Exploring User Memory for AI Applications

I’ve been diving into the concept of user memory in AI applications, and I wanted to get your thoughts. Most LLMs today rely on short-term context (session-based) or external knowledge sources (like RAG). But what if we could give them long-term, user-specific memory?

This opens up a lot of potential for personalization in AI systems, where the model retains information about individual users over time—like preferences, past conversations, and behaviors—making interactions more intelligent and tailored.

What are your thoughts on implementing scalable, profile-based memory in LLMs? Are there any frameworks or approaches you’ve explored for this? I'd love to hear how others are tackling user-centric memory management for LLM-based applications!

Looking forward to your insights!