Anthropic's Boris Cherny: Why Coding Is Solved, and What Comes Next

以下内容是YouTube平台的Sequoia Capital频道的《Anthropic's Boris Cherny: Why Coding Is Solved, and What Comes Next》（原始视频链接：https://youtu.be/SlGRN8jh2RI）的文字稿全文内容（语音转文字生成的）： okay I'm excited to introduce our next speaker show of hands who here uses cla code okay show of hands who here has cloud code psychosis come on guys it's okay it's okay um my my my team lovingly says I have Claude code psychosis which may or may not be true um we're delighted to have Boris Churnney with us today uh Boris is the creator the father of Claude Code um and uh in the process of doing that has just had a front row seat to to reinventing uh the modern way of of software development um and we're we're really grateful to you Boris for taking the time to speak with us today we know that um the entirety of software development kind of rests on your shoulder so thank you for taking an hour of your time to be with us today and interviewing Boris is Lauren Reer from our team thank you getting our chairs um you took my you took my opening line i usually ask who here uses quad code that was a lot of hands that's awesome thank you for joining us Boris it's very special to have you here um as a room full of builders I think you are changing building entirely and so I'm very curious to explore how you think about the future of software coding and what we should spend all of our free time on um but I'll give you a tiny bit more background on you so that everyone has a little bit more context so beyond creating cloud code Boris is very much an engineers engineer you were writing a lot of code through your whole career writing textbooks about code including programming in Typescript um and I think last time we chatted you hadn't written a single line of code in the last year or at least so far in 2026 which is quite the change um there's also a little known thing back in middle school I wrote a guide about uh writing basic for TI 83 plus calculators and I I just I I searched it it's actually still on the internet it's extremely embarrassing so please don't search it but it exists we will definitely be finding that um so we're going to do I'm going to start with a few questions here maybe we'll start with a little bit of the history of Cloud Code how you started it and then we're going to have a lot of audience Q&A for this one and so start thinking about your questions in the back of your head uh and would love to turn it over to you all soon yeah um and also real quick so for people that use Quad Code do people use the CLI mostly like okay majority CLI that's a lot majority desktop okay majority VS Code or Jet Brains ID okay that's actually not a lot okay other i'm like iOS mostly these days yeah okay cool um Yeah so I started Cloud Code kind of accidentally in in a lot of ways um I joined this team back in late 2024 it was sort of this incubator within Anthropic called Enthropic Labs and uh the team kind of served its purpose um we created quad code uh MCP and the desktop app it was a team it was just a few of us so very much like innovation team we built the thing that we wanted to build we disbanded the team uh now the team's actually back together for round two mike Rger who's the you know like the chief product officer at at Anthropic and used to be one of the founders at Instagram so he's leading that right now um so the kind of the the the the reason that I started to work on coding is we felt like there was this product overhang and I'm guessing people here use that word a lot uh but we definitely use this word a lot in kind of within the lab uh there's this idea that the model can do all this stuff that no product has yet captured and in late 2024 when we were looking at coding the way that we did coding the state-of-the-art at the time was type ahead was you open your ID and you press tab and you can like complete like one line at a time and that was the thing that Sonnet 3.5 enabled for the first time but the feeling was we could actually go a lot further than that and the model was almost ready for the next big step so we don't have to do type ahead anymore we can just have the agent write all of the code and so I built it and it just really didn't work for the first six months it was like not very good it was barely usable i wrote it for I used it for maybe 10% of my code or something like that and even after we released quad code initially it was not a hit there's a lot of people that used it but it did not have this exponential growth that it has today um that started with Opus 4 in May and I I remember that very clearly that's like when the exponential growth started and then it kind of inflected with every model release uh like it started with Opus 4 then 4.5 then 4.6 six now 4.7 it just kind of keeps inflecting but essentially we were trying to build this thing that was like pre PMF and we knew that it wouldn't have PMF for 6 months because we were building for the next model and that was the idea the pretty much the whole time and you know for enthropic in general we've always just been very focused we've always cared about business and enterprise and safety and coding that's just always been kind of the way that we wanted to build and so at some point we kind of knew that we wanted to build a product we didn't know exactly when so this kind of ended up the the product bed it's an incredible story especially that it was an accident um so you've said on the record that you think coding is solved uh if this is one of the three bets for anthropic can you tell us more about what you mean by that and what might still not be solved or what second order problems might come all right I can ask another question for the room who writes a 100% of their code by hand who writes a 100% of their code using a agent like quad code okay who's like somewhere in between okay so like 50% solved i mean for me for me it's like for me it's 100% like the the quad codebase um you know it leaked so you know people know uh it's pretty simple it's just like TypeScript and it's React like there there's no big secret there's there's nothing really complicated the the reason we picked TypeScript and React is it's very on distribution for the model so when we started you know building the codebase the model was not as intelligent as it is today so the language and the framework mattered a lot nowadays you know it can write whatever and it can pick up new languages new frameworks it hasn't seen but back then you wanted to use something pretty on distribution because of that I think fairly early we got to the point where the model just wrote 100% of the code and for us this happened sometime in October November last year and so for me today you know like the model writes 100% of my code i write somewhere you know usually a few dozen PRs every day uh there was a day last week I did like 150 PRs in a day that was like that was a record I was just trying to kind of push to see how far I can get it um but yeah it's like for me for me it's just solved um but this is not the case everywhere there's very big complicated code bases there's kind of weird languages the model's not good at yet um and you know as everyone here knows it's it's getting there usually the answer is just wait for the next model can you actually tell us about your personal setup you walked us through it the other day it is pretty wild yeah um so I shared my personal setup like 6 months ago or something on on Twitter and it it's funny i actually I shared it i didn't realize that it would be surprising for anyone that was just like the way that I coded and it's changed since then it's changed um and so now actually most of my work I do from my phone um and so I don't know if like you guys won't be able to see this but I have um so I have like the Claude app and if you open the Claude app on the left hand side there's this little code tab and I just have a bunch of sessions going um you probably can't see it how many sessions uh usually I have like maybe like five to 10 sessions uh and then the sessions usually have a bunch of agents so I think currently probably like a few hundred agents going um usually every night I have like a few thousand that are doing kind of deeper work there's a few ways to manage it one is that you ask claw to use a bunch of sub aents to do work actually the the thing that I've been finding myself using more and more is loop so this is sloop and it's just like the coolest thing it's like the simplest thing that works all it is is you have Claude use cron to schedule a job for some point in the future and it's a repeat job and it can run every every minute every five minutes every day kind of however often you want to schedule it and at this point I have like dozens of loops that are running for stuff so I have one that's babysitting my PRs so like fixing CI auto rebasing i have another one that keeps CI healthy so like if there's like a flaky test or whatever it'll it'll go and fix it um I have another one that grabs uh feedback from Twitter and kind of clusters it for me every 30 minutes so I just have a bunch of these loops running at any time i sort of feel like loops are the future at this point if you haven't experimented with it highly highly recommend it and we also just launched routines which is the same thing but kind of on the server so even if you close your laptop it it keeps going so that's your personal setup tell us about what you think teams will look like in the future how do you extrapolate from all the work you're doing to keep everyone on the team moving forward understanding the context or do you think we need to let go of a lot more agents to make it work um I think so i you know it's like it's so hard to make predictions but um I'm here to make predictions so I'll try to make some i I I feel like the way that things are going is generally there's going to be a lot more generalists than there are today and today when we talk about generalists I think largely we're talking about people that are still engineers so they're still writing code but maybe they're kind of product engineers so maybe when we say generalist it's like a you know they do iOS and web and server for example that's like a generalist in engineering but I think the thing that we're going to start to see a lot more of is generalists that are cross-disciplinary so this is engineers that are really good at product engineering but also really great at design or really great at product and data science and engineering um I don't know is it's something that we're starting to see on our team so actually like a lot of people on the cloud code team are generalists across disciplines everyone on our team code so like our engineering manager our product manager our designers our data scientists our finance guy our user researcher every single person on our team writes code and so you know like they're specialists in something but now also everyone's just coding and you know I'm seeing some nods but I bet also it's actually not that surprising to people in this room because I bet you're seeing the same things um I'll have one more thread of questions and we'll open up to the audience so we talked a bit about what's changing with coding i'm curious about what you see changing in the world of software or software products um I think as we see AI making writing code 10 or 100x cheaper what happens to the value of the products that are produced with software do we have a SAS apocalypse on our hands how do you think this plays out and again you're gonna have to make another prediction the SASpacov's question is my favorite question and um I think there's two things that are going to happen and I I don't think either of them is the thing that people have been talking about i think one is is anyone here an acquired listener like the acquired podcast yeah it's like the best podcast uh I actually I I got to do a unplugged with them the other week and I I just I I felt like I got to like meet my heroes because they're they're just like the hosts are the best so they have this idea of uh seven powers and and this is uh this is like Hamilton he kind of wrote he wrote a book about this and this is kind of the seven modes in business and I think what's going to happen is because of AI some of these modes are going to get more important and some are going to get less important and so like for example one that gets less important is uh switching costs because you can just use the model and you can kind of port from one thing to a different thing another one that gets less important is process power because for companies whose mode is like workflows and process and things like this quad is getting really good at figuring out process and especially with 4.7 it can just hill climb anything so if you give it a target and you tell it to iterate until it's done it will just do it i think this is the first model like that so I think these are going to get less important but I think the previous modes actually still matter so this is like network effects uh scale economies cornered resources things like that these are not really changing with AI i think the second thing is if you look at the number of startups today or like maybe in the next you know the past 10 years I think the number of startups in the next 10 years that are just going to like disrupt everything is going to increase like 10x because right now you can be a tiny startup you could build a thing that's as valuable as a large company and you can actually compete head-to-head because the large company has to evolve their business process they have to evolve the way they work they have to retrain everyone to use technology they're going to face a lot of internal resistance to that but uh you know no one here has that problem if you're starting fresh then you can kind of build with AI natively from the ground up so I don't know i I think it's the best time to build it's the best time to be a startup it's there's so much disruption coming so there is hope for us after all thank you Boris um I would love to open up to audience questions if anyone has anything they would like to ask dan hi yeah I'm curious um you said that you built uh six months before there was product market fit but now given that the models are good enough how much do you attribute the success of quad code to the model versus like product decisions and the the like feel the product uh I think it's probably a mix yeah I think it's a mix i I think if you ask maybe a year ago the ratio was maybe something like 50/50 um maybe I don't know if you asked me six months ago the mix would be 50/50 what about in two years oh two I don't know dude we plan on like we plan one week out six months sometime in the future and by the way I think the reason it was 50/50 is um you know I I I like I I did YC back in the day i was like the first hire at a YC company and like I did a bunch of startups and in startups like the thing that they drill into and especially in YC over and over is build something people love and so it it doesn't matter what the product is it doesn't matter like the model and all this stuff you still in the end have to build a thing that people love and I think that's that's why the product matters is we we pay so much attention to the little details so that as you use it all day it's a really great experience i think as the model's gotten better the harness kind of gets less important and I I think like a thing that we're thinking about right now is like how do we evolve the harness so like how do we make loops more of a first class thing how do we make it easier to run a lot of agents uh you know beside you know like sub agents is one idea there's a bunch more stuff that we're cooking but I think in a year the model will be much better aligned and so all the safety mechanisms that we have today around uh prompt injection and kind of static verification of commands and uh permission modes human in the loop all this kind of stuff is just going to be less important because the model will just do the right thing um so yeah that's that's my prediction thanks thank you you want to toss the box Dan great um to z to zoom out a little bit from software I think cloud code did a cultural change a few months ago where it democratized like building software you can see uh shop owners building their own uh um software for themselves or even uh programming microcontrollers to control the light when someone opens the door um do you see in the future um building software becoming a skill like I know Microsoft Office um so it's a thing that everybody can do not just people in the tech industry oh my god yes yes yes i I I think it's going to be even more than that i think it's going to be I don't know it's going to be a skill like Yeah like I know how to send a text message i I I think um you know like I I read my my two genres are essentially sci-fi and tech history this is what I read a lot of and I I think in tech history there's one thing which I think to me is the clearest parallel for what's happening right now and this is in the 1400s the printing press in Europe and what what happened was before the printing press essentially 10% of the European population was literate they knew how to read and write they were often employed by like kings and lords that were not literate and their job was to you know their job was to read and write and this is not something that everyone knew how to do the printing press was invented then there were two more presses and in the 50 years after the first printing press there was more literature published in Europe than in the thousand years before and over the same period the cost of literature the cost of a book went down like a 100x and then you know it took a couple hundred years because you know learning to read and write is hard you need education systems and government and everyone can't be working on farms and so on but over the next few hundred years literacy globally went up to like 70% and so you know now we can all read and write and you don't need a a degree in reading and writing to know how to read and write although still there are professional writers and that is a thing that you can do so I I think the thing that's about to happen and it's going to be much faster than 50 years is software will be a thing that is fully democratized that anyone can do and you know there's a lot of coraries to this so for example let's say you're writing accounting software the best person to write accounting software I think maybe even today is not an engineer it's a really good accountant because they know the domain really well and coding is the easy part it's knowing the domain that's the hard part and I I think this is just obviously the the future so one of the things Greg said was that you guys are living in the future a little bit because you get to have access to the models and the agents cloud code was an internal tool before you released it um is the gap between where you guys are in engineering and the rest of the world is that a month is it three months is it six months and is that is that gap getting bigger or smaller over time yeah so so internally we use the same models everyone else does um for us the dog fooding is really really important so we use the thing that everyone else here does um you know we use like a little bit of mythos to try it and then we use a lot of Opus 4.7 to to dog food it to write most of our code um I think on the model side there isn't really a gap um you know it's like it's pretty much mythos and you know that will become some version of some descendant of that will become available at some point to everyone i think on the product side there's probably a far larger gap and that's just related to us changing all of our processes like if you talk to people at Anthropic we use cloud for literally everything and our clouds are talking all day like as as I'm coding as my quads are coding in a loop they will communicate over Slack to talk to other people's clouds that are also running in a loop to kind of figure out unknowns we have no more manually written code anywhere at the company all of the SQL is written by uh by models everything is just built by the models so I I I think actually the place that we're ahead is not the technology because the same technology available to us is available to everyone here because fundamentally we are building a platform and so for us it's really important that developers can use the same thing that we're using and that we we dog food everything that we put out there but I think there's actually a far bigger lead in kind of the organizational structure and organizational process and this is a place where you know hopefully we can talk about it in places like this and uh everyone can kind of learn from it and and also evolve yeah and I think that's one of the advantages startups have it's so much easier to start there jiren yeah um last time we talked I think I think you'd mentioned we talked a little bit about multi- aent and it was very incode at the time at a prior square event and you'd mentioned that there were some things going down the pipeline thing you're talking you're thinking about now obviously there's slashbatch there's sloop there's sub teams there's teams can you speak some to either at the model level and at the harness level how you're injecting priors in the harness level how the objective functions changing at the model level to kind of make this experience around delegating work spinning up agents better because so much of the work is paralyzable you can kind of do so many things so much faster and I feel like I have to overlay my own intuition for when to paralyze things rather than the model kind of understanding that you can spin up tens of agents for something yeah i mean on on the product side it really just comes down to prompting that's that's all it is and so you know we we tweak prompts to kind of help the model do stuff in parallel more but also honestly as the model gets better it just naturally does this and so something like loop I found actually 4.7 it just starts doing uh which is really cool it's like it does something like uh you know I'll I'll tell it go uh uh pull this data query and it's like hey I notice that the data is changing over time i'll start a loop and I'll give you a report every 30 minutes and I'm like great can you send it to me over SWAK and then it uses the SWAC MCP to do that so so I think actually over time it's not on users to figure out how to hold the tools better and if that's the case it's actually a product design problem and like I'm not doing a good job it's really on the model to do this stuff better and on us kind of prompting it so it naturally does this um so right now it seems like a lot of us use um like cloud or codecs or these uh tools in the cloud to do a lot of our computing but then there are some very vocal advocates of uh have your AI be local and I could imagine over time as um open way models and other things catch up that this could be more of a possibility for people get really high quality coding assistance so I'm curious your vision of say over the next like years or something like that do you see the trajectory of everyone still really relying on the like cloud centralized compute or uh is there a pivot to oh we all just have our local agents that we can rely on and they don't get throttled and other benefits yeah I think it um I don't know there's maybe a few ways to answer that i think maybe like kind of the the most fundamental way to answer that is it doesn't matter because because I think now we're getting to the point where the model is just able to figure it out so I think like by a couple years from now the model is just going to be doing all the code it's going to be starting the agents it's going to be building the environments and so like if it decides like actually I'll use like local models to do this then you know that's what it'll do the I I don't think these will be decisions that we are making as engineers anymore we have time for a couple more questions so I can toss this out jamie Nester thank you it feels like one of the great decisions with cloud code was making use of the fact that a lot of developers tools and workflows are local but um that isn't necessarily always the case for sort of general knowledge work with you know cloud tools i'm curious how you're thinking about this with co-work enough access to the tools that we use to be powerful the same way that cloud code is for developers yeah it's that's a really great question um I know I know when I was uh when I was at a big company we took like five years moving all the environments to remote it's just like so much work especially at a big scale um but for knowledge work largely it's there already with like Salesforce and Docs and things like that um for us it's always just the simplest answer it's just MCP so the same MCP connector that you have in Quad AI you hook up like you know Salesforce you hook up Google Docs Google Calendar uh and then core can use that quad CLI can use it quad code everywhere can use it and for the for the systems that don't have MCPS like do you think that's where computer use is going to be a big opportunity yeah I think computer use is kind of a catch-all um so I think currently for as far as I know I think Anthropic is like pretty far ahead on computers and so like if you use it through co-work um so it's able to use pretty much any piece of software that you have on your computer it's very slow but it does it quite well now especially with 4.7 um yeah but I I think otherwise like MCP is is kind of the answer it's and you know all this stuff just doesn't matter that much it could be MCP CLIs APIs just some sort of programmatic access because the the model doesn't care is to to the model is just tokens all right we have time for one more question um Ryan Sean do you want to toss the Thank you um you've kind of alluded to this but if like some time ago you saw the probabil the product overhang and thought to build a product that would then become more interesting once models got better could you just talk even in vague terms about the shape of a product you built today that you think becomes a much more interesting as models get better in six months to a year yeah cloud design I I think is a really good example it's uh it's pretty good today it's going to get a lot better um there's also a few things that we're cooking up for cloud code uh that are going to be landing over the coming weeks so you'll see those um and then I think uh I think loop and batch and things like this around like massively paralyzing agents that's going to get better i think computer use is another good one all right Boris thank you so much for joining us i think we'll be here for a little longer if anyone has questions thanks guys