James van Geelen on His Viral AI Doom Scenario

about the start, consensual telephone call with Dr. Diwasang.

“China's Ministry of State Security is one of the most mysterious and powerful”

spy agencies in the world. But in 2017, the FBI got inside. "Wait? That's a Noshikina."

"Hey, Noshikina. I've never seen that much evidence in my entire career and I don't

think we'll ever see that much evidence again." I now have several terabytes of an MSS officer, no doubt, no question of his life. And that's the Unicorn. This is a story of the inner workings of the MSS, and how one man's ambition and mistakes open its vault of secrets.

Listen to the sixth bureau from Bloomberg Podcasts, starting on February 13th on the I-Hurt Radio app, Apple Podcasts, or wherever you get your podcasts. Bloomberg Audio Studios Posts Radio News. Hello and welcome to another episode of the OddLots podcast. I'm Tracy Alloway.

“Have you ever had an article, "Go Viral Unexpectedly" viral?”

Yeah, I'm trying to remember specifics, but yes, and it's one of those things, typically where you're really excited, there's getting a lot of traction, cool people are talking about this, and then it goes multiple orders of magnitude bigger, this is super weird. No context for what this is, and you want to hide in your home and close the laptop because then you make it all go away and stuff like that.

It's kind of like once you release it into the world, you don't actually have a lot of control over how people use it, and I think back to, I wrote a piece about some investors trying to revive claims on Chinese imperial bonds, like antique Chinese imperial debt from the early 1900s, and somehow this one absolutely viral in Hong Kong at the time of the pro-democracy protest.

So I would walk down the street, and I would see these homemade banners that people had

created saying that China owes the US like 20 billion in payments on all debt.

And it was just so real, absolutely surreal, and completely unexpected, because you wouldn't think that some intricate debt story was suddenly going to become a pro-democracy protest slogan, but the world works in mysterious ways, and speaking of the world working in mysterious ways, there is something that went viral this week. We are recording on February 27th, and if you haven't heard of this particular thing,

you have probably been living under the proverbial rock. Right, so past odd lots of guests, James Van Gielin, a co-author to piece on his sub-steck, it's a true new research, talk about a potential AI-doom scenario, which a lot of people talk about, and there's been a lot of talk about mass white color displacement, as a possible thing that could happen as AI gets adopted, et cetera.

But, you know, we know that the market's been very skittish about this specifically. We've been seeing the software stock sell off all year, which we've talked about plenty on the podcast, and some of the private insurers, and all of this, and something about this moment,

“and this particular piece, I think it came out on Sunday, last Sunday, landed with a sort of”

like unbelievable thought, and so it evidently started moving markets on Monday, and then throughout the week, and this is the part that really flabbergasted me, was you see like all these

banks and every economist, et cetera, like weighing in, and many of the very critical,

and like Citadel securities, which I didn't even know they like published stuff, because that's just a market maker, like they put out all this stuff, so I'll be responding to it, and trying to take it out. It was a, as a market story and a media story, a wild week. It has become the discourse due to your, there's actually a prediction market on it, which you're telling me about a few minutes ago, like this thing has just become much bigger than

the initial substrate, which to me again says much more about the nervousness of the market, and how little anyone actually knows about how AI is going to unfold at the moment that people are so keen to just like latch onto any scenario that comes out. I get these notes from like sell side or research shops, although like clients have been asking us about this a trainee scenario, and it's just like,

"I managed a portfolio of $100 billion, and I am concerned about a substrate." Okay. Well, we should talk to

- Please talk. - The author of the substrate, and as you said, we've had them on a number of times before, often talking about AI. It is, of course, James Van Gielin, the founder of Citrini research. So, James, thanks so much for coming back on the podcast. - Thanks for having me. - Why don't we start with what Citrini research actually is, and what it is that you actually do in some of your other

“enterprises, because I think this has become also a source of confusion or at least interest for”

people who are reading this. - Citrini research is a pure investment research firm. We focus primarily on thematic equity and macro research. The progression of it was, I started it as a newsletter, just speaking about stocks and bonds and whatever else, and as we had a kind of string of good calls, which you were kind enough to have us on with the GLP-1 early July 2023, I think was- - Yes, that was a great call. - Yeah, and the first piece we ever published was a piece that was very

bullish on the AI infrastructure complex. So, that's been an area that AI robotics has been a big area for us in terms of thematic equity. We've kind of covered this winding road of bottlenecks in terms of optics, memory, power, whatever else you can possibly pollute to. We've probably covered from a what stories are people telling about the movements that are going on in stocks. I remember the last time that I was on OddLots, it was about this massive stargate data center buildout,

and Joe was very surprised to see that Caterpillar was, and I think very happy that the old economy

“was getting a bit better. - It's an old economy standard. - And really that's what we've been”

doing for the past three years, I've built out the team, and this piece very much was just a response to what the market has done here today, which is Fons of Rally, so I'll for companies have gotten sold off, a lot of fintet companies have gotten sold off, private equity has sold off, and we're

always kind of looking for the cohesive narrative that can connect disparate market moves. And the

pieces co-author Olive posed to me a question, which was, we've been focused on the bullishness surrounding AI infrastructure for a while, and it's translated into this capability curve that is moving a lot faster than anyone could expect. If you imagine this exponential on a logarithmic chart, it's just a diagonal line. It goes up into the right. People have been trying to put sigmoids or kind of level that curve off for a long time, and it hasn't. So we basically drew that line out and

said, what could be the implications of this happening? It's a scenario, which we would describe maybe 10, 15 percent towards, and it comes from a place of everybody talks about equity markets being forward looking, but really a lot more of what you see is people justifying historical moves with new narratives that they come up with afterwards. Very little of it is driven by, let me think of potential future outcomes. As an investor, which was the audience that this was meant to go out to,

I feel a lot more comfortable when I can envision the bulkase, the bear case, the base case, and the most uncomfortable that you can be as investors, when you can't see the bear case at all. So every time that we get into a market that's similar to this, people start asking, what if this time is different? And I guess the thing that this piece did differently was it asked, what if this time is different, but not so much in a Escanics and Micron are going from price to

book to price earnings, but in a way where what if this time is different, where the period of transition has to respond to a very, very fast accelerating capability curve? And you start from a place where there's a strong kind of historical precedent for the past century or two centuries, every time you've had a technological revolution, it's been great, it's been awesome. And you see that when you go from 95% of the population working in agriculture to 5% of the population and you create all these

amazing jobs, but it happens over a period of 50 years. And now we have this capability curve where you

go from two minutes, agents are capable of two minutes of autonomy on intellectually complex tasks, and now depending on who you ask, it's 8 to 16 hours. And that's happened in two years. That is an exponential curve. What happens when we get to multi-day? You know, what happens when we get to multi-week? And really the core of this is if this capability curve continues being as fast and exponential as it is, what does the world look like? There are a lot of very good reasons why that

capability curve could level off, but that is the core of the argument. I do think that's just like a

“important sort of level set for people here, which is that the progress that we've seen since”

ChatGPT came out whenever that was late 2022, has exceeded all of the expectations of

bullish and the true believers. And they're various measures and stuff, but you know, you mentioned the length of time, you know, that it could replicate a human focused on stuff, like all the people like they made like these bets, right? And they're even prediction markets on their capabilities. And so, like, as you say, like, it seems very plausible that the gains will level out in some way, or that perhaps simple computer tasks don't actually replace a lot of white color work,

because there's more to white color work than what could be done on a computer, including personality, and all kinds of stuff. All of that seems very plausible, and I probably even buy some of that, but this point that you make, it's like, yeah, sure, but it is still a perfect very fast. And it's something where the overall trend of the cost of inference per cognitive task has gone down so significantly, maybe depending on the forecast 10 to 30 times over the past year. And a test that was

uneconomical in the first quarter, 26, might cross that threshold in the third quarter. And the other

interesting thing is this capability gap where AI is capable of a lot of things, and a lot of people don't know that it's capable of that, right? So is it about the capability improving or is it about people becoming more familiar with that? And as AI infrastructure, it's been a great trade,

“and it continues to stay tight. And I think the best rebuttal to this piece has been, well, I think”

Gavin Baker made this point, which is the world is short on Watson waivers. And that's true. Absolutely true. But technological revolutions are volatile, right? Improvements come from places that you don't really expect them to. And I think you can't fully underwrite the idea that there aren't algorithmic improvements or there aren't improvements to the computer infrastructure. So we should look at, okay, if this capability curve continues improving, what are the downstream impacts

there? And has the financial system ever been stressed as the force scenario like this, because even if it takes five years, even if it takes seven years, eventually we will get there. And that's not a bearish take. It's a very bullish take. I think that there will be great opportunities that arise because of AI. But that's not to say that there won't be a period of

“transition. And the faster that it comes, the more aggressive that transition is. And I think the”

point of the piece really was to get comfortable with what monitoring that looks like. And I'll just make the point that the piece also starts out with an SMP that goes to 8000, because AI infrastructure is a very bullish trade that makes up a lot of the index. And that's a very strong and very momentum having trade right now. And it ends with the reminder that it's still February 2026. But in the middle of it, it says, how do we kind of get comfortable with the non-immediacy of the replacement?

If a company decides whether they're doing it because AI's gotten better or because

the market likes it when they cut jobs, what is the first thing already?

Sure. So it was a block last night. And you can argue whether that's because of AI or whether that's because of the overhiring during COVID. But Caine said that by the end of the century, we'd

“have a 15 hour work week. And he was wrong. And there's a lot of, you have to kind of look at why”

he was wrong. There are a few explanations, David Grayberg says that we just kind of created all these both jobs. This is a title of the book. I'm not cursing. People have said worse on this podcast. The other explanation is that, you know, human wants and desires, you can't really model for. And we will create whatever we need to fill that. At the same time, that required mechanisms by which humans kind of are involved in the process of making those machines better. It's kind of

not necessarily in every scenario concurrent with the idea of a piece of software that has the ability for a recursive improvement. This isn't to say that tomorrow, every single company in large enterprise goes out and replaces have their workforce. But you do have to take a holistic

picture, which is everybody in inventor capital has been talking about who's going to be the first

one person unicorn because of a gender AI. I don't know if we're there yet. I haven't really kept on top of that, but that does seem like something plausible to me. And I think one of the better lines of the Citadel securities counter argument, yeah, was recursive capability doesn't imply recursive adoption. That's an extremely true. The S curve framework, though, is kind of describing the wrong variable. And it's a variable that's really important when you don't just

have incumbents adopting, but you have startups threatening. And that variable is not necessarily breadth of adoption. It's intensity of adoption and capability of adoption. So you might have a flattening out S curve. And the seats that you've already enabled with these AI tools are just constantly

of new technologies. And what I would ask is was there an S curve for the adoption of spell check?

Everybody already had a PC. Everybody already had word processing software. It was kind of added as a feature. There are a lot of people in the world today that have no clue how to use ChadGPT that are using AI every single day. It's probably what is going to recommend you this podcast. It's probably what is making these decisions of what items you see when you go on Amazon. So if these agentic capabilities are introduced as features to a technology that everyone has already

“adopted, you have to adjust your model for them.”

Keeping an eye on what's happening across Europe and around the world. We do it early so the news is fresh, not recycled and so you know what actually matters as the day gets going. From Brussels, I'm following the politics, policy and the people shaping the European union right now. And from London, I'm looking at what all that means for markets, money and the wider economy. We've got reporters across Europe and around the globe feeding in as stories break.

So whether it's geopolitics, energy, tackle markets, you're hearing it while it happens. It's smart, calm and to the point. And it fits into your morning. You can find new episodes of the Bloomberg Daybreak Europe podcast by 7am in Dublin or 8am in Brussels, Berlin and Paris. On Apple Spotify, YouTube or wherever you get your podcasts.

I have so many things to say about this, but first of all, there's something very

dystopian about living in a world where like the upside is well, we have a lot of bullshobbs and existence already. And so maybe some of those bullshobbs will continue to exist even with AI. But the other thing is like the self reinforcing nature of AI seems really important to me in the sense that as you point it out, James, like it's not necessarily that people have to go out and find these new capabilities themselves. It's that the technology itself that there may be already

using just a substitute search or something like that can do it on their behalf. And so you just get this feedback cycle where like one AI thing creates new AI things and it just builds and builds on itself. I really would be remiss if I didn't say this again, which is a lesson that I've learned over the past five days that you can put something in all caps, you can build it and people still not read it. But maybe this is different because I'm speaking, my base case is probably

a lot closer to a lot of the people rebutting this article than the article itself. The point of this really was to explore what the bear cases, if we continue to have a very bullish world in

“AI infrastructure. I think that any investor that reads it and thinks and disagrees with half of”

the things that we say, maybe agrees with half of it and forms some more nuanced understanding of what to watch out for. That's kind of our job. So this is important and people who haven't read the piece should know that like right up front, you do say this, you say this piece is not a forecast, this is a possible scenario and how it could go. And we're going to get into some of the details, but you know one counter argument to sort of the idea of macro economic doom or financial crisis

or whatever is okay, if you have AI and it's driving incredible productivity gains, it's very

disinflationary and so forth. If some people are becoming fabulously wealthy in part of this big redistribution that would happen, well then the government has a lot more fiscal capacity to stabilize this, right? Then the government could spend a lot of money rates have come down, they could counteract the disinflation, not totally unlike perhaps COVID would be like a great example. But it strikes me as like, well, if we're ever going to have a government that's thinking about these things

proactively, that strikes me as a good reason to write them out. And it's notable like many of the executives at the top AI labs, they talk about exactly this. In fact, it seems like they're pleading almost with the government to take this more seriously because if we're going to have this big disruption and redistribution, we're going to have to start thinking about what are the fiscal

“mechanisms to counter it out. 100% I think that it's something where it's perfectly fine and”

good to say that the government will be able to deal with it. But it's probably better to

you kind of have to have an idea of what to keep track of. And I can say that in the discourse that

I've seen, I don't think that there's a very strong kind of data collection on this specifically. One of the big rebuttals has been that software job postings have gone up 11% year over year. Those job postings include AI and machine learning engineers. So you're really seeing a composition shift where these new AI engineers are coming in and they're creating software that will improve itself. And when it comes to the government response, jolts doesn't really speak

about composition. In my opinion, there's not a great amount of data on white collar specifically. And yeah, it was almost worrying in itself to see this reaction where we write this article that's

“kind of saying what I think most people are thinking. We're putting trillions of dollars at the”

white collar productivity machine. And that might have some level of disruption. And I get it. The thing that I'm very thankful to a lot of the rebuttals for is that they've reminded people that it's 2020/6, which we tried to do three times in the piece. But apparently we're not successful. Thank you to everyone that made sure that this isn't like a spin-out, crazy, whatever. But the worrying side is, well, everyone seems very, very comfortable that this is all going to be okay.

And I think that that, reasonably, I'm also a student of financial history that reasonably comes from when you look back at the past and you say, well, we had this industrial revolution and it was amazing. And we've had the mechanization and it was amazing. And we've had the internet and

it was amazing. And it created all these jobs that we couldn't have possibly first seen beforehand.

And you're looking at that from 100 or more years in the future. We have the term Lottite because of the fact that the transition was so abrupt and market that people were moved to physical violence. We don't want that to happen. The transitions do occur. And the faster that this happens, if this were going to happen over the next 20 or 30 years, fine, what a, you know,

“that that's going to be great. Everything's going to be awesome. I think that the real time frame is”

closer to 5 to 15. And obviously this piece extrapolates where it's three years. We should be prepared for anything because the, the government isn't going to accurately forecast technological advancement, but they can accurately forecast what they should watch and what the best policy response would be.

Yeah, this is the thing that Lottites were like ultimately on the wrong side of history in terms of

thinking that resistance to new technology would actually matter, but that doesn't mean that there wasn't major resistance and disruption on the way. And then it wasn't absolutely awful. Yeah. No, exactly. Right from their perspective, from their lives. Exactly. You know, you mentioned software job openings still rising. And one of the reasons that's able to happen is because we still have a financial system that up until relatively recently has been very comfortable with extending

credit to software companies. And there's obviously a reflexivity between the financial system, the market and the real economy. And you dig into that in your piece as well. And this is the part of it that I actually found the most interesting where you describe how AI could actually and the disruptive effects of AI could actually end up becoming problematic, especially for private capital. And this again is something that is very much in the public slash market psyche this

week, because we've had a number of private credit blowups starting to become public. Talk a little bit more about how you see that kind of private credit AI disruption now insurance as well

“nexus unfolding. Just to reiterate. I don't see it on foot. But I think this wasn't like a”

single out of private credit. It was very much a response to the price action of the market. But it is something worth considering that it's a relatively new in the grand scheme of things. And there's a system that's built upon the assumption that things they relatively stable. And if things aren't relatively stable, then what could possibly happen? We're not really private credit analysts, right? We're a thematic equity and macro research. This was something

where we presented kind of if you were to have a wave of defaults in one of these disruptive industries, what would happen. And then the other thing is maybe the job losses are fine. And we go back to a economy like the 1950s where the participation rate is much lower but productivity is much higher. That's great too. In the transition, the people that are at the highest risk of being replaced by AI have like seven eighty five goes scores. And they're not classically

what gets modeled as a risk in terms of a default. So these are all things where it's not saying that this is going to happen. It's saying it has a private credit lending and you know to their credit, I will say Apollo much earlier to the software thing than even I was or the market was, right?

For the rest of it, you know, like has there been enough changes to the assumptions about the

“income and about, you know, does AR stay recurring? That's just something to consider, I think.”

What's your base case on private credit, then, is the sort of Jamie Diamond Cockroach scenario? So I think that private credit isn't banking, right? Like Ron the bank dynamic doesn't necessarily play out. They are in possession of permanent capital to a certain degree. And and that's through in a lot of areas, the acquisition of these life ensures. So I think you could definitely see the contagion being very minimized if there were to be, I don't think there have been

any like very high profile blowups yet. Everything's pretty much fine. As far now as I understand it,

the progression of it though, I don't think that you're at a very high risk. My base case

would be just like that. And the only kind of added risk is if you were to have some sort of change to how private credit is treated from a regulatory perspective on the balance sheet of these life ensures. So there's sort of two major components to the piece that you wrote. And one is obviously the macro scenario. And the way it's framed is like, okay, the year is 2028. Unemployment is above 10%. The stock market is fallen 40%. So there's the macro story. But then there's also this sort of

“secular micro story. And I think this is really interesting. And this is the part that I've been”

trying to work out and try to understand better. This idea that like, there are all these businesses that have essentially been built up around building a mot based on network effects. Payments, platforms and so forth and whatever. And so this idea that AI and agentic commerce will fundamentally change the way a lot of these businesses operate. And these modes will disappear. And talk to us about that because I have a harder time wrapping my head around what is it about AI per se that's like,

here you have these legacy networks, delivery drivers, payment companies with whatever they have out the desk and you swipe your car and stuff like that. What else I was called? Turtle. Point of sale. What? Point of sale. Missions. But talk to us about like, just from a pure tech standpoint, what is it about agentic AI that can sort of evaporate this mode? So I will say, if I had to go back in time and write the piece differently,

“okay. I would not have single that. I would have just kept it on a sector basis, right?”

And I think that if I knew that it was going to get 30 million views, I would not have mentioned

single stocks at all. So I won't do that here. But what I will say is, and this future could be wrong. But if you envision a future where I remember talking to you guys about this in 2024 when I was using it as a bullcase for Apple, which didn't come in. You know, Apple was kind of let the chips fall where they may and then we'll come in afterwards, which saved them a lot in the past 10 years. But the idea is you have this agentic assistant and it's in your phone and it knows everything about you.

And then you kind of extrapolate that to a lot of people spend a decent amount of time shopping. What they don't spend a lot of time doing is price matching. If you're going to buy a box of protein bars, you don't really check five different vendors because it's tedious. AI agents do not experience tedium, right? So the kind of way that there are a lot of layered intermediation and rent kind of extraction layer in the economy. And then there are a lot of places

where having a like an oligopoly, essentially, has allowed margins to really be artificially increased. So just to address, I don't think that code is the amount on a delivery network for like that's you have the drivers, you have the customers, I get that. What I could see happening is something that's already happening where these startups are enabled to create something that's similar and well, you don't have the network effect. Okay, but if you have an AI agent that has

the explicit instructions to go out and find the cheapest option, then it doesn't really care about using this thing that has the network effect. It cares about using the thing that's the cheapest. So if you have an order aggregator that's an agentic kind of aggregator on the driver side and the customer side, then the customer says the agent, hey, I want this burrito from Chipotle and then there's a bunch of different platforms that the listing is on because the restaurant has used one

of these agentic aggregators to go on every single one and put their thing. And the driver also has the one that will get them paid most. So the idea of taking half of the delivery fee as the company kind of goes away because your margin is my opportunity. And if someone that's five people that's kind

modes here, but that's just one example of how you might see a world in which agentic commerce

and it's very similar to like the paperclip problem. If you tell a machine that to do something, it's just trying to get you the best price and maybe that includes finding way around interchange. Just to push back on this, they're just a pressure. I mean like comparison shopping websites have existed for a long time. Almost it's the beginning of the internet, right? And you know, in theory you could Google, I don't know, it's just like Google shop had a thing for why I don't think

people ever that ever took off. But you know, it showed you like here's the price of a computer monitor on Amazon and Walmart.com and newwegg.com and a few of these sites that like don't exist anymore, et cetera. Like in theory, like isn't that describing the same thing that like from the customers perspective, it's like, okay, they're all the same. I'm going to click the cheaper. Totally. I get that and that's an entirely possible case. What I will say is there's a big

difference between actively going and taking the effort and taking the time to go to one of these comparison shopping sites to get the best price versus just telling your phone, get me a burrito, get me the best price, right? Those are, there are two kind of fundamentally different things. This will play out over the next five or 10 years and we'll see and I'll also, I'm sure that

“we're not going to just delete friction overnight, right? So that's why it was so shocking to see this”

kind of like immediate reaction. It's like, this stuff hasn't happened yet and we don't know exactly how it's going to happen. It's just the future scenario where things happen in a certain way. (music) If there was a big rent button that would just demolish the internet, I would smash that button with my forehead. From the BBC, this is the interface. The show that explores how tech is rewiring

your week and your world. This isn't about quarterly earnings or about tech reviews. It's about what technology is actually doing to your work, your politics, your everyday life, and all the bizarre ways people are using the internet. Listen on BBC.com or wherever you get your podcasts.

Can you talk to us for a second just where you see AI valuations at the moment? Because I think

this is also part of the reason that people are very nervous at the moment, which is like, okay, on the one hand, we think AI is going to eat the world. But on the other hand, it's not entirely clear that a lot of AI is going to make money in doing so. And if you look at some of the big hyperscalers at the moment, they're still losing money on certain power users. So how do we think

“that AI is actually going to make money as it sort of eats the world? I think that that's the”

other thing that's important here is these companies need to go out and search for ROI. And there are a lot of threats. You just saw themthropic respond to the Chinese distillation of models. And if you go and you use mini-max, it's relatively comparable, but it's also 90% cheaper. So this is like a, there is a race happening right now. And the economics are, they span the gamut, right? Good and bad on both sides. The thing that drives this kind of capability improvement

is you do need customers to pay for these things that you have spent so much money on. And that means making it capable in a way that's useful to your customers or integrating it in a way that's useful to your customers. So I personally think that that will happen how quickly it happens is anybody's gas. But I think valuations right now reflect of this expectation that we are going to

“continue adding compute capacity to be able to handle this. And I think that if you spend eight hours”

just thinking about it, you can see a lot of places where AI is pretty valuable. But a lot of those places are places where you might otherwise pay a human right now. So yeah, it's just that you just have to balance it. And there's a lot of ways that it can go well. And then there's a couple of ways

that it doesn't. Let's talk about enterprise software for a second because okay, the public facing

these modes, these network effects, et cetera, maybe AI agents allow us to get the best price wherever. It's a different economics if we're saying the enterprise, we know about the enterprise, the SaaS sell-off, et cetera. What is this scenario? How would you articulate the fear in the market right now that all of these incumbent software companies could theoretically get ripped out because something something AI will make it so that customers don't need them. So you can separate software,

you have kind of like this long tail of SaaS that includes these, you know, workflow automation tools.

at least the systems of record have like a short squeeze in the sense that right now they kind of just have upside in that they are they're most situated to be able to improve their margins because of AI. Right, because coding is a cost for them, right? It's like they can theoretically maintain these things much cheaper than they are. Yeah. A hundred percent. And what we said in the piece, which will be interesting to see in real life and I don't necessarily, it's a good point

that enterprises don't really react as quickly as this. So the timeline is probably aggressive,

but the way that these kind of contracts are negotiated last year when you had the first half,

the kind of budget resetting, DCIOs and procurement teams, they agentic AI was still kind of a buzzword, right? It wasn't until the end of November that it became insane. You know, I saw you have vibe quoted a couple things yourself. So there was a cool comment next week. Nice. There was a

“great kind of jump in capability. What is it by the way? Are you can you to speak about it?”

No, he can't. It requires some finesse, I think. Well, this is the thing, like I used to blame Joe for the SaaS sell off, right? Because he was the one vibe coding and publicizing vibe coding. But now we can all blame. Yeah, you're welcome. But the strategy that's been adopted by open AI is very similar to Pound here where they say we have these forward deployed engineers and we're just going to install them at your place. And so maybe, you know, I don't necessarily think the enterprises

are going to jump to vibe code their own system record. But what I do think is that when you have these sales teams that call up their customers and say, hey, remember last year we said this was what inflation was and then we had a couple percent on top of that so you're getting a 5% price increase. All good? Okay. You're not going anywhere because you know how many were else to go? Done. Now the person on the other side of the phone can say, you know, open AI called me the other day.

Even if they're bluffing, right? So you do see like some potential downside to pricing power. And that's in the places where it's very unlikely that these vibe coded alternatives actually pose a threat. And then you see it's been interesting how anthropics handle it where they've recognized this capability gap where they say, oh, the people don't really understand what these tools can do. So they started releasing like sweets of AI tools. I don't know if

“you saw the wealth management one, right? It's they released the wealth management one, I think a”

couple days ago. It's like you could have done this yourself with these systems. This is a really good point. And I hadn't really thought of it in that terms. Because these things that like

Claude announced or anthropic releases something, they're not that incredible in some sense.

But they're essentially just very simple reminders. You hadn't thought to use this for modeling various retirement scenarios. Actually it's very simple. You could do that. You hadn't thought to use this. So because they're simple, they're like marked on files. They're not like particularly exotic pieces of software. But they are reminders that this thing you didn't think of, yeah, just do it. It's like a thing that you can use to hammer your supplier over that with, right?

Yeah, I don't know exactly what the timeline that that happens on. But there are going to be adjustments to pricing power because of it. And yeah, it seems that this is kind of the reason why in the beginning, I thought that framing the piece this way was valuable to our client base and reader base was because as an investor, you don't really care if you're presented with 10 scenarios and nine of them are wrong if one of them makes you money. Right? So I have to see new that some

people who would already bought the dip in software would disagree with the software part. But maybe they would agree with the, you know, with the disintermediation part. But then it kind of escaped containment and in retrospect, if I was going to write a piece for broad distribution, it would probably be pretty optimistic because I'm a pretty optimistic guy in like, uh, so yeah, that's been an interesting experience. What was the most surprising thing from this week for you?

Well, I had someone that that really strongly disagreed with me and then when I asked why send me a quad read out. The, the Kelshi is cool that you, there's a, you can use this as a hedge for like, yeah, there's no instrument, which let's see, Kelshi, I'm going to look it up, Kelshi, Katrina scenario. Like, if you start typing in Kelshi and then start, or it's see it, auto fills the Katrina scenario. Will this, I love that, will this Katrina scenario happen,

said 11.6%. Is that basically the right that you would get if you put it in the money market?

It's probably, so I, this is just, I read the specifications of this contract. The fine print model summary. So if at least three of colon unemployment rate exceeds 10% for the BLS,

“S&P 500 declines more than 30% from a closing level of issuance. That's what we're trying to”

analogy. Zilla homindex declines more than 10% than any of New York City L.A. San Francisco, Chicago, Houston, Phoenix, labor share of GDI, falls below 50% and CPU falls below 0% if any of those three

just a financial crash. Right. It's like, it's not really tied to AI. It's cool. Do you like that?

There's like, this is now going to be known as the Katrina scenario forever. Like, when, like, when we get the next crisis, whatever, it was like, this is like an omen. I feel like, uh, anybody consider, like, I feel like you could make a lot more money on TLT calls. If it's really things good hit, but, um, there's $125,000 been traded in this market. Oh, so it's still pretty money. Deep liquidity. You can't, right. You can't probably hedge, you can't hedge your whole life

for, you know, your whole business. But, you know, if I was going to pick a thing, I'd be known for probably would have been not this, but, you know, you don't get back. So, I still stand by what we've

“written and I think that it's, uh, as a scenario useful to consider. All right, James, thank you for coming”

on during a very busy and I'm sure it's a real week for you. Thank you for having me.

All right, Joe, I, I'm very glad we got James on to discuss that because obviously this is the talking point of the week, at least. It is just fascinating from a media perspective of how you can have these viral pieces that kind of get out into the world and develop a life of their own. But, obviously, the major point of interest in all of this is these are the things that the market seems to be actively considering at the moment, right. Paul Krugman wrote a good piece. He

disagreed with a lot of it, but he pointed out, you know, when the radio broadcast of World of the Worlds happened and a bunch of people panicked because they thought there was some big invasion. It occurred in the environment of a very, it was like, you know, during the depression. Yeah,

I've, like, existential dread. And look, like, this is the worry that there's been people

“been talking about all year long before this piece. And so, like, the whole reason people are like”

talking about, oh, are all these software companies that have thrived forever or the reason whether they're many of them are at all the time lows and because of, like, wow, people are very impressed with the capabilities. And you have a lot of people talking about the potential for mass white color layoffs. And so, therefore, you know, I read it as a sort of, let's put this all together. And so, the point is like, you want to be thinking about scenarios, particularly

from the public sector response. Like, let's actually talk about what this could look like. It's straight to me as a useful exercise. Right. And the reaction itself is informative. Yeah. So, right. So, again, we should not be in an environment where you can have a think piece, a single scenario that actually causes a broad cell off of a lot of people start like painting on this particular piece. And likewise, we shouldn't really be in a scenario where

Citadel securities publishes a rebuttal and then everything starts rallying. All it underscores is that no one really knows anything. And this is on Tentero. Yeah. Like, there's like, people are extremely stressed and know it. It's, you know, it's like, it's genuinely, it's uncharted territory. It's uncharted to have a technology that is approving as fast as it is. It's uncharted to have it. You know, it's not like one lot, one specific industry is it's like a broad range, no one knows

where it's going to be. So, it's like, people are like deeply anxious about it. And it articulated a lot of views and it landed at a moment where this was just top of mind for everyone. The one last thing I'll say about this is I'm really glad you asked about policy because this also seems to be the wildcard in some tired discussion, which is like, the outcome of all of us could end up being very different depending on what policy makers actually decide to do about it.

And so far, we haven't really seen any, like not even early signs of how people are thinking about this. There's virtually no discussion in DC about anything substantive related to like the actual impacts of AI. There's almost none. And there's, it's this very weird chasm that's opened up between how much of a big deal so many people are thinking about this. And how politicians like they'll talk about anything, but it's very strange. It's actually, it's starting

to get pretty surreal on this. Yeah. All right. Well, shall we leave it there? Let's leave it there. Okay. This has been another episode of The All Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Jill Wyzenthall. You can follow me at the store. Follow our guest James Van Gillen. He's at Katrina 7. Follow our producer's Carmen Rodriguez at Carmen Armandeshal Bennett at Dashbot and Kill Brooks at Kill Brooks.

And from more AdLaw's content, go to Bloomberg.com/AdLaw for the Daily Newsletter and all of our episodes. You can chat about all of these topics 24/7 in our discord discord.gg/AdLaw's. And if you enjoy AdLaw's, if you like it, when we talk about the AI doomed scenario of 2028, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes, absolutely add free.

“All you need to do is find the Bloomberg channel on Apple podcasts and follow the instructions”

there. Thanks for listening.

Since you said in September last year that you were short, gold, it has doubled in price.

“So listeners, when we say this show is not investment advice, we make it. It is not investment.”

There are, we ought to put up a plaque in the FTO offices to how wrong I have been about gold.

Unheached from the financial times, get it wherever it is you get podcasts.