Public Launches Prediction Markets, Meta's Muse Charm, & $2T of Debt

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0:54This episode is brought to you by VCX, the public ticker for private tech. My name is Austin Hankwitz. I'm joined by my co-host Robert Croak. And the three things sitting at the top of our rich habits radar this week include public.com announcing prediction markets on their platform, specifically the ability for their AI agents to use the information derived from these prediction markets to make informed decisions with your money. Yes, very interesting and more on that later. We'll also be talking about Meta's new Muse AI agent that has gone incredibly viral and the new little charm keychain that was just announced, as well as the$2 trillion ticking time bomb that is debt on U.S.

1:35apartments. Robert, let's dig into our first story. Definitely. I'm super excited about this because Public just announced AI agents for prediction markets, and it's really, really cool. So Public, the investing platform we've partnered with for years now, just announced something that's a genuine first for retail brokerage. AI agents that can trade prediction markets on your behalf and use those markets as a live signal to trigger trades anywhere in your portfolio. Public already calls itself the world's first agentic brokerage, and this launch is them leaning all the way into that narrative.

2:12Members now, as of today, have access to prediction markets across nine different categories on the platform. Cryptocurrency, commodities, climate, economics, corporate events, markets, indices, tech and science, and politics and elections. But the real story isn't that public added prediction markets because plenty of platforms have already done that. The real story about this is what they are doing with these AI agents on top of the prediction markets. Yeah, this is so cool because we've been talking about public for years. And today, as of today, members can trade these events directly the way you'd expect.

2:50But they can also hand the reins to an AI agent and say in plain English what they want to happen when the probability crosses a certain threshold. Lythe Abraham, Publix co-CEO and co-founder, put it this way. Quote, prediction markets give those agents a new input, real world events. So members can trade a position on the event directly or use the market's data as the signal that triggers a trade anywhere else in their portfolio. And the examples that Public put out in their press release, which we'll have linked in the show notes below, are worth sitting with for a second because they show exactly how far this can actually go.

3:27So here's three examples they gave out in the press release. The first example is, if the probability of FDA approval for a healthcare stock in my portfolio crosses 75%, automatically execute a$5 ,000 market buy for that ticker symbol. The second example they gave is, if the probability of at least three rate cuts this year rises by 10 percentage points in a single day, alert me and summarize my exposure to bank stocks. And the third example they gave was if the probability of a Q3 earnings miss rises above 60 % for any stock I own, buy in the money put options spending no more than$2 ,500 per position.

4:09And the cool thing is it's not a chatbot answering questions about the market. It's an autonomous agent sitting on top of a live prediction market feed, watching probabilities in real time and executing actual trades, dollar amounts and all the second a condition is met. No open app, no manually checking the odds, no logging in at 2 a.m. because you're worried about a Fed decision, all automated. And notice what public deliberately left out. They specifically built this around events that move markets, rate decisions, earnings, FDA approvals, elections, and explicitly excluded sports and entertainment betting.

4:47So this is not a gambling product wearing a fintech costume. It's positioned as a genuine portfolio risk tool dressed up as a prediction market. So, Austin, this is really, really cool stuff. I hope everyone is taking notes. Break this down for us. What does this mean for you and your money? Yeah, I think it's awesome. I mean, we all know public as this platform where you can have different asset classes. They've got equities, they've got crypto, they've got bonds, they've got treasuries, they've got, you know, option contracts, generated assets, AI agents, and now we've got prediction markets and AI agents can use the prediction markets like public.com is the best broker out there full stop.

5:30Now, what I think is interesting here is that prediction markets now stop being a side courtesy and start becoming the actual input on how your portfolio behaves automatically and continuously without you having to be the one watching the screen every single moment. For years, prediction markets have been around. We know Polymarket and Kalshi, and they've been treated as a novelty for political traders or people who want to bet on election outcomes. But public just repositioned the category entirely and sort of is reframing it now as market infrastructure, which means you have this live probability feed that can trigger real trades inside of a real brokerage account.

6:07So the winners here are less about the single tickers and more about the trend. The trend is that public is strengthening its position in the increasingly crowded agentic brokerage race. And if this resonates with its members, I would expect to see Robinhood, Charles Schwab, and several others begin to start sniffing around the prediction market integrations of their own within the next, I don't know, 3, 6, 9, 12 months. Kalshi and Polymarket, which are two of the largest prediction market operators, also benefit from a major brokerage effectively validating the category as a serious financial infrastructure rather than being this like, you know, gray area of y 'all make some bets on, you know, whatever the election outcome is going to be.

6:46So I think public is absolutely trailblazing what it means to have a holistic portfolio, not just in different asset classes, not just with prediction markets, which have been around for a while, but to be able to take the information, the probability insight of that event contract saying, wait a second, the Fed might raise interest rates. That now is a higher odd happening than it was last week. What does this actually mean for my portfolio? What does AI tell me this could mean? And what trade should I be thinking about if this type of outcome actually occurs without, and again, we've kind of been, we had an episode about this, Robert.

7:23We talked about how to use prediction markets in your own portfolio. We got some flack on it because y 'all thought we were talking about gambling. We're not. And public just validated our episode back from March, essentially, which was us saying, hey, prediction markets tell you what is the chance of something happening. And yeah, the chance of that thing could be a sports game or some sort of like bet on a TV show, but it could also mean an election outcome. It could also mean the Federal Reserve. It can mean, you know, Tesla deliveries. It can mean so many different things for you and your money.

7:52And that episode now just got super validated by public that said, yeah, those probabilities are important, let's now also put an AI agent on top of it to make sure that they've got their eyes. And it's really cool, Robert. I'm pumped. Yeah, we've talked about this for a few years now, that these prediction market data points are really, really important. But let's talk about the risks that go along with it, because automation can cut both ways. Let's say an agent executing a $5 ,000 buy, the instant a probability crosses 75 % is powerful when you're right about the setup, And it's just as fast at compounding a mistake if the market data driving that probability is thin, manipulated, or just wrong.

8:34So prediction markets, especially in a less liquid category, can move on small volume. Handing a trading agent explicit dollar amount authority based on that data is a new kind of risk most retailers have never had to think about before. We love the tools, but we also want to make sure you understand the risk. A hundred percent. And, you know, we've seen this trend, Robert, from a lot of finance companies. First, it was the robo-advisor automating your allocation to different index funds. And then it was the AI chat assistant answering your questions about, you know, how is my portfolio structured?

9:08What should I think about these investments? Now it's AI agents executing real trades off of real-time event probabilities. So whether or not you personally use this specific feature, it's a preview of where every major brokerage is headed, in my humble opinion. And it's worth understanding and doing some research on before it becomes the default, not just a cool thing that public.com does. Like, this is going to be the future. And you have to understand where all this is going or you're going to get left behind, which is why you listen to the Rich Habits Radar and what we have on these weekly episodes.

9:40So to break all of this down, we are joined by Leif Abraham, co-founder and co-CEO of Public. Leif, welcome back to the show. Hey guys, good to see you. Really glad you're here, man. Thanks so much for taking time today. Let's start with the prediction markets themselves. We've watched this category of prediction markets explode over the last couple of years, but Public is taking a pretty deliberate approach on the prediction markets themselves. You're not offering sports or entertainment. you're focusing specifically on events that could impact the financial markets. One, why did you decide to draw that line?

10:17And two, what role do you think prediction markets should play for investors? Yeah, the instrument of an event contract and like the use case of that, I would argue has been stretched over the last few years, right? And that's why you see it being used for sports and entertainment things and all these kinds of things because, you know, in theory, it's just an instrument and you can in theory use it for a lot of different things um now obviously we're like public is a platform where people put the life savings into they grow their wealth in it etc and even though there might be a category of like entertainment finance you know let's call it um we think that should be arm's length from your portfolio and your life savings you know but nevertheless there are to your point like there are some really good use cases for certain event contracts, aka prediction markets, that can actually help you kind of maneuver the markets a little bit, you know?

11:13And that's exactly what we're kind of focused on, right? So like the high-level principle for us is, you know, basically events that move the markets, so things that could have an impact on your portfolio. And then you can either just trade those, or you can also just use the data and like the, you know, kind of live event probabilities and those signals to, you know, do other things your portfolio that might not be related to actually trading those markets. It might be related to something completely different, you know, that you're doing in your portfolio. Yeah, like just taking the insights from the probabilities of an event contract resolving to a yes, right?

11:49Just taking that insight and saying, wait a second, that's interesting. How might this impact the rest of my portfolio if it actually did happen? Exactly. and like an example is we're we're we're also showing the events on stock pages now right and if there's one use case that we very much believe in it's this use case of dissecting a company and its performance and its kpis and you know a lot of companies are these like big behemoths now they have multiple businesses and so on you know um or also i'm sure most people who are sort of active in their portfolio had this moment happen once where you have a trade in mind on an earnings call or something.

12:31You had your thesis. You've done your research. You've done the work. You were right on what your thesis and your work was. And the stocks tanked anyway because of something weird the CEO said on the call or because the outlook was different than the analysts expected or whatever. and so now you know what collection markets can do is you can dissect company performance into specific KPIs and if you basically want to be like oh I have a very big understanding of you know the model Y delivery numbers because I am in the business I'm forecasting this myself whatever it might be you can place a trade just on that as well and those are the aspects that are quite interesting because then if you go to you know things like the Apple stock page you're gonna have to trade those those events contracts but you can at least even in the context of a stock for example, see, hey, what does the prediction market, what do the event contracts say around the probability of a European antitrust case to be won or lost, for example?

13:32And it might give you some understanding of why the stock is priced a certain way and things like that. Yeah, we've taken and talked about this for so long that we look at prediction markets because we're not gamblers and we look at this information as just another way to gain an edge on a thesis. And you guys have blown that out of the water by making it so specific to what moves the markets because we don't care about entertainment and gambling. And I think that's very, very important because there's been this debate over whether prediction markets are primarily another form of gambling or whether they're a legitimate source of this information we all want those edges from.

14:11And if a market says there's a 70 % probability of three Fed rate cuts this year, for example, that becomes a real-time signal of what tens of thousands of people collectively believe is going to happen. And so from your purview, how should investors interpret those probabilities and what makes prediction market data useful alongside more traditional things like analyst estimates, economic forecasts, or these market implied expectations? Break that down for our listeners. Yeah, I mean, the general theses behind the data that prediction markets generate is the sense of that the minute someone puts their real money, their own money behind it, we become more objective.

14:57Suddenly, your political opinion or whatever it might be does not matter because it only matters to you what do I believe is going to happen. And so I can put my own kind of opinion a little bit out of the window and it becomes much more, much more rational kind of, you know, activity than from those people who participate. And because of that rational, you know, kind of analysis that everyone applies because it's literally just about putting my own money to work and see if I win or lose, so to say, that that basically creates like a cleaner, you know, outcome than, for example, running a general poll, you know, where you just call a bunch of people and they will just express their opinion because they have nothing to, you know to to lose as a study on the other end right that is the like general uh theory there now i would always say caveat that doesn't mean that you know if you see a market with an 80 % probability that you know that will definitely turn out to be that way right like there's many examples of prediction markets completely flipping you know um um around at some point but it is again it is one data point that you can take into take into account and i think specifically you've you made the example of just like general public market analysts you know i would always argue that a lot of public market analysts are actually quite biased right like if you're the bank who is ipoing a certain company you know there's a reason that banker or like that that bank will likely be at you know called out first on the first six earnings calls at that company to be able to ask a question to set the tone and have a very nice global question be like oh congrats such a great quarter you know because there's other financial centers that the bank had and whatnot to like you know make sure that this is all fine and good and you're getting like a nice little you know kind of off landing into the public markets and things like that right so like there are biases in these things you know uh in the like old systems and um Even just by like having more of a wisdom of the crowd and blending it down versus a room of three analysts at Citibank or whatever it might be, you know, already also, I think, makes the data potentially a little bit more useful because it is this more crowd wisdom, you know, blended pool than just, you know, a few guys in a conference room somewhere.

17:11Well, definitely. And I think what this does is it levels the playing field for the retail investor, giving them more tools to work with. But it also, I'm going to trust data more if people are putting their money where their mouths are. And I think that's one of the key factors here is that people are actually betting on the data themselves. So that's why I think prediction market data is so important when you're making these decisions. So I really, really like that answer. Yeah, I completely agree. Right. Because I remember back, you know, we were having midterms are coming up now, but I remember the most recent presidential election.

17:44I feel like a lot of headlines were saying one thing, but then you log into some of these prediction markets and you see a completely different side of the story. And that side of the story is what actually came true. And so I agree with you, Life, that, you know, when people put their money where their mouth is, that to me is a real signal versus the noise of headlines and, you know, talking heads on the Internet. Now, speaking of some of the signal here, walk me through the actual mechanics because in your press release, you gave this example of like an FDA approval, right? If probability crosses 75 % of this FDA approval for this specific stock, auto execute a buy of$2 ,000,$5 ,000, whatever it might be.

18:21where is that probability data actually coming from how thick is the liquidity behind that probability and then even like what happens if maybe the market itself gets too thin or maybe manipulated right before triggers you know are created there with the trade like really walk walk our listeners through what's happening behind the scenes here yeah and it obviously very much depends contract by contract because think of the prediction markets as similar like i have a float on a stock where it's like the amount of people trading a certain amount of money the exact same thing happens with an event contract of course and so the more popular a contract the more people participate you know in theory the better and more you know substantial the data behind it should be right and if you have less people participate then the data becomes thin up and you know in theory i would argue you should likely trust it less you know or believe the data less and that is obviously very true to these markets as well right then hence also why the more they mature i think the better they will become you know because the more people have participate um the better the data actually should end up being um but hence also why you know often when you look at these charts on any kind of prediction markets um you always see that volume number in the lower left of like of the chart and i think that's actually quite important number because it gives you a little bit of like a specific you know value that you can kind of learn from a little bit of like okay you know at which volume numbers you know do i feel like i will you know i believe the data becomes like starts to become substantial and so on that's still subjective of course you know um but you but i think those those things can can help a lot uh in terms of like how you know serious you should take uh the like current kind of standing of that chart another example you gave that I want to talk about here too was around interest rates.

20:15And I want to make sure I understand this so I can properly, you know, educate everyone within the Rich Habits Network. And that is, I can tell an agent that if the probability of at least three rate cuts this year rises by 10 percentage points in one day, alert me and summarize my exposure to bank stocks. I love that example because the agent isn't necessarily trading the prediction market at all. It's using the information from the prediction market to help me manage the rest of my portfolio. So walk us through how far can you take this idea? And could we eventually have hundreds or thousands of these real-time signals being monitored across all of our portfolios using these tools?

20:58Yeah. And the answer is that can happen today. Wow. And the general thing is that think about it as you have, it is one more data source that you can plug into potentially making an order or any other action. It doesn't even mean you have to make a trade. You can use these data points and connect them to your agents, not even connect them and just like and have an agent kind of use them to add things to your watch list, to send you an alert. you know so it doesn't have to lead to a trade at all times right and so there's even just a sense of if you want to get a better feeling around a certain topic in the markets you can have agents kind of serve you alerts you know on these signals all the time just you develop a little bit of a better kind of understanding and feeling on these things you know and then you can layer it as you know narrowly and deeply as you want right so you could be that hey uh i want to at the dot plot but i also want to look at the probability of the events contract you know and you know if both of those together equal x you know only then i want to do this and that with my treasuries you know and so you can you can really nerd out about the stuff and and go really deep and build very complex things obviously the more complex you build something the less likely something will come out of it you know because you're kind of going very deep in your if this and that stack a little bit in your little equation there.

22:25But you can go as deep and wide as you can and you can set up as many as you like. Robert, before we ask life our next question, I need to talk about a tool that we started using to help run our business. And we love this tool. It's called Granola, like the snack bar. Yes, Granola. Granola is an AI-powered notepad that makes your meeting notes actually useful. It captures what happens in your meetings and turns it into clean, structured notes with decisions and action items pulled out and made easy to find. Let's get one thing straight. It transforms messy meeting calls into something you can actually reference weeks later, which has always been a problem.

23:08So your notes become searchable, organized, and the key term here is actionable. So, for example, Austin, Christian, and myself have a weekly call about the podcast, the network, our social media, everything. And we started using Granola for these calls a few weeks ago, and it has been a game changer for us. 100%. Robert, you know, because we find ourselves searching for specific action items, and then we connect Granola to Claude's MCP. And it takes those action items that we talk about during the weekly stand-up call we have here, and it actually does the action items for us. Our productivity as a small business here with the podcast has genuinely improved so much since we started using Granola.

23:51It's really hard to put into words just how capable this product is, especially for someone who isn't an AI power user, but instead an everyday W-2 employee trying to be a better note taker or an entrepreneur looking to be more efficient in their business. Once you try it on a first meeting, it's hard to go without. You can try it totally free. Go to granola.ai front slash habits and try it on your next call. Austin, let's get back to the episode. I'm curious from your perspective, Life, how do you think about like the guardrails here to make sure that investors understand the difference between using this like, you know, prediction market signal with the probabilities versus treating it as like a crystal ball?

24:36because I feel to your point earlier, you know, heading into 2026, you can go on any of the prediction market websites back in January and February. And the number one most popular outcome for interest rates in 2026 were three rate cuts. That is obviously not happening. So it's like depending on the time and the day and the quarter and the month, right? It's like just using about this stuff as a way of information and better, you know, I just want to get your perspective on like holistically thinking about a portfolio versus crystal ball, predict the markets, let me get fancy here and really start making some aggressive predictions.

25:13A hundred percent. And that's exactly what I mean when we started this conversation earlier of people should look at this as a data point, not the data point. And there's enough examples out there where market completely flips. And I think what you're bringing up with the interest rate cuts is a great example, right? Like that has changed. Maybe that's something that changed more gradually than just from one day to the next, but it has definitely changed, right? And so, you know, no one can predict the future as much as the word predict and prediction might be in this name of this, you know, of this instrument now, but no one can.

25:52And everyone's got to be cautious on, you know, not taking it as, you know, a truth-telling machine. You know, they should take it as a signal. And it's a signal, you know, which means you should likely have multiple signals that you're looking at before making your own decisions and stuff, as you always should in any other investment, in any other asset class as well. 100%, man. So zooming out, you guys, you know, we love working with public and you guys build incredible tools. And this feels like another bigger piece, a bigger idea that you've been building towards with public to become an agentic brokerage.

26:30And for everyone watching and listening, historically, a brokerage basically gives you the access to the markets and then waits for you to tell it what to do. But now we're talking about software that can monitor markets, understand your portfolio, watch outside signals and potentially take action for you. So where does this ultimately go? Let's think in the future a little bit here. What does a brokerage account look like in three to five years from now with these AI agents becoming as powerful as you expect? If you look at what it does right now, and then that will bring me to what it does in the future.

27:06Right now, what agents are fantastic at is taking a kernel of an idea or an idea and turning it into action. I would not say that it is fantastic yet at giving you ideas. And we're getting there, you know, but I would say right now, it's really good at you have a fairly specific understanding of what you want to do, or you're picking something from the marketplace, even if you have like an agent marketplace, right? And then you put that into action and it executes as like a deterministic workflow where you have a very clear understanding of what it does. You know exactly what it's going to do and that's it, right?

27:45So when, because when you say agents, people's minds goes to, oh, let me prompt it. Make me a lot of money. Don't make mistakes. And that's obviously not how it works. You know, it is much more about automating strategies, but also automated strategy. you've got to know what the strategy is in the first place. And currently we're still in the spot where it's really powerful if you know what the strategy is in the first place. And, you know, and so that's where it's really good. Now where it's obviously going to go is that it has all the context in your portfolio. You might not feed it the whole strategy, but you might feed it, you know, behavior.

28:19You might feed it interests, you know, around your portfolio, you know, themes that you're interested in, you know, industry that you're interested in, you know specific things you might understand well events that you care about earnings calls you know macro events etc and then it will take all that input and it will essentially serve you things you know it doesn't mean it will automatically trade for you all the time because then you're going into like full-on you know you have your you know ai advisor who like takes over your account i think it's going to take some time to really get there but in this in-between state between you having already your defined strategy and the AI just running with it.

29:00You have this in-between state of it understanding a bunch of different things about you and then serving you proactively things to consider in your portfolio, things to change in your portfolio, et cetera, right? One thing that is running right now that's quite popular, one thing that people use Agents Republic for right now is just tax-cost harvesting, which a little bit is like a not as intelligent version of what I'm just describing you know because to do tax loss harvesting you've got to know okay here's a position in my portfolio that I'm currently down on I want to harvest those losses and so I'm going to take that cash and put it into you know something similar that doesn't count as a as um as like a wash sale and um you know and then three months later I might revert that trade back you know and so on And that is always something that an agent is great at just automating.

29:55And so, you know, tax loss, like a portfolio-wide tax loss harvesting agent is something a lot of people are doing. And I would say there's a good example for like a kernel of how this is going to look like. I want to like linger on this a little bit longer because it's cool. I mean, not every day do we get the opportunity to kind of dig into the brains of people who are building a brokerage platform that's used by millions and millions and millions and millions of people, right? So, like, talk to us more from your perspective, too, about, like, the prediction markets. Five years, three years, two years from now, how big do you think prediction markets are going to become within the broader financial ecosystem?