The landscape of Large Language Models (LLMs) is transforming at breakneck speed. Moving beyond the era of basic Retrieval-Augmented Generation (RAG), cutting-edge LLM applications now integrate specialized data layers, sophisticated agent runtimes, multimodal interfaces, and robust model management tools. Add in AI safety frameworks, dynamic prompt engineering, and intelligent routing layers—and you have the blueprint for building scalable, enterprise-ready LLM solutions.

What You’ll Learn:

• Next-Gen Retrieval Strategies: How to mix vector search, graph databases, and textual search engines to create a versatile, context-rich data layer.

• Advanced Agent Runtimes: Discover how tools like Vertex AI Agent Builder orchestrate long-running sessions, manage “chain of thought,” and leverage contextual feedback loops for ongoing refinement.

• Model Management at Scale: Explore how model factories and LLMOps stacks (e.g., SageMaker) enable continuous fine-tuning, version control, and seamless updates.

• Dynamic Prompt Engineering: Learn how dynamic prompt management (e.g., PromptLayer) streamlines development cycles, adapts prompts in real-time, and ensures ongoing alignment with business goals.

• AI Safety & Compliance: Implement robust guardrails, ethical filters, and transparent governance frameworks to ensure responsible AI usage across your enterprise.

• Intelligent AI Gateways: Understand how AI proxy layers orchestrate requests, manage capacity, maintain reliability, and unify policies across all of your organization’s LLM-powered applications. 

Who Should Attend: 

AI Engineers and Architects looking to operationalize advanced LLM workflows. Product Managers seeking to differentiate their AI-driven products with robust, future-proof architectures. Data Scientists and Developers interested in emerging AI tools, practices, and frameworks. Innovators and Enthusiasts who want to get ahead of the curve in building the next generation of AI solutions.