Invest Like the Best with Patrick O'Shaughnessy
00:41:33 · Sarah Guo, Patrick O'Shaughnessy
[00:41:33] S2: Well, if you just work backwards from a data center full of GPUs, cooling, powering, training, and inference so we can support the use cases. All of those inputs, it actually looks a great deal like energy independence or something like that. All those inputs, there is a global supply chain. I've got my TSMC mug with me. There are parts of that supply chain that are like a very thin sieve in a place that is not necessarily stable or accessible to The US and allies. A different version of the world that will take a bunch of investment and national security and energy policy is, for example, Jacob Helberg is working on something called Paxilica. And it was like, okay. For every part of the supply chain, can we invest in more capacity and figure out what the independent paths are? I don't think that means it's all got to be created in The United States. Comparative advantage is real. But having more than one source is a position that everybody wants to be in. When we think about the components that we've invested in, we've invested in the labor gap for data centers and robotics. We've invested in nuclear energy. We've invested in alternative chip architectures. We keep looking at people who are essentially data center builders, solar and battery installers of some kind. Part of this is the actual capacity buildup. That's a very operational business, like somewhere between operations, some technology, and real estate. [00:43:03] S0: And financing. Yeah.
00:43:03 · Patrick O'Shaughnessy, Sarah Guo
[00:43:03] S0: And financing. Yeah. [00:43:04] S2: And financing. Absolutely. That's probably the dominant thing. We have not invested in it yet despite looking very closely. I'm not opposed to it, but fundamentally, I'm a technology investor. Like, I wanna understand what it is that is the durable product asset people are building. [00:43:20] S0: What are the base debates inside of conviction? You've got such an interesting team. Like, partner is a very technical person, amazing engineer. The young talent in your firm brings really interesting perspectives. So I'm imagining great lively debates about things that matter, etcetera. What are the big debates today? [00:43:38] S2: Alad and I have a podcast called No Priors. This premise of some of the things you believed, especially about markets as a pastor, like no longer true is an interesting one. And regularly, we look at companies in domains that are not traditional software domains. Not even traditional software domains, but can you make money in this market at all? Venture investing in semis companies, Lip Bu Tan aside, was like a god awful business for the longest time. The returns [00:44:10] S0: Everyone told me this.
00:44:10 · Patrick O'Shaughnessy, Sarah Guo
[00:44:10] S0: Everyone told me this. [00:44:11] S2: Yes. It was really bad. That's like a example of Bella, a partner on our team, started looking at a bunch of these companies and it's obvious that the demand is there. Now I think we have arrived at the conclusion that others are as well, which is, well, the market is different today. We are seeing consolidated at scale demand for accelerators or even supply chain independence because the big buyers of it want it too. We can't all be stuck on one line at TSMC. All of that is very, very valuable and that changes the risk equation for these companies. We start with pretty aligned beliefs about the direction of travel or the problems that are worth working on. And then a lot of the debates are like, is the market friendly to a venture backed company or not? Space is not a friendly market to a venture backed company, but is it possible? Is the distribution of outcomes worth betting on? That could be true in solar and batteries and nuclear, in turbine manufacturing, in robotics and biology. These are not your favorite software markets from ten years ago. Each of them is a new debate. Biology is an interesting one where by virtue of seeing the data empirically, I have now strongly moved to one side of the debate. [00:45:32] S0: What side is that?
00:45:32 · Patrick O'Shaughnessy, Sarah Guo
[00:45:32] S0: What side is that? [00:45:33] S2: You can create and capture enormous value with models in biology. And there could be different AI software in biology. We're the first check-in a company called Chai Discovery. And Chai is working with a number of top 10 pharma companies in really significant ways to accelerate some part of the r and d process. The conventional wisdom when we invest in this company... And I've been looking at computational biology companies of different sorts for five plus years at that point. The conventional wisdom was the only way you make money in biotech or serving pharma is by make a drug and then get biobucks deals and then decide how far along that risk path you wanna take. And what that means for the capital structure of the company is, okay, the great traditional biotech firms find these principal investigators, and they own 40% of the company, and they're kinda assembling these things, turning them into candidates. But most of it doesn't work. So it's just like a very different distribution of outcomes and structure and way to invest in businesses. Dumb software investors, you can't make money selling software to pharma or build platform businesses in pharma. The debate is, does it change with models? I'm a strong yes now. We still have a question to solve on regulatory. There's the speed of the physical world and safety is not something you can overcome easily, but I think we should see a massive acceleration in cures. [00:47:00] S0: What flipped that for you? What evidence did you see from we don't know yet?
00:47:00 · Patrick O'Shaughnessy, Sarah Guo
[00:47:00] S0: What flipped that for you? What evidence did you see from we don't know yet? [00:47:04] S2: We invested when we didn't know yet. That's part of the fun adventure. We were like, it is possible. It is worth trying. Yeah. There's no genius here. That's a $10,000,000 contract. The other piece is actually you just talk to the scientist at the customer or somebody who leads a [00:47:20] S0: User of the tool. [00:47:21] S2: Yeah. The user of the tool or you see there are also end user adopted tools, product led growth tools that are working in the space. Well, the customer knows if it's valuable or not. The light bulb moment for the industry is when we will have a new indication or a new drug that clearly the trajectory of the thing was changed, created by AI. We should see a huge wave of investment and rightfully so, but it's going to happen. I'm, like, very impressed by the speed with which pharma and health care overall has said, yes, this is gonna make a difference, and we actually think it's gonna change the business.
00:47:59 · Patrick O'Shaughnessy, S3
[00:47:59] S0: Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions nobody's watching. Ramp puts guardrails on spending before it happens. Real time limits, automatic rules, zero firefighting. Try it ramp.com/invest. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest. Ridgeline offers one unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Schedule a demo at ridgeline.ai. Every investment firm is unique, and generic AI chatbots don't understand your process. Rogo is built by finance professionals. It's connected to your data, learns your process, and quickly produces client ready outputs. Check them out at rogo.com/invest. The best AI and software companies from OpenAI to cursor to perplexity use WorkOS to become enterprise ready overnight, not in months. Visit workos.com to skip the unglamorous infrastructure work and focus on your product. [00:49:07] S3: Article conviction.