Invest Like the Best with Patrick O'Shaughnessy
00:35:04 · Gabe Stengel
[00:35:04] S1: It's still super important. I think it's actually more important to be auditable than it is to be accurate. And obviously those two things are conflated. But what's really important is that I give you an answer, you know how to use it. And if it's not accurate and you don't know how to check it and it's hard to see where it came from, you can't use it at all whether it's accurate or not because you don't trust it. If it's accurate most of the time but even when it's not, it's very easy to see the assumptions that went in where the data was pulled from, it's still actionable and it still saves you time. And then increasingly as these things go from copilot tools that you're just using for information retrieval to autopilots where you're trusting them not just to gather the information but to execute on it to have agency and actually make an investment decision or send an email, you need to have the full confidence that if you were to go back in and see why it made the decision, you would be able to understand why. Because you're gonna need to debug it. And the same way that there's gonna be individual investors that make horrible decisions and you need to go in and see what went wrong. Was there an incorrect data input? Did someone to lie to them? What was going on? You're gonna need to do the same thing with agents. And then especially in parts of capital markets that have regulators that look at these things and need to make sure there's no foul play. If you can't explain why you made a decision and the data went in, that's not gonna fly.
00:36:26 · Patrick O'Shaughnessy, Gabe Stengel
[00:36:26] S3: You were talking before about how you have to sell like a normal enterprise sales organization would. You have to grow or can grow many multiples faster than the fastest growing enterprise SaaS companies of the last era. How do you solve that problem? Like, you're really limited by the speed of humans to some degree in enterprise sales. How do you hire enough people fast enough? Like, how do you think about being able to grow at the right rate when you don't have the Anthropic cognition API usage growth? It's so easy for them to grow 10 x. It's much harder for you. How do you solve that? [00:36:58] S1: The core problem we need to solve is how fast can you make a human being productive as a salesperson, salesperson, but anyone else as a marketer, as an SDR, as a post salesperson. How quickly can they understand our business and help push us forward and push customers forward and help our end users? And so enablement and training people and constantly retraining people is the fundamental problem that we and I assume other fast growing enterprise startups have to deal with. [00:37:23] S3: So did you like use AI to build tools?
00:37:23 · Patrick O'Shaughnessy, Gabe Stengel
[00:37:23] S3: So did you like use AI to build tools? [00:37:25] S1: Oh, the internal tools we have are kinda magical. First off, every internal conversation that happens at Rogo is recorded. When anyone starts we say hey, just FYI Patrick That's how we do. You're always being recorded. It's always being filtered into the company brain. This is not in a kind of big brother situation. It's just everyone you're gonna speak to is gonna have granola or some meeting transcription running because they need to use it and they need to have excellent recall and they need to compound the knowledge that they have. And as a result, we just have this huge reservoir of information. And then we have all of these tools that people can use on top to say, oh you know what, we're deploying with this sort of public equities firm in this sort of market. Have we ever served this kind of data before or are there use cases that might be helpful? And you can pull in the conversation that a peer of your had three weeks ago and you've never even met that person because they're stationed in APAC. Being able to sponge all that information in and then get it out to people when they need it is the core problem of enablement. [00:38:25] S3: So maybe describe the internal brain.
00:38:25 · Patrick O'Shaughnessy, Gabe Stengel
[00:38:25] S3: So maybe describe the internal brain. [00:38:27] S1: How we call it Shrek for some reason because my engineers thought it would be hilarious to call it Shrek. There's a dashboard where you can see the swamp of everything that people are working on at any given time. But it's connected to all of our different systems. It is very prescriptive about what it knows our company goals are. What are our values? What are the things we wanna deliver to clients? What are our north star metrics? And so it can shape every answer and deliverable that way and it's both proactive and reactive. Someone can go in and say, I'm trying to get up to speed on how I should talk about model routing and how I should think about the value prop there for a very large institution and what the savings will be. And it can pull out all that information for you. But it can also say, hey Patrick, I see on your calendar on Thursday, you're meeting with this sort of private credit firm. Here's all the information you should know, all of the use cases that will resonate and then all of the types of ROI metrics that firms we've worked with in the past would wanna hear. [00:39:25] S3: So what's the sales pitch to talent? Let's say there's somebody that if you landed them tomorrow would be transformative because they're so high quality or well known or whatever. What is the pitch to them to come work at Rogo versus go somewhere else that's exciting right now?
00:39:25 · Patrick O'Shaughnessy, Gabe Stengel
[00:39:25] S3: So what's the sales pitch to talent? Let's say there's somebody that if you landed them tomorrow would be transformative because they're so high quality or well known or whatever. What is the pitch to them to come work at Rogo versus go somewhere else that's exciting right now? [00:39:39] S1: Always depends on the person's motivation. So it's hard to give a generic pitch. But my pitch for Rogo today for Talon is AI is going to completely transform the world. The place that is gonna be the most interesting is applied AI cause that's where AI intersects with humanity. And so the companies that dictate how AI intersects with humans and touches humans are gonna do the most interesting creative engineering and product work in the world. Finance is a domain that is the catalyst for all human progress and innovation. And capital allocation is upstream of the financing of every company, every idea, every economy. And so if you can make that more efficient, you can supercharge the world. And we're the category leading player who is the best shot on gold and not just be the $100,000,000,000 business to do it, but the $500,000,000,000 business that completely transforms capital markets. And there's such a depth and a complexity and an amount of interesting problems that's so exciting. And we have a killer group of people that is super smart, hungry, curious, and low ego that's gonna do it. Good fucking pitch. Glad I got it. Glad I invested.
00:40:40 · Patrick O'Shaughnessy
[00:40:40] S3: Say more about this capital markets piece. Historically, as markets get more efficient and liquid, their positive impact, in my opinion, grows a lot. You can chart this through market history, which isn't that long, three, four hundred years of like proper markets. What do you think is possible? Like, where might this be going and why you believe that creating more or less friction I guess in capital markets can be so powerful?