Economic Moats and Future Outlook

Let's talk with Cloud Codehead Boris Turnney about the product's explosive growth. What's next on the roadmap and whether all of this is sustainable? That's coming up. Right after this. In the face of ongoing disruption and opportunity, TMT leaders need to deliver tangible results, not just ideas. When pace and performance matter most, PWC combines market insights and deep sector experience with AI, cloud, and emerging tech to accelerate your transformation and drive measurable ROI from strategy to execution PWC can help you anticipate what's next, outpace disruption, and compete. For more information, visit pwc. com Welcome to Big Technology Podcast, a show for cool headed and nuanced conversation of the tech world and beyond. We have a great show for you today Claud Code Head Boris Tourney is here with us in stududio. We're going to talk all about the product, the way it's taken off, what's next on the roadmap, and of course, whether it's sustainable We go into things like token maxing token inefficiency, and then of course, the future of knowledge work. So no lack of topics to cover. Bis, it's so great to see you. Welcome to the show Thanks for having me So let's talk a little bit to begin with about the growth of Cloud code been massive, right? I think at a recent event, Dara Amadee, the CEO of Anthropic talked about how demand for Anthropics' products has been up like eighty times year over year. I remember speaking with him Last year around this time and he was thrilled that anthropic was at four billion dollars ARR, That seems quite right now. The numbers right now say maybe it's forty five billion.. So a ten X there, eighty X demand. And the question is how fast a company conserve the demand here. But talk about the portion of demand that Cl code makes up and what you've seen in terms of demand growth and the amount of people using this thing 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 quad code in particular And you know, of course phanthropic, there's a lot of different products. There's you know, there's Qad code, there's quQad i chat, there's quQad Design, there's There's cowork, there's like API products. There's a lot of ways to experience some topic. But for a lot of people, Qlaad 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 before we even release Qadcoat to anyone outsideanthropic We felt that it's pretty likely that this was going to be a hit. And around the time that we released Opus four and Sonet 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 With Opus four point five, that was November and then four point six, that was February of this year and then four point seven He 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 hypergrowth products. likeike this is something you talk about in tech all the time. theseese like, you don know quarants and hypergrowth, but even on the team, We've never seen growth like this. h and so we're we're just trying to figure out how do we how do we make it so Everyone can continue to experience this How do we make it so we can continue growing at this pace and the pace that we expect in the future, which might be even steeper than it is today? And we're learning a lot how to do this and how to keep scaling the services. So a year ago it was clear that the bulk of usage of anthropics AI models was happening through the API, right? That would 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 that compared to the cllaod chatbot, it was far and away the API was the lion's share of usage, revenue, all these things Do that still the case today or is Claudd Code overtaking that We have a mix. So you know, like products play a much bigger role phanthropic than they did a year ago. That's definitely the case. h productro 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 a 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 shouldhould we even build products? Like is this actually a useful thing to do? And it turns out it's very useful, you know for mind share, but then also for safety U 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 Right. And so this is why we also have to provide a platform. and we have managed agents and API and SDK, all of these products. So People can build on top and you know, thousands and thousands of businesses to do that. Yeah. it's interesting to hear you even answer the question saying that it's a mix I take it, you're not going to share which is bigger right now. Maybe not right now.. But the fact that like it's not a clear cut, the API is bigger Um Maybe it is, but the fact that you even say it's a mix just shows the The fact that anthropics owned and operated products are just growing massively. And now so you knowve that we've set the stage here that this is thing something that's growing exponentially We've obviously we obviously have seen the anthropic revenue grow exponentially Kind of alongside this product, this is a product that you conceived of and built and run today I think that there's probably some people watching who are like, well, what is Clad code? Um Most of our viewers obviously know what it is. And I was like, how do I write this like in a simple one sentence definition? And I wrote that it's a way to build websites and software play in English and then on the way over here, I was like, well that kind of sells it short a little bit. I mean, what would you describe it as M I think that's actually a pretty good description. It's all right, we'll take it. I think when a lot of people think about AI, they think about chatbots. And you know, for engineers, that's what AI was. maybe like a year and a half ago before we started quQad code That's what IIe was for most people And we realized at some point that the model is actually getting really good at coding and it's getting really good at using tools. And these are things that we've kind of always trained the model to do. And you know, this has kind of been the research direction for a while It started to become commercially useful about a year and a half ago And so for Claud code we took this bet and We deviated from the way that everyone wrote code at the time Because the way that everyone in the world wrote code was using essentially a fancy text editor in We just thought maybe we can do much better than this and we could do something really, really different than what's been done before is very much a bet. And so we introduced, you know quQad code. and the thing that made Qad code different from chat bots at the time was goode can use tools And this is it. this is just the difference. It's with a chatbot, you're going back and forth and you're talking, but an agent and Cloudcode is an agent, it can use your tools. Right. And could we just quickly define the tools? So tools could be anything, and you tell me if I'm wrong from using a browser So like logging into Cloud Flare and then setting up some agents that way, right? So it becomes less of what does this product do itself and more of like, what can this product log into and then sort of do with a multiplicity of products. Yeah. on mine. That's right. It can it connect all your different tools. It can use your browser, it can use your computer Even something as simple as like editing a file on your computer You know, like a year and a half ago, there was no AI product that could actually do that This is the first thing that CQad Code was able to do. It could edit a file on your desktop If you have a bunch of files on your desktop, it can organize them. And so like quQuad code and cork have this access if you choose to give it granted. Yeah. and you know, it can do this. And this is magical. It's this tiny difference. completely changes the way that people can use this product and it totally changes what this product can do for you Yeah, I mean, the fundamental thing, I think, just to drill down here is that I'm It seems like AI has shifted from sort of like As great at auto compleomplete, right? Because at the fundamental layer, AI is just predicting what comes next you know if you're using machine learning and applying it on a large datas set, predicting whether you might default on your mortgage and whether a bank should grant a mortgage. When it comes to a sentence, predicting the next word Code the next bit of code in the sequence, right? So I think that was G one But what you're talking about now is The machine is actually just able to go And after you give it this natural language prompt ode itself, hook into tools and then do things for you. And so correct me if I'm wrong, but the use cases here have gone from deevelopers hooking into it and writing code with cloud code. And we've seen this explosion, I guess, largely driven by them But then by a secondary force, by non technical folks peopleople like me who can build software by directing AI agent, which is Cloud code to build a piece of workflow software for them or a website, or to take control of your computer via something like Cloud Cowork, which is sort of the mayaybe I would call it the easier sister product and saying Well, you have access to my u to my browser now You know what type of flights I like to book? I need to be in India in a couple of weeks, book the flight. Yeah Yeah, exactly. I actually just used Cowork to book a bunch of flights. I'm going to be flying a bunch this month for, you know, we have a code with Claude coming up in London and Tokyo to some other stops along the way And I went back and forth with coork and I was like, okay, I need to be in these in these places at this time And it was five stops. It was like a lot of cities And here's roughly the schedule U Look through my email, look through my calendar and just double check it Make sure I'm not missing anything It found actually two stops that I was missing And also a couple dates that I told it wrong And I just found this by looking at my email after, you know, I asked it to do that. And then I told her to book the flights. And I went and, you know, was coding on something and was I was just doing work And I came back an hour later and it booked eight flights and five hotels. And one of the hotels was kind of incorrect. It was in the wrong area. I asked her to rebook it and change it and it was done other than I actually, this is something that I try every time with cowork and with quQad code these sort of like test cases So these sort of like a common thing that I would do, and I just retry it with different models and you know, as the model improves. This are the best result I've ever gotten And there's something about co workork combined with Ous four point seven. where it's able to do this. and I think one of the hardest things for me has been As the model improves, you constantly have to readjust your expectations of what it can do. And if you talk to people, especially engineers that used the model a year ago They might and they didn't use it since They might say something like Oh, well, you know, it's not very good at coding. and you know, I don't trust it to write more than a few lines at a time at a time because That's what the modotel was a year ago. It wasn't very good yet And if you fast forward to today and you sit down these people and you know, they try the new model and as like a lot of people have been doing an increasing number of engineers It's just a completely different experience, the capability is completely different And I think this is the first technology I've used like this where every month. There's a step change in what it can do And as a user of this technology, it's just quite hard because you have to kind of keep retraining. You have to keep retrying You always need this like beginner mindset to retry the technology and use it for a thing it was not good at before because the next model might just do perfectly. And so I think this is the vision, the way that you're outlining it is effectively previously, when you would use technology, you would be subject to the interface You would have a software company that' built for scale but you get a lot of features that may be more in applicable to you you would have to go through all these bells and whistles whenever you were trying to book something, even though you knew what you wanted and you wouldn't have a website that would know your preferences. Now it sort of shifts the paradigm where you have Again, it's an agent, It's something that goes out and does things for you. and can potentially shape your experience online the way that you want it Ands that is, I think what people are seizing upon. And that's why we're seeing why you're seeing really the explosive growth. But now I want to pressure test the thesis a little bit and u bring up some things that make me curious how much of this is real uh, and how much of this is just unbridled enthusiasm at the potential. maybe stuff we should have a reality check on And the first thing is that There is such great demand question is how much of that demand is pure demand versus Dm manand that's gamified And there is a practice that's going on within Silicon Valley and outside of it. token maxing Im sure you've heard of it It's where companies are have a mandate where people are supposed to use lots of AI tokens by running their AI agents as much as they can and then those who run the you know, use the most tokens are like rewarded leader on a leaderboard or meet a goal of AI actions that they have to take as opposed to physical actions So I want to hear your perspective on token maxing and whether you think that makes up a large portion of the usage of the products that you're building. Yeah, I don't think token maxing is a large percent. The way that I would think about it is You know, before Anthropic, actually, I used to work at a big tech company You learn Facebook. I was Facebook, which is one of the companies that's token maxing for. That's right That's right. Yeah. And one of my responsibilities was the health of all of the code Cross you know, the across metass apps. So this is like Facebook, Instagram, you know, whatsApp? And one of the reasons that we care about the health of the code, and this is essentially things like code quality is if the code is really high quality, engineers are more productive And there's like a big team of people that worked on productivity And before models, before Claud You would work for a really long time and you would see maybe like a one to three percent improvement in productivity per engineer Over the course of a year something like that And that was like a pretty big improvement And it was like very hard won Yeah since you had to try a lot of ideas And eventually you find something that improves productivity like this And what happened with Claude is now Many companies, including Anthropic and all of our biggest customers are reporting gains on the order of hundreds of percentage points And I think the last number that we reported is the amount of code written per engineer at anthropic has grown something like two hundred and fifty percent since we introduced quad code And this is with while keeping code quality and reliability and all these things kind of stable. So without those things regressing, the volume of code has grown a lot And so u This kind of productivity imp fact, I think is just like very new And I think people are trying to figure out how do we get this? There's a lot of companies asking, like, how do how do we get these kind of benefits? because a lot of companies are seeing it And then some are still figuring it out. And I think my advice is almost always the same The first thing is just give everyone tokens, let people experiment. I wouldn't necessarily recommend token vaxing. but I would recommend let people experiment so they don't have to ask for approval for every token. The second thing is give people psychological safety Because a lot of times when people are innovating and they're building tools that make them more productive they're changing their own worklos to make them more productive They try a bunch of ideas, some of them might not work, and then some of them work So you want to give people this kind of psychological safety so they feel okay experimenting with it and finding these new processes. And then, um The thing that a lot of companies see is that productivity improvements and the innovations do not come from the people you expect. Back in the old days, you know everyone could point out like these are my most productive engineers. But I think nowadays, a lot of the improvements are coming from people who you just never would expect. It could be like an accountant somewhere in the corner of your org that just automates accounting in a way that no engineer would have thought of It could be some marketer automating like marketing in a way that you never would have thought of. It could have been like a new grad. software engineer that just builds something amazing. And this is something that just like didn't happen before. The challenge is you can't identify these engineers and these people ahead of time You don't know who they are And it's almost always going to surprise you. And so the thing you want to do is let people experiment, give them safety And then once there's some kind of use case that scales up That's when you think about optimizing it. But you don't want to optimize ahead of time. So I don't know if Doing it in a competitive way works for some companies with their culture Um, then I think that's great If for other companies, the way they want to do it is just kind of create safety and create space for engineers to experiment, which is what we do at Anthropic then I think that's great too. It really depends on the company Yeah. And I'll say look, I use a lot of tokens I'm in the tools all the time. I think Cloud Code and Cloud Cork have both been pretty great for My business, I'm a solo operator, although that kind of sells it short because I have a team of people behind me that help me U mostostly on a part time basis, but That's for a different show. but I do wonder, you know, when I read these stories The large corporations are largely making up big percentages of these budgets And the incentives, you know, and again, like I started the show saying, how sustainable is this The incentives are bad in some of these places. This is from the Financial Times recently Amazon staff use AI tool for unnecessary tasks to inflate usage scores. Some employees said colleagues were using the software to automate additional unnecessary AI activity increase their consumption of tokens They said the move reflected pressure to adopt the technology after Amazon introduced targets for more than eighty percent of developers to use AI each week. got check this with an Amazon employee. they're like, Yp This is what's happening. They told me I triggered an autobation that runs for hours and then gets deleted every day in order to meet these targets So You said you don't think that this token maxing stuff is a big part of demand Is there anything that you can see on your end to indicate that it's not that this is an outlier and not the rule in most places Yeah, this is, I don't know how many companies are doing this token maxing thing. I've heard of it as a trend, you know a little bit. If you look at Quad Codes customers we have just many, many, many customers Um, so it's not like, uh, you know, there's like one company driving the usage. It it's not like I do want to kind of step back a little bit and just think about like how does this kind of change happen Because I think the goal of what these companies are trying to do, I don't want to speak for them and I would recommend just talking to them. Yeah, but the goal of what they're trying to do, I think, is probably like organizational change and business process change. How do you make it to your company benefits from AI And this is often unclear It's very dependent on the company because every company has a different business a different culture, a different org, a different way of doing things. There's this old Harvard Business review article from the nineties which I just love. and I forget the title, but it was something like Computers are here, why is no one seeing the productivity impact And this was a big question R? It's like, to us it's obvious computers make us more productive. This is just incredibly obvious today But in the nineties, this was not obvious And what was happening is personal computers were being adopted They were replacing main frrames And now they're affordable. So the average company, the average startup can buy one You don't have to spend, you know, millions of dollars on a mainfame anymore But there was this challenge and there was this paradox. Companies were adopting it But they were not seeing productiv improvement What's going on And so this Harvard Business Review article, it made the case that in order to get benefit from computers You have to restructure your product your whole business process around computers. They have to be at the center of the way that you do things And if you still have like paper you know filing cabinets and you have a bunch of drawers full of stuff and it's still a paper and pen kind of physical process And there's a computer somewhere on the periphery you're really not going to benefit If you throw away your filing cabinets, you throw away your you know, desk drawers full of you know papers and you put a computer at the center of it And that's the way that you do all your business process, then you benefit And there was the split between companies. Some were doing this and they were doing this very painful change and they benefited from it and then others didn't And I think it's kind of the same thing now A lot of companies are trying to figure out how to benefit from the productivity impacts of AI. And there's just a lot of experimentation and everyone is trying different approaches to figure out how to benefit from it. I don't think there's one right approach Okay And u Look, I think that When we see something grow as fast as Coud code has grown and asast as fast as Anthropic has grown It's good to just kind of talk this stuff through and it's good to hear your perspective. So okay, that's token maxing. Now, tokens, of course, are the output of the model, like the words or portions of words that the model outputs and the words and portions of words that go into it, right? And that is how these companies charge and the more you have The more dat centers you need, etcetera, etcer Um You know As these models get better, they they haven't and well, Let me put it to you this way. Sometimes I wonder whether they're as efficient as they can be. these big models can sometimes do a lot of work use a lot of tokens, even if the output is great Uh people wonder, well, is this sort of just driving up token demand where it could have been a really easy process. And and the models are expending many, many tokens and not getting there as efficiently as they could. Let me give you an example I've been using Claouud Cowork to make PowerPoint presentations It's really good at it. And I've been using the OPS four point seven model And a couple of times I've said All right, you know, you're working on this this ship it as a PDF And u, It just starts to lose its mind, It cycles and it uses as many tools as it possibly can. and you know it just seems unable to ship the PDF and And eventually I kept telling it, No, you're making this powerowerPoint. You know where it is. ship. And it goes I owe you an apology I went down a rabbit hole, worrying about a constraint that wasn't actually blocking us files there. And then it shipped it I mean, talk a little bit about the efficiency of these models. Um, and whether that is a legitimate worry that you know, as we've seen the growth Part of it is these like loops that a model like Opus four point seven might find itself in do basic tasks Yeah, genererally when we think about models, there's a few different aspects of it One is just how intelligent is it Another one is how fast it is and another one is how efficient it is We generally try to move all these together betweenween these I think we should probably optimize for intelligence. That's the most important thing. So even if it's like a little bit less efficient. but it's more intelligent and it lets you do more things, that's really useful because the efficiency optimization comes after After we make it more intelligent, then we can make it more efficient. So it's sort of kind of We do one then then we do the other We've been experimenting a lot with like how exactly we give people control over this because we don't always know the right default Sometimes like when you're using it, you know better, you know better. Um, And so one mechanism that we had for this is picking a model So you can pick, you know, Ous or Sonnet or Haiku. Another mechanism that we've been experimenting with isopus is like the biggest sonet middle, Hiku, smallest. That's right right. That's right That's right. And this is just like the size of the model. R And then there's effort. And effort is essentially how, you know, I think the word is actually really descriptive. It's how much effort do you want to put into it And you can set this. We have a recommended effort So, you know, for example, to maximize intelligence for Ous four point seven, You want to use extra high or maximum effort. But if you want it to use less tokens, you can think like medium or low effort. And this is a control that you have I talked about this on the show recently and we had a commenter that came in. And I was of the opinion that this will these you know bigger models will find a way to become more efficient on like the export, the PDF thing. We had a commenter come in that wrote, Alex, they can't fix things like that PDF problem. It's inherent to LM technology and it's the biggest barrier to useful widespread dissemination and usage of agentic AI. I think I'm going to try to translate that What they were trying to say is we talked about predictions earlier that this is all probabilistic. It's sort of predicting the next word. You don't get the same Answer from an AI agent twice And so therefore, this type of thing is a feature of the way that they work and not fixable What do you think I don't think that wass right When you think about like, okay, let's oom out a little bit. Yeah. So engineers are the first adopters, right? Like engineers started using Qot code like a year and a half ago And you know, this is before non engineers were using agents in a meaningful way. This is, you, before cor and so on If I think back to what Cot code was a year and a half ago. He wasn't very good I could use it to write a little bit of code, but if I really trust it to build an entire feature or entire product It wouldn't turn out well It did the same thing, like it would go in spirals and the quality wasn't good or you know it built it and either the code was bad or it didn't work And at some point he just started to get better And as the model improved and as Qat code improved, The result just got better and better and better And so you fast forward to today Qad code is a hundred percent written by quad code Corework is a one hundred percent written by quQad code An increasing number of features are fully written by Qadcot across anthropic and products And this is something that we hear from customers also. I did a I did a talk at Y Combinator, you know, the the the the startu incubator yesterday And I asked people to raise their hands, you know everyone's using quQad code and I asked them, you know, raise your hand if one hundred percent of your code is written using Qad code today. About half the hands went up. And then you know, I ask people, raaise your hand if zero percent of your code is, you know writt written with AI. there's like one hand th. And this is room of like a few hundred people. power to that person, whatever. And you know, there's still room for this, obviously And then everyone else was somewhere in the middle. You know, it's like most of their cod is written with quad code but not all ofib But that's kind of the place where the moto is at today It was not there a year ago. a year ago, it was not good enough for this And so this is exactly what you're saying playay out with Cowork right now It's still early You know, we were at we stood Well, like a a few months ago Um it's it's going to keep improving. It's going to keep getting better as the product gets better as the model gets better, but this early days. I think still Everyone using Cork today is an early adopter, everyveryone even using AI today is an early adopter. There are so many people in the world and most people have not tried AI in a meaningful sense U So there's just like, there's a lot more room to improve this Yeah, we're hosting an event here in San Francisco on june eighteenth and a lot of the marketing material I've turned out with Cowork. Now I go back and forth, I don't let it one shot it, so I'm looking at the copy But I do things like, you know, upload are are you know download statistics to sort of show the growth of the podcast and I give it the names of the speakers and it like is amazing at saying builduilding a perspective. Here's what the event's going to be, here's who's going to be in the audience. Here's who's speaking, Here's where you should be there. Here's how to get in touch. inssane. It's so good What was your what was your feeling like the first time that they used it and the first time that you saw like the agents use your tools Well, I mean, obviously I've sort of enabled everything. And I think this is kind of an experience that many people have had where there's a browser extension for Claud and you realize that you can only get the benefit of this or you'll get the most benefit by letting Claud take over your browser and do things for you. Um And the experience is kind of it's almost the same as I had with the WMo. where those first couple turns, I was like white knuckling and like watching them like, shouldh I approve reading everything? And then you start to trust it a little bit and you just hit approve, approve, approve, right? And the way of, the same thing, you're like, okay, this looks like it's not going to kill me. And then five minutes later, you're on your phone as the AI does the work And that was my experience with code and cork. Yeah it's like sort of track. I mean, this is like my experience too. It's like I think it's like any technology. I was watching someone that's it's like a friend that's been learning to use cowork over time. and like, you know, she's not an engineer And there's this use case the other day like her there was like a language input on the computer where you can kind of choose between languages on a laptop and there was some issue with it. and she couldn' figure out how to fix it And so before what you would have done is go to Google and ask like, hey, how do I fix this you know, this issue that I'm having at my computer? And this time she just like asked cow workk. And a corper was like, cool, let me take a look. can I use your computer And she said, yes, and it took over the computer And I guess this kind of like orange glow and you get to watch as cowork open settings and it sees what's going on with a language picker and it diagnoses it and it fixes it And, you know, you're still in the driver's seat So you can see this happening, you can monitor it. It's not happening in the background or anything. Yeah, but it's just it's magical. I actually did like my instinct was toop in Google And so it's funny that like For free She went to using cowork for this And this is actually something I feel all the time. I think for people that have kind of grown up with these products and they've seen previous versions, they might not be as ambitious as they could But for people that are new to the products, I often see them using quQad code and codork for things that I wouldn't have even thought of and it's just like amazing. It's so creative and I learn a lot every time I see it. Yeah Now the biggest drawback right now, I would say, and I've seen you reply to people on X about this U, is the rate limits. like When I see people say, I've given Cloud code a shot, but I'm kind of done with it. It's typically because They've hit their token allotment and it only works for like an hour for them And then they have to wait four to use it again and they look for alternatives. Um What do you think the rate limits have done to the ability for your product to grow And what is the plan, if there is one? to make people be able to use this without those rate limits There's this is something we're actively working on The reality is a very small percent of people actually hit their rate limits which is surprisingice For pro users, it's a little bit higher. for Max, it's actually quite low And I think the thing that you're saying when people talk about it is Um there's a couple of things happening One is that we actually reduce the peak rate limits and that's now rolled back And we've actually doubled rate limits So we're giving people more real limits But there was a brief period where we reduced them And so people were running into that The second thing that's happening is cloud code is actually quite extensible And so people can use plugins, they can use all sorts of integrations and some of these use tokens in a pretty inefficient way And so the thing that we've been working on is surfacing this to you So users can decide Do you want to use this plugin or do you not So you can see kind of what percentage of your tokens goes to it And then I think the third thing is there's a lot of people that have just increasingly become power users. like The first when we released Cot code, you, you ran one clot at a time Nowadays, I'm running, you know, like, On my computer, I run maybe five at a time. and then every night I run like, you know, not every night, but most nights, I run like hundreds of quads at a time. all parel Yeah hundreds, sometimes thousands And this is something that I just like wouldn't have imagined a year ago And obviously this uses a lot of tokens And there's a lot of people that are figuring out these new workflows that are using a lot more tokens and this is sort of like at the edge of what you can do with a Max plan Um And, you know, this is why you can just like pay using API also. so if you just want to have as many tokens as you need You can do this too. And this is what a lot of enterprises do Now it wasn't long ago where I'm pretty sure Dario Anthropics CEO was referring to open AI and talking about the spending on the buildout And he and he's talked about this afterwards, he said, I'm trying to be disciplined in the way I spend, which is still spending many billions of dollars on data centers to enable this stuff like you're talking about, and others, which we think is open AI, are yoloing Um, Now openpAI is doing this too with Codex And You could call it yoloing, but they have a lot of data center capacity that they've built. U How do you think about that? Because you know when people do hit these rate limits, They may just go over to Codex Um pretty intense competition. so How do you think about that? How does anthropic think about that internally that, you know But at least from the outside perception is that Um, this added discipline on data center buildouts might end up losing users in the most important product battle that your two companies are engaged in Yeah, so, you know, first of all, our growth has never been faster than it is today Um So, you know, for Qad code, the growth is accelerating And I think because most people don't actually hit rate limits very often Um, it's, u uh it's actually not not a huge issue For the people that are, we are laser focused on improving the experience And so we doubled the five rate limits We are announcing today that we're increasing the weekly rate limits And of course, we announced the new Colossus capacity, which, you know, we brought online to serve all these new users. Via Eon Musk. Via Elan. Yeah, because this I mean, this growth is just no one, no one would have predicted this. This was beyond our wildest Forecast m And so, you know, I think for us what matters the most is We need to serve our users. We want to make sure our users are really happy. U and we're doing everything we can to make that happen Are you surprised by Codex How do you view them as a competitor I think there's always, you know, there's always copycats, there's always competitors. Um For me, it's flattering And I think it just forces everyone to do better U So, you know, I for me, the thing that I care about the most is just doing the best job that we can to serve our users. And we encourage everyone on the team to, you know, talk to users every day And, you know, just make keep making the product a little bit better every day So this is what I care about the most Um I want to take a break, but we have so much more to cover. I want to talk about how this extends beyond code, the future of the chatbot And then maybe talk a little bit about I mean, I could go through our agenda. 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Listeners of this shel will get a seventy five dollars sponsored job credit at indeed dot com slash podcast That's indndeed. com slash podcast. Terms and conditions apppply. Need a hiring hero? This is a job for indeed sponsored jobs. And we're back here on Big teechnology podcast with Boris Turnney the He head of Cloud Code at Anthropic For us. It's great having you here Uike I said, I'm in your product daily, so it's really fun to speak with you about it U We talked a little bit about this, but I think one thing we should highlight is that this is really going to extend Beyond the Chapa, we talked about booking flights I talked about it with marketing presentations , you know, the week that we're talking, you have a new use case out where, um Cork can be used for small businesses, including taking over quick books and doing some bookkeeping Um, Where does this go? I mean, what do you think the broad roadmap Where does where does the broad roadmap take you? We're thinking about a few things for quad code and for c workk. There's a few big themes. One is improving intelligence. And you know 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 cowork, 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 your QickBooks 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 modode and auto modode is essentially a replacement for permission prompts Before what we used to do is whenever the model uses a tool Claude would ask you is it okay if I use this tool? And you know usually you just say yes, and you get kind of tired of saying yes, gota over it over. Always allow. That's the button to hit. That's right, That's right. But it's actually very important for security that you're very thoughtful about this And the thing that we're realizing is actually instead of being thoughtful about, you know, every prompt, because we're showing people So many of these dialogues, they just kind of got fatigued And they would just say yes or, you know, always allow And so auto mode is the answer And this is a new way of routing these tool calls and the way that it works is Whenever Cloud wants to use a tool It asks another quad Is it safe to use this tool Ifat has some of the contexts, it doesn't have all the context. And there's also a number of layers of safety checks And we spent months iterating on this to make it really safe There's thousands of different benchmarks and evails that we use to make sure that this is safe And essentially we found both in the laboratory setting and now we're finding in the wild. This is safer than what we had before So as a user, it's a really nice benefit because you don't have to sit there and say yes over and over And actually the result is better Because if there's one unsafe command buried somewhere in this big list of things that Quad asks you to do You might have accidentally said yes. But actually if you ask a second claod using auto mode It's not going to say yes So this is kind of one big investment Um Maybe the third big one is just running more quad and parable One of the cool things about Quad and this is something that we started to see pretty early with Quad code users is Actually very few people nowadays run one quad code at a time. Most people run many, many quad codes, you know ranging from a few to thousands And with COork, we're starting to see the same exact thing As you get more comfortable letting cork run, you start a task and then you start a second task and you move on and just do more in parallel And I think there's just a lot of opportunity to make this experience very nice and to make it more obvious for people How do you do this? When do you do it And and it probably extends. to the way that you use a chatbot, right? And it's interesting because anthropics had this kind of interesting relationship with the chatbot started out as technology first, decided to build the chatbot Claude and then just kind kind of moved more towards enterprise, like you looked at all the charts And Um and Claude was always at the bottom But now you're seeing Claudd's usage rise And I've a to check this by you, that the future of the chatbot is is not like I'm going to give you a question and you'll give me answer. I will give you a question or you know, talk to you about a problem and you the chat bot will then suuggest some sort of action you can take on my behalf. Like right now I'm talking a lot about trip to India. And what I think I'm going to get back in the future is this thing being like like what you said, not having this like secondary step between having to go there and and book the flights, a more proactive chatbot that's going to say Okay, let take let me take care of this for you. Is that the right direction? Like am I thinking about that? I could say that. I could say that. yeah. Are you working on it? Agents are the future and you know, we're trying all these different experiments. Okay. There's some stuff that we're trying that's like this. Yeah. Um But there is a limit here, right to what this can do A funny way people have talked about the limits of the thousands of clds that you can run in parallel is kind of looking at who Anthropic is hiring. My favorite job listing on the Anthropic site is that you're hiring salesforce administrators you're also hiring consultants to help enterprises deploy this technology And many are viewing that as like a sort of tacit admission that This stuff can only take you so far. Here's Wharton prorofessor Ethan Mollk on it. He says You will know that the AI labs believe in artificial superintelligence 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 on that Yeah. Um When you look at the kind of engineering that I do. I don't write code I prompt Qad And actually nowadays, mostly what I'm doing is I have a clod that prompts other clods So I don't even talk to Claud. I have a claud that's talking to my clauds 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 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 marketers that are using Claud to do things We're starting to see this also forward deployed engineers that are using cld code to build implementations We're seeing this for our sales team because You know, actually atanthrop, I think like half the go to market team uses squad codat And the other half uses core, you know, I think everyone's using all these products Um, And so the thing 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 still the bottleneck for us I would say like Pople peopleeople would argue that if this stuff was so powerful you could say, take a look at the way my sales organizations operates and then configure Salesforce that way with a prompt Is this and another people, another example people give is Um, believe that Anthropic has very powerful AI if they let it handle the the IPO paperwork and don't hire an investment bank. Are these unfair tests Well, we're starting to see there's one person the Tableos using Quad to do their taxes you know, I would not necessarily recommend this, but I'll admit I've run my taxes through Claud and compared it against my accountant and it was pretty close. Yeah. I did the same thing. Folks, not not saying you should do that, but it is It's an interesting use case. That's right. But I think fundamentally, what people are missing in this conversation is In the end, it's a person that has to talk to Claude to ask Claud to do this thing So even if Salesforce is automatically configured and you know, it's not a person pressing all the buttons, it's cllawd doing it Someone has to askQad to do that And if you have to configure Salesforce in a bunch of different ways, it could actually be a full time job to askQad to do this And at some point, Claude is going to become really good at asking Claude to do this And that person is going to be asking Claud that askks Claude to do this And this chain would just keep getting deeper. But in the end you still need people. that are piloting this But maybe their job is just asking one question then in the future. Yeah, but imagine how much effage that has asking the right question That's true It's a good point Uh So You know, we talked about Salesforce, so we have to talk about the S apocalypse. you have some interesting views on the type of software companies that will be safe as we get more automated programming and those that might be in trouble. And you talked you've talked previously about the different moes that exist and which modes are more important and which modes are less important. Can you just share that briefly, know while we're talking about it? There's this really good framework called the Seven Powers for talking about modes and business. know There's so many of these frameworks for this, but this is my favorite I actually studied economics in school. I didn't study computer science. So this is still kind of the way that I think is in terms of these kind of frameworks. There's a lot of these different modes in business. and some companies have one mode, some have a few modes you know, they they have like a portfolio of modes uh, There's a bunch of these modes. So like one is scale economies. So as you scale up your production, then there's increasing returns to scale Another one is network effects. So this is like a you know, like a messaging app or something like that. The more people that are on it, the more valuable it is for any person Another one is switching costs. there's another one that's process power I think most of these modes are still going to matter And relatively, some are going to increase in importance over the next year and some are going to decrease in importance One that I think will increase in importance is something like network effects becausecause it doesn't matter who's writing the code It doesn't matter if it's an agent at the core of your product or something else or if there's intelligence in your product If there's a network effect in your product, that's still going to matter Some modes get less important, and this is for example, switching costs because if you want to switch from vendor A to vendor B, you can you know you can just askQad to do that InQata is going to get better and better over time out it And so I think as a company, a thing that you should be thinking about is What are your modes? And I think a lot of the largest companies just have many, many modes. It's not just one thing because the way you get to a scale and the way you build a defensible business over time is you accumulate these modes, you need a number of them Yeah, I would just think what's going to be more valuable in your and what's less valuable I think that When you think about these different software companies, though, if you're using code do the mod all modot kind of blend away because you could potentially be in this like one app that is interfacing with all software, which means therefore There's really only one software company Yeah, I mean, there's just like a lot of ways that this could play out I think something like this is possible, but it seems a little farfetched to me because if I think about, for example, like Let's say I'm using a messaging app, how do I decide which app to use I use the app that my friends are on that I can reach so it doesn't matter if I can build a really awesome app for myself, which I can do today. Like I can build a great messaging app with Quadcode in like a few hours It's still not useful because he can't talk to my friends. But this is the example exactly. you'll have you can You can fact check me on this. You're going to 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 is as long as the companies play ball Yeah, I mean it could be kind of the agent in the end, but 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 in 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 They like I can have an agent that uses my app to do that messaging using an existing app that supports this. Yeah. So ye, it's not obvious how it's going to play out. I think today people use a mix of,, apps and agents. Um But you know, 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 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 So if you have this kind of effect It doesn't matter if you were I can build apps That's still a really powerful note But I do think for sure, both things are in play. Okay, I got three more in ten minutes. Let's see if we can get to them all. Jack Clark, one of the anthropic founders. Reently said I think that he believes there's like a sixty percent chance. these models will start improving themselves By twenty twenty eight It could be off by a percentage or year, but Ballpark, that's accurate your're In the app where coding happens autonomously, you're running this app Do you agree with Jack was right When I look at the way that quot code is written, one hundred percent of Qad cod is written using quad code This has been the case since I think November last year Since open is four point five. It's like a fast takeoff scenario, then Do you anticipate that? I mean, it's possible. and like this is why anthropic exists. If you ask anyone, any engineer, any researcher why they joined Anthropic 're going to tell you it's for AI safety And it's because for us when we think about the future, you know, years from now, The thing that's the most important and the thing that we want to get right, you know, for our kids is we want to make sure this thing is safe and we want to make sure it goes well. becausecause yeah, like that is one of the possible outcomes I think that's not yet we're saying U you know, right now Cd code is writing itself, but it's still a person that's doing the prompting CQlad is starting to generate its own ideas for what to build next for Clouad code But it's, you know, it's not always good ideas. And I still generate most of the ideas And you know, at some point, it's going to change. The model is going to improve. and It's going to become more of a self reinforcing loop. Okay, I definitely want to get your thoughts on the world model uh, argument here where people who are pro world models says say that Um A large language model has no understanding of the consequences and you need to build a world model into it to have effective agents. Here's something from Yan Makun, he says you cannot build a reliable eentic system. Without a world model, LMs don't have world models They can't predict the consequences of their actions before taking them, according to Jan, they just act and whatever happens next is someone else's problem I was speaking with Greg Brockman from Open AI recently and he said Basically, he doesn't accept that argument and he thinks LMs are the way directly these text models are the way to AGI. Which side are you on? Are you believer that that world model intelligence needs to be baked in Or do you think that LLMs alone are goodood enough I would put out an offer to Jan if he wants to sit down and quad go together for an hour. I'd love to Chm. I should do that on this show Yeah, and then I'm curious to share what you think. Maybe he'll changes mind, mayaybe he doesn't. Right. But your perspective though You know, I'm I'm pretty firmly on the product side Um so, you know, I I don't I don't really have a have a perspective on Okaykay, let me drill down the tiny bit deeper if you don't mind. Um you're on the product side, but I've heard multiple people bring out this idea that without a conception of the way the world works, like in a world model A LLM just doesn't have an understanding of the way that the world works and the consequences and stuff You use cowork 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 I think from what I've read from folks working on a research at anthropic It is surprising the degree to which these models are intelligent Because like you said at the beginning, 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. likeike how can this possibly lead to intelligence You know, we've actually published a lot of work about how the models are able to plan they're able to actually reason 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 wouldn't discomment I mean, I think my favorite is when they write poetry as they're writing the first line. You can see in the model, this is anthropic research that they're already thinking The next line. that's right which is like How is that even possible That's right. I mean, and that's kind of you know, how I think about it. Like if I read poetry, that's how I would do it too. And it's yeah, it's crazy. likeike you teach this thing to predict the next word and somehow If the next word is hard enough, it has to learn to really plan ahead and it has to learn how to do all of this Okay, last one for you Um Sometimes I wonder when I see big tech changes underway And in my career covering this stuff, some have worked out and some haven't Um I always have to ask myself How are we sure that this is the future and this is not a fever dream? Um, And I think the data indicates that this is a real thing But I also wonder you have to sort of You have to question how much you can extrapolate towards the future in terms of how will this continue to progress The argument that this is a fever dream is that Um Maybe people just want simple interfaces and they don't mind tapping through things and Speaking in a cld code feels a little bit too techy. and it just won't appeal to the everyday user as much as it's really taken off with developers mean, how do you answer that We had this we had this hackathon for Opus four pointint seven recently and one of the winners was a doctor Nibilt an app, there was a There was an electrician There was a carpenter And a lot of these people didn't have coding experience, but they use quad code to build something useful There's one person that built and sold a startup as a result of one of these hackathons that we put on and Undoubtedly, when We first built Cot code. it was for engineers and engineers kind of figured out how to use it but very quickly People that were not engineers figured out how to use this to build economically useful things. And actually, if you look at a lot of the usage today, it's like it's not engineers. and it's just so useful for people that they are going out of their way. They're jumping through hoops even before coork People were like installing quQad code in a terminal For a lot of people, this was their first time using a terminal And of course, now, you know, for Coudcode, we have a desktop app, we have IOS app We have a Slack app. You know, there's many ways to interact with it But people were jumping through hoops to use it because it was so useful And so for me as a product person, this is the ultimate market test of is this thing useful is are there a lot of people? They use this every day and I keep using it every day And yeah, it's a lot of people and it just keeps growing And I'm just constantly surprised by the way that people use this Yeah, I will say I've been surprised by the way that I found myself using the tools and I don't know. we'll see what it comes next. So. excited to keep using it and thrilled to have a chance to speak with you. I hope we can do it again. Thanks for having me on. All right. than you, Boris. Great speaking with you Hi everybody, than you so much for listening and watching, and we'll see you next time on Big Technology Podcast This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome, that's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a fifty page restoration block, or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online makes sense? There's no place like Chrome. Check Responssees set up required compatibility and availability varies eighteen plus Evening, buyers remorse. Buy a new car? I'll be moving in. Let's get started. Sorry, I think there's been a mistake. I bought it from Carvana. You what? Yeah, great price. 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