Iterative Retrieval: The Retrieve → Reason → Retrieve Again Loop
~15 min read
The book's 12-step agentic RAG workflow includes an explicit retry loop: if a relevance-checking agent decides the answer isn't good enough, the whole process runs again — bounded by a maximum iteration count so it doesn't loop forever.
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Key points
- •Naive RAG has no recovery mechanism if the first retrieval is bad — agentic RAG's loop is exactly the fix
- •A relevance-checking agent evaluates the generated answer; if it fails, the process restarts from query rewriting
- •The loop is explicitly BOUNDED — it runs for a few iterations, not indefinitely
- •A clean 'cannot answer confidently' fallback after the iteration budget is exhausted is far better UX than an infinite loop or a confidently wrong answer
- •This iterative recovery is exactly what the book means by agentic RAG being 'much more robust' than a fixed one-shot pipeline