While Large Language Models have advanced rapidly, building reliable production-grade systems around them remains a complex engineering challenge. In this webinar, Anni Chen introduces a systems-driven framework for deploying LLMs in real-world environments. The session explores how to identify high-impact use cases, design retrieval-augmented architectures, navigate latency and cost trade-offs, and establish continuous evaluation and feedback loops. Drawing on experience with large-scale deployments, the talk emphasizes disciplined engineering, responsible AI practices, and scalable infrastructure. It offers a practical blueprint for turning powerful models into dependable, measurable business systems.