Invest with AI
00:40:05 · Khe Hy, Doug Clinton
[00:40:05] S1: Yeah. I I would say that I have seen a small resurgence of kind of like the wrapper vertical tools, this first pass tool or something that just gives me all the investor transcripts and so on, like cleans it up. You know, the three steps that you had to do in Claude to get to sanitize and get that data into the working format. And people are more open to those. But it's a little bit aside of your outside of your question, Brett. In terms of the platform, I think that people want to... People kind of want the iPhone of all this. It's like you push a button. Yeah. And there's a recognition that the minute it becomes the iPhone, then you've flattened out the edge into the product. Right? And so you need to have an iPhone that's more like an Android where you can customize this widget and this widget and this widget and this data source. But then you're kind of back at the same starting problem. And so I think that people are it's a big change management question. And I think one of the questions that I think larger firms will ask is like, what will get people to use the thing? Right. And if it's giving them an iPhone, then give them a damn iPhone. But I think that there are always going to be firms that are going to say like, I want you to have the iPhone and I want you to have Chrome because I want you to take that widget because we never do the widget that way. Yeah. [00:41:36] S0: Yeah.
00:41:36 · Doug Clinton, Brett Caughran, Khe Hy
[00:41:36] S0: Yeah. [00:41:37] S2: Yeah. And then that intersects the sort of obsolescence or the bitter lesson dynamic. Like, I look back to our fall twenty five curriculum where we were teaching people about chat GPT projects and downloading documents, uploading them, creating system prompts, all of this, which is, like, completely obsolete now. Yeah. So how do you deal with the change management problem while the sort of like the baseline of what needs to be changed is constantly evolving and continually up for debate? A hairy Lots [00:42:10] S1: of work for people like us. [00:42:11] S2: It's a hairy, it's a hairy problem.
00:42:11 · Brett Caughran, Doug Clinton
[00:42:11] S2: It's a hairy, it's a hairy problem. [00:42:13] S0: I think, you know, and I think a lot of lot of finance organizations, larger ones, even mid sized ones, I think they want to try to build this themselves in certain ways and for certain reasons. Compliance related, right? Control related, all these things. But working with somebody who knows and has a vision for it, I think, is super important. Kaye, I know you work with a lot of companies that are trying to figure this problem out. But the thing I think every firm needs to think about is they all need to operate a little bit like a start you know? And and to the extent that you're not willing to maybe break a few rules and and really try to figure things out in a unique way because things are changing so fast, I think it will put you behind the firms that are willing to take the risk, invest in the technology, invest in, you know, maybe even some of the governance risk and whatever else comes with that and understands what this new world looks like with LLMs being a much bigger part of all investment related processes.
00:43:13 · Brett Caughran
[00:43:13] S2: Yeah, the tricky part is if you look at the top 100 hedge funds, certainly near the top of that stack, I think most funds will build that in house. But even quite large funds, multi 8 figure you know, AUM, billion AUM funds, like there many of these teams, the investment teams are still quite small, you know, 10 to 15 people and, you know, relatively small internal IT teams. This is a big lift to build these, not just to build the first version, but sort of navigate this obsolescence risk and eval structures. And it's a it's not a it's not an immaterial expense. It's not an immaterial, you know, corporate strategy shift.
00:43:55 · Khe Hy
[00:43:55] S1: And to just piggyback off what Doug said, the need for a vision, right? You cut it outside of the Citadels where like, you know, there's hundreds of people that are paid a lot of money to solve this problem. But once you get to that tier below, you need to have someone in leadership that's AI pilled because they will not break the thing that needs to be broken. They will not take the risk that needs I mean, there are I still talk to very successful firms like we have web search turned off on Claude. Like, what? Like, I didn't even know that that was a feature, let alone in 2026. Right? Like you need someone with that vision because from that vision, you're going to nudge compliance. You're going to take a governance risk. You're going to pay some money to give some analyst who's, you know, also AI pilled a bunch of Fable tokens to go figure some stuff out. Is a hard those are a lot of hard pieces. You know, it's like playing chess, like with all these pieces to move around and someone added. And then the chess table board is vibrating at the same time. So like the piece that you thought was in the corner is actually have moved over one cell by, you know, within, you know, a quarter. Yeah.
00:45:19 · Brett Caughran
[00:45:19] S2: Alright, Doug. Asked I I asked Fable, build me a stock portfolio of 10 stocks. Alright. Compute substrate is 35% of the portfolio. NVIDIA is a 12% position. TSM 10. AVGO 8%. VRT 5%. I didn't I didn't tell them make an AI portfolio. I just said build me a portfolio of 10 stocks. Distribution abstraction layers, 35% Microsoft, Meta, Amazon, and now another 35%. The token beneficiaries Palantir, Spotify, another 20%. And then it's giving me a 10% cash or hedge. So without any prompting, it built like a super concentrated high octane AI portfolio. No biotech, no consumer staples, no REITs, no banks. So yeah, over the last thirty six months, that probably shows like massive alpha. But how do you, like, you know, sort of when the tide goes out, this portfolio is getting absolutely smacked. Right?