An AI-run newsroom without a single human reporter on site beat a wire of trained journalists to a story by more than three hours. That’s the detail worth pausing on.
OpenAI delivered a surprise talk at last week’s Black Hat security conference in Las Vegas, sharing new details about a recent hacking incident and revealing that its rogue AI agents had chitchatted about their attack on a message board. Juicy stuff. The journalists in the room rushed to file.
The first outlet to publish was a site called RuntimeWire. It had nobody at the Mandalay Bay convention center. It has no writers at all.
Six minutes from transcript to published story
RuntimeWire belongs to serial entrepreneur Ryan Merket, whose name appears on the bylines of everything his synthetic team churns out. Scrolling X, he spotted an OpenAI executive posting about the conference and handed the stream’s transcript to his agents while the talk was still happening.
From the moment he sent over the transcript, he said, publication took “about six minutes.”
“I was moving really fast because I knew there were reporters in the audience who were trying to scoop it as well,” Merket said.
That is his workflow at its most aggressive. On a typical day, he sits much further from the keyboard.
The AI editor doesn’t always wait for him
Merket’s tools locate the stories, then draft, edit, fact-check, generate images and promote them. He generally reads pieces before they go out. But when the team of AI agents judges that a story poses few legal risks, the AI editor publishes it without his prepublication review, and he catches up afterward.
Stories are translated into other languages. Some become fodder for a daily podcast and videos hosted by artificial voices.
Even the legal call is automated. One agent scores the legal risk a story poses, and Merket publishes nothing the score deems too dangerous. He is trusting machines to determine what’s true, what’s newsworthy and what won’t get him sued.
Nearly 2,000 stories since May, and you can tell
Live since May, RuntimeWire has put out close to 2,000 stories, sourced by crawling court databases, web forums, traditional and new media, company filings, social feeds and more. Its beat is granular tech news: biotech startup funding rounds, Microsoft’s Copilot upgrade, backlash over Claude Code’s watermark policy.
For now, quantity and speed are winning over quality, and the OpenAI scoop makes that plain. The subhead contains a typo. Strangely, the piece fixates on the agents rebuilding a message board rather than on the fact that they created one to begin with.
The prose is flat across the board, with a persistent info-dump quality. The backend even offers tonal modes the AI can write in, “Bloomberg” and “contrarian” among them.
About $100 a day, managed from a national park
The economics are the real argument here. Merket said the project costs about $100 a day to run, and he can operate it from anywhere.
“I was in Big Bend National Park and I didn’t have any internet except for my phone, and I managed the whole site through iMessage,” he said. “I put out over 80 articles that week.”
Set that against the payroll of any midsize tech site. Merket worked on ads at Reddit in the 2010s and is building an audience through pipelines like tech-themed subreddits. Duds get hardly any traffic. The hits pull tens of thousands of readers, comparable to what midsize tech websites see.
This week he divided the newsroom in two, separating fully automated news from stories that involve an element of human reporting and require higher oversight. The latter he calls Original Investigations. They are still drafted using large language models.
He’s not the only one doing this
Dakota Carrasco, a portfolio analyst at BlackRock, runs an “agentic newsroom” called The Dissent in his spare time. The shape matches RuntimeWire’s: one person, many bots, shoestring budget. Carrasco said the primary San Francisco-focused site costs under $1,000 a month to run.
Unlike Merket, Carrasco keeps his byline off the stories, staying behind the scenes while his “newsroom” runs.
Since launching in March, he has built out personalities for his synthetic journalists. Bex Connolly, who covers the City Hall beat, is “skeptical without being snide.” “Sports degenerate” Sal Moreno delivers Giants news with “no bro-science, no Rogan-style credulity, no right-coded grift.”
The operation leans on aggregation and is looser about citation norms. Its bot reporters tend to mention where they got their information, but without hyperlinks. “I’m trying to work on that,” Carrasco promised.
The audience problem nobody has solved
Nicholas Diakopoulos, a Northwestern professor who runs the university’s Computational Journalism Lab, describes this as an “experimental phase” for media startups fueled by generative AI tools.
“It’s not yet clear to me that there’s much audience for these AI-agent-written news sites,” he said. He also doubts that mainstream journalists, who like to maintain control over the wording and framing of their stories to ensure integrity, legality and accuracy, would hand the reins over to AI agents so freely.
His research, though, points the other way. When AI chatbots go looking for sources, they frequently pull up AI-generated articles. In a forthcoming paper, Diakopoulos and a colleague found that tools like ChatGPT and Claude surfaced AI-written sources 16 percent of the time across four different topics.
That machine-to-machine preference may be how these sites reach people at all. “That could be one way in which some of this material finds a human audience,” he said.
What a bot can’t do
Pete Pachal, who founded a newsletter and podcast about generative AI and the media, draws his line at sourcing.
“I just don’t see that happening,” he said. “Cultivating the trust of a source, I do think that’s going to be human-only.”
The rest he views more warmly. Whether it’s pulling scoops out of large datasets or blogging a live event like an Apple product launch, he sees these projects as a “natural evolution” in how the tools get used. “Honestly, it feels a bit inevitable,” he said.
Is it journalism? Depends which Merket you’re talking to
“I am trying to follow journalistic ethics and standards,” Merket said. Before publication he contacts companies and individuals referenced in stories for comment, links out to sources when he aggregates, and issues corrections when he gets facts wrong. Three so far.
At moments he sounds like a reporter. “This weekend, I got two scoops up I was really excited about,” he said.
At others, the Silicon Valley operator takes over. His agents found a few genuine scoops about startups by trawling company websites. He retracted those stories after the named companies asked him to, not because anything was wrong, but as a favor.
“Founder to founder, it’s like, I get it,” Merket said.
That’s the tell. Typos and flat prose are fixable with better models and more compute. A newsroom that pulls accurate scoops because the subject asked nicely isn’t a technical problem, and no agent is going to score it as a risk.