LinkedIn has built an in-house AI code reviewer that processes over 40,000 pull requests each week, with most reviews completed before human reviewers even open the PR. As coding agents automate the writing of software, the bottleneck has shifted from writing code to reviewing it. LinkedIn's system addresses this by automating the review process, reading PRs the way humans do and commenting on lines that need attention.
The company interviewed Min Chen, Principal Staff Engineer, and Balaji Srinivasan, Senior Director of Engineering, about their AI reviewer system. The article explores what an AI code reviewer is, why code review has become the bottleneck, and three main approaches teams can take to handle this challenge. It also covers how to build a multi-agent AI reviewing system that works in production.
Once automated review is complete, authors address the feedback so human reviewers can focus on judging fixes rather than reading every line. The article examines what evaluation looks like for AI reviewers, including tracking token costs, detecting prompt injection attacks, and evaluating output quality in real time. As models improve, more teams are automating reviews, but new bottlenecks will inevitably emerge.
Source: ByteByteGo · Summarized by HeadlinesBriefing