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Discusses practical challenges in combining long-term memory and knowledge base for personalized AI agents, questioning whether stuffing everything into context is standard and exploring alternatives like separate retrieval pipelines or tool-based interaction.
A user shares a custom harness for Claude Code that uses RAG with a graph database and bash script hooks to prevent context stuffing, saving tokens.