Design an agentic RAG system that plans, decomposes, and iteratively retrieves to answer complex multi-hop questions.
## CONTEXT Single-shot retrieval fails on complex questions that need multiple lookups, comparisons, or reasoning across sources. In 2026 agentic RAG addresses this by letting the model plan, decompose the question, retrieve iteratively, and decide when it has enough to answer. The risk is unbounded loops, cost…
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