Moving Beyond RAG

Retrieval-Augmented Generation (RAG) has been the standard approach for giving language models access to external knowledge. However, for long-running autonomous agents, RAG has fundamental limitations.

The Latency Problem

RAG relies on vector search to find relevant information for every query. As the agent's context grows, the retrieval process becomes a bottleneck, introducing significant latency.

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