AI agents are already doing work that, until recently, was done by people. Some companies are cutting staff, others are simply no longer opening new roles, and some are discovering that digital labor can be surprisingly expensive. Meanwhile, the people who keep their jobs are increasingly becoming operators and supervisors of machines. I tried to understand what is actually happening with the economics of AI agents by the end of summer 2026 — and where this story could go over the next nine months.
Until very recently, a good idea had one rather inconvenient characteristic: someone had to build it.
Suppose you’re a marketer. You understand the market, you know where to find your first customers, and one day you notice a problem people seem willing to pay to solve. Great. Now you need a developer. Then a designer. Then you discover you need another developer because the first one is working on the backend, while the app, inconveniently, also needs a frontend.
Generative AI improves essays, code, and grades faster than universities can work out what a piece of student work now proves — and what stays with its author once the laptop closes.
Picture two students handed the same assignment. Both are bright, both are motivated, both want the top grade — and from there their paths split.
The first loves the subject. She reads the sources, spends a long time building her argument, writes a messy draft, and only then opens ChatGPT — not to replace her thinking but to stress-test it.
Mass unemployment hasn’t arrived. But the claim that “nothing has changed” no longer holds up either.
Five years ago, most people answered the question “should I go into tech?” the same way: yes. Learn Python, build a few projects, land your first job, gain experience, grow. It wasn’t a guarantee, but it worked well enough that millions of people built their plans around it. Today the answer isn’t so obvious — not because developers are no longer needed, but because nobody can honestly say what that first career step will look like in three or four years.
AI changed stock and crypto trading. But not the way it was promised. A breakdown of what AI trading can really do — and what it only sells.
A few years ago, the dream sounded simple: one day, AI would trade while we sleep and make us richer. It would not panic. It would not try to revenge-trade after a loss. It would not buy out of excitement or sell out of fear.
A reported essay on fear, candor, and the new jobs born beside AI
Last August, Mateusz Demski, a radio journalist in Kraków, walked into the studio for the last time. His termination notice was bloodless: “financial reasons.” A few months later the station’s schedule carried shows hosted by avatars—perfect voices that never needed a pause or a sick day. “I spent twenty years learning to love silence on air,” he told me.
AICaver
