Prompting was middle management - by Michael Mayernick

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Prompting was middle management<br>Loops fired you from a job you didn't know you had, and sent you the bill

Michael Mayernick<br>Jul 20, 2026

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Every prompt I typed was a small act of direction, every read of an answer was a review, and every follow-up was a course correction, delivered so fast that none of it registered as work. The AI seemed to be doing the job by itself, and the reason it seemed that way is that my half of the job was nearly invisible, even to me.<br>Fired from the middle of the job

Loops are what made me see it. A loop is the newer way of working with agents: instead of asking for one thing at a time, you give an agent a goal and it runs on its own, reading what it made, deciding what to do next, going for hours and sometimes days without you in the conversation. More of our work runs this way every month, and the plain way to say what a loop does is that it fires you from the middle of the job.<br>Thanks for reading The Inference! Subscribe for free to receive new posts and support my work.

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All the steering you were quietly providing from inside the conversation has to come from somewhere else: the goal written down the way you actually mean it, the context that used to live in your head, the checks that catch it when it drifts. A loop without those isn’t faster work, it’s an agent wandering, and it wanders on your budget.<br>All the steering you were quietly providing from inside the conversation has to come from somewhere else.

For as long as I’ve worked, the expensive part of building was making the thing. It cost human time, human time was capped by attention and headcount, and we organized companies around that scarcity: the backlog, the quarter, the roadmap negotiation, all of it machinery for choosing carefully because you could only make so much. Agents dissolved that constraint, the making itself is fast and close to free now, and what a loop bills you for is the steering around it. Some of that bill is literal compute, agents that either converge on something useful or wander and burn money until you stop them, and we’re already hearing about companies blowing through their AI budgets this way. An agent left running for a day is a spend decision in a way a prompt never was. The rest of the bill is the human half of the collaboration, now explicit: deciding what’s worth pointing an agent at in the first place, and being able to tell whether what came back is any good. Neither of those gets cheaper as the models get better.<br>A level up from the keyboard

You can watch planning change shape under this. The old planning question was whether you could build something at all, and you arranged your people and your quarters around that limit. The new questions are what deserves the compute and the attention, and how much you can trust what comes back without reading every line of it yourself. Those are judgment calls, and they ask for a different kind of attention than the kind we built our companies around.<br>The collaboration that was hiding inside prompting all along is now visible., priced, and worth being deliberate about.

I don’t think any of this is a loss, and if anything it’s the opposite of the worry that AI flattens the work and leaves people with nothing interesting to do. The bounded, repetitive middle of the job is what got cheap. We keep the two ends that were always the most human, choosing what’s worth making and telling whether it came out right, and the collaboration that was hiding inside prompting all along is now visible, priced, and worth being deliberate about. That’s where the cost lives now, a level up from the keyboard, and I would rather spend my time there anyway. Getting fired from the middle turns out to be a promotion.<br>Thanks for reading The Inference! Subscribe for free to receive new posts and support my work.

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