When I reject AI code even if it works
A software engineer discusses the challenges of relying on AI-generated code, noting that the cognitive load of reviewing AI output often outweighs the speed of implementation. The author argues that human oversight remains essential to ensure code quality and scalability.
Why it matters
This highlights the evolving role of software engineers as they transition from primary creators to reviewers of AI-generated work.
With implementation getting faster and faster, the real bottleneck moves to reviewing the volume of code generated by AI. I’m not even talking about your coworkers’ (and their agents’) PRs, but your own git diff after your coding agent has finished its job.
The article reflects a personal professional perspective on technology usage rather than a political or social bias.
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