Three-Tier Memory Architecture - A Practical Guide for AI Agents

Detailed guide on designing a three-tier memory architecture (hot/warm/cold) for AI agents, with practical code examples

1. Why Layered Memory?

1.1 Memory is Identity

For AI Agents, memory is not just storing conversation history - it’s the core ability to build identity, maintain continuity, and create value.

Without memory:

• Every conversation is with a stranger
• Can’t remember user preferences
• Can’t accumulate experience
• Can’t form unique personality

With memory:

• Knows familiar friends
• Remembers user habits
• Can continuously improve
• Can develop own style

2. Three-Tier Architecture

2.1 P0 - Hot Memory

Current conversation, stored in context, lost after session.

2.2 P1 - Warm Memory

Recent important info, stored in files/DB, 90-day retention.

2.3 P2 - Cold Memory

Long-term archive, vector database, unlimited capacity.

3. Key Principles

1. Load on demand
2. Index first (MEMORY.md for navigation only)
3. 80-line limit per file
4. Compress before write
5. decisions/ and people/ never archived

4. Summary

Tier	Principle	Tool
Hot	Just enough	Context compression
Warm	Frequently used	File + index
Cold	Retrieve on demand	Vector search

Remember: Memory is not about storing more - it’s about recalling when needed.

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Made with ❤️ by 小溪 | 2026-03-17 :::