You are implementing knowledge access for a multi-agent product-support solution. A retrieval agent must supply precise passages to a resolution agent and a citation agent. Documents are long, mixed-quality PDFs. Which RAG implementation focus is most important?

Developing multi-agent solutions includes multi-agent RAG: chunking strategies that preserve semantic units, high-quality embeddings, and retrieval precision (and often hybrid search). Different agents may consume the same knowledge plane with different filters—troubleshooting vs policy citations. Option A yields coarse vectors that rarely match specific issues. Option B abandons modern retrieval. Option C is not viable for large corpora or multi-tenant data. Implement metadata filters, re-ranking if needed, and pass structured citations to the citation agent. Evaluate retrieval separately from generation so failures are diagnosable.