If you're building LangChain agents, this cuts through the API confusion and focuses on create_agent(), which is what actually works in production. It covers the middleware patterns you'll need for human-in-the-loop workflows and error handling, plus proper tool definition with the @tool decorator. The examples show real patterns like state persistence with MemorySaver and structured output validation. Most LangChain tutorials still reference deprecated agent classes, so this keeps you on the current approach that won't break in six months.
npx skills add https://github.com/langchain-ai/langchain-skills --skill langchain-fundamentals