Invest with AI
00:46:59 · Robert Yang, Brett Caughran
So so a hypothetical experiment is like, okay, if you can build an agent or like a team of agents that operate like a hedge, like a hedge fund, or even just like a team within a like a multi-manager hedge fund, right? Like a portfolio manager and analyst, right? If you just have uh agent teams like that, and you show that they can actually do paper trading and uh and make good outcome, right? The sharp ratio is high, etc. etc. Now you provide that foundation to real professionals, and they can build on that and they can customize that and they can make it really, really good, right? So that's that's what we're thinking now, right? The core of it is still like the workhorse is an Excel agent that's really good at like understanding models, but beyond that, you're gonna have agents that is able to do research, right? That's that's able to like keep monitoring news, right? And um, and uh all these agents need to be orchestrated, for example, by some portfolio manager. So this is this is what we're building next. [00:48:10] S1: Yeah, yeah, yeah. That makes sense. And what what has been your reaction to the rise of the personal agents? So sort of instinct was the first to hit the national sort of awareness, then Muse far behind, and now we have Hark Labs and Rockbox getting a lot of attention recently. Like what was what was your take on what what was and is your take on those personal agents?
00:48:35 · Robert Yang
[00:48:35] S0: Yeah, yes. So the first shock was OpenClaw, right? So OpenClaw, I was I think earlier this year, right? It feels crazy because it feels like a long time ago, but I think it was just earlier this year. Um, and uh when that first came out, we did a journal club like every week on Open Claw for three weeks in a rope because we felt like this is so important. And uh, in many ways, it's very similar to what we did back in Minecraft, right? These like long-running agents that had their soul, that had their memory that keep getting updated. Um, they're autonomous, they're proactive. So I think we felt a sense of um maybe loss, like, oh, like we missed out on this opportunity. Um, but now there's an opportunity to for us to combine, I guess, personal agent with what we have been doing. Um so I definitely think the but overall, I think the the rise of personal agent reflects a really deep desire to have a better interface with agent, right? Because the traditional interface we have had as people who, for example, use codecs, uh, cloud code, and etc., is like, okay, you have these threads, right? Everything you want to do is a thread, right? Um, and at some point it becomes very like annoying to manage, right? You have all these threads, and and it was okay when you're just working on like three threads or like two threads at a time, but as the agents become more and more long-term autonomous, right? So this is almost mathematical. As the agents become more and more long-term autonomous, right, they require less intervention from you. And as a result, you can run more threads concurrently, right? So if you have to, if an agent can be independent for five minutes and require one minute, and then you have to intervene and it takes one minute for you to intervene, then you can run five agents at a time. But if they can run 50 minutes and it takes one minute to intervene, then you can run 50 of them at a time, right? If you can afford it, etc., etc. But when you can run 50 agents at a time, then having 50 threads that are just there and you have like jumping back and forth is crazy. And I know this because I've done it, right? I've had time like having like literally 50 agents running, 50 threads running concurrently. At some point, I had three monitor, I had thread desk, I had threet desk, seven monitors, right?
00:51:13 · Robert Yang, Brett Caughran
And each monitor had like six terminal opens, terminal windows open, each with was a like a cloud code or codex red. So I would literally have have like 40 terminals open just like all around me, and I was like managing them. I would like turn my chair and manage them, and that's a very bad user experience, right? So yeah, that's a very bad user experience. Whereas in reality, right, you can talk to someone who manages a large team without having to worry about micromanaging every single person, right? Um, so I think that's fundamentally what the personal agents are doing. Most users don't really care how the work is done, right? They just want it done. They don't want to be like individually managing all the 50, 50 sub-agents, 50 agents that's that's working. Um, and I think we see that definitely in our users as well, right? Our some of our power users are really like going very like um very hard, very hard on like multi-agent, right? And we want to provide them also a better interface so that they can just talk to like one agent who will essentially manage all their agents for them, right? And they can talk to them just like you talk to a human instead of having to type out some prompt. [00:52:35] S1: How close do you think we are to working with a digital hedge fund analyst? And as a sort of existing analyst, we just interface with that with that being as we would a new junior analyst on the team.
00:52:49 · Robert Yang
[00:52:49] S0: Yeah, yeah, absolutely. So I think um the short answer is I think very, very soon. The model capability is already there. I think it's just like and the interface, we already kind of know what it should be. So it's it's just about some polish. But I think within like like two months for sure, like people uh it it will be there, but then not everyone's gonna have it, right? Because it takes time to go through the the the essentially the compliance uh review uh for good reasons, right? It takes time to go through this, but I think the industry, uh pretty much everyone would be using these, I would say in six to six to nine months, right? I think I think as in there would be a point if you work at like an investment firm, and if you're not like working with these kind of always-on agents, right, like a digital analyst, then you would feel like it's like prehistoric, right? It's like doing work today manually in Excel, right? I'm like building out everything just with keyboard shortcut, right? So that's how people would feel. Um, that's my guess, is maybe six to twelve months, right? Uh so now that said, um I don't think it will necessarily be uh complete, like, oh, like a human analyst, right? So I do think there are things that it will do much better than an analyst, like a real human analyst, like it will just like monitor all the news like much much better, much faster, preemptively, do a lot of analysis. But there's still a lot of things that a human can do much better than um than a model. Uh, and and I don't think that's gonna go away that fast, right? For for one, is to really build kind of um conviction, right? Conviction on something, right? Um, for example, uh a good financial model need not only be like syntax syntactically correct, right? It's like that's a baseline, right? There shouldn't be like like big mistakes in the equations, but it should should also have a view, right, about your future, right? Your your thesis. Um, and that view needs to be expressed through the financial model. And so so for agents to come up with a strong enough view that is not um is a little bit contrarian, right? Um, but turn out to be more correct than the consensus, I think that's that's still gonna be pretty hard. All right.
00:55:30 · Robert Yang, Brett Caughran
And that's something that really good, I think good human investors uh they will do, and it's still an open question about how to do that in the machines. [00:55:41] S1: Yeah. You know, something I've been very passionate in asking Claude an investment question, you you get you know often a different answer, you know, six times, you know, yeah, six days, you get six different questions, and then if you push back on the answer, you get the yes, sorry, I was wrong. So it's sort of spineless by by nature, the the ability to sort of inspect the actual Excel artifact and sort of trace the assumptions that the agent is making in the Excel structure. To me, has been something that has been super super eye-opening.
00:56:16 · Robert Yang
[00:56:16] S0: Um, I think this is this is definitely like um I guess we talked a lot about like spineless, and I think that's that's a profound issue with um with today's language models, right? They're trained to be uh aligned, and but the specific ways that they're aligned is essentially to kind of just like more or less agree with you, right? Now, of course, if you throw them something that they know are not facts, right? If you tell them like, look, United States is actually full of like lizard, right? Something that's it's then they'd be they'd be like, no, no, no, that's wrong, right? But but for things that are require opinion, right, they don't take they don't take stance, right? And that's that's fundamentally for for the big labs, they have to do it, right? So like imagine like a language model actually taking a political stance, right? It'd be really bad. Like and it will piss off half of half of Americans if it takes any stance, right? Um so so you can't do that, but but of course, a great investor, they have some stance, right? They have some belief in the world, right? Um, and that's how you can hold on to like a good stock for a long time, right? Without like just like, oh, like it's up, it's up like 60% year on year. Let me just like sell it, right? No, no, no. If you believe that this can go like if you if you get NVIDIA right 10 years ago, right, and you're like, I believe in this, I believe in AI, right? You can hold on it forever, right? You can still hedge by like short other things, but um, but you're like, no, NVIDIA, I'm gonna hold on on to it. So that I think requires the agents to really have uh to be opinionated, right, in a way that is grounded in real facts. Um and it takes human influence into account, but fundamentally it's about like being grounded in facts, being grounded in the market, right? And the real like finance of a company, of the industry and what it believes the the future will be, right? Instead of being just like so easily moved by whatever the last prompt from a human they got, right? So getting to agents that can do that, I think is something that that as you know, I'm very excited. Um, and that that is a human quality that I don't think it's we're gonna get it, like at least not in production within the next 12 months.