Four agentic AI memory systems for smarter LLMs

AI agents , and the large language models (LLMs) that power them, have short memories. There is only so much conversation that can be encoded into tokens and accessed reliably by the LLM. Retrieval-augmented generation , or RAG, can be used to give agents and LLMs memories larger than their context windows.