Yesterday, we launched LLMs as Operating Systems: Agent Memory with Letta. LLMs have limited input space, so managing context is crucial to maintain speed and reduce costs. In the innovative MemGPT paper, its authors, including the course instructors introduced an LLM agent that uses persistent memory to select relevant information efficiently. Using Letta’s open-source framework, this course will show you how to implement MemGPT, adding long-term memory to your LLM agents. Enroll for free: http

New short course: LLMs as Operating Systems: Agent Memory, created with Letta, and taught by its founders Charles Packer and Sarah Wooders. An LLM's input context window has limited space. Using a longer input context also costs more and results in slower processing. So, managing what's stored in this context window is important. In the innovative paper "MemGPT: Towards LLMs as Operating Systems," its authors (which include Charles and Sarah) proposed using an LLM agent to manage this context wi