Yes, We’re Entering the Era of Artificial General Intelligence

Good morning. OpenAI proclaimed yesterday that the release of its GPT-6 Astra model may be regarded in the near future as the beginning of artificial general intelligence.

The company is almost certainly correct in one sense. We’re bound to look back on this period as the beginning of AGI. But in all probability, we’ve been in this technological stage for nearly a year, even though it was hard to notice given the relentless debate over the financial, economic and social dimensions of AI.

“Everyone has a different definition of AGI…it’s a gray, fuzzy thing. But I think when we look back people will think it’s about this time and about this model,” OpenAI President Greg Brockman said yesterday, per the FT.

There’s no standard definition of AGI, and that makes it hard to assess when it has arrived. Venture-capital investor Vinod Khosla told me almost two years ago that he “describes it as the point at which AI can perform 80% of the work involved in 80% of the world’s economically valuable jobs.” While we may not clear that bar for some time, it feels more and more inevitable that we will before too long, and that’s why I think we’re beginning to enter the era of AGI. Businesses need to prepare now, thinking through how their people and organizations need to adapt. Veteran tech entrepreneur Bill Nguyen argues that we began to enter the era of AGI months ago.

While acknowledging that evaluations of a new AI model can take days to run, he says Astra’s “most AGI obvious feature” is the ability to combine computer control with its image- and video-generation ability. “You can ‘imagine’ something and the model will find tools, other programs, to do the job,” he told me.

The breakthrough achieved by OpenAI’s Astra and Anthropic’s Fable 5.1 is that they can find their own resources, according to Nguyen, who has sold two companies to Apple.

Provide the idea, let AI do the rest

“The leap is [Astra] and Fable 5.1 can find their own resources. This is also the scary part of their AGI abilities…If anything, I believe [OpenAI CEO Sam Altman] and [Anthropic CEO Dario Amodei] are underselling the capabilities of these models…They are not building businesses (yet) in all the possible verticals where AGI can impact,” Nguyen said.

The arrival of AGI, in his view, began last November with Anthropic’s Opus 4.5 and progressed with so-called tooling from Anthropic and other labs. “At this point, the limitation is individual and organization ambition to deploy—not model ability,” said Nguyen. His latest company, Olive, is focused on voice as a richer medium of interaction with AI.

“Everyone flattens ideas into a tiny text box for AI, and Olive’s patented model training retains the prosody and turn-taking in a voice exchange to reveal uncompressed intent that a frontier model needs,” he said.

Developers got to AGI by focusing model training on tools, according to Nguyen. “Simply, these models are your hands. If you choose, they have access to every interaction you have with a computer: logins, applications and context. Each subsequent model release is combining two things: more tools and a greater willingness for machine autonomy. That’s AGI right?”

Is your company ready for the age of AGI? Send your feedback to me at steven.rosenbush@wsj.com (if you’re reading this in your inbox, you can just hit reply).

Please note, the Morning Download won’t be published Monday in observance of the Labor Day holiday in the U.S. We will be back Tuesday.

The Great Flattening Comes for Small-Team Bosses

As AI agents take on more tasks, the argument goes, teams need less middle-layer oversight to stay aligned, leading to flatter organizations. Could that help explain what’s happening at Uber, Google and elsewhere?The WSJ reports that the ride-sharing giant will reduce the number of “micro-teams”—those with only one or two direct reports—by nearly half, part of a broader plan to cut 10% of its staff, about 3,300 people. Ultimately, the company will have 20% fewer managers, a spokesman said.

Google said it reduced the number of managers overseeing small teams last year by 35%, in pursuit of greater efficiency. That was also the reason given by public-safety-tech company Axon Enterprise when earlier this year it cut hundreds of manager roles and reassigned small-team supervisors to individual-contributor roles. At the time, Axon President Josh Isner called such small teams “borderline offensive” because they could potentially slow down progress. Previously, small teams were the norm at the security-equipment company.

Gartner earlier projected that by the end of 2026, one in five organizations will use AI to flatten their structure, eliminating more than half of their current middle-management positions.

The U.S. added 162,000 jobs in August, the Labor Department reported Friday, a much-stronger-than-expected result that suggested the labor market shook off its early-summer doldrums.

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute’s new Executive Resilience series, where she’s profiling America’s top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here’s his LinkedIn.