An army of cheap doers (and why we’ll all end up being managers) – Matteo Forte

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An army of cheap doers (and why we’ll all end up being managers)

AI is changing the way we work, and most of us have figured that out by now. What gets discussed much less is that it’s not changing it the same way for everyone: whether you’re a manager or an individual contributor, the same thing hits you in very different ways and places. Even though, looking far enough ahead, the endpoint might be the same for everybody: ending up a manager.

If you’re a manager

If you’re a manager, delegating is part of your job. With AI you find yourself with what is effectively an army of cheap doers that on many tasks perform on par with (on just as many worse, on some better than) flesh-and-blood collaborators. And in the world of remote teams – where the people you work with are participants in video calls, names on emails and profile pictures in Slack messages – the difference is less and less noticeable. Not just in the quality of what you get back, but in the day-to-day experience itself.

There’s a misconception I see plenty of managers fall into, though: thinking this stuff is mostly about other people. We always talk about AI as an accelerator of personal productivity, so in execution terms: those who produce get impacted, those who decide orchestrate. Sounds comfortable, if you think you’re sitting on the right side of the desk.

But if we think about what most management roles are, at their core, we notice they rarely involve big strategic decisions. Much more often it’s a continuous stream of small ones: setting a priority, approving or postponing, assigning a task to the right person, deciding whether something is good enough to ship. Decisions that, more than anything, require context. And with well-organized context, the best models are often already able to make them, those decisions.

What remains harder to hand over to a machine, for now, is not so much the decision: it’s putting your name on it, answering for what happens. So, all in all: I’m not at all sure the impact will be stronger on execution than on management. What’s certain is that a lot will change for everyone.

If you’re an individual contributor

If instead you’re not a manager (maybe because you don’t want to be, fair enough), AI greatly increases the amount of things you can do. And as a consequence your job changes quite a bit.

If your role used to be effectively – even if maybe not exclusively – productive and executional, things now get complicated. People who prefer this kind of role often do so precisely to avoid all the stress and the chores that come with managerial positions.

And there’s a bit of a dilemma. If you don’t use AI, you’re certainly less productive and therefore less valued inside your organization. Maybe called out by management, maybe cut out – depending on how AI-pilled the organization you work in is. If you use it heavily instead, the amount of stuff you produce grows a lot, and your ability to make sure that what gets produced is actually up to what you’d want it to be shrinks. Maybe, in some ways, so does your ability to feel that work as “yours” (especially when it doesn’t come out well).

So you find yourself in an objectively uncomfortable position: on one side you pretty much have to use these tools to keep up, on the other using them can expose you to responsibilities you partly feel aren’t yours. Because you would have done that thing differently. Or you wouldn’t have done it at all, if we were all still in the old world.

The friction

A good manager is used to taking responsibility for work produced by others too. They accept a series of trade-offs on the degree of control and quality they can get, and in exchange they focus on creating the conditions for others – at this point I’d say humans or agents, indifferently – to do their best work.

When you’re a contributor, you may simply not have that vocation. And that’s exactly the point: a friction gets created where you either accept being dramatically more productive, losing at least part of the control and consequently taking on responsibility for things you didn’t, in a way, generate yourself, or you risk not making full use of these technologies and suffering consequences of a different kind.

Now, granted that there are many known ways to get a certain degree of control even over work generated by others – after all, it’s what managers have always done – it remains true that for organizations, and for the people in them, the very fact that this friction exists is objectively a risk.

So much for the present. But this story has another piece: what happens when processes really start running on their own, and who puts their name on things in place of the systems.

The job of taking responsibility

One thing, for sure, automation doesn’t eliminate. Quite the opposite. A process can even run on its own, but the responsibility for what it produces…...