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How AI agents use layered memory to remember clients

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AI agent memory can be built in layers, pairing a summary of the current context with a long-term knowledge base the agent searches when answering questions. ChatGPT can also save details and draw on past conversations when those features are enabled, though it does not keep every detail. In one custom system, agents periodically summarize what matters and archive the rest to free up working memory. Client-specific records with sources and dates let agents reflect current agreements rather than outdated ones. Developers must still decide what agents should remember, keep data from different clients separate, and provide a way to correct wrong records, since search can miss or return outdated information.

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