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Join this 54-minute webinar to explore why retrieval-augmented generation (RAG) continues to serve as the backbone of modern AI applications in 2025, from chat systems to search functionality and complex agentic workflows. Discover the critical role of context engineering and management in transitioning successful AI prototypes to production-ready applications. Learn about the key benefits of implementing RAG in AI applications, including effective context management, addressing challenges with training and fine-tuning large language models, and grounding AI agents with fresh, relevant data for enhanced tool use and workflows. Examine common arguments against RAG and understand why they don't hold up in practice. Follow along with a hands-on Jupyter notebook demonstration that walks through implementing a complete RAG pipeline using Pinecone, LangChain, and OpenAI GPT-5, providing practical experience with the tools and techniques discussed. Access the accompanying notebook and additional RAG examples to continue your learning beyond the webinar.
