Natalie Kitroeff: From the New York Times, I'm Natalie Kitroeff. This is The Daily. On Monday, we looked at the growing push back against sprawling AI data centers in communities across America. Today, my colleague Kevin Roose takes us inside one of the most transformative technologies that infrastructure is enabling, a new way of programming that may be the biggest development in artificial intelligence since the launch of Chat GPT. It's Wednesday, February 18th. Okay. So, the other day I slacked you, Kevin Roose, my colleague, my friend, the host of The New York Times tech podcast, Hard Fork, and I asked you, "What is vibe coding?" Because this is a thing I had been hearing about, and I had no idea what it was. And you answered me roughly in the tone that one might use with their very elderly grandmother. I think it's like fair to fair to say.

Kevin Roose: Well, I I am not agist. I I I think people have lots of different levels of comfort with technology. I think my tone of voice was directed at you specifically, Natalie, because I know that you are younger than me and so you have no excuse to be this confused by technology.

Natalie Kitroeff: Yeah. Okay, fair enough. So since then I did my own research as any young person would do and I've come to the understanding that vibe coding is in fact very important. It appears to be using AI in a way that is truly revolutionary. And I do think that I cannot possibly be the only one who has not caught up to this. And so I want to ask you to just start by laying out the basics for those of us who aren't there yet. What is vibe coding?

Kevin Roose: So vibe coding is a term that was coined about a year ago by a guy named Andre Carpathy who's a former programmer at OpenAI, very well known out here in Silicon Valley. and he was describing this thing that he was doing using these new AI coding tools, which is that instead of learning a programming language and writing the code line by line by himself, he would just sort of let the program write the code for him and build software that way.

Natalie Kitroeff: Let the vibes do the work.

Kevin Roose: Let the vibes do the work. Exactly. And suddenly, for the first time about a year ago, you didn't have to know how to code to build software. you could just use these tools. They would help you along the way and you could just kind of oversee them as they worked.

Natalie Kitroeff: So what does that actually look like? You experimented with it. What did that do for you?

Kevin Roose: Yeah, so I tried vibe coding about a year ago when this term first emerged and I would build these little test tools for myself. I built an app called Lunchbox Buddy, which was basically a way to help me pack my son's lunch by just taking a photo of whatever was in my fridge and giving it to this tool and saying like, "What are the different combinations of things I could put in this four compartment lunch box?"

Natalie Kitroeff: Oh my god, that's amazing. So useful. I want it.

Kevin Roose: Yeah, I I built some other stuff, too. But honestly, it was kind of clunky. The tools basically you still needed to know a little bit about programming to be able to do this and they were pretty buggy. I tried to build some stuff to help me sort through my emails and it couldn't do it. It was mostly useful to professional programmers.

Natalie Kitroeff: and it doesn't stay that way I'd imagine because here we are talking about it as something that is revolutionary. So what happened? So the big innovation between last year and now is what is called agentic coding. Agentic coding is basically just a fancy way of saying an AI system that can do much more of the process autonomously. So you still do have to like have the idea for what you want to build, but then with these new tools, you can just sort of give them a project and they can make a plan. They can decide what programming languages they want to use. They can even create their own little team of agents and say, "Okay, this agent's going to go off and do the research. This agent's going to build the website. This agent's going to test it." And so you sort of have a little team of robots working for you to do whatever task you've given it.

Kevin Roose: My dream, a team of robots. Just sketch out why that's a big deal. Kevin.

Natalie Kitroeff: Well, because these models are getting much better very quickly and they are now able to do the kinds of tasks that would take humans hours or sometimes even days to do. And so they are working their way up into the entrylevel functions in a lot of white collar industries. The models themselves are also getting much better. They're not hallucinating as much as they used to. They're not making as many silly mistakes as they used to. They are doing better at things like reasoning and solving complex math and science problems than they used to. So sort of across the board these things are getting better at a pace that is surprising even the people who are building them.

Natalie Kitroeff: Okay. I want to ask you about the transformational potential of that about the impact on jobs. But first just tell me at a really practical level where do you see these new tools? what or who is driving this agentic phase?

Kevin Roose: So this is largely being driven by a handful of companies that are sort of the leaders in this AI race. So one of them is OpenAI the maker of Chat GPT. They have a new agentic coding system called Codeex. I have been using Claude Code which is made by Anthropic another AI company. And these are the tools that have come out just in the past couple of months that have people feeling like things are really accelerating. Cloud Code sort of blew up. Millions of people have been using it. They are doing increasingly complex tasks with them. People are using these in their jobs in the software industry. And what's really changed is that if you talk to people at the big AI companies who used to program, who used to write code by hand, they'll say, "I I don't write any code anymore. I basically supervise this team of agents and I kind of orchestrate them and set them off toward tasks and then I go get lunch and I come back and the work is done.

Natalie Kitroeff: Okay, I want to understand this. I want to understand the story of this. I think we should pick one and it sounds like claude code has been the one that's been blowing up. So tell me the story of this model. How did it start? How did it get created?

Kevin Roose: So this app Claude Code started as a side project. Basically an engineer at Anthropic named Boris Churnney had an idea. He was trying to sort of get a sense of what Claude Anthropic's chatbot could do. So he said, "Well, what if I just give it my computer? What if I install Claude inside the terminal app, which is the app that you use to write code and interface with your computer if you're a programmer? And what would happen if I just set Cloud loose inside my computer with a bunch of tools like give it the ability to write scripts, to create files, to organize things, to debug code, and he starts seeing something really interesting happening around the office. His colleagues are starting to use this tool to do their jobs. They're starting to program with it. It started with the engineers. They're saying, "This is really great for coding." At first it's maybe 20% of their engineers and then it's 40% and now all of them are using it. But it's also being used by people who are not professional programmers. People in marketing and sales and finance are using this not to just build little apps but to automate parts of their jobs.

Natalie Kitroeff: So it's like really catching on way beyond you know the technical people like normies are using it.

Kevin Roose: Exactly. What people have discovered is that it can do lots of stuff. It can automate your email. It can create dashboards for things. It can reorganize the files on your computer.

Natalie Kitroeff: It's sort of like you just have a computer that can use a computer. Now, this is starting to blow my mind, but I want to see it in action. Can we make something together? Can you make something for me? How does this work?

Kevin Roose: Okay, I would love to show you. So, what I'll do is I will share my screen here.

Natalie Kitroeff: I'm excited and a little scared.

Kevin Roose: Don't be scared. It'll be fine. Okay. So, this is the terminal app. Have you spent much time in the terminal app on your computer?

Natalie Kitroeff: The answer is not going to surprise you. No.

Kevin Roose: Okay. So, I had not either before I started using cloud code.

Natalie Kitroeff: Okay. This looks technical though, Kevin. Can I just say this is not my chat GBT window.

Kevin Roose: No, this looks like hardcore programming things. And I think the interface is what has made a lot of people feel like this is a tool that they can't use because they don't write code. Right.

Natalie Kitroeff: So I will just say I do not write code. I am not a coder.

Kevin Roose: You're closer to me than them. You're saying

Natalie Kitroeff: I am much closer to to you than them.

Kevin Roose: So okay, here we are. We're inside Cloud Code and I'm just going to give it a prompt. I'm going to say build a website for my colleague Natalie Kitroof. And I noticed, Natalie, that you don't have a personal website, at least that I could see. Correct. Do you have Do you have one?

Natalie Kitroeff: I don't. I've kind of given over my identity to The New York Times.

Kevin Roose: No, see, you need one. You are a big-time podcast host now. And so, you need a website for yourself. So, she's the co-host of The Daily. And the site should look, how do you want it to look? Sleek and professional.

Natalie Kitroeff: Yes. And cool. Make me look cool, please. Thank you.

Kevin Roose: And cool. And professional. Make her look

Natalie Kitroeff: And also cool. Sorry. Thank you. Yeah,

Kevin Roose: she really likes the Philadelphia Eagles, so maybe do it in eagles colors.

Natalie Kitroeff: This is getting better and better.

Kevin Roose: All right, so I I hit enter and it says burrowing, which is one of its words that it uses for thinking.

Natalie Kitroeff: Do we know what it's doing?

Kevin Roose: I promise you I do not understand what it's doing. Like a professional coder would know what it is doing, right? All I know is that is doing something and it's going to think about it. It's going to make a plan and then it's going to start building.

Natalie Kitroeff: How long does it take?

Kevin Roose: It depends on the complexity of the task. I've had tasks that have taken 10, 20, 30 minutes before, but I think this is going to be just a minute or two at most.

Natalie Kitroeff: And the idea is that it's kind of scraping the internet for information about me. Did you tell it to make sure that everyone knows I'm young? Also, I'm just

Kevin Roose: We can add that in a subsequent version. So, it wrote 644 lines of code. Okay, so it's live. Let's just see what it looks like together.

Natalie Kitroeff: What was that? A minute.

Kevin Roose: That took a minute and 36 seconds. Look at that.

Natalie Kitroeff: Wow.

Kevin Roose: We've got a little like Eagles Green website.

Natalie Kitroeff: Yeah, I see that. Oh my god. It knows that I was in Mexico as a foreign correspondent.

Kevin Roose: Uh-huh.

Natalie Kitroeff: Oh, the spirit of The Daily. The best journalism doesn't just inform, it makes you feel the weight of reality and then pushes you to care. It's a quote that is attributed to the spirit of The Daily,

Kevin Roose: which is not a real person.

Natalie Kitroeff: So, because I didn't give it a lot of information, it it just sort of made some stuff up to fill the space. But the cool thing about this is now if you want to change it, you can just go into this window and you can say, "Hey, that's a fake quote. Can you make sure all the info on the site is accurate?"

Kevin Roose: Yeah.

Natalie Kitroeff: I'm thinking we should maybe add like an Easter egg to this. Um something fun for for people who go to your website and really want the full Natalie Kitf experience. Okay. What's it going to be?

Kevin Roose: So, you're a big football fan. There was a video game called Techmo. Very early football video game. And so, I would like to see if we could put a version of Techmobile that's playable, like a little playable video game on your website.

Natalie Kitroeff: Yes. Wow. Can I also hire you? I feel like you're good at this. You're good at talking to Claude.

Kevin Roose: So, I'm going to go back to my terminal app here and I'm going to say, "That's great. Could you add a playable Techmo Bowl style video game to the site. Oh, it says this is going to be fun. So, it's writing hundreds of lines of code.

Natalie Kitroeff: I mean, this is insane.

Kevin Roose: It's wild. I mean, this is why people are freaking out about AI right now because this was not possible even a couple of months ago and now it is. Okay, so now our our video game is done. Should we go see it? Yes, please.

Natalie Kitroeff: Okay, so here's Natalie's techmobile.

Kevin Roose: Oh my god.

Natalie Kitroeff: And do you see it?

Kevin Roose: Oh my god. Yeah, I do.

Natalie Kitroeff: So, it says press space to hike

Kevin Roose: and arrow keys to move. Okay, so Oh. Oh, we got to run. We got to run.

Natalie Kitroeff: Oh,

Kevin Roose: touchdown Eagles.

Natalie Kitroeff: Go birds. This is incredible. Wow. This is like I feel like I'm going to draw a lot of people to my new website with this feature.

Kevin Roose: Yeah, you're going to be getting so much traffic.

Natalie Kitroeff: Okay. So that is Cloud Code and that is how these new coding tools work. How do you feel?

Kevin Roose: I feel pretty blown away. I honestly can't believe that we just made my first website and that it has a video game on it. I have so many questions that I want to ask you about it and we'll do that after the break. We'll be right back.

Natalie Kitroeff: Kevin, I have to just acknowledge that it is honestly an amazing feeling to see this AI agent at work. It's probably the first time that I have felt awe at this technology since Chat GPT came out. It's been a really long time and there is something a little bit unnerving about it. And so I just wonder for you, what do you make of this moment? What do you make of this change that we're seeing in these tools?

Kevin Roose: Yeah, I think this is a big deal in the world of AI. This is something that people inside the AI industry have been saying is coming for a long time, but until recently, people couldn't really see it for themselves or try it for themselves. And you know, chat GPT has been around for three years now. And for most people, the novelty is sort of wearing off. You know, it's a fancy Google. You can get a meal plan. You can sort of give it some questions. It can help you write your emails or memos or things like that, but it doesn't sort of shock you anymore. This feels different to me and I think to a lot of other people when you can actually build something useful without knowing how to write code. And I think this is what people think is the thing that's going to take AI from just kind of being a fancier Google to something that genuinely changes how people work. When you say that this is something that the tech companies have been saying is coming for a long time, what is the it that is coming? What makes it special? Is it just the complexity of the stuff it can do or is it the utility of it?

Natalie Kitroeff: I think it's the utility, but it's also the economic value. This kind of agentic system can actually do work. It can do tasks. It can perform things that humans would have had to do by hand. So it is sort of a step in the direction of making these things actually kind of members of the workforce in some sense where you could have a company with some human employees and then a whole bunch of AI agents doing tasks.

Kevin Roose: Okay, let's talk about that because obviously when we're talking about economic value, what that presumably means for the people that run these companies is lowering labor costs by potentially eliminating jobs.

Natalie Kitroeff: Yeah. So that's the big question is will this just help people at work? Will this kind of agentic coding tool make people faster and more efficient and more productive and give them a new powerful tool in their toolkit or will it start to replace people? We are starting to see in the data some signs that this kind of tool is maybe displacing young software developers. So there was a study from Stanford recently that looked at payroll records and found that employment for young software engineers just people who are early in their careers has dropped about 20% from its peak in 2022.

Kevin Roose: So companies that used to hire five or 10 people to write code for them may only need one or two now with a bunch of AI tools.

Natalie Kitroeff: Can I ask we were pointing to issues with my beautiful website. How good is this stuff? I mean, can it debug itself? Because I guess I'm seeing that there is also a lot of doubt and skepticism that you can really do this only with an AI tool at this point.

Kevin Roose: Well, coding is an interesting test ground for this because in some sense it is very verifiable. The code either runs or it doesn't. And so, in some sense, it's very easy to tell. I mean, the website we built, it works. You can go visit it on the web. it has a playable video game inside of it, right? So, yes, there are a lot of software engineers who are still saying these coding agents, they're not perfect. You still kind of need to hold their hands and oversee them if you want to get really useful code that you could like deploy inside of a big business, but that is maybe temporary because they're improving at a very rapid rate. And we're seeing that some of the things that these tools couldn't do even a few months ago, it's now doing in ways that are correct and and useful. Well, can you just tell me quickly like what's making this improve so quickly?

Natalie Kitroeff: So, part of it is just that the models themselves, the things that are sort of underneath tools like cloud code are just getting better very rapidly. And part of that is because they're being trained on more coding data. So, they're sort of improving over time. The other really interesting and really important thing that is starting to happen is that these AI tools are building versions of themselves. They are starting to improve themselves.

Kevin Roose: What what does that mean?

Natalie Kitroeff: So, OpenAI's latest coding model which is called GPT 5.3 Codeex was used to help build itself. Early versions of the model were used to make changes to the training runs for later versions. So this is happening across all of the leading AI companies right now which is that you have these systems which can build websites which can automate certain financial or legal tasks. They can also help train AI models and so we're starting to see

Kevin Roose: so AI models making AI models just to be clear about what we're saying here.

Natalie Kitroeff: Yes.

Kevin Roose: Is that scary to you? Because it gives me the vibe of a sci-fi reality.

Natalie Kitroeff: Yeah. This is a sort of scenario that we've heard about in science fiction for years where you have AIs that are becoming increasingly capable. They're building better and better AIs within the AI community. There's this idea, this phrase of the intelligence explosion, which is when you have these systems that are doing what's known as recursive self-improvement, building better and better versions of themselves. And so that is one possibility that these systems just start to accelerate their improvements to the point where they are sort of doing all of this autonomously without human involvement. Now there are some people who think this is still a far-fetched scenario but just look at the trajectory. I mean a year ago you had these very clunky AI vibe coding tools. Now they're running autonomously for sometimes hours at a time. they can build and maintain real software and they're starting to help build the next versions of themselves. So I think we are right to be paying attention to this and I think it's irresponsible to sugarcoat what's happening. I have to say for the companies and for the people that have been involved in AI, this also has to really be a kind of proof of concept moment for them because there has been so much skepticism about AI over the last year. A lot of fear about frothiness in the market, about whether we're in a bubble, about whether AI is really going to live up to its potential. And what you've described is a transformative tool that can be incredibly useful. and with that the potential for real job loss. So anyway you slice it, this is AI doing what they said it probably would.

Kevin Roose: Yeah, it is. And I think you know I don't blame people for questioning last year whether we were in an AI bubble. I think most people up to that point had only used things like chat GPT which are you know very capable on their own but I can understand why people would look at that and then look at the billions of dollars being spent on data centers and infrastructure and think like okay isn't this a little bit much but the bet that these AI companies were making is that you could actually turn this stuff into useful tools that would be able to do real valuable work in the economy and I think we are starting to see that bet pay off.

Natalie Kitroeff: Kevin, I think it's worth pausing here for a moment. Like, it's very easy to talk about job loss from all this in the abstract, but at a practical level, if a whole class of workers just lose their jobs, if those jobs cease to exist, we'd be talking about a pretty massive impact on the economy at large. And I mean this could hypothetically just be the very beginning. If agents like these can do other forms of work, you could see many more jobs wiped out. So I just want to ask, how likely is it really that these tools create that kind of job loss? And what are the AI companies saying about it?

Kevin Roose: So I'll answer the first part, which is that I don't know how likely it is. I have intuitions and guesses, but no one really knows how this is going to go. It could be that there's a short-term spike in the demand for software engineers because everyone's building new kinds of software and they need people to manage it all

Natalie Kitroeff: and it could be that these tools just never wipe out millions of jobs on mass but the AI companies and the people who run the companies are increasingly worried about this. So Dario Ammed, who's the CEO of Anthropic, which makes Claude, has warned that he believes that AI could potentially eliminate half of all entry-level white collar jobs within the next 5 years.

Kevin Roose: Wow.

Natalie Kitroeff: So that could be wildly off, but even if it were partially true, even if it were 10% or 20%. That would still be a massive change to the labor market and to the lives of millions of people. Yeah, there's something deeply unsettling about all of that.

Kevin Roose: Yeah, I agree. And I myself feel very uncertain about this. And I think there are a lot of people in the tech industry who are very excited about these tools cuz it's letting them, you know, build a bunch of stuff very quickly. But as I'm hearing from more people in white collar knowledge work fields, they're just very anxious right now. People are really uncertain. They don't know if the skills they're building are obsolete. College students don't know what they should be studying so they can get a job after they graduate. People are really getting nervous about how quickly this technology is improving and the possibility that it could make the future look very different.

Natalie Kitroeff: Okay. And I want to ask about that future. I mean, are we on a runaway train? The speed with which this is changing feels hard to even capture honestly. And I wonder if you think about the progress made over one year, what's the next year? What can we expect?

Kevin Roose: I mean, my honest prediction is that a year from now, these agentic tools will be dramatically better, right? They'll handle big complex problems. You won't have to hold their hand as much. They will become full-fledged members of the workforce and you know a lot of companies will still do things the old way because institutions are very slow to change as we know but there will be this sort of new kind of company that is emerging with AI work at the center of it and I think that's going to be a really fast growing part of the economy. I think the job market impacts that we're starting to see hints of today will become much clearer a year from now. But honestly, I lose a lot of visibility myself. I mean, I have stopped trying to predict more than about 6 months out because that's about as far as I can see right now. I would not have predicted a year ago when vibe coding first came into my consciousness that it was going to be capable of doing all of this today. So, I think the most we can say right now is these tools are getting better at a at a very fast and accelerating rate and that they keep doing things that are surprising and useful and there's a lot of unknowns about what that will mean for the future of human work.

Natalie Kitroeff: Kevin, one of my favorite humans, thank you so much for coming on the show. I really appreciate it.

Kevin Roose: You're welcome. And we should also thank Claude who built you that beautiful website.

Natalie Kitroeff: Thank you, Claude.

Kevin Roose: He's been a good bot.

Natalie Kitroeff: He has. Yeah.

Natalie Kitroeff: For more on the latest developments in Agentic Coding, listen to Hardfork wherever you get your podcasts. We'll be right back.