LangGraph models LLM agents as explicit state graphs instead of an opaque loop. When it beats the traditional LangChain agent loop, how checkpointing and failure recovery work, and how to structure flows that do not fall apart the moment they reach production.
LangChain is a Python framework that unifies building LLM applications: prompt templates, retrievers over vector databases, function-calling agents, and conversational memory. It earns its keep in fast prototypes and multi-model systems, but for a single well-defined production use case, direct code usually stays more maintainable.
6 min2664.4
We use first- and third-party cookies to analyze site traffic. You can accept them, reject them, or configure your choice.
Learn more about cookies
Cookie preferences
NecessaryEssential for the site to work. Always on.
AnalyticsHelp us understand how the site is used (Google Analytics).