YouSaid · the spoken record

Daniel H. Chai

lines on the record: 82
first: 2025-08-04
most recent: 2025-08-04
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“Right Back with any sphere CEO Michael Truel. Before the break, we were discussing how his company's product, cursor AI, is being adopted by professional coders. But now I wanted to ask about a different use case, vibe coding. You mentioned non technical people. Cursor is used by a lot of professional programmers, but this year saw the coining of the term vibe coding to describe what more amateur programmers can do, sometimes even complete novices, and often with tools like cursor. How big is the vibe coding use case at cursor? And what do you think is the future of vibe coding?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Ball of mud, that massive things, it's very unwieldy, and they need to edit it. That's why I think that it's kind of shocking to many people that some software release cycles are so slow. But so, yes, I think that there are real productivity gains. I think that it's probably not reducing the number of hours that programmers are working right now.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Yes, in the sense that I think that the productivity gains of what would have taken you eight hours before in some companies now actually can take you five or six hours. I think that that is real, not across all companies, but it is really real in some companies. But I think that the thing I would nitpick on there is I don't think programmers are actually just working or are shortening the hours that they're working. And I think a lot of that is because there is just a ton of elasticity with software. And I think it's really easy for people who are non-technical just don't program professionally to underrate how inefficient programming is at a professional scale. And a lot of that is because programming is kind of invisible. You know, what a programmer is doing at a company like Salesforce is there are just tens of millions of lines, many millions of files of existing logic that describes how their software works. And anytime they have to make a change to that, they have to take that.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Yeah. I mean, my sense is maybe if I used to have to work eight hours a day, now it's maybe closer to five or six. Is that part of it?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Still more to do there. But the next thing that's kind of picked up the torch in making models better has been reinforcement learning. So it's been basically teaching models to play games, kind of similar to how in the mid-2010s, humanity figured out how to make computers really get at play and go and playing Dota and other video games. We're kind of getting to a level of language models where they can do tasks and you can set up games for them to get even better at those tasks. And programming is great for that because you can write the code and then you can run it. And then you can see the output and see if it's actually what you want. And so I think there's a lot about the technology that makes it especially good for programming. And yeah, it's just, you know, I think one of the use cases that's the furthest ahead in kind of deploying this tech out to the world and people finding real value from it.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“I think that we're just already at a point where we are far, far, far from the ceiling of where things can go and far, far, far from a world where much of coding has been replaced with something better. But just already at this point, these products and these models can do a lot for programmers and already taking on quite a bit of work. And I think that the technology is especially good for programming for a few reasons. One is that programming is text-based, and that is the modality that the field has figured out perhaps the most. There's a lot of programming data on the internet, too. So a lot of open source code. Programming is also pretty verifiable too. And so one of the important engines of AI progress has been training models to predict the next word on the internet and making those models bigger. That engine of progress has largely run its course.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Recently, I had dinner with the CTO of a big tech company, and I asked him about what coding tools were popular with his engineers. And he told me that he actually regularly surveys them on this question. And they had Chris are available as like a trial, it was labeled. And he said he was getting these panic messages from engineers saying, please tell us you're not about to take a weight cursor because they've become so dependent on it. Can you give us a sense of why for programmers this has kind of felt like a before and after moment in the history of the profession? What is it that tools like Chris are making so different in the lives of these engineers day to day?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Working on for sure. I think one of the things that really did help us was when we were working on CAD and also in some of our explorations before, my co-founders had to dig very deep into kind of the ML infrastructure and modeling side of things. And so when we actually set out to work on Cursor, we thought it would be a long time before we started to do our own modeling as a product lever, but it happened much sooner than we expected.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“For instance, with our tab model, which does over a billion model calls per day, this is one of the large language models that writes actually almost some of the most production code in the world. And we're also on our fourth or fifth generation of it, that is trained using product data of seeing where AI is helping people, seeing where it isn't, seeing what in the places where it isn't, trying to predict how it can help humans, and also requires a ton of infrastructure, specialty talent to be able to make those models really good. For instance, one of the people who has worked on those models with us is Jacob, who built actually the kind of GitHub co-pilot before GitHub co-pilot, which was tab 9, which was the first kind of programming autocomplete product. He is also one of the people who built one of the first million token context window models and so has done a lot of work on making models understand more and more and more information. But yeah, specialty talent and specialty infrastructure too to do that work. And one of the, in our ambling kind of windy way to”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“I think that also one asterisk before getting into the model side of things, I think that the rapporteur term came from that very start of when people were building AI products, when there was only so much time to kind of make the products a bit deeper. And now I think we're at a point where there's a ton of product overhang. And so even if you're just building with the API models, I think that there's lots of areas, our area, working on the software development lifecycle, but in other parallel areas too. I think they're very, very deep products to be built on top of those things. And in that sense, I think the wrapper term for at least some areas is a little bit dated. But on the model level, from the very start, we wanted to build a product that got a lot of people using it. And one of the benefits you get from that scale is you can see where AI is helping people. And you can see where AI is not helping people and where it gets corrected. And that's a really, really important input to making AI more useful for people. And so at this point,”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, let's talk a bit about these proprietary models. They seem to be fueling a lot of your success. When ChatGPT and the OpenAI API first got released, we saw a lot of startups come out that quickly were dismissed as just wrappers for an API.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“And then also, for some form factor, or for some of the features, it's entirely custom, for instance, like the Sup Autocomplete. And so that's also one thing that has kind of distinguished us from other solutions.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“From the very start, we've thought that the solution to automating code, replacing it with something better, is this kind of two pronged thing where you need to build the pane of glass where programmers do their work and you need to discover what the work looks like. You need to build the UI. And then you also need to build the underlying technology. And so one thing that would distinguish us between some terminal tools is just the degree of control you have over the UI. Another thing too is we've done a lot of work on the model layer, on improving going beyond just having things that show up well on a demo level. And there's a lot of work on AI products to dial in the speed and the robustness and the accuracy of them. And for us, one important product lever there has been building kind of an ensemble of models that work with the API models to improve their abilities. And so every time you kind of call out to an agent in cursor, it's like this set of models that some of them are API, some of them are custom.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Thousands of hours and really large teams and lots of work, especially at professional scale. So that's where we want to get to is kind of inventing that new form of programming. I think that that starts as an editor and then that starts to evolve. And so we're already kind of in the midst of that, where right now cursor is this place where you can work one-on-one with an agent and you can work with our tap system and then increasingly we're getting you to a world where more and more programming looks like starting to delegate your work to a bunch of helpers in parallel. And there's a product experience to be built for making that great and productive and understanding what all of these parallel helpers are doing for you, being able to intervene in the places where it's helpful, you know, understanding their work when they come back to you at a level that's not having to read every single line of code. Yeah, I think that there's a competitive environment with a bunch of tools that are interested in programming productivity. One of the things that's limiting about just a terminal UI is that you have only so much expressiveness in the terminal and control over the UI.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Both of those are really useful tools. The thing we care about being, so I think we start as this IDE, we start as this text editor, and what we really care about getting to is to a world where programming is completely changed, and in particular, you know, a world where you can develop professional grade software, perhaps without even really looking at the code. And it's that kind of future programming and changing it from this weird, you're reading these millions of lines of logic and these esoteric programming languages to getting you to a world where you can build software by just specifying the minimal intent necessary to kind of build the software you want. You know, you can tell the computer that the shortest amount of information it needs to really get you and it can fill in all of the gaps. And yeah, programming today is this intensely labor intensive, time intensive thing where to do things that are pretty simple to describe to get them to actually work and show up on a computer. It takes many.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“So you described cursor as kind of like a souped up word processor, software engineers, I think, would call it an integrated development environment or IDE. And developers have been using IDEs since the 80s. But recently, AI Labs have released tools like OpenAI's Codecs or Cloud Code that can run directly in a terminal. Why might someone use cursor over those options?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, I think caring about the tools we use was helpful, and I think that they're actually kind of different degrees of that on our co-founding team. One of my co-founders in particular is straight out of central casting early adopter, who's the first one on these new browsers, first one on kind of the new category of everything. A couple of us are a little bit more laggards. And so I think actually kind of having maybe that diversity of opinions has helped us in some of the product assumptions we've made.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“That's interesting. So, you guys sort of like software, you like using software, you like trying to find software that makes you more productive. I feel like that probably made you well suited to tackle a problem like the one cursor is trying to solve.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“The product was wrong in really obvious ways, and you couldn't completely trust its code output, but it was nonetheless really, really exciting. And another thing to note, too, is apart from being the first useful AI product, it was the most useful new dev tool that we had adopted in a really long time. And we were people that had kind of optimized our setups as programmers and had kind of modded out our text editors and things like that. And we were using this crazy text editor called Vim at the time. And not just the first useful AI product that we'd use, but also the most useful Devfol we had used in a really long”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Kobalo was awesome. CoPilot was a really, really big influence. It was the first product that we used that had AI really at its core that we found useful. One of the sad things to us, as people who had been working on AI and interested in AI for a while, was that it was very much stuff that was just kind of in the lab or in the toy stage and felt like for us, the only real way AI had touched our lives as consumers was mostly recommendation systems, right? You know, the news feeds of the world, YouTube algorithms, things like that. And so GitHub was, yeah, it was the first product where AI was really, really at the core that was useful. And so that was a big inspiration. And at the time, we were considering, should we try to pursue careers in academia, co-pilot kind of was this existence proof that, no, actually it was time to work on these systems out in the real world. And even back then in 2021, there were some rough edges. There were some places, you know.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“I have read that one of the AI tools that you used early on was GitHub Copilot, which came out about a year before ChatGPT. What was your initial reaction to Copilot and how did it influence what you wanted to build?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“As AI starts And then hopefully Job well We're building useful things, but they weren't really pointed in the same direction, and they didn't really seem to be approaching the space with the requisite ambition. And so, yeah, we decided to build the best way to code with AI. And that's where cursor started.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“By co founders and I, we come from Programming for a while. And we've also been working on AI for almost as long as we've been programming. And so one of my co-founders, one of us had worked on recommendation systems in big tech, another one of us had worked on computer vision research for a long time. Another one of us had worked on trying to make machine learning algorithms that could learn from very Little data. Another one had worked on Google using the antecedents The things that came before LLM technology in machine learning, but worked on AI for a long time, had been engineers also for a long time, and loved programming. 2021. There were two moments that really excited us. One was using some of the first really useful AI products. Then another was kind of this body of Going to get better Even if we kind of ran out of ideas.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“We'll dig a little deeper into the product in a moment. But first, let's talk about how all of this started. When you founded Anisphere, you were working on computer-aided design software. How did you get from there to cursor?”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“And then the other way that people work with cursor is they're kind of increasingly delegating to cursor like they're working with a pair programmer working with another human. So they're handing off small tasks to cursor and having cursor kind of go end-to-end on them.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Way more efficiently, especially with AI. And there's kind of two different ways cursor does that right now. One is kind of watching you do your work, and it's trying to predict the next set of things you're going to do within cursor. So this is the autocomplete form factor, and that can be really souped up in programming compared to writing, because unlike writing, it's actually, there are oftentimes when you're programming where the next 20 minutes of your work are entirely predictable, whereas with writing, It's a little hard to get a sense of what a writer is actually going to put down on the page. There isn't really enough information in the computer to understand the next set of things.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Our intention with Kursher is to be the best way to build software and in particular the best way to code with AI. For people who are not technical, I think the best way to think about cursor as it exists today is think of like a really souped up word processor where the way engineers build software is they're actually doing a lot of writing. They're sitting in something that looks like a word processor and they're editing millions of lines of logic. So things that don't look like language. And Kusher helps them do that.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Michael Trull? Here we go. Michael Trell, you are the co founder and CEO of Anisphere, the parent company of Cursor AI. Welcome to Decoder.”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Are regularly telling me about how much they are using and liking cursor. So look, a lot of people are worried that AI could take their jobs, and rightly so, I would argue, but you'll hear Michael say that job losses are not going to come from simple advances in tools like the one that he's making. Lots of people in the Bay Area think that superintelligent AI is going to remake the world overnight, making products like cursor pointless, but Michael believes that change is going to come much more slowly. I also wanted to ask Michael about the phenomenon of vibe coding, which lets amateurs use tools like cursor to experiment with building software of their own, even if they've never built anything before. That's not cursor's primary audience, Michael told me, but it is part of this broader shift in programming, and he's convinced that we're only scratching the surface of how much AI can really do here. So, anySphere CEO,”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“IDE Code Write them. And Cursor has become one of the most popular and fastest. Growing AI products in the world and any The company that Michael co Us three years ago after graduating. Is now shaping up to be one of the biggest startup success stories of the post ChatGPT era. So I sat down with Michael to talk about Cursor, how it works, and why coding with AI has seen such incredible adoption. As you'll hear, Michael explain, this entire field has changed a lot over the past few years, and now here in San Francisco, tech executives and employees and employ”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“And also, they're fun. I like trying new software, and every new tool brings with it the hope that this is the one that is finally going to complete the setup of my dreams. Over the years, I've used a lot of these programs, but I rarely get a chance to talk to the people who make them. So for my decoder episodes, I really want to talk to the people behind some of the biggest and most interesting companies in productivity about what they're building and how they can help us get things done. And that brings me to my guest today. Michael Truel, the CEO of Anisphere. You may not have heard of Anisphere, but I bet you've heard the name of its flagship product. Hurs Is an automated programming platform. Integrates with generative AI models from Anthropology. To help you write I guess there I And give my disclosure for the epis”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT
“Hello and welcome to Decoder. This is Casey Newton. Founder and editor of the platformer newsletter And co host of the Hard Fork podcast. I'll be guest hosting over the next few episodes of Dakota while Nehi is out on rental leave. Congratulations, Neil. And I'm very excited for what we have planned for you all. If you follow my work at all, particularly when I was a reporter at the Burge, you'll know that I'm a total productivity nerd. I love productivity apps, whether it is a to-do or some kind of collaborative app or something making use of AI. At the best, I think productivity apps are the way we turn technological advancement into human progress”
2025-08-04 · Decoder with Nilay Patel · Why tech is racing to adopt AI coding · IDENTIFIED FROM THE TRANSCRIPT