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    Tag: Agent Memory

    Sep 16
    16 min read
    The Evolution of Memory Architectures: Vector Stores vs. Graph-Based Agent Context

    Throughout the opening phases of the modern generative artificial intelligence surge, enterprise software teams treated long-term memory as a solved mathematical problem. When large language models were released with strict context limits, developers turned to Retrieval-Augmented Generation (RAG) powered by dense vector databases. The playbook was universally applied: extract unstructured enterprise documents, slice the text […]

    Sep 16
    13 min read
    The Battle for the Context Window: Why Long-Context Models Alone Won’t Solve Agent Memory

    The rapid expansion of foundation model context windows from four thousand tokens to one million, two million, and beyond was widely celebrated as the definitive solution to the memory dilemma in artificial intelligence. Venture presentations, enterprise pitch decks, and developer demonstrations confidently declared that the architectural complexities of external knowledge retrieval, semantic chunking, and complex […]