RAG Is Simpler Than You Think

Rafael discusses challenges and developments in building AI systems, focusing on Retrieval Augmented Generation (RAG). He highlights that pre-embedding 1 million documents costs $10 for one-time embedding and about $10-30/month for 6GB storage. The search latency is under 50ms, but freshness depends on the last re-index. The RAG approach uses focused sub-queries, parallel execution for lower latency, adaptive routing for cost efficiency, and structured output for improved user experience.