AI-Native SDLC for Regulated Software Delivery

AI-native delivery models matter when leaders need faster software throughput without relaxing architecture, testing, security, or operational controls. The page explains S-PRO’s SDLC pattern across specification, AI-assisted development, infrastructure-as-code, agent QA, deployment, observability, runbooks, retrospectives, and recurring tech audits. It highlights how private project knowledge, IDE context, design-system handoff, CI/CD quality gates, browser-based regression evidence, and human engineering review are combined. Leaders should care because AI changes delivery risk only when it is embedded into governed workflows, not used as isolated code generation.