When I reject AI code even if it works
AI can make implementation cheap while making review and judgment more expensive.
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June 19, 2026 When I reject AI code even if it works 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. Even when I follow good practices – like starting with the plan mode, dividing big tasks into phases, and shipping small changes – I still feel cognitive overload when reviewing something I haven’t actually thought through myself. GENERATED BETTER FIT Before coding agents, when given a task, I would explore the codebase, think of different solutions, experiment, and only then implement. That could take days of consolidating all that context.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Vinicius Brasil.
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