Hello, and welcome to Decoder! This is Alex Heath, your Thursday episode guest host and deputy editor at The Verge. One of the biggest topics in AI these days is agents — the idea that AI is going to move from chatbots to reliably completing tasks for us in the real world. But the problem with agents is that they really aren’t all that reliable right now.
There’s a lot of work happening in the AI industry to try to fix that, and that brings me to my guest today: David Luan, the head of Amazon’s AGI research lab. I’ve been wanting to chat with David for a long time. He was an early research leader at OpenAI, where he helped drive the development of GPT-2, GPT-3, and DALL-E. After OpenAI, he cofounded Adept, an AI research lab focused on agents. And last summer, he left Adept to join Amazon, where he now leads the company’s AGI lab in San Francisco.
We recorded this episode right after the release of OpenAI’s GPT-5, which gave us an opportunity to talk about why he thinks progress on AI models has slowed. The work that David’s team is doing is a big priority for Amazon, and this is the first time I’ve heard him really lay out what he’s been up to. — Read More
Daily Archives: August 22, 2025
Building AI Products In The Probabilistic Era
I was recently trying to convince a friend of mine that ChatGPT hasn’t memorized every possible medical record, and that when she was passing her blood work results the model was doing pattern matching in ways that even OpenAI couldn’t really foresee. She couldn’t believe me, and I totally understand why. It’s hard to accept that we invented a technology that we don’t fully comprehend, and that exhibits behaviors that we didn’t explicitly expect.
Dismissal is a common reaction when witnessing AI’s rate of progress. People struggle to reconcile their world model with what AI can now do, and how.
This isn’t new. Mainstream intuition and cultural impact always lag behind new technical capabilities. When we started building businesses on the Internet three decades ago, the skepticism was similar. Sending checks to strangers and giving away services for free felt absurd. But those who grasped a new reality made of zero marginal costs and infinitely scalable distribution became incredibly wealthy. They understood that the old assumptions baked into their worldview no longer applied, and acted on it.
Eventually the world caught up. — Read More
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