In this talk, we'll focus on the challenges of building retrieval-augmented generation (RAG) chat applications and how to overcome them efficiently. We'll explore common issues such as file processing, semantic search, and prompt iteration, showing how Elasticsearch helps streamline these tasks. Using Elastic Playground, we'll fine-tune settings and quickly test RAG prompts to optimize performance. I'll also walk through the process of transforming files into sparse vector embeddings for better search results, and demonstrate how to seamlessly export code for integration into a functional chat application.