00:18:51 · Raj Shah
[00:18:51] S0: So it can do almost all of that except for the Bloomberg part. And this is probably somewhat by design or it's just kind of been this way and it's worked out fortunately. The Bloomberg authentication process is obviously, like, notoriously annoying because you gotta... It's two FA. So if you're logged into Bloomberg, yeah, absolutely. It can do all of that. It can grab stuff from Excel. Claude, by the way, I don't... I actually don't know about Codex two, but I would guess it would be. Claude is remarkable at writing Bloomberg, like, BQL language. It... I don't know if it's ingested all of the documentation. Because BQL is, like, still fairly new, but you ask it to write an entire script, and it'll do it in BQL in a matter of minutes. It's pretty amazing. And so you can do that. You can do that with co... You know, with CoWork or you can do it natively with Claude in Excel, and it'll drop the data in for you really quickly. It'll export it. You can then manipulate. You can upload those in the AlphaSense. And that's part of what we're doing is is... And going back to this, like, specific providers and how we're sort of piecing this thing together. One of the things we wanted to do to kind of just jump ahead here, because I talked about sort of point three of AI being monitoring portfolio monitoring is we don't have nearly as much turnover on our portfolio, I think, as the average fund does. We do have some turnover on our portfolio. I wanna be able to, on an automated basis, if a new name comes into the portfolio, I want the next five to seven comps of that name. Automatically, I wanna start monitoring news flow for those names. I wanna start seeing if there's anything on expert networks coming off. So what we can actually do, and we're working on this in real time, is you put that... You have that... Our our portfolio management system or our order management system will automatically generate a file for what our portfolio looks like. That can then go into Claude. Claude then threw an MCP into Portrait, which it has direct access to, will then ask Portrait, hey, Portrait, you know, you have a much better idea than even Bloomberg who the next five comps or peers to this company are. Give me those next five peer companies.
00:20:44 · Raj Shah
Claude can take that, throw that into a watch list for AlphaSense, which then has expert network access, has access to SEC filings, and has access to news flow, and create a monitor automatically for me. And so, again, it's like piecing all of these things together, but it gives you at the end of the day for a two person shop, an institutional level ability to monitor a lot of positions and know what's going on, not only in your names directly, but what's going on maybe in their industries or with their competitors. We had this great thing. We own a company called Luxe Experience. It's like now the dominant ecommerce provider for high end luxury. It was the result of a transformative acquisition, which is what got us involved in the name. And one of the things that was behind our thesis was, look, this is kinda gonna be the only place that these luxury brands have left to go if they wanna do ecommerce outside of their own websites. And we've done this process and, like, three weeks after we put this process... This, like... And it was, I think, a light version of what I just described in. I got an alert from AlphaSense that Brunello Cucinelli, the luxury house, had specifically called out Luxe experience on one of its commentaries as being one of the biggest growth avenues for its business. I'm like, that's huge. I would never have put a, you know, random Italian shoe, you know, shoe company on my monitoring, but AlphaSense's AI sort of knew to do that and Portrait had sort of told it, look, this is one of the peer companies you should monitor if you care at all about luxury. So it's it's it's pretty amazing, like, what you can do. I'm sure if I worked at a much more well resourced shop that had analysts, maybe there was a guy who was covering luxury and then I'm the guy covering the Internet, like, maybe he would have told me, but, you know, it's obviously not the way we work.
00:22:20 · Brett Caughran
[00:22:20] S2: Yeah, fascinating. Tell me more about the interns, a sort of a narrative violation to the current narrative on the street that AI is killing juniors. How have you thought about the ROI? Obviously, sort of discrete cloud code project's a nice thing to have interns work on. But how do you think the ROI of junior talent shifts? And how have you thought through sort of the utility of younger, more invest... AI native, perhaps investment talent?
00:22:55 · Raj Shah
[00:22:55] S0: I think the ROI... I think the value add of a junior analyst has the potential to be much higher than it was in the past. And I agree with you. I think it's a narrative violation. It's so easy to say they're gonna get run over by AI. Look. I think I'm much more likely to get run over by AI. I'm a 41 year old portfolio manager who's, like, rooted and learned the ways of the past in terms of how to invest and how to do research. And these guys are coming on the forefront. They know the best tools to use when a problem is placed in front of them, and they have a real potential to be one of the most valuable people on an investment team because the world is changing. And so there is now every day more places to go to get information. It doesn't just reside in street account and FactSet and Bloomberg and Cap IQ. Like, it's everywhere. And these guys know where to go get it. So anybody who is creative, who is driven, can enter an investment firm with a whole pipeline of ideas of, hey, here are differentiated ways that I can accelerate our workflow. Here's I can get more coverage and more efficiency out of us. And so I'm excite... I'm super excited about it. You know, when we started the firm and even as we sort of checked in as we've grown AUM at, like, where do we want to invest resources? We originally had, you know, an analyst at at a higher threshold of where we were gonna be. And now I'm like, man, and we were originally gonna hire someone in the back office first. But now seeing what's possible with somebody who's sort of just an AI native person. There's a lot of talk about AI native companies. Like an AI native person, I... Like, that value of that person is extremely high potentially. And so that's where the next hire for us may very well be is we're gonna hire somebody who can come in and automatically start knocking things out that we didn't think were possible.
00:24:44 · Brett Caughran, Raj Shah
[00:24:44] S2: Yeah. [00:24:44] S0: And it's different. [00:24:45] S2: I would sort of add... [00:24:46] S0: And I'll hand it to you, Brett. Like, I think on fundamental edge, you know, you started out having to train analysts in the ways of the Tiger Cubs and the ways the platforms, you know, how it's been done for the last ten, fifteen years the way you did it. And then I think you very early on saw this happening. You're like, well, shit. This is totally gonna change now. What the analyst needs to do, not only to survive, but to thrive, has completely changed. And I think it's exciting. [00:25:08] S2: I'd sort of give you one I'm giving to all PMs is that you've taken so much time to articulate your screening, your research and your monitoring process, go into your systems and be like, please turn this into an intern training guide and just have it spit out a 30, 40 page. Because like most PMs haven't done that. Now doing that almost for the first time, deeply articulating all elements of their process, because that's the key thing that makes these agents go, Yes. That also creates an exoskeleton for the junior person no longer has to learn through osmosis. They can actually see that articulation. They can step into the exoskeleton and actually spend their time in a much more effective way with human action cues and all sorts of these other other Totally.
00:25:50 · Raj Shah, Brett Caughran
[00:25:50] S0: And they can query it, which is amazing too. They can ask. I mean, the analog to that is just our investment values, our investment process. Stoic Point has three core investment values. It's how we sort of measure everything. We have our own investment scorecard. We grade all of our investments that way. And in the past, I'd have to sit with somebody and sort of walk through that. Instead, we upload it and we write sadly, like, very long investment letters. We don't... We only now do two a year because they're so long, but we've written hundreds of pages of our thought process. What we like about ideas, what we don't like about ideas. Some of those ideas in there are probably not good ideas, but nonetheless, we've sort of detailed them out. We can now... You could throw them as simply as, you know, somewhere in a notebook LM. And a would be analyst or an analyst that we're gonna hire can go in there, listen to a podcast about how we do it, re... You know, get summaries of different ideas and is there, you know, specific ways or mental models that we use, and they can have a conversation with an LLM about our investment process. How cool is that? [00:26:45] S2: Oh, yeah. Or do... I've seen funds do like the the Raj agent where the intern has to pitch up to an agent first before I get to find the logical flaws in this thesis. Yeah. Sort of in a low stakes way. By the time they sort of sit down and pitch you the idea, some of those dumb mistakes have been ironed out of the process. It's pretty good. You haven't done that- [00:27:06] S0: I love that.