Invest Like the Best with Patrick O'Shaughnessy
00:32:38 · Martin Casado
[00:32:38] S1: I lived through on the ground with formal studies in security. I lived through the internet and it was way worse than this. Like by this time with the internet, we had worms that had caused billions of dollars of economic damage. We'd taken out critical infrastructure. Remember Windows 95? You're probably teasing. No. I remember. Okay. Remember Windows 95? Just barely. It used to be that if you took Windows 95 and you installed it and it was connected to the Internet, before the installer was done, it'd be infected. Like, this has been taken away. Like, not a joke, right? Like... So like you didn't even have time to patch it. It was so chaotic and there was so much mayhem and this is what happens every time you've got a new technology that changes the nature of how we run computers in the security posture. And we're definitely dealing with another one of those moments. And so I think we can look to what happened with the internet, is like there's a few years of mayhem. You do have breaches that cause real issues and then the industry evolves. And normally, way you think about security is like, will the good guys be able to spend more money than the bad guys? If the answer is yes, which is typically the case, you will come up with a technical solution and I think that will be the case here. And you're already starting to see it. These vulnerabilities that you see showing up, this is good. That means that somebody used the model to make things safer by pointing out the vulnerabilities. I think that's going exactly like you would expect it to go. But I think the net impact at software will be much more secure because AI is also securing it.
00:34:05 · Patrick O'Shaughnessy
[00:34:05] S0: Can you talk about capital? There's very interesting things happening in capital markets. There's clearly lots of demand destruction happening. We're not funding things that we would have in a different environment because the cost of capital to fund them is too high and the cost is rising because the returns are so high on anything AI. So you've got these, I was looking at this company this morning where if you and I had seen the deck five years ago, we'd be like this is an amazing software business and we should fund it. And now it seems to pale in comparison to other things that we could put our capital to. The capital itself feels like this interesting variable in this whole equation as a constraint. I'm curious how that feels to you.
00:34:40 · Martin Casado, Patrick O'Shaughnessy
[00:34:40] S1: I sit on the boards of a lot of great companies that have the problem that you have. Profitable, growing 40, 50, 60% at scale, $304,105 100,000,000 in ARR. What do those companies do? You can't really IPO because they're subscale but they're great companies and I think about my own personal portfolio, I'm like, I'm in muni bonds, man. I'd rather be in these companies, right? And so I think that everybody would be happy with an asset that grows 40%. Like you'd be happy with your personal money being in there And if you could guarantee so I still think these are very good companies. I feel it's more a question. Again, this is my naivety of not understanding this of like, are we gonna see a shift in the market so that people can get exposure to this asset class? Because I think the risk profile is very, very different than AI. Nobody knows what's gonna happen to AI when the market slows down. Nobody knows. It could be easy come, easy go. It could keep going forever. Like nobody really knows. And so the only free lunch I've ever seen in investing is diversification. And I would love to personally have Ask it. A basket that includes these slower growing but these assets that don't disappear. [00:35:46] S0: Are most of the ones though that are in your mind extremely subjected to this disruption risk? There's lots of companies with that rough profile which seem terrifying in the face of how easy it's gonna be to create software.
00:35:46 · Patrick O'Shaughnessy, Martin Casado
[00:35:46] S0: Are most of the ones though that are in your mind extremely subjected to this disruption risk? There's lots of companies with that rough profile which seem terrifying in the face of how easy it's gonna be to create software. [00:35:59] S1: I'm an infra guy, so for me, more software means you need more infra. We don't vibe code databases yet. You do have your data [00:36:06] S0: Snowflake be a well known example of kind of what you're talking about?
00:36:06 · Patrick O'Shaughnessy, Martin Casado
[00:36:06] S0: Snowflake be a well known example of kind of what you're talking about? [00:36:09] S1: Yeah. It's a great example. It's not just building it. It's really hard to have the long tail of features, the long tail of performance tweaks to actually operate these things is really really tough. And so let's say that Snowflake is growing 30 to 40% and the economics are good. Like I don't think that they're at any risk of being disrupted by AI. Maybe by Databricks but that is like pre AI type of thing. And so, again, I'm very naive when it comes to these things. I'm a very simplistic thinker. My view is like I don't think AI is gonna disrupt these. I think they are good businesses. I think more and more, the industry is gonna want to wrap these up and get exposure. And I don't know what that looks like. It's kind of interesting. Like, we're even seeing SPACs come back. I get a lot of calls now for companies that sit on the board, which are good companies, where these SPACs are like, hey, listen. Like, we can make this stuff go public. So I think that the financial markets have to figure that out. There's a lot of companies that will be disrupted by AI but there's a whole bunch that will not and I just think the market doesn't know what to do with them right now.
00:37:02 · Patrick O'Shaughnessy, Martin Casado
[00:37:02] S0: Most meetings that you have around here, at least for me in the last let's say three months, half the meeting is about compute. And that the product across categories just needs more compute that is available to accomplish its goals. This is another way of asking about the capital thing. You guys manage a ton of money, everyone's deploying their funds at very fast paces. Each company that's working requires lots of capital. I'm trying to get a sense of the feel of how much capital itself is the constraint that like if we just air dropped a trillion dollars more in all the funds, that would be a good thing. [00:37:37] S1: I said this before but I'm gonna reiterate because it's so important. I really think the big disruption of AI is the fact that you can throw capital at problems. In the history of tech, you haven't been able to do that because it was always an engineering problem which just doesn't scale. The mythical man month is a mythical man month for a reason. Ten years ago, if I had five founders show up and they asked for a billion dollars and I gave it to them, what would happen? [00:38:00] S0: Sits there. [00:38:01] S1: Or they would detonate, right? They'd like hire a bunch of engineers and then you're really fucked. You can't throw capital in it. Can you [00:38:08] S0: explain the mythical man month? It's a very interesting idea. [00:38:11] S1: Yeah. Mythical man month basically says that you can't increase the speed of engineering. It's like a natural law [00:38:19] S0: of It's very