AI can reduce code review time for repetitive checks and well-structured changes, but the actual gain depends on precision, repository context, and review policy. A reviewer that produces many weak comments can increase rather than reduce developer effort.
Use AI to summarize the diff, identify risky files, trace changed interfaces, detect missing tests, and flag likely correctness or security issues. Leave formatting and deterministic style rules to linters. Configure repository-specific review rules and rank findings by severity and confidence.
Measure active review minutes, time to first useful feedback, accepted finding rate, false positives, and defects found after merge. Compare similar pull requests before and after adoption. Large generated diffs may still take longer to understand even when the initial scan is automated, so keep changes focused.
Verdent's Reviewer can provide a separate analysis pass and can use configured rules or model choices. Pair it with CI, static analysis, tests, and accountable human approval. The best workflow lets AI narrow attention to the parts that deserve judgment. It does not ask developers to rubber-stamp code they do not understand. Review time is reduced only when confidence and quality remain at least as strong.
