Summary

The article discusses the importance of memory in AI agents, particularly how it enables them to learn from past interactions and improve their performance over time. It categorizes memory into three types: session memory, user memory, and learned memory, each with distinct characteristics and benefits. The author provides code examples for implementing these memory types in agents, emphasizing the significance of learned memory for enhancing agent capabilities. The article concludes with a discussion on what constitutes a good learning and the need for human oversight in the learning process.

💭 Your Thoughts

This article is quite basic, but the idea about "Save learnings — When it discovers something reusable, it saves it", maybe i can try it with my product FAST...

Technologies Referenced