Invest Like the Best with Patrick O'Shaughnessy
00:34:19 · Alex Sacerdote
[00:34:19] S2: Of all the s curves we've done, AI is by far the most complex and the fastest changing. We have to keep in mind that there are risks. The rewards are the highest because we're talking about a market in the trillions, maybe clouds 800,000,000,000. This might be we now think three to five, but there's higher risk, higher reward. But let's just say with Anthropic now, it looks like they have critical intellectual property. Generally, they've been able to maintain their high market share in code. Number two is they've built a strong brand for enterprise to where go talk to any CIO and the first thing they'll say is Claude. Three, they're gonna have escape velocity and scale. And what was scary for OpenAI and Anthropic fighting these big companies like Google was they had these huge cash cows. And to both of the management teams credited OpenA and Anthropic, were able to work in these super capital intensive industries and find ways to raise capital. And certainly with Anthropic, with their 10 x sales growth and their fundraising ability, it looks like they've reached escape velocity. So now they have scale. And the other thing that Anthropic and OpenAI could have is Anthropic, now that they're leading in code, they set that code back onto their model, and it's this concept of the recursive improvement. And if you look at the pace of their innovation, it's accelerating. Maybe they can have this lift off stage. OpenAI, they were focused on so many different other sectors. They're starting to do better in enterprise and their coding tools good, and they're starting to see accelerating growth on that side. And then look, the consumer franchise, it looks like enterprise right now is much better because you and I, we're willing to pay a lot because it's replacing human beings. Now consumer, maybe you can get advertising, but maybe they would pay for a claw bot type assistant if you can make that perfectly well for them. But they have gazillion eyeballs there. Things do shift. We have this charts that we almost do for all of our pitches. On the internet, the leader grows bigger, faster and wins. Most of the time the leader gets it. Shopify becomes the leader, just keeps on going. Amazon the leader keeps on going. SaaS company, x y z, you get the lead, it compounds on itself. And another thing is you need to be big.
00:36:48 · Alex Sacerdote, Patrick O'Shaughnessy
Another is scale, you need the compute, and you gotta pay for the compute. So there's only so many people that can do that. Those are some of the moats that we think are now showing up in this business. Now there are some exceptions to that rule, usually with the paradigm shift AOL, and then dial up went to broadband and they didn't make the change. Netscape came out early and it wasn't as strong of a business model. And if you talk to anyone in the Valley or any startups, they'll tell you that they're building on top of these three and the world's a huge place and the economy is a huge place that they'll be able to differentiate within those. [00:37:30] S0: I'm so curious then what you think all of this means for software. When I look through your portfolio, I don't see a ton of big software companies, enterprise software companies. I don't know if you once had them and sold them. But it's hard to have the experience of building really useful, cool little tools, even if they're still toys, and not have the thought of, wow, if I spend enough time on this, even if I'm not technical, maybe I could build a ERP equivalent replacement or something for my company. There doesn't seem to be a fundamental reason why that's not possible and then those companies could be in lots of trouble. Seems like everyone has a strong view on this one way or the other. I'm curious how you've approached those sorts of companies given that you don't seem to own a ton of them.
00:38:12 · Alex Sacerdote
[00:38:12] S2: Five years ago, we might have had 40 or 50% of our portfolio in software. And early on in our April 2023 webinar, we said definitely invest in chips first. But at the application layer, initially we thought these companies are huge. They have huge sales forces. They can take these AI APIs and build products and they have the data. This is gonna be amazing for software. Pretty quickly, we realized their AI products were not very good, they weren't moving the needle, nobody could charge for them. We basically sold almost all of our software. Entering this year we were net short, It really helped us in the first quarter. There's so many layers to this. I mean, the old way of software is like using pen and paper or it's like a horse and buggy. The new way of software is like a jet engine or frankly, the transporter from Star Trek. It's so revolutionary changing that it feels like it has to be disruptive. If it's not disruptive now or right away, the software companies have another problem which is their list on the to do list or priority list of any CIO has fallen a lot. So even if AI is not going to be disruptive, they're spending it on anthropic tokens because there's faster ROI there. Second, if they're spending all that money over there, it pushes on the budget, so that hurts them. Third, a lot of software companies were able to raise price every year, and now they're probably nervous about doing that. Then fourth, we'll see what happens with jobs because there's smart people on both sides of that but we are seeing some companies really gut their jobs.
00:40:10 · Patrick O'Shaughnessy
[00:40:10] S0: Free hiring or whatever Free hiring and
00:40:12 · Alex Sacerdote
[00:40:12] S2: so that hurts on seats. In terms of them building their own apps, if you wanna be optimistic, it's taken them a while to do that. We talked about how early the primitives in AR. So maybe they have just taken a while to get to something they can commercialize, but they might not have the right people. It's a different selling motion from selling a fixed system versus if you're installing something that does human work, you gotta be right at the side to make sure it's really getting done. So you need the FDEs, forward deployed engineers. They might not have the right people internally to do that. Then of course, there's the risk of you can build it yourself. The bulls will say, well, they're never gonna build their own ERP system. And that's probably right. And it is true that old tech is very sticky. Mobile video games didn't hurt console games, and the tablet didn't hurt the PC, and the smartphone didn't hurt the PC. There's a lot of integrations and work that goes into the software. That's all true, and companies do like to buy. They don't like to build themselves that much. That's all true, but you can imagine a world wherein one, two, three, four, five years, you could have a brand new AI native company going after each one of these very strong incumbents, and if their data advantage could get obviated, it might be easy to take it out and put the new one in with AI. The valuations are very high and everybody knows they're under pressure. Some people are tempted to buy these, but the AI coding tools are just getting better and better. We'll have to wait and see. We're watching these software companies very closely to see if they're getting any revenue that can change that trajectory. But it's hard because if you're a company like Salesforce, you've got 40,000,000,000 in sales, you might have 500 of ARR, 700 of ARR of AI. So you've got this huge base. Now maybe this starts to work but it takes a while. In software there's the rule of 40 which is your growth rate plus your operating margin and if you have 20% growth rate, 20%, that's good. For AI, we have a new rule of 40. What percent of your sales are AI? 30%. And what's your market share in that category? Say 30%. You'd be 60. That's a great place to look cause you've got exposure and you've got a strong market position.
00:42:40 · Alex Sacerdote, Patrick O'Shaughnessy
Problem with software is their AI is one or 2% at this stage and it's a long way to go. One thing we are picking up though now lately, and this is half baked, but AI could make some of these software platforms more important because what's the first thing you do with Clog? You plug it into Slack. If that can become a key repository, that will make Slack a permanent fixture within the organization. And so maybe the next wave of AI will be these agents that use tools and they might operate inside of the existing incumbent software tools to use them like a human being would. [00:43:17] S0: Just to pull on that thread, seems like the commonality of the tools they might use that are the most sticky would be network based tools. So Slack is a great example of the software in Slack itself. The software is not the special part, it's that everyone is there. I'm curious what kinds of things you would want. Is it just the presence of a network effect? Is that the only thing that really matters?