For years, the dominant narrative around AI has been simple: machines are coming for jobs. We’ve heard this framing so often that it’s become background noise, but it rests on a flawed assumption. The assumption is that jobs are fixed bundles of tasks, and if you automate enough of those tasks, the job itself disappears. That’s not how work actually functions. As Jensen Huang recently articulated, a job isn’t defined by the tasks. A job is defined by its purpose. The tasks are just implementation details. Once you grasp this distinction, everything about the AI-and-work conversation begins to look very different. Jobs Were Never About Tasks in the First Place Ask someone what a lawyer does, and they’ll tell you: they write contracts they research case law they prepare arguments they draft legal documents Ask a marketer, and you’ll hear about writing copy, running ads, analysing metrics, testing campaigns. Ask an engineer, and they’ll mention code, debugging, documentation, building features.…