One Useful Thing

Every few months, I write a guide for people who want to use AI to do stuff. This time, a lot has changed, in part because what it means to “use AI to do stuff” encompasses so much more “stuff” than it used to. Until recently, using AI meant talking to a model through a chatbot in a constant back-and-forth conversation.

If you feel like things are accelerating in AI, you are probably right. Better AI models from the leading American AI labs have been releasing more quickly than ever (though government interventions have stopped access to two of the most powerful models, Claude Fable and GPT-5.6). But it isn't just release timing. The evidence points to accelerating capability gains as well (though the frontier stays jagged, and AIs remain weak in many places).

I had early access to the first Mythos-class AI model being released to the public, Claude 5 Fable. Much of the discussion of Mythos has centered on its impact on software security, but I tested it on everything except that (the guardrails around Fable essentially prevent it from being used for cybersecurity at all). My conclusion is that it represents a very real leap over every model I have used before, and, maybe more important, suggests our relationship with AI is changing in drastic ways.

It has been two years since Co-Intelligence, my book about AI, was published, and it was successful beyond what I could have hoped (it was a New York Times bestseller and has been translated into 25+ languages, with the biggest markets being the Netherlands and Korea). I don’t think the book is out-of-date, exactly, but it was written about a world of chatbots and earlier AI models.

If you go to your favorite social media site, you will find it full of posts that start to look suspiciously similar to each other: Many of the comments to these posts are also generated by AI. So are an increasing number of academic papers and New York Times opinion articles, and, apparently, award-winning short stories.

I had early access to GPT-5.51, and I think it is a big deal. It is a big deal because it indicates that we are not done with the rapid improvement in AI. It is also a big deal because it is just plain good. And it is a big deal because even with all of this, the frontier of AI ability remains jagged.

AIs are already far more capable than most people realize. A large part of this so-called capability overhang comes not from the limits of AI (though, of course, they still have many limits), but from how people interact with it. The vast majority of people access AI through chatbots, and usually the free versions with less capable models. A chatbot is fine for a quick question, but it is a bad way to get real work done.

In October of 2023, I wrote about the “Shape of the Shadow of the Thing,” speculating on the Thing that AI might turn into in the coming years. I think we can see the Thing much more clearly now, and some of the consequences that come with it. As I have been discussing in recent posts, we have entered a new phase of AI. After ChatGPT was introduced, human-AI work took the form of what I called co-intelligence, where humans would prompt AI back-and-forth to get help on tasks.

I have written eight of these guides since ChatGPT came out, but this version represents a very large break with the past, because what it means to “use AI” has changed dramatically. Until a few months ago, for the vast majority of people, “using AI” meant talking to a chatbot in a back-and-forth conversation. But over the past few months, it has become practical to use AI as an agent: you can assign them to a task and they do them, using tools as appropriate.

I just taught an experimental class at the University of Pennsylvania where I challenged students to create a startup from scratch in four days. Most of the people in the class were in the executive MBA program, so they were taking classes while also working as doctors, managers, or leaders in a variety of large and small companies. Few had ever coded. I introduced them to Claude Code and Google Antigravity, which they needed to use to build a working prototype.