BG2 with Bill Gurley, Brad Gerstner & Aaron Levie | Software Valuations, Earnings, AI, Immigration & More | E02

25:04And that, that, that certainly worked. That gave us a boost. That has had different characteristics than, than just getting us to the, the billion as quickly as we wanted. So we had to get into security and workflow. So, so it's like, we're like, we're, we're beyond like second act. And it's more like, we've got multiple, you know, kind of additional capabilities that we monetize. But you do have to, there, there's definitely like a finessing to your, your product strategy, your go -to -market strategy. Like, we used to be like super skewer -oriented. And then we had to rebundle things. And so your, your whole company is sort of, you know, riding these, these shifts in, in some kind of, you know, kind of concerted way.

25:42And it's interesting. Like, part of this, you know, part of this as like a founder, and just your own kind of like, acknowledgement of where you are in, in the journey, is sort of saying, okay, like, there's two kinds of companies, maybe out there. Let's just, like, two kinds of successful companies out there, forgetting, forgetting, you know, the ones that don't work are getting acquired. There's, you know, wouldn't be great if everybody was Google or Meta. That would be great. Like, you just grow 50 % a year forever. And then, you know, 10 or 20 % a year. But then, and that's, that's fantastic.

26:13Like, I'd love to have a trillion dollar company. It wouldn't love to be, you know, Congress like Zuck is, but, but other than that. And then there's, and then, but then there's like actually like, like, extremely good valuable companies that you're, you're just are building a real business. And, and like, you don't like, you don't think about them as Google or Meta or whatnot, but they, they produce, you know, in the same amount of value for the world, for their customers, for their, their cultures and employees. And so we started studying the auto desks and adobe's of the world, which is like, okay, well, what's a compounding model where you're growing 10 or 20 % and your, your free cash flow is 30 to 40%.

26:52And you just do that for like, literally decades. You know, there was a company we studied a ton that, that, you know, it almost further proves the point in the past couple of weeks. Ancest, we studied these guys a year or two ago. And it's, you know, a 30, 40 billion dollar, that mean 30 billion dollar company. They just own their space of, of CAD, you know, simulation, industrial, you know, software, maybe, you know, $2 billion revenue, you know, plus or minus 40, 30, 40 % margin. Like, that's a fantastic business. Like, everybody would love a 20 to 30 billion dollar market company. And, and they don't have to deal with the, the sort of daily, you know, changes of Wall Street of, okay, we're valuing growth at this percent more or whatnot.

27:34They're just like, let's just build a very profitable business, like dominate our market and scale that. And I think that, you know, I think it would be great if, if the Valley also got, you know, more and thralled by those types of names. I love, I love, I love that idea of studying other businesses. That's another thing that I think people don't do enough of, but going out and getting the peer data, looking at how others did it, finding good experts. Have you, have you looked at like cadence? Not deep. Okay. Of course, Brad has, but like, like, we should all be talking about cadence more. Like, we should be talking about cadence, we should be talking about synopsis.

28:10We should be talking about ancis. Like, these are free, like literally, like 15 years ago, cadence was, I'm going to make up a number. So please just, like, do all your charts or whatever, like, I don't know, three, five billion dollar company. It's a 50, 60 billion dollar company today. Like, and, and just dominate a vertical and just keep building and just do it profitably. And I think if we, if we got as enamored by that as building meta, you know, first of all, we'd have a lot less stress all the time. But, but I think we'd just be building, you know, more, more attractive and valuable companies.

28:41Speaking of dominating and meta, several of the large companies reported last week, Brad. And if I think about the public markets, like prior to, right prior to 2024, everybody's talking about magnificent seven, own 2023. And everybody's talking about cost reduction in the valley is something you're very familiar with from, from your back and forth with meta. So what did we learn this week that, and how does it affect the playing field? Well, yeah, I mean, so you and I talked about last week, you know, 2023, like, all these things were up a lot, but it was really a reversion to the mean. I mean, we started 2024 still trading below kind of the 10 year average.

29:23That's how, that's how debilitating 22 was, right? But I said this year, like I thought this year would be more normalized, like I think return expectations, you know, or more and kind of that 15 to 25 range, not, you know, the return to target of 80 like we had at the start of 23. But, you know, I went into Q1 kind of holding my breath a little bit to see, right? What in fact, whether or not we were seeing any of this acceleration? So, you know, we had Google, we had meta, but we had, you know, Amazon and Microsoft report last week. And I took, yeah, I had a couple, a few big takeaways. The first was, you know, the mag seven's really not the mag seven, and maybe the mag four right now, right?

30:04Because we have, you know, a few of these companies Apple's flat on the year, Tesla's down on the year, Google's basically flat on the year, you know, and you have four companies that are, chat GBT to do a really nice illustration of that. This seven with three of them falling behind. I think we're still paying, I guess. We'll insert that post back. You know, but last week, what we saw at a meta, and I think this is really significant. You know, obviously as a big beaten race, stocks up over 30 % year to day, they're clearly benefiting, right? They are at the tip of the AI spear. Their video engagement was up 25 % year over year, which is just like hard to get your head around.

30:47There's only one way to do that. That's through the application of AI.

30:57We're seeing their I think is so impressive, right? They nearly tripled their earnings per employee, right? Their head count in Q3 of 22 was 87 ,000. This quarter, they reported 67 ,000. So they're doing this while that like they really believe that flatter is faster. And I think there are a lot of people who are cutting 9 % or 12 % or this or that, you know, and it's not a fundamental change to the ethos of the business. It's just a little bit more CYA, you know, and I think that, you know, what you see with Mark is a real commitment to transform that business. And it's showing up in the results.

31:33And you know, I think I tweeted something about, you know, reality labs is still losing, I think, billion dollars. And if you look at that on a per share number, okay? And that's about six dollars a share, you know, in losses for the company due to reality labs. And if you apply a 20x multiple to that, that's about negative $120 a share that's being attributed to the valuation of meta as a result of their failure. That's only true if you put zero future free cash flow from that unit in your analysis. Yeah, no, I think you're doing well, I would like to think that everybody was doing that analysis bill, but you and I both know that most sales ID analysts are slapping a 20x multiple on earnings for this company.

32:19And, you know, that's what suffices for research these days. And I would just say in a consolidated view that is pretty crazy to me. And Zach even mentioned on the call. But also, I mean, alternatively built, like it's not, like it's also not crazy because how should you figure out like what the actual profit potential is of reality? Like like, like, we have no evidence at the moment of what that looks like. So so everything else would just be a made up number. So I don't know what I don't know. But any non zero, you know, one of the things that Mark said during the call is that the meta eyeglasses with Ray band, they sold twice as many as they expected to sell.

32:57Okay, I think we're going to have this explosion of AI devices. We're going to talk about a little bit later. But he said that was the first clear example of some of this convergence between the work that they're doing in reality labs, right? And what they're doing in the rest of the business. And so, you know, again, as an investor, I assign greater than negative $120 to share value to Mark Zuckerberg investing $20 billion a year on something that's in the zip code of AI, you know, and augmented reality. The second thing we saw this week bill Google, you know, I mean, it was a solid quarter, but the stock is flat to down now on the year.

33:39I think you're seeing increasing concern about the core business, you know, from threats you and I've talked about this, chat GPT perplexity, just go through the list. You go into any room, clearly answer engines are becoming more relevant. You know, when you said, you know, chat GPT could have made the chart, you didn't say Bard could have made the chart or Google could have made the chart. So I would say Google Cloud was pretty uninspired. And I think I don't think they've gotten real on the efficiency and the fitness. You know, I have a slide here. I asked my team to pull together. This slide plots, you know, what they've done on headcount and what that translates into in terms of earnings per employee over the course of those, you know, same six quarters, right?

34:24And so Facebook is actually reduced headcounts significantly and their earnings per employee is exploded. And Google kind of, you know, they're fine, but they really just haven't made many changes. Now, if this was just about earnings per employee in the short term, then you see your differential in terms of share price performance right there. I think a much, much bigger issue here is the implications this has for future product development. The implications it has for, you know, real focus out of the business. And I just think this flatter is faster is very real. I think that meta is very focused.

34:59And I think that Google is still trying to sort out, you know, you know, how to get focused around some of this stuff. And then finally, Cloud software, you know, after a year of belt tightening, you know, what we really heard out of Amazon and Azure last week is that kind of core workloads are back to their prior growth rates, right? So that CFOs are largely through the, you know, the belt tightening on the core. And we saw real evidence, right, of AI workloads beginning to kick in. Both at Amazon as well as at Azure, I think Azure, I've got a couple of charts here, you know, that the team threw together.

35:37The first is just, you know, you can see the re -acceleration on the right hand side in terms of this is all three of the cloud providers put together. So this is their growth aggregated growth rate. And on the right hand side, you can see you finally saw that turn, that re -acceleration. Now mind you, these things are re -accelerating in the case of AWS from a hundred billion dollar run rate, right? Simple. Like, you know, you're re -accelerating. These are massive growth rates at massive scale. On the left side, what you see is they actually set a record quarter, 15 billion in net new ARR across these three platforms.

36:14So I think, you know, that to me is, is, you know, kind of the real story that came out of, you know, out of the big cloud providers. And, you know, one of the questions I think that we now have to answer, you know, is does that read through applied everybody else in software? Right? Like, you know, is this something that you need to the big cloud providers? And then a second question that I had in my mind, you know, was like, when do we just hit the wall on this? Right? You know, I had a friend to, you know, say to me the other day, they thought that three years from now that the cloud providers, the revenues would actually be smaller than they are today, right?

36:57Which I, which I can't get my head around. When I look at this, you know, I talked to Adam Salipski, runs AWS and he said, Brad, this is a multi trillion dollar market. And that does not include AI. Okay. So yeah, $100 billion is a lot, but it's a multi trillion dollar market and it doesn't include AI. So Aaron, I can get back over to you. That's, you know, that's my brain dump on what happened in the public markets this week. But on the software side in particular, you know, were you surprised at these numbers? And how do you think about, is this unique to what's going on with the cloud providers, you know, or are you starting, you know, to, you know, hear other software companies talking about how, about similar trends?

37:41Yeah. So, so, first of all, you might want to short your friends portfolio, or do you, I've never heard that metric of been three years from now. We're going to be smaller, but that's an interesting take. I honestly, I'm so done with trying to guess when this thing runs out. Like, it is, I think we just have to honest, like you basically are just, it is an uncapped, unknowable total amount of, of, of addressable market in, in this space. There are, there are clear differences between the hyperscalers and the rest of software simply because a company can just move their, their core data center infrastructure from their, you know, their current co -lo and server providers to the cloud.

38:25And, you know, some software providers will make money in that transition, but that's, that's basically 90 % hyperscaler benefit. And so that doesn't sort of all show up in, in the rest of software and SaaS in the same way. So there's some kind of tale of two cities of, of, of these massive infrastructure migration where the hyperscalers are just, you know, again, un, uncapped market opportunity for, for, for these guys. And then there's a lot of surrounding services like you would imagine that as this goes up, the, the snowflakes and confluence and, and whatnot also, also, also see some benefits because there's lots of data services that you need around that.

38:59But, but yeah, we're, we're not seeing any slowdown of, of, you know, companies that we talk to just continuing to be moving to the cloud. I, I, you know, get the fortune of talking to, I don't know, you know, dozens of CIOs a month. And, and there's nobody that is sort of like done with their cloud journey. There's nobody even at 90 % and this is across every, every sector of the economy. So we're still weirdly, relatively early. And then to Adam's point, like, yeah, like that's even pre -AI. AI is just in the experimentation phase for all intensive purposes in, in the enterprise right now. And so we don't even have the AI, Tam, you know, quite understood from a software infrastructure standpoint yet.

39:40Brad made the comment that in his view from, from checking around that CIOs had moved past their kind of shrink and reassessment. Do you, do you agree with that? Um, I, I wouldn't want anybody like trade on my, on my qualitative anecdotes.

40:01But, not investment advice. But, you know, there's, there's like, there's very clear like this interrelated, you know, system of like, like you are like listening to Powell's commentary and then deciding deciding at your management committee meeting. You know, should we, should we lean into budget? You know, and so, so, you know, if, if we're only hearing doom and gloom 18 months ago, inflation is exploding, interest rate, we're about to go, you know, crazy, massive layoffs happening in tech. That's like a scary environment to then be investing, you know, and leading into, whether it's a software company or an insurance provider in, you know, Minneapolis, like, like, we're all, you know, kind of thinking about this the same way.

40:41Fast forward to today, you know, okay, inflation coming down clearly, interest rates either at the peak or, or starting to come down at some point, like, I feel like, okay, we could invest a bit more, which means that, that, that incremental application we wanted to launch, um, that had some data consumption as a part of it. Um, you know, the extra focus of the engineers working on optimization versus innovation, you can kind of tune that knob a little bit. Um, and so I think that's the, that's the sort of qualitative not captured in the, you know, econometrics, um, you know, kind of elements of this that are actually happening now in businesses, which gives me a little bit of, you know, incremental confidence that that means CIOs are going to be putting on, on more growth initiatives going for.

41:19Hey, Aaron, you, you just hit on something so important. Um, you know, perhaps one of the greatest sources of alpha for me and certainly my mentors in this business over a long period of time is this idea of positive and negative reflexivity, right? That in fact, when there is all doom and gloom, that causes people to behave in a certain way, right? And when confidence begins, you know, like as we started entering this year's confidence is turning and the second derivative on, on interest rates is down, et cetera, it needs to the positive reflexivity on the other side. So it actually leads to acceleration because people feel comfortable in doing that and you need to invest ahead of that, right?

42:02Um, and, and oftentimes to really get ahead of it, you have to be buying when there is, you know, the proverbial blood in the streets, when there is that doom and gloom, and people say it can't ever, you know, it can't ever be different. Well, yeah, yeah, uh, yes, uh, I mean, I can only imagine though there is some timing element to that because you have to know when you've reached the bottom of the doom course, but, but that aside, which, I don't, uh, I don't, actually want to like, view this politically at all, but like, as just like a bookmark, this is, I get very confused why we are so passionate about changing the government right now.

42:33Like, they're like, they're nailing it. Like why, like, why, like why pull out a jenga piece out of nowhere and then see what, what changes. Um, but again, you know, different, different podcasts, but, uh, uh, like, like, like we, we are so lucky right now that we somehow landed this thing and, and sure, there's, you know, a bunch of, of incremental issues on the margin that we're dealing with, but like, wow, we should like be, you know, you know, not, uh, not taking this for granted too much. So, that's a software take. I know you have opinions on this other one as well, right? There's, you know, there's a spicy battle out there about, you know, Google and 10 blue links and, you know, and what happens next.

43:14And, you know, I tweeted over the weekend, you know, this isn't a question about like knowing, right? Larry and Sergei always knew that 10 blue links was like a waypoint in route to answers, right? Like anybody who was in the business of information retrieval or they've been around artificial intelligence and, and, and out in front of everybody else. Um, and so the idea here is that, you know, I think it's not a matter of will. I don't think it's a matter of knowing, right? I just think it's this, this innovator's dilemma, right? The Google faces, which is that 99 % of their profits or 110 % of their profits comes from an advertising model around 10 blue links that is just at its core seem somewhat at odds with what perplexity is doing with what chat GBT is doing the age of answers.

44:03Um, and so I, I just love to, you know, kick it around for a second.

44:10How, faced with this innovators dilemma around this? Like, like, what, what should they be doing here? Well above my pay grade, fortunately, I am just a lowly enterprise software. But, you know, so, so as a reminder, obviously for everybody, like innovators dilemma is about business model, you know, difficulties, and we always, we always think it's a technology problem. It's, it's always about your business model, um, doesn't make the, the new thing attractive to you. And so you avoid doing it until you get disrupted. You know, I, I might take, uh, after, you know, thinking about this a little bit, not maybe not enough is I don't think there's a totally 100 % classic innovator dilemma issue with, with, um, the move to AI with Google.

44:53I think on the other end of this, uh, the business model could be as good if not better. And Brad, you think about this a lot of like, like, if you, if you actually had Google, literally tell you the thing to buy, um, and, and they got a transaction on that, it would actually be a similar business model. Um, they would just get you to that answer even faster. And you'd still transact and you still do commerce and, and they are still the distribution engine. Correct. Um, or all of the people that need to advertise somewhere, like, like everybody has to find a customer. And so you still need an interface to, to get my product into that customer's hands.

45:28And so if Google's AI is doing that better than the 10 blue link model, that's great. I actually think the, the more complicated thing is probably more of a product management user behavior experience issue, which is how do I navigate my customer base? How do I navigate my user base to this model, uh, in a way where, in the process, I don't get totally hammered by that journey. And I don't know, I don't know how to do that. Like, like, Bart is clearly their way of experimenting to do that. But like, you know, they're, they're big problem is like, you go to a search box, you type in a search and they give you a lot of results and perplexity and chat, you be T are just totally different product interfaces.

46:04And so they can't clearly make the Google homepage just do that. Um, so they have the kind of sound done that, done that rhyme in your ear. I mean, 1999 Google was just a different interface relative to the portals that existed at the time. And you can say why the hell didn't Yahoo just copy Google because they had an existing business model that required them to sell real estate on the, on this big port. There was probably probably probably your 90 % more right. But, um, but there was also a literal tech tech differentiation that Google had. Um, and Yahoo did not have pay drink. And so, and so Google just literally gave you better results.

46:40And so the youth base migrated. I, I mean, maybe short of maybe some internal, you know, kind of political issues like that Google's technology is probably not in the way of this issue. Um, and so now it's actually like a, as a user now, I, I will leave like one big X factor, which is just like maybe our brains are the limited limit here. And like, and like, like, ChatBT just owns that little slot in our brain of you ask a question, get an answer. And like, now we have like a whole like brain rewiring problem that Google's going to have to contend with. Um, I don't know, I mean, like, but like that's above the, the, the, you know, that's above what a PM on the Google search homepage can do.

47:14Um, so I, this, this one is, this one is, uh, you know, pretty complicated bill where you're raising your, I didn't want to interrupt. Um, so, so for the college game bay fans, I'll do a lead course. So, uh, not so fast. I'll take the other side of this one. Um, I think it's a horrific problem. Oh wow. But, but because one is, is the user interface is subject to disruption. So the, the whole idea that I'm going to throw you 10 links, it's really more than 10, right? Because four ads on top and four ads on the bottom. And you got to search through and find what you want. I'm a big sports fan. I often search for the roster of a team.

47:55That's not even at the top. No, it's like five links down. I have to find it and get around the ads. So it's like, so that's one, two, you already mentioned the business model. Their business model is to throw their customers in a cage match and let them compete with one another to the death. And, and, and, and, and that drove revenue sky high because it created, predo, uh, light is super optimal. Yeah. Uh, payment. And no one wants to see four or five ads. You're not going to get to the same revenue per visit with a, with a transaction model that you do with the ad model because you already mentioned cactl TV, people will pay using marketing math 40, 50, 60 % of first purchase with a transactional integration.

48:46They want to pay 5%. So you have a 10 X reduction. If you were to partner on a transaction enablement, then you do on a marketing lead. And so, yeah, the customer wants neither of those on the screen. Like, I'm going to push back a little bit on the, uh, so, so, and when I said transaction, it didn't necessarily mean that you, you turn it into a CPA model, but, but maybe, maybe you do. And I understand the, the changes in economics there. I guess what I'm saying is that when I do a chat to BT question of, hey, give me a recipe for this thing. Right. It's actually a gap that they don't then let me go buy the things that, but, but if you were to go buy them, you wouldn't buy them from a marketing model.

49:27You'd buy them from a transactional model. Otherwise, you're going to say, I'd like to book a flight to Chicago and get a hotel room and, and, and instead of giving of doing it, uh, the, the Google AI is going to say, would you like to hear deals from hotels .com and explain it and booking .com. Can I read you through the deals they're offering? Like that. That's not bread, bread, bread, bread, you're the expert on this. Why can't Google get $40 for that flight or $30 for that flight instead of the $2 for clicking through to Expedia? Well, I think to, I think to Bill's point, if you look at the traditional commission models, and I think the iconic example is in travel, the traditional commission model, for example, in hotels is 10%.

50:12Let's just say the average daily rate is a hundred bucks. So they're willing to spend on a commission model, 10 bucks. But in a marginal advertising model where they're, where, where they're bidding up all the way to, you know, their gross profit on, uh, you know, in order to get that next customer to drive that growth rate, which I think, which, yeah, and, and if you're a startup, you certainly go above it, you may spend two or three X, right, on that individual purchase. It certainly has extracted more rents. But I think the other piece here is that if we really just telescope way out here, like we are heading to answers and actions, right?

50:51And even the people who invented the damn blue link model don't believe that that is where this thing ends. So what, and all I'm saying is the idea that Google can replicate a 99 % monopoly and take all of that pool of profits with it into this new world after letting chat GPT become the verb, at least at the start for what this new world is. It just, you know, that to me is almost impossible to believe. But the consensus view has continued to be that, you know, they're going to dominate this new thing, the way they dominated the world of search. And I just think if they pull that off, I hope I'm a shareholder along the way.

51:29That will be one of the greatest jujitsu's in the history of capitalist. I'll be, I'll be remarkably impressed. One last thing. There's one last problem. In addition to everything I brought up because their core business model is to throw their customers in a cage match. They don't, they don't have the culture internally to partner in a friendly win -win way. Every company I've ever had it set down to do a deal with Google has been shown a contract that you would never, ever, ever, ever consider. And if we're going to get to a place where I just tell Google my favorite travel site is this my whatever, they're going to have to work out a deal that's reasonable on both sides.

52:13And I don't think they're capable of it. I don't think they're capable of sitting down. And it's a, and it becomes a cultural problem because if every meeting you have with an external third party, you bring this kind of, I'm in charge of attitude. Getting that out of a company is very, very, very hard. Yeah, I mean, I know that there's great anecdotes of of that of that problem in tech, but like at the end of the day, you know, the entire world is advertising on Google. So they clearly have made, they, they, they clearly figured out how to partner with the CMO of every company on the planet. And, and so if my, if our CMO got a call that said, hey, from Google, we can get you more customers when they ask a question about, about, you know, content management software, we're still going to say like it's like, we're going to follow where the distribution is.

53:07So at the end of the day. And so then that's why I still think it's all like the name of the game is still can they navigate their customer base to a new user experience paradigm? Well, obviously fast enough before, you know, it's the classic can, can Amazon become a studio before the studios become Amazon or Apple or whatever. I mean, the company with the buzz is perplexity, not not even chat, TBT. And so like, barge not in the top two. Yeah. And then you can do a different issue, which is like, obviously, they should just buy these things. And, and then, you know, Lena Khan doesn't let that happen.

53:38So, uh, so, you know, how do you like, like if they bought perplexity, call it Google Assistant, like, I don't think we'd be having this conversation in the same way, but they obviously, you know, yeah. Which, which, which is like the Instagram, what's that? I'm just saying that's like what's a grant? What that's like Instagram? What's app? What are you saying? And what met it did? And so it goes like not allowed to do that right now, which, yeah, it's totally crazy. I mean, I mean, which actually, I'm one last thing. It's similar to Microsoft in the 96 97 timeframe where they were, you know, independently box and couldn't do those similar things.

54:17Yeah, I was saying it's not only the government's not allowing, but you got to remember with Instagram and WhatsApp, it was not, they were not facing innovators dilemma. Those deals did not cannibalize their core business in the way that perplexity would cannibalize at least in part the core business at Google. So let me shift us, let me shift us forward. You know, you brought up, you know, a subject on, on our episode one, Aaron, we talked about, you know, these interesting investments made by one of my partners had called MANG. So investments by Microsoft Amazon and video and Google into the big model businesses, Bill suggested, you know, at a very minimum, that's low quality revenue.

54:59But, you know, this credit for investment thing is we've seen historically in the past. It wasn't lost on me that the very next day that the FTC came out. I think we have a tweet on this. It was on Squawk, you know, and said, hey, we're going to look into the nature of these relationships, you know, between, you know, the open AIs and Microsofts, etc. So, Bill, just to close that one out before we jump into our third time, you know, what do you think the outcome is of this inquiry that, you know, that the FTC announced, you know, which was right in line with some of the things that you were talking about.

55:33My concern, which was really a concern for the industry more than just those players, is that those deals pervert and distort the market. And when that happens, people do things you wouldn't expect, just like Zerp, all the sudden competition doesn't look like you would think it would because those are happening. And just real quick, the one thing that, I don't think Lena was, she never mentioned accounting or anything like that. But the bright lights, you know, being shine dad, it might prevent more of those deals in the future, which I think would be healthier for the environment. The thing that I actually don't understand for you guys is, is, so if I'm a big tech company, I have an entirely different incentive structure for these rounds, then obviously, Adventure Capitalist, and yet they're pricing these companies.

56:20So that's the distortion effect for, you know, either those rounds directly or for everybody else in the space, it's like, yes, X company got a $20 billion valuation from a non -economic, you know, actor that does not make your revenue or your multiple have any correlation to that because the acquisition premium or the ultimate cash flow of this company doesn't have any relationship to the credit model that just, you know, got a deal done. I think it's even trickier because based on what I've read, secondary transactions are kind of expected now in the hiring in that world, that LLM competition world.

56:58And if you can't get a financial investor to invest alongside, because these are non -cash credits, then you don't have the cash to do the second areas and you can't keep up. So, and then that's tricky. And on our last show, Brad talked about why these big companies might have an incentive that's other than ownership at the right price so that, you know, as you're saying, the valuation's not real. And that, you know, there's all kinds of problems this can create, especially if you're running the company. Yeah, I think, unfortunately, there's like an inevitable, there's going to be an inevitable, you know, the musical stop at some point on this particular dynamic, opening eye, you know, aside just because they actually do have the traction, they probably do have the real revenue.

57:47But I don't love to see the broadening of this, just from a, again, healthiness of this model. I mean, it's a bill referred to it a little bit like the soft bank effect from 2021 where capital was used as a weapon of economic destruction. Capital was the kingmaker and all of this rather than allowing the product and the fundamental performance of the business to go. But I'm going to shift this a little bit there and, you know, into, you know, perhaps a little bit broader discussion about AI. You know, you had a tweet that caught my eye, where you just said, you know, this is, you know, you've been around for a while, you're deeply respected, uh, technology.

58:26As you said, hey, we got this confluence of events going on in the world right now, confluence of technologies that make this in many ways the most extraordinary of times. And so as we dig into AI a little bit with you, maybe a little context for that tweet. And then I would love for you to go inside out like where are you actually seeing the traction, uh, for AI in your business? What are your guys's top three priorities in terms of leveraging AI? And how do you think those reflect the priorities of your peers? Sure. Yeah. I mean, I mean, this this tweet specifically was was like, um, was related to a bunch of stuff, including like Vision Pro or not.

59:03Just like, I just think it's a great, I just think it's an incredibly exciting time, purely like, you know, economics aside, um, to just be building technology. We are literally given these platforms to build on that are doing incredible things that, that, you know, quite literally a decade or two ago is just not, was just not possible. Um, so that's, that's like more of an emotional, psychological thing of just like, Hey, incredibly exciting times. As it relates to the opportunities, uh, and, and maybe then AI specifically, um, we are, uh, we're, so, so maybe just like three seconds on box and then, and then I'll broaden it.

59:36So our, what we're doing is we have hundreds of billions of files that are stored in box. And every single one of those files, uh, has more value inside of the file than what currently the customer is kind of getting, you know, benefit from because you have to like, open up the file, look at it, read it, you watch it to get actual, like, you know, real commercial economic benefit of that content. With AI, you now have little bots that can run around and do things on that content to generate more value for you. Um, you could get a decision in your business faster. You could summarize a, uh, a contract and accelerate a workflow.

1:00:10You could extract data from something that's unstructured to automate a process that was unautomatable before. So, so that's, that's why it's incredibly exciting for us. Um, the, uh, the, the dynamic right now is, is I think we have, um, you know, we are still, even though we're, you know, a year and a quarter into chat to BT phenomenon, we're still literally in the earliest of days. I think most enterprises right now are just in the experimental period. Yeah. They are trying to figure out where, where to plug AI into their overall stack. I don't think anybody has sort of fully figured that out, um, you know, commonly across kind of normal corporations.

1:00:46And, uh, and that means that it's anybody's game, right now in terms of, of, of the winners and losers of AI. I think, um, uh, I think, you know, I, I probably prefer incumbents and software on the margin right now because it's so important to have the customer data in an environment that is already trusted, is already secure. They don't have to move the information back and forth. Um, they often already have the workflow. So, so if I'm thinking about who wins in CRMAI, it's to me Salesforce as opposed to a startup, ITS MAI, it's service now versus a startup. Um, that, that's like the, the quick thing because, there's not as much innovators dilemma in the kind of pure software categories.

1:01:27Um, in, in fact, this is just really like an advantage for anybody again who has users, data, and workflows. AI is like this dream come true because now we can just literally offer more value to our customers. So that's, that's sort of like in the classic incumbent categories. Um, I'm extremely bullish for startups. They're just not going to probably be about disrupting, you know, known categories of software. There's probably much more about, uh, known categories of like the economy. And, um, and so I think if we spent like the past 20 to 30 years putting software, making it so, you know, um, software is a layer above what humans do.

1:02:03Now we're at a point where software will just do what the human did. And that creates a whole new vector of, of opportunities. Um, and, uh, and I think, you know, the classic way to look at this is sort of like, you know, figure out which parts of knowledge work can convert into tokens. And then those are the areas where where there's new software opportunities that we did not have software for before. And then those are the businesses. So, so I think there's, you know, there'll be trillions of dollars made in, in, uh, in AI. Um, uh, and, um, but I think it's going to be in verticals. It's going to be, you know, kind of helping augment the people element of the work.

1:02:35Um, it's going to be in the infrastructure and the scaffolding around it. Um, I'm a little bit bearish, not bearish, but just like more, more like on the margin, not as excited about, about the economics of the actual pure AI model providers. Um, I think it's, it's tough to be in a space where, you know, at any day, could just open source, the thing that you've been working on for, for, you know, three or five years. Um, and, and then all of a sudden, you know, now, now, you know, there's just this leap frog moment of, of technology. And, um, you know, the thing that I go back to is like, there's, there's rarely been technology.

1:03:09I think we've seen where the actual like, like, the thing you're building, the asset you're building is almost perishable as it, as a piece of IP. Like, the thing literally like can just become obsolete, like a second later, and you can't update it. You, you don't, like, I can't take, I can't take the obsolete thing and make it a little better. I have to like, rerun the training run and then like, do the new model. And so I actually have like converted, you know, capex dollars into this like thing. And at any moment, something else could be better than that thing. And I have no, I can't pivot around that.

1:03:40Like, I'm stuck with this perishable asset. So then you kind of just say, okay, well, then, then open AI, Microsoft Google, um, you know, Facebook are, are basically like where you, you place the bets on who makes the models. And then everybody else should just be building software essentially. What about internally? I'm curious as a, as a someone that runs a large public company, how do you feel about, like, what's the right expectation for programmer productivity improvement? Are you measuring it? Do you care? Where in your org? Are you seeing impact early? Yeah. So, uh, and, you know, programming, obviously, the first place with, with co -pilot.

1:04:20And I don't know, we have not, we have not done a specific measurement internally. You know, I'll walk, I'll walk, you know, through the office and see what's, what's on people's screens and, and, you know, AI is certainly actively being used for and chats, which he to optimize a code, you know, um, the code that somebody's working on as, you know, how do I change this, you know, SQL query to be more efficient, that kind of stuff. Co -pilot, obviously, for writing code, obviously the estimates are, I would, I would probably just agree with the estimates of, you know, 30, 40, 50 percent. And I heard, Drugs said seven X.

1:04:53Yeah, yesterday. Anyway, move. Drugs at that? I think he did. Yeah. Okay. I have not seen some I don't think that was accurate. Okay. Okay. Yeah. I like 30 percent. Yeah. So I'm probably more in the, you know, 30 to 50 percent camp in it, like in the best case scenario right now with where we're at. And, and, and I think still coding is the number one use case. And, and there's actually, I think this actually is an important element of thinking through AI. Like coding is still working better than most other use cases. And it's because you basically have a workflow where you're in a text interface.

1:05:30That is just linear where most of the, the sort of knowledge of that of the, of the field is all public and open source for the most part and available for training runs. And, and the next line prediction, you again have the perfect interface for next line prediction. Most knowledge work actually doesn't look like that. Like we want it to. We want to find these. Drugs treat. Yeah. It's, it's, and so, you know, even, even the legal work, I'm still like talking to the client. And then, and then, like comparing something with somebody else. And, and so this idea that that user and a get a, you're going to get a get a get hub co pilot effect for all forms of knowledge work.

1:06:07At least in the near term, it's, it's way too early to be kind of jumping to that. If programming is like a more precise language than language. Yeah. And then, and then literally it's all automatically testable instantly. Right. And so you just don't have those characteristics for a lot of other work. So, I think it's going to take a longer than maybe we'd like for AI to sort of show up in the average knowledge workers sort of day at the level that get hub co pilot did. You know, if you could automatically write all of my emails, you know, faster, I still would have to read each one. I still have to process like, do I agree with with that thing that that is being said, I still need to understand the substance of the content from the risk from the sender.

1:06:46I can't have AI just sort of jump in and replace me. So I think we're probably a little bit early in the general knowledge work. Sort of, you know, transformation and the things I'm much more excited about are, where can you take a process where a person does does that kind of wrote task over and over again, and we can swap that out with AI and improve that workflow. And that's where the opportunity is and certainly what we're spending our time on. I mean, it reminds me so much. I saw this chart this week, maybe we can pull up from Morgan Stanley. And it shows how we systematically underestimate the size of super cycles, right, over a reasonable period of time.

1:07:26When I think about what's going on here, of course, they show they went back and did some math against initial estimates and said, you know, super cycles are about 40 % underestimated at the start. So, you know, the initial forecast for the PC or the initial forecast for internet, 152 million users in 2000 ended up being 361 million users. When I think about what's going to happen here, I can absolutely see sometime over the next four quarters, we're going to hit a zone of dissolution, because everybody's big pile in here. They think it's all happening now. It's going to take a little bit longer, just like the internet did, just like cloud did, right to hit it stride.

1:08:07When that happens, those who were, you know, who are always against the super cycle, call it a fad, everything else, they're going to see, see, I told you so, you know, it's not really happening the way you all thought it was, you know, you made bad bets, etc. But my sense here is, you know, and I've said, the AI is going to be bigger than the internet itself in terms of impact on economic productivity. But I do think sometime in the next several quarters, we have this zone of disillusionment set in a little bit. It doesn't happen quite as fast as we all thought. But then when we look back three to five years from now, you know, you had a tweet about, you know, the dramatic reduction in costs of these models.

1:08:49So you can imagine chat GPT five or six and it's costing us 90, you know, percent less than today. I don't even think we can get our heads around how that's going to change everything. Well, well, so most of, just to underscore this, most, and again, we're like, we're deep in, in sort of the use cases of, I have a really long contract. I want to read the contract. I want to automatically present data from that contract with AI. And so think about like just all of those things, you know, an invoice, a contract, a presentation, most of the things that customers are asking us for, what they want to do with their content is 100 % possible.

1:09:34And just there's a curve, which is AI cheap enough to make that use case be worth transforming to a software -based way of doing that versus a database way. And so that's exactly what you want in a market because you know the costs are going to come down. And then you'll know that you'll reach that conversions point. So like we are increasingly not limited by the architecture of the technology. And now we're just limited by like, can Jensen make these things cheaper? Can the engineers at OpenAI have more efficient model algorithms? And that's great because then you can just ride that curve. Like we are way more inundated with use cases that companies want to do with AI today, then simply just like the scalability of these architectures from a cost standpoint.

1:10:22Brad, I'll give you one other reason why I think you might be right about the trough of disillusionment. You know, I saw this great interview once with Spielberg when he was talking about jaws. And he said, you know, I didn't show the shark until like 75 % of the way through this thing. And the reason he said he did that was because humans imagination is much grander than anything I could possibly put on the screen. And I, you know, we had AI before LLMs. Like I heard Nick catch bring this up once. And so, but in our modern lexicon, we think of AI as chat GPT and what the LLM did. That's what really shocked us.

1:11:03And I just worry that the one, two, three thing has caused people to think there's this linear extrapolation. I do think the text has kind of been solved and everything's kind of been scanned. And I think the next steps, not linear are super linear. I think it's going to be a little bit of a find. Well, I think that I mean, the growth of cloud as just a shape of the curve is somewhat instructive because it at least closely approximates like the change management dynamic that is that is required to change your infrastructure architecture. So, so obviously not a perfect analogy, but like, but like we like anybody in 0607 when we saw AWS were like, oh, shit, like this is clearly the future.

1:11:51I would literally I would never want to go and manage servers again. But now here we are, it's 2024. And you have the you have the biggest growth rates, you know, from a dollar standpoint, still happening. And so why it did it? Why's it taking 18 years for that still to occur? It's because there's somebody in a data center in Minneapolis that still has to feed that they just move the data. They have to move the services into the cloud. And so the equivalent of this is we'll talk to a customer and they say, we will, you know, we'll we'll show them the demo of AI can now read that invoice and and do what the human was doing instantly and much more costively.

1:12:28But it's still going to take a year or two to do the change management of the workflow itself to swap in AI for where the where the human was. And so now, multiply that. It should have been an XML file and not an invoice. Yeah, exactly. Well, I believe me, I'm I'm glad that it's actually a document still. And and we are we're still in business because most of these things still are documents and not XML files. I still think the press like they watch the movie her, they they expect chat GPT seven to be this all knowing, all loving, you know, personality that they can talk to and and and and this does spend to one thing I would be hyper optimistic about.

1:13:10I do think this memory issue is a big, big deal, at least on the consumer side. So none of the major contenders today can remember who you are because it would require them. And I mean, remember over five years, 10 years to really become a personal assistant kind of thing that that her represented. And it's because you'd have to redo the model for each human. And of course, that makes no sense economically. So it's actually a huge structural problem. There are complaints, you know, and read it about character AI on this front. I think all of the people sitting atop these companies know that this is a huge breakthrough opportunity.

1:13:53And the first one that gets to it, I think could outrun whoever the contender is at that moment in time. Because the things you could do if it could remember everyone in your contact database, you know, all your emails that you've done like the thing, the personal productivity individual could have if this thing could be that way. And I think most of the press thinks it'll be that way tomorrow. And no one's really solved this problem yet. I think it's a huge opportunity. Yeah, I'm going to move us on to the fourth topic. I mean, we had to do a whole show just on that one that we're just on because it's it's so good.

1:14:31And I'm quite certain Bill that what you just talked about a fiduciary and agent assistant that knows me longitudinally that knows everything about me like my personal assistant five years from now, this is cracked, right? The cost curves going to come down, security curve, confidence curve, all those things are going to intersect. And we're going to give a personal assistant in people's pocket to billions of people. And when we think about the broad implications to Apple, to Google, to meta, et cetera, of this change, right? We haven't seen this scale of change in 25 years, but we'll come back to it because Aaron, you had a tweet that really caught Bill and I's imagination.

1:15:10You know, maybe we can pull it up on immigration. And you know, like the world is, you know, right now, I think, appropriately objecting to the insanity of a legal immigration and what's going on at the southern border and lots of fights and and and finger pointing as to why that's going on. But what was interesting about this is you took on the subject of legal immigration. And you know, why don't you explain to us a little bit about what the tweet was about and about this chart. I saw it went a little bit parabolic in terms of in terms of Twitter. Well, I mean, I'm mostly Elon wrapped it into the the illegal immigration as well.

1:15:46So, so that's the only reason for the the parabolic nature. But my point was 22 million views. Yes. Yeah. Everybody really liked H1B immigration this day. Actually, the amount of racist responses I got was was pretty impressive. So, so I mean, it's so simple. It's just the biggest cell phone in economic history. We have the best environment for the smartest people on earth to contribute value and and we are literally doing everything we can to make sure they cannot work here, pay taxes here and start their next company here. And so I'm it's just like it's it's just the most offensively, you know, illogical thing that that I think we have in the country.

1:16:31I put it above all other things that that we do that is totally inane. And we are, you know, by the grace of God, Apple was created here, Google was created here, Microsoft was created here, Meadow was created here, it is not a given that in 20 years from now, those companies will be created here. So why not make sure why not just like seal that and walk that in as a monopoly and get all of that talent here. And the thing that is crazy to me is that is that US companies are currently employing all of the people we're talking about moving here. They're just employing them in a different country.

1:17:05And we like we have expanded dramatically in Poland, Facebook obviously expanded dramatically in India and UK. Like we are employing all of these people. It's just the they're not going to get the local community, you know, benefits. We're not going to get the local tax dollar benefits. And then we're certainly when they go off and leave one of our companies, they're going to build a company that is in and native to their, you know, their country. And then it's over. And we just have to pray that that is not the next Apple or Google or Microsoft. And otherwise you just flip the entire, you know, kind of economic environment.

1:17:36And so it's just very frustrating. This is just happens to be a chart of H1B demand and applications, you know, per year. It's actually like not even that interesting graph because if you actually looked at the true demand, if you could measure how many people actually wanted and were capable and qualified to work in the US, the number would be, you know, five times larger. And again, we are currently employing all of these people. This is not going to reduce US jobs. They're employed. There's no way, like, like, you know, the kind of responses I always get is like somebody will randomly, some troll will be like, you're just, you know, trying to take US jobs.

1:18:08It's like, no, no, no, no. Like no matter what, this person on the other end is going to be employed by our company. They're just not going to be living in the US and improving our economy. And so, and so I think it's crazy. And I think that, you know, we, I'm a part of a, you know, kind of a tech lobbying kind of group or whatever we, you know, will lobby about all the things all the time. And so we'll meet with Congress and talk to the senators and and Congress, you know, people about this. And and what is what's really sad is that, you know, on a one -on -one basis, everybody right left, everywhere in between agrees with the issue.

1:18:43And there's just always one thing that's holding it up. It's, no, we have to solve the whole immigration package or we can't give this one, you know, we can't give into this particular deal that we're working on. And so this one little number in a document, i .e. the, the, the, the quota that we have, you just change that one number and our whole problem goes away. And nobody's willing to do it. Nobody's really willing to just like sign up for that project in Congress to say I'm going to do it. Brad, do you have the chart of the actual grants that happened each year? It's, it's flat. It's, it's, it's, it's been, it's basically 85 ,000 a year and it's been that way for, yeah, in 20 65 K of that's a Trombie.

1:19:22And then there's another form. And, and the process is remarkably bureaucratic. So that's another thing that probably would make the demand higher if it were, as we've proven on the southern border, if you, if you ease the pathway, you call it more to my hand. Yeah, it's, it's tough, you know, I think the biggest thing that we probably lose by not increasing that is this future founder thing that you're talking about. And on one hand, it's kind of impossible to numerate like why that could be so huge. But when you look at the legacy of immigrant founded companies in the Bay Area and the headcount that's now under those companies, it's almost impossible not to believe.

1:20:07And, and you, why wouldn't you want that aperture bigger? Well, the only thing that we just said that like, like, there, you know, there's also, you know, the argument of, okay, this is just a Silicon Valley thing. And I mean, clearly it's not like, so we all know it's not. But like, even if you wanted to prove it, it's not Silicon Valley, well, we're going to literally run out of real estate. Okay. So like, and room, we know that. So guess what? If I'm a freaking town in anywhere in the country, and I could just be like, what, I can create like 10 ,000 tech jobs. If I just become, if I, if I'm able to get this amazing talent, and they're all going to move here, like, this is totally a country wide opportunity for us.

1:20:42And we are just, we're just sitting on this and not doing anything about it. And I think it's insane. So yeah. You know, this really comes down to the question of whether we have the will, right, to increase the quota of legal immigrants. Again, we're talking about legal immigrants who companies want to hire in order to drive our economy. To your point, Aaron, we're effectively you're shipping your GDP to Poland. That would be US GDP. And said it's the GDP of Poland, because it's workers in Poland who are doing the work that you can't hire to be done here. And Bill, you make the point about, you know, we may, you know, it's hard to enumerate what we won't have started.

1:21:23The counterfactual of the companies that won't be started. But I look at just the acceleration generally, the moment we live in, we just talked about the acceleration around AI. This is not just about economic advantage. This is about national security. This is about national strategic advantage, right, that we have these things invented here, right. Again, we're lucky that Chad GPT was invented here. The open AI is here, that anthropic is here, but that's not a given. And the best way, and you know, this has been a source of our national strategic advantage for hundreds of years, right. And you know, Bill pinged me this morning.

1:22:03And he said, you know, it reminds me of this speech, you know, that Reagan gave his last speech in office. And, you know, and it made me to be fair, I found it on the Twitter's. But keep watching. Maybe we'll play it here, play it here, and then we'll end with all three of us by just wrapping in reaction to the video. It is that lady who gives us our great and special place in the world. For it's the great life force of each generation of new Americans that guarantees that America's triumph shall continue unsurpassed into the next century and beyond. Other countries may seek to compete with us, but in one vital area, as a beacon of freedom and opportunity that draws the people of the world, no country on earth comes close.

1:22:55This, I believe, is one of the most important sources of America's greatness. We lead the world because unique among nations, we draw our people our strength from every country and every corner of the world. You know, you can't say it better than that. And you know, you look at, you know, you look at what it's given us, right? You know, I came to a age in 1978 when the Japanese were devastating our auto industry, where the view in the country was that our best days were behind us. I grew up in a place that people referred to as the Rust Belt. We didn't have really venture capital. We, you know, the innovations around technology were just starting.

1:23:38And, you know, and so I think about we are, we now have such great global advantage in technology, the only way, right? In which we give way on that is to shoot the golden goose. And part of the equation, you know, the most important part is the human talent and desire to start the next thing, to invent the next thing. And I think you pointed out something incredibly important, Aaron, which is yes, we need to solve the illegal immigrant crisis on this other border. But, you know, we really do need to focus on how we continue to be the place that all the best entrepreneurs on the planet, the best technologists on the planet want to come start the next company.

1:24:24Well, Aaron, thanks for being here. You know, one of the reasons Bill and I wanted to, you know, to do a pod wasn't just to hear each other, but was really to tap into the people we admire. The big thinkers in Silicon Valley, you know, kicking around with them on occasion. So really appreciate you taking the time and I look forward to when those people join the pod. So I'll tune in for that one. But thanks for having me. Appreciate it and good luck on the charts.