Agentic RAG: Letting the Model Decide When to Search
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In a classical RAG pipeline, retrieval is unconditional: every request searches, whether or not searching helps. Handing the model a search tool turns that into a decision — and decisions have both a cost curve and a failure mode. Two pipeline shapes Always-retrieve is a fixed graph. Query in, search, concatenate, generate, answer out. One generation call, predictable latency, predictable cost, and the retrieval either helped or wasted some tokens. Decide-then-retrieve gives the model a…
1Key Takeaways
- In a classical RAG pipeline, retrieval is unconditional: every request searches, whether or not searching helps.
- Handing the model a search tool turns that into a decision — and decisions have both a cost curve and a failure mode.
- Two pipeline shapes Always-retrieve is a fixed graph.
- Query in, search, concatenate, generate, answer out.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that in a classical RAG pipeline, retrieval is unconditional: every request searches, whether or not searching helps.
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