Learn about advanced techniques in retrieval-augmented generation (RAG) going beyond simple vector databases. LLMs need guidance! Building on the foundation of combining search algorithms with language models to produce more accurate and contextually grounded responses, I aim to delve into the intricacies of advanced RAG methodologies. My session will cover the spectrum from chunking and vectorization to sophisticated query transformations and the integration of agents, highlighting the role of prompt engineering and fine-tuning in optimizing RAG pipelines. This exploration is designed to offer developers a comprehensive understanding of cutting-edge RAG techniques, paving the way for innovative AI applications that leverage the full potential of LLMs.