AgentScope Agent Memory
An agent that forgets what it just tried is doomed to repeat its own mistakes. As covered in the general agent memory architecture post earlier in this series, managing what an agent remembers — and how much of it stays in active context — is one of the harder practical problems in …
Agent Memory Architecture
An agent working through a long, multi-step task needs to remember what it's already tried, what it's learned, and what still needs doing — but an LLM's context window, as covered in the tokens post earlier in this series, is finite. Agent memory architecture is the set of...
LangChain Memory Concepts
Introduction: The Stateless Nature of LLMs Large Language Models are fundamentally stateless. Each API call is an independent transaction. The model does not remember what you asked five minutes ago unless you explicitly include that history in the new prompt. This...