Agentic RAG transforms retrieval into a control loop, allowing systems to iteratively refine evidence gathering beyond a single pass, while Classic RAG relies on a linear pipeline for straightforward doc lookup. This shift addresses limitations where basic retrieval fails, such as ambiguous queries or multi-source evidence needs.

However, agentic approaches introduce unpredictability in cost and latency due to potential retries or tool calls, contrasting with classic RAG's predictability for simple tasks like configuration flag lookups. The choice hinges on use case complexity: classic RAG excels in stable scenarios, while agentic RAG repairs weak retrieval through deliberate retries or source switching.