AI lets people produce more, and more of that output starts to look the same. Vanessa Meyer founded Afoot, a company building AI to help people coordinate. She counts that sameness as the first of five linked things breaking as companies rework management around AI. The other four are job boundaries, what managers know, how well they manage and how workers feel.
She traces the sameness to the tools, which learn from everything done before and are designed to return the most obvious, most average answer. When many people attempt things with the same kind of tool, the results end up alike, and she calls that sameness, repeated over and over, AI slop. Because AI makes production cheap, bad judgment becomes more expensive.
Those attempts also cross job lines. Roles and boundaries are collapsing, Meyer says, as people try things outside their usual expertise and more act on their own, without coordination. When some attempt the same thing, work collides and effort gets duplicated. At Lovable, a company built around AI, Elena Verna writes that people occasionally “do the same work at the same time in different directions.”
Managers usually learn about such collisions from the questions people ask them, Meyer says. Each one shows where direction is unclear and what people are working on. Workers ask internal AI tools questions they once brought to managers. That leaves managers without the information they use to correct course and keep work from colliding.
Managing gets harder as a result. The need for effective managers has risen, she says, while their ability to be effective is shrinking. In a 2026 survey of tech workers by Lenny’s Newsletter, 25.5% rate their manager as highly effective and 36.5% as ineffective.
The last break shows in how workers feel. In the same survey, 82% say AI makes them more productive. Yet 55.7% report significant burnout, up 11 points in a year. On their careers, 51% worry about being expected to do more for the same pay, and only 22% about losing their job to AI. Across the survey, manager effectiveness drives burnout more than anything else, ahead of role, company size and attitude toward AI.
Those findings come only from tech workers, and the survey’s manager ratings changed little in a year. Verna writes from one company and calls her account field notes. No figure from either measures whether managers hear fewer questions.
