I’m not really discussing smaller scoped patches, though. An LLM can change a single line in a file, sure, but the prerequisite there is that the file adequately contains the necessary context to do so. With small patches, you’re advantaged in that way.

Larger patches suffer from a distinct kind of problem where the LLM can heavily over optimize submodules within the code, without proper consideration for the larger premise. This is a problem I’ve seen referred to as “decoherence.” In large projects, it can sort of take over the codebase after enough LLM engagement.

Decoherence makes your codebase unmaintainable. The cost of every change increases logarithmically and the situation gets worse. The heavily optimized submodules are often incompatible semantically, so the agent also optimizes channels between them. This is an explosion in unwarranted complexity. This isn’t a human problem.

Good developers can accelerate their work with agents. However, back to the topic on hand, reviewing agentic code changes is necessarily harder — because it’s prone to more issues that run far deeper. You have to review the code almost adversarially, with more cognitive load being used to unravel the gargantuan mess of barely sensible changes when viewed from a birds eye.