You design a multi-agent RAG solution where a Research agent retrieves policy documents and a Writer agent drafts customer replies. The Research agent often returns partially relevant chunks, so the Writer invents policy details. Product owners require higher retrieval precision without forcing the Writer to search itself. What should you implement?
Select an answer to reveal the explanation.
Short Explanation
C is correct. In multi-agent RAG the Research agent owns retrieval quality; the Writer should consume verified citations, not guess. Improve precision at the retrieval layer: better chunking strategy, metadata filters (product line, jurisdiction, effective date), re-ranking or score thresholds, then hand the Writer only high-confidence chunks with source anchors. Bigger embeddings alone will not fix bad chunks or missing filters. One-vector-per-PDF destroys precision and blows context. Full fine-tuning for every policy change is slow, costly, and still needs grounding for freshness. Design the agent-to-knowledge path so precision is enforced before generation.
Full Explanation
Correct Answer — C
Multi-agent RAG architecture emphasizes chunking quality, embedding effectiveness, and retrieval precision for the agent that consumes knowledge. The Research agent should apply tuned chunking, metadata filters, and re-ranking or confidence thresholds, then pass only high-quality citations with source anchors to the Writer. That separation of retrieval and drafting roles is a core multi-agent development pattern.
Why A is wrong: Embedding size alone does not fix poor chunk boundaries, missing filters, or weak relevance ranking.
Why B is wrong: Whole-document vectors reduce precision, waste context, and still do not guarantee the right passage is used.
Why D is wrong: Fine-tuning every policy PDF is operationally heavy, lags document updates, and is not a substitute for grounded retrieval in regulated content.
Exam tip: Multi-agent RAG = specialist retrieval quality + citation handoff, not writer self-search or pure fine-tune.