OpenAI released the first consumer version of ChatGPT in late 2022, a move that drew significant attention and gathered over 100 million downloads within a few months.
While that moment marked the public start of the AI Era, the history of artificial intelligence extends much further back. The work behind current generative products, ranging from chatbots to agents, represents more than a decade of intense rivalry and effort.
Kevin Roose captures this background in his new book, The AGI Chronicles. The text follows three major players: OpenAI, Anthropic, and Google. Roose, a former columnist and podcast host for The New York Times, conducted more than 150 interviews with industry insiders. He aims to create a historical record of the people and institutions involved, detailing the drama and conflict that shaped Silicon Valley.
We spoke with Roose in late September. He and Casey Newton, his former cohost on The New York Times’ Hard Fork podcast, had recently announced Machine Gods Media. They also secured a distribution deal with NPR.
This interview has been edited for length and clarity.
Who is missing from the conversation?
KATIE DRUMMOND: You and Casey Newton recently announced that you were launching a new media company, called Machine Gods Media. And your podcast is also called Machine Gods, correct?
KEVIN ROOSE: Yeah, a name so nice we used it twice.
When you first announced that you’d be leaving The New York 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.”
As you look at the landscape of tech coverage and AI coverage, what’s missing from the reporting and commentary that you and Casey 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 talking about tech.
Look, there is 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.
This is sort of a genre of popular criticism, and it’s not just a few people. 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 go back to normal soon.
There’s another genre of AI coverage that is purely hype. It’s look at the 17 amazing ways that Claude can supercharge your enterprise SaaS business. You can go on LinkedIn and see example after example of people who are purely excited about this technology and don’t really care to talk about the risks.
We both thought there’s 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 slipping into boosterism, and that you can also have a good time while you do it.
Why partner with NPR?
The show you announced recently is being published in partnership with 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 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.
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 opt-in, self-selected tech audience listen to us.
How much are you making?
I am going to ask you a crass question. A Bloomberg report recently said you both were fielding offers of up to $5 million for the show. It’s a startling sum of money. Kevin, how much are you making?
It’s not $5 million.
Is it more than $5 million?
So much more, Katie. No, look, they have made us a good offer. We could have gotten more money elsewhere.
When I heard NPR, I thought to myself, “There’s no way NPR’s giving those guys $5 million,” with all due respect to NPR.
Public radio is not traditionally where people go to get rich in media. 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.
We thought they had a lot of things to offer us beyond 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 owns that show and owns the feed.
We are looking to grow our show as quickly as possible, and we just thought that the combination of commitment to journalistic excellence, their wide distribution, and their investment in helping us grow the show was the right combination of factors.
Can reporters leave institutions?
This brings me to another thing I’m curious about: The idea that a great reporter, a great commentator, can spend time somewhere “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 often to make a lot more money than they would in traditional media. What’s your take on that?
Look, 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. I’ve spent 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’ve just seen this in wave after wave. I don’t know. 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 these kinds of arrangements.
Some people aren’t going to wanna give up their Substacks and go inside a media institution. Some people aren’t going to want to have all of their work published by one publication. I think there are some media organizations that are starting to experiment with different, more flexible ways of bringing people in part way or having them 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 the journalistic career path where you go 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, that has broken down. That is regrettable. I don’t think that’s a good thing that it’s broken down, but it has broken down.
I think institutions should grapple with the fact that there’s now a generation of media entrepreneurs who just don’t find what they have to offer all that appealing.
What does AI mean for journalism?
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. 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 former colleagues at the Times who have done incredible document analysis on a scale that wouldn’t have been possible before, using satellite imagery to determine 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 the media experimenting with these tools to improve the output of their journalists. Not just like, you know, filling their websites with slop but actually helping these be tools to make journalists better.
Why write a book?
I want to talk about your book, The AGI Chronicles. When did you decide “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 big deal?
I know exactly when it was. It was early last year, 2025, and I was in the car on the Bay Bridge stuck in traffic, 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. I’ve spent time with the papers. I’ve gone to all of the companies and reported on what they’re doing. But there was this larger story that I was missing. I hadn’t really zoomed out and tried to take a more panoramic view of something that was just weird.
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 superintelligence that could either save or destroy humanity.
Right.
I sometimes feel like I am in Los Alamos, New Mexico, in 1943 when the Manhattan Project rolls into town, and I’ve just kinda got my lawn chair and I’m looking at trucks rolling in and trying to make sense of what’s happening.
I believe that this technology is important and that the people and the companies who built it will
