Kevin, thank you so much for being here.
Katie, thank you for having me. Nice to see you again.
So you and Casey recently announced that you were launching a new media company called Machine Gods Media, not to be mistaken for your podcast of the same name minus the media. "Machine Gods" the podcast, Machine Gods Media, the company, correct?
Yeah, a name so nice, we used it twice.
There you go. So when you first announced that you'd be leaving The Times, you described your vision for what you wanted to do as one that, quote, "Takes AI progress seriously, is clear-eyed about the capabilities and risks of powerful AI systems, and tries to empower and entertain people in the face of radical uncertainty." I'm curious, as you look at sort of the landscape of tech coverage, of AI coverage, what's missing from the reporting and commentary that you and Casey feel like you can address, that you want to address with the new show?
We just feel like it was high time that two men had a place to talk about AI.
I've been saying this for years. I want more men.
No, look, I think there are obviously no shortage of podcasts, and YouTube shows, and mainstream media coverage of AI. It's the biggest story in the world right now. But when Casey and I looked out at the media landscape, we saw some issues. One was, there are people who just are getting very famous and having a lot of success saying that all this AI stuff that's going on is fake, it's hype, it's a giant financial bubble. No one is using these tools. They're not going to have any impact on the economy. You know, OpenAI is going to go bankrupt, Anthropic's going to go bankrupt. But basically this is sort of a genre of popular criticism and it's not just a few people. This is now, I hear this from friends of mine who don't pay close attention to tech news, and just assume that what's going on is just fleeting, and trivial, and that it will all sort of go back to normal soon. But there's another genre of AI coverage that is purely hype. It's look at the 17 amazing ways that the new version of Claude can supercharge your enterprise SaaS business. And you can go on LinkedIn and just see like example after example of people who are just purely excited about this technology and don't really care to talk about the risks. And we both thought there's like a large gap in the middle for what Casey calls AI realism, which is basically this idea that you can take AI seriously, acknowledge that the tools are powerful and impressive, and in many cases dangerous, and that you can help people understand that and demystify this area without sort of slipping into boosterism, and that you can also have a good time while you do it. We don't want this to be just a dour take on AI doom. We want to actually give people a good experience and have a good time.
I have to ask, the show, you announced recently, is being published in partnership with NPR. Why NPR? Why was that the right partner?
A bunch of reasons. Both Casey and I are big fans of NPR. We like the fact that they have a broad independent reach and mandate. We like the fact that they're going to let us own the show, and make the creative decisions, and it will be a distribution partnership rather than like a full acquisition. So we will still have some operating distance. We think this is a really critical time and a really important story. And we like the idea that people might be in their cars just listening to their local NPR member station and happen on our podcast. And maybe that's going to be someone who works in policy, or maybe that's going to be someone who is involved in local government, maybe that's going to be someone who has a very different point of view on AI. We don't just want to have the sort of opt-in, self-selected tech audience listen to us.
Now I am going to ask you a gauche question. A Bloomberg report recently said you both were fielding offers of up to $5 million for the show. I have to admit that link did travel through Wired's slack at rapid clip. [Kevin and Katie laugh] It's a startling sum of money. Kevin, how much you making here?
It's not $5 million, I'll tell you that.
It's not? Is it more? It's more? [Kevin laughs] It's more than $5 million?
I mean, look, they made us a good offer. We could have gotten more money elsewhere.
I mean, that's kind of what I was wondering. When I heard NPR, I thought to myself, there's no way NPR is giving those guys $5 million, with all due respect to NPR.
It is not traditionally where people go to get rich in media is to public radio. They made us a very good offer. We loved their new chief content officer, Nadine Zylstra. She's just a total force of nature and we're very excited to work with her. And we just thought they had a lot of things to offer us, beyond just money, like their distribution on radio. People don't realize how big radio still is. The reach of radio, and especially public radio, is still quite large. We've had this show, "Hard Fork," for the last four years. We built up a pretty good size audience, but The Times owned that show.
Owns the feed. So we are looking to grow our show as quickly as possible, and we just thought that the combination of NPR's like commitment to journalistic excellence, their long history, their wide distribution, and their investment in helping us grow the show was the right combination of factors.
This brings me to one more question that I'm so curious about. The idea that a great reporter, a great commentator, can spend time somewhere that's sort of, quote unquote, "traditional," like the New York Times. They can build a brand, and then they realize that they can just go do it themselves, and they don't actually need that institution anymore to exist in the world as talent, and to make, often, a lot more money than they would in traditional media. What's your take on that?
I don't have anything bad to say about the New York Times. I had nine wonderful years there. It was my second stint at The Times. So I've spent like the vast majority of my career at the New York Times and inside these big media institutions. I do think we are entering this moment where, at least for some portion of the audience, they want to connect with individuals more than institutions. We have just seen this in wave after wave. I am not doing this for ideological reasons. I'm doing this because I thought it was a really exciting opportunity. But I do think that organizations that want to retain and attract very talented people will just need to be more flexible about the kinds of arrangements. Some people aren't going to want to give up their Substacks and go inside a media institution. Some people aren't going to want to sort of have all of their work published by sort of one publication. They'll want to do some things for one place and a few things for another place. And so I think there are some media organizations that are starting to experiment with different, more flexible ways of, I don't know, bringing people in part way, or having them sort of maintain their independent operation, but also contribute on an ongoing basis. I think there are a lot of ways this can work, but I think it all has to start from a recognition that like the journalistic career path, where you like go in in the mail room, and you work your way up, and you spend 25 years at the same employer, and you eventually become an editor, and then a manager of editors, like that has broken down. And that is regrettable. I don't think that's a good thing that it's broken down, but it has broken down. And so I think institutions should grapple with the fact that there's now a generation of media entrepreneurs who just don't really find what they have to offer all that appealing.
When you think about the talent piece of that, when you think about AI, are you optimistic about journalism and the industry of journalism?
I am very optimistic about the application of AI to journalism. Like that is one place where I have wanted to do more experiments, not with having AI write for me, or do all my reporting, but like ways of extending journalism using AI.
What's an example of an experiment you would love to do?
I have colleagues, former colleagues at The Times, who have done incredible sort of document analysis on a scale.
That wouldn't have been possible before. Using satellite imagery to tell whether a munitions factory has moved, or something like that. That's the kind of thing that I don't do much in my own life, but that I would like to see other organizations trying, because I think that's really cool. I have used AI to research, and edit, and improve my own work for months now. I have found that very helpful. I think the caliber of my work is better. And I would love to see more institutions in media experimenting with using these tools to improve the output of their journalists, not just like filling their websites with slop, but like actually helping these be tools to make journalists better.
I want to talk about your book. So "The AGI Chronicles," which I have read, it is hugely compelling. And I'm curious, when did you decide, when did you have that moment where you said, "This is a book. Like I'm going to commit years of my life and my career because there's a book here." What was that moment for you, when you realized that this was a, you know, a big fucking deal?
I know exactly what it was. It was early last year, 2025, and I was in the car on the Bay Bridge, stuck in traffic, and I was sort of zooming around from like thing to thing. And it just kind of hit me like an epiphany. It was like, I have been following this story in all the incremental detail for years now. I've interviewed all the major AI researchers, and CEOs, spent time with the papers. I've gone to all of the companies and reported on what they're doing. But I sort of realized that there was this larger story that I was missing, that I hadn't really zoomed out and tried to take a more panoramic view of something that was just weird. Like it was, it's a weird story. And I felt, living in the Bay Area, being immersed in San Francisco tech culture, I had kind of gotten acclimated to that. And it no longer seemed as strange to me that there were these companies racing to build the machine super intelligence that could either save or destroy humanity. And I feel sometimes like I am in Los Alamos, New Mexico in 1943 when like the Manhattan Project rolls into town, and I've just kind of got like my lawn chair, and I'm just kind of looking at the trucks rolling in and trying to make sense of what's happening. But of course, all of this is going to be important. I believe that this technology is important, and that the people and the companies who built it will be important historically. And so when I thought about like, who is actually doing the work of like writing all this down? It was nobody. Nobody was doing it. And I just felt like, I think it would be a tragedy if all this just kind of disappeared in a bunch of Signal messages and Slacks that auto delete. And if we just sort of end up with no durable historical record of this really strange decade in AI, when things went from not working at all to like threatening the future of humanity. So that was the job I tried to do. I spent about a year reporting and writing. I talked to more than 150 people. I should have probably taken more time, because it was very hard and intense. But I think what came out of it was like exactly what I tried to do, it was like, make an artifact that people, and future AI systems can look back at to say, "Here is how this happened. Here's who made it happen. Here were the key decisions and moments along the way."
And the book follows three key companies, OpenAI, Anthropic and Google in their sort of pursuit of this technology. I'm curious, what were sort of your big picture learnings about those companies, and sort of the key differences between them that you think it's important for people to know?
Yeah, I mean, the companies are very different from one another, both in the sort of makeup of their personnel and also in their ambitions. Let's start with Google, because they're the oldest. They have had, for decades now, an advanced AI research effort, but they were pioneers in AI. They developed the transformer, which is the T in ChatGPT, the sort of foundational technology that all of this other stuff rests on. And then there were these two guys, Elon Musk and Sam Altman, who got very worried about how well they were doing, about the fact that Google and DeepMind were racing ahead, and they decided to start OpenAI to.
So funny to imagine that now. [Kevin laughs]
I mean, it's wild and we have the emails. Like it's all there in the record, where they're basically like, we have to start a lab that's going to sort of beat them, or at least challenge them, so that they don't kind of run away with the whole game. So they start OpenAI, and they do a couple years of that, and then this guy at OpenAI, Dario Amodei, he takes six of his colleagues, and they leave and start Anthropic, basically to make sure that OpenAI doesn't get to the critical threshold of AGI first. So the whole industry sort of spawned out of itself. These people all used to work together, and now they run these companies that are, in some ways, mortal enemies. Like I was shocked. This was actually my biggest surprise was I thought this was more like Coke and Pepsi. This is not a buddy-buddy industry. This is like a blood feud.
From all of the reporting that you did, who do you trust? Who do you trust with our future in the context of artificial intelligence?
I don't trust any single person.
But I think what I learned through reporting this book is like, these are people. They are flawed, they are fallible. Their motives are never 100% pure. Some of these people are quite nice. Some of them are very thoughtful. I think we have, in some ways, gotten very lucky with the people who are running these AI companies who I think are, on the whole, much better suited to build powerful technology and release it into the world than like the social media barons were. I think they are.
You see a marked difference between sort of the Facebook era and this AI era?
Oh yeah, I mean, I think, for one, they are just way less naive. The social media guys came in and they said, "We're going to change the world. We're going to free communication from sort of the bottlenecks that hold it back. We're going to distribute the benefits of technology to everyone." And they really didn't start thinking about the problems until they were being questioned in front of Congress.
I mean, I will say, some of these AI guys talk a lot about saving the world. They talk a lot about how great this will be for humanity. You know what I mean?
If you go back and look at like the founding emails of OpenAI, they have been very consistent that they think this is a potentially very dangerous technology. Now, they're racing toward it, so maybe their words don't mean that much, but I think you can't accuse them of being naive, because they just have such a long track record, all of them, of saying that, "Yeah, this could be great for humanity, but it's not a given that it will be, and we need to build it really carefully and thoughtfully to make sure that it's actually going to turn out well for us."
