AI Code Review at Scale: LinkedIn's Multi-Agent Approach
LinkedIn built a multi-agent code review system that handles thousands of PRs daily — not a chatbot bolted onto GitHub, but production infrastructure that understands org context.
Why it matters
A major tech company deployed autonomous agents at scale to solve a real operational bottleneck (code review). This is a concrete case study in agent reliability, integration, and organizational fit — exactly what practitioners need to see working.
The key facts
6 to knowMulti-agent architecture for code review (not single-model approach)
Designed to minimize hallucinations and low-signal feedback
Treats code review as production infrastructure, not a feature
Built to understand LinkedIn's specific coding context and standards
Handles scale that off-the-shelf AI solutions cannot manage
Published Aug 2026 on InfoQ — credible engineering publication
Go to the source
InfoQ AI/MLinfoq.com
Publisher excerpt: At LinkedIn's scale, relying solely on human reviewers or simply putting an off-the-shelf AI reviewer in front of GitHub is not an effective way to manage PRs. To address this, LinkedIn engineers built a multi-agent AI code review platform that understands the organization’s coding context,…