The Exchanges

Q flights. Uh, I talked about it, uh, with marketing presentations, uh, and, you know, the week that we're talking, you have a, a new use case out where, um, Claude Cowork can be used for small businesses, including, uh, taking over QuickBooks and doing some bookkeeping. Um, where, where does this go? I mean, what do you think the broad roadmap, where does, where does the broad roadmap take you?

A We're thinking about a few things for quad code and for co-work. There's a few, few big themes. One is improving intelligence, and, you know, I, I think almost all of this is just the model. As the model improves, we can do more and more ambitious work. For coding, it used to be writing a line of code at a time. Now it's building entire features or entire products. For co-work, it used to be, you know, like, you know, it started pretty recently, but it was like, you know, making a document, and now it's things like booking flights, combining many tools, doing, doing your QuickBooks. Um, so this, this frontier is improving and moving just very, very quickly. We're also thinking about how to do longer running tasks. For Cloud Code, we recently shipped this thing called Auto Mode, and Auto Mode is, ah, essentially a replacement for permission prompts. Before, what we used to do is, whenever the model uses a tool, Cloud would ask you, is it ok if I use this tool? And, you know, usually you just say yes, and you get kind of tired of saying yes, kind of over and over.

AI assessment note: “We're thinking about a few things for quad code and for co-work.”

Q a world model, um, a, uh, LLM just doesn't have an understanding of the way that the world works and consequences and stuff. You use co-work to book how many flights, eight flights in hotels? Like, you must think that it has some understanding of consequences, otherwise you wouldn't have given it. Your credit card, which I presume you did. So what do you think about that argument in particular?

A I think from what I've read from folks working on, on a research at Anthropic, it is surprising the degree to which these models are intelligent. Because like you said at the beginning, the, the thing that they fundamentally do is they predict the next token. And so you think like, this is kind of like a stupid thing. Like how can this possibly lead to intelligence? But you know, we, we've actually published a lot of work about how the models are able to plan They're able to actually reason. Um, there was all these, like, very surprising behaviors that you actually wouldn't expect from a model that just predicts the next token. So, I don't know. I, I wouldn't discount it.

AI assessment note: “we've actually published a lot of work about how the models are able to plan”

Q can only take you so far. Here's, uh, Wharton professor Ethan Mollick on it. He says, You will know that the AI labs believe in artificial super intelligence when they disband their newly formed consulting, sorry, forward deployed engineering groups. As long as people are required to figure out how AI is useful and do organizational change and systems integrations, jobs seem pretty safe. What do you think about that?

A Yeah, um, when you look at the kind of engineering that I do, I don't write code. I prompt quad. And actually nowadays, mostly what I'm doing is I have a Claude that prompts other Claude. So I don't even talk to Claude. I have a Claude that's talking to my Claude. And I think in engineering, you've seen just this explosion in the amount of leverage that a single person has. It's about how, how, how big of a business can a person build? How many products can one person support? The leverage that one engineer has now at Anthropic is just insane. And I think we're starting to see this across other disciplines too. So we're starting to see this with the marketers that are, you know, using Claude to do things. We're starting to see this also for forward deployed engineers that are using Claude code to build implementations. We're seeing this for our sales team because, you know, actually at Anthropic, I think like half the go to market team uses Claude code and the other half uses core. You know, I, I think everyone's using all these products. Um, and so the thing that we're seeing is the amount of leverage an individual has goes up. And we are still bottlenecked on the number of good people. And so even if the leverage per person goes up, you still just can't hire enough good people because the demand is so insane. And there's so much more to build. So that's, that's still the bott…

AI assessment note: “even if the leverage per person goes up, you still just can't hire enough”

Q four billion dollars ARR. Uh, that seems quite right now. The numbers right now say maybe it's forty-five billion, right? So a 10 X there, 80 X demand, and the question is how fast the company Uh, conserve the demand here. But talk about the portion of demand that Claude Code makes up and what you've seen in terms of demand growth and the amount of people using this thing.

A For an increasing number of people in the world, I think the way that you use agents and the way that you use AI, it's not just Anthropic products, but it's Cloud Code in particular. And, you know, of course for Anthropic, there's a lot of different products. There's, you know, there's Cloud Code, there's Cloud AI Chat, there's Cloud Design, there's, there's Co-Work, there's like the API products. There's a lot of ways to experience Anthropic. Um, but for a lot of people, Cloud Code is their first introduction. And yeah, the growth has just been insane. It's, you know, when we first released it internally, It just skyrocketed immediately, and so before we even released Cloud Code to anyone outside of Anthropic, we felt that it's pretty likely that this is going to be a hit, and around the time that we released, uh, Opus Four and Sonnet Four, this was in May of last year, the growth just went exponential, and I've just never seen growth this deep, and then it just kept going more and more exponential with, uh, with Opus Five, that was November, and then 4.6, that was February of this year, and then 4.7. It just keeps inflecting over and over. And, you know, there's a lot of people on our team that have worked in tech for a long time. And, you know, we worked on all sorts of hyper growth products. Like, this is something you talk about in tech all the time. These, like, you know,…

AI assessment note: “the growth has just been insane. It's, you know, when we first released it”

Q be like a company, like a consulting group, for instance, putting it into action at a bank, and the bank using it to summarize some calculations. I'm just throwing an example out there. Um, that compared to the Cloud Chatbot, it was far and away, the API. Was the lion's share of usage, revenue, all these things. Um, does that still the case today, or is Cloud Code overtaking that?

A We have a mix. So, you know, like, products play a much bigger role for Anthropic than they did a year ago. That's, that's definitely the case. Uh, product growth is accelerating. It's growing very quickly. API is also accelerating and growing very quickly. And for us, we are investing in both. We have to be a product company because there's kind of a lot of reasons for lab to build products. And, you know, this actually wasn't clear early on. Like, very early on in Anthropics history, this is before I joined, this was actually like an active debate. Should we even build products? Like, is this actually like a useful thing to do? And it turns out it's very useful, um, you know, for mindshare, but then also for safety. Um, fundamentally, we exist to study AI safety. This gives us better tools to do that. We're also a small number of people, and so most things in the world we will not build.

AI assessment note: “We have a mix. So, you know, like, products play a much bigger role”

Q can, um, fact check me on this. You're gonna have an agent in your messaging apps that's going to let you know when your friends have messaged you. I know you use cloud code on your iPhone a lot, right? So then you will just see the notification and you'll speak back to people. All your communication could potentially be centralized in these as long as the companies play ball.

A Yeah, I mean, it could be kind of the agent in the end, but how, how does the communication actually happen? So like, you know, for example, if you look at a messaging app like a, you know, like Signal, there's a protocol that it uses to communicate. And, you know, I can build an app, it can maybe use that same protocol, but I think it actually can't message other people that are on Signal. But yeah, like, I can have an agent that uses my app to do, to do that messaging using an existing app that, that supports this. Yeah. So, yeah, it's not obvious how it's going to play out. I think today people use a mix of, you know, apps and, and agents. Um, but, you know, I, I do fundamentally think that a lot of these modes are actually still gonna increase in value over time. You can think of another example, let's say, you know, like a TSMC or some kind of like chip manufacturer. If you think about, um, the amount of work that they put into making a process, and in making a process where the costs go down with scale, This is a fundamental economic force, and there's a lot of companies that, that, that do this kind of thing where, you know, especially in manufacturing, where with scale the cost goes down. With tech companies, this is the case for infrastructure. So if you build a really great infrastructure, you can support more users, and the marginal cost per user goes down over time.…

AI assessment note: “it could be kind of the agent in the end, but how, how does the communication actually happen?”