The Great Fold: Al slop, less jobs, a big flop or something else entirely?

Will jobs curl up into more general less pronounced roles meant to fulfill the promise of more productivity per employee?

You open your laptop Monday morning, and somewhere between coffee and your first meeting, you’ve already done the job of three people. You pulled the data yourself. You drafted the brief yourself. You fixed the whole deck. And almost nobody said thank you, because they’re doing the same thing. We’ll kind of expect this.

That’s The Great Fold.

The pitch is as follows: AI handles the repetitive stuff, humans absorb the rest. Roles compress. Fewer people, same output, better margins. On a slide it makes total sense. The uncomfortable part is what it feels like from the inside. Which is: you used to have a job. Now you have a jurisdiction.

And it’s getting bigger every quarter.

Here’s what I think is actually going on. Tools that used to require a specialist look like they are only one prompt away. Need a quick data analysis? Don’t ask the analyst — just do it yourself. Need copy for a campaign? Don’t loop in the copywriter — generate something and clean it up. The argument is that this is empowering. And sometimes it genuinely is! But there’s a second version of that story. One where ‘empowering people to be more self-sufficient’ is just a polished way of saying: we’re not backfilling that role, try to avoid the AI slop and make it look like it could well be your job.

What happens when everybody is absorbing more or well could absorb more? The metric shifts. It’s no longer only important that you’re doing your job well. It also becomes important how much you’re doing compared to the person next to you. The colleague who never asks for help, who somehow always delivers without creating dependencies — they become the benchmark. Not officially (yet). Nobody puts it in a performance review like that. But you can start to feel it.

Will you stop asking questions you should ask? Because you think you can find the answer yourself? Or rather, you get the feeling an AI will give you the right answer without knowing how to compare. Will you stop flagging things that need a second pair of eyes? Do a second pair of eyes become a second pair of LLM’s with an LLM-as-a-judge to make the final judgement? So what if everybody starts optimizing for independence over being most effective? There is an argument that can be made where you can point out that it is here that the fold starts cutting rather than just compressing.

We should not overlook: we built up specialization for a reason. The person who spent years learning how to structure research without biasing the result. That wasn’t just a job title. That’s accumulated knowledge that took a long time to build.
But we should not overrate it either: It does look like that the more specialized your job has become, the more bounded training data and instructions you left to grabble for LLM’s. So where are we now? Can we fold specialisms into more generalistic roles or do we undeniably lose critical nuances? Too early to tell.

But will this trend continues? Obviously. Is it all bad? No. Honestly some of the best work I’ve done and seen from people comes from exactly stepping beyond a certain scope and making more of it your own — not because of pressure but because you want to. That’s a different energy entirely.

The question isn’t whether The Great Fold is happening. It is. The question is whether the organizations driving it are building something resilient — or just squeezing harder on what’s already there, and calling it progress.

At some point, something gives. Let’s see who’s still standing when it does.