Software quality's decline: How AI accelerates it

The report analyzes how AI coding assistants boost development velocity but often degrade software quality and security by amplifying existing process weaknesses, creating variability in outcomes, and overloading decision-making and CI/CD pipelines. Citing studies from Cycode and DX and commentary from industry leaders, it highlights increased productivity alongside rising vulnerabilities, poor governance, and mounting technical debt. It proposes “spec-driven development” and rigorous engineering discipline—measuring spec quality, improving visibility and control, and sustaining talent pipelines—as key strategies to manage risk and realize durable quality gains in an AI-native development era.