Closing the Loop: Feedback based Learning for Agentic RAG on Azure
Enterprise agentic RAG systems lack active feedback-based learning in production today
“there is uh no active learning uh for agents is visible anywhere”
An AI MVP presented a Microsoft Build session on using human-in-loop feedback to improve agentic RAG accuracy on Azure, applied to an aviation industry use case. The core claim is that despite widespread agent hype, active learning from feedback in production enterprise systems remains rare. The solution demonstrates a practical feedback loop architecture that lets agents improve accuracy over time from human corrections.