Invest Like the Best with Patrick O'Shaughnessy
00:18:51 · Patrick O'Shaughnessy
Ad[00:18:51] S0: Vanta automates compliance so your team can spend less time on security reviews and more time getting customers. Vanta cuts audit prep by 82% and gives you instant up to date proof of trust without all the manual work, so you can close deals faster and with less friction. Customers report a 526% return on investment, and more than 16,000 companies use Vanta, including Ramp, Harvey, and Snowflake. Get started with $1,000 off at vanta.com/invest. Ridgeline is the first end to end system of record with embedded AI for investment management firms running portfolio accounting, reconciliation, reporting, trading, and compliance on one unified platform. Firms are moving off legacy technology and onto Ridgeline because of how far ahead Ridgeline's AI features are compared to anything else in investment management software. I've been hearing from a lot of investment managers about AI and they fall roughly into two camps, with some unsure where to even start and others convinced they can build their own order management system over a weekend. The reality is that running an investment firm will always require governance, controls, and a single source of truth for your data. And no amount of AI enthusiasm changes that requirement. Ridgeline is built on exactly that foundation, which is why I believe that the firms that come out ahead in the AI era will be the ones running on Ridgeline's unified platform. If you're serious about your firm's AI strategy, Ridgeline should be part of that conversation, and you can request a demo at ridgeline.ai. We were just talking about the weird nature of the market where on the one hand you've got Elon saying there's gonna be all this stranded capacity and compute and Neo Cloud's having quite a tough week in the markets. At the same time, literally nobody can seem to get generation prior, let alone current generation, bilirubin or something allocation from NVIDIA. And the price of GPUs just looks unidirectional. It seems to me like a very bizarre moment in the market.
00:20:49 · Ramtin Naimi
[00:20:49] S1: The thing that we're seeing in our portfolio companies is that we are routinely helping them find compute because finding compute for them is not easy. A lot of the largest neoclass, and we have relationships with a number of them, aren't really interested in engaging with compute deals that are, like, sub $200,000,000 in scale. And so companies that don't have that level of scale are, you know, trying to lease some capacity here, some capacity there. But those guys, on a relative basis, don't actually make up for the scale of this market. The people that are actually moving the needle for how much compute is necessary in this ecosystem are the hyperscalers, the frontier model labs, and then, you know, the companies that are private. NeoLabs raising $1,000,000,000 plus seat valuations effectively. I think the only thing that limits demand for compute over time is if their compute needs from these companies diminish or the companies that have these compute needs have a harder time raising capital. There's a subset of companies that you know, I know that are gonna continue raising because they're the best assets, and they'll have all the cash they need to buy all the compute they need. I think the most interesting segment of the market, which on a relative basis is still small for the hyperscalers, but if you can aggregate all of them together, I don't think the scale is that small. It's sort of the Neolab segment where people started looking at NeoLab, saying there was gonna be, like, two or three great ones, and now there's probably 80 or 90 NeoLab that have raised somewhere between one to five billion dollars. And the funniest thing with them is, like, they all need to raise tons of cash. We met in NeoLab a couple weeks ago that was raising a $1,000,000,000. I think this was their second round of financing. And they were gonna spend the entire billion next year on compute for one training run, and they said they would probably need to raise another 5,000,000,000 throughout next year. The tricky thing with these companies is it's very hard to underwrite how well they're doing. The funny thing with Neolabs is you kind of underwrite how well they're doing this and how much money they're raising. But oftentimes, they're launching things that are very impressive.
00:22:36 · Ramtin Naimi, Patrick O'Shaughnessy
Oftentimes, it's hard to discern whether they're launching something that's truly impressive on a generalizable scale or if they launched something that was specifically tuned to perform really well on benchmarks. So that's the whole benchmark maxing concept of whether these things are truly groundbreaking and innovative or they did something that shows really well on the benchmarks but isn't really commercializable yet. It's not gonna be commercializable for the near future. But I think there are a lot of those companies that have massive capital needs, and it'll be interesting to see if all of them continue to raise, if 50% of them continue to raise the capital they need or if it's, like, 10% of them continue to raise. [00:23:10] S0: Could it just be capital is the actual constraint that if the capital markets dry up, then that will be what causes the compute story to change? That's it? [00:23:18] S1: Potentially. And I think it's more on the debt side than the equity side. I think a lot of these guys that are building these things, they need debt in excess of five to 10 x of the equity that they raised. Given what happened in public markets with some the neoclass in the past couple of weeks, I think their cost for debt is going to increase. So I think it's less about whether these companies are able to raise the equity they need to produce this compute for the demand is gonna be more along. Could they raise the debt they need at terms that make sense for, like, business viability to continue for the show to go on?
00:23:18 · Ramtin Naimi, Patrick O'Shaughnessy
[00:23:18] S1: Potentially. And I think it's more on the debt side than the equity side. I think a lot of these guys that are building these things, they need debt in excess of five to 10 x of the equity that they raised. Given what happened in public markets with some the neoclass in the past couple of weeks, I think their cost for debt is going to increase. So I think it's less about whether these companies are able to raise the equity they need to produce this compute for the demand is gonna be more along. Could they raise the debt they need at terms that make sense for, like, business viability to continue for the show to go on? [00:23:48] S0: What about commenting just on seed as, like, a concept? Some seed deals that get done at just crazy prices and don't really feel like seed, they're like seed risk for a series D pricing or something like this. Of course, with the promise that these new markets are bigger than ever and everything can be a 100,000,000,000 company now as part of every single pitch. How do you feel about seed given that's where you've spent most of your career?
00:24:12 · Ramtin Naimi
[00:24:12] S1: Every few years in Silicon Valley, the goalpost moves for what terminal outcomes can actually be. So, like, when I got started in early stage investing in 2016, people looked at every company from the lens of in a best case scenario, this could be a $10,000,000,000 outcome and price deals accordingly. And then you started getting towards 2021 when you had Stripe and Databricks and Airbnb and DoorDash approaching $100,000,000,000 valuations, then everybody started looking companies from the lens of, in a best case scenario, this company can be worth a $100,000,000,000. And then they started pricing deals accordingly. Turns out the companies that were on track to be $100,000,000,000 companies in 2021, give or take two or three more, ended up being the only companies worth a $100,000,000,000, but every other company started getting prices if that was the potential outcome for them. And then now we're at a new goalpost. In a best case scenario, this company could have a trillion dollar outcome. Then now between SpaceX and Anthropic and OpenAI, you have three trillion dollar companies. My bet is there might be two to three more and not 40 more. But now everyone's looking at companies from the months of, in a best case scenario, you have a trillion dollar outcome. So, like, what is a $1,000,000,000 entry valuation, a trillion dollar outcome scenario? So I think that's what ends up happening that that shifts the dynamic for what these valuations happened at. But if you look at every stage and venture, there's always opportunities to get good pricing on great companies. I think, generally speaking, the investors that don't do great and bad vintages are the investors that deploy the majority of their capital into the most obvious thing. Venture capitalists that deployed the majority of their capital into the most obvious thing in 2021 were VCs that were doing 100x revenue multiple SaaS deals with pretty much the entire bulk of their portfolio. And they're probably in now the bottom quartile or bottom 75% of venture capital funds for that vintage. But I think, generally speaking, if you are at the early stages at least, if you're backing great founders working on obviously good ideas, you're going to pay sky high market pricing, especially in frothy markets.
00:26:07 · Ramtin Naimi, Patrick O'Shaughnessy
But if you back great founders working on non obvious ideas, that generally tends to be the best way to generate alpha in markets like this. Because if you are truly backing the best founders, they're not working on bad markets. They're usually just early to markets. I think in venture capital, there's two ways to make returns. One is by being reactive, and the other is by being proactive. And I think reactive, if you pick correctly, allows you to be a top quartile manager. And I think being proactive allows you to be a top 5% manager. Being proactive means trying to back great founders working on markets that aren't yet obvious. And if the ideas aren't yet obvious, that means you're not gonna get a lot of competition. You can price these deals accordingly. Couple of examples for this. We seeded a company, like, nine months ago called Conduit, which is which is working on BCI, brain computer [00:26:53] S0: Really interesting people.