Can A.I. Already Do Your Job?

Summary

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Podcast Summary: The Daily – "Can A.I. Already Do Your Job?"

Date: February 18, 2026
Host: Natalie Kitroeff (with guest Kevin Roose, NYT tech columnist)
Theme: Exploring the recent breakthrough in “agentic” A.I. coding, and what it means for work, jobs, and the future of knowledge labor.

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Episode Overview

The episode delves into one of the most transformative trends in A.I.: the rise of “agentic coding”, where A.I. models can autonomously write software, complete complex tasks, and even improve themselves—all with minimal human intervention. Natalie Kitroeff and Kevin Roose break down how these new tools work, their leap in capabilities, and the economic and social implications, notably the potential impact on jobs.

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Key Discussion Points & Insights

1. What is "Vibe Coding" & How Did We Get Here?

• Definition:
  • Vibe coding refers to using A.I. to write code on your behalf, without needing traditional programming experience.
  • Coined by Andrej Karpathy, ex-OpenAI engineer, a year ago.
• Significance:
  • “Instead of learning a programming language and writing the code line by line… let the program write the code for him.” – Kevin Roose (02:30)
  • The real turning point: A.I. has advanced to the point where anyone can build software, not just coders.
• Early Limitations:
  • “Honestly it was kind of clunky. The tools… you still needed to know a little bit about programming… pretty buggy.” – Kevin Roose (03:51)
  • Initially, only truly useful to professional software developers.

2. The Shift: "Agentic Coding" and A.I. Teams

• Evolution:
  • Agentic coding means A.I.s act as fully autonomous agents capable of managing whole projects independently.
  • “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…” – Kevin Roose (04:20)
• Industry Impact:
  • “They are now able to do the kinds of tasks that would take humans hours or sometimes even days to do. They are working their way up into the entry level functions in a lot of white collar industries.” – Kevin (05:07)
  • A major leap in the models’ reasoning, accuracy, and autonomy.

3. The Claude Code Case Study (Anthropic’s Tool)

• Origin Story:
  • Born as a side project by engineer Boris Czerny at Anthropic.
  • Initially used by engineers, but rapidly adopted by non-technical staff (marketing, sales, finance) to automate parts of their jobs. (07:19–08:33)
• Viral Popularity:
  • “Millions of people have been using it. They are doing increasingly complex tasks with them. …I don’t write any code anymore. I basically supervise this team of agents, and... go get lunch and I come back and the work is done.” – Kevin Roose (06:05–07:04)

4. Live Demonstration: Building a Website in Minutes (09:07–14:35)

• Process:
  • Roose prompts Claude Code to make a sleek, professional, Eagles-colored personal website for Natalie—plus an embedded playable Tecmo Bowl-style football game.
  • The A.I. writes 644 lines of code in just over a minute.
  • “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.” – Natalie Kitroeff (14:41)
  • Demonstrates how non-coders can direct agentic A.I. with simple instructions.

5. Broader Implications: Jobs, Talent, and the Economy

• Is This the A.I. Moment?
  • “This feels different to me… when you can actually build something useful without knowing how to write code… this is what people think is the thing that’s going to… genuinely change how people work.” – Kevin (16:42)
• Evidence of Impact:
  • Stanford research: employment for young software engineers is down 20% since 2022 as companies hire fewer coders, relying on A.I. tools. (18:31)
• A.I. as Workforce:
  • “You could have a company with some human employees and then a whole bunch of A.I. agents doing tasks.” – Kevin (17:50)

6. How Good Are These Tools, Really?

• Verification & Self-Correction:
  • “Coding is an interesting test ground... the code either runs or it doesn’t.” – Kevin (19:35)
  • Not perfect yet; still needs human supervision, but improving rapidly.
• Self-Improving A.I.:
  • “These A.I. tools are building versions of themselves. They are starting to improve themselves.” – Kevin (20:25)
  • OpenAI’s GPT 5.3 Codex used itself to help train future versions. (20:53–21:26)
  • “This is a sort of scenario that we’ve heard about in science fiction for years, …Recursive self improvement, building better and better versions of themselves.” – Kevin (21:35)
  • Potential for “intelligence explosion”—still debated, but the acceleration is undeniable.

7. The Specter of Job Loss and Economic Disruption

• Industry Anxiety:
  • “...AI could potentially eliminate half of all entry level white collar jobs within the next five years.” – Dario Amodei, CEO of Anthropic, quoted by Kevin (25:23)
  • Even a partial realization would transform labor markets.
  • “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… People are really getting nervous.” – Kevin (25:38–26:24)
• Will it Be as Big as Feared?
  • Even the A.I. insiders admit there’s massive uncertainty on how quickly or extensively displacement will happen. (24:39–25:23)

8. The Uncertain Road Ahead

• What Comes Next?
  • “A year from now these agentic tools will be dramatically better... They will become full-fledged members of the workforce. …a new kind of company [will emerge] with A.I. work at the center of it.” – Kevin (26:45)
  • Both rapid improvement and unpredictability are signature features—Roose cautions he can’t predict beyond 6 months because of the breakneck pace. (27:30)
• Cautionary Note:
  • “The most we can say right now is these tools are getting better at a very fast and accelerating rate, and... there’s a lot of unknowns about what that will mean for the future of human work.” – Kevin (27:59)

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Notable Quotes & Timestamps

• “Let the vibes do the work.” – Kevin Roose (03:01)
• “You just have a computer that can use a computer.” – Kevin Roose (08:40)
• “My dream, a team of robots.” – Natalie Kitroeff (05:02)
• “I feel pretty blown away... It has a video game on it.” – Natalie Kitroeff (14:41)
• “AI could potentially eliminate half of all entry level white collar jobs within the next five years.” – Kevin Roose quoting Anthropic CEO Dario Amodei (25:23)
• “These AI tools are building versions of themselves. They are starting to improve themselves.” – Kevin Roose (20:25)
• “The most we can say right now is these tools are getting better at a very fast and accelerating rate…” – Kevin Roose (27:59)

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Key Timestamps

• 01:12–03:17 – Vibe coding explained and early experiments
• 04:20–07:04 – Agentic coding & how these tools run “robot teams”
• 07:19–08:56 – Claude Code’s story and viral adoption
• 09:07–14:41 – Live demo: building Natalie’s website (w/ video game)
• 16:15–17:50 – The leap: Why agentic A.I. is a paradigm shift
• 18:31–19:14 – Signs of job displacement in tech jobs
• 20:25–21:35 – Self-improving A.I.; science fiction becomes real
• 24:39–25:23 – A.I. leaders’ warnings about job loss
• 26:45–28:08 – The next year: predictions, uncertainty, acceleration

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Memorable Moments

• Natalie’s delighted awe as her personalized website (with a football game) is built on-air by Claude Code (14:04–14:41)
• The candid discussion of both excitement and anxiety from Kevin about the velocity of change and the lack of predictability (especially 25:38–27:30)
• The clear acknowledgment that for the first time, A.I. is not just a “fancy Google,” but doing real, valuable work autonomously (16:42–17:34)

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Tone & Style

The episode is conversational, playful, and curious (plenty of banter between Natalie and Kevin), but also direct and earnest about the serious economic stakes and uncertainty posed by A.I. advances. The excitement of experimenting with agentic A.I. is tempered by real concern for what it means for employment and society.

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Summary

In this episode, The Daily explores the startling leap of A.I. from simple chatbot to autonomous agent capable of “doing your job”—building real software, automating tasks, and even improving itself at a staggering pace. Host Natalie Kitroeff and tech columnist Kevin Roose offer a behind-the-scenes look at how these new tools work, their rapid evolution, and the implications—both exciting and unsettling—for the future of work. As A.I. edges closer to being a true participant in the workforce, listeners are left to ponder: How fast, and how far, will it go?

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Transcript

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[Natalie Kitroeff]

From the new York Times, I'm Natalie Kitrolev. This is the Daily. On Monday, we looked at the growing pushback against sprawling AI data centers in communities across America. Today, my colleague Kevin Roos 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 ChatGPT. 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 fair to say.

[Kevin Roose]

Well, I am not ageist. 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.

[Natalie Kitroeff]

Thank you for saying that.

[Kevin Roose]

To be this confused by technology.

[Natalie Kitroeff]

Yeah, okay, fair enough. So since then, I did my own research, as any young person working 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 Andrej Karpathy, 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 lunchbox?

[Natalie Kitroeff]

Oh my God, that's amazing. So useful. I want it.

[Kevin Roose]

Yeah, 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?

[Kevin Roose]

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.

[Natalie Kitroeff]

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

[Kevin Roose]

Kevin 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 out hours or sometimes even days to do. And so they are working their way up into the entry level 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 like 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 ChatGPT. They have a new agentic coding system called Codex. 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. Claude 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, 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 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 Czerny 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 Claude 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. Started with the engineers. They're saying, this is really great for. 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. It's sort of like you just have a computer that can use a computer.

[Natalie Kitroeff]

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 Claude code.

[Natalie Kitroeff]

Okay. This looks technical, though, Kevin. Can I just say this is not my ChatGPT 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.

[Natalie Kitroeff]

Right.

[Kevin Roose]

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

[Natalie Kitroeff]

You're closer to me than them. You're saying.

[Kevin Roose]

I am much closer to you than them. 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 Kitroweff. And I noticed, Natalie, that you don't have a personal website, at least that I could see.

[Natalie Kitroeff]

Correct.

[Kevin Roose]

Do you have one?

[Natalie Kitroeff]

I don't. I'm kind of giving 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 and also cool.

[Natalie Kitroeff]

Sorry. Yeah. Thank you.

[Kevin Roose]

Yeah, 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 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.

[Natalie Kitroeff]

Right.

[Kevin Roose]

All I know is that it's 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 min 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:36. Look at that.

[Natalie Kitroeff]

Wow.

[Kevin Roose]

We've got a little like eagle's 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, which is not a real person.

[Kevin Roose]

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?

[Natalie Kitroeff]

Yeah.

[Kevin Roose]

I'm thinking we should maybe add like an Easter egg to this. Something fun for people who go to your website and really want the full Natalie Kitcharev experience.

[Natalie Kitroeff]

Okay, what's it gonna be?

[Kevin Roose]

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

[Natalie Kitroeff]

Yes.

[Kevin Roose]

Wow.

[Natalie Kitroeff]

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 Tecmo 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 video game is done. Should we go see it?

[Natalie Kitroeff]

Yes, please.

[Kevin Roose]

Okay, so here's Natalie's tech mobile.

[Natalie Kitroeff]

Oh, my God.

[Kevin Roose]

And do you see it?

[Natalie Kitroeff]

Oh, my God. Yeah, I do.

[Kevin Roose]

So it says, press space to hike and arrow keys to move. Okay, so. Oh, we gotta run. We gotta run. Touchdown, eagle.

[Natalie Kitroeff]

Yes. Go, birds. This is incredible.

Wow.

This is like. I feel like I'm gonna draw a lot of people to my new website with this feature.

[Kevin Roose]

Yeah, you're gonna be getting so much traffic.

[Natalie Kitroeff]

Okay.

[Kevin Roose]

So that is Claude code, and that is how these new coding tools work. How do you feel?

[Natalie Kitroeff]

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.

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[Ivan Penn]

Hi, I'm Ivan Penn. I'm an energy reporter for the New York Times. I think a lot of people take electricity for granted, but it's an essential piece of some of the biggest stories right now. The rise of artificial intelligence, the threat of climate change, and the real challenges that everyday people are facing with increasing electric bills. I spend my days talking to experts, sometimes traveling to really remote places and investigating the role that energy plays in these huge issues. I'm just one of hundreds and hundreds of journalists at the Times, experts in what they cover, who carry the same level of commitment to their reporting. And that's the beauty of the New York Times. We're all working together to help you better understand and make sense of the world today. So if that sounds like something that connects with you and you're not a subscriber yet, you can go to nytimes.com subscribe.

[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 ChatGPT 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, ChatGPT 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.

[Natalie Kitroeff]

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?

[Kevin Roose]

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.

[Natalie Kitroeff]

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.

[Kevin Roose]

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. 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 to it works. You can go visit it on the web. It has a playable video game inside of it.

[Natalie Kitroeff]

Right.

[Kevin Roose]

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 useful.

[Natalie Kitroeff]

Well, can you just tell me quickly, like what's making this improve so quickly?

[Kevin Roose]

So part of it is just that the models themselves, the things that are sort of underneath tools like Claude 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.

[Natalie Kitroeff]

What, what does that mean?

[Kevin Roose]

So OpenAI's latest coding model, which is called GPT 5.3 Codex, 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, so.

[Natalie Kitroeff]

AI models making AI models, just to be clear about what we're saying here.

[Kevin Roose]

Yes.

[Natalie Kitroeff]

Is that scary to you?

Because it gives me the vibe of a sci fi reality.

[Kevin Roose]

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 of 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, we are right to be paying attention to this, and I think it's irresponsible to sugarcoat what's happening.

[Natalie Kitroeff]

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, and with that, the potential for real job loss. So any way 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 ChatGPT, 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 writ 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]

Mm.

[Kevin Roose]

And it could be that these tools just never wipe out millions of jobs en masse. But the AI companies and the people who run the companies are increasingly worried about this. So Dario Amade, 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 five years.

[Natalie Kitroeff]

Wow.

[Kevin Roose]

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.

[Natalie Kitroeff]

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 because it's letting them 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 six 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 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.

For more on the latest developments in agentic coding, listen to Hard Fork wherever.

You get your podcasts. We'll be right back.

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[Kevin Roose]

We are living in interesting times, a turning point in history.

[Natalie Kitroeff]

Are we entering a dark, authoritarian era? Or are we on the brink of a technological golden age or the apocalypse? No one really knows, but I'm trying.

[Kevin Roose]

To find out from New York Times opinion.

[Natalie Kitroeff]

I'm Ross Douthat, and on my show Interesting Times, I'm exploring this strange new.

[Kevin Roose]

World order with the thinkers and leaders giving it shape. Follow it wherever you get your podcasts.

[Natalie Kitroeff]

Here's what else you need to know.

[Reverend Jesse Jackson]

Today we meet tonight at the crossroads, a point of decision. Shall we expand, be inclusive, find unity and power, or suffer division and impotence?

[Natalie Kitroeff]

The Reverend Jesse Jackson, America's most influential black leader in the decades between the death of Martin Luther King Jr. And the election of Barack Obama as president, died on Tuesday. He was 84.

[Reverend Jesse Jackson]

I know abandonment and people being mean to you and saying you're nothing and nobody and can never be anything. I understand.

[Natalie Kitroeff]

Jackson, who worked closely with Dr. King, became the first black man to mount a major nationwide campaign for president in his 1988 campaign. Jackson turned his own life story, which began in poverty, into a rallying cry for a new kind of Democratic party.

[Reverend Jesse Jackson]

I understand I wasn't born in the hospital. Mama didn't have insurance. I really do understand. Born in a three room house. Bathroom in the backyard, slop job by the bed, no hot and cold running water.

[Natalie Kitroeff]

In one of his most famous speeches delivered at the Democratic national convention in 1988, Jackson declared that his life experience had taught him that what bound working Americans was not party nor race, but the shared experience of struggle.

[Reverend Jesse Jackson]

I'm a working persons person. That's why I understand you. Whether you're black or white, I understand the word.

[Natalie Kitroeff]

Jackson won almost 7 million votes in the Democratic primary for president.

[Reverend Jesse Jackson]

I was born in Islam, but Islam was not born in me.

[Natalie Kitroeff]

He failed to win the nomination, but he'd cemented his place as a defining figure in American public life.

[Reverend Jesse Jackson]

You can make it. Hold your head high, stick your chest out. You can make Gets dark sometimes but the morning comes don't you surrender? Suffering frees character. Character frees faith. In the end, faith will not the support. We must never surrender. America will get better and better. Keep hope alive Keep hope alive Keep hope alive on tomorrow night and beyond.

[Natalie Kitroeff]

Today's episode was produced by Nina Feldman, Ricky Novetsky and Olivia Natt, with help from Devin Greenleaf and Mustafa Mirza. It was edited by Brendan Klinkenberg, Paige Cowett and Lisa Chow, contains music by Diane Wong, Dan Powell and Will Reed, and was engineered by Chris Wood. That's it for the Daily I'm Natalie Kitroweff. See you tomorrow.

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