AgentsAugust 22, 2026via InfoQ AI/ML

AI Code Review at Scale: LinkedIn's Multi-Agent Approach

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.

Key signals

  • Multi-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

The hook

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.

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, treats

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