How CodeRabbit helped The Linux Foundation streamline code reviews and accelerate development

If anyone knows how challenging manual code reviews can be, it’s The Linux Foundation The global non-profit supports over 200 popular open-source projects like CNCF and PyTorch. With a globally distributed engineering team of 40 to 60 in-house devs, they develop and maintain essential tools for project memberships, telemetry data management, and IT infrastructure. However, the foundation had a significant roadblock: manual code reviews. According to David Deal, Senior Director of Engineering, "manual reviews caused workflow delays, particularly due to globally distributed teams across time zones, often leaving developers blocked for several hours awaiting feedback." Eager to free up developer time and accelerate their release schedule, The Linux Foundation decided to try CodeRabbit, an AI-powered code review platform. The result? Drastic improvements in review speed, code quality, and developer satisfaction. For The Linux Foundation, that translated into less time spent on pull requests and more time focusing on critical open-source initiatives.

Challenge: A manual code review bottleneck

Before CodeRabbit, the Linux Foundation relied on a traditional manual review process. While functional, David mentioned that their previous review process, being manual and distributed across multiple time zones, inherently caused delays, making it difficult for teams to move forward on code changes quickly. This manual approach couldn't keep pace with their ambitious development cycle and created a code review bottleneck.

• High pull request volume As a host of some of the most widely-used open-source projects, The Linux Foundation manages a constant stream of pull requests, including contributions from a vast open-source contributor community. Their senior engineers faced an overwhelming daily workload that involved scanning countless lines during manual code reviews. Research indicates that the quality of manual code review degrades significantly after a few hours of reviewing too many lines. David's team struggled to keep up with the pace.
• Limited context in PRs Many developers provided minimal or no descriptions for their PRs, forcing reviewers to piece together the context. The manual reviews required reviewers to manually investigate files and changes extensively, creating extra work and prolonging the review process, according to David.
• Slowed delivery and hidden bugs Manual code reviews slowed down merges and releases, impacting The Linux Foundation's product roadmap. While basic static checks or linting tools caught some issues, many bugs, security vulnerabilities, and refactoring complications often slipped through because each PR demanded substantial engineering attention.
• Trapped in a cycle of low developer productivity Developers dedicated excessive time to manual code reviews, which left them with less time for actual coding. This affected velocity and degraded code quality, leading to even longer future manual review cycles. For the Linux Foundation's senior engineers, this created what felt like endless review cycles.

Why The Linux Foundation loves CodeRabbit

Instant AI Summaries & Automated Feedback

For The Linux Foundation, CodeRabbit's AI-generated summaries were an immediate time-saver.

The immediate feedback of CodeRabbit, having gone through and recommended some things, was helpful. CodeRabbit flagging that you didn't handle this case or you made a mistake here provided immediate feedback for those engineers who couldn't get an immediate manual review. - David Deal, Senior Director of Engineering

This alone shaved hours off their daily reviews.

Early issue detection

Like most engineering teams, The Linux Foundation must balance rapid iteration with stability and scalability—a challenging task when constantly responding to production issues or addressing significant technical debt. AI code reviews helped considerably:

It's caught so many mistakes and has highlighted gaps. It’s amazing and speaks to the inferencing engine CodeRabbit uses, as it matched the things that aren't aligned. It catches them immediately. So that's been super valuable. - David Deal, Senior Director of Engineering

With CodeRabbit, issues that might have been missed—including security vulnerabilities, logic errors, or inconsistencies in documentation and tests—were flagged immediately. This proactive approach significantly reduced the chance of shipping bugs into production. CodeRabbit was particularly valuable in identifying discrepancies between documentation and actual test coverage in their SQL and DBT testing frameworks.

Faster, more efficient workflows

The Linux Foundation's workflow improved dramatically because CodeRabbit was able to understand the context behind their code changes. David described CodeRabbit as significantly improving their workflow by providing instant, AI-driven feedback that accelerated reviews, highlighted errors promptly, and offered clearer context to reviewers. That allowed them to put an end to their code review bottleneck.

Set up in minutes

Implementing CodeRabbit was seamless for The Linux Foundation, allowing the team to start seeing value immediately. "The integration onboarding was very quick," David stated, confirming that integration onboarding was very quick. This ease of integration meant CodeRabbit fit into their workflow without friction.

Results: Quality code & faster merges

Once CodeRabbit was fully implemented, The Linux Foundation saw rapid improvements to its process:

• Significantly decreased code review time This acceleration means CodeRabbit customers generally see a 50% reduction in overall review time. "The immediate feedback of Code Rabbit having...recommended some things...provided immediate feedback for those engineers that weren't able to get immediate manual review. Super helpful." David noted.
• Fewer bugs reaching production CodeRabbit catches an average of 90% or more of all customer bugs and errors. By catching issues at the PR stage, The Linux Foundation team saw notable reductions in post-release fixes. David noted that CodeRabbit caught numerous mistakes early, significantly reducing the likelihood of issues reaching later stages of development or deployment.
• Faster merge cycles With better context and fewer open questions, the team could merge PRs faster, staying on track with their release schedule. While results vary, CodeRabbit customers experience an average of four times faster PR merges.
• Improved developer productivity Less back-and-forth in PR discussions and fewer manual code reviews have allowed engineers to focus on building rather than reviewing. David believes CodeRabbit is essential for any development team because developer productivity is so important.
• Immediate impact The Linux Foundation began to see the value in faster reviews, better PR context, and improved collaboration. "We're using it increasingly. 99% of devs have been very receptive to it and found immediate value," David shared.