Multi-Agent RAG
A retrieval-augmented generation setup where multiple cooperating agents share a retrieval layer.
- Category
- AI & RAG
- Tech stack
- RAG
- LLM
- Role
- Prototype — design & build
Content
A prototype where several cooperating agents share one retrieval layer, each pulling the context its own sub-task needs. It explores the coordination problem: a single retrieval pipeline serves no sub-task well when the sub-tasks want different context.
Problem
A single retrieval pipeline struggles when different sub-tasks need different context; coordinating multiple agents over one shared retrieval layer is the design problem this explores.
Limitations
Prototype-stage: agent coordination was hand-tuned rather than learned, and evaluation was manual.
Next steps
A production version would need routing rules for which agent retrieves what, plus systematic evaluation of answer quality.
Outcome
Working prototype that demonstrated multiple agents coordinating over shared retrieval; deliberately kept at prototype stage. The retrieval lessons carried directly into how I build grounded systems like Alex OS.