Most AI code review tools lack codebase context, which is critical for catching bugs, understanding dependencies, and providing meaningful suggestions. Without this context, these tools can miss antipatterns and bugs, provide shallow suggestions, struggle with onboarding new developers to legacy codebases, and fail to identify potential side effects. In contrast, Greptile AI takes a fundamentally different approach by analyzing entire codebases, building a detailed graph of dependencies and relationships, and providing actionable fixes for minor issues while also identifying hidden antipatterns and potential side effects. This allows Greptile to deliver context-aware code reviews that align with a project's architecture and goals, setting it apart from shallow AI tools that often fall short in this regard.