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Paper · arXiv

The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development

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% more 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. Through a multivocal literature review of 67 sources (2022-2026), this paper: (1) formally defines the PRP with three moderating variab...

AuthorsSabry E. Farrag
Primary categorycs.SE
Published1 May 2026
Last updated at source1 May 2026
cs.SEcs.AI
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