The Exchanges

Q that, and you know, as the author of probably one of the best handbooks for how to grow a startup that exists, how do you advise founders to think about, you know, it's going to be 10 years. We, you might end up failing once. You might end up failing twice before you figure out what works. Like, how do you advise people to think about a 10 year journey?

A Yeah, I think, um, I think there's a few different ways to think about it. I think on the downside, in some sense, I think if things aren't working, I think because money has been so available, people have kept their companies going longer than they should. And in a lot of circumstances more recently, where sometimes the best thing you can do is just kind of quit and restart and go do something different. And the way I kind of think about it is, you know, as a founder, if you're able to go and start a company, those are probably the best, most productive years of your life in terms of ability to take risks. And therefore, if the thing isn't working, move quickly onto the next thing, right? And that goes counter to the advice of grind forever and an iteration 73.

AI assessment note: “if the thing isn't working, move quickly onto the next thing”

Q you're talking about billions and billions and billions of fuck around dollars, right? Being thrown around. And how do you feel about that as an investor, right? And as a capitalist, when you think about, yes, I mean, I agree. In enterprise value from some of this fuck around stuff, but the cost is going to be a trillion dollars of capital sunk to create that three hundred billion dollars.

A Yeah, it's, it's a really interesting question, because if you look at some of the numbers that are being quoted in terms of revenue, the revenue basis of these things is really high too. I'll come back to that in a second. I think in prior waves, we also saw mass scale investment. I mean, crypto was huge sums of money invested in ICOs and You know, even five, six, seven years ago, bad meme coins and other things, um, the internet on a relative basis to prior venture capital scale was massive investment in the internet, including public markets because companies used to go public within three, four years. And so the public market investors were really the flood of capital that happened there versus private. So now we just have these long private things. But if you look at it, for example, Azure in their last quarter announced a twenty five billion dollar quarter of which a five percent lift came from AI. So they added something like a billion, a billion and a half per quarter in new revenue for what they considered AI services on their cloud. And that's one cloud provider, right? So if you extrapolate that forward at say a five billion dollar run rate, assuming no new growth just for Azure. And if you assume, you know, AWS and GCP are seeing something reasonably similar, you're talking about 10 to fifteen billion dollars in revenue today that's growing really rapidly for AI stu…

AI assessment note: “the revenue basis of these things is really high too”

Q Who basically was asked about the next big AI applications. And this is a guy as in the weeds as any. And he goes, I don't know. So I guess I, I kind of put that out there as a little bit of a framing a lot over to you. What are you seeing in this moment? And what is your thesis about how and where to invest right now?

A Yeah. You know, it's an interesting question in terms of where, where adoption is happening. And I think like any technology wave, what we're seeing is a bunch of stuff get adopted really fast and then a bunch of things not working. And I think it's clear that 90, whatever, 99% of AI companies are not going to work out, but the one percent that will could be quite large. And, you know, I kind of think of it as three or four sort of layers to it. Obviously there's the semiconductor layer and that's NVIDIA and some startups. There's the foundation models like OpenAI, but also there's a bunch of other types of models that nobody ever talks about, right? We always talk about the language models, but there's models for biology, physics, materials, et cetera, et cetera. There's all the infra, and there's like five different types of infra, and then there's the application layer. And in the application layer, there are a handful of areas that enterprises are adopting really fast, and then there's a set of consumer products that are very clearly skyrocketing in ways that we haven't seen in a long time, right? That's ChatGPT, that's Perplexity. That's mid journey. You know, there's actually things that are working there and there's things that are working on the enterprise side. And I think from that is this under overhyped perspective, one could argue this is very under hyped in part b…

AI assessment note: “I kind of think of it as three or four sort of layers to it.”

Q Are there other aspects of, I know beyond AI, longevity is, is a big topic for you. Are there, are there others that are currently in your broader?

A There's a lot of stuff I've looked at over time and I'll give you an example. I started getting into defense tech when Google shut down Maven because I was like, oh my gosh, if Google isn't doing it, what a great startup opportunity, you know? So I started looking for defense companies and then I met Anduril and I was like, oh my God, this is like an amazing company. And at the time it was very unpopular. To back a company that was doing defense, right? And you're like, it doesn't matter left or right. It's just, let's protect our democracy, you know, like that was kind of the impetus. So, you know, it kind of feels like there are these moments in times where you realize there's either something missing, or there's interesting things happening, or a bunch of really smart people are all starting to collectively aggregate around something, and sometimes those are real trends, and sometimes those are fake trends, but

AI assessment note: “I started getting into defense tech when Google shut down Maven”

Q Answered, you ask anyone, is like, biology sounds like a good idea, and then everyone's like, everything else is like, eh, I don't know, like, there'll be something, right? Like, you know, no one has, but I am curious, like, what capital light shots on goal you think are worth taking effectively, knowing that, like, we don't know, and like, that is, should be, and very scary to everyone, right?

A Yeah, I think it's a lot of, um, if you ask, what is this wave of generative AI good at, at least on the LLM side. And again, I think there's all sorts of things you could talk about in terms of image gen and video and text of speech and all these other areas. Right. But I think it's a lot of things which are highly repetitive email jobs. Right. That's, that's what this wave and right now is really good at. And then we'll start layering on more and more complex forms of reasoning and memory and other things over time. And that'll expand the, the suite of things that can be done. But if you just ask, where is there a lot of people doing stuff that's reasonably repetitive and is effectively cutting and pasting text or data and manipulating it in small ways. That's a lot of stuff right now in our economy. And that's the places where I think this will be most impactful in the short run.

AI assessment note: “places where I think this will be most impactful in the short run”

Q venture capital of the last decade where you get tiger to Mark up your round or whatever, right? It's clearly we've seen a tremendous shift, and we talked a little bit about that with the exit market, but Yolanda, I'm curious, do you feel a shift in investing now versus kind of five years ago, and if so, kind of what is it, and how has it affected your strategy?

A It feels like we've had, uh, three or four different shifts happen over the last decade, right? If you go back 15 years ago, the types of venture capital firms that existed are very different from today, right? In terms of stages, in terms of multiple different areas of investment and dedicated funds around one umbrella across lots of different areas. And at the same time, you had certain types of specialists that didn't exist before in terms of crypto and hiring engineers and doing all sorts of things. So I think there's been lots of shifts, right? And I think what people are mixing together in different ways are shifts in business models. The fact that we just went through ZERP and basically really weird monetary policy, global pandemic, et cetera, and all the stimulus that was associated with that. And then, you know, what should venture capital look like long term? And those are, I think, overlapping topics.

AI assessment note: “It feels like we've had, uh, three or four different shifts happen”