hooks into it. Oh, I can use this on a mobile phone. So the person's got it with them all the time. Okay, that's interesting. Oh, it's got GPS built in. Okay, that's interesting. Oh, it's got a camera. Okay, Instagram, you get the idea. People started looking at the feature set of the device and then backing into experiences. That's what I see people doing with a lot of these AI models. They're like, what can it do? Okay, let me see if I can build a product out of that. We have one I've talked about here, Saga, which is doing like, it started with screenplay writing. There's a famous piece of software called Final Draft. So they kind of like, we're going to make an AI Final Draft. And then they started doing storyboards. And so now like people in Hollywood are like, make me some storyboards of this action sequence. And AI is like really scarily good at that and it unlocks a lot of creativity. And so this idea that like even the people in Hollywood who kind of thumb their nose at AI, they're all using it on the DL. They're all using it to come up with ideas, to write jokes, to do dialogue, to try to figure out interesting scenes or views and angles to do. So every single person's job is going to be impacted by this. Everything's going to be made more efficient and people will be willing to pay 20 bucks a month, 200 bucks a month for it if it saves time. And you just think about, you know, the amount you can save on salaries if you make somebody who's a hundred thousand dollar or two hundred thousand dollar asset inside an organization, if you make them 5% more efficient, it's 10K. Or if you don't have to hire every 20th person because everybody's getting 5% more efficient a year with AI, which seems like a very low benchmark if I'm being honest. So I think this is going to be the greatest efficiency revolution ever. I do think there's going to be a lot of white collar middle manager product managers who have hit peak salary in their lives and they may not be able to hit those salary notes they hit. So it's going to be pretty chaotic. But I'm liking what I'm seeing from founders. Early on they're really running their companies with AI and building AI into their thing. And when they run their companies with AI, I see them writing content faster, making videos faster, writing code faster, doing sales faster, organizing data faster. Just they're they're like bionic, they're like little superheroes. Like they got some superpower just based on being able to use these tools. So it's, this is the real deal. This is not crypto. In my mind, you know, crypto was like an intellectual weird grift where people were like, yeah, I can sell and exit my position before I launch the company. It was like really weird moment in time and they will look back on it as a complete grift and a failure if I'm being honest. 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Anna, you mentioned what's crazy about AI is there's tens of billions of dollars going into it and not clear business models in different cases. Do you expect this to be kind of like the early 2000s where there's a couple winners and if so, you know, if you had invested in everything like Google and Amazon, you would have done pretty well. But do you expect some of your funds to do really, really well and some of them to, to have a couple bad vintages?

So this really tells you how old I am before you could make the investments into Google and Facebook and all of those there were the people who laid the cable for the Internet, all of whom overspent. Things like Global crossing, companies that no one on this podcast has ever heard of that overspent and built the infrastructure to allow the Internet to flourish globally. And we didn't actually see the fruits of that investment until we saw Facebook and Google and all of these companies get created in 2004. But prior to that, from basically 1998 to 2002, a huge amount of capex investment like you're seeing now. I'm not saying today's is any different. Today the business model for the hyperscalers is very clear. You invest in having it and you have a cloud business. It's sort of a loss leader for your cloud business. It's great. The cloud business is the business. And the more enterprises want to have secure walls for their data, the better the cloud business is going to be. So there is definitely a business model for the hyperscalers. Whether there's a business model for all of the apps and everything that we've seen. I think what's really interesting to me, and I would love to throw it out to this group, is is there an advantage to being AI native architecture versus traditional software, SaaS architecture with an AI feature? In other words, are we disrupting a generation of SaaS with AI native applications? That, to me is the critical thing. The hyperscalers will have a business model like you say, whether it's inference, as a service, workload, as a service, they will figure it out. But it's everything else that the venture ecosystem is funding and has funded over the last six years. That is where I'm trying to figure out the technical assistance. And that is what Konstantin and I talk about. So I'll throw it to Konstantin first.

Well, I'll jump in and say one of the main reasons why AI first companies are succeeding and will succeed is because of what Jason was describing. They just move faster. They use these technologies to get more done faster, more efficiently. And I don't think that using AI in the product itself is going to be enough differentiation, period, full stop. You have to solve a real problem. You have to integrate this new capability, which is knowledge as a service, into some application that solves a real new problem for your customers. But moving fast is a sustainable advantage for any company. And the ability to integrate AI, cut costs, boost efficiency, that is lasting. I wanted to connect two things here, which is all this AI conversation and Cisco and their Cisco AI fund. And it kind of gets to how I think about the huge amount of investment in the past couple years in AI. To me, all of this investment in AI is kicking off an AI era. This is the starting gun. This is by no means the end of it. And we're going to see in the hard work over the next 10, 15 years how that plays out. There have been 12 companies that have been the most valuable company in the world on the S&P 500 in the past 100 years. And I just want to run through them really quickly because they each were more or less starting guns to major technological revolutions. 1925, AT&T most valuable company 1927. So that was telephony, 1927. General Motors, that was the automobile revolution. 1955 and that actually General Motors kept for 30 years. 1955. Dupont Chemicals, 1957. And these two are tied. Exxon, that was the era of oil and petrochemicals. 1967 kind of this initial movement towards computing in IBM and that lasted all the way until 1992. And by the way, that is the case for Nvidia enduring because IBM was kind of this foundational layer for the compute layer for almost 30 years until 1992. Philip Morris, Altria Group, for a very short period of time, just eight months, until Walmart in retail, then General Electric, Microsoft, Cisco. And Cisco was the foundational layer for infrastructure for the Internet. And so that was the Internet revolution. Cisco was peak.

Apple.

These are the first times they became the most valuable company. Obviously there's a lot of back and forth. Apple then and that was the really mobile era and now Nvidia. And that just happened in 2024. And that is the past 100 years. Every single company that has been the most valuable in the world on the S&P 500, every company has been tied to a major technology revolution. You've never seen a most valuable company that isn't tied to a long term trend. These are enduring. I think Nvidia is a great sign that the AI revolution is going to be invested in for 10, 20 plus years. And we have to be really smart about the companies that we pick to partner with to build legendary companies from there.

Yeah, I think that's exactly correct. It's a great overview and there's going to be a ton of winners here. I hope with this next administration. It seems like it's going to change. I'm not making any political commentary here. We got to get M and A back on the table. We got to get M and A back on the table. There's so many Great companies here that are being built, that are hitting tens of millions, hundreds of millions in revenue, that maybe they're not going to be standalone IPO candidates, but would be incredible acquisitions for the Googles, Apples, even the Ubers and Airbnbs and Coinbases of the world. We need to have a high functioning M and A ecosystem and we don't have it right now. Everybody's scared to, you know, after Figma, they're just scared to even try to sell a company that's dysfunctional. You know, now on the other side, not going public and staying private forever, that's also dysfunctional. We need a really much more vibrant M and A situation here. And I don't know how we get there without, you know, somebody other than Lina Khan being in office.

So we need some DPI for anna and our LP friends.

It's more than DPI. I mean I get that LPs like you're painting LPs is all they care about is DPI. And yes, we care about DPI. But part of the reason we have venture in our portfolios is because we are investing in innovation. And so we want to see innovation, we want to see these founders, we want to be able to back these founders that are going to create and continue the US dominance technology. But we feel like not every company can be a legendary standalone company. Some companies create just great technology that can then be commercialized much better by somebody else. And that is part of the US innovation ecosystem. And I feel like that is what is being stopped. It's not like the greedy dpi.

Yeah, no, it's not like people are just like, give me my money. It's, I think a healthy ecosystem, to Anna's point, needs to have a place for the mid market companies. They just need to have a place to land where they can. That technology and that team can be fully utilized to create productivity in the world. And that's what's missing.

And it's all the way back to the start of the conversation. It's, it's people's highest and best use. Right. Like if you can make the impact on the world that you want to more effectively by being part of a huge platform and you built a great product that plugs in nicely. Don't waste the time like go, go get it into the hands of everyone.

Yeah. Sequoia knows this. You sold YouTube for 1.6 billion.

And it's maybe a little early.

That might have been a little early, but they did have the sword over their neck with that lawsuit. But then you sell WhatsApp for 19 billion. Right. So like these are two extraordinary sales. Could those companies, you know, YouTube maybe could have been, you know, you could do all the hypothesis, you know, hypotheticals you want. Maybe YouTube could have survived, but it probably would have got crushed by the lawsuit. And this was a different era of venture capital. There weren't unlimited amounts of money for a company with a trillion dollar lawsuit over their head. And Google was brave enough to take that risk. Right. And so you just, you need to have homes for these places.

I'm very curious. Constantine, you're a great first principles thinker. Do you ever invest into companies that you think will be only M and A? Do you ever go swing for a triple at the seed stage or at the early stage?

So I don't think we've ever set out for that. But we're, we're, we're pretty sober that that is a large probability of any given distribution. If you reach for the stars like you, you might fall and catch the moon or, or something along those lines. But we never kind of reach for the clouds. Right in, in other words, we reach for the stars. And you know what, like, let's do our absolute best and we will see where that goes from there.

Yeah, it's fine to have a backup plan, but you don't want to make the. I never make an investment thinking, hey, you know, Microsoft's going to bail us out on this one. It's nice if that's a possibility. If you build a great team, you got a good customer base, you got some solid tech. But it's not, that's generally not where the power law takes place. Right.

David, what you're getting at is the difference between early stage, which is like seed, and early stage, which is where Jason and Konstantin live, and then the growth stage and just the shift in what venture capital has become over the last 20 years from very much of an early stage industry to having an industry that has evolved into the at bats might be smaller in growth stage, but the dollar checks just overwhelm the amount of money that's gone into early in series A. And so you're talking to three people that like spend their life thinking about venture as very much of a massive multiples. A 3x would be like no one would ever approve a deal. If you thought you were going to get a 3x in venture, the risk reward just wouldn't make sense. And so venture became sort of, this venture has evolved as an industry over the last 20 years as more and more money has come in and sort of started this growth effort. Some growth efforts are extraordinarily successful on their own merits. Some are not. What you've seen, there is more willingness to underwrite to a 3x or a 2x, and the lines have blurred between sort of what used to be growth buyout and growth pre IPO stage of venture capital. So I think that's where the 3x doesn't really apply to Jason and Constantine.

Because they're just like, yeah, we've got to be. We try to underwrite everything to a 5000x minimum. Right. Like, we're getting in at a 1 to $15 million valuation. How does this become a unicorn? Is like the whole name of the game.

Now onto our lightning round with everyone's latest three investments.

All right, Just three quick ones. Super proud of the fact that many of our Foundry University companies, I explained earlier in the program, these 25k checks, a lot of them are getting accepted into other accelerators. So we'll sometimes make the 25k check and then they'll come to our accelerator. Other times they'll apply to another accelerator. So tax GPT is a copilot for CPAs. We put in, you know, a little bit of money. They got great product velocity, some traction with customers, and they got accepted to Y Combinator. Again, the application level, verticalized AI. I think this is, you know, gonna be a big winner. This next one fitted great app for people sharing their daily outfits. And then there's this big recycling trend amongst young people. Millennials, they don't want to buy sheen disposable clothes. They care about the environment. Again, a very small investment for us. We helped get the product going with the team and they also got accepted to Y Combinator, I believe. And then Cicada, we found this artist, a musician, wonderful individual, who started growing his mailing list and trying to figure out ways to earn more money by selling merch or engaging with fans with this interactive media. So you could be a fan, you could ask for a cover song, etc, you can tip. And this is really becoming a thing, just like podcasting is becoming. You know, there's a long tail of podcasting, people making a living from it. Cicada is helping people monetize their passion for music and gigs, virtual and real world. They just got accepted into tech stars. So this is a big focus of what we're doing at our firm. Every year I try to make a new focus for our team. Sometimes it's every six months. We really worked on a couple of years ago getting massive Amounts of deal flow. Now we have 20,000 people applying for funding. We can't possibly get more applications for funding. Then we did a big push. How many meetings could we do with founders? We started breaking 100 introductory meetings a week over zoom. That got crazy. It was almost too much to process. And now we're focused on what I mentioned earlier. And then we also did decision making, how to really make thoughtful decisions and what we're looking for in companies, multiple developers and builder founders, product velocity, great design. And we have a whole framework of 13 reasons why we invest in 25 red flags. Finally, this second half of the year, I've been working on this Whisper Network which is us saying, hey, this, this founding team got traction. And then hey, here's some people at Sequoia, here's some people at Craft, here's some people at Valor, here's people at techstars, here's people at Y Combinator who should know about the company. And we really kind of serve these companies up to those interested parties on a platter with very detailed specifications. But we know what they like. So we know this firm loves, you know, multiple co founders who are technical. This firm loves go to market and they love marketplaces. Okay. And we put that in our database and now we have 450 members of the Whisper Network across our 11 investment team professionals, about 40 people each. That means we can really customize the pitches. So every week, twice a week, we say who should know about this company? We go into that list of 450 and we find the 30 people we think need to know about the company and we really customize an introduction to that firm of why we think it's a fit for them and it's working.

I'll jump right in. And first, Jason, thank you for Whisper Network. We certainly appreciate it. And it is one way to get in touch with us at Sequoia and certainly such a smart value add for the huge shop of Funnel and the great companies that you work with throughout.

Thank you.

Yeah, smart innovation like venture changes just like any industry. So I'll also screen share and share two that are announced and one that is public. So this first one is called Dust. Dust TT was founded by second time founders who'd sold their first company to Stripe. One was an OpenAI researcher. They started the whole Europe office because he was so good back in the day. The other one was a brilliant product mind who ran French product org in Alan. And really what it does is they said, hey, we have this new capability with LLMs with AI how do we make a productivity suite that's as fluent as Slack for you to communicate with AI, be able to communicate with the information in your enterprise database and actually have a product that makes you super productive? So let's just try it out. I'll call GPT4, I'll also call Mistral. I'll also call Anthropic. So what you see me doing is call GPT4, Claude and anthropic. Just like I'd call someone in Slack and I'd ask them to please give me a rundown of the VC Market in 2024 Conversation we talked about just a moment ago. And what you'll see is it's querying all of them in parallel. And first thing is I get to say, hey, actually I really like GPT4's answer to this one. I might prefer Claude's in another one, I might prefer Mistrals in the third and I can actually have them build on each other. So I can ask Mistral and Claude to then add citations to the GPT4 example answer above. And they're really good at adding these citations. And you'll actually see a, you'll actually see that they're pulling in, yeah, they're pulling in some of these citations to make it much more rigorous. So you actually have these AIs working against each other, but also with each other to have much better solutions. This is just the tip of the iceberg. It also does multi action. It also queries my entire internal database here at Sequoia. So if I'm doing diligence on a particular company, I can write an entire memo with a single query. Or if we do market research, let's say market research. Tell me about the VC market in 2024. That's a custom bot that's built from a lot of these. And what you'll see is it's going to do exactly what I like. It has headlines, it's highly quantitative, it's actually giving a rundown. I've already told it and designed it, how much hallucination, temperature, et cetera to include in this. And it's pretty phenomenal. Huge productivity booster in my work and I think the future of AI is going to be many of these AIs working together.

It's one AI checking the other AI and making sure like they are better at spotting the mistakes than we will be. And so I think this is, this is a huge deal.

So thank you for saying that. And yeah, try it out. Number two, this is a brilliant team. Four postdocs three postdocs and a Stanford professor, Christos Kozerakis, another Greek. Jason, who are some of the best in the world at not just computer vision, but technologies relating to actually pipelining and analyzing computer vision. And they are taking on the body camera market. So there's a huge body camera market. It supports tens of billions of dollars of market cap. Currently it's almost exclusively focused on body cameras for police. And by the way, that's really good for police because one, it keeps police safe but two, it also helps with the integrity of, of patrolling and service and making sure that things are well documented so that both police and civilians are behaving appropriately in these circumstances. PLICS has said we're going to take this, we're going to bring it to the private markets. We're going to make it so that a private security guard can have an AI enabled camera that understands the world around it actually makes inferences around the world around it verifies that all the doors that are being checked are in fact being checked, infers exactly the behavior that the security team has to, has to take from there. So this is a example of a hardware/ software Computer vision business going into an existing market and opening up new doors with a great technical team. And the third is actually a stealth company, but I will give you guys a little bit of context because it is officially the newest. So this is a go to market oriented agent. So the idea is you've had Salesforce for the past 20 plus years as your single source of truth. Now you can actually have, yes, your sales development REPs and your AES and all of that plugged into Salesforce. But you can also have AI agents plugged into Salesforce. They can make decisions, they can be constantly talking to you Anna. If you're the ae, they can say, hey, by the way, you can upsell Jason who's engaging with your product in this way or that way or the other way. You can actually engage with them a little bit better by doing this action or the other action. So it's constantly monitoring the single source of truth and helping you make better decisions. They've already got customers like Confluent and Laceworks up and running to double the sales productivity pipeline. And this is a team that's built AI and go to market at Google, at Cisco, at New Relic and a bunch of other places. So those are our recent three.

You just got a customer. I just signed up for dust TT 29 bucks a month and I just did three queries that I was recently doing. On Claude and ChatGPT4O in separate windows and now I've got them consolidated. Pretty clever idea.

Welcome in, welcome in. Thank you, Jason.

All right.

But again, one of the things that you, that I think it bears some watching is how much of this stuff is being done in experimentation and then the lag time between when experimentation by all this, you know, the other startups that are. I think one of the lessons of the last three years has been you can't just sell to other startups guys. You have to sell through to actual enterprise customers that will have long lives and so and lots of seeds and so how long it takes for enterprise customers to actually adopt and change internal processes.

You are so right, Anna, that it'd be an issue you Maybe about six or seven years ago I realized this trick because somebody at an accelerator explained it to me. They're like, yeah, we got 20 customers. I'm like, how'd you get the 20 customers? Like, oh, well, I went to our internal discussion board, I won't say which accelerator, I'm not trying to give anybody a hard time. And they just said, hey, can you, can 20 different people buy my product and I'll buy yours? And they did their own little round tripping thing. So what we did in our diligence and we do diligence even at the seed stage, which is nuts. People tell us our diligence is insane for doing 25, 125K checks. And I say the reason we do this is because we're trying to train our founders on what diligence is so that they're smarter and they have it dialed in when they go meet with.

Sequoia or Craft or Ingredients, such a service.

Yeah. And we basically give them the diligence list and we walk them through and they're like, we don't have, you know, enough employees for any of this to matter. Anyway, putting it all aside, we tell them, give us your 10 customers, top 10 customers, what date they started using the product, when they churned, if they churned, and then tell us how you source them. And we put in there, we tell them and we understand that you may have asked your friends and family or previous colleagues or cohort mates in your class to buy your product. So just note that for us and then tell us like Even if like 8 of the 10 you got cause they're friends and they're doing you a favor, let's focus on the two that you know, you earned on LinkedIn or through a cold call and it just kind of diffuses the little scam that goes on where people are doing this, but we've caught people. And the. The other really interesting hack, Anna, was people would take their hundred K check from their accelerator and they were told by their mate at the thing, here's what you do over the 12 weeks. Week one, you spend $500 on Facebook ads. Week two, you spend a thousand. Week three, you spend 2,000. I think you get where this is going. And then you have this beautiful curve of website visits and of people trialing the product, and then you sell that to a bunch of dentists who are coming to demo day. These things do not work on real investors, so you may be able to fool the dentists. You will not fool Sequoia or lunch. We will find out immediately. And then reputation goes down as opposed to up. And you're trying to build your reputation up, not down. Public service announcement.

Thank you.

You wouldn't believe what we find in diligence.

Totally.

Oh. Oh. Considered.

Maybe she would.

Maybe you found somebody.

We had somebody cast on diligence.

We had somebody literally, like, took their family on vacation and like their Airbnb, their ski trip, champagne. I was just like, did you accidentally use your corporate card for this stuff? And they're like, no, I just didn't pay myself a salary, so I took the equivalent in like vacations. I'm like, IRS is going to consider that a big no. No. They're like, really? I'm like, income tax, sales tax. You're breaking all the tax rules. Like, look up Imelda Marcos. Like, she went to jail for this exact thing.

Yeah. These are the people we do not want to partner with. And the person you're doing the biggest disservice to is yourself.

It's crazy. I mean, I understand, like, you thought your off at home office. I get the home office thing in the age of remote. But the ski trip. No. No ski trips. Please wrap us out of here, David.

Well, it's been another great episode of Liquidity podcast for Constantine Buehler, Anna Marshall, Jason Calacanis. This is your host, David Weisberg. Thanks for listening.