LangGraph explained in 1 minute

You can get an LLM to call a tool in an afternoon. Getting an agent to behave predictably over many steps, or across a whole team of agents, is the harder problem, and it's the one LangGraph is built to solve. This one-minute explainer from LangChain Academy shows how LangGraph models an agent as a graph, where nodes do the work and edges decide what happens next. It also covers shared state, which lets a run pause for a person's approval and resume exactly where it stopped, or recover a failed agent at step 50 instead of starting over. Chapters: 0:00 Why agents fail over many steps 0:19 What