Invest Like the Best with Patrick O'Shaughnessy
· Henry Ellenbogen
And I think the same thing applies to AI, but I think it's not product based this time, it's IP based. So let's go back to Max as an example. Affirm most people would think about, and correctly so, as a FinTech company that empowers people to get access to credit in a safe way and actually pretty compliant, friendly way, with no tricks. And he's doing even more than that now. But at the end of the day, because he is regulated, he has a lot of legal costs in the company. He's got hundreds of thousands of contracts with merchants, he's gotta monitor his partners on how they communicate credit. And that just requires a lot of people. If you talk to him and he is talked publicly about this, he's got great belief that Affirm can grow at the rates it's growing at for a reasonable period of time. In addition, they can do it without adding headcount. And the reason for that, obviously he's gonna go lean out a lot of processes that were not possible to go do before AI. I'll tell you a really funny story with that. So I talked to him one day after he reports earnings and he explains to me, you're always asking me about how I'm using AI to become more efficient. I feel like I was late to the curve but I finally figured it out. And so he says, I have this team that goes around the company and understands processes, and we start from not a cost standpoint, but we start from a leaning out standpoint. And I think I'm making real progress there and that's why I'm able to make this public pronouncement. He is like, isn't this great? And I say to Max, why don't you come to DC and let's go see Mitch Rales. Because Danaher, who he and his brother started and he's chairman of, has been doing this for 40 years. It's called DBS, and they basically brought Kaizen back to the US and they started—they're obviously more of a healthcare company now—by going into factories, putting processes up in whiteboards, studying how they could lean them out, leaning them out and coming back in a month later to make sure because change is hard, that the change is held. And then they basically built a whole business system which has basically not only helped build Danaher, but there's over a dozen Fortune 500 CEOs in the United States who started their jobs at Danaher, including the guy who just has turned around GE.
· Henry Ellenbogen
So since you're so excited about this, let's actually go to the godfather of the United States. The reason I say that is this is just so profound, it's even hard to get your head around. Mitch would say for 40 years, because of China, we've been able to really lean out product-based businesses, working capital. But in many ways I feel like we're just getting started on processes that are done by humans. The second example that I'll talk about, and I'm talking about things that haven't been talked about as much on this show. When I first really understood what was going on with the internet, I ran a global TMT fund and my largest investment was Amazon. We invested in that when it was a $10 billion company, so I used to go to Seattle twice a year. So interesting the things you remember because it was far from Baltimore, no one would come with me, and it was a small company and people thought I understood it. And I used to go have lunch twice a year with Jeff Bezos. At the time I worked for the firm that was his largest outside shareholder. And it was obviously my research position for the firm. I learned so many things from those meetings, but one of the things I learned is the very best businesses that leverage technology, leverage it in a way where they use it to lower costs and drive revenue that result in them gaining 30% or more incremental market share in their end market. And then they take that unit economic advantage and they reinvest it in something that is persistent, even if their competition were to wake up tomorrow and do the exact same thing with people just as good as they are. And to me, that's one of the definitions, at Durable, of a competitive advantage, is if your competitor does a competitive moat attack, doing the exact same thing with people as well, or…
· Patrick O'Shaughnessy, Henry Ellenbogen
[00:00:00] S0: Doesn't matter because you're too far ahead. [00:00:00] S1: Doesn't matter. And as we all have come to understand with Amazon, they took that 3-5% cost advantage of getting that box to you. and their ability to put more than one item in the box, and they used that economic advantage to then go build fulfillment centers that are physical to reinvest into capital and infrastructure that allowed them to go down that 3% to 5% cost curve for 20 years. As I said earlier in the show, they woke up and the only people who could play their game, when eventually everyone realized what they were doing, were the people who still had the scale and the customer relationships and the trust of Walmart and Costco. And then eventually when they figured out, all three of them were great. Now the problem is the rest of retail was not so good. That's what we think about here. [00:00:00] S0: So if I say it back to you, we've seen through Mitch and others like him, this 40 year benefit of Kaizen brought to physical product world, and that AI represents a sort of kick-off of Kaizen to human work world and that that is going to have lots of stories like the Amazon story you just said, where someone gets on one of these curves early and they can't be caught. And so you're trying, I'm sure, to find who those people might be. [00:00:00] S1: We're trying to do two things. We're trying to find the people who that might be, and then we're trying to make sure we don't… [00:00:00] S0: Get killed by them.
· Patrick O'Shaughnessy, Henry Ellenbogen
[00:00:00] S0: Get killed by them. [00:00:00] S1: Mistakenly own a company, that based on last generation competitive risk was a great company and correctly, we thought was competitively advantaged, and had a good operating culture, was led by high quality people who thought like owners. But because discontinuous change changed the world, they weren't able to adapt. Now ideally what we go do is we go find those already advantaged companies and then they leverage this to go from good to great. [00:00:00] S0: If you think about all the people that have navigated change as CEOs the best that you've worked with. I'm an investor with Dave Duffield in his latest company and so he comes to mind 'cause now he's tackling AI and the guy is incredible. If you think about whether it's Mitch or Jeff or Dave or people like this that you've seen operate, what methods have impressed you the most, of how they themselves adapt first, their own mentality and then their teams, to these fast-changing circumstances. And this is a question for everyone out there that's running businesses, that is facing this same change that's a risk and an opportunity at the same time. [00:00:00] S1: Let's go pick on Luis. We talked about Luis earlier. Duolingo has a lot of opportunity with AI and a lot of risk. And the stock, depending on the day, reflects it. When OpenAI demos, how you can use OpenAI to basically do translation. A lot of times the stock goes down, or when Apple shows you how AirPods can be used to, in the physical world… [00:00:00] S0: Live translation.
· Henry Ellenbogen
[00:00:00] S1: Yeah, live translation. Stock goes down. And actually I don't think the market's wrong. Now, it's probably wrong on the magnitude, but I think what the market is saying is there's a risk, there's a risk here. So that's probably in our portfolio, one of the higher risk names. But what do we look for when Luis or Max or Dave Duffield, I think the first thing we look about is a business that already is operating well. Because if you're not operating well when you have to deal with change, you're not gonna be able to do two things at once. You can't do a turnaround and do well. I think the second thing we would say is a business that already was winning in its first end market. All the definitions we would have about winning. Substantially gaining market share, driving real economic profit that allows it to reinvest in this next S-curve. And also the other thing we really care about is people, we really stress resiliency at Durable. It's one of the reasons we like so much investing in Act 2 managers, we can go study their resiliency. When you're an investor in Max and you saw how resilient he was in Slide, and now you understand how he's gotta be resilient to implement AI, to lean out his cost and drive his revenue before his competition does. You're like, we've seen him under stress before. I think you're looking for people who have a perspective, can execute but also are humble. Because we at Durable write down our views on AI every six months and we update them. And as we've gone more into this period of change, probably we're less wrong. Our perspective is more informed you would say, than it was, as we change it every six months. But we're learning, we have the benefit of having a job that allows us to spend our time reading and thinking and talking to smart people. So even if these are really talented people, most likely they don't have as much time to go do it as we do. And we have to be very humble in our approach. So they have to have a perspective, figure out how to go do this, not be paralyzed, but they also have to be humble and constantly learning. And you know, the last thing I think practically we have to think about as investors goes back to the memo.
· Henry Ellenbogen
If you have a high risk situation, which we would all agree, Duolingo is and Affirm is, and you're really close to that part of the change, then you need to be compensated for the risk. And so what we would tell people on Duolingo is yeah, like because of this risk, the discount rate has gone up but probably commensurate, the opportunity has also gone up. We can articulate it. Luis has talked about being 20x faster in generating content. We've already seen it. He's publicly said—he developed chess, which is doing incredibly well and my kids really love that product, I mean they're addicted to it—first it was two people for six months, and then he added another four people and he developed a product in nine months. That's the best product he's ever done. And if you ever talked to him, how long would it have taken in the past? He's like, I don't know, I probably need 4-6x as many people and it would've taken them four times as long. And so you could say a startup could do that, but he's doing it. He's doing it out of his platform. That product is well over a million DAUs and is growing at astronomical rates and it's a great underserved end market. It could be a huge business. And so yes, the discount rate has gone up, but this company was purpose built for AI. You actually have a person who studied AI and taught it at Carnegie Mellon and has an organization of A players who are agile in his company, and is humble and constantly learning. A proof point on how it's making him faster than other people. It's driving real value, and obviously that means the probability of it going from a point solution or a couple products to a suite is higher. And so that's what we look for.