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Most AI agents are built without a deliberate memory architecture. They accumulate conversation history until context windows overflow, retrieve documents with brittle vector searches and fail in unpredictable ways when information changes or contradicts itself. This book treats agent memory as an engineering discipline rather than a feature. You will learn how to design systems that remember what matters, forget what does not, retrieve accurately under pressure, scale without exploding costs and operate reliably across days of continuous use with multiple agents sharing state. The material progresses from first principles through working implementations in SQLite, PostgreSQL and vector indexes to production architectures for long-running autonomous agents. No single model, vendor or framework is assumed correct; the emphasis is on understanding mechanisms deeply enough to make your own trade-offs with confidence.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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