Engineers cannot efficiently validate AI-generated code quality and architectural soundness at scale

As AI coding agents generate exponentially more code, engineers lack practical tools to quickly assess whether generated code follows architectural best practices, is maintainable, and won't introduce technical debt. Current code review processes and architectural knowledge are insufficient to keep pace with AI output volume, creating a bottleneck where teams either accept risky code or spend unsustainable time on manual review.