Classic RAG vs. Agentic RAG
Classic RAG follows a fixed pipeline: query, retrieve, assemble context, generate. It is easier to control and evaluate. Agentic RAG lets a model choose sources, rewrite queries, decompose questions, or retrieve again. This can help with multi-part questions but increases latency, cost, and failure modes.
Start with classic RAG and add agentic decisions only when evaluation demonstrates a need. Bound tool steps, deadlines, and budgets. The agent must use the same authorization filters and citation validation as a fixed pipeline.
Implementation example
Classic: query -> fixed retrieval -> answer
Agentic: query -> plan/search -> inspect -> search again? -> answer💡 Agentic retrieval is a complexity trade-off, not an automatic quality upgrade.
Key Takeaways
- Inspect the relevant pipeline stage instead of guessing.
- Preserve source provenance, versions, and access scope.
- Measure quality on representative queries.
Knowledge Check
Why start with classic RAG?