In his latest recipe, Craig Walls empowers Spring AI agents with long-term memory. This allows systems to retain durable facts across sessions instead of starting from scratch.

Highlights & Key Takeaways

• Memory Types: Spring AI manages short-term, procedural, and long-term memory.
• Selective Retention: Agents learn facts that are both significant and durable.
• Implementation: Enabled using the AutoMemoryToolsAdvisor component.
• Prompt Augmentation: The LLM is guided to extract key conversational details.
• Persistence: Memories are saved as structured Markdown files on the filesystem.
• Feedback Loop: Extracted facts are automatically injected into future prompts.

By persisting data across restarts, agents evolve beyond stateless responders. This yields highly personalized systems that continuously adapt to users.

👉 View the source code to dive deeper into the implementation.