Executive Summary The AI-Native SDLC or the AI-native software development lifecycle changes how engineering teams build, review, test, deploy, and maintain software when AI becomes an active participant in development. AI can interpret requirements, generate code, create tests, review pull requests, analyze failures, and support CI/CD workflows—but faster generation also increases the importance of verification, risk-based testing, and human decision-making. The traditional lifecycle: Requirements →