The view that imagines AI wiping out jobs or causing some overnight shock to the system doesn’t contemplate that companies are a made up of a series of bottlenecks. When AI accelerates work in one area, you run into a bottleneck somewhere else. As any individual workflow gets more efficient, the ultimate productivity gain is still constrained by some other part of the system. And usually it’s the case that that part of the system will not have inherently seen the same impact of AI efficiency, which means humans are still doing the work. Take almost any process in an enterprise and you can see how this plays out. If AI Agents generate leads for the sales team, the bottleneck will be humans to have conversations with those customers. And if the leads are good, that will mean more sales hiring. If AI Agents generate more code, you will eventually be bottlenecked by the engineers that can review and incorporate that code into production. You can quickly see how this scales to any process in an organization. Economists and others tend to totally miss how work actually happens in a company; it’s not a series of wholly independent tasks, but instead highly interdependent tasks that all link to each other across a system. This is of course the natural rate limiter of AI efficiency gains, but also the reason why humans will still be doing so many jobs in the future.