Jonathan Fernandes

This talk details the iterative process of building a Retrieval Augmented Generation (RAG) system, highlighting lessons learned from 37 failed attempts. It emphasizes practical choices for different components of a RAG stack, distinguishing between prototyping and production environments. The core thesis is that careful selection and integration of components like orchestration, embedding models, vector databases, and language models are crucial for effective RAG implementation.