Code Review Becomes the New Bottleneck in the Age of AI

AI coding assistants like Claude Code have dramatically accelerated code generation—a single engineer can now produce in hours what previously took days—but code review capacity cannot keep pace, creating a fundamental bottleneck that hiring cannot solve. Unlike human-written code, AI output is qualitatively harder to review because it lacks institutional context, subtly violates architectural constraints while passing automated tests, and drifts from team conventions. This structural problem marks a critical inflection point for engineering organizations, requiring fundamentally new approaches to code quality and team workflows.