One of the biggest challenges in building conversational AI is that LLMs are stateless by default—they don't remember what you said five seconds ago. In this course, we solve this by implementing Short-Term Memory using LangGraph's persistence layer.

We will dive deep into "Checkpointers," the mechanism that saves the state of your graph after every step. You will learn how to create conversational agents that maintain context across multiple turns, distinct user sessions, and even allow for "time travel"—the ability to rewind and edit the conversation history. By the end, you will have the skills to transform a forgetful LLM into a context-aware partner.