AI Slop Is Changing How Engineers Review Code
TL;DR
AI coding tools can now generate thousands of lines of code in minutes, helping companies build features, run tests, and fix issues faster. But the flood of AI-generated code still has to be reviewed. Large language models can produce code that looks clean on the surface but conceals sloppy mistakes such as faulty assumptions, security vulnerabilities, or subtle errors that emerge only after deployment. Fixing those problems could erase the productivity gains AI promises.
Nauti's Take
Teams reviewing plans before coding and routing risky diffs to humans is real progress in review culture, and that is the useful part of this shift. The problem is volume: when an agent produces more diff in an afternoon than a team can read in a day, the bottleneck simply moves.
Small teams gain the most by assigning ownership per change instead of adding review headcount.
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