AI RESEARCH
The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development
arXiv CS.AI
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ArXi:2605.01160v1 Announce Type: cross Since 2022, AI-powered coding assistants have produced contradictory evidence: controlled studies report 20-56% productivity gains on well-scoped tasks, while the most rigorous RCT documents a 19% slowdown for experienced developers, and telemetry across 10,000+ developers shows 98% pull requests but 91% longer review times with flat delivery metrics. This paper argues these findings constitute the Productivity-Reliability Paradox (PRP): a systematic phenomenon emerging from non-deterministic code generators and insufficient specification discipline.