…or if you like the good/old one: The future is here it’s just not evenly distributed — and this time it’s on AI (or SI as from last week).

There is a growing disconnect in the AI/SI conversation, and it’s not because one side is wrong. It’s because people are having radically different experiences with the same technology.

Andrej Karpathy has been pointing at this for months, but his latest framing makes the problem particularly clear: the gap between what people think frontier AI can do and what it can actually do is widening, not closing. He describes a steep capability funnel, with most people near the wide end and a tiny group at the narrow end experiencing something that looks almost like a different technology.

Consider the distribution.

Around six billions people have barely touched AI. Another billion or two use free chat interfaces for search, writing, brainstorming, and the occasional questionable answer. For them, ChatGPT AI is useful, sometimes impressive, but hardly revolutionary.

Then there are roughly 20 million people, many working in technical fields, using paid frontier models and agentic tools on serious, multi-day projects. They are handing agents entire codebases, complex mathematical problems, and substantial research tasks that once required weeks of focused human effort. Increasingly, they return to find much of the work done.

At the very narrow end are perhaps a few thousand people with (free!) access to the latest internal systems. They are experimenting with fleets of agents working for days or weeks on substantial software and research projects, including security-sensitive work such as vulnerability discovery and exploit development.

These numbers should be understood as estimates illustrating the distribution, not a precise census. The important point isn’t whether the boundaries are exactly right. It’s how dramatically the experience changes as you move down the funnel.

And that’s where things get interesting.