Agentic RAG Needs a Search Budget: Stop Letting Retrieval Loop Forever
Design bounded Agentic RAG with query, source, token, latency, and cost budgets, evidence tests, contradiction handling, and honest stop states.
Agentic RAG systems can get stuck in an unbounded search loop where the model continuously rewrites queries, selects sources, asks sub-agents, follows relationships, verifies evidence, and repeats the process until the model feels done. This flexibility is valuable for complex questions that often require multiple lookups. However, without limitations, the loop can be indefinite.
To prevent this, production search requires a budget and a stop condition. Retrieval should only happen when necessary, and the model should decompose the query into claims, verify evidence, and define a multi-dimensional budget with independent limits for queries, parallel branches, sources, documents, evidence tokens, model calls, wall clock time, and estimated cost.
Each claim should have supporting evidence from trusted sources, with contradictory evidence clearly documented. A practical sufficiency test could require every must-answer claim to have evidence, meet an authority threshold, be up-to-date for time-sensitive claims, have independent corroboration for high-impact claims, and have no critical gaps.
The model can score relevance, but a deterministic policy should decide the required evidence class. The run should terminate with specific stop reasons like sufficient budget exhaustion or contradictory evidence unresolved. Query rewriting should be limited, and each rewrite should have a reason code indicating why it was performed.
Before synthesizing the answer, the model should handle contradictions by classifying them based on factors like publication dates, jurisdictions, or scope mismatches.
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