By Naresh | AI Delivery Manager & Agent Systems Architect | February 2026
Memory is the difference between an agent that feels intelligent and one that just executes prompts in a loop.
Most agent frameworks today treat memory as an afterthought — a single vector store bolted onto a RAG pipeline and called done. But as AgentOS architectures mature into multi-agent, multi-session, long-horizon systems, memory becomes the central nervous system. Get it wrong and your agents hallucinate, repeat themselves, lose context, or fail to generalize. Get it right and you have an agent that genuinely learns from its environment.
This post breaks down every major memory paradigm — VectorDB, GraphDB, Key-Value, Relational, In-Context, Procedural, and Hybrid — and tells you exactly when to use each in an AgentOS context.
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