Everything is gambling now

Welcome to the BirdCast, the flagship podcast of the difference between tool use and computer use. I'm your friend David Pierce, and I am almost done setting up my new studio. I mean, studio is strong. I'm at my desk. I have some lights. I put up all this cool, like, they're acoustic tiles, but they also just have nice texture and look sort of like I'm doing this on purpose. I have this awesome light from MoMA. I have my knockoff TikTok shop headphones. I have everything I need, except for a couple of things. I need to fix the sound. I'm gonna get another one of these shelves because I just don't have enough space to store all of the boxes for gadgets that I have, but we're getting there. I'm starting to feel slightly settled in this house. I got a space heater right there because it's like 40 degrees down here.

We're getting there. We're making progress. But today, we are not here to talk about what's going on in my home office, although I could do that, and I will at great length. Today, we're going to do two things. First, I'm going to talk to Joe Weisenthal from Bloomberg about Polymarket and Kalshi and this general rise in what's called prediction markets, how they got here, how they're so controversial and yet so popular, and where they go from here. Then, Hayden Field is going to come on and talk about model context protocol, which is a new and pretty important idea about how AI is going to work. And I think if we're going to get agents in a real way, the way that all of these companies are promising, MCP is a big part of how we get there. We're also going to do a hotline question about some AI stuff. We've got a lot to do.

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All right, we're back. So over the last few years, a lot of betting has become normalized on the internet. And you can go all the way back to the meme stocks that really started to take off during the pandemic and the way that people talk about crypto. But I've been really fascinated with this idea of prediction markets. These are apps and platforms like Polymarket and Kalshi. And what they do is they let you bet on...

essentially everything. I'm currently looking at this website and right now you can bet on things like, will we be rescheduled in 2025? What will Trump say during a bill signing on December 12th? Who will be the first to leave the Trump cabinet? You can bet on the Jake Paul, Anthony Joshua fight, which is a relatively normal thing that people bet on. That's a big fight coming to Netflix. You can bet on what SpaceX is going to IPO at on its first day. You can bet on sports. You can bet on elections. You can bet on all kinds of things. This is the idea of prediction markets. They're gambling, but they're not trying to be gambling. They're trying to be something different. And this is what I want to understand. How is this not just turning everything into gambling? And if it is that,

How do we regulate this? How do we talk about this? How do we integrate this into our society? These platforms are huge, and they become sort of central to the conversation as more and more important events happen. There were a lot of people talking about Polymarket after the election in 2024, saying that Polymarket was predicting it because there are a lot of people making real bets with their money, and that that is a meaningful way to understand what people think is going to happen. I just don't understand how any of this works and how it has become as big as it has. So I invited Joe Weisenthal, who's a reporter and a podcast host at Bloomberg. His podcast, Odd Lots, is terrific, by the way. Highly recommend listening to it if you're into any of this kind of stuff.

I invited him on the show to come and explain prediction markets to me. Why they exist, why they matter, where they came from, where they're going, and whether it is, in fact, just gambling. We had a great time. Here's the conversation. Joe Weisenthal, welcome to VergeCast. Thank you for having me. I'm thrilled to be here. I have been listening to your voice for a very long time. One thing I always enjoy is I have meetings with people sometimes. I just work in this space all the time. People are like, weird, I feel like I'm making a VergeCast. I feel like I'm now inside of OddLots, which is very exciting for me.

I love talking to other podcasters. We're inside of each other's podcast. It's so easy to talk to other podcasters. You know, we know how it works, et cetera. I know, your tech check didn't take 10 years like it often does. Yeah, totally. It's just a smooth sailing in many respects. Exactly. So I brought you here to talk about prediction markets, which I think, if I'm being completely honest, are the thing about sort of the tech adjacent culture that make the least sense to me of almost anything I can think of. And so I'm hoping you can explain it to me. But let me just start with sort of the...

building blockiest question here that I want you to make sense of for me, which is what is a prediction market and how is it any different in any meaningful way from a gambling platform? I understand what gambling is. Sure. Prediction markets are different and the same in ways that I want to try and parcel out here. Yeah. There's a lot here to this question. You know, I think, first of all, I would say the first difference is sort of just a sort of mechanical structural aspect of it. So prediction market builds off of the types of markets that have existed in legacy financial markets.

for literally ever since markets have existed, which is essentially some bet. So, you know, if you go back to that economics textbook where you learn about how like, you know, corn futures work, right? They always talk about the story of like, well, here's the farmer who needs to hedge against weather and bad prices. And so they lock in a price. And then here's the speculator that wants to make money and take the other side of the bet.

This is the sort of mechanically speaking, this is what it's built on. It's built on sort of these outcome based, specific outcome based bets. Will the price of corn be over X over a bushel or below it or whatever? But you can apply that to say basically anything. And so the most common example that people hear about in recent years is the presidential election. Right. And so or any other political election. Here is a contract. We're going to bet on whether Donald Trump wins the presidency or maybe 2028. We're going to bet on whether J.D. Vance wins the presidency. You think he's going to win. You make a bet.

If he wins, you get paid a dollar on the dollar. If he loses, you get zero. Right now, maybe the contract trades at 30 cents. So you put down 30 cents. If he wins, you get paid a dollar. If he loses, you get paid nothing. I don't think he's going to win in theory in this bet. I don't really have forecast. I put down 70 cents. And if he wins, I get a dollar. And if he loses, I lose my 70 cents. That is sort of the essence of it. And this idea that like outcome-based.

betting or hedging or trading does not have to just be confined to the realms of commodities or traditional financial assets is the idea behind prediction markets, basically. I do think it's interesting even just to hear you describe it, that all of that is very much like that is the language of commodities markets and stock markets. It seems like it's sort of careful to not use words like gambling and betting, that in fact, these are financial predictions, right? These are contracts. These are not bets. I think to start, we should be realistic about the fact that even within the realm of traditional finance,

What constitutes like sort of investing and speculation or gambling is like it's in the eye of the beholder, right? It's not like we have really good definition. And so here I'll say something very sympathetic to the prediction markets, which is it's very easy to say, this is just gambling. What are you talking about prediction markets? You've just reinvented gambling. And I think there's a lot of truth to that. On the other hand, it's not like when we look at traditional markets, we have some very clear definition or bright line that distinguishes investing.

from speculating. And people talk about this all the time in the stock market, or they particularly talk about it in the options market, because an options market is not really that different. You're going to buy a contract that pays off if the S&P 500 rises 10% over the next two months. Which is actually like one of the safest money things you can do in many ways. Yeah. I mean, look, buying contracts on outcomes of, you know, there's buying the S&P 500 and holding it for a long time. And everyone would agree, okay, you're like more investor. What if you buy the S&P 500 and you only are holding it for a month? I don't know. What if you're only going to hold it for a day? Well, that really starts to sound like gambling and speculating. What if you're going to buy a contract that...

pays off if the S&P 500 closes up over half a percent within the next day. Is that investing? That's like really, it does not sound like investing to me. That sounds like speculating. But it only drives on the point that the idea that we can draw some bright line between what is an investment, what is a legitimate hedge, and what is a pure punt, what is a pure gamble is very difficult. And so you look at the prediction markets, and especially the ones on sports. I think this is a really important thing that maybe we'll talk more about, which is that

And I get it, but the founders of the major prediction markets, oh, we could put a price on everything. We can hedge everything. You want to hedge the weather? Great. You want to hedge the outcome of the primary in New York City's 12th congressional district? Great. You could put a hedge on that, et cetera. Maybe it's useful to have prices on all these things. I don't know. We can get into that question. The fact of the matter is today, these markets, mostly when we're talking about this, we're talking about Kelsey and Polly market, they get attention for major elections, which they tend to get a lot of interest in, and they get attention for sports. And so all of these things want to make a market on whether the Minnesota Vikings are going to win.

That really looks like sports betting. The structure is a little different. You're not betting against the house. You're betting against other bettors. There are some other interesting aspects that you could get out of your position. You bet the Vikings when they were at 20%. Now they've run up a few touchdowns. Now it's at 80%. You're like, you know what? I don't need to grab that extra 20%. I'm going to sell out of my position before the end of the game. There are people who really like that, et cetera. So there are many aspects of this that are sort of different to how we think about...

the sports betting industry as it is at a casino or as a fan duel. So I would say economically, though, it's roughly the same thing because you're just making a bet on sports. But structurally, they would make the argument that a gambling entity is one in which the house sets the odds. And they would say in our system, the market sets the odds and you're trading against each other. But, you know, we are never going to resolve the difference between what is speculating, what is betting and what is hedging. It's sort of a human judgment question. It reminds me of the people who talk about, you know, the difference between going to a casino and playing poker versus going to a casino and playing slot machines. It is fundamentally...

Are those fundamentally different or in most important ways the same? I think is, like you said, very much in the eye of the beholder. Yes. Poker is, A, a game that you can improve your odds with skill. And B, it's a game where most of the money that's lost ends up going to other players. And so therefore you would make the argument, this is a fundamentally different type of product than a typical gambling product. And so one could argue that in prediction markets, most of the money that's lost is to other players. And if you're very savvy, if you're very knowledgeable, you understand politics maybe or other current events at a deeper level than others, then maybe you can improve your performance with skill. Okay.

If I buy that premise, and I think in many ways, actually, I do, right, that there is some eye of the boldness in here that there is something fundamentally different about the structure of this thing. Why have polymarketing calls she been so controversial politically and in a regular sense? Is it just because there's something completely new or is the argument about whether they're betting more messy than I may be thinking of? Sure. I think there's a few reasons they're controversial.

When it comes to traditional sports gambling, that's regulated on a state-by-state basis. So every state has different rules. Some states allow physical casinos. Some states, it's still illegal to use the popular gambling apps, et cetera. So states want to have the ability to control what types of gambling occurs within their borders. That's like the story of anything that ever happens on the internet, right? Somebody does it online and somebody goes, well, who is in charge of regulating this? And no one knows for a while and then eventually we figure it out. But because these companies have managed to sort of frame themselves differently, they are regulated on a national level. And so I would say it's...

This is not an ideal situation, which is, OK, one person has a gambling app and you're not allowed to use this if you're in the state. And so that is an app that is clearly what we all call sports betting. Now, here you have another thing that sports trading. And because it's used as the sort of the trading idiom, the trading metaphor, so to speak, it's regulated by the CFTC nationally. And therefore, they found themselves in this ability and they've won in court at times to preempt state laws.

I really think it's not a very good situation. For one thing, I think, you know, obviously under current law, states have the prerogative to regulate betting within their states. And now here are these entities that have come along and allow, basically offer people the economic equivalent of betting and the state can't do anything because it's like, no, this is a trading app. This is a futures trading app and it's regulated by the CFTC and your state law doesn't apply there. So that's one source of controversy. Then there's other sources of controversy, which is like, okay, well, like.

what is the societal function of having markets on everything? And they would say, well, look, it's good. We understand prices. On the other hand, this could create perverse things. So for example, There is a controversy recently about like who was going to be the most searched person of the year on Google. And there was a market for this. This is the type of thing nobody would have ever betted on before. Someone made a bunch of correct bets. Oh, is this a Google insider who knew in advance who Google is going to say were the most searched people of the year? Now this creates an issue where if you're a company and there are these betting markets on everything, suddenly you have to like really tighten up your circle of trust. It's like, wait, can I tell you this? How many people need to know this in advance? You think these were sort of low stakes questions before. And now suddenly you have to be like worried that like this random thing, it's like, oh, we're going to.

put out a press release naming the most searched person of 2025 could be the type of thing that an insider could use to profit, which is not great. And so in a way that that goes back to the regulatory thing, right? Where we have... Very clear laws that say if you do insider trading, you will go to jail. I'm assuming insider polymarketing is not a thing we have like fully properly. No, it's not. And this is also an important thing to think about the industry in the future. So let's go back to the example of markets on most searched person. Now, look, these markets are never going to be that big because they're not like there's not a lot of people who need to hedge their most searched person exposure. There's not a lot of natural participants might be fun to bet on. So this is really important for the players, too, which is like, let's say I want to bet on this market. I have a feeling this person is going to win. I am not going to participate.

in these markets if I think there are like these very well-informed sharks on the other side. I think I'm smart, so I sort of know something. I sort of triangulated and I figured it out. But I'm not going to like start betting if I have reason to think that other participants have true insider knowledge. In a weird way, that's the closest thing to playing the house that exists on these markets. Yeah.

The conclusion that sort of follows from this is for these markets to thrive, they might want some sort of insider trading regulation. So one argument that people make is, well, insider trading is good because you want to have people who are informed. That helps set the price, et cetera. These things become oracles of truth. We want to elicit people who are knowledgeable, and then you get a price that's better. But no one is going to provide liquidity for these markets. No one's going to gamble and speculate if you have good reason to think that the other person on the other side of the trade is not speculating because they just know the answer in advance. And so then you get liquidity totally drying up.

And then the market is totally useless and so forth. So there is this sort of tension that's going to emerge where the idea is you want the market to be an oracle of truth, to have an odds that reflects something about reality. But if people are too informed and there's no regulation and there's no laws against insider trading, there's no penalty for exploiting your insider information. The non-insiders are never going to participate in these markets and they're going to fizzle out before they even get off the ground. Okay. I really, I can't decide if it is very funny or deeply dystopian, but now I can't stop imagining like a bunch of Google VPs sitting in a meeting, getting this presentation about, you know, here's what we're going to show. Here's all the stuff that happened this year. And every one of them is just sort of quietly on their laptop. I know, but it is, but this is the thing, which is that if you had reason to think that this was happening, no, me and you would never enter into that market or make a bet.

knowing that some executive or PR person or something like Google saw that in advance and was able to bet on it. So, you know, people in all industries are like, oh, we like regulation. We want to be regulated. Regulate us. There's actually very good reason to think that for this industry to thrive and go forward, more regulation about things like insider trading might be helpful for establishing the legitimacy of the market. I think we would never have this sort of rich, liquid, deep capital markets we have in the United States today if there weren't legislation or rules about how you can exploit your insider knowledge.

Totally. So to what extent is there a crypto story in all of this? Because I think both the kind of arc of what you're talking about and some of this, you know, anonymity and the fact that it's hard to regulate and the fact that it's hard to trace, there's crypto adjacent stuff underneath a lot of this. Is there crypto really sort of tied up in where these things have come from and how they've grown? Yeah, I would absolutely. And I would say it's probably on two levels, which is I just think that like, you know what I wish sometimes? I wish that I had like a thousand friends who are really into the online poker boom in 2005 and that I could just track the stuff they're into. Because I really think like if you had this cohort and you just follow them over the next 20 years, you would have been like really early to Bitcoin. You would have been really early to, you know, daily fantasy sports. And, you know, they sort of understood that prediction markets are.

exciting and hot would be a big deal. It's the Tim Robinson. I got to figure out how to make money off of this meme. And it's basically like there's a handful of people who are, as the meme goes, it's like there's a million dollars trapped in your phone. And if you click the right sequence of buttons, you can save that. You can pull that million dollars out of your phone. Like there's people whose minds are always in this space. The crypto people were very into that. And so like a lot of them were like the early movers, the people who got excited about prediction markets. The other element, I think, which is really important is if you go back to 2020, as recently as 2024, the regulatory environment pre-Trump was not as favorable at all. Kelshi.

Barely had any markets. It barely had any volume. But Polymarket was already a thing because it was stable coins. And it was one of those things like, this is not open to anyone in the US. But it was like, wink, wink, anyone with a VPN could have obviously figured out how to get stable coins on there. But it is one of these things where like, I don't know if...

We could talk forever about the optimal way to regulate these things or what markets should be allowed and what shouldn't be allowed. But as long as smart contracts and stable coins exist, I think it's going to be very hard. It would be very hard to, you know, there's a certain kind of anarchy. They create this sandbox that exists outside of the American regulatory perimeter that anyone can really access specifically thanks to crypto and stable coins. And so then you get this situation where it's like, OK, here you have this thing that is not only not allowed in the United States, but it's booming everywhere and everyone can really access it. And so part of the reason, perhaps, that regulators have ultimately acquiesced, I mean, is this sort of reality.

And it was very, it was going to be very hard to stop thanks to crypto. And I'll just say one more thing, which is that, you know, people like to say, oh, crypto doesn't have any use cases. And we can dispute those and these conversations go around in circles. It does have a use case. It lets you circumvent the law. And being able to trade on a prediction market platform, use a stable coins that run on blockchains is a use of crypto. Yeah, fair enough. So I do want to go back to this idea about these prediction markets as sources of data and prediction. Because I don't know if you saw the 60 Minutes thing about this a couple of weeks ago that was like, Anderson Cooper like really loves prediction markets, it turns out. Thought that was really fascinating.

They spent a lot of time talking about, to some extent, this is a place where people spend and make money. But our sort of value to the world is that we are a reflection of the wisdom of the crowds. And actually, if you want to know how something is going to go, you're better off looking at prediction markets than anything else. Do you buy this theory? Is there something to these platforms' ability to actually accurately predict things?

You know, so I don't so I don't love the term prediction markets and I don't think the test should be in defense. And this is me making a defense of the prediction markets. I don't think the test should be. Are they accurate about predicting things? I think the test really should be. Does that price on a given?

contract accurately reflect conventional wisdom. Now, if you, in a sense, a prediction market is a replacement for your typical cable TV news pundit. And the pundit is talking about, you know, some issue and they're like, well, what do you think about the prospects that in the next 10 years, China launches a blockade of Taiwan or something like that? And then they'll say, well, we think there's a 60, we think there's a 40% chance that in the next 10 years, it's like, this is totally useless. Everyone always is making these 60, 40% chances. It informs us nothing. There's no track record. We have no way of going back, but it's, you know, you sound smart. I think there's a 60% chance.

I think the prediction market is like we can improve on that to some extent because we no longer have to rely necessarily on pundits to come up with that number. We can rely on the wisdom of crowds. I actually think there's something to that. And not only the wisdom of crowds, but the wisdom of crowds willing to put their money where their mouth is, which I do actually find to be very compelling. And I think there's a pretty legitimate reason to think.

Now we, oh, you know what? It's 75% chance now. The people with money on the line are very concerned about X or Y happening, whatever it is. And there's a meaningful difference between 55 and 75%. And when you see it moving, something is going on. I think, you know, it's very interesting from the media perspective. To some extent, I would say that I think of prediction markets as media companies. You can go to polymarket.com and you can see what's moving. And if something has moved significantly in the last day or whatever, that is a reason to think that some development has happened in the news. So I would say that is very useful. A couple other things I want to say too. You know, like.

A point that I've stressed for a long time when it comes to prediction markets is if you think about the U.S. government bond market in the United States or really anywhere, that is literally a prediction market. Let's say, what is a six month T-bill? A six month T-bill is what the market expects that the overnight interest rate by the Fed is going to be on average over the next six months. Who sets the overnight interest rate by the Fed? The 12 voting members of the FOMC. So this is one of the most liquid popular instruments of the world. And it is literally, not metaphorically, it is literally a bet.

on what 12 people are going to decide over their meetings over the next six months. It is not like a prediction market. It is a prediction market in the most classical sense. And so to some extent, prediction markets not only are vindicated and validated, they've been vindicated and validated for a decade because this is an instrument. People betting on what 12 people in a room are going to do is actually at the core of the financial system. Did you see this thing that happened recently where Spotify put out its year-end data and who was the most streamed artist? And there was this one person, I think it was on Polymarket, who was like, well, Taylor Swift has won the last two years.

Taylor Swift is obviously going to do it. The market is way underpriced. They spent, they put like, I think $15,000 on it. And they were like, this is the best bet ever. I'm going to win. I'm a genius. And then like 15 minutes later, they're like, oh, it's Bad Bunny, the number one artist of the year. And they're just following up a tweet. Like, well, nevermind. You know, there's some interesting, so let's go, even going back to the most searched person of the year. Incidentally, from what I understand, Google's most searched person of the year is not strictly speaking, the person whose name was searched. It's about trends. It's about trends. But this gets to something important, which is contract specification. And so what actually, you have to, like in many cases, there's a lot of disputes. And I think.

The companies probably have to mature on this and get better and be more clear about what we are actually betting on and so forth. And so there could be many of these situations where people think they're betting on one thing because it's like, who's the most searched person in the year is probably literally Donald Trump. And so it's based on some trends. But I think a lot of people get into these markets and don't read the exact contract specs and they get really frustrated because, oh, they didn't realize it. And so probably as these companies mature, they're going to have to get better about being more transparent so that people know what they're actually betting on.

Yeah. Agreed. So given all of that, you're a reporter, you're a markets guy. You tweet obsessively about jobs data every 15 minutes, which I used to think was like a bit. And now I think it's just actually central to your personality in a way. That's right. That's right. No bits here. No bits. How do you think about Polymarket and College? Do you look at them as useful sources of data in your work? Yeah. I regularly check the prices of things. I want to know, like, who is the favorite in some primary that's going to come? And so absolutely.

I, you know, we have here at Bloomberg, we have put the we have we have Polymarket and Cauchy data on the Bloomberg terminal, which I think is like a pretty, you know, we don't just put on data willy nilly. And so I think there's like people use this stuff. People find it to be helpful. You can do other things, too. You know, it's fun. Like occasionally you can find a chart.

of, you know, I'm going to track Donald Trump's odds of winning the 2024 election along with the S&P or along with the series of energy stocks within the S&P or various sectors that are perceived to perhaps do well under Trump. And you can see sometimes they move together. So there are a lot of reasons for even people who don't bet or who are just in sort of news media or want to be informed consumers of the news to check these markets from time to time. OK, that's interesting. All right. Two more things I want to talk to you about. Thing number one is if all of this seems to be.

growing at the pace that it is and seems to be sort of culturally hitting in these really interesting ways. If I'm FanDuel or DraftKings or Robinhood or Bank of America, like why wouldn't absolutely everyone anywhere who does anything with your money get into prediction markets? Like, is this just the future of finance? There's two things there. So one is it certainly feels that way. I mean, the bigger trend is not just prediction markets, but the complete obliteration of any lines between sort of legacy financial institution, speculative trading and, you know, gambling. So like one of the...

more surprising news developments. The Chicago Mercantile Exchange has a partnership, I believe, with FanDuel, where they like allow FanDuel users to make bets in small denominations on the price of gold and the price of oil and stuff like that. That was a very surprising news to me. So we really have just completely lost all definitional difference between all of this stuff. Kind of feels like it. And then, you know, the other thing is that the brokerages, so IBKR, Interactive Broker, is one of the, I would say it's the most popular.

brokerage for the sort of prosumer trading audience. So it's like someone who wants a little bit more than like a Schwab or Robinhood or something like that. They have, you could trade prediction markets right there. If you go to Robinhood, if you go to the app store right now and you download Robinhood, one of the main things that you'll see there is that you could trade football games through Robinhood. So I think it is absolutely the case that all of the lines between trading, speculating, gambling are just being, yeah, they're just being completely torn apart.

Where do we even go from here? If we're at this moment where like, you know, we go all the way back to the pandemic and it's like, this is when crypto went nuts and everybody started betting on everything. And then it's like, we're at the death of the American dream and the male loneliness epidemic. And it's like, you can kind of thread everything into, what if I could just bet on everything that happened in the world? And it feels like, for better or for worse, and I think in many ways, it feels scary. It feels tenuous. Whatever it's going to be, it feels tenuous. But it is hard for me to imagine that if that collapse you're describing continues, that we're not headed towards some just like insane rewiring of what it means to like be a person in the world.

I feel the same way. And I was like, oh, this is also crazy. Like we're at some sort of like turning point in the world. It's all going to like collapse or something. And then I'm like, no, you know what? I'm 45 years old. This is just like middle-aged man anxiety. Like every 45-year-old man through history has had the same fear. But then I like talk to everyone else and like, oh, shoot, it's not just me. Everyone sort of feels this way. I want people to say, what are you talking about? Like, you're just like, you're just a boomer at this point. No wonder you're like anxious and don't like all this change. But everyone I talk to more or less feels the same way. Unfortunately, I don't really like that. I want people to tell me I'm wrong, but it does. I don't know where this is all going. I don't know how we could possibly know. But this feeling that you have or this.

tuition i would say it's like shared by like by almost everyone i can think of yeah i did read a study yesterday that said that young people think sports betting is bad um and that made me happy yeah i mean maybe we can have some of this but like let's find a little bit of equilibrium here somewhere i think as a society we have lost the concept of the difference between um differences of degree and or that differences of degree can manifest as differences of kind i think we look at things very black and white these days so you say like i want to regulate Like the idea of just going back to, you know what? You can still bet on sports, but the only condition is you have to drive an hour to a casino and place the bet in person. Like that is strikes me as like a very healthy balance. I don't want to like ban sports betting such that the only people in the business are mafioso who will like break your leg if you don't pay back. I don't think it's great that like all of sports coverage seems to revolve around gambling or increasing or you can't watch sports without ads for gambling. The idea that like, you know what? Let's just like find a moderate position where we allow it. That just seems so antithetical to our contemporary values. People just can't accept middle grounds anymore. But.

It does seem like there is a bit of a backlash forming. I think a lot of people know people who are addicted to their phones, addicted to betting on sports. They've lost a lot of money betting on sports. The question is whether we as a society or really as a political system have the capacity to sort of do productive regulation anymore, draw lines. I don't know what the answer is to that. This is what I mean. I think you can tell the whole story of the world through prediction markets. And it just makes it so sort of head wrangling to me. It's crazy. You're a guy who knows things. Do you ever find yourself staring at Polymarket being like, should I bet on the jobs numbers? No, I think I will. I'll save my money for losing at poker.

Sounds good. All right, Joe, thank you for doing this. This is super fun. I appreciate it. Thanks for having me. It was a blast. All right. Thanks again to Joe for coming. Go listen to his podcast, Odd Lots. Subscribe to his newsletter if you're a Bloomberg subscriber. It's good stuff. We're going to take a break and then we're going to come back and we're going to talk AI protocols because that's what we do here. We'll be right back.

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All right, we're back. Hayden Field is here. Hi, Hayden. Hey, happy to be here. Hayden wearing like a big red, it's just, if you're listening to this, I just want you to imagine like devil wears Prada Hayden Field sitting in the studio right now. It's a testament to how cold this office is right now. So I am looking glam, but feeling extremely cold. I turned off the space heater in my basement before we started, and I'm going to freeze to death over the course of this segment. It's going to be great. You need the coat like this, clearly. So you're here because you just wrote a big piece about this thing called Model Context Protocol, which if anyone has ever listened to or watched the first cast, you know we love a protocol. And there's a real bet being made in the AI industry that...

This is not only just like a piece of the infrastructure of AI, but it's like crucial to how we get to the future everyone is predicting and kind of needs to make happen. The stakes for this seems super high to me. Is that fair to say before we get into it? Like this seems like a big thing that a lot of people need to go well. Definitely. Yeah, it's something that I've been hearing about increasingly over the past year, every month more and more. And then this is kind of the biggest milestone so far in its journey because donating it to a neutral body and having a neutral body to govern it actually is going to help it improve so much because all these companies are going to make tweaks to it, improve it, make it better at security, other stuff, because they aren't afraid that they're secretly going to be eventually contributing to their competitors' bottom line. So now that it's all out in the open, no one can own it. It's going to help a lot with it getting better and therefore AI agents getting better, which is something we really need. Right, yeah. It's like if agents are going to happen.

MCP kind of has to work. But let's just start at the very beginning here. If you are just a regular person in the world, you should not know anything about MCP. You just shouldn't. And you probably never should. But I think it is a thing that your life is about to intersect with. So let's just start from scratch here. What is the model context protocol and where did it come from?

Great question, because I was doing some of my own research on this when I was writing this piece. I'd heard about it. I knew what it was, but it was something that I would have had trouble explaining to someone else. So it's a good thing I wrote this. Essentially, the simplest way to think about it, and this is going to be oversimplified, but imagine you went to a resort and there were a bunch of activities you could do, and you were handed a brochure of all those activities and how to book them. So before you got that brochure, you wouldn't know what activities were there, and you also wouldn't know how to book them. So that's kind of the situation with MCP for AI systems. It's allowing a model to know what...

tools are available to it or what databases, what contexts, just other things that it can use to make a user's experience better and then how to use them. So it's not just how to use all this stuff, but also what's even available to begin with. So that's why it helps make AI agents so much better in theory, because instead of just browsing the web and trying to figure things out, you know, in terms of like a web made for humans to browse, it's able to talk to other systems on the back end and get answers like, you know, connecting to Slack, connecting to, I mean, honestly, every single thing that OpenAI announced in October with its ChatGPT apps was powered by MCP. Interesting. Yeah. I saw a diagram a few days ago that has stuck in my brain ever since. And it's basically like, if you think of the way that software has always worked, which is just through a series of what are known as APIs, you have, if I want to connect my thing to your thing, I connect my APIs to your APIs. And then we are connected. This is like standard software building stuff. This has existed for forever. But if I want to integrate my thing with a hundred or a thousand or 10,000 other things, I have to do each one of them individually. And it is like a gigantic pain in the ass. And for like the example I give to people all the time is like, if you've ever used.

an app that integrates with like Gmail, but not Outlook. It's because Gmail's API is really easy and Outlook's is really hard. And so it's like, it's just that simple, right? Like some things are easy to plug into, some things are not, but you had to do it one by one every time. MCP, the idea is sits in the middle and says, okay, all of the apps are going to provide a thing to me that says, here's how to talk to AI tools. And then the AI tools just go to MCP and say, what's available out there? And then like you said, the MCP server says, here are all the things that are available to you and all the stuff that you can do. And it just says rad. And you get it all at once instead of having to like build it every single time, every time you want to do anything.

Exactly. That's exactly how it works. And yeah, like we put it like, you know, AI agents need new kinds of APIs and MCP is the standard those APIs will take. Exactly. Yeah, I love that. So where did this come from? Who built this?

This guy named David Soria-Pera at Anthropic built it. And his co-creator was a former Anthropic employee named Justin Spar Summers. So they kind of built this as a pet project. They just felt like within Anthropic, people should be using Claude more for their work, like their everyday life. And they felt like people weren't. So they were like, let's make this actually more useful for the end user. And let's just figure this out on our own. So they both convinced their managers to let them spend like, you know, 80% of their time working on this project. And luckily the managers were like, yeah, go for it. You know, if it doesn't work out, we'll see. But, you know, try it out. Why not? That's just a funny way of like Anthropic slightly telling on itself, right? That they're like, wait a bunch of people.

people on our product team who are like, that's weird. We make an AI bot and no one wants to use it for work. Why is that? And I think they came to the correct conclusion, right? Which is like, well, because I can't. I have to do all of my work somewhere else. And so having it live inside of this chatbot is less useful to me than like what I actually need is a thing that can make Excel spreadsheets for me. That's a very different project to try and solve. And it seems like that is the thing they went out to try and do. It's like, how do we get the things that are happening in Claude into the software we actually use to do our jobs? Exactly. So they decided to work on this and they spent a couple months on it. I think they started in.

in August of 2024. And then by October, they kind of introduced it at this internal hackathon. And everyone that was participating in the hackathon, pretty much at Anthropic, built on top of MCP for it. So that was like the first time they were like, oh, wait, maybe we really have something here. And then from there, it just ballooned. They ended up releasing it like right before Thanksgiving because they said that they figured people would need a break from their families. And they were like, let's just, you know, do it now. And then people have time to work on it, to play around with it. And yeah, then by, you know, early the next year, Sam Altman and everyone were tweeting about it. So there you go. I mean, that timeline is crazy, right? That's so fast.

Totally. I couldn't believe it. And neither could they actually. They kept saying how surreal it felt and how, you know, it was something that, yeah, David Soriapera was like screenshotting tweets from tech CEOs, you know, and just like saving them because he couldn't believe something he created made it that far. I think it's because honestly, I think the success is partly because engineers made this for engineers. You know, it's like the people that were on the ground doing this stuff are the people who made it. And maybe that's why it worked. Interesting. Yeah, it's just wild to see how quickly it has gone from like a thing somebody built to a product that a company uses to.

like a broader standard. And I want to get to the news that we have this week, which I think is a telling sort of next piece of the story you alluded to a minute ago. But it's weird to me that all of a sudden Anthropic builds this thing that is working very well and makes a lot of sense. And rather than do what always happens in business, which is Google and OpenAI and a million other companies look at it and say, oh, cool, good idea. We should do that too. They all just pitched in behind.

How did that happen? That's such an unusual turn of events here that Sam Altman would be like, oh, good idea, Dario. We'll just throw in with you. I think it's because they knew that it was the best possible standard, the one that had the chance of going the furthest. And they still were a little bit cagey about it. I mean, they had a group of core maintainers at each company that would talk and meet in person and have a Discord chat and talk about ways to improve the protocol. But still, you wouldn't see Google...

going all in on fixing MCP's security potential problems right now. Because they didn't, you know, if Anthropic ever decided to, you know, to change its mind, right now it's open source. But if Anthropic ever said, oh, actually, no, we want to keep this for ourselves, none of these companies wanted to improve it too much because they would be helping Anthropic out in the end. So I think they would improve it and they, you know, talked about it and they thought it was the best possible standard for making all of their AI agents work better. So it was kind of like they were all getting something out of it.

That's why I think the news that is happening this week is so big, because now that it's going to be governed by a neutral body and overseen by the Linux Foundation, it's going to be a real standard that people can contribute to, tweak, make real improvements to without the fear of one company eventually benefiting by itself. Yeah, well, so then that brings me to the sort of flip side question, which is why would Anthropic release this to the world? You look at this like this is great. We've built a thing everybody suddenly wants to use. This is a way we can get MCP and Claude to be more powerful.

why would they give it to everybody? I know you talked to Mike Krieger at Anthropico, I think is probably the person who made this decision. Do you have any idea why he made that decision? Yeah, he said that he just felt like it was really important and it was the way to make this an industry standard, that it would not really happen without doing that. And, you know, it was always open source, but a couple months in when, you know, the two co-creators were seeing the pickup, they started thinking, oh, should we donate this? Should we, you know, give it to a foundation that has done stuff like this in the past so that it can actually like go the extra mile and become a standard? And Krieger was apparently super supportive of that and one of the most vocal.

you know, proponents of that. And the other reason is because Anthropic has shortcomings. You know, there are certain things that they're not going to have the resources or the knowledge to go full-fledged into when it comes to bettering MCP. So Krieger himself said authentication and security are two of those things. Like, you know, they don't hit those problems first, and they don't have as much knowledge as, say, like, you know, Google or another tech giant in fixing those things and those potential security concerns. So that's why, I mean, you know, it's kind of benefiting everyone if you just donate it.

I mean, it's funny, my immediate instinct is to be like, well, there has to be something more cynical to it than that. But then I was like, well, they did just open source the thing and give it to the Linux Foundation. So I suppose it can't, there can't be but so much cynicism, they did then go and, you know, do the thing. And the fact that I mean, it's like, it's kind of like a rising tide lifts all boats in this one situation. Because, you know, I mean, for Anthropic, if they ever do need it to be way better at security and authentication, it will be. And that, of course, it'll help their competitors, but it'll also help them. So I think, you know, basically, it's like this would have been stymied if they kept it, you know, never would have advanced quite as far as it could. So now that...

I think they just knew that this was the only next step that they wanted to ever get significantly better and actually become an industry standard for real. Interesting. And I would assume that this change, giving it to the Linux Foundation, bringing these other companies in, it is now... officially or unofficially, it is an industry standard, right? Like this is, have you talked to anyone who is like, well, we're still waiting to see on MCP. Like this thing seems to have essentially unanimous momentum at this point. Yeah, definitely unanimous momentum. I mean, I've talked to some people that are like, you know, we'll wait and see because, you know, the real market industry standard is just when everyone adopts it, which has already kind of happened in a lot of ways. So, I mean, some people are like, it basically is. Some people are being a little cagey about it just to see where it improves in certain areas, but it's certainly on its way. And I would say it already is. The other thing about it is, and I think this goes back to your point of, you know, what do the other companies get out of it?

Anthropic wasn't the only company to donate something to the Linux Foundation. So, you know, OpenAI donated agents.md, Block donated Goose, its open source AI agent. So, you know, I mean, they're all going to put this like... Block donated Goose is just a... I just, I can't, I can't just let that happen. I just had to look up what it was called again because it constantly goes out of my brain because it's so strange. But yeah, the Agentic AI Foundation is what all these companies established. It was like Cloudflare, Bloomberg, Block, AWS, Microsoft, Google, and OpenAI and Anthropic. So all of them came together to create this neutral body that's under the Linux Foundation. So technically they all can have a hand in everything, but none of them own it.

I think that consortium helped with all of them feeling comfortable enough to donate also. That's fair. So what happens when something gets given to the Linux Foundation? What is actually going on here? What is now under the control of this group?

So now all of these tools and this protocol are under their control and, you know, it's just open for people to make it better. So, you know, Google could, for example, put like 10 or 20 engineers on this just to improve its security. You know, another company could be like, we got to fix authentication potential issues here. Let's put a ton of engineers on this and everyone's going to benefit from it. The other interesting thing to me was that I talked to the CEO of the Linux Foundation and he's been in the field for over 20 years. Like he oversaw, you know, the expansion of like Kubernetes and containers. Like he was the person that kind of like shepherded that.

For him to say that he'd never seen anything like this in terms of interest in MCP was crazy to me. And that's what he said. He said he could barely keep up with the number of inbound calls from organizations that wanted to be a part of this. And he said that oftentimes when a new protocol or, you know, a new thing that he's trying to push gets introduced, he has to scratch and claw his way and try to convince people to, you know, make it a standard. And in this case, he didn't have to convince anyone. It was just like already widely seen as being obviously the standard. And so I think that's part of why this is such a big deal, too. That is really interesting. And it seems to me that that, again, it's just like momentum begets momentum, right?

even, God, like nine months ago, it was like, okay, MCP is the thing, right? Somebody might try to build a competitor and we might end up with two weird standards. And it's like, it just reminds me of all this sort of Fediverse stuff where it's like, okay, well, somebody built ActivityPub and everybody got really excited about ActivityPub. And then Jack Dorsey was like, I don't like it, I'm gonna build Noster. And then they did AT protocol for Blue Sky. And I actually think that has been like hugely detrimental to all of those services. And it would have been better for everybody if they had just picked one. And I think the AI industry seems to have correctly understood that picking one...

is very important. And that what we need is for all of this to work. Like, I cannot emphasize the extent to which none of this works. And MCP is a way to get it there. And it feels like they made this call correctly in that sense. I think they all have taken kind of an honest look on the fact that their agents are not doing what they want to do. And this is a way to hopefully bridge that gap. And they're like, at this point, you know what, let's just all help each other instead of because there's no other way. I mean.

They need this stuff to work and they need to drive a profit, as we've seen from OpenAI's $1.4 trillion situation. I mean, they all need to make money and they need to do it quickly. So this is kind of their best bet. The next piece of the explainer I want to talk about here, and I want you to just sort of cast out a little bit. Let's assume this works. What happens next? Everybody is like, all right, sick. MCP is the thing. Agents don't just magically get better, right? What happens now that this is a thing everybody is sort of, in theory, willing to bet on and believe in? What are people going to go spend the next 12 months doing?

I think that this basically gradually is going to make agents better in a lot of ways, just because now that everyone can take a deep breath and say, OK, I'm not going to be contributing to Anthropics IP secretly in the future. You know, I can just make it better and make this work. Everyone's going to spend the next 12 months, you know, working on MCP and integrating into stuff and hopefully making agents actually better. Like, here's an example. Agents traditionally have been pretty bad at buying you stuff or like if you're like, oh, you know, let me find a pair of, you know, white sneakers from this brand in my size for pickup.

in my city, as I think V wrote about recently, it has trouble doing that. And it has trouble finding that and putting it in your cart and all the things. It's gotten better, but it still struggles a lot. So I think in this way, that type of stuff, like actual consumer facing end user tasks are going to be more useful with agents. And we won't have to know anything about MCP or even know the name of it. Hopefully this stuff just gets easier and better and more successful over the next 12 months. And we don't even need to hear anything about the back end of it. It just happens. So for example, like, you know, let's say you ask Chachi Petito.

do what I just said for you. Find those shoes. You know, maybe with a Macy's integration or whatever, I can talk on the back end to Macy's instead of just like browsing the internet like a human would, which is not that efficient for an AI agent. So yeah, that stuff I think is just going to gradually get better. But then again, you know, agents have always moved slower than companies said they will. So we'll see what the actual timeline ends up like. Well, to your point about the Macy's thing, it's not lost on me that not that long ago, all of these companies launched features that would just go use the computer for you, right? Like this was computer use was the thing that actually.

ChatGPT would open a Chrome window inside of ChatGPT and click around the web browser to do stuff on your behalf. And then it would, you know, dump stuff into your cart. And again, this didn't work, but it was kind of the idea there for a minute that like, okay, what we can do is solve this problem in literally like a brute force way. This is just the end of that, right? This feels like everybody's, I think, must have correctly surmised that was never going to be possible and it was always going to be problematic. We need a better way.

So I floated that. And whenever I floated that to an expert I was talking to for this piece, they were like, no, it's not the end of it. I was like, well, what do you mean? I mean, clearly it is. But their caveat was that they still really need that for a bunch of areas of the internet that aren't going to have MCP. There's going to be some areas of the internet that humans, they're built for humans and they're going to stay built for humans. And that's just the way it is. And so that was an important milestone and it's going to keep needing to get better. But MCP is going to shortcut a bunch of the stuff that you would have had to use tools like computer use for and make it way faster and easier.

Like, you're right in that it's going to diminish a lot. Like, we don't need to use computer use for everything now or in the future. But it's apparently still going to stay around for a bunch of areas where, you know, it might just be a euphemism for saying we still need to do it in case companies don't want to give us access to their data. Yeah, I think that's true. Yeah. I mean, this is the thing we talk about all the time, right? Like, Nelai calls this the DoorDash problem. Like, if I'm a platform provider, why am I going to just happily offer AI models a perfectly mapped set of my data so that no one ever comes to my website again? You might not, right? Like, there are a lot of...

reasons it's useful and valuable to do so. Like flight tracking is one that I'm sure came up a bunch in your conversation. Because this is like the canonical one, right? You can go and you can try to scrape airlines' websites to get their flight info, but that is inefficient and bad and wrong. And also all of these companies have set up this like incredibly accessible database so that, you know, the kayaks and booking.coms of the world can access this stuff. And if they just point that at MCP, all of a sudden LLMs will actually be able to go in and get good data in order to buy you flights. Sure.

As far as that goes, sure. And I think the airlines may be more likely than most to just be happy selling you flights, even if you don't go to their website. But there are going to be a lot of them. that don't want you using LLMs to do their thing. And so maybe that's the computer use angle is like, yeah, it's going to still have to click around the DoorDash website because not everybody is going to want to let the LLMs access DoorDash. Totally. And I think about the flight thing a lot, especially because, you know, when the scandal broke that a lot of airlines were doing, you know, per person pricing or like pricing solo travelers higher than group travelers. You know, I mean, I'm sure that that's going to be a thing. They may want to just hold on to the power to do that stuff. And, you know, that's how it is. And, you know, I even saw a story the other day about like, you know, some grocery.

app testing algorithmic pricing. So, I mean, I even saw something about Instacart potentially, you know, introducing like AI pricing tools. So, yeah, I mean, a lot of companies want control over who's searching and when and what their history is like so that they can charge you different prices. So we'll see how that works out here. I hate that. So I would love for MCP to overhaul that and just like, you know, we all have equitable insights into what something costs. I know, right. On the one hand, MCP is sort of a great user experience in the sense that you can just...

sort of describe what you want to have done and it gets done. Like I was talking to Amir, the CEO of this app called Todoist the other day, and he is all in on AI and MCP. And the thing that he really likes about MCP is he's like, well, we get a lot of these people who have really specific feature requests for us. They're like, I have my to-do list, but I want all sorts of things to happen. Whenever I, if I complete a to-do list, I need it to also go to JIRA and market complete, or I need it to send an email to my boss saying that I've done this thing, whatever. Everybody has these sort of specific automated or semi-automated workflows that they want. And Todoist can't build them all. But the idea that through MCP, Todoist can just say,

Here are all of your tasks. Here is their state of completion and their due dates and their projects and their priorities. Have at it, right? And then Claude or ChatGPT or Jira or whoever can tap into that. And suddenly you can build these automations essentially just by asking for them. It's very, very cool. And there's just like little pieces of that that is like, if we can put that stuff in front of users and just say, I want to, whenever I book a flight to LA, I want it to also book me a hotel automatically. Like that's a thing you can do that MCP makes possible in a way that has not been possible before. It probably still won't work, so I don't recommend trying it. But it is like, theoretically, MCP is what helps us get there. Do you know what I mean? Exactly, yeah.

But there's just it really, really, really relies on everybody being on board. And there are still enough reasons to not be on board that I'm just skeptical. Right. I know. I totally agree. And that's why I think we'll have to see what happens over the next year with companies addressing some of their concerns in MCP, like authentication, security, stuff like that. There's a bunch of areas that I think.

could be improved and that'll get more companies on board. But we'll have to see how that actually shakes out. Plus, you know, I've been burned enough by AI agents not working that, you know, I'm too cynical. We'll have to see how it actually plays out. Like, you know, do some tests now, do some tests in a year, do some tests in six months. But yeah, it'll be interesting to see how much this actually overhauls the landscape for consumers. Because I mean, you know, enterprise users.

agents are working a little bit better because it's a predictable, controllable environment. But when it comes to like, you know, booking flights, booking travel, figuring out a restaurant that everyone can go to and putting on their calendar, stuff like that is still kind of a pipe dream in some ways because it just doesn't work well enough for everyday people to be using agents for this type of thing. What are the things about the protocol that the people you talk to are still working on or thinking about or paying attention to? I mean, this is 14-month-old software that we're just going to stick at the middle of the AI industry. Are people concerned about pieces of it? Pretty much just security is the main concern I've heard. You know, there are things that Anthropic just isn't equipped to, you know,

beef up on MCP. And so that's part of also why they're donating it. They're like, you know what, you guys go ham and just fix all this stuff they're concerned about. Great. So yeah, that's the main thing I've seen. Are we talking about security in the sort of normal AI agent kind of security where it's like, if I'm allowing an LLM to go talk to a bunch of tools and talk to a bunch of services and access a bunch of my data, there's just a lot of potential points for, like everybody talks about prompt injection and there's a lot of places where my data becomes available to a lot of different services. And there's just like, this whole system needs to be kind of hardened against releasing my data and my work in the wrong places. Is that the security stuff you're talking about?

Yeah, that's a big part of it. The other part is like authentication and just making sure someone is who they say they are. So that's another thing Anthropic wasn't really fully equipped to handle. So they're, you know, saying, OK, you guys do this. So, yeah, those are the things like when it comes to payments, stuff like that, sensitive data. So, yeah, I mean, we'll see how that stuff shakes out. I think there's going to be a lot of work done and certain companies are going to put teams on this and just say, hey, like you guys for the next couple months, just work on MCP and try to fix this aspect that we're a little concerned about. Do you think every like big and small company is going to spend the next year doing that, like pointing somebody at MCP and saying, OK, let's stand up a server and see what's possible here? Is this is this going to happen that fast?

I don't think it's going to be every company. I think it'll just be the main players that have a vested interest. I think, I mean, this is just kind of anecdotal, but I think smaller companies are just going to wait for the bigger companies to do it. You know, they don't need to put the resources on this. And they know that bigger companies have, you know, a lot of the same concerns they do. So they're like, yeah, just you guys work on the infrastructure part of it. We'll use it when it's ready. So, yeah, I mean, I could see all the companies that are involved in this AAIF foundation, you know, putting their teams on it. You know, AWS, Google, OpenAI, a lot of the same.

companies that have representatives involved in this kind of like Discord group chat and core maintainers group where they were already kind of talking about ways to improve it, but now they're going to actually make all those changes. Yeah, it does feel like we're six to 12 months away from all of those companies just making it like plug and play MCP tools where it's like AWS is just like click here and you have an MCP server. It's like, great. And that's when it'll start to really take off. And it's like, I don't even have to figure out how to do this relatively easy thing from scratch. It just comes free with whatever piece of software I'm using. And that's, if you want MCP to win, that's what it's going to have to look like.

But we'll see. 100%. We'll see. I really do hope. I both am very excited to talk about MCP, and I also hope this is the last time we ever talk about MCP. Do you know what I mean? Same. That's the correct answer. It's like, we don't talk about TCP IP on this show for a reason. It's just like, it works, it does the job, and I don't ever have to think about it ever again. It feels like that's what MCP needs to become. All right, Hayden, will you stick around for five more minutes? We have a hotline question. Oh, yeah, 100%. All right, we're going to take a break. We'll be right back.

Listen to Machine Gods from NPR on the NPR app or wherever you get your podcasts. Support for this show comes from Airbus. Every experiment we've ever done down here on Earth has involved gravity. So, when the International Space Station launched in 1998, it opened up new frontiers for research in human biology and medicine. An opportunity to see how DNA strands, stem cells, and more might grow and evolve without the weight of the world on them. Now, a game-changing new space station, Starlab, is launching double-study agriculture, medicine, robotics, and more. And Airbus, who lead the ongoing design and engineering of the station, have designed it to be the next evolution for early research and real commercial production.

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Support for this show comes from Airbus. Every experiment we've ever done down here on Earth has involved gravity. So when the International Space Station launched in 1998, it opened up new frontiers for research in human biology and medicine. An opportunity to see how DNA strands, stem cells, and more might grow and evolve without the weight of the world on them. Now, a game-changing new space station, Starlab, is launching double-study agriculture, medicine, robotics, and more. And Airbus, who lead the ongoing design and engineering of the station, have designed it to be the next evolution for early research and real commercial production.

On Starlab, it's possible to scale the amount of research and manufacturing. The research humans are doing up in space can help us down here on Earth. And experiments in microgravity might fundamentally change our understanding of biology and medicine. Learn more about Starlab and how Airbus is making it happen at fly.airbus.com slash theflightpath. Hey, how's it going? I'm Eric, one of the Vergecast producers. And before we move on with the rest of the show, I just wanted to mention that this week's hotline is presented by AWS, how leading businesses use AI for next-level innovation. Now back to David.

All right, we're back. Let's do a question from the VergeCast hotline. As always, you can call 866-VERGE-11. You can email vergecast.verge.com or you can do what we're about to do, which is you can just post at me on social. I will lose the post and I will continue to think about the question you asked me for so long that I bring it back up on the show. So to the person who sent this to me, please know that I'm very sorry that I cannot find this post to give you credit. I'll put it in the show notes if I can find it. But Hayden, the question was essentially, why is it that every AI company is trying to get me to shop?

that somehow everyone has simultaneously decided that the main thing you want to do with an LLM is buy something. I have a couple of theories on this, but I'm curious what springs to mind for you. That's a great question. I think partly it's a really good foil for like a complex multi-step task that involves common sense and logistics. So in a way, it's just like kind of a good tell for whether an AI agent is actually good-ish or not. You know, I mean, common sense of which things to highlight or put in your cart. You know, can it understand the instructions of what you were even looking for? So let's take the shoe example. Let's say you wanted like white Nikes size 8.5 for pickup in, you know, Manhattan.

And that's a lot of different steps. And AI agents are designed, they say, to do really complex multi-step tasks. And they need to be able to reason, OK, well, this shoe is white, but it's not Nike. So OK, I'm not going to put that in her cart. Things like that. It's just a kind of a good foil for what.

an AI agent can actually do. Plus, yeah, time. We've already learned that chatbots can't really tell time. So yeah, like, you know, is it available for pickup today, tomorrow? Manhattan, geographical, you know, limits there. So yeah, I think it's just kind of a good foil. The other part of it is, I'm sure, you know, all these companies want to make money. So why is TikTok shop a thing? Why are influencers, you know, peddling their special codes for you to buy something? It's because e-commerce is a great way to make money. I'm sure that if you buy something in ChatGPT or in Claude, eventually they will have a certain cut or a commission of that, you know? I mean, it's like easy money. Why not? And the other part of it is...

they'll learn more about you. Data is valuable and what you buy says a lot about you and is really lucrative to these companies. So yeah, I think those are the main reasons that come to mind for me. I haven't even thought about the data piece of it. It does seem to be true that 2026 is going to be the year of ads in AI tools. And A, one really great thing to advertise is products people can buy. And B, one really great way to get better data is to watch people go through shopping flows. That is where all of the money is in advertising. So if you want to do that, having one-click shopping stuff inside of your AI tool goes a really long way.

Um, I think the only thing I would add to that is that, uh, it is, it is like a sort of obvious and benevolent use case, if that makes sense. Like, I think I'm sure you hear this too, but I think I hear from AI companies all the time is they're not very good at explaining to people what you can do with their product. And this idea that they're just like fun to talk to and sort of act like your best friend gets you a long way, but ultimately the tool has to do something for you. And a thing that the internet until now, frankly, has not been very good at for all the reasons you just described is shopping. Shopping is a thing everybody does. It's like a universally appealing demo. Almost everybody likes shopping in some way, shape or form. And it's a non-scary and totally mainstream use case that you can just point people at and be like, yeah, we can find you better deals than you would otherwise. There was this Alexa announcement last week where you can have Rufus, Amazon's shopping AI, which again is like clearly named to not seem scary. I don't like when they do that. But anyway, it will actually monitor prices on an item for you and will buy it automatically when it hits that threshold.

This is like it doesn't need to be a generative AI use case, but it is also like a perfect and understandable use case for this kind of tool in a way that I think there are not a lot of those for AI. Yeah, especially because you're absolutely right. I mean, I think I can't think of anyone that wouldn't use that. You know what I mean? That is a thing that Amazon has to build on top of Amazon. Like what a funny way to admit that your pricing scheme is insane and doesn't make any sense to anyone. Again, algorithmic pricing. Yeah, truly insane. But yeah, I think.

It's funny because these things are built, I think, a lot of times. Honestly, a lot of AI tools in general are just built, I think, sometimes without an end use case in mind. They're just built to build them without really solving a problem or without thinking about what it's actually for. So this is a great example of something that, yeah, people would use and want to use. Booking travel, shopping, saving money. Do you remember when, like, Google Chrome had that extension, Honey, where it would, like, try automatically every coupon code when you were going through a cart? I mean, that's a great use of technology. So it's like, people want to save money. They want to, you know, be. And also, here's another example. Honestly, Instagram ads, a lot of people like them, right? They find them useful. They buy stuff from them. That's one of the only ad experiences that I've seen people actually enjoy. And so, I mean, yeah, I think that's what ChatGPT eventually is going to offer. When I was at DevDay.

For OpenAI in October, Sam Altman was talking about ads within ChatGPT, and he said specifically that he wanted them to operate kind of like Instagram ads in that, you know, he wanted to recommend products that people did want or would find interesting. So I think that's what we're going to see happen next year, honestly. They put it on pause for a little while during their Code Red, but I think next year they're allegedly going to release adult mode in the first quarter, and I think they're going to release ads soon after that. Yeah, it's really, it's going to be a banner year for it being a fun product for humans to use. No, I agree with all that. The only other thing I would add is just to put an even finer point on your this is how they make money piece of it.

This is how they make money, right? Like it is so easy to make money from shopping because this is like a huge industry that everybody understands. The commissions are well-established, the pipeline exists. And if you can be the one who's like, oh, now we're the place that people go to find products, you can just take part of that for yourself. Like I've been following Google Shopping for years because I think Google Shopping is fascinating. It's like, what if you had all of the data in the universe and could see the whole internet and still couldn't do better than Amazon?

fascinating but the the google shopping's whole thing has been okay people are searching anyway if we can just prevent you from going to their website and then clicking to buy something and we can just google pay you straight through that whole process a that's a pretty good user experience because you found the product you wanted faster you pay faster you get the thing faster but also google now owns and gets to extract value from more parts of that process so you can think even like if chat gpt gets access to my credit card number and can just be like oh i found the nike shoes you're talking about do you want me to just go ahead and buy them you can say yes a excellent user experience b ChatGPT gets to just run around a whole bunch of people who want to take commissions and just take it for themselves. 100%. And I can rate because one of my first jobs in New York was a personal assistant. And yeah, that's the type of thing that I would be doing for people. So there you go. I mean, it's useful. People want it. Were you a good personal assistant, would you say? I think I was pretty good. You know, I booked the travel. I kept the calendar. I did a myriad of random chores. You know, I think I was pretty good. I was way more organized about the person I was being an assistant for his life than my own. Because I think you can only manage one person's life at a time. I managed her life. Mine, I fought by the wayside a little bit until I was done being a personal assistant.

I also had a separate phone with a separate ringtone that I had to keep on at all hours. So there you go. This is why ChatGPT is going to totally collapse as it starts to take over more and more of our lives. ChatGPT is just going to get like weird and sad, but it's going to be very helpful for us. Exactly. All right. We got to get out of here. Hayden, thank you as always. Thanks so much.

All right, that's it for the show. Thank you to Hayden and Joe for being here. And thank you, as always, for watching and listening. If you have thoughts, questions, feedback, feelings about prediction markets, or guaranteed winners on Polymarketing Call Sheet, I can't do anything about it, but I want to hear about them anyway. Email vergecastatheverge.com or call the hotline 866-VERGE-11. We absolutely love hearing from you. It is the single best thing. I have a lot of inboxes in my life, and the only one I like is the Vergecast hotline and the Vergecast email. So keep all of your stuff coming. We love hearing from you.

This show is produced by Eric Gomez, Brandon Kiefer, and Travis Lurch. VergeCast is Verge Production and part of the Vox Media Podcast Network. We're going to be back on Friday, and then next Tuesday, those are our last two shows of the year, next Tuesday is the VergeCast Holiday Spectacular, which is one of my favorite episodes every year, and this one is extremely fun. So stay tuned, and then we are all going to just fade into the holidays, and I'm very much looking forward to it. We will see you next time. Rock and roll.

Running a business shouldn't feel like surviving a software group project. One app for accounting, another for inventory, another for sales, and somehow none of them talk to each other. That's where Odoo comes in. An all-in-one business management software that brings every part of your business together. From sales and accounting to inventory and marketing, all-in-one powerful platform. No messy integrations, no bouncing between tabs, and best of all, no spreadsheets. Stop managing software and start managing your business with one unified system. Try for free today at odoo.com slash vox. That's odoo.com slash vox.

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