The Exchanges

Q You get asked a lot about how to educate yourself. If you're a parent of kids, So that you can put them on a path to launch and do well and chase their dreams? Do you have a good answer for that question?

A I mean, the, the second chapter of the book's all about lifetime learning, and it's kind of a requirement that you're following your fascination because the lifetime learning comes for free if you're fascinated with something. Like, you just constantly soak up and devour new information, and I, I do think that a lot of kids get exhausted because We've made high school and college such a grind that they think the learning ends the day they walk out with their diploma. And as we all know, the best and brightest in all of our fields are on a constant learning journey. And when something new comes out, they dive in and try and figure it out. Right. And so in every, every single, uh, person in the book that we profiled has that kind of attitude about their craft, you know, in every day. And so I, I think the real test is. If you're not proactively self-learning, then you're probably not tilting against something that you really adore and are fascinated by.

AI assessment note: “it's kind of a requirement that you're following your fascination”

Q Well, when you, when you look back on your career, unpack it for a minute, um, what, what do you think the things you got right were or the things, you know, you might change in terms of your career and, and being happy and finding your passion?

A Yeah, I do feel super fortunate that I was able to do, you know, my, my dream job for over two decades, and I love innovation. I love betting and gambling, and I love the combination of being able to think through markets and disruptions and, and to be able to place bets and all those things are super exciting. Things I got right. Um, studying history, which is something I talk a lot about, and we'll be talking about in the, in the book, like knowing who the, the patriarchs were of your industry and knowing what they thought I think is super powerful in any endeavor. And then networking, you know, just like crazy. Which I think is actually easier today. So those are a couple of the themes that we developed.

AI assessment note: “Things I got right. Um, studying history, which is something I talk a lot about”

Q What's your take on all of this doomerism? Like if you're a young person, And you're in college or you're in high school. Is this, is this much ado about nothing or how do you run down a dream in the face of something like that?

A Yeah. Well, I, you know, I started the book before this happened and I've been asked the question a lot and it, it came up in the Ted talk. I, I fear that the, a lot of people are in jobs. They actually don't care about that much. And, um, there's a Gallup poll that backs this up. They came up with that word quiet quitters. They're like, 59% of the people they surveyed. Are kind of ambivalent about their job. And when you're ambivalent about your job, you're not high agency. And so you don't lean in, you know, if you, if you look at how Jason talks about how they implemented AI and all of his, his different working groups. You hear that enthusiasm and that high agency, and then you want to go try these things. And I think the best way to protect yourself from AI is to be the most AI enabled version of yourself you can be. But if you're ambivalent about your job, you're probably not doing that. And you could be, you know, a sitting duck. So I think it's the mindset that's the problem.

AI assessment note: “the best way to protect yourself from AI is to be the most AI enabled”

Q Super interesting. Bill, you, I mean, you're, you're like the software Guru. I mean, like, do you feel the same way? I mean, yeah, we'll call it. Yeah.

A Actually, I want to make a quick comment on, especially with this slide on SAS multiples. So obviously it's a price to revenue multiple slide and, and price to revenue is like this really crude evaluation tool. It's like the crudest you could possibly have. Um, I published a blog post once where I took all the internet stocks and laid them beginning to end on the price to revenue multiple. And it was like just a massive diversion. There is no such thing. Um, And so what really values companies, you know, it's typically a discounted cash flows. And so now all of a sudden the buy side's asking SaaS companies about net dollar retention, about long-term operating margin, about whether their free cash flow is greater or less than their net income, about SBC as a percentage of free cash flow.

AI assessment note: “Actually, I want to make a quick comment on, especially with this slide”

Q United States driving cabs and trucks and doing that as a job right now, how many of those do you think will lose their jobs To self-driving in the next decade or two based on just being in there. And I'm not trying to lead the witness here in any way. Obviously some people prefer a human driver, but what's your take on, on that specific part of the economy?

A I think it's impossible to go with a hundred percent automated, uh, solution because the economics don't work well. And so I think like some of the other examples that were given ATMs and whatnot, I think the, the use of non-ownership Cars is going to go way up, so it's going to keep growing through this, and humans are going to be used for, like, 50% of it instead of a hundred, and so I might not be surprised if the number actually stays the same or grows, and re, let's remember, these jobs didn't exist before because regulation had limited what the taxi market was capable of, and, and getting around that actually led to job creation, and so I, I'm not a big fan of the doomerism because around jobs, you know, there's a word Luddite that kind of is used to, to talk about it. And I don't have high confidence in any government program for skills retraining. So it's not clear to me what, okay, yes, it's happened. What do we do now? It's not clear to me. I think the thing you can do the most, one, we already talked about, use the new tools, know what it's capable of in your field. Like, get out there. And then two, if your job is going to go away, and maybe it's a job you don't care about, start thinking about where there are opportunities. Everyone's talking about it. The skilled trades are, like, we're, we're, we're short of people everywhere.

AI assessment note: “I might not be surprised if the number actually stays the same or grows”

Q It was a long walk in the desert. I mean, a lot of great companies were started, but a lot of founders gave up at that time, right?

A Yeah. And, and, and look, I mean, I think to the, if you're an early stage investor, or if you're an early stage founder, that's just getting going, or even an early stage company, because if you haven't scaled out yet, this probably hasn't affected you. It could be, it could be wonderful. Like your access to talent is going to be a lot easier. People are going to be more pragmatic and rational, but it's a lot, it's usually a long window on the other side. The other, the other challenge you have here is, In 20, I mean, we basically had a mini pullback in March of 2020, but then the Fed hit so hard that things just blasted off again, and now, and now, you guys have talked about this, but that tool's not in the toolbox anymore.

AI assessment note: “it's usually a long window on the other side”

Q on these models, roughly produce the same thing, which theoretically says that these things are getting commoditized way too quickly, and then you'd say, well, what's the ROI on all this incremental spend, which is a very interesting economic and investment question. So, I don't know, like Gurley, what do you think happens if these evals continue to asymptote, and we need more and more and more money for training?

A Some of the smarter people in the open source community have suggested to me that we need more open source connectors of types. So, MCP is actually run by the Linux Foundation, and if you think about any surface area where a model might interact with other software, the more of those connectors that can be open sourced and commoditized, it would lower, this is what Google did with Kubernetes, uh, to, to try and commoditize where workflows live off of AWS and to make it easy to migrate. And so the more you can create systems that make that type of exchange you just described super easy so that you can plug and play the model and you have to worry about things like context and how does context come in and, and data and, you know, stuff that like Glean and, and Databricks do, but how, Anyway, if you can do that, if you can create more of those connectors like that, then the models become swappable. And certainly with the, with the model companies trying to move up the stack, you have massive desire from the app layer players to try and figure this out. And we already, you know, watched what cursor's doing and playing with their own model and being forced to kind of reckon with the fact that they're coming up the stack fast. So I think that's a really good insight that this gentleman shared with me. And I think We, the founders and developers that are out there should work on more …

AI assessment note: “if you can create more of those connectors like that, then the models become swappable.”

Q always just a kind of directional vector? You know, they're, they're always like a force on the system. They're not an absolute or objective, right? They're, uh, they're just always pushing in one direction. I mean, what ends up happening With the resolution with unions, or is it just a constant back and forth to try and manage the impact they'll have on policy, politics, tax, free market, et cetera?

A So from, from, from my point of view, the, if you, if you think about Citizens United, which a lot of people were upset about, I think rightfully so, um, because DC is so money oriented, like it's coin operated. And a lot of people have vivid awareness of it being core core coin operated on the right through corporations. This is why the most heavily regulated industries are the hardest to break into hardest to innovate against. What, what I think They miss is how much of its, is, is, is regulatory capture on the left, and the difference that a union has versus a company is it's a natural monopoly, and so it actually has more power to write regulation than a company does, um, and it's going to be around every single election cycle, so if you listen to them, you know, you get what you want, and the, you know, people have pointed out that The, um, the gentleman, or he's not a gentleman, the, the individual that, that, that killed George Floyd probably wouldn't have been on the force if it weren't for the union protecting him, um, because of the stuff he had done before. But, and this goes back to the red and blue and blindness of just being dogmatic to your party. Most of the people I know that are heavily, um, Uh, prescribed to the, to the Democratic tribe refused to acknowledge that the, one of the big problems in police reform comes from the unions. And, and you can't see thos…

AI assessment note: “a union has versus a company is it's a natural monopoly”

Q because we, we invested at two million in Stripe. But then whoever did the, you know, series G or whatever it's up to, we did the hundred billion dollar mark, it's like, ah, we'll mark it down to 90. But, you know, somebody CalPERS or Harvard has two Has the same share class in two different funds at two different prices. So then you could really triangulate on reality, huh?

A Another dynamic that, uh, that makes the powder less, less dry that, that I didn't mention in the tweet storm. Imagine you're on your first or second venture fund, or imagine you're a fund that used to just have a one fund, but they've expanded to four funds. Okay. Now, imagine you don't have a lot of liquidity proof points on those funds. Do you really want to run out of money And go test whether or not you can raise your third fund or your second fund, or do you kind of want to wait and see if you can develop some track records so that, because you may be facing the imminent death of your firm if you run out too quickly and, and go back to market and there is no market.

AI assessment note: “Another dynamic that, uh, that makes the powder less, less dry that, that I didn't mention”

Q Surfare, a company I'd passed on investing in, but was intrigued by. They do Pilatus, uh, shuttles between places on the west coast here, little short runs. They did a direct listing in July. Market cap of eighty-five million didn't go well. Bill Gurley, is, uh, the IPO window opening, or are people kind of on the ledge who have no choice but to jump and hope for the best?

A One thing we didn't probably spend enough time on in the last topic, which I'll just hit on briefly, is the complexity of those unicorns. So Brad mentioned, I, I saw a deck that said there were more, um, private unicorns than public tech companies over a billion dollars at one point in time, um, which is shocking, but those, Because those companies grew up in the 99, 22, 21 timeframe where you could raise money at excessive valuation, their cap charts are very complex and rigid. They have different lick preferences at different places, and, and, and they've got board members who all have different marks and are all very worried about whether this thing can get to a certain place or not, and so it's very difficult to come in and do another private round in those situations. You might have to You, you might have to put the return in a guaranteed pick dividend IPO or some complex derivative. And a lot of people, and I think Brad would agree with this. A lot of people just say they opt out and say, no, this is too hard. I'm not going to go in there and negotiate with five different constituencies on how to do this. You can't just do a simple investment because of that.

AI assessment note: “One thing we didn't probably spend enough time on in the last topic”