there is absolutely no doubt in my mind that excess capital distorts company behavior, okay? And in particularly these early phases, it's very difficult, it's not impossible, but it's very difficult to stay fit and efficient when you have a buffet of all options sitting in front of you and you can fund all of them.

Scarcity breeds necessity, scarcity breeds innovation. So I think if you're on the board of a company or a founder of a company or CEO of a company, you have to think long and hard about the negative cultural and negative fundamental effects to your business of taking too much capital.

(upbeat music) - Hey man, good to see you, happy Saturday pod. - Good to see you, sir. - What's been on your mind? - Well, look, I mean, so much has happened and I think we took a few weeks off. So like, it almost feels like the world has changed dramatically from when we last talked.

So there's a bunch of different things on my mind. I've been thinking a lot about the, I'll call it the pre-IPO market. I don't know why I don't wanna call it late stage 'cause I think some of the money has moved down to companies that are even pre-revenue, but the pre-IPO market I think is changing dramatically.

I think there's always this interesting question of where are we in terms of reality and perception on whatever the newest trend is. And we've seen that with other things like crypto and whatnot. And I think it's interesting to think about that relative to AI. And then lastly, one topic I really wanna get your opinion on, after some of the earnings releases since we last talked in the software category particularly, people have thrown out this question, like is software as we know it dead, which is obviously overly provocative.

But there are a lot of questions around that and a few people weighed in and I'd love, so anyway, I'd love to talk about all three of those things if you're up for it. Well, no doubt about it. And it sounds like we have our agenda, but before we jump in, I have to say, I was driving in this morning and I don't know, I'm just reflected in a reflective place.

I mean, my oldest son, Lincoln turned 16 this week and my mother turned 88 and it's just a moment, just a moment. My mom sent me this note. Well, she actually sent it to all the kids and I just, I have to read a bit of it because it goes to how I'm thinking about things and she's 88, right?

So she starts by saying, I was born on this day in 1936, right between the Great Depression and World War II. Times were tough, we didn't have much, but we shared what little we had. Does that sound bad? Nope, these have been the best 88 years possible to be alive.

Sure, I've seen lots of bad stuff, assassinations, bad politicians and wars, lots of wars, but the good outweighs the bad by a long shot. Just think about what I've seen. The first TVs, the first commercial flights, the first computers, the first mobile phones and Google and now even chat GPT.

The world's gotten better in almost every way. We live longer and healthier. We solve problems we could never have dreamed of and we're all more connected. I wish people weren't so negative. Let me tell you the struggles of no food or housing in the Great Depression or being shipped off to war at 18, knowing you wouldn't come home, that is hardship.

But the truth is I understand people feeling overwhelmed by all the hustle and bustle today. I too have a love-hate relationship with technology myself. While I know it's made the world better, I didn't realize how lucky I was to grow up in small town America at a quieter time.

It was a simple life, long walks and card games, fewer friends, but you shared everything. So enjoy your technology, but never let it rob you of the personal touch. It's a tool to use. You should run it, don't let it run you. But never turn against progress because without it, we go backwards.

And personally, I can't wait to see what comes next. That from like an 88-year-old woman. I mean, I was so blown away by just that perspective, her optimism and just like the framing of her life. It really was like all the innovation we've seen, like it compressed into such a short period of time.

And so I know today we're gonna talk a bunch about where markets are going and is software dead and where are we in the age of AI? But it just caused me to think we live at such a unique moment in human history. I mean, I think you would agree, just innovation of all sorts, it's raging at a pace that you and I have never seen.

And it's not an accident. Like there's been all this attack on capitalism and free enterprise over the last few years, but it is in fact that system, that and a direct result of that system that inspires and incentivizes people to dream and to build this stuff. And I was looking at the Starship launch this week, which is just this insane feat of human engineering.

I mean, in four launches, right? We now had a soft landing in the ocean. This is a ship that nobody thought was ever achievable. It's gonna make us a multi-planetary species. And I saw the looks of exhilaration on the faces of those young people in the control center. And I just told my kids when we were watching that, I just said, find something in life that makes you feel that way, right?

And I think that may be Elon's, frankly, greatest legacy is just the motivation, the inspiration he's giving to all the generations that are coming up, right? To dream big, to think big, to build stuff that matters. I think that was only half of your mother's message, by the way.

Yeah, I mean, like, you know, I think it was the part to me that really inspires me and motivates me. And, you know, I'll get off the soapbox, but, you know, as we start diving in here, the one thing I'm just thinking a lot about is we as a country need to make sure we don't screw this up.

It's the system that's creating all that prosperity. It's the system that's creating, you know, the advances in biology, the advances in space, the advances in AI. And certainly they'll have challenges, but it's an extraordinary time to be out here in Silicon Valley doing what we do, so. Well, and I, you know, adding on top of that, something we talked about in one of our first episodes was that Reagan speech that he gave.

And one of the reasons why the U.S. has been so successful is open skilled immigration and getting the best people in the world to come practice their craft here. And why we have limited that and not advanced it is shocking to me. And there will be ramifications 'cause the technology allows those people to stay in other places if they so choose.

So you gotta make it easy for 'em. Yeah, no doubt about it here, here. Why don't we jump into, I guess, the first topic, you know, about this new reality in the late stage market. Why don't you take us through what's piqued your interest there? So let me walk you through this.

And you and I have talked about it in the past, but I think I've come around to a new perspective. So I've lived through two different major cycles, venture cycles, and, you know, I've watched there be high periods of liquidity where a ton of returns are made in '99, kind of 2021, even kind of '07, '08.

And then frequently on the downside, like '01, you just see a washout, right? And I've seen people completely cleared out. And I've often thought about there are changes to the venture industry that are systematic, like increasing competition has been completely linear and systematic since I joined, but other things are cyclical and they come and go.

And I think I had always thought that the presence of large amounts of money, presumably easy to get in the private, in the late, well, we say late stage, but it's come so early, I don't think that's the right word, but the large, let's just say large round private market.

I've come to believe that it may be a systematic trend and not a cyclical one. And there was a mini correction. I think you have to call it a mini correction in venture in 2022, 2023. A lot of companies did layoffs. You had right sizing. You had a lot of talk about free cash flow and profitability, but then the AI wave came and then the AI wave got so big, right?

What's AI as a percentage of venture capital right now? 50% at least. Yes. And so, and that market is behaving almost like it was prior to this mini correction. And so I look around and at some of these data points. So there was an FT article since you and I talked last that someone aggregated the cumulative losses in the food delivery business at $20 billion.

And that's just not your grandfather's venture capital industry. That's something new. There are four companies in the coding co-pilot space that are not named Microsoft that have raised over $200 million each. And we're just, these companies are all of a year and a half old, right? Right. And so it's just a different world.

I look at someone posted just the investments Sequoia has made in Elon's companies. And they were rounds that were in the, you know, 500, $600 million range. And there were three or four of them. And once again, just not the historic venture capital model. Lots of money, lots of, you know, you're in this world.

So don't take this the wrong way, but like these people are getting two and 20 to write a check for three or $400 million and not take a board seat. And for the listeners that may not know that two represents an annual management fee, not a one-time management fee.

And it's taken generally over seven, you know, seven to eight years. So that could be 10% of that money. So they're getting- Although I would point out, Bill, I think on some of those very large multi-billion dollar rounds where the investment size is multi-billions, I think there are creative fee structures.

I think what's more standard is like zero and 10 or one and 10. I've heard those things are changing. Yeah, yeah, fair enough. I think that's a fair point. But I guess my point is, I think this is more permanent. I think it would take a massive shake out, like a gargantuan '01 style or more to change this at this point.

Well, I mean, listen, I totally agree with you. In fact, you know, you and I have talked about this for well over a decade. You know, in fact, part of the reason I started Altimeter and part of our thesis in 2005 is we thought companies would stay private longer, more of the value capture would occur in the private markets because they would scale faster.

Now, at the time, we thought it was because they would also be more capital efficient, right? Think Google raising less than $40 million pre-IPO. But, you know, I think a lot of this has to do with the function of changing market structure, both technology, the way it scales, regulation, making it less desirable to go public, and frankly, the development, right?

The market development and responding to that is just a much deeper and much more liquid pool of capital for companies that choose to stay private. So, you know, I pull up a couple of charts here, but let's ground it in some facts. Over the last 10 years, there's no doubt there's been more multistage funds, larger fund sizes, right?

And this accelerates the trend because you no longer have to tap the public markets. So if you look at this chart, it just shows you the share of private capital that was raised by the large funds, and that's just becoming a much, much bigger part of the total market.

And what I think is particularly interesting about that, it said through Q2, 2024, 521 private market funds have raised a total of 295 billion across these asset classes, but fund counts fell by 45% during that same period of time, right? So yes, this is the case that there is a structural and dynamic change in these markets.

You've got these multistage funds. You've got funds like Altimeter that's been doing this for a long time, where we do early all the way through public markets. And that's the amount of capital that's been raised. And then, Bill, if you look at the amount of capital that's been deployed and where that's coming from, you can pull up this chart from Crunchbase, and it also shows you, right, that you just have a lot of these late-stage dollars.

Now, what this chart doesn't show you is the valuation of the rounds when they were getting done. So I think you're exactly right there. And then, of course, this isn't just VC and growth funds anymore. We have world-class sovereigns that have moved into this domain. You can see here this new fund out of Abu Dhabi, MGX, which is run by, frankly, extraordinary investors, long-term time horizons aligned with national sovereign interests.

And it's not just them, right? The Saudis, the Kuwaitis. And then don't forget, we've also seen the private wealth, the high-net-worth platforms move into this space. So Goldman Sachs, JP Morgan, Morgan Stanley, those platforms are now aggregating and put big dollars into this space. So the most fascinating part of this is that we do now, in my estimation, I think this has been the case for quite a long time, we have the permanent emergence of what I've been calling the quasi-public market, right?

And the reason I call it the quasi-public market is because VC has a certain connotation to it, right? You're taking that first, second, third round of risk into a company. You often own somewhere between 7% and 20% of a company. You take a board seat, you actively engage and help build that company's success.

That's very different than investing in a company at 10, 20, $30 billion that frankly is in a very different place in its life cycle oftentimes. So, you know, I don't know. I look at that and if I ask the question, is that good or bad? I don't know. More liquidity allows guys like Elon's to better experiment, to take bigger swings of the bat.

Maybe it compresses the margins for those of us in the investing business, but I think it leads ultimately to a lot more innovation. Although I'm sensitive to the point you put out there. You know, it was just two or three years ago where we were talking about, right? The soft bank effect, weapons of economic destruction.

You know, we certainly led to excess competition in the ride-sharing space. And so what it did is it slowed down and prevented the natural order of things. The 80/20, the winner take most from developing in a profitable way. And once that capital dried up a bit, Bill, obviously you saw the profitability of Uber skyrocket and the natural kind of market structure set in.

So I do think that's a downside of this, but net-net, I think it's a positive development for entrepreneurs and innovation. Yeah, I could certainly express some things that I worry about that are not necessarily in the best interest of the entrepreneur or the investor. So one, just with this much money being pushed upon you, and if you don't take it, your competitor will take it.

You're forced into the game. Like you're not allowed to not play. Is that what you feel like happened between Uber and Lyft? Sure, sure, absolutely. But there were many examples. I mean, I think that a company back on the board of Zillow was forced into this home purchasing market because the open door team raised so much money and was gonna tell the world that they're gonna be obsolete.

And so if you don't engage, you could have multiple compression on your head. It's an interesting dynamic. Anyway, you're gonna have higher burn rates. And so you're gonna know less about your unit economics just by a natural fact 'cause you get further away when you're operating that way. And you can't raise $400 million and not have a high burn rate.

Like there's no point in it unless you just like interest income. The staying private longer thing becomes both the dog and the tail. Like it's hard to know what's causing which, right? Because once the investors want, and this is true of founder liquidity and employees secondaries also, once the people want to bring the money to you, especially preemptive rounds, this kind of thing, you start searching for ways to make it easy for that round to take place.

And so you start encouraging staying private longer, you start encouraging the secondaries. And that can create a misalignment of interest. Let us not forget that the Byrd founder took out 50 million in a private round, and that company's now bankrupt, right? Well, I definitely, there are two things, two features of this that worry me.

There is absolutely no doubt in my mind that excess capital distorts company behavior, okay? And in particularly these early phases, it's very difficult, it's not impossible, but it's very difficult to stay fit and efficient when you have a buffet of all options sitting in front of you and you can fund all of them.

Scarcity breeds necessity, scarcity breeds innovation. So I think if you're on the board of a company or a founder of a company or CEO of a company, you have to think long and hard about the negative cultural and negative fundamental effects to your business of taking too much capital.

I mean, we saw this song and verse over the period 2018 to 2022. And frankly, we're still moving through the hangover of it, Bill. Yeah, and stay private longer can become stay private forever, which has a negative impact on IRR and eventual liquidity. And if you've taken, there's another element of this that's gonna bring the regulators in and Lord knows what they'll do, but it'll probably mess it up, is that if this sector of growth has been stolen from the public markets by the quasi public market, as you call it, then the people in Congress will cry foul that the individual investor doesn't have an opportunity to play.

I'm sympathetic. And they'll start doing stuff that will cause more chaos, I'm sure. Well, I'm sympathetic to the argument. You and I've discussed this many times, the number of public companies in the US has collapsed. The whole idea of accredited investor status that you have to have a certain amount of money in order to be deemed worthy to invest in private companies.

And if they stay private until they're worth $100 billion or take open AI, like there are a lot of retail investors that would love to buy open AI today. And the only ones who can fundamentally, or who can really access it are accredited investors, high net worth investors. So it is ironic- And then you have to know some, like there's no, and it doesn't matter, but we're making the same point.

But I would say, again, at least the companies that we're involved in, we have these conversations very openly with the founders about the risk reward and the trade-offs. I do think there is a lot of these pressures that you rightfully acknowledge. But ultimately it seems to me like, as to this question, whether or not this is going to yield good results, right?

I think it's a net, net, I think it's generally deeper liquid, more liquid markets, generally a positive for the entrepreneurs and the founders. And I think for the firms, listen, late stage private deals, like let's go back to think Groupon. I think the last private round there was 19 billion and two years later, it's worth 1 billion.

This comes down to stock selection. This comes down to investing. It comes down to your underwriting. It comes down to risk reward. I might think that open AI at $90 billion is an incredible risk reward and wish that I had more money in open AI at that valuation. Others may think that's ludicrous.

That's called a market, right? And you're going to be proven right or wrong in the fullness of time. And frankly, Bill, to your point about two and 20, LPs get to decide. If you go out and you want to raise money from them, you want to raise billions in order to put billions in open AI, they get to ultimately decide what they're willing to pay.

And, you know, again, they're going to probably be held accountable at some point in time for their returns as well. Although that can take a very, very long time. As you know, that could be a 10 to 15 year window before, like corrections in the LP market are one of the slowest things that can possibly happen.

And I'll close this part by acknowledging something that you've said before, which is, and I've talked about in other places, but some of this and the reason it's systematic and not cyclical is just a recognition that when technology companies gain a foothold and have positive momentum, they often go much further and longer and higher and they have network effects.

And so this is, some of this at least is the market coming to grips with that and recognizing that you can pay 30 or 40 times revenue for something if it's going to hyper growth for four or five years because of systematic advantages and adjusting their game on the field as a result.

- I blame a fair bit of that on you. I mean, you educating everybody on power law and network effects over the last 15 years hasn't helped our plight at all. I mean, the competition is stiff. I think that the efficiency of the late stage private market, you know, it's no longer five or six players in that market.

As you know, you're talking 20, 30, 40 players, you know, that will show up to these things. So it's difficult. And I know, I stress about this all the time. We're going to be judged ultimately by the returns on that capital. And I think the folks who are deploying that capital for the most part are pretty extraordinary and worthy competitors.

And we end up, frankly, these big rounds oftentimes are collaborations between many firms, much as you've seen in private equity develop over the years. But one of the things I did want to touch on, you raised this question, like how much of this has gone into, you know, generative AI and how is this skewing it?

And so we have a couple of charts here. I think Sapphire Ventures, you know, put these charts together and it just shows like, you know, the vast majority of money, I think AI funding in 2023, Forexed, you know, 28 billion and over 700 deals. But what was interesting is about 65% of that, talking about power law, 65% of that, I think went into five or six companies, you know, that you know of.

And by the way, those companies need big checks because they're consuming voracious amounts of capital. And you know, perhaps that's a jumping off point. Although some of this may involve these credit deals, some of this count. Oh, for sure, for sure. And listen, that's another thing one has to take into account when thinking about these valuations.

But I know that you have a little bit of angst based on prior pattern recognition, just about, you know, whether this is developing into a bit of a hype cycle. So why don't you talk to us about your thoughts about what's going on. Look, I think it unquestionably is in a hype cycle.

And by hype, I don't mean negative necessarily, just that everyone's talking about it. There's not a CEO or a CIO in the US or probably around the world that hasn't asked the question, what are we doing in AI? You know, how can it impact our business? Like it is on the tips of everybody's tongues, right?

And so when you get in these situations, I'm always like, I don't know why, but I'm always fascinated with what's reality and whether we might go too far and what we're promising versus what can actually be done. I think in this case, because some of the leaders and I'd say OpenA is probably the strongest, are willing to spout hyperbole.

And what I mean by hyperbole is they're willing to just state really vague, broad, big ideas without much meat on them. And I think that then creates a situation where I think you end up having tension in the system where some people feel like their own business model is threatened by this notion, especially if the notion goes too far.

There was a super interesting comment made by the new chairman of TSMC where he said, "OpenAI Sam Altman is too aggressive for me to believe." Now, why would he go out and say that out loud? Like, you know, what's his incentive? And I would say his incentive is he's running a business.

He's got people asking him questions all the time about where this business is going, how's it gonna be. And there's this other person running around the globe telling everyone everything, including spreading rumors that he's gonna spend 100 billion of Microsoft's money and he's gonna build his own chips and build his own fabs.

And that then starts to be distracting to a company like TSMC. Yeah, but hey, you know, like let me take the other side of it, right? I'm sure you would. No, I mean, I'm just saying, you know, Elon set out a vision for rockets that could land themselves and auto fleets that would be replaced by electric cars at the time he said these things, they sounded totally outlandish.

And by the way, the time took longer to get to most of these points than Elon envisioned, but we ultimately got there and it ultimately blew our socks off. And I think two of the things you have to do, right? You have to will the future. You have to manifest the future.

You have to describe the future. You have to motivate your employees. And importantly, you have to motivate sources of capital. Right? And so I think in the case of Sam, you know, he's out there saying these things. And again, I don't need to come to his defense. I think he's incredibly thoughtful.

I think he is a true believer. As I am a believer, I don't know what the time series is going to be. And I'm certain all of these experiments will not work. With that said, if I am the CEO of TSMC, I would say exactly what he did. And the reason I would say it is because if Sam's going to emerge as competition, build his own fab, build his own chip, et cetera, what would I want to do?

I would want to undermine the sources of capital so that he can't become competition. I would say to the sovereigns who are thinking about funding him, whoa, you better be careful because this guy is too aggressive. This is part of the war of words that we see out there all the time.

I mean, Databricks does this and incredibly, Ali is amazing against Snowflake. I see this happen in VC land all the time where people will say something to try to freeze the markets so a company doesn't get funded. - Rarely works, yes, yes, yes. A company doesn't get funded. So all I would say is that it may in fact be very shrewd by Sam to be doing exactly what he's doing.

I don't think that necessarily undermines the advances that we're making. Although I would say that we're in the fog of war right now and it's very hard to know the timescale that a lot of these things will unfold. - I would, so you use maybe like Elon and the Tesla example.

I think another example is crypto, right? And so we went through a phase where there were very, very smart people on podcasts like this and around the globe saying that crypto and blockchain would replace the corporate entity and that marketplace companies like Uber wouldn't exist and all this stuff.

And that just didn't play out and I don't think it's going to. - Yeah. - I'll go out on a limb. And so, but for a while, we all believed it. There was a moment in time where the scooter companies were claiming that they were gonna take 75% of Uber's rides.

That did not happen. There hardly anyone riding here in Austin. And so sometimes you're right. Sometimes you are drawing a picture of the future that we actually get to. And sometimes that doesn't play out. So, you know, there's more meat on the bone here to be fair. But when you say this stuff will do anything and everything, when you say-- - Oh, for sure.

- My computer, when it's not summarizing my email, will be curing cancer. And when you start talking about UBI and how no one's gonna work, like, I just think that's like la la land stuff. And lots of people are saying it. Lots of people are saying it. - No, no, listen, I think here's where I think your admonition is smart.

And as you know, we've looked at a lot of stuff at Altimeter in the AI landscape. You know, enabling technologies, infrastructure, picks and shovels. For all the reasons about uncertainty and high valuations, a lot of valuations reflect or discount or underwrite high levels of certainty, right? That I think are hard to peg at this moment in time.

This is what I think happens in the fog of war, right? And the goal of an analyst is to develop deep conviction at these moments in time and be right before everybody else does, right? I think about this in the internet. People had deep conviction it was going to be huge, that search was gonna be important.

But a lot of people ran out and invested in Ash Jeeves and Alta Vista and Lycos and Excite and name all the companies that a few years later would go to zero. And it's almost certain that that will also happen in AI. That didn't mean that the internet wasn't going to be huge or that Google wasn't going to be a multi-trillion dollar company, which I also think will happen here.

But the, go ahead. Well, I just think this is, so I wanted to do this one before the software one because I think they're relevant to one another. So there are people that believe that AI, and when they say that, I can't, I never know whether they're talking about AI or LLMs, which I view as a very small subset of AI, but we'll just do everything.

It's just gonna do everything. And so this, our last topic about, these people have come out and said, well, because of what you saw in the earnings period and how the stocks reacted, software is dead. And so there are people that believe one day you'll just tell your LLM what you want it to do and it'll do everything that software did.

- Right. - That's a pretty strong form of it. I think there's a lesser strong form of it that the UI around LLMs are gonna enable a type of interaction with what we used to think of as a SaaS application, that's gonna make the older apps feel tedious and therefore you end up with a replacement cycle, maybe as big as SaaS replacing on-prem, maybe as big as SaaS replacing client server or whatever came before or many in mainframe.

And if you believe that, how much of this gets rewritten? So you've invested in so many software companies, you guys are deep in your analytics. What did you see in the past three weeks from earnings and how do you think about AI as a risk for multiple compression and disruption for the software industry writ large?

- Yeah, no, I think it's super important question. By way of transition to that, I did wanna say this thing that not everybody is all in on AI. I'm going to WWDC at Apple tomorrow and Apple Intelligence is out this morning talking about AI service that they're gonna unveil.

They have not spent tens of billions of dollars building LLMs or frontier models and there are some people who are critical of that bill. And I imagine they're looking at it and saying, "We don't see the industrial logic. We don't see the return." It's known to be a very financially and fiscally conservative company.

And so they'll probably announce a partnership with OpenAI. My sense is they probably look at that and say, "Oh, that's a transition for us. Let them spend all the huge early dollars. We'll come in and be a late mover. We'll spend a fraction of the money." And ultimately we control the platform.

We control the device. And so we're not at risk of getting disintermediated. My point is that I think there are different choices being made by different companies. But that said, using the Apple example, I do think that the heat is so loud. Even on this very podcast, we go on, "What are they doing?

Why haven't they made Siri better?" And like the drumbeat gets to the point. If they were to hold that tomorrow and not mention AI, which they would never do, it would raise immense questions. No, that's for sure. Of course not. Why would they? But I think they're going to have a series of announcements in terms of integrating with OpenAI.

They're gonna make the phone better. They're gonna say you can only get it on 15 plus or 16. They'll drive a replacement cycle that begins in 2025, but they won't spend the dollars to have their own solution probably until you get in to the release cycle at the end of '25.

And I think that's a perfectly acceptable solution. Listen, if everybody was critical of them, Bill, for not building their own LLM, everybody knows they have not yet. And so if people were critical of them, the stock wouldn't be at 196 bucks a share, right? People are voting with their wallets and saying, "Listen, it seems like a pretty good balance between the choices that you've had." In fact, I think if people are gonna be critical of anything, a lot of people are looking at the total CapEx of the hyperscalers, now at $200 billion, and saying, "When are you gonna get a return on the dollars that you're spending?

And how on earth can you go up from there and have the industrial logic to earn a return?" Since you mentioned the hyperscalers, there was a series of layoffs announced in two of them. I think it was Google and Azure, was it? Or Amazon? Yes. I think they were small targeted.

If you're in just hyper growth mode, why are you doing layoffs? I don't understand. I mean, listen, look at the most recently reported number of employees at Meta. Everybody knows that Zuck's in beast mode around AI. And yet, when he reduced the headcount from 86,000 to 69,000 a couple years ago, I think at the end of the most recent quarter, he still only had 69,400.

There's massive slack in these businesses, Bill, if they weren't firing people or encouraging them to turn over. Yeah, it was just within the unit specific to this, which was confusing to me. Anyway, I think it's a good sign out of those guys, but let's unpack the software stuff that you led us to.

And what I want to start off by saying is there's a lot to unpack, but let's start with the obvious, right? When the future gets less predictable, right? For any reason, whether it's macro, whether it's micro, then you have to increase the discount rate in your free cash flow and your DCF, right?

And that means that multiples go down. Slowing growth also reduces multiples. And then we've talked a lot about how high interest rates, higher than expected, reduces multiples, right? So this is the triple whammy. The perfect storm for software multiples is right now because we've had slowing growth. We have a lot more uncertainty about the future, irrespective of what side you're on.

And on top of that, interest rates have remained higher than expected this year. And we were starting from historical highs during ZURP. So let's take a look, right? This is the chart a lot of people have seen, and this is made by our team. And it just shows you where we are in the historical context of forward revenue multiples, right?

And so we're trading, you know, about 20% below the 10-year average ex-COVID. And some people are starting to view that as an opportunity because when you see headlines that all software is dead, if you don't believe that to be true and you see these valuations, then you say to yourself, "I need to go hunting." And I'll tell you, there is smart money that's starting to buy software again.

You see this next chart, which was by Goldman Sachs, and it just shows us a multiple of free cash flow. So similar to the chart above. But what did we hear in the quarter, Bill? Okay, so UiPath came out and said their growth slowed down to 6%. Salesforce came out, said their growth slowed down to 7%.

And I think for a company like Snowflake, it came in at 26%. And Databricks is rumored to still be growing well in excess of 50%, okay? But I pulled some snippets that we could throw up on the screen here that we got from the commentary, right? Workday said we saw probably a bit more scrutiny than we've seen this time last year.

I just think people have taken a little bit of a pause. Salesforce, the momentum we saw in Q4 moderated in Q1, and we saw elongated deal cycles, right? So deal compression and high levels of budget scrutiny. UiPath, in mid-March, we began seeing increased deal scrutiny and longer sales cycle with large multi-year deals, right?

So multiples in all of them have compressed. And one of the things I think about is public markets, when they hear things like that, they shoot now and ask questions later, or as Druckenmiller likes to say, invest and then investigate. And so if you look at the forward free cashflow multiples on these business, UiPath is now trading at something like 20 times and Snowflake at 36 times.

If you look at their revenue multiples, 4X and 9X respectively on 2025. So those are a hell of a lot lower than what we saw over the past few years. But the question really is, what does this all mean for the future of growth, for the future of profitability of these businesses?

And can you plausibly see, is the core business gonna be attacked or do you see use cases where AI is actually going to be an accelerant to the business? Let's take those one at a time. So I would make the argument that the pressure, and I say this without judging it as positive or negative, the pressure to be completely focused on AI at the CEO level and the CIO level is so high right now, from everywhere, picking up the Wall Street Journal and reading it, watching CNBC, listening to us, whatever, that they have to spend or they feel they have to spend.

And we'll post a link to the CIO survey that Battery Ventures published. But what you see is, I think 8% of CIOs have a budget increase over 10%. So 92% don't. So think near fixed budget. But 85% of them say they're aggressively increasing their spend on AI. - Right.

By definition, it's gotta come out of something. - It's gotta come from something, right? And so I think we're at a point where if you're not AI, you're budget's somewhat at risk in selling into a CIO. And by the way, one category that almost never gets reduced is security spend.

So if security spend's not going down and AI's going up, it's even, you're more, if you're not security or not AI, I think you're even more at risk of having trouble with expansion dollars. - No, there's no doubt about it. That's what we've seen. That's why I think you see some of this course slowing.

Then one thing you didn't point out is when people have questions about the future, which they do around AI. So let's say they're spending a bunch of money on Workday, spending a bunch of money on Salesforce, spending a bunch of money on Snowflake or Databricks or you name it.

And now they go in to present their case for this year. And the first question that's gonna get asked to them is, well, how are these guys doing with AI? What are they doing with AI? Is this the multi-year bet we wanna make? Or should we be betting on Google?

Or should we be betting on Microsoft Azure? It just freezes. It says, go back, do more analysis, and then come back to me. And I think that's probably the number one thing you're seeing here, Bill. Rather than budget pressures, what I really think you're seeing is the slowing down and the elongation of the big commits because people really need to make sure that they're betting on the future, not on the past.

- Well, and that becomes especially true in two areas. One is any area where LLMs are proving to be effective. And so in the enterprise, customer support is the one everyone's talking about, right? So if you sell a system in that space, and it's gonna cause this freezing you're talking about writ large, because this is the area where enterprises are experimenting the most.

It's where there's the most number of application-based AI startups. And it's the one where you're getting the most reinforcement in the public discourse about success. You're hearing people, I don't know if the clarinet thing's real where you fire 70% of your workers, but there's plenty of people that echo something similar to what you heard about copilot for programmers, 20% gains of efficiency for your workforce, that kind of thing.

And so those areas are especially true in what you're talking about. Another area that you just mentioned in HR, there are a lot of applications in the hiring process. I've seen a lot of AI apps in that area. And so you're gonna freeze, you're naturally gonna freeze and say, "Oh shit, I gotta figure out what this is gonna mean." So there are repercussions.

Now, there's a question like that kind of thing can go too far. Like in the example of scooters and Uber, where everyone thinks that it's gonna be disruptive and it won't. And these are hard things to figure out. The second category where this can happen is just where LLMs are really good.

UiPath was a company that took a particularly big fall. And if you study the different uses of RPA, some of them are form-based, some of them are ingesting invoices, some of them, some of those automation processes are things that LLMs are very, very good at. Right. And then that puts you more in the crosshair, right?

Yeah, I think you nailed it. And listen, lots of people were short UiPath, lots of people are short these call center software businesses for all the reason that you're talking about. I think our good friend, Aaron Levy, laid this out pretty well in this tweet here, where he talks about these three major axes, the things that are most likely to be replaced.

I mean, it's similar to what you just talked about. What's the level of automation being applied to the work? What's the cost of the work that's being automated? What's the volume or frequency of the work that's being automated? So like in the case of UiPath, to your point, here's a business, think about the setup here, Bill.

It grew only 6% in the quarter. Most of its free cash flow gets eaten up by stock-based compensation. So one might argue that it's not even real free cash flow on a per share basis. And it's right in the center of the bullseye how AI can automate this stuff, which at a minimum causes a lot of churn, a lot of delay, and a lot of pricing pressure.

So I think the market's reaction to some of these things is pretty rational. Now, take something that's, I think, a hotter topic among a lot of our friends, which would be Salesforce. An incredible founder, CEO, and Mark Benioff. Mark has been early to get on trends, whether they're social, whether they're mobile, et cetera.

And he's been all over AI. But you have a debate. On the one hand, you have folks like Chamath saying his company 80/90 can really disrupt them because you can get 90% of the benefits for 80% of the cost. Aaron Levy would argue, no way, you can't do that.

People don't want a constellation of services. All these things exist because this is what Salesforce customers are demanding of them. But I think part of the reason Salesforce has recovered well here, Bill, is this is a company that has gotten fit. This is a company that is running efficient.

So out of their $13 billion of free cash flow, they convert-- I think they have $2 or $3 billion in SBC. And so they convert over $10 billion in free cash flow. So if you look at it for a market leader, it's not that expensive, even though its growth rate has slowed way down.

And then I think, listen, you've asked me a fair bit about Snowflake. And folks, because we were early investors in that company, I get questions about Snowflake and Databricks and these data platforms all the time. Like, what does it mean for the database? What does it mean for these data platforms?

So maybe just a second on that. I think one of the things people question when-- in the case of Snowflake, growth decelerates to 26%. People are like, OK, yes, the multiple on free cash flow has come down a lot. But they still have a lot of SBC. All that free cash flow gets eaten up by SBC.

So a lot more scrutiny gets put on those free cash flow. And I think they're going to have to demonstrate how the growth rate will remain higher for longer and how they can get more fit around SBC if they want to maintain or re-expand their multiple. But when I evaluate them or Databricks across the three axes that Aaron laid out, they have a lot of things that they can expand and are upsides, I think, from AI.

First, I just think the core business of data-- data is a primitive to AI. You need structured data. You need unstructured data. I happened to be at their event last week. I see the head of data from ExxonMobil talking about how they're going all in on data engineering and the data platform there.

And there's a lot more workloads that they're going to bring to bear. So I think just the stickiness of enterprise relationships outside of Silicon Valley, it's deep and it's broad. And these companies have made long-term commitments to these platforms. They're not just going to shift them in a second, though they may slow down expansions to the point we just made.

But what are a couple of the easy places I think that Databricks and Snowflake can go to automate functions? One would be transforming data. So if you have 100 different sources of disparate data, just think you've got to dedupe that data. You've got to cleanse that data. All the things that there used to be a lot of manual interventions, a lot of workloads in order to do, I think AI can do that particularly well.

AI infrastructure, training models, building chatbots, fine tuning. Again, I think that they can build-- all those guys are building the AI infrastructure to do that. And then just basic thing, like how do we extract signal from the data? So text to SQL, right? Being allow-- allow somebody to talk to the data and spin up UIs that really used to be big businesses unto themselves, business intelligence companies.

So I think that there is an opportunity for that. And in fact, there was this video, I think, that one of my analysts posted. I saw it posted by a few people on Twitter, which is Jensen. And we'll spin it up here. So that Snowflake is no longer just a data company, but they're also a computing company, running Cortex AI.

Big opportunity for Snowflake. If you guys are watching, if you guys are following Snowflake, Snowflake just added a new business to themselves. Not just computing, not just data processing, but computing. Accelerated computing. Jensen talking about Snowflake over in Taipei this week in the context of Cortex AI. And he said, listen, this is a huge new business that we've done in partnership with them that is totally upside to their core business.

Now, whether or not that, in fact, shows up and the revenue shows up, that's at the heart of the debate that everybody's having about every one of these platforms today. It's interesting. And ironically, it gets at one of the same things we've talked about on the consumer side with memory.

And today, the LLM, because it's so text heavy in how it works, how it was built-- I mean, text is the cornerstone to it, and language. And as a result, when people use the word hallucination or whatever, they're talking about errors. And you can't really rely on a system to be numeric if it hallucinates.

And so you're not going to run your accounting on an LLM today. And I think the interesting-- so today, in the enterprise, you're seeing a lot of-- we already talked about customer support. In the database area, we're talking about having basically language translate into very complex queries and have the LLM live between the questioner and the data source and therefore provide value by being a UI of sorts for input and output.

Let me give you the example of this. I mean, how many times have you wished that a CEO running a business, they don't want to go to their data analyst to try to spin something up. They have a question. They just want to ask their computer. Ask Google, and it gives you the freaking answer.

Yes, yes, yes, totally. I totally get it. And that's what's happening, and that's what people are doing. There's a company called Glean that has a bit of momentum that props up kind of a universal corporate AI query against a bunch of different data sources in your business. And there's authentication and security risk and all this stuff, and they help you manage all that.

But I think the long-term question about how disruptive this will be for the app companies comes down to whether any of the foundational model companies eventually build in a data store that is easy to query and is holistic and not lossy. And that hasn't happened to date, but I bet you it's something they're thinking about from a multimodal standpoint, such that a developer-- today, any developer using a foundational model is using a separate data store, right?

And they're using it for UI. They're using it potentially for data cleansing or anything like that, but they're not storing numeric data inside of it. So I think that would be something to watch over a very long time frame to see if anyone tries to build that into the API, if you will, on how you use one of these models.

And this really, Bill, is, I think, what happens at the start of these phase shifts, right? It is the fog of war, and we get these headlines-- the end of software. Software is dead. I will tell you, in technology, you probably have better opportunities listening to the wise words of Warren Buffett, which is, you buy when there's blood in the streets, and you sell when there are trumpets in the air.

And trumpets were the air in software during 2021, right? Because people said, these are annuities. The discount rate should be really low. They're going to last forever. They're going to grow to-- They got comfortable with 22x revenue multiples. Correct, correct. And now, in a very short period of time, you had a disruptive force.

We tend to overshoot. And I suspect that these headlines, the end of software, the death of software, in, I would argue, less than 24 months, will appear to be silly. I think there are some really interesting investments to be made, particularly in the public markets, because a lot of these incumbents have incumbent advantages.

And they're going to accelerate when all of this inference starts coming online in Q3 and Q4. And remember, they had to invest ahead of the revenues coming online. You have to buy that capability and build that capability and hire those teams now. My suspicion is you'll start seeing some of this acceleration late in Q3, Q4 of this year, heading into next year.

And when that happens, people will say, oh, no. Software is not dead. It, in fact, is an accelerant. But it's not going to be equally good for all companies. I do think there are companies like UiPath, where the fundamental value proposition is challenged. They have to reinvent the model.

And I think there are other businesses that's going to be an accelerant to the core business. I will take the other side of this, what you just said, to a certain extent, which is I don't think you can simultaneously have people get re-optimistic about software and the hype cycle of AI to continue at the pace it's been on, because I think they're at odds with one another.

Because the most glorious statements about what AI is and can do say it replaces everything. And as long as that's being trumpeted and believed by enough people, I think the onus is on-- everything moves from half full to half empty for anyone that's not holistically AI. Yeah, we shall see.

That's what makes a market. That's what makes a podcast. That's what makes the basis for urinized debates over the last 20 years. I mean, if it wasn't AI disrupting something, it was the mobile phone disrupting desktop search and whether we could monetize that. It was the internet disrupting what came before it.

By the way, two quick things before we leave. One, I look forward to tomorrow. It's cool you're going to be there. So you can let us know exactly how it goes. I think that'll be really interesting. And then I was really kind of positively moved by this. We can put it in the thing, but Google, Jim and I did an ad with Mark Cuban highlighting their enterprise apps, Docs, Sheets.

And I was compelled. It's an area where they have not invested a lot. They've always had Sheets and Docs. And a lot of the startups in our community live on that stuff. But it hasn't really competed with the Microsoft stack. And with Satya's comeback, everyone's been super excited about what this means for Microsoft.

And if they play their cards right at Google and tie this into Android even, it could be a huge win for them. It's fun to see this thing. I recommend people check it out. It's a-- you've got to pay for the price of admission here. This is an incredible time to be alive.

All this innovation, I certainly know coming out the other end, it's going to yield a lot of prosperity. And so who the particular winners or losers are, what the timescale is, that's what we get paid to figure out. But I have no doubt that this is good for all of us.

Bill, I'll see you soon. Take care, Michael. As a reminder to everybody, just our opinions, not investment advice.