The Exchanges

Q to take money off the table with the essential private markets, given how big a name you are and how big a position you often have? You're just a big piece of a cap table. For someone like me, it's much easier to sell out in a later round. Are you able to, and do you have that discussion internally of, hey, We should take chips off the table now.

A We could, but we historically have not. And so, you know, for the most part, for the companies that have decided to stay private, we've been really excited to, to stay in them, keep backing them. And that's probably the strategy that we'll, we'll continue to have. You know, I think this staying private dynamic is a little bit overblown because I think there's some idiosyncratic reasons why certain companies have stayed private. Um, and many companies, many CEOs that I talk to, they are very happy to be public or they're excited to go public. So, you know, I tell our CEOs all the time, I've been fortunate to work with a bunch of public companies. Never one of them has said, I regret going public. And so, uh, I think for most of the companies that we're talking about, they'll wait longer than they had historically, but they will still end up going public.

AI assessment note: “We could, but we historically have not.”

Q mentioned, like, making competitive categories there. One I just can't get over, dude, and I've tweeted this, is the customer support category, because there's just, like, 50. Like, there's so many. And, like, Brett and Sierra is obviously, like, you know, the OG of OGs of SaaS. Like, can you help me? Why am I wrong on being so confused by this space? Because there's just something for every vertical.

A Yeah, well, I think there's a good reason why there's excitement in the space. It's Better, faster, cheaper already today with today's model quality, with the reasoning capabilities, you know, with the cost of the models. And so you don't need to believe any future state of a different product or a different, you know, model capability. The functionality is there. And so, you know, I think there's good reason why, you know, we, we, um, you know, we put on EBCs for our portfolio companies. Every time Decagon appears in one of these EBCs, there's extremely high interest and, uh, and, you know, most of the time conversion to a deal. So I think the market pull, the market size is what is most interesting about that space. You know, Jesse and Ashman, this is, again, this is not my deal. It's Sarah and Kimberly's, but They are special founders. They're really, really good. They're relentless. They're the kind of founders that we really love to back. If you look at like SaaS and cloud markets, about half of them are winner take vast majority, like the overwhelming majority. And about half of them, you know, they're sort of a sort of breakup of market share. So for example, you know, you mentioned deal like payroll, payroll market, like payroll market is not a winner take Vast majority market. Uh, there are many markets like this and in SaaS and cloud. And so it's possible that, you kn…

AI assessment note: “I think there's a good reason why there's excitement in the space.”

Q Totally get that. The bar for other companies is also way higher, it seems, and my question to that is, dude, I'm sitting on a lot of great enterprise software companies, and then, you know, we were, I was always taught, dude, that you're going to get great funding if you treble, treble, double, double. Is trouble, trouble, double, double dead in this new world?

A I don't think it's dead in this new world. I, I tend to think that companies are The number one way to measure a company is ultimately return on invested capital. And so the way you do that with an early stage company mostly is efficiency of customer acquisition. And so not every company needs to go, you know, zero to a hundred, like it depends on what market they're in. Uh, but I do think the companies with AI, if there's very sort of starving and customers momentum gives you High momentum gives you a chance to build a moat. And I think that's the most important thing about this sort of debate about how, how high of growth is, is good enough. Um, it depends on the market you're in and some markets, like they're not going to move as fast, but in the markets that are moving really fast, if you're not moving really fast, you know, that's a, that's a risky place to be. But I think the most important thing about momentum is just, you know, it's relative to your peer set. And so if you're, you know, if your peer set is growing really fast and your competitors are growing really fast, You know, and, and it's, and it's, you know, high retention and customer acquisition is, is relatively easy. Like, you need to be growing really fast too.

AI assessment note: “I don't think it's dead in this new world.”

Q Do you think the market will evolve with like open AI winning consumer and anthropic winning dev and B to B?

A Yeah, I think they actually will, um, diverge in pretty meaningful ways. Um, this is sort of what we've seen in historical technology markets, but I think each will try and remain competitive in their spaces. And so, you know, uh, B to B Anthropic is certainly putting more resource after it today. Open AI is going to have a really good B to B business. They already do. Uh, so I think that market is going to be pretty competitive. Um, you know, not just, not just coding, but general B to B API usage and moving up into the application stack. Both of them are, are obviously trying to do that. So I think that market is going to be pretty competitive. I think Google will play some part in that market. Um, but you know, the big head to head competition will come, you know, between open AI and, and anthropic on the consumer side, I think, you know, it's chat GPT, like ask, Ask my family in Kentucky, what do they use? You know, they, they know what, what is AI? They know Chattupt. They use Chattupt, you know, extensively. Google's going to take a crack at, and they already are, uh, trying to compete in that market. But I think, you know, brand and the best product in the market can take you a really, really long way. Uh, and so, you know, as we under have, have kind of underwritten future rounds of open AI or later rounds of open AI is very much, you know, with the mind of, of consumer…

AI assessment note: “Yeah, I think they actually will, um, diverge in pretty meaningful ways.”

Q Totally get that. The bar for other companies is also way higher, it seems, and my question to that is, dude, I'm sitting on a lot of great enterprise software companies, and then, you know, we were, I was always taught, dude, that you're going to get great funding if you treble, treble, double, double. Is trouble, trouble, double, double dead in this new world?

A I don't think it's dead in this new world. I, I tend to think that companies are The number one way to measure a company is ultimately return on invested capital. And so the way you do that with an early stage company mostly is efficiency of customer acquisition. And so not every company needs to go, you know, zero to a hundred, like it depends on what market they're in. Uh, but I do think the companies with AI, if there's very sort of starving and customers momentum gives you High momentum gives you a chance to build a moat. And I think that's the most important thing about this sort of debate about how, how high of growth is, is good enough. Um, it depends on the market you're in and some markets, like they're not going to move as fast, but in the markets that are moving really fast, if you're not moving really fast, you know, that's a, that's a risky place to be. But I think the most important thing about momentum is just, you know, it's relative to your peer set. And so if you're, you know, if your peer set is growing really fast and your competitors are growing really fast, You know, and, and it's, and it's, you know, high retention and customer acquisition is, is relatively easy. Like, you need to be growing really fast too.

AI assessment note: “I don't think it's dead in this new world.”

Q Like, what one really lingers? For me, it's Revolut and Deal.

A Yeah. For current companies on the model side, Anthropic has done a really great job. You know, we're not investors in Anthropic and they've, they've done a really good job. And so, you know, I think it's one of those cases where similar to cloud, like if you could own all of AWS, Azure and GCP as independent companies, You know, like that would suit you pretty well. And again, that's, that's one of those markets that was not winner take all, even though it's a scale market, you know, it's sort of oligopolistic. Like if the model companies turn out to be something similar, given, given how much we expect demand to grow, um, you know, that's, that's probably one.

AI assessment note: “For current companies on the model side, Anthropic has done a really great job.”

Q I believe that kingmaking does exist, and kingmaking, for those that don't know, is when a financier is able to bluntly invest so much that they are unable, able to anoint a winner in a category, and that then leads to moats and everything that comes with it and ultimately winning. Do you believe that kingmaking exists, or do you disagree that it exists?

A As we think about investing in companies, so we always seek to invest in the winner. Uh, if the investment thesis is our investment is going to make them a winner, it's probably a pretty flimsy investment thesis. Now, an investment that we make in a company that is already attracting resources, hiring really well, able to raise capital well, um, able to deploy more money into go to market, able to deploy more money into R&D, It can, it can generally help. Like, this is the whole theory of preferential attachment, which is, you know, why increasing returns to scale is a concept, right? Even if you're not a network effect driven business, if you're salesforce.com or, you know, Workday or ServiceNow or CrowdStrike, the more you become the leader, the more resources come your way, and the easier things get for you, potentially. Uh, and so we look for situations like that. I would contrast it with situations You know, like, the original SoftBank Vision Fund did a lot of really good things. Honestly, they, they did a bunch of really good things, and...

AI assessment note: “if the investment thesis is our investment is going to make them a winner”

Q mentioned, like, making competitive categories there. One I just can't get over, dude, and I've tweeted this, is the customer support category, because there's just, like, 50. Like, there's so many. And, like, Brett and Sierra is obviously, like, you know, the OG of OGs of SaaS. Like, can you help me? Why am I wrong on being so confused by this space? Because there's just something for every vertical.

A Yeah, well, I think there's a good reason why there's excitement in the space. It's Better, faster, cheaper already today with today's model quality, with the reasoning capabilities, you know, with the cost of the models. And so you don't need to believe any future state of a different product or a different, you know, model capability. The functionality is there. And so, you know, I think there's good reason why, you know, we, we, um, you know, we put on EBCs for our portfolio companies. Every time Decagon appears in one of these EBCs, there's extremely high interest and, uh, and, you know, most of the time conversion to a deal. So I think the market pull, the market size is what is most interesting about that space. You know, Jesse and Ashman, this is, again, this is not my deal. It's Sarah and Kimberly's, but They are special founders. They're really, really good. They're relentless. They're the kind of founders that we really love to back. If you look at like SaaS and cloud markets, about half of them are winner take vast majority, like the overwhelming majority. And about half of them, you know, they're sort of a sort of breakup of market share. So for example, you know, you mentioned deal like payroll, payroll market, like payroll market is not a winner take Vast majority market. Uh, there are many markets like this and in SaaS and cloud. And so it's possible that, you kn…

AI assessment note: “I think there's a good reason why there's excitement in the space.”

Q get to two 50, and then four X to get to a billion, and then three X to get to three billion, and then, which is all pretty optimistic fucking gross rates, and then with a six X in public markets or seven X, we're looking at a, what, three X on the cash on the price that we're paying today? Wow, that's not a good opportunity cost dollar spent.

A I've been historically surprised at how good the best companies can be and how fast they can grow, especially in markets that are early innings with a big technology shift. So I'm very optimistic. Those are abstract numbers. I also don't think that every great high growth company will end up trading for six times in the public markets. There are some that are going to trade higher based on very high growth rates or high cashflow. And so, you know, it's hard to debate Like an abstract financial case. Uh, but, you know, for, for most of these companies that we've backed, these, these winning apps, they're growing faster, three X faster, you know, than predecessor SaaS and cloud companies. And so, you know, sure, the high, high valuations from the outside, I think in many of those cases are warranted.

AI assessment note: “sure, the high, high valuations from the outside, I think in many of those cases are warranted.”

Q But, but an ultimate one, if you could change anything with Inside Andreessen, what would you change?

A I wouldn't change this, but one of the elements about us scaling has been, we've had to decentralize the way we run our business. Right. And so when I first joined the firm, you know, we used to sit around in partner meetings all day, uh, on Mondays and hear all the pitches from all the various sectors, uh, you know, on Mondays and then on Fridays too. And so, you know, obviously that's not a scalable, uh, Approach to doing venture, especially given, you know, we're in a bunch of different sectors now, but selfishly at the growth fund side, like that was extremely high signal, great information, you know, tons of, tons of soak time with all the best thinkers.

AI assessment note: “I wouldn't change this, but one of the elements about us scaling has been”

Q At what point does the entry price do you think for OpenAI become not a good use of dollars? This is one thing where I'm permanently, like, reflecting on it myself, where it's like, you know, if you think it's a two trillion dollar company, well, you can still see a forex from here. At what point does the opportunity cost no longer make it worth it?

A We have to constantly reassess this. So again, you should look back at our investment case for investing in Databricks, you know, in 2019. Like it's, you know, we did, we did an investment out of our growth fund. It was one of our first investments, the largest growth fund investment in fund one at six billion dollars. And our investment case never would have predicted, uh, you know, what, what they became. And so we have to constantly push ourselves and think about, you know, Um, how big they can become. I, I've been surprised at how big and absolute dollar terms the companies can be and how good they can be. So we constantly have to push ourselves on this. The example I always use is, you know, Google and Facebook. Like, 10 years ago, Google and Facebook were monetizing their users at like one-seventh of what they are today. And it's just hard to, it's hard to forecast that. It's hard to model that. Um, but it would be limiting to think, you know, you're ever at like an end state of productivity or end state of new products. So, you know, we've been, we've been surprised. We like to invest in the ones where there's a theory on how the core market can be bigger than we would expect or others would expect. You know, Stripe is an example of this. SpaceX with Starlink is an example of this. You know, Waymo when we invested is an example of this. And then we also like to invest in…

AI assessment note: “We have to constantly reassess this. So again, you should look back at our investment case”

Q Completely agree. So I'm an institutional investor with a ten billion dollar endowment fund. How should I change my asset allocation between P, Venture, Publis, given that blurriness, merging, lack of clarity that you just mentioned? What would you genuinely advise me?

A I'm heavily biased. Uh, and you know, look, I, I recognize that many of the endowments have kind of They have a starting position, which is, you know, I think many have probably find themselves a little bit over allocated to, to privates. And so I don't know how to assess that relative to the, to the future outlook. But if I take the future outlook only, um, where do I think of the most attractive opportunity set? Like if you just start with where the 10 most valuable companies in the world are today versus 25 years ago, like, Eight of the top 10 are U.S. West Coast based technology companies, and, you know, they were venture backed. Uh, and so if you assume that the future is likely to be, you know, something similar to what's happened in the last 20 years, I think the most interesting place to be is, is this asset class, you know, which has exposure to what those next generational kind of dominant companies can be. And so, you know, I think the allocation should reflect this sort of melding of what, Used to be part of the public markets that no longer is, uh, that's sort of a, you know, a newer, a newer asset class. And so that's one piece of it. You know, my, my friends in private equity do an amazing job. They have incredible returns.

AI assessment note: “I think the allocation should reflect this sort of melding of what, Used to be”

Q Completely agree. So I'm an institutional investor with a ten billion dollar endowment fund. How should I change my asset allocation between P, Venture, Publis, given that blurriness, merging, lack of clarity that you just mentioned? What would you genuinely advise me?

A I'm heavily biased. Uh, and you know, look, I, I recognize that many of the endowments have kind of They have a starting position, which is, you know, I think many have probably find themselves a little bit over allocated to, to privates. And so I don't know how to assess that relative to the, to the future outlook. But if I take the future outlook only, um, where do I think of the most attractive opportunity set? Like if you just start with where the 10 most valuable companies in the world are today versus 25 years ago, like, Eight of the top 10 are U.S. West Coast based technology companies, and, you know, they were venture backed. Uh, and so if you assume that the future is likely to be, you know, something similar to what's happened in the last 20 years, I think the most interesting place to be is, is this asset class, you know, which has exposure to what those next generational kind of dominant companies can be. And so, you know, I think the allocation should reflect this sort of melding of what, Used to be part of the public markets that no longer is, uh, that's sort of a, you know, a newer, a newer asset class. And so that's one piece of it. You know, my, my friends in private equity do an amazing job. They have incredible returns.

AI assessment note: “I think the allocation should reflect this sort of melding”

Q At what point does the entry price do you think for OpenAI become not a good use of dollars? This is one thing where I'm permanently, like, reflecting on it myself, where it's like, you know, if you think it's a two trillion dollar company, well, you can still see a forex from here. At what point does the opportunity cost no longer make it worth it?

A We have to constantly reassess this. So again, you should look back at our investment case for investing in Databricks, you know, in 2019. Like it's, you know, we did, we did an investment out of our growth fund. It was one of our first investments, the largest growth fund investment in fund one at six billion dollars. And our investment case never would have predicted, uh, you know, what, what they became. And so we have to constantly push ourselves and think about, you know, Um, how big they can become. I, I've been surprised at how big and absolute dollar terms the companies can be and how good they can be. So we constantly have to push ourselves on this. The example I always use is, you know, Google and Facebook. Like, 10 years ago, Google and Facebook were monetizing their users at like one-seventh of what they are today. And it's just hard to, it's hard to forecast that. It's hard to model that. Um, but it would be limiting to think, you know, you're ever at like an end state of productivity or end state of new products. So, you know, we've been, we've been surprised. We like to invest in the ones where there's a theory on how the core market can be bigger than we would expect or others would expect. You know, Stripe is an example of this. SpaceX with Starlink is an example of this. You know, Waymo when we invested is an example of this. And then we also like to invest in…

AI assessment note: “it would be limiting to think, you know, you're ever at like an end state”

Q Let's do one more. So let's hear from David George, who runs Andreessen's Growth Fund. David, how do you think about price and price sensitivity today?

A I wrote a piece about this called When Entry Multiples Don't Matter. I'll just talk to you about our process, and then I can address the valuation points. So we first start, we assess the company, we assess the market, We assess, you know, founder, all independent evaluation. If those check out, then we spend a lot of time on valuation and scenarios and making sure that we see our way to target return. So the best thing that we can do is invest in great companies that are growing very fast because those afford you more degrees of freedom on valuation. They're the ones that are more likely to deliver upside scenarios. So one of the frameworks that we use and talk about a lot, and it's, you know, this is relevant for valuation because it speaks to the flavor of companies that we tend to match make with. Is, you know, we look for what we call Glengarry Glen Ross market structures. So, you know, the famous movie, you know, we can't get this wrong. Like this is like independent evaluation. We just absolutely cannot get this, this piece wrong. So what that means is there's a scenario. Have you seen the movie?

AI assessment note: “I'll just talk to you about our process, and then I can address”

Q much cash. The prices are so high. It's just much harder to do those multiples with the entry prices that we're paying. I had Layla From Capital G on the show. She said that prices are two X what they were a couple of years ago on average entry price for her. I'm interested, like, how do you think about your own price sensitivity today, given where we are today?

A Yeah. Look, this is a fantastic question. I wrote a piece about this called when entry multiples don't matter talking a little bit, it touched on this and other things. I'll just talk to you about our process and then I can address the valuation point. So we first start We assess the company, we assess the market, we assess, you know, founder, all independent evaluation. And so if those check out, then we spend a lot of time on valuation and scenarios and making sure that we see our way to target return. So the best thing that we can do is invest in great companies that are growing very fast because those afford you more degrees of freedom on valuation. And, you know, I talked about the upside scenarios, like they're the ones that are more likely to deliver upside scenarios. So one of the frameworks that we use and talk about a lot And it's, you know, this is relevant for valuation because it speaks to the flavor of companies that we tend to matchmake with is, you know, we look for what we call Glengarry Glen Ross market structures. So, you know, the famous movie, you know, we can't get this wrong. Like this is like independent evaluation. We just absolutely cannot get this, this piece wrong. So what that means is there's a scenario, uh, have you seen the movie?

AI assessment note: “I'll just talk to you about our process and then I can address the valuation point.”