LangGraph has introduced long-term memory support in its platform, available for both Python and JavaScript, allowing agents to store and recall information between conversations to better learn from feedback and adapt to user preferences. This new feature, part of the open-source library, is automatically enabled for all LangGraph Cloud & Studio users, addressing the common issue of AI applications' inability to remember past interactions. Unlike many high-level "agent memory" products that attempt a one-size-fits-all approach, LangGraph's memory support is implemented as a simple, persistent document store, providing a flexible foundation for building custom memory solutions. The cross-thread memory capability extends LangGraph's existing short-term memory feature, enabling agents to maintain context across multiple conversation threads. This functionality includes cross-thread persistence, flexible namespacing, JSON document storage, and content-based filtering, all integral for organizing and retrieving memories efficiently. LangGraph offers various resources, including guides and templates, to assist users in implementing long-term memory in their applications, encouraging experimentation and feedback to refine these capabilities further.