What is AI Agent Memory Patterns — Build Agents That Remember?

Design patterns for adding persistent memory to AI agents. Covers conversation memory, entity extraction, knowledge graphs, tiered memory, and memory management strategies.

Is AI Agent Memory Patterns — Build Agents That Remember free to use?

Yes. AI Agent Memory Patterns — Build Agents That Remember is freely available on TokRepo. Check the Source & Thanks section on the asset page for the specific open-source license.

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Visit the asset page on TokRepo and click "Copy for agent" to get the installation instructions. Most assets can be installed with a single command.

AI Agent Memory Patterns — Build Agents That Remember

What Are Agent Memory Patterns?

Design patterns that define how an AI agent remembers information across conversations and sessions.

TL;DR: AI agent memory design patterns. Conversation buffer / summary memory / entity extraction / knowledge graph / hierarchical memory (Letta-style). Implemented by tools like Mem0/Letta/Zep. Essential for production agents.

6 Patterns

Conversation buffer — simplest; store all history
Conversation summary — LLM auto-summarizes
Entity memory — extract facts about people/projects
Knowledge graph — entity-relation graph
Hierarchical memory — core / recall / archive tiers
Sliding window + summary — recent in detail, older summarized

Selection Guide

Short conversations → buffer; long conversations → summary; multi-session → entity + vector; complex domain → knowledge graph; fully autonomous → hierarchical.

FAQ

Q: Does Claude Code have memory? A: Yes — the auto-memory system stores user/project/feedback memories under ~/.claude/projects/*/memory/.

AI Agent Memory Patterns — Build Agents That Remember

What Are Agent Memory Patterns?

6 Patterns

Selection Guide

FAQ

来源与感谢

讨论