How AI code review reduces review cycles to improve developer productivity

AI code generation tools are getting better and better every month, helping engineers build software faster than ever before. However, AI code generation also poses new challenges, especially when it comes to maintaining code quality. As AI coding tools become ubiquitous, the sheer volume of code produced can overwhelm even the best engineering teams. What if we could use AI to help tackle this increased volume of code changes? By leveraging an AI-powered review tool to assist in reviewing AI-generated code, engineering teams can streamline review cycles, boost developer productivity, and ensure that quality doesn’t slip through the cracks as they adopt these powerful new AI tools. In this blog post we’ll explore how to get the most out of AI-powered code review tools to reduce your team’s review cycles and improve developer productivity.

If you ask any developer what the most challenging part of the code review process is, they’ll likely say waiting for reviews. Reviewers are often juggling multiple tasks, leaving pull requests (PRs) in limbo for hours, days, or even years. This delay can cause a domino effect: without stacking, change authors are blocked from working on the same part of the codebase while they wait for feedback, bringing the project to a complete halt. As teams scale and codebases become more complex, these inefficiencies only become more pronounced.

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