OpenAI Cofounder Karpathy Says Great AI Agents Are Still a Decade Away. But There's Magic to Be Had in Incremental Work.

The Week in Short

Top AI researcher Andrej Karpathy sees a long road to AGI, even as Amazon robots promise to replace half a million people. The American Medical Association embraces AI, with caveats, as new Menlo Ventures data shows quick uptake by doctors. Relatedly, OpenEvidence raises $200 million. Sesame smart glasses get big dollars too. Sequoia’s COO quit over the firm’s tolerance of what she saw as Islamophobic comments by partner Shaun Maguire. Benchmark shores up partnership with Ev Randle. Josh Kushner’s Thrive Capital raises new funds. Reddit sues Perplexity as scraping battles rage.

The Main Item

AGI May Be a Distant Dream, but Amazon’s Robot Rollout Shows Intelligence Isn’t Everything

With AI hype in overdrive, comments this week from Andrej Karpathy, the OpenAI co-founder and former Tesla Autopilot lead, were a bucket of cold water for the industry.

Here was one of the most respected AI researchers arguing on the Dwarkesh Podcast that red-hot coding apps like Claude Code and Cursor were still pretty dumb, and that effective agentic AI would be a decade-long effort.

Oh, and AGI is most definitely not just around the corner, predictions from the likes of Sam Altman and Dario Amodei notwithstanding.

Karpathy contended that the coding apps, though impressive, lack the “continual learning” that would characterize a truly intelligent system, and thus get hung up on tasks that aren’t directly referenced in training data. The current crop of AI agents tends to get tripped up just a couple of steps into a job, for similar reasons.

Yet Karpathy’s message isn’t that of well-known AI skeptics like Gary Marcus and Ed Zitron, who believe that generative AI has fundamental limitations that will cap further progress, nor was he taking aim at the almost incomprehensible numbers being bandied about for data center buildouts, or arguing alongside those who are crying bubble.

Karpathy just thinks that progress will be incremental and — frustratingly for the techno-optimists — tied to practical, cost-effective utility. When AGI finally does arrive, he says, it will likely “blend into” normal productivity growth rather than trigger a singular leap.

As it happens, a New York Times story this week about Amazon offered a good illustration of what Karpathy was talking about. In fact, it provides an excellent framework for thinking through the practicalities — and implications — of broad-based AI deployment at big companies.

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