AI code review is the use of an AI model or agent to inspect code changes for bugs, security risks, style issues, missing tests, and architecture problems. It works by reading the diff, project context, and sometimes related files, then returning comments or suggested fixes.
The strongest AI code review is not a replacement for human review. It is a first pass that catches repetitive issues, highlights risky patterns, and helps reviewers focus on higher-level decisions. The review should be grounded in the repository's rules, test commands, and coding standards.
Verdent's angle is review as part of an agentic workflow. Code can be planned, generated, tested, reviewed, and refined before merging. When paired with workspace isolation, AI review becomes safer because each worker's changes are separated and easier to inspect. The goal is fewer missed issues, not blind approval.
