Guides hub · 7 tutorials
How to Build Memory Into AI Agents
Practitioner guides for adding memory to AI agents — step-by-step implementation for long-term memory, RAG+memory, personalization, persistence and cost optimization.
Implementation path
Start here
Add memory to any agent
The flagship step-by-step guide: choose a store, write memories, retrieve them, inject into context and evaluate before production.
Collection
All implementation guides
Add memory to an agent
Flagship step-by-step for any agent stack.
Start →Build long-term memory
Extraction, embedding, storage and consolidation pipeline.
Guide →RAG with memory
Combine static knowledge and dynamic user memory.
Guide →Persist conversation memory
Cross-session chatbot context without blowing the window.
Guide →User memory personalization
Per-user preferences and history over time.
Guide →Multi-agent shared memory
Common stores, namespacing and write conflicts.
Guide →Reduce token cost
Memory and summarization to cut prompt size.
Guide →Paths
Choose your path by goal
| Goal | Start with |
|---|---|
| Durable cross-session memory | Build long-term memory |
| Chatbot session persistence | Persist conversation memory |
| Per-user personalization | User memory personalization |
| Docs + user state together | RAG with memory |
| Multi-agent teams | Multi-agent shared memory |
| Lower token bills | Reduce token cost |
Framework quick-starts: best tools · Engram · LangMem · Mem0
FAQ
Frequently asked questions
Which guide should I read first?
Start with how to add memory to an AI agent — the flagship step-by-step that covers store selection, write, retrieve and inject for any stack.
Do the guides include code examples?
Yes — guides are practitioner-focused with implementation patterns. The flagship add-memory guide walks through a complete integration; specialized guides go deeper on LTM, RAG+memory, persistence and more.
How do I add memory to LangGraph?
Use LangMem for native LangGraph checkpointer integration, or Engram/Mem0/Zep as framework-agnostic APIs. See LangMem and add memory guide.
How do I persist memory like Claude?
External memory stores persist across sessions — unlike model-native memory. See persist conversation memory for chatbot patterns.
Can I add memory to n8n agents?
Yes via HTTP APIs from memory services (Mem0, Supermemory) or custom store integrations. The add-memory guide patterns apply to any agent orchestrator.
How do I integrate CRM data into agent memory?
Sync CRM fields into semantic memory on user identification — treat CRM as a write source, not the memory store itself. See user memory personalization.
How do I test memory before production?
Run LOCOMO and LongMemEval subsets on your use-case queries. See evaluation hub and step 5 of the add-memory guide.
What's the production checklist for agent memory?
Choose framework → implement write/retrieve → add eviction policy → handle conflicts → benchmark → monitor latency/cost/storage growth. See memory management.