Openclaw AI Memory Setup with SQL + Qwen 3.5 🧠#openclaw #ai #shorts

This tutorial demonstrates how to set up persistent memory for Openclaw AI using SQL database integration with Qwen 3.5 model. The setup enables AI agents to retain conversation history and context across sessions, preventing loss of chat data. The guide covers the Athena tutorial approach for implementing this memory system in Openclaw.

Key Points

• •Implement persistent memory storage using SQL databases to prevent loss of AI chat history
• •Integrate Qwen 3.5 language model with Openclaw for enhanced AI agent capabilities
• •Use Athena tutorial framework as the official reference implementation
• •Configure database connections to store and retrieve conversation context
• •Enable stateful AI agents that maintain context across multiple sessions
• •Leverage SQL for scalable memory management in production environments
• •Combine vector embeddings with traditional SQL for hybrid memory retrieval

Workflow Diagram

Concepts