Traditional RAG systems are designed around a simple idea: find the most relevant information, add it to the prompt and generate an answer. This works well for questions where the answer can be found in a small set of relevant documents.
An agentic workflow is a multi-step process where an AI agent plans the steps, picks tools, acts and adjusts based on what comes back, instead of following a script written in advance. In this post, we walk through how that loop runs, where it beats traditional automation, and the guardrails it needs in production.