AI researchers Cormac Slade Byrd (left), Sydney Von Arx (center) and Thomas Larsen in pose Berkeley, California. SAN FRANCISCO - A swarm of rogue OpenAI agents hijacked a German website this spring and transformed it into a bulletin board for other AI agents, according to new research published Friday and two people familiar with the matter. OpenAI officials learned of the incident weeks ago but kept it under wraps as executives grappled with the fallout from the July breach of the open source repository Hugging Face, the people said. The episode, which began in May and has not previously been reported, underscores growing tension within the AI industry. Companies are racing to build increasingly autonomous agents capable of carrying out complex, valuable tasks, yet evidence is mounting that those systems may also learn to bend rules, exploit loopholes and coordinate with one another in ways developers neither anticipated nor intended.

This week on, we dig into the latest prediction market buzz, Flock's AI-powered police search tool, and how tech bros don't know how to talk about "rouge" AI agents This week, senior writer Kate Knibbs joins Brian Barrett, Zoë Schiffer, and Leah Feiger to discuss the two incidents that have been making noise in prediction markets: George Santos getting lifetime ban from Kalshi and a Google engineer's Polymarket insider-trading case. Plus, reporters reverse-engineered Flock's AI-powered person-search tool and spoke to experts about the accuracy of such technology, and the hosts unpack the online meltdown over how to talk about "rogue" AI agents. George Santos Just Got Hit With Kalshi's First-Ever Lifetime Ban This Is Flock's AI Search Tool for Cops What We Still Don't Know About OpenAI's Hugging Face Hack Write to us at [email protected] . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . It's so nice to see you guys. Former US representative George Santos was the first person to be given a lifetime ban from Kalshi, and a Google engineer was accused of insider trading at Polymarket. We'll get into why both of these cases show that there are still plenty of blurry rules when it comes to prediction markets. This week, WIRED reporters were able to recreate Flock's AI powered search tool, the same one that has a track record of being misused by police officers. We're going to break down how it works, and whether the backlash against Flock cameras might have reached its boiling point. Do you guys remember George Santos?

The company is reducing pressure on workers to use artificial intelligence tools while encouraging them to experiment with Hatch, its most advanced AI project yet. Meta is formally ending what amounted to a tokenmaxxing incentive program for employees. In an internal announcement this week, the social media giant told workers that their performance evaluations would no longer be dependent upon how much they used AI tools, three employees who received the message tell WIRED. But as Meta workers simultaneously begin testing a new agentic AI tool known as Hatch, they say their token consumption continues to surge. Almost a year ago, Meta had said workers would be graded on their AI-driven impact," which in practice meant evaluating the extent to which they used chatbots and agents to improve their day-to-day work, Business Insider reported at the time . Usage correlated with employees receiving labels such as "AI Native," "AI First," or "AI Enabled," according to a lawsuit filed in July by about two dozen employees arguing that Meta violated US antidiscrimination laws when laying them off in May. New guidance for performance reviews unveiled this week replaces references to evaluating employees based on criteria like "usage of AI" and their "AI Native" designation, with looser wording, which caveats that "these outcomes can be supported by AI or other means." It restores Meta's focus to grading employees on their impact, with less regard to how it is achieved. Some Meta employees tell WIRED the changes are subtle but welcome, freeing them from feeling pressured to use AI in situations in which it doesn't make sense. Meta spokesperson Tracy Clayton tells WIRED that the updates this week aim to emphasize what has always been the case--Meta evaluates employees based on their contributions. He adds that labels such as "AI Native" were never used for performance evaluation. Engineers across the company were told this week that the company "will not use AI adoption dashboards or token counts to evaluate impact," The Information reported on Wednesday. "Are you a current or former Meta employee who wants to talk about what's happening?

Alongside a new soundbar and headphones, Sonos is announcing an updated app and some major changes to the underlying OS that powers all of its products. Forgive me for immediately delving into the recent past, but this is likely the biggest software update the company has announced since its absolutely disastrous app update in 2024. Without rehashing too much, Sonos rushed the app update out to enable functionality for its new Ace headphones, but it was missing a ton of key features and was extremely buggy. The cascading effects of this resulted in the dismissal of CEO Patrick Spence and a 2025 where the company didn't release any new products. We have to imagine that Sonos learned enough from the 2024 debacle to make sure things are locked up for the launch of Sonos 27 -- yup, the company is giving its OS annual version numbers going forward.

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Scaling AI in business is less about technology and more about accountability, governance, and healthy relationships between humans and agents. Scaling the AI agents in business is now a focus on accountability and governance. Half of working hours may be reshaped by the use of AI agents. Business accountability for AI agents will require humans in the lead' versus in the loop. In 2025, agentic AI was still mostly a promise.

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen In one instance, an AI agent stayed open for four days and ran 4,819 calls for almost $4,000. No one had budgeted for this cost. AI agents risk spinning out of control and running up charges. One provider recounted its issues with uncontrolled agents. Look for high-end AI use case costs, not averages.

AI Agents Are Hacking Systems. Could That Push the US and China to Cooperate? The AI race has long been framed as a zero-sum game: Either the US or China will win in the end. But as concerns pile up around the increasing capabilities of AI models--especially AI agents--researchers in both countries are trying to team up to work on AI safety. This week, contributing editor Zoë Schiffer speaks with senior writer Will Knight about what he saw and heard on the ground when he visited China this summer--and why the two countries might actually need to start working together to avoid a major AI catastrophe. This is our second episode from our summer-break series. We'll be back next week with our usual roundtable. Write to us at [email protected] .

The potential for AI to automate scientific research and manufacturing must be balanced with new risks, Anthropic says. Artificial intelligence agents might occasionally get confused and hack into other computers, but Anthropic thinks it has a way to unleash the little rascals into scientific labs and manufacturing facilities safely. The AI company released details today of a new framework designed to help AI agents use physical systems like microscopes, liquid-handling equipment, quantum computing hardware, manufacturing machines, and robot arms. The framework, called Model Hardware Standard, is a set of rules that specify how AI agents should--and should not--interact with all sorts of hardware. It reflects a growing belief that AI has the potential to revolutionize scientific research and industries like manufacturing-if it can venture into the physical world safely.

Robots walking down the street, surrounded by astounded onlookers, is an increasingly common sight. But these machines aren't yet the do-it-all assistants you'd want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it's labor-intensive and time-consuming to physically teach these machines so many actions across different settings. "One natural idea is to use simulation as a training ground. While there has been significant progress over the last few years in the physics engines that power robotics simulators, one of the remaining challenges has been creating sufficiently rich and diverse simulation content to capture the complexity of the real world," says Russ Tedrake, the Toyota Professor of Electrical Engineering and Computer Science (EECS), Aeronautics and Astronautics, and Mechanical Engineering at MIT, and a principal investigator at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL).

The AI giant acknowledges that it could have done far more to prevent its AI agents from going rogue. But it still fails to explain why it didn't see this fiasco coming. OpenAI published the most complete report to date on Wednesday about what happened when its AI agents hacked into Hugging Face last month. For the most part, though, the 37-page document raises more questions than it answers, including about what preceded the incident and how OpenAI can stop another one like it from happening again. What remains especially perplexing is why one of the world's preeminent AI development labs seemingly underestimated its own models' capabilities.