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Skills as Contextual Memory: Reusable Procedural Knowledge for LLM Agents
Anthropic's Skills pattern packages reusable procedural knowledge as folders of instructions, scripts, and resources. Progressive disclosure loads only the metadata at startup and brings in the details on demand. Context capacity becomes effectively unbounded.
Generative Agents Memory: The Stanford Architecture for Persistent LLM Agents
Stanford's Smallville study ran 25 LLM agents that formed relationships and organized events autonomously. The mechanism that made their behavior coherent over days was a three-part memory system: observation, scored retrieval, and periodic reflection.
Short-Term and Long-Term Memory for LLM Agents
An agent with no memory repeats itself. An agent with bad memory contradicts itself. Getting memory right means splitting it into kinds: short-term for the session, long-term for durable facts, procedural for how-to, episodic for what-happened.
The Augmented LLM: Retrieval, Tools, and Memory
A bare language model is a closed system. It cannot look up a fresh fact, cannot act in the world, cannot remember the last conversation. Every non-trivial agent is an attempt to lift one or more of those three constraints.