AI memory tools and articles

Build AI systems that remember the right context.

AI Memory WD curates the tools, implementation references, and writing that help builders design durable memory for agents, assistants, and personalized AI products.

Memory map

Long-term user memory
Agent state and thread history
Semantic retrieval and recall
Reflection loops and preference learning

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Featured tools

Useful memory infrastructure.

ToolFeatured

Mem0

Memory layer for personalized AI agents.

Mem0 provides an API and open source memory layer for AI applications that need user-specific context over time.

agent memorypersonalizationapi
ToolFeatured

Zep

Long-term memory for AI assistants and agents.

Zep is built for agent memory, chat history, entity extraction, and retrieval over evolving user context.

long-term memoryagentsretrieval

Short-term and long-term memory patterns for graph agents.

LangGraph documents practical memory approaches for stateful AI agents, including thread-level state and persistent stores.

langgraphagent statepersistence

Featured articles

Read before you choose an architecture.

Research entry point for memory mechanisms in agent systems.

A reading starting point for comparing episodic, semantic, working, and procedural memory patterns in AI agents.

researchsurveyagent architecture

How reflection loops connect to agent memory.

An accessible article for understanding how agents can review prior actions and use stored context to improve future behavior.

reflectionagentsdesign patterns