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A technical opinion piece argues that human reviewers should use AI to scan large code changes (10,000+ lines) rather than reviewing them manually line-by-line, because LLMs have become skilled at catching high-severity vulnerabilities and are better suited to nitpicking than human reviewers.
Why it matters
Code review is a bottleneck in many engineering teams, but human reviewers' real value lies in catching design problems and architectural inconsistencies that only someone with deep codebase knowledge can spot — knowledge that neither the code author nor the LLM possesses, such as deprecation plans discussed in recent meetings or team-specific coding conventions.
What to watch
The advice comes with a caveat: this workflow applies to codebases where individual lines are not critical. In domains like embedded systems, where each line may be sacred, traditional line-by-line human review remains necessary.
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