Agentic RAG Needs a Search Budget: Stop Letting Retrieval Loop Forever
Traditional RAG has a visible failure mode: it retrieves the wrong chunks once.
Agentic RAG can retrieve the wrong chunks creatively for ten minutes.
The model rewrites the query, selects another source, asks a sub-agent, follows a relationship, reflects on the evidence, and searches again. This flexibility is the point. Complex questions rarely fit one nearest-neighbor lookup.
The same flexibility creates an unbounded loop whose success criterion is “the model feels done.”
Production search needs a budget and a stop contract.
Adaptive Retrieval Is a Search Policy
An Agentic RAG system may choose:
- whether retrieval is needed;
- lexical, vector, graph, database, API, or web source;
- query decomposition;
- filters;
- follow-up questions;
- source expansion;
- evidence verification;
- another retrieval round.
The Agentic RAG survey literature describes patterns such as reflection, planning, tool use, and multi-agent collaboration. Microsoft GraphRAG's DRIFT mode similarly expands local search with community context and follow-up questions.
These are search...
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