Beyond RAG: Orchestrating Multi-Agent Workflows in Real Enterprise Environments
The Problem with 'Chat with your Data' Last year, most of us spent our time standing up RAG (Retrieval-Augmented Generation) patterns. It was the low-hanging fruit: take some PDFs, chunk them into a Vector DB, and let a chatbot answer questions. It looked great in a demo, but in production, we're finding that enterprise users are hitting a wall. They don't just want to ask, 'What is the refund policy?' They want the system to actually process the refund, check the warehouse inventory, and update the CRM. The moment you try to move from passive reading to active doing, the single-prompt RAG architecture breaks. It can't handle the complexity of hitting five different internal APIs, managing state across long-running tasks, or deciding what to do when a service returns a 401 error. In real projects I’ve seen recently, trying to jam all this logic into one 'super-prompt' results in a brittle, non-deterministic mess that no sane SRE would let near a ...