CodeRabbit is an AI-driven tool designed to deliver accurate code reviews on large and complex codebases by incorporating historical context, architectural knowledge, and team coding conventions into the review process. It effectively manages to address the challenges of reviewing massive codebases by mapping dependencies, identifying frequently co-modified files, and ensuring changes do not disrupt existing dependencies. CodeRabbit stands out by not only examining the surface-level changes but also delving into the broader context, which reduces unexpected side effects and enhances feedback on potential risks. The tool employs a combination of semantic indexing and lightweight mapping to detect cross-file issues and improve consistency while avoiding unnecessary comments. It integrates with linting and security tools to provide a comprehensive review that respects organizational standards, and it adapts to scale with isolated and resilient execution environments that streamline the review process. This approach, termed "context engineering," enables CodeRabbit to offer precise, context-aware reviews in large, legacy code environments, ensuring a deeper understanding and faster resolution of potential issues.