Your agent has no memory. That is the problem.
Three memory types fix this permanently. Context is temporary. Memory is permanent.
Most AI agents forget the moment a session ends. Three memory layers fix that for good: implicit (baked into weights), explicit (RAG and vector DBs), and agentic (state that survives across sessions). A one-glance visual companion to the long-form post on the three paradigms of LLM memory.
Tags#Memory#AgenticMemory#RAG#VectorDB#Architecture#AIAgents
Key takeaways
- 1Most AI agents forget the moment the session ends. The window is not memory.
- 2Three memory types fix this permanently: implicit (inside the weights), explicit (RAG and vector DBs), and agentic (persists across tasks and sessions).
- 3Implicit memory holds general facts and stable knowledge. No retrieval needed.
- 4Explicit memory holds dynamic data, user docs, and anything you need to search. RAG and vector DBs sit here.
- 5Agentic memory is the layer most teams skip. It is what makes multi-session tasks, personalisation, and team agents actually work.
- 6Context is temporary. Memory is permanent. Give your agent a brain, not just a window.
