Treating Models Like Code: The Discipline of Al Lifecycle Management

Large Language Models have become integral to enterprise workflows, yet remain among the most powerful yet least understood software components in production. This presentation shares lessons learned from deploying LLM applications at scale across major enterprises, introducing a comprehensive framework for treating LLMs as dynamic, logic-bearing artifacts rather than static black boxes. We demonstrate four essential ingredients for production-ready AI: artifact integrity verification through confidential computing, supply chain security, intelligent guardrails for runtime safety, and functional correctness monitoring. Attendees will see these principles demonstrated through a live confidential AI platform, showcasing secure, attestable AI pipelines in practice for engineering leaders and AI practitioners responsible for deploying trustworthy AI systems.