Code reviews have traditionally focused on finding errors in code, but this approach creates bottlenecks and hinders team growth due to knowledge silos and overloading domain experts. Modern tooling such as automated tests and static code analyzers can identify bugs more accurately and efficiently than human reviewers, allowing code reviews to shift focus towards knowledge sharing and long-term code maintainability. This new approach fosters collaboration, continuous learning, and a healthier codebase, with a focus on evolvability defects, missing documentation, algorithmic efficiency, and cyclomatic complexity. By leveraging automated tests and static analyzers, teams can reduce the time spent on reviews while increasing the value of code reviews as a knowledge-sharing tool.