What problem does it solve? LangGraph agents lose conversation state between invocations by default, and developers struggle to correctly configure checkpointing, thread isolation, subgraph persistence scoping, and long-term memory across conversations. ## Core Features & Use Cases - Checkpointer Setup: Configure InMemorySaver for testing or PostgresSaver for production-grade durable state persistence. - Thread Management & Time Travel: Isolate conversations by thread_id, browse checkpoint history, replay past states, and fork from earlier checkpoints. - Subgraph Persistence Modes: Choose between checkpointer=False, None, or True to control interrupts, multi-turn memory, and parallel namespace isolation. - Long-Term Memory Store: Share user preferences and facts across threads using Store with put, get, search, and delete operations. - Use Case: You are building a multi-user chatbot where each user needs isolated conversation history plus shared long-term preferences; this Skill shows how to combine a Postgres checkpointer with a Store and correct thread_id configuration. ## Quick Start Ask the AI to set up a LangGraph graph with a Postgres checkpointer and thread-based conversation memory for your chatbot.