How to keep agentic workloads orchestrated, fast, and affordable - Azure AI Tech Accelerator (opens in new tab)

Getting AI to production is only half the battle. Once agentic workloads are live, organizations face compounding challenges: token costs that grow non-linearly, latency that degrades user trust, Retrieval-Augmented Generation (RAG) pipelines that return noise instead of signal, and orchestration overhead that multiplies with every agent added to the mesh. This is where the real engineering begins.Wrap up your Path to production Tech Accelerator experience with a practical optimization playbo...