Vector RAG Isn’t Enough — I Built a Context Graph Layer for Multi-Agent Memory

# Vector RAG Isn't Enough — I Built a Context Graph Layer for Multi-Agent Memory When AI systems try to remember previous conversations, simply storing text snippets isn't good enough—the AI forgets important connections between ideas. A developer tested three memory approaches and found that adding a "relationship map" between topics (rather than just keyword matching) helps AI assistants understand context much better and give more relevant answers. This matters because it means the next generation of AI assistants will need smarter memory systems to actually understand what you're asking about, not just find similar words from past conversations.
I benchmarked raw chat history, vector-only RAG, and a context graph on the same multi-agent conversations. The results exposed a surprising weakness in relational retrieval. The post Vector RAG Isn’t Enough — I Built a Context Graph Layer for Multi-Agent Memory appeared first on Towards Data Scienc
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