Maybe We Shouldn't Be Reviewing All This Code

The article argues that AI-driven code generation is exposing a long-standing weakness in software delivery: code review has been overloaded with responsibilities like knowledge sharing, architecture alignment, and mentorship that should happen earlier and more continuously. For CIOs and technology leaders, the strategic implication is that organizations relying on PR-centric workflows will create bottlenecks and diminish AI’s productivity gains unless they shift to practices such as pair programming, trunk-based development, automated checks, and selective human review by exception. In effect, IT leaders should redesign engineering operating models around earlier feedback loops and team-based ownership, using AI to augment—not replace—continuous design, testing, and governance.