AI in the AM — Week 1 Highlights (June 2026)

**Erik Torenberg** (0:00)
The Cognitive Revolution is brought to you by Mercury, the fintech that more than 300,000 ambitious companies and individuals trust to run their finances. Over the last few months, I have made tremendous strides with my personal AI infrastructure. Today, I've got high context instances of both Claude Code and OpenClaw running on a Mac Mini, and it's amazing what they can do. However, until getting started with Mercury, I didn't have a great way for them to pay for things. I didn't want to give them unrestricted access to my money, but my old bank didn't give me any other options. With Mercury, I can create as many virtual cards as I want, each with its own daily, weekly, or monthly spending limit, and I can lock any card to a single category of purchase or even a single merchant. Now I have a card that my agent can use to buy our family's groceries, and only our groceries, and I can create another any time I want to give an agent a random one-off project that might require making a purchase. This is honestly just the start of Mercury's AI-friendly offerings. Does your bank offer API keys, an MCP, or a CLI tool? If not, check out Mercury at mercury.com. Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column NA., members FDIC. Thank you to Mercury for supporting The Cognitive Revolution. And now, on with the show.
Welcome to The Cognitive Revolution, and to a new experiment we're calling AI in the AM. Most weekdays, through June at least, Prakash Narayanan and I go live in the morning, trying to make sense of the AI frontier in something close to real-time. Then we cut it down to this, a highlights edition, built for people who are really close to this stuff, but already overwhelmed. And I'll be up front, this whole thing is an experiment. The studio we broadcast from, Prakash Vibe-coded it. The booking, the research, the clipping, those are AI skills we refine as we go, and we plan to publish them in all sorts of artifacts as this matures. Which, it turns out, is the story of the week. The Frontier Labs are running away with everything, and increasingly, they seem a little scared of their own progress. OpenAI is publicly asking for independent review of models. At a closed-door event on recursive self-improvement, people from multiple labs agreed a coordinated slowdown might one day be necessary. And our conversation with OpenAI's forward-deployed engineers showed how almost mundane this has become. Walk into a tax firm, stand up a thin scaffold, capture where it's wrong, and let the model rewrite its own scaffolding, correction by correction. That's the whole loop, and it climbs the hill astonishingly fast. So when the harness is that cheap to build, the real question becomes, what around the core intelligence is still safe? That's the lens for this week. And please, tell us what's working and what isn't. We mean it. This only gets good with your feedback.
Start with a day I spent inside a closed-door event, full of people from the Frontier Labs, all of whom think self-improvement is close and is the plan. Here's the honest version of what they believe and what they don't.
So this was called recursive. It was premised on the idea that recursive self-improvement seems to be coming pretty soon. It is increasingly the explicit plan of at least Anthropic and OpenAI, and Google did mind to some extent, although they kind of waffle on it a little bit more, as OpenAI has publicly put forward timelines of later this year for an ML research intern and early 2028 for the full AI R&D researcher that they hope will perform on the level of their human researchers. So the kind of basic theory of change there is a pretty obvious one, but we're stating that today they may have a thousand or a couple thousand people that they would really consider to be top-notch ML researchers. If they can get that same level of performance from models on chips, then they're only limited by the amount of compute that they can throw at it. Obviously, they're building out a lot of compute, so presumably they could throw a million human researcher equivalents at problems.
By the way, you may have noted they run faster and they run 24-7.
The hope is that this will allow them to move much faster than they have moved and pull away from the competition.
I would say most people at that event thought that that was very credible. There was not too much debate around will this move off? Now, obviously, there's some selection effect there. But you could just go to the whole event was under Chatham House rule, so I will respect that and not attribute specific statements to specific people or organizations. But you could go to the recursive website to look at speakers, whose identities were shared obviously with their permission. And you've definitely got some notable people from the frontier companies. So these were not people that are fringe or you would say, likely don't represent mainline views at the companies. It really seemed that the expectation is, yes, this is going to work. It's going to have a major accelerating effect. We don't necessarily know if it's going to have a simple accelerating effect, like in a human organization, if you went from 1000 to a million researchers, you probably wouldn't get 1000x output. So there may be some sort of coordination challenges or just kind of duplication challenges that we see in human organizations. Maybe that happens in the same way. That's one possibility where you still get acceleration, but it's not a blinding kind of takeoff acceleration. Or I would say also understood to be a credible, realistic possibility was that it is even a more profound phase change than that. And things like pre-training just become dramatically more efficient, and models suddenly have all these new qualitative abilities that they didn't used to have, such as, continual learning that really works or what have you. And so everything could change in a very dramatic way, potentially very quickly once these milestones are hit. In the room, people said, and there was quite a distribution, I was pretty much right at the median when we were asked, how many copies of you would it take to do the work that you are currently doing with the benefit of AI? The median answer was basically two. In other words, people felt like they're getting two times as much work done thanks to AI. But that was also framed in an interesting way where it was like, but note that as of today, at least, if you were not there, your productivity would drop to close to zero. Not too many people felt that they had any system that would continue to work in any meaningful way if they were entirely removed from the picture.