“You could generate a million lines of code,” says Sahil M. Bansal, Senior Product Manager at CodeRabbit. “But if your review process only supports 1,000 lines, that’s all you’re shipping.”

The insight was simple but powerful: the bottleneck in software development had shifted from code generation to code review. So the team focused on using OpenAI’s models not only to write code, but also to unlock the speed, accuracy, and intelligence required to review it. Over the last year, CodeRabbit has been used by more than 5,000 customers and 70,000 open-source projects.

As engineering teams leaned into AI for code generation, the limitations of manual code reviews became more apparent. Reviews were slow, repetitive, and missed critical issues—particularly across large, distributed teams, unfamiliar codebases or edge cases that are hard to detect. Valuable developer time was spent reviewing instead of building, and costly bugs were escaping into production.

CodeRabbit’s team knew the problem intimately. “Even when teams used AI to generate more code, they weren’t shipping faster,” Bansal explains. “The code review cycle was the bottleneck.”