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Chapter 1: What is the main topic discussed in this episode?
Welcome back to The Rundown for another weekend deep dive. Today, I'm talking with Life Abraham, the co-CEO and co-founder of Public.com, the company behind this very show. Outside of the show, Public also has an incredible investing platform, and they've been on a tear lately, launching new features on a weekly basis.
In fact, they recently became the first brokerage to bring AI agents directly to investor portfolios. So in today's conversation, we talked about the role that AI agents will play when it comes to investing, the best way for investors to use agents, and a big picture look at the impact that AI will have on investors. This was a great conversation. I think you guys will really enjoy it.
So let's get into it. Life Abraham, welcome to The Rundown. What's up, Zade? What's up? For anyone who doesn't know, Life is the co-founder and co-CEO of Public, who is the company behind this very show. So I'm happy we could finally get you on the pod.
We could finally use it for some self-promotion. Look at us.
Yeah, I know. It's about time. It's about time. So... Well, let's talk about some of the cool stuff that Public is doing. I mean, I feel like you guys are releasing new features on a weekly basis.
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Chapter 2: What are AI agents and how do they impact investing?
And the one that caught everyone's attention recently was the AI agents. You know, you guys became the first brokerage to release AI agents. Now, I'm not going to lie to you, Life. I feel like every app these days is trying to integrate AI into their product. So I'm kind of curious to hear from you. Why are AI agents going to be a game changer for investors?
Yeah, obviously as public, we are focused on people that are actually truly building their portfolio, not just like gambling in the markets and so on. You can do that if you like, but generally speaking, like we're, we're designing for the person that is like trying to compound their wealth over time.
And in that specifically, we believe AI has can play a massive role in really helping people manage their portfolios through the markets and therefore also just like level up their own sophistication, you know? And yeah, AI agents specifically, obviously, are a tool for automation in most cases, right? So agents in public essentially mean that you can automate any workflow in your portfolio.
That can be a trading strategy, that can be money movements, that can be alerts around certain events that might happen. And therefore, you can basically have a little bit more sophisticated touch on your portfolio than you might have had before.
I got access to the agents when you guys launched it, and I've been messing around with it. The hard part, though, is figuring out what it can do because you can go in so many different directions. I'm still trying to figure out the best use case for it. What I've used it to do is figure out buying opportunities if a certain stock drops under a certain RSI, things like that.
What do you expect will be the most popular use case for these agents?
Okay.
The most popular is what we're already seeing. It is really training strategies. I think everyone has these general ideas in their head and these like unstructured strategies, sometimes call it internally.
And, you know, many times it's just people lack the skills or like the last piece of, you know, like a financial knowledge, for lack of a better wording, to like really put these things into action.
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Chapter 3: Why are AI agents considered a game changer for retail investors?
And so it doesn't have own reasoning once it's created, essentially. And that kind of takes that risk out of it. The other thing we think is very important is like over communication. And so once a agent is set up, you see every action that it takes as well as every action it might skip.
So that's like, you know, let's say it's, you know, checked some trigger that you've set up and then decided to not do anything because it didn't, you know, actually hit the specific things that you, you know, that you were looking for. You will see all that in the agent's history.
And so this like over communication of knowing exactly every single little thing that it does or didn't do, we think is also very important to just build trust over time as well, that you really know and learn even as you use them, that it truly can't do something that you didn't tell it to do beforehand.
I'm glad you guys have thought about that because you know, when the whole open claw stuff was going viral, you know, back in January or whatever, you would see these tweets of people saying it just deleted all my photos or like it started replying to all these emails. And I'm like, that's kind of scary.
But the fact that you guys have kind of thought about it in the safeguards and stuff, I think is good. And I think over time as people build trust, you know, we, people trust their cars to like drive themselves. I think over time people are going to trust AIs and stuff to start, you know, executing trading strategy. So that's good.
But I, but I think there is a really this aspect of, um, that, um,
obviously trust is earned and not just given in that regard, but there is really, you know, because we've created it into this deterministic kind of, you know, workflow at the end that like the AI kind of creates, it creates also the sense where you can now actually use it for real things, like for real strategies with real money behind it.
And I think right now, a lot of the agent use cases you see out there are still very much in this, you know, kind of scientific side project world, you know, and it is exactly because of this open floor kind of, kind of like kind of concept because they have their own reasoning, even once out into the world.
And so this separation of reasoning and, and, and execution makes it possible for it to even use it in a brokerage account in the first place. And that is just like that, that design piece, you know, is, is, is really like, like the core infrastructural kind of, I'll call it like innovation, but like the core infrastructural kind of idea that we've created that. So like,
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Chapter 4: How can AI agents automate trading strategies?
Yeah. In a way, I would say yes, because I think we've transcended from this point where AI was just augmenting labor to AI becoming labor. And that can sound scary in one regard because you're suddenly thinking about, you know, basically people's jobs being replaced and so on. But even in this
Like, even if you look at what agents in public do now, we always have a lot of conversations internally of, you know, what is the value a financial advisor provides? And we're looking at that in these like three buckets, right? It's the grunt work of trade selling. I'm a trading strategy, textiles harvesting, you know, these things.
And it's like advice, which is essentially like, you know, opinions on the back of data and market movements and articles and, you know, things like that. And then the third is like emotional support. Like who do you call when everything is red and, you know, I freak out and my anxiety is at all time highs.
And if you now look at agents and what we've built within public and agents, it does one already. So one of three of these components of what a financial advisor does for you already now is being done by agents. And we think each of these pieces is going to be tackled by AI agents at some point as well.
And that is now something that I think is entirely possible and not just possible as like a future vision, but like possible, I would say within the next 18 months. Oh, wow. And... So I think that is where, at least in our space, I see that agents really have unlocked like a little bit like that next level of possibilities with AI for sure.
Do you, I'm kind of curious, like, how do you feel like the entire finance industry as a whole will change? Because, you know, we've had algorithmic trading for, you know, decades now. Do you feel like with AI agents, I guess I'll ask it this way. Do you feel like the gap between retail and institutional investors will close because of AI agents or maybe even widen?
Because I imagine these hedge funds and these trade shops have access to even more powerful agents and they can throw more compute at some of these problems.
Yeah, it's always like, we always get thrown this question of, of, you know, retail versus institutions. And I always bring it back to, I don't think there is a versus here. I don't think they're competing in some regard. And I think that narrative is not necessarily true. And I think a big part of it is that they're running on very different incentives, right?
Like some hedge fund essentially runs on annual returns. And if you're an actual manager somewhere, you will get your bonus payment in Q1 for the performance of last year, and you will make your decisions on the back of that. And that will drive your day-to-day decisions and how you view the markets and so on, in most cases, I'm generalizing here.
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