Every AI agent has the same Achilles' heel, memory. Once a conversation ends, the context vanishes. The agent forgets what it learned, the user's preferences, and the resources it had. Traditional RAG systems try to solve this with flat vector databases, but they bring their own problems, such as fragmented context, ballooning token costs, and retrieval pipelines that behave like black boxes. Open...