Azure AI Search in 2026, how to build a RAG pipeline
Most RAG tutorials online show the same pattern: take a document, split it into chunks, generate embeddings, store them in a vector database, and when a query arrives search for the nearest vectors an
carlosjcastrog.hashnode.dev9 min read