Agent memory explained in 12 minutes: working, procedural, semantic and episodic
_AustinCalvert_ · x · 2026-10-26
A 12-minute explainer video, paired with a LangChain blog post, walks through how AI agent memory actually works:
- Memory types: working memory & context, plus procedural, semantic and episodic memory
- Stack: RAG, vector DBs and Top-K search for storing and retrieving past conversations and events
- Learning loop: capture traces → analyze mistakes → update memory, with consolidation and summarization for long-running agents
- Efficiency: token usage considerations
The takeaway: as agents take on bigger, longer tasks, memory becomes essential for keeping context and building on past work. A solid starting point for agent-memory newcomers.
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