What I learned from the world's leading minds in 2025

0:00Hello, everyone. It's Azeem here. And as the year comes to a close, I have been reflecting on why I started this podcast nearly a decade ago. It began as an attempt to understand how exponential technologies are going to shape the world. And in truth, I just wanted to have some great conversations. Now, that lens and those discussions have taken us through many themes, including artificial intelligence, energy systems, biology, pandemics, geopolitics, and many of the other deep structural forces that influence our world. And yet, the very first episode back in November 2016 centred on a question that remains as relevant today as it was then.

0:43How is work evolving in the face of transformative technology? Back then, I discussed this with Ryan Avent, who was then a writer at The Economist. But the question has been core to my analysis this year, and it sits inside a wider set of concerns. Artificial intelligence is starting to behave like a real general-purpose technology. and we're watching an enormous industry and economic architecture form around it. It's raising the live question of whether this is sustainable progress or the hallmarks of an investment bubble. Work itself is being rewired from labour markets to agentic workflows and the way teams are organised.

1:21In the US and the UK, graduates are bearing the brunt of changes in the labour market, but is the softening in demand for their skills as a consequence of technology or something else? The physical world has reasserted itself as the build-out of compute and the struggle for energy and grid capacity become the binding constraints of a move to an AI economy. More than a decade ago, we used to say that software was eating the world. Today, we've realised that software is demanding a new one. All of this is unfolding within a more fractured geopolitical environment, shaped above all by the evolving relationship between the United States and China.

2:02In this episode, I've pulled together highlights from the most interesting conversations I had on all these questions over the past year. You'll hear from Matthew Prince, Steve Hsu, and many more. These are just glimpses of the exceptional dialogues I was fortunate to have this year. Please go to Spotify, Apple Podcasts, YouTube or the Exponential View Substack page for a full access to all of them. Let's begin with the question that's dominated 2025. Is all this progress real? How fast is AI improving? What's driving that progress and how is the economy bending to accommodate it? We've looked closely at whether this is sustainable growth or the familiar shape of a speculative bubble.

2:45The clips that follow will give you a sense of the new development loop inside Frontier Labs, the economic dynamics of the industry, and the strategic bets that will define the coming years. We've also built a data-driven live dashboard to track the most important developments in this investment cycle. You can find it at boomorbubble.ai. Here's what I asked Kevin Weil. He is the Chief Product Officer of OpenAI. So let's imagine my son, 20 years old, and he wants to build a a product on top of OpenAI, where is a good place for him to go and build it? Sam said this one time, and it stuck with me.

3:23He said, if you're building a company and you're building at the frontier of, you know, the model capabilities, if you're building something that really just barely works and you can't wait for our next model because you know it's going to make your product sing, then you're probably building in the right place. If instead you're building like some sort of scaffolding around that covers up the weaknesses of a current model and you're actually afraid of our next model because it might not have those same weaknesses, that's a bad place to be building because on average models are going to improve really fast.

4:02I also asked this to Matthew Prince, CEO of Cloudflare. We have this price discovery mechanism and we have this efficiency across the market. And then we have what I can only describe as a socialist suggestion from you, which is that smaller companies should sort of pro rata pay much, much less than bigger companies. Tell me how that works out. So I think that's actually very capitalist, not communist at all. And what you're as an AI company really paying for is on behalf of each of my users, do they get access to this content? It's almost like a subscription fee. If you have an AI that only one person uses, they're going to pay a relatively de minimis amount.

4:40Whereas if you have 6 billion users, like a Google does, then of course they should be paying more because the value is being spread across a much wider population. There's a really interesting idea in there, which starts with the fact that LLMs don't get addicted to dopamine. They are this aggregate of human knowledge and their training and the reinforcement learning to get them to behave in particular ways. But it's quite hard to get them to be extreme by the time they reach us. There is also this really important point that you've made, which is we can start to identify more clearly where there are gaps and opportunities.

5:18For the first time in human history, we effectively have a mathematical model for the representation of all of human knowledge. You also then inherently get a pretty good model for where the holes in human knowledge are. And so, again, I picture it like a block of Swiss cheese where there's a lot of cheese that's there, but there's a lot of different holes because the business model of the web is going to change no matter what. it's going to change because answer engines are coming and they're better. And as a result, the business model is going to change. What I hope it changes to is one in which we reward content creators that create content that fills in the holes in that cheese, where they're actually doing things, where they're making things better.

6:03Tyler Cowen, a professor of economics, has this to say about the AI boom. I heard a lot of people there talking about the prospect of AI driving 10, 20, 25 % of economic growth, there would be this bounty that AI would bring us. And I don't really agree with that. What are those projections getting wrong? They're ignoring the all-critical role of human imperfections in systems and institutions. So the more powerful AI becomes, and I'm not a pessimist on that, the more it bumps against people who don't want to adopt it or institutional systems where it does not get incorporated into the workflows.

6:43The general economic point is that as one thing in your economy gets better, the remaining imperfections become all the more important. When you look at healthcare, education, government, the nonprofit sector, as you work in these, as I have, you will see the rate of improvement is going to be pretty slow. I asked Nicholas Thompson, CEO of The Atlantic, about the future of journalism. I've been on Substack for eight or nine years now. One of the things that struck me, and this does connect in a sense to our questions of trust and business models, is that you know, sub stack funded pundits like me are being paid to be believed, right?

7:23It's about my reputation. It is moving from a world of selling attention to advertisers to selling conviction to subscribers. And that is a different way, I think, of thinking about the relationship between, you know, an expert and the people in their network and in their community. Imagine if you could have a sub stack where you got an Applebaum and Tom Nichols, like and David Frum, right? Like and Jeff Goldberg. And it was$80 for just that sub stack. Well, it's like The Atlantic. You get 100 of them. And, you know, so from a reader perspective, subscribing to The Atlantic versus subscribing to a whole bundle of sub stacks is really appealing.

8:00I don't think there's any doubt that power has moved. You know, it's true in media. It's true in all kinds of it. it's even true in the NBA, right? Where you follow teams less than players, like the all-star game, it's Team LeBron versus Team Giannis. It's not East or West or whatever. You know, you see it in all kinds of industries where power has moved from the center and from the brand to the individual. And so our challenge at The Atlantic is, how do you make the individual writers stay? How do you give them incentives? So why would you write for The Guardian or The Times? Well, you'd get a salary, but you'd also get read, or at least you'd get distributed.

8:32Kevin Kelly, the executive editor of Wired, and I discussed multiple topics about AI. So one could argue that some aspect of the Western condition and, you know, any sense of the malaise perhaps may come from an excess of comfort, right? So the appeal of being sort of super served by a network of thought also sits counter to something that has also been inherently human, which is we have to struggle and we often do struggle and struggle forms a part of the creation of our moral virtues. I don't believe in utopias. I think they're a bad idea, even if you can make one. I believe in protopia, which is this incremental move to slight betterment, even if it's only 1 % improvement over time.

9:15And that you accumulate. We can create 1 % more than we destroy each year. We can accumulate a civilization. I think the struggles are never going to go away. The struggle is the process. We may change the kinds of things that we are occupied and struggle with, but I see that, again, as progress. I actually, as a human, really like the fact that when I turn the tap on the faucet in my kitchen, I know clean drinking water will come out of it. Behind that is a whole load of really complicated stuff. And as our world gets more complicated, We actually, I think, do want to abstract away from that complexity.

9:54You mentioned complexity. I have another term. I use the word options, possibilities, and opportunities. That's what we get with technology. It's not just complexity. It's the fact that we have more options, more choices about what we want to do in life. And by the way, if we want to be an Amish farmer, farming the old way, that's still a possibility. and that is there. If you want to be a mathematician, if you want to be a ballerina, if you want to be a mortgage broker or a web designer, you now have that possibility and we have even new ones in the future. And so that's what technology gives us.

10:33You come to the city, which is a possibility factory, and you come to modernity, which is increasing the options. One of the most significant shifts this year has been that AI is rolling out into our workplaces. It's altering tasks, roles, and organizational flows. And it's colliding with other long-running forces that impact the labor market, such as post-pandemic norms and all the economic uncertainty that surrounds us. The result is a complex and sometimes contradictory picture. I spoke with people who each hold a different part of that story, and together they help us understand how work is being rewired.

11:10Steve Hsu, co-founder of Superfocus, had this to say. We have been researching putting that brain into a small plush toy. So imagine that small dinosaur bunny rabbit that your kid is carrying under her arm. She's your kid is two or three years old. And this thing is teaching your child perfect French or how to count or telling its stories, singing little songs. And we find that the systems we built, kids really enjoy interacting with. And just imagine the learning possibilities like, There's a window of neuroplasticity where you can acquire a foreign language at native level fluency when you're quite young, if you just hear it.

11:52I'll ask Ben Zweig of Reveglio Labs to explore what's happening to the world of work. I think you could say, oh, well, you know, AI, you know, seems to be affecting the execution of tasks, which, you know, young people do. rather than the orchestration, which favors more senior workers, because, you know, in the age of generative AI, we're essentially managing these bots to go and do things and execute on some subtasks. I could see a world where even entry-level workers are kind of middle managers in a sense. They have more orchestration of systems to do. And that is kind of how we think about middle management.

12:29You know, they're sort of piecing things together to ultimately deliver, you know, something more abstract. How do you solve for that novelty risk? One of the reasons we had discussed that managers were slowing down their new hiring was that Jason from outside the firm, who's 24 and just finished a grad degree, is not known to the firm. And Jason can get all his orchestration skills and he does it through Khan Academy and Exec Ed and whatever else, but he's still outside the firm. So are there any mechanisms that allows that signaling to de-risk for the manager? It's a tough part of labor economics because, you know, signals have been eroding over time.

13:08So, you know, higher ed was always like a great signal and you get, you know, a diploma and that was always a good signal and still is. That's part of education. And part of education is actual education, actually increasing your skills. And that part is more and more suspect. Employers have a kind of high discount rate. They're optimizing for the short term more than the long term. And young workers generally, entry-level workers, are workers that are more uncertain, whereas more experienced hires are the safer bets. That is such a fair summary. And taking on board a millennial who might need their kombucha and early break on a Friday afternoon is higher risk than whipping the corporate wage slave in their 50s.

13:52Thomas Donker, CEO of GitHub, had this to say. Isn't there a case that we've gone over the hill, over that point where the languages were high level enough, abstracted enough that we could understand them to a point where we're going to be creating so much code so rapidly that it'll be less inspectable for the human. I believe you're already past that point. With or without AI, we passed that point, you know, a few years ago when it became clear that the majority of projects, commercial or not, are based on 90 %-ish, you know, plus or minus of open source libraries. It's very rare that a a single person can navigate that whole code base, right?

14:32So what do companies do? They divide and conquer and they assign, you know, subsystems to individual teams. We've often argued that technology is increasingly weightless, that computing is intangible, that information defies gravity. But what we've learned this year and the year before is that all of these technologies, this AI fabric, is really fundamentally physical. And the race to build compute, secure power and upgrade grids has become one of the defining challenges of this period. But at the same time, the energy system is changing because energy is shifting from being a simple commodity that we pull out of the ground to a technology that we can develop, iterate and innovate on.

15:16In this section, we're going to hear from people who've been examining how these physical limits shape what's possible in the digital realm. Here's what Greg Jackson, CEO of Octopus Energy, had to say. This week has been pretty bleak for energy transitioners. A lot of people will believe that we're going too fast, that this is happening helter-skelter, and you can understand why that is. We're halfway across the road. Now, if you've ever seen anyone hesitate crossing a multi-lane highway, that is a very dangerous thing to do. The best thing is to get right across as quick as you can. And that's what we have to do in the transition now.

15:49And to do that, we need to be taking sometimes hard decisions. The faster we get across the rest of the road, the safer we're going to be. Because at the moment, you kind of try to ride two horses at once. And that's really never very effective. Certainly the minister in the UK, when I hear him speak, Ed Miliband, what I hear is somebody who is first and foremost thinking about a political objective, which is net zero. A number of the advocates are promoting it in a way that is very ideologically driven, that is probably not very persuasive, frankly, compared to the notion of, I'm not going to pay an energy bill.

16:24I was joking to someone recently that I'm not a good salesman, which is why we had to build Octopus to show not to help. We are now building homes. We'd signed deals in eight of the biggest house builders in the UK to build homes where there will never be an energy bill because they have a combination of heat pump, battery, and solar panels. We shouldn't try to convince people this. We should be able to show it. The lived experience beats the techno-optimism. I also asked Dan Wang, author of Breakneck, about his thoughts. The point about power is really, really critical. I mean, we've seen the tremendous, tremendous demands that AI data centers of 2025 are already putting on not just the U.S.

17:05grid, but the supply chain and the regulations that slow things down. Maybe the U.S. has a lead in reasoning models right now, but there are other big advantages that China can bring to the table, which involve much bigger aspects of hardware. AI requires a lot of power to both train and to actually run. And China right now is producing, by the end of this year, 500 gigawatts of new solar install. The U.S. will have about 50 gigawatts, so just one order of magnitude difference. China right now has 33 nuclear plants under construction. The U.S. has zero. These shifts, both technological and economic, sit within a world shaped by rising geopolitical tension.

17:45The dynamic between the United States and China is becoming the central influence on how AI and its supporting industries develop. It affects supply chains, national strategies and the emerging logic of sovereign AI. Let's hear from guests who've examined China's political economy, its manufacturing depth and the strategic consequences of a splintering global system. Dan Wang also talks about this. There is that, you know, the mRNA vaccine, the smartphone or GPS. These are things that have emerged from, you know, the American innovation stack. Has a Chinese stack produced anything that is comparable?

18:26My view is that science is, for the most part, a public good. Does not matter whether the innovation comes from Zhejiang University in Hangzhou or Stanford University in California. It's whoever can make the most use of it. and the American firms have not made very good use of it and the Chinese have done a much better job. So maybe this process of innovation is less important. Maybe what matters the most is just having most of the industry and being able to iterate upon it. Most of what technology is are the sort of things that cannot possibly be written down. When you have a workforce that is endlessly just working through all of these different products, producing new knowledge, training each other, that is a lot of what the U.S.

19:06as well as the U.K. have lost in which the U.S. manufacturing employment keeps going down. Right now, it stands at about 12 million people. For China, it's about 70 million people. And I think that really places the U.S. at a disadvantage when the stock of process knowledge is unwinding. Jordan Schneider, best known for China Talk, makes sense of what's going on in the U.S. and China. There are different versions of techno-accelerationism. There is a techno-accelerationism that comes out of Silicon Valley, which is really about building AGI. But there's also policy accelerationism. And, you know, as a slightly distant observer of China, what I see is a type of technical acceleration on the deployment side.

19:48Get it out there, get it used, an acknowledgement that there's going to be job losses and labor market ructions, but a willingness to push past that. Yeah, I mean, that question of like, which societies will hold up better in a time of sort of rapid employment turnover is one that I find fascinating. At what point is a system going to feel like change is coming too fast? And then this sort of like anesthesiologist lobby, that sort of thing, to me, is going to be the more relevant variable of which country is going to gain the most from this. I read this great essay by Kaiser Kuo. He says, China has become a principal architect of modernity.

20:36Kuo argues that legitimacy is actually moving from procedure to performance and that the Chinese track record of the last 30 years is really about that performance. If we're calling China the sort of like archangel of modernity, we also have to understand that there are parts of that modernity, which I hope listeners of this are very uncomfortable with. Thanks for listening. You can find every full conversation on YouTube, Apple Podcasts, or Spotify. For deeper weekly analysis of these trends, join me at exponentialview.co. The coming year will test many of the assumptions we've discussed, and I look forward to exploring them with you.

21:16Let me know in the comments which podcast was your favourite and what you'd like to see more of in 2026. Happy New Year.