Intel / article

High Signal Ai Code Review That Adapts To Your Codebase At Scale

Source: linkedin.com
Author: LinkedIn Engineering
Date: Published Aug 13, 2026

Context

LinkedIn's AI code-review system has several agents inspect the same proposed code changes independently. A coordinating system then combines their findings, checks them against the surrounding code and applies company and repository rules before posting comments.

Agreement between reviewers raises a finding's priority, while an issue found by only one receives additional validation. Duplicate, cosmetic and already-addressed suggestions can be filtered out. The design concentrates effort on deciding which comments deserve a developer's . Human review remains required, and the company measures adoption of suggestions separately from their correctness.

Terms in this piece · Glossary

AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
attention — The mechanism that lets a model weigh which earlier words matter for the word it's currently processing — the core operation of a transformer.
multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.

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