So, Dario, we're at Davos. There's a lot going on, but I wanted to start with a big picture question, which I'll characterize like this. It feels to me that this time last year, everybody was very excited about AI, and everyone was talking about what AI can do, its potential, its capabilities. It feels to me as though the debate has shifted somewhat this year to be less what can AI do to what is AI doing to the world? And I know that you think a lot about these things. So, my question is, do you think businesses, policy makers, governments, whatever, are doing enough to prepare for the impact?
No. I'll explain the longer version now. You know, I've been watching this field for 15 years, and I've been in this field for 10 years. And one of the things I've most noticed is that there's been a surprise that the actual trajectory of the field has been surprisingly on the same trajectory. Whereas the kind of public opinion and the reaction of the public has oscillated wildly. I would say that in two different ways. One is the capabilities of the technology. Every 3 to 6 months, we have this reversal of polarity, where the media is incredibly excited about what the technology can do, it's going to change everything, and then it's, you know, it's all a bubble, it's all going to fall apart. And what I see is this smooth exponential line where, similar to Moore's law for compute, we basically have a Moore's law for intelligence, where the model is getting more and more cognitively capable every few months, and that march has just been constant. The up and down, the we invented a new thing, it's all going to crash, it's hitting a wall, it's going to go crazy, that is a public perception phenomenon. That's on the capability of the technology. I think there's a similar thing on the polarity of whether the technology is good or bad.
You know, in 2023 and 2024, there was a lot of concern about AI, right? There was concern AI's going to take over. There was a lot of talk about AI risk, AI misuse. Then in 2025, the political wind shifted, as you say, to AI opportunity. And now they're sort of shifting back. And I think throughout all of this, the approach that I have tried to take, and the approach that Anthropic has tried to take, is one of constancy, of saying that there is balance here. And balance of a very strange form, because I think the technology is very extreme in what it's capable of doing. But I think its positive impacts and its negative impacts, they both exist, right? I wrote this essay Machines of Loving Grace about a year and a half ago. It had a very radical view of the upside of AI, that it would help us to cure cancer, eradicate tropical diseases, bring economic development to parts of the world that haven't seen it. And my view hasn't changed. I believe all of those things.
But the other side of it, which I'm now writing more about and may release something about soon, is yeah, bad things will happen as well. If we just take, just for an example, as one of the risks we take, the economic side of it, my view is the signature of this technology is it's going to take us to a world where we have very high GDP growth and potentially also very high unemployment and inequality. Now, that's not a combination we've almost ever seen before, right? You think of it as high GDP growth, that's lots of stuff to do, lots of jobs for everyone. It's always been like that in the past. We've never had a technology that's this disruptive. So, the idea that we could have 5 or 10% GDP growth, but also 10% unemployment, it's not logically inconsistent at all. It's just never happened that way before. And I'm really quite, for those both reasons, excited and worried.
If I take an example, something like AI coding, the latest model we released, Claude Opus 4.5, I have some engineers, some engineering leads within Anthropic, who have basically said to me, I don't write any code anymore. I just let Opus do the work and I edit it. We just released a new thing called Claude Co-work. We can go into that later, but this was a version of our tool Claude Code for non-coding. This was built in a week and a half, almost entirely with Claude Opus. There are still things for the software engineers to do, right? It's like, even if the software engineers are only doing 10% of it, they still have a job to do, or they can take a level up. That's not going to last forever. The models are going to do more and more, and so there's an incredible amount of productivity here. Software is going to become cheap, maybe essentially free. The premise that you need to amortize a piece of software you build across millions of users, that may start to be false. Like, for this meeting, it might cost a few cents to just say, let's make some app so people can talk to each other, or whatever, it just may be very flexible and recyclable. But at the same time, there are whole jobs, whole careers that we've built for decades that may not be present. And I think we can deal with it. I think we can adjust to it, but I don't think there's an awareness at all of what is coming here and the magnitude of it.
So, how do you think, in a world of high GDP growth, but also high unemployment, what does that do to society? And you say people aren't thinking about it now. Can you give concrete examples of how society might organize itself to adapt to such a world?
Yeah. So, I think there's a few things. The first thing that we've done, that we've focused on, and this is not a solution so much as it is a first step, is we have this thing called the Anthropic Economic Index. We've had it for about a year. We've updated it, I think, four or five times now. And what that does is a real-time index that lets you track what our model Claude is being used for. It goes across all the conversations and kind of uses Claude in a privacy-preserving way to statistically query how Claude is being used. What are the tasks it's being used for? To what extent is it automating versus augmenting tasks? What industries is it being used in? How is it diffusing across states in the United States and countries in the world? We've just added more and more detail here. And my view is until we can measure the shape of this economic transition, any policy is going to be blind and misinformed, right? Many policies have gone wrong because they're based on premises that are fundamentally incorrect. So, that's step one.
Step two is I think we need to think very carefully about how do we allow people to adapt, right? People can adapt more quickly, or they can adapt more slowly. This can mean adapting to use the technology within existing jobs. This can mean adapting from one job to another job. For example, I think there are probably going to be more jobs in the physical world and less jobs in the knowledge work economy. Now, maybe eventually robotics makes progress, but I think that's on a slower trajectory. So, that's one. Are there jobs that still really value a human touch? Some of them do, some of them don't. We may find out how important that is in the market and where it's most important. At the level of companies, what are the moats when software becomes cheap and then subsequently the rest of knowledge work becomes cheap? We don't know. We've never quite asked that question. We thought about moats in a certain way. So, there's going to be a huge scramble at the level of companies. So, teaching people to adapt, teaching them what to expect, I think, is the second step.
And the third step is I think there's going to need to be some role for government in a displacement that's this macroeconomically large. I just don't see how it doesn't happen. The pie is going to grow much larger, right? Like, the money is going to be there. Like, the budget may balance without us doing anything because there's so much growth. The issue is distributing it to the right people. And so I think this is probably a time to worry less about disincentivizing growth and worry more about making sure that everyone gets a part of that growth, which I know is the opposite of the prevailing sentiment now, but I think technological reality is about to change in a way that forces our ideas to change.
So, obviously, in your desire to create this greater sense of urgency, are you speaking to people in the administration? I mean, Anthropic hasn't always been the sort of first on the guest list for this administration, but do you have people there that you're talking to?
I have said it to them myself. And, you know, to be clear, there are plenty of things we agree on, right? You know, I think the AI action plan that the administration put out in the middle of this year actually had some very good ideas here. I think we probably agreed with the vast majority of it. But I think most of all, we just want to say these things in public and kind of have a public debate about them, right? We don't control policy. I think the most useful thing we can do is describe to the world what we're seeing and provide data to the world. And then it's left to the public in a democracy to take that data and use it to drive policy. We can't drive policy on our own.
Are you going to be talking to officials while you're here? Have you been along to USA House yet?
I've not been to USA House. You know, I will be talking to officials during my trip to Davos.
Good. So, just to go back to Anthropic then. So, you founded Anthropic specifically because you were worried that you didn't think that OpenAI was taking safety seriously enough. Now, some people say that, you know, the competitive pressures mean that you've gone more hawkish now. I mean, are those competitive pressures, you know, to keep up with China and keep ahead of China and all the rest of it? Do you think they have compromised your safety principles?
So, we've taken a very different route than some of the other players have. I think one of the good choices we made early was to be a company that is focused on enterprise rather than consumer. And I think, you know, it's very hard to fight your own business incentives. It's easier to choose a business model where there's less need to fight your own business incentives. So, you know, I have a lot of worries about consumer AI that it kind of leads to needing to maximize engagement. It leads to slop. You know, we've seen a lot of stuff around ads from some of the other players. Anthropic is not a player that works like that or needs to work like that. We just sell things to businesses and those things directly have value, right? We don't need to monetize a billion free users. We don't need to maximize engagement for a billion free users because we're in some death race with some other large player. And so, I think that has let us think more carefully.
But even with that, we have made sacrifices, you know, we do all these tests on our models that others have not done. Some other players have done them, but I think we've been the most aggressive in, when we run tests that show up concerning behaviors in our model. You know, these things around deception, blackmail, sycophancy that we show in tests and that are present in all of the models. But we make sure to always talk to the public about these things. And we've pioneered the science of mechanistic interpretability for looking inside models. So, have we been perfect? Of course not. I think we've done a generally good job. I mean, you mentioned China. I think that's not about competition. That is about actually the public benefit mission is I'm worried that if autocracies lead in this technology, it will be a bad outcome for every single person in this room.
And what are your specific concern there? Is it about the chips? About sharing data around chips or...
Yeah, well, I think the means of selling the chips, right? That's the thing that I think will have the most impact on who is ahead and who's not. But, you know, the concern, and it's not about any particular country or certainly not the people in any country. It's about a form of government. I am concerned that AI may be uniquely well suited to autocracy and to deepening the repression that we see in autocracies. We already see it in the kind of surveillance state that is possible with these technologies. But if you think of the extent to which AI can make individualized propaganda, can break into any computer system in the world, can surveil everyone in a population, detect dissent everywhere and suppress it, make a huge army of drones that could go after each individual person. It's really scary. It's really scary and we have to stop it.
But again, is that something that you feel governments aren't paying enough attention to?
I think it's fair to say that, you know, obviously, different countries think of themselves as having geopolitical adversaries, but the specific focus on we don't want autocracies to get this powerful technology and we should have targeted policies. Like, we don't need to fight them. Like, we just need to not sell these chips. That, I think there's not enough focus on that.
I want to talk a bit more about Claude because I think it's fair to say it's having a real moment. I mean, we recently reported on how engineers and regular users are getting Claude-pilled. And I just wondered how you feel about the state of the business today versus a year ago.
Yeah, I mean, this is one of these things that's been the growth of the business has been fast but kind of on the same smooth exponential curve as the technology. So, you know, we have this revenue curve that in 2023 went from zero to roughly 100 million, went in 2024 from roughly 100 million to roughly a billion, 2025 went from roughly a billion to roughly 10 billion. Not exactly, these are rounded numbers, but that is roughly it. You know, through that, if you go on Twitter every couple months, it's like, 'Oh my god, Anthropic's changing the world. Oh my god, Anthropic's totally destroyed.' You know, just the excitability of the moment. But we just watch it and we watch this curve. It's fast. It's constantly progressing. It's given us confidence. We never know for sure if it's going to continue. It might not. But that has been empirically what we have observed the whole time.
And then there are these moments where even though the curve is smooth, there's a breakout moment. And so, right now, I think there's a breakout moment around Claude code among developers. You know, this thing about being able to make whole apps and doing things end-to-end. Again, that advanced gradually, but with our most recent model, Opus 4.5, it just kind of reached an inflection point, right? Where the improvement was gradual, but it's just like boiling the frog. You see the gradual improvement and then there's a specific point at which suddenly that's the point people notice.
I think the second thing that has maybe accelerated that further is we looked at Claude code and one of the things we noticed is there were a lot of people inside Anthropic and outside Anthropic who were not technical, but who realized that Claude code could do these incredible agentic tasks for you. It couldn't just write code, it could also organize your to-do list or plan your projects or organize your folders or process a bunch of information and summarize. So, the idea that not just a chatbot but agentic tasks were needed, non-technical people were realizing it and they wanted it so much that they were wrestling with the command line, right? Non-technical people, they have no reason if you're not a programmer. It's such a terrible interface to use if you're not a programmer. But people were going through and using it anyway. And so, I looked at that and I said, 'That looks like unmet demand.' And so, we used Claude code again like 2 weeks to make basically a version with a better UI that's customized for tasks other than code. And we released it and within like a day, most of the metrics on the tape were like four times as much as anything we'd ever released.
So, those are the two moments. I don't know that these are new capabilities, but there was just one of these kind of consensus moments where people got really excited and it's driving adoption really fast. I think people are catching up to what the technology is capable of because it's reached a certain point and because we built interfaces that have made it accessible.
Can you tell us a bit about how you personally, in your life, your family life, use agentic AI?
