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"YOUR AI AGENTS DON'T HAVE A MEMORY PROBLEM. THEY HAVE A SELECTION PROBLEM."Most teams solve this wrong. They add more storage. Bigger context windows. More vector dimensions.None of it matters if the agent retrieves the wrong eight things out of eight thousand stored ones.The bottleneck was never how much an agent can remember.It's whether it picks the right memory at the right moment.
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This kid linked Claude and Obsidian in one app and made $250,000.Now his AI has 10,000,000 tokens of context from his vault.The app also cut his Claude usage by 57%I’ll show how to copy his success step-by-step:The whole thing is one trick: do not give Claude the vault, give Claude the slice of the vault that matters.The app:Chunk the vault. Split every markdown note into ~500 token pieces, keep the file path and heading as metadata.Embed locally.Run a local embedding model (nomic-embed, BGE, or
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