Invest Like the Best with Patrick O'Shaughnessy
· Gokul Rajaram
[00:00:00] S1: First and foremost, you've got to start with a deep and compelling problem. The good news is, there's a tremendous number of deep and compelling problems today, in every vertical and every industry. Why? Because till today, till recently, software was used more as a tool by humans. We finally have software that is agentic in nature, which means it can do the job of people. The question you have to ask is, what industry are there roles of people that are highly paid, that are doing somewhat of a repetitive job, and that can be done by software? Every three months, the answer gets deeper and deeper. You couldn't have told me that a designer's job could be automated by AI six months or nine months ago. You couldn't have told me that an architect's job could be automated by AI. A lawyer's job could be automated by AI. It turns out, increasingly in every vertical, these capabilities are getting better and better. So you want to start with, what industry do you want to be in, and what kind of job do you want to do? Second, you want to target a high-value workflow. You want to target a workflow that is deep, that is complex, and that requires custom data. I think one of the challenges with this whole space is that the models are becoming so good that, if you try to build a company that is light, that is not a hard problem, the foundation model companies are going to eat you. I met with the CIO of a Fortune 500 company a few weeks ago. I was asking him about a few startups I had invested in and worked with. He said, "Look, I don't know why I would use any of these startups. Gemini has an agent builder product, and I also use ChatGPT Enterprise, and they also have an agent builder product. And I have a thousand IT engineers who work for me. They all want to be retrained as AI engineers. So I'm just going to put them using these horizontal tools to build my AI agents. Why do you need any startups?" And so that's the kind of thing you're going to face, that if the CIO of a company, of your target customer, can build what you're building using these agent building tools, you're not going to be successful. So you've got to really go one step ahead of what can be built. Multiple steps ahead.
· Gokul Rajaram
And you've got to extrapolate to where can the capabilities of these agent building products go, and you've got to do something very, very different. So what that means is you've got to have durability, because ultimately as venture capitalists, or even as an entrepreneur, your time horizon can't be building something that lasts for one year. And that's the biggest challenge. It's not building an application, it's building an application that's durable, that basically will last a test of time. And I think there are a few things around durability. One, you need to have ownership of a scarce asset. A scarce asset could be a license of some kind, it could be a regulation of some kind where you have unique insight into it. Second, you might basically own a control point. A control point is a thing that controls how people interact with money or with data. Third, you want to maybe have hardware, which is hard to replace. Fourth, maybe you want to be part of an essential workflow. Fifth, you want to have network effects. You want to think about those things and figure out how after you take on that workflow, you can make it more durable. And finally, I think your ambition has to be to replace the entire system. In other words – increasingly what is going to happen, and I'm seeing this more and more, is every vertical has either a legacy, or somewhat new, what is called a system of record. Which is a system where most of the data is stored for that system. For example, in legal, there's a company called Filevine or another company called Clio. In sales, it's Salesforce. In healthcare, it's Epic. Now, for many years, these companies all had APIs that if you enter that industry, you could build an agent company on top of these APIs. In 2024, things changed. These companies started seeing that these agent companies, AI companies that are being built, they are starting to take on the functionality out of these companies and are treating them like a dumb database. So you started seeing last year that these companies are cutting off access to APIs. Slack has done it most publicly. Slack is owned by Salesforce. They cut off access to Glean, where Glean can no longer access Slack data. And the reason is they don't want Glean to build on top of them and then slowly suck out the value that Slack has.
· Gokul Rajaram
And I'm hearing from other verticals that they're doing one of three things. They're blocking access to APIs. They're offering their own agents for free, bundled. I think that is a great and effective strategy. Or they're charging these AI agent companies to access the data. Just to access data, the API was free. They're saying now it's $2 an API call. They're trying to make the model of these agent companies unviable. I think it's going to be very hard for an end customer to use multiple companies, where you have a system of record and then you have this agent that sometimes doesn't work with it properly. So the agent companies have no option but to also start building and offering a system of record. So every company I know is now trying to figure out how do I build the entire platform, and not just a system that does some workflows. I think last year, everyone was like, "Oh, we can do workflows. We can build what is called a system of action and live on top of the system of record." I don't think that's an option anymore.
· Patrick O'Shaughnessy
[00:00:00] S0: The Slack example is a good one of a last generation software company, which was very big and very successful. One of the most interesting investor questions, and I'm curious for your answer from the perspective of a builder and a technologist, is that the degree to which these horizontal model companies are going to destroy or be very bad for old software companies because over time it will be trivial to spin up your own Slack that has features that you want for your company and it's very reliable in all those same ways that Slack is, and therefore Slack's in a lot of trouble. How do you think about that question? Obviously, public markets seem to think software's in a lot of trouble. The multiples are really, really low. How much would you be worried if you ran a good, solid, but older software company today?
· Gokul Rajaram
[00:00:00] S1: There are two kinds of legacy companies. One is systems of records, and one is things that are priced based on outcomes. The software companies that should be the most worried right now, is where they are pricing the product based on utility. Zendesk is a good example. Literally, Zendesk prices seats, and each seat comes with utility. In other words, each seat corresponds to a customer service agent that takes a certain number of customer tickets. So, that company should be worried because I can have an AI agent sit right next to Zendesk and you can slowly siphon off. Instead of paying for 50 Zendesk seats, you can pay for 20, and I can have 30 AI agents sitting next to Zendesk. And that siphoning can happen over time. You don't have to have an all-in-one decision. It can be a two-way door decision. Those are the most endangered companies in my opinion. For these companies, you need to change your pricing model to be based on outcome, and you need to actually build the product to be based on outcome. It's easier said than done because literally you're going from a $20 or $30 per seat to maybe charging a buck, or $0.50 or $0.20 per ticket resolved and you don't know how that's going to turn out. So, you've got to change your pricing model and I think that's a very challenging thing. That's why I think many of them probably need to go private because they have to make this business model transformation in private. I think it's going to be hard for them to stay public. The companies that are less exposed are ones where the utility is not based on seats, but it's based on data that has been collected and captured over a period of time. The more timeless the data is, the more protected they are. Slack, for example, I would say might be in a little bit more precarious state because the data in Slack is not timeless. Half-life is very short. But if you have, ERP is a great example. Somebody uses NetSuite as an ERP. Now, I don't know how NetSuite actually charges but it doesn't matter how many seats you buy, the reality is it runs your whole business. And there is no compelling reason for someone to put their career at stake by ripping out NetSuite.
· Gokul Rajaram
I know over the last year there's been a lot of AI-enabled ERP businesses but there is no compelling reason to take NetSuite and say "I'm going to rip it out" because it is career limiting to suddenly take NetSuite out when you're a company running on NetSuite. So I think those companies are much more insulated, and I think obviously – you could argue that NetSuite has more time to build AI agents on top of it because they have the data. They can train the AI agent on top of it and bundle it. So essentially, I think the software public markets are not distinguishing between these two types of companies. Companies where the half-life data is low, and where you can actually have, you can literally take half of the value of this company and put it onto an AI company that sits next to it. Well, something like an ERP system, or even Salesforce for sales data and records, those are real customer records. It's going to be hard. So what are AI-native companies doing? The first thing you've got to do if you ever have to compete against them is you've got to spend a year or two first building a system that literally takes, migrates your Salesforce instance to your own company's platform. One of my companies is an AI-native company. They literally hired engineers in an Eastern European country for two years to build this migration thing, transition tool. So, you have to build a migration tool, because who's going to migrate it? You can just present your spanking new system, but this data is still there. Even for Square, for a small business, I remember, they had a point of sale. They wouldn't move to us even though it was cheaper because they had gift cards, customer data, loyalty data, payments data, all of that, even credit cards. So we had to build scripts and that took us months or years to build it for a simple POS. For something like Salesforce, you can't just say, "I'm a much better CRM." If you look at CRM, what does the CRM contain? It contains your customer record. Your customer support system contains what your customers are complaining about. And Jira or Atlassian contains what your product development team is building. Now, all of these things should be linked, because there is no linkage. You should be addressing the biggest complaints of your customers, which are in Zendesk.