🤖 AI Summary
This study addresses the risks associated with ungoverned conversational AI deployments in enterprise settings, which often result in low reliability, architectural degradation, security vulnerabilities, and technical debt. To mitigate these challenges, the paper introduces a Specification-Driven Development (SDD) paradigm anchored by a novel Specification Governance Reference Model (SGRM). This model enforces probabilistic AI outputs through specification contracts, a three-tier rigor framework, and deterministic verification mechanisms, thereby transforming generative AI into auditable engineering practice. The approach integrates constitutional constraints, mappings to the ISO/IEC 25010 quality model, and an agent-driven delivery pipeline. Empirical evaluation demonstrates that the proposed framework simultaneously ensures regulatory compliance and safety while reducing security defects by 73% and accelerating time-to-market by 50%.
📝 Abstract
Large language models (LLMs) and agentic AI are shifting software engineering from manual coding toward intent specification, architecture, and governance. Two paradigms have emerged: vibe coding, an intuition-driven approach accepting AI artifacts via observed behavior, and Specification-Driven Development (SDD), which uses structured specifications as the authoritative source of truth. This article makes three contributions. First, based on a verified literature corpus, it identifies failure modes of ungoverned conversational generation: the productivity-reliability paradox, architectural erosion from limited context, security exposure, and technical debt. Second, it introduces the Specification Governance Reference Model (SGRM). This tool-independent framework defines four-component specification contracts, constrains stochastic generation via deterministic validation, formalizes three rigor levels, and integrates generation, verification, and governance into a closed-loop architecture. Third, it evaluates SGRM against ISO/IEC 25010, mapping quality characteristics to governance mechanisms. Empirical evidence supports this, reporting a 73% reduction in security defects under constitutional constraints and a 50% reduction in time-to-market through specification-governed agentic delivery. The analysis concludes that while vibe coding is valuable for ideation and rapid prototyping, enterprise software requires specification governance to transform probabilistic AI generation into deterministic, auditable engineering. Boundary conditions, threats to validity, and future research directions are discussed.