AI is removing the middle class of software engineering

Herrengt argues that AI didn't make bad engineering decisions worse, it just removed the limit on how fast a team can make them: a codebase can now absorb more change over one weekend than it used to accumulate while its senior engineer was on vacation for weeks. The harder part, he argues, is that reverting a bad decision, like a hastily added database table, was never the fast part, and AI hasn't changed that: "By the time you've untangled one bad decision, five more have been merged." His conclusion is economic rather than technical: with implementation now cheap, "you are paid to make good decisions," and he expects AI to pull engineer compensation further apart rather than flatten it, since "there's a bar you have to clear and that bar is whatever the current best model du jour can do."

Why it matters: Herrengt argues about who gets expensive and who gets cheap once review capacity becomes the bottleneck. Read it against the reviewer-fatigue numbers above: one is a company's controlled study, the other a practitioner's persuasive essay, and both describe the same failure mode from different distances.