What AI Exposed About Engineering Management

Lately I have been hearing the same pattern from engineering leaders at different companies. An org rolls out AI coding tools across the board. Three months in, the EM walks into a quarterly review proud of one number. PR velocity is up two or three times. Two slides later, on a different dashboard, the bug count is up too. Sometimes by half. The numbers sit in different rooms of the same deck. Nobody connects them. The conversation moves on.

That gap, the one between the slide everyone celebrated and the slide everyone skipped, is the part of the AI conversation engineering leaders are mostly skipping over.

Most of the talk I see is stuck on a different question. Should engineering

managers code? It was a contested question before AI showed up. Now it feels existential. Will Larson published “Good Engineering Management is a Fad” last October arguing that the industry’s preferences shift with business reality and dress the shift up as moral progress. Gergely Orosz has been writing for months about EMs perceived as technical landing jobs faster than EMs who are not. Charity Majors keeps making the case that the engineer-manager pendulum is now swinging on a shorter cycle. Each of them is right about what they are seeing, and what they are seeing is a symptom.