Invest Like the Best with Patrick O'Shaughnessy
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?
00:43:17 · Patrick O'Shaughnessy, Alex Sacerdote
[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? [00:43:38] S2: Still early in our thinking here but even maybe Workday or the HR systems or the big systems of record, the agents may be running on top of them. It's good and bad. I mean CRM is going headless or they're making a headless version. And that's the bear case too that you get relegated to just being a database. There's a human interface to it, then they need to make the AI interface, which is no interface. It's just them going right into the data. You lose that customer interaction. But if the agents are going right to CRM and doing the work inside of CRM, that will solidify CRM so you won't have to think it's going away. [00:44:21] S0: Can we talk about chips? You've referenced them a few times. Infrastructure chips, everything around the data center maybe, I don't know how you conceive of it. Why is this so interesting to you? I love the modified rule of 44 percentage that's AI and percentage market share in the category. It's an interesting stat. What companies shine on that? What are laggards you know that are surprising?
00:44:41 · Alex Sacerdote
[00:44:41] S2: For the past forty years, nothing has changed in the data center. Even with cloud, Intel x 86 became the data center chip sometime in the nineties. And compute grew in the cloud era and compute workloads grow 25 to 40% every year. But Moore's law is improving at that rate. It didn't require tremendous innovation. And then there really was almost no growth in hardware for years and years and years. And the whole industry basically commoditized every part, every chip, every part of the server, the printed circuit board to the memory, to the enclosures, to the networking, there was no innovation. You would go from one gig to 10 gig, that would take seven years. And when you do switch in the first year, it does take some innovation to get to 10 gig and would create a little cycle, but then it would commoditize. Now you go to AI, the workloads are growing 10 x every year. And they're pushing every single aspect of this hardware to the physical limits of what it can do. Not only are you creating tremendous unit growth, but we call it the decommoditization of the hardware industry. I met with Sean McGuire like three years ago and he said, I wish I could come back and be a hardware hedge fund because all the companies are public and they all have powerful IP and Sequoia made some of their best investments back in the hardware day with Apple and Cisco and others. And we're in this renaissance of chips. So not only do you have tremendous unit growth, it's requiring tremendous innovation. That means every aspect of the server, memory, which used to be a pure commodity, this high bandwidth memory is stack 10 chips on top, input outputs are 10 x what they were before, took Samsung for years to do it, and it's a critical piece. And then that is constantly upgrading. So they've gotta be working with Nvidia for three or four generations in advance. We had this with Celestica. Celestica was a contract manufacturer. This has been a disaster industry since 1999. It went all offshore to China. It was commodity, but they hung on. Celestica's heritage was IBM supercomputing and they kept all that talent and skill. And then we noticed they were the sole supplier of the Google TPU server three years ago. The stock was trading at eight times earnings.
00:47:22 · Alex Sacerdote
And then they also had this whole business of selling Ethernet white box, which is code word for commodity, white box Ethernet switches into the clouds. It turns out these are excellent businesses. Not only do they have tremendous growth, but to do an AI server, it's liquid cooled, it's running so much hotter, it's 2 or $300,000 piece of machinery, whereas an old server was $5,000. If it breaks, you just throw it away. If this thing breaks, the whole thing goes down. So you become a commodity like supplier to like selling a critical part on a plane, you'll never get swapped out. It turned out they were quite good at liquid cooling. A lot of other people tried to do it and failed, and so they've retained that position. Then it also turned out that the ethernet market, in the old days, you would go from 100 gig to 400 to 800. It would be a seven year cycle to upgrade. Now they're upgrading every year. That's really hard to do. Then there's a whole software layer, the open source sonic layer. The guys at Celestica invented or some of the people that wrote that open source software, they worked very closely with Broadcom. What we thought was just a great growth driver turned out to be great competitive advantages, And they have like 60% share of the cloud Ethernet switch market, which is a crucial market for AI because AI is incredibly network intensive. And then even something like the printed circuit board. A regular server, you need 10 layers. These AI server, you need a 40 layer. And there's very few PCB suppliers that can make this. There's all kinds of complexities in there. Then we also own Elite Materials, which makes the leading ingredient, which is copper clad laminate, which goes into these boards. The PCB units are growing. The layer counts are rising. So you've got like a 50 to 60% CAGR just in the units. And then the ASPs are rising, and then the gross profits are rising, and your visibility which used to be, hey, we'll call you next week if we need you to like, hey, we need you for the next four years to be like designing this road map with us. You've gone from a 5% grower low margin to a 35%, forty, fifty top line CAGR for the next four years with rising margins. On top of that, there's shortages of everything. So even if it is a commodity, it's gonna be a great cycle. So we see that up and down the supply chain.
00:50:09 · Alex Sacerdote, Patrick O'Shaughnessy
You find these companies like, I mean, Corning, they make the fiber. They've got some ridiculously high share of the fiber that I was reading this Microsoft data center they just built. There's enough fiber to circle the world four and a half times in that one thing. And their fiber is thinner and more bendable and can be specially manufactured to the exact specs. And it's higher margin and it's the fastest growing part of their business. In networking, there's scale out, which is connecting all the server racks together. Then there's scale across, which is connecting the data centers together. And when you wanna build one of these huge clusters and you can't get all the power in one place for training, you wanna wire them together. But the wires that you need like 10 x, the wire has to be so much thicker. So that's creating huge growth. And where the real kicker comes in is when you do scale up, that's connecting every GPU in the rack to the other ones. That's done over copper. Eventually that'll be done over fiber. When that happens, that two to three x's Corning's opportunity. So you just have at every layer of the rack [00:51:31] S0: Everyone's overwhelmed.