Invest Like the Best with Patrick O'Shaughnessy
· Gavin Baker
[00:00:00] S1: Everything was not keeping up with them. So I think it's the fact that semiconductor venture has come back with a vengeance, Silicon Valley stopped being Silicon Valley long ago. My little firm maybe has done more semiconductor deals in the last seven years than the top 10 VCs combined. But that's really, really important because now you have an ecosystem of companies who can keep up. And then that ecosystem of these venture companies is putting pressure on the public companies that are also need to part of this if we're going to go to this annual cadence, which is just so hard. And it's one reason I'm really skeptical of these ASICs that don't already have some degree of success. So I do think that's a super, super important dynamic and one that's absolutely foundational and necessary for all of this to happen, because not even Nvidia can do it alone. AMD can't do it alone. Google can't do it alone. You need the people who make the transceivers, you need the people who make the wires, who make the backplanes, who make the lasers. They all have to accelerate with you. And one thing that I think is very cool about AI as an investor is it's the first time where every level of the stack that I look at, at least, the most important competitors are public and private. Nvidia, they're very important private competitors. Broadcom, important private competitors. Marvell, important private competitors, Lumentum, Coherent, all these companies. There's even a wave of innovation and memory, which is really exciting to see because memory is such a gating factor. By the way, something that could slow all this down and be a natural governor is if we get our first true DRAM cycle since the late '90s.
· Patrick O'Shaughnessy, Gavin Baker
[00:00:00] S0: Say more what that means. [00:00:00] S1: If the price of DRAM, if a DRAM wafer is valued at a five karat diamond. In the '90s, when you had these true capacity cycles before Taiwan Semi kind of smoothed everything out and DRAM became more of an oligopoly, you would have these crazy shortages where the price would just go 10X, unimaginable relative to the last 25 years, or like a giant DRAM cycle, a good DRAM cycle as the price stops going down. An epic cycle is maybe it goes up, whatever it is, 30, 40, 50%. But I mean, if it starts to go up by Xes instead of percentages, that's a whole different game. By the way, we should talk about SaaS. [00:00:00] S0: Yeah, let's talk about it. What do you think is going to happen?
· Gavin Baker
[00:00:00] S1: Well, I think that application SaaS companies are making the exact same mistake that brick and mortar retailers did with e-commerce. So brick and mortar retailers, particularly after the telecom bubble crashed, they looked at Amazon and they said, "Oh, it's losing money. E-commerce is going to be a low margin business. How can it ever be more efficient as a business? Right now, our customers pay to transport themselves to the store and then they pay to transport the goods home. How can it ever be more efficient if we're sending shipments out to individual customers?" Amazon's vision, of course, "Well, eventually we're just going to go down a street and drop off a package at every house." And so they did not invest in e-commerce. They clearly saw customer demand for it, but they did not like the margin structure of e-commerce. And that is the fundamental reason that essentially every brick and mortar retailer was really slow to invest in e-commerce. And now here we are and Amazon has higher margins in their North American retail business than a lot of retailers that are mass market retailers. So margins can change. And if there's a fundamental transformative kind of new technology that customers are demanding, it's always a mistake not to embrace it. And that's exactly what the SaaS companies are doing. They have their 70, 80, 90% gross margins and they are reluctant to accept AI gross margins. The very nature of AI is a software. You write it once and it's written very efficiently, and then you can distribute it broadly at very low cost. And that's why it was a great business. AI is the exact opposite where you have to recompute the answer every time. And so a good AI company might have gross margins of 40%. The crazy thing is because of those efficiency gains, they're generating cash way earlier than SaaS companies did historically. But they're generating cash earlier, not because they have high gross margins, but because they have very few human employees. And it's just tragic to watch all of these companies. You want to have an agent, it's never going to succeed if you're not willing to run it at a sub-35% gross margin because that's what the AI natives are running it at. Maybe they're running it at 40. So if you are trying to preserve an 80% gross margin structure, you are guaranteeing that you will not succeed in AI. Absolute guarantee.
· Gavin Baker
And this is so crazy to me because one, we have an existence proof for software investors being willing to tolerate gross margin pressure as long as gross profit dollars are okay. And it's called the cloud. People don't remember. But when Adobe converted from on-premise to a SaaS model, not only did their margins implode, their actual revenues imploded too, because you went from charging upfront to charging over a period of years. Microsoft, it was less dramatic, but Microsoft was a tough stock in the early days of the cloud transition because investors were like, "Oh, my God, you're an 80% gross margin business." And the cloud is the 50s and they're like, "Well, it's going to be gross profit dollar accretive and probably will improve those margins over time." Microsoft, they bought GitHub and they use GitHub as a distribution channel for Copilot for coding. And that's become a giant business, a giant business. Now for sure, it runs at much lower gross margins, but there are so many SaaS companies. I can't think of a single application SaaS company that could not be running a successful agent strategy. And they have a giant advantage over these AI natives in that they have a cash-generative business. And I think there is room for someone to be a new kind of activist or constructivist and just go to SaaS companies and say, "Stop being so dumb." All you have to do is say, "Here are my AI revenues and here are my AI gross margins, and you know it's real AI because it's low gross margins. I'm going to show you that. And here's a venture competitor over here that's losing a lot of money. So maybe I'll actually take my gross margins to zero for a while, but I have this business that the venture funded company doesn't have." And this is just such a obvious playbook that you can run Salesforce, ServiceNow, HubSpot, GitLab, Atlassian, all of them could run this.
· Patrick O'Shaughnessy, Gavin Baker
[00:00:00] S0: And the way that those companies could or should think about the way to use agents is just to ask the question, "Okay, what are the core functions we do for the customer now? How can we further automate that with agents effectively?" [00:00:00] S1: If you're in CRM, well, what do our customers do? They talk to their customers. We're customer relationship management software and we do some customer support too. So make an agent that can do that and sell that at 10 to 20% and let that agent access all the data you have. Because what's happening right now, another agent made by someone else is accessing your systems- [00:00:00] S0: To do this job. [00:00:00] S1: ... pulling the data into their system, and then you'll eventually be turned off. And it's just crazy and it's just because, "Oh, wow, but we want to preserve our 80% gross margins." This is a life or death decision, and essentially, everyone except Microsoft is failing it. To quote that memo from that Nokia guy long ago, "Their platforms are burning." [00:00:00] S0: Burning platform. Yeah. [00:00:00] S1: Yeah. There's a really nice platform right over there and you can just hop to it and then you can put out the fire in your platform that's on fire, and now you got two platforms and it's great. [00:00:00] S0: Your data centers in space thing makes me wonder if there are other kind of less discussed, off-the-wall things that you're thinking about in the markets in general that we haven't talked about.
· Patrick O'Shaughnessy, Gavin Baker
[00:00:00] S0: Your data centers in space thing makes me wonder if there are other kind of less discussed, off-the-wall things that you're thinking about in the markets in general that we haven't talked about. [00:00:00] S1: It does feel like since 2020 kicked off and 2022 punctured this, a series of rolling bubbles. So in 2020, there was a bubble in startup EVs that were not Tesla. And that's for sure a bubble, and they all went down 99%, and there was a bubble in more speculative stocks. Then we had the meme stocks, GameStop. And now it feels like the rolling bubble is in nuclear and quantum. And these are fusion and SMR. It would be a transformative technology. It's amazing. But sadly, from my perspective, none of the public ways you can invest in this, or really good expressions of this theme are likely to succeed or have any real fundamental support. And same thing with quantum. I've been looking at quantum for 10 years. We have a really good understanding of quantum, and the public quantum companies, again, are not the leaders. From my perspective, the leaders in quantum would be Google, IBM, and then the Honeywell Quantinuum. So the public ways you can invest in this theme, which probably is exciting, are not the best. So you have two really clear bubbles. I also think quantum supremacy is very misunderstood. People hear it, and they think that it means that quantum computers are going to be better than classical computers at everything. With quantum, you can do some calculations that classical computers cannot do. That's it. That's going to be really useful-