sdlc-regulatorylisted

# AI-Driven SDLC Regulatory Framework > **AI accelerates execution, SDLC controls correctness, risk, and accountability.** > Source of truth: **this skill**. It supersedes and absorbs the deleted `SOW.md` > (AI-Driven Software Development Lifecycle); the `SOW §…` section labels below are > historical provenance from that document, kept to trace each control to its origin. This skill is the methodology layer consumed by the `sdlc-*` subagents (BMad-style role agents) and enforced by the `sdlc-gates` always-on rule. It encodes: stages, quality gates, risk-based autonomy caps, AI vs human responsibility split, change traceability, Definition of Done, key risks, success metrics, and a compliance crosswalk. ## Anti-pattern (SOW §Why We Need This) The failure mode this framework exists to prevent: **Requirement → AI → Code → Merge** That flow has no analysis, no validation, no review, and no accountability. AI-driven development adds risks beyond human mistakes: hallucinations, architectural drift, inconsistent implementations, AI-generated technical debt, missing edge cases, security vulnerabilities, over-engineering, incorrect database changes, AI modifying unrelated components, **AI reviewing/validating its own incorrect implementation**, and code volume outpacing human review capacity. Every gate below exists to block one or more of these failure modes. If a proposed shortcut skips a gate, it is regressing toward this anti-pattern — refuse it. ## AI across the SDLC (SOW