C (2:18)

So I think, you know, those are all great corporate euphemisms and of course that's how they're going to say it. But I think the way I would think about this is it' not necessarily like agentic powers happened and now everyone's going to get fired. Agents and LLMs broadly are just sort of on the tech tree as a continuum from software. And so software has been making companies more efficient for decades and that has caused a lot of downstream effects. And now that software has just become much more intelligent. And so in that sense, I think companies that are efficient have been doing a form of this for a really long time. And we think about the age starting now in 26 is just something that's going to accelerate that.

A (2:57)

Okay, so yeah, what else was key in the thesis or maybe potentially overlooked that you think people should be really focusing on?

C (3:09)

I think the problem, a first thing, the most important thing is just the labor market dynamics. We've just been in a really weak labor market for a while and that's before these things roll out. But then you put that together with the fact that we just have a very structural environment where what is the thing that drives our entire economy, it's wages. Most of those wages that are ultimately driving all the discretionary spending is coming from the white collar worker. And the problem with that is that we're now entering this place where you made all these assumptions on loaning money to all these companies, you know, to mortgages and everything else. Like white collar economy is our economy. If you all of a sudden just take a leg out of that economy, it has a contagion effect into basically every asset in the world. And so that I think is the part that people haven't thought about because when, you know, people were making these loans, no one ever consumed a world in which, wow, okay, now like white collar jobs are in sort of permanent decline. Right. If that's at 2% a year, then I think we can skate through. But if it's at 4 or 5% a year, then, you know, we have to, we need action a lot more quickly.

A (4:15)

Is the, is the white collar economy actually the full economy or is it more just like the stock market? Because it feels like white collar workers are disproportionately allocated to assets versus consumption. And you see things like, you know, like there's a lot of health in more blue collar sectors. Health care is growing. And then you Also see dynamics like just, you know, like we've seen like jitters in the, in the consumer market for a long time and then we just see the health of the American consumer just continue and continue and continue. And it feels like it's maybe driven by something like lower level. And there's always this disconnect in my mind between like the economy and the market.

C (5:00)

It's a great question. I think the issue here is that it's all just one labor market. And right now blue collar is doing better because they're not firings there. Yeah, I don't think, you know, I think Robots are probably 18, like 24 to 36 months behind other forms of alums that are, you know, just diffusing through society. But the problem is, let's just say that it's one labor market ultimately. And if there's no more white, if the white collar jobs are going away, let's say, you know, in our scenario we talk about 5% of folks might get fired in a couple of years. Those 5%. If there aren't white collar jobs for them to relocate into, then they're going to have to move into the gig economy and the blue collar labor force. And so that puts pressure on the entire labor market, not just the white collar one. And to answer your other question, healthcare is growing, education is growing. The reason those things are growing ultimately and we did some work in our piece to try and isolate white collar that is not government driven. And so the government continues to spend more. That's why healthcare is growing. They're the biggest payer in health care. They're guaranteeing all the loans in the education industry. And so those sectors continue to grow because government spending grows. But that's again, it gets very circular if government spending is coming primarily from taxes and primarily payroll taxes because the average worker pays a lot more in taxes per dollar than the average corporate does. And so some corporates make a lot more money. Workers payroll taxes go down more than. There is a bit of a contagion effect into bonds as well there too.

B (6:23)

On Saturday, John and I were going back and forth about some of the really wild predictions around the impact of the Internet that were being made in the 90s. There was clicks replace bricks. People were predicting total die off. Clicks did.

C (6:37)

Well, I mean, to be fair, I

B (6:39)

mean to be like, I'll just finish. They were expecting a total die off of all brick and mortar stores in five to 10 years, which was like widely discussed prediction. It was like, why would you ever go to a store to Buy something if you could just get it online, sent to you directly. Yeah, and I think a couple, a couple, a couple others. So like not as relevant to your piece, but people were predicting like permanent high growth, the end of business cycles. There was the like media disintermediation narrative which was like the Napster era. Everyone was going to get all media for free forever. Newspapers would, would die off, record labels.

C (7:23)

Aren't you guys the, Aren't you guys the media disintermediation narrative?

B (7:27)

Yeah, we are, but yeah, it's all about timelines. 20 years later and CNBC is still a much, much bigger business than all, all business media, at least in our world.

C (7:39)

But like newspapers, like magazines, completely gone.

B (7:43)

Right?

C (7:43)

All of that has moved to the Internet.

A (7:45)

Totally, totally. It's just like, sure, but like 5% employment shock in a unique quarterly different. I mean like a 5% unemployment shock is completely different if it happens over a quarter than if it happens over two decades. Right. Like these are just fundamentally way different.

B (7:59)

Yeah, so the other, the other thing, yeah, the last thing I would say is like there was like this concept of like frictionless capitalism, meaning that like middlemen would be eliminated because you could just go directly to the source and that would push pricing pressure down. My question, and I know you guys are not writing your piece saying like, you know, this. We, we believe we will stake our entire reputation on, on this sort of narrative. But what do you think? What, what, how much did you pay attention to like the 90s, early 2000s Internet predictions? What do you think they got wrong? Why is this time different in terms of how a new technology will diffuse to the economy?

C (8:43)

I think the difference is if you just plot what's happening to technology, it's all just going exponential. These are all just continuous timelines of like, we have microcomputers, we had the Internet, we have mobile phones. And today, you know, we have very powerful AI. And so I think most of the predictions that you ticked off there, it's kind of interesting. I would, you know, just looking at them today, you know, I would say they couldn't really happen until you had proper AI because like, if you have the ability to just freely, you know, commerce, like have commerce the way you do today doesn't work if you still have to do all the work ultimately, like you have to go and you have to log and think about the amount of friction there is in buying a product for most people today. Right. You still have to go to the website, you have to put your credit card in. It's all work. We only have gotten to kind of the tech required for those predictions I think this year. And that's why this is the year that I think it really begins. Because now it is completely seamless. You just, and no one's really doing this yet, but it's going to happen. I think, you know, in the next six months is just tell your agent, you know, tell Gemini, tell ChatGPT, go buy these things, it has your credit card. And now that world that they were describing is truly going to come to pass.

A (9:51)

Yeah. What about the canary in the coal mine analogy? I was looking at unemployment statistics in India and the Philippines and it doesn't seem to be doom and gloom over there. I don't know, I didn't dig in super far. But would you at least expect that the unemployment rate would spike overseas before it spikes in America? Or do you think this all happens simultaneously?

C (10:20)

It's a tricky question. I think ultimately white collar work is a lot more of our economy than it is the economy of India and the Philippines. And they are much sort of like more immature economies that are growing through investment and things like that. But certainly I think we called it out, the consulting sectors in India are certainly going to be challenged in other places. Well, but the reality is like the timing, timing is everything in the markets, clearly. But the trick here is if you're a corporate and you are hard pressed to get AI into your organization today, you know ChatGPT and OpenAI will send you a forward deployed engineer if you have billion dollars in budget. Right. But if you have a $10 million budget, they're not going to. And so who are those folks turning to? They can't usually do it themselves. And so they are going to the outsourced providers, the accentures of the world. And so I think those businesses are likely going to be in a lot of trouble over the medium term, but they probably will have a big bump from people really putting that AI into their organizations first. And so it's a bit of a tricky timeline there.

A (11:20)

What moats do you think hold beyond this? Because I think a lot of people latched on to like the doordash example as something that they thought had a moat and that in the post you sort of underline like how that could maybe not be as durable as a moat as people thought. But in the long case, like what moats do exist? Like do network effects stay do complex coordination, intellectual property, what doesn't break down

C (11:54)

real brand value when people are choosing you over other things because of the brand and the Status signaling across brands matters a ton. Network effects are more powerful than ever, I think, in this world. So things like Meta really have a lot to sort of gain in that sense. But I think things that look like their network effect businesses, but in fact are just the ones that are doing the hard work of aggregating demand and supply, I think will be more challenged. And so DoorDash is a good example there. It's not necessarily the biggest risk versus some of the other things, but I just was in a thread with Gavin Baker talking about this. But the problem for DoorDash and Uber and folks like that is right now they're doing two jobs. They're doing the job of aggregating demand and the job of aggregating supply. They're both hard jobs, but the demand side is the harder side. And in, we think, the world of the future, there are lots of folks in, let's say, food delivery. You know, Instacart wants to get a bunch of market share and, you know, GrubHub wants to get a bunch of market share. And so let's say the agents are the ones doing the buying. It's 2028 and 40% of the sales are through agents. You just tell Gemini, hey, order me some noodles. In that world, instead of it's going to go to each and every provider. And right now there are four providers that do that. But now it's very easy, as if I'm building a startup in the space. Previously I had to get all the drivers on board, get all the restaurants on board and acquire customers. Now Gemini and ChatGPT are acquiring the customers for me and all I have to do is get the supply side going. So it makes it much easier for new entrants to come in. And for existing second, third, fourth tier players can really sort of say, I'm going to like, relax my margins, try to get more top line. And so you would think that whatever the 15% vig is that DoorDash gets today, maybe it's more than that. You know, some of that. I would think Gemini and ChatGPT are going to ask for themselves. Wherever I send the traffic, I'm going to get a piece of that and then some of that's going to go back to the consumer.

A (13:46)

Yeah, it feels like. Was this the most, like stretched or controversial prediction?

C (13:54)

It seems like it was certainly the one that got chatter. And I think we did it for a reason. We wanted to be a little provocative and think it through because it's an amazing business and they're gaining A market share. But the fundamental idea that you're. Because what did the lock in the drivers have lock in on DoorDash or on Uber? Not really. Right. Most drivers are doing Lyft and Uber, so they're not locked in. The real lock in, the real business value, the franchise value of an Uber or DoorDash is the customer lock in. Because the customer gets comfortable, they've got everything saved. They want to hit a couple of buttons. They don't, they don't price shop. Agents are happy to price shop as much as possible. And so if you take that away, then it's a real problem for businesses that are ultimately built on customer lock in.

B (14:35)

Yeah, yeah, I don't know. I think the interviews that we've had with the Lyft, I mean, you know, again, take, take it with a grain of salt. They have a narrative that is important to their business. But like, if you ask these people what is the greatest challenge, it is managing the supply side, the demand side is not where they're saying like, hey, this is really what we need to solve. It's like, hey, as we get more drivers on the platform, revenue naturally goes up. And so I'm just hard pressed to imagine a world in which, you know, somebody think, think about if somebody in my town, which is like 15,000 people, like Vibe, codes a delivery, a delivery app and I go into ChatGPT or with another agent and I say like, I want food. It's like the agent wants to get the best possible service. I would imagine the agent to route to the platform with the supply that is going to be able to deliver in the shortest possible time horizon. And imagining a world where there's like this Vibe coded small team operating that just happens to aggregate as much supply, which is just increases the likelihood that my order will be delivered on the best possible timeline, which is going to be the number one factor for customer satisfaction. I just don't see how solving the front end kind of demand piece actually makes a better consumer experience, which I assume the agent would optimize for on behalf of the user.

C (16:13)

So let's consider what actually happens here. Right? You make the order on DoorDash, DoorDash sends it to the restaurant. The restaurant essentially, you know, sometimes they use their own drivers, sometimes they send the drivers from doordash. But now imagine the agent can take you directly to the restaurant site and place the order directly with the restaurant and you can keep half the savings and the agent can keep half the savings.

B (16:40)

Right, but where's the driver now?

A (16:42)

Where's the driver coming from? Because I feel like I understand the customer demand side. Like you start with an LLM or an agent who shops around for you. So maybe that's solved. Maybe it'll find you just via SEO and you can just put out like we only take a 5% cut instead of 15% and the agent picks you. I understand getting all the restaurants on board because you email them and say, hey, it's 5% instead of 15%, they're sure we'll turn it on. But for the drivers, how do you actually reach out to them and get them on the platform? And how does AI lower that cost? Because right now I think about what was the driver marketing budget over the last decade at Uber or at Doordash and it's probably like in the billions of dollars. And so I feel like to generate that much liquidity, I have to invest that much board. All those drivers build awareness. Maybe it just goes viral because they're like, hey, I can make more money here. But that feels hard.

C (17:42)

I think it's going to take time. But I think there are a bunch of smaller sort of driver aggregation networks that exist today that are not the ones that we know about. For instance, I started a business called Thistle and we do delivery of healthy foods to your door. We, we split it between half of them, our own employee drivers and the other half, you know, I think we have like, like 500 or 700 drivers that we just use a third party service to provide. So I think there are a lot more of these businesses. All those businesses now will also just have huge opportunities to kind of take market share. Ultimately what we're saying is the friction in doing commerce is going way down. Places where there are rents, the prices can go down. But ultimately this is just an opportunity for more and more entrepreneurs to kind of build businesses for the new world.

A (18:22)

Yeah, I think the, it's interesting because we're here like debating like this, this like somewhat temporary thing because like self driving cars, robotics like changes all of that like huge way. But we use the term sloppable for companies that are, that can be vibe coded away and clankable for companies that can be disrupted by robotics. And I've always put the delivery services more in the clankable category than the sloppable category. So I was shocked to see what

B (18:50)

are the, what would you spend more time on if you knew you were going to get 50 million views and the markets would react in the way that they have?

C (19:03)

I would have finished writing the third piece where I Talk about solutions, which I have not gotten.

A (19:08)

A lot of people are demanding solutions. You just got to, you just hit me with a ton of problems. That's funny. Do you think that there's any. There's this question about like in my mind, like yes, Google and Nvidia are public, but anthropic OpenAI and XAI through SpaceX are not public. And there's sort of like this massive, you know, multiple hundred billion dollar sell off in the public markets that sort of should, if you believe your thesis, that should sort of funnel to the labs. I would imagine when I read it like there's a lot of doom and gloom about companies that are out there, but it's a lot of bull. It's a lot of bull case for AI labs but that can't happen in one day because like rounds happen every once in a while. They're private. There's all these different things. But do you think that the world would change when the big labs get out in the public markets?

C (20:03)

I think it's absolutely going to change. I have a strong suspicion that Anthropic is going to go, you know, in the next three to six months. They just have so much momentum and there's a lot of value being first. PNL also just looks a lot better than anyone else. So I would think that gets public and it's going to be pretty interesting if it happens. Certainly labs are ultimately, they seem like they're, we're very well positioned to win. I would wonder over the medium term, like, you know, what happens with some of the Chinese models and whatnot, if people actually want just something that's more local and something that they own. But it does seem like the most likely outcome is going to be that the existing incumbents are going to get the most share. And I think Google is particularly well positioned since they already own all of those customers today and they can finance losses from inference a lot longer than everyone else. But I think ultimately there's a world in which the labs are the biggest winners here. There's also a world in which like you end up with just a lot more competition and people trade and change. But the thing that seems very clear to me that the absolute, like there's no way they won't be the hugest winners here is going to be the underlying tech, meaning the semiconductors. So you know, everything, you could go even deeper.

A (21:07)

You could go into like, you know, commodities and like copper and energy and oil and natural gas and stuff and people have.

C (21:13)

Yes.

B (21:14)

Did you see the.

A (21:16)

Yeah.

B (21:16)

Did you see, the. Some of the criticism was that the essay was very Marxist. Oh yeah, he said Mark. Mark's writing during the Industrial Revolution predicted capitalism would periodically devour itself. Firms replace labor with machinery to boost profits, but competition diffuses. The technology drives prices to marginal costs and the gains get competed away. Meanwhile, displaced workers lose purchasing power, hollowing out the demand the whole system depends on. Production rises, but no one can afford to buy what's produced. The contradiction between production and realization. Citrini's piece describes this exact dynamic, then declares there's no natural break. It's the most Marxist piece of financial analysis. Not my word.

A (21:56)

I don't think that critique and makes

B (21:59)

the same errors Marx did. Yeah, creative destruction doesn't just destroy. It creates industries we can't yet conceive of.

A (22:07)

Yeah, that's an interesting. I mean, maybe that's going in the solutions.

B (22:09)

Is that going in the solutions?

C (22:11)

So let me address it a few ways. Marx was a really smart dude. He got a lot of things right. Very early Marxist can mean communist. Marxist can also mean just understanding how capital and labor interact. And in that sense, yes, it is Marxist. He was very insightful. But I think the thing that we're missing here is that there's the economic layer, but ultimately it's the political layer that matters. And we're in a world where we've had two parties and both parties economically have a little bit of difference, but not a huge amount of difference. And so we kind of bicker. But in a world in which jobs are going away really fast, I think there's going to be a much stronger alignment for just the laboring class overall to say, hey, we need to fix this problem. It's a very fixable problem. What we're actually expounding here is that gdp, if done properly, will absolutely explode. Right. We were getting way more efficient. We have, you know, we built a machine dot, we build machine intelligence. But we have to structure our society such that as those things happen very, you know, hopefully very slowly, you know, we. We do the right thing from a taxation perspective to say the winners should win. But, you know, if that's what's causing the displacement, let's sort of make the pie a little bit bigger for everyone. And that I think ultimately should be something that appeals to a lot of folks in the AI complex because if we don't, then something like this is likely to happen and, you know, progress will slow down because we'll have an economic crisis and we're not going to finance nearly as much of it. As we otherwise would.

B (23:40)

So do you think the future is what anthropic head of sales position in France, the company will be spending €530,000 per year. The government will get €340,000 and the employee will get 190,000. Is that, is that the level of taxation you think we're, we're headed for?

C (24:01)

I think when we're at, you know, France's level of government spending, then, you know, the math probably means roughly that I would say that, you know, government spending would be at France's level, I'm guessing like, you know, five, seven years from now if this, if this scenario kind of comes to pass. And so I think we'll head there over time, but I think it's less a question of the percent of spending and how much goes to the employee versus goes to the government and ultimately what is the size of the total pie. So the bet here is that the piece, if done properly, can just increase multiples of what it is today and thus it's just a win win.

A (24:35)

One question. I mean, it sounds like you're working on potential solutions post, which I'm very excited to read. Thank you. I'm interested to know your reflection on the messaging that's coming from the leaders of the AI labs because they've outlined many sort of low probability, but, you know, potentially negative scenarios. You know, we have the white collar work number. We've had many of these comments from lab leaders, but I rarely hear them follow it up with. And the answer is print, print, print or interest rates will be will save us or unemployment insurance or ubi like all of those like solutions that I think people. It's funny because people are quoting your post being like, this is easily solved with this solution. It's like, okay, well that's great. If we all agree, agree. And I think you might with some of the quotes, people are all over the place. But I'm wondering about your reflection on like the, like the messaging from the labs around solutions versus pure focus on problems.

C (25:39)

I think it's a really interesting question and very interesting setup in that the labs are on the one hand, you know, want to get the word out there. And so, you know, Dario especially has been the loudest here. There's a really good Axios article from last May where he's kind of sounded the alarm bells. People aren't really. He's like, people are not listening. Obviously a lot has changed since then, but they can't go so far as to say like, hey, if you put the pieces together, Then this is how it's going to play out. I think it's too sort of damaging to sort of their reputations and like, you know, their ability to fundraise and things like that. And so I think it's other folks like ourselves that kind of have that duty to go and really start thinking that through. I sort of. It seems like anthropic is pretty engaged, you know, should that conversation really start happening. And I think this is the year it needs to really start happening. And so I think they all kind of get it. And so it's just a question of like, how do we as a society start moving in that direction?

A (26:31)

Yeah, I think, you know, obviously there's. I'm still processing part of the piece. I agree with some of it, I disagree with some of it. But what's really underrated is just like how useful this process of writing an article for a particular audience is. Like, I disagreed with a lot of, you know, something big is happening, but it hit with a very different audience than machines of loving grace or the adolescence of AI or of machine intelligence. And there's pieces that are written for like AI insiders, leaders, researchers, then there's like the broader tech community, then there's like everyday people. And you clearly hit the nail on the head with speaking to the financial community. And we see that in the markets. Not amazing results, but maybe it's worthwhile because we will get really great solutions and a better conversation around it. So I think, I think in due time this discussion needed to be had. So thank you.

B (27:36)

What's it, what's an industry or job of the future that you could see emerging?

C (27:43)

I think again, if we solve this, like everything related to sort of leisure is going to absolutely zoom and that those are going to be the biggest growth industries of the future. Right. Like, what do humans want to do?

B (27:54)

Total victory.

A (27:55)

Watch polo. Cloned horse play polo? For sure. Yeah.

C (28:02)

Imagine humans have the entire day to just enjoy themselves instead of having to work.

A (28:08)

Now that is something I've been promised for 100 years. So I'm deeply skeptical. But this time is different. I want it to be different. Let's bring on the leisure boom. I'm here for it.

B (28:20)

Anything in your solutions, doc? Around re industrialization? I mean, the frustration that so many people in tech that have been building in kind of hardware in the real world or trying to recruit people that are getting offers from social media companies or Now Labs or SaaS companies. One of the problems for America in the last 20 years was that if you just wanted to make $100 million, you probably were much more likely to do that building enterprise software than building critical infrastructure or anything in the real world. So is that is kind of new infrastructure and re industrialization like a potential landing point for people that had the 180k a year PM job that might be going away?

C (29:12)

It's a great question. I think there's certainly going to be a lot more opportunity in those sectors and I think we, we've done some pretty smart policy things that are moving us in that direction. But we're also, you know, just in a lot of ways so far behind China there. And doesn't I affect kind of those jobs both for, you know, on the re industrialization side just like it does for writing code. And so that's where I think it will get trickier. I think over as a, as a country we're going to spend an awful lot more on that and I think we're going to, we're going to catch up, but we're not, it's not clear that's going to be through just creating a bunch of additional jobs versus the ultimate thing we're seeing with AI period is just high agency. People who really know how to use the tools can just do the work of many, many people. And I think that trend applies in every industry to some extent.

A (29:57)

Yeah. What an exciting time. Thank you so much for taking the time.

B (30:02)

When's the next piece dropping?

C (30:05)

Hopefully by the end of the week, but don't hold me to that now

B (30:10)

when you know that it could. It'd be hard for the follow up to get as much reach as this one. That's kind of the way these things go. But now the pressure is on to really pay attention.

A (30:19)

Just don't have any anxiety, you'll be fine. We're excited to read it and we'll talk to you soon.

B (30:25)

Yeah, great to meet you.

A (30:26)

Have a great rest of your day. Thanks so much.