Scoped AI Review: Eliminating Noise in Automated Code Analysis

AI code reviewers currently flag all issues in analyzed code, including pre-existing problems unrelated to a developer's changes, creating reviewer fatigue and reducing finding credibility. Implementing blame-aware scoping—where reviewers focus only on changed lines and their dependencies—delivers more actionable feedback and prevents developers from dismissing legitimate findings. This approach becomes critical as AI-assisted development grows, where development tools help write changes but reviews still encounter surrounding legacy code.