langchain-fundamentals

Build LangChain agents with persistent memory by implementing MemorySaver checkpointers to maintain conversation state across multiple invocations. This approach ensures robust stateful AI agents retain context reliably throughout continuous interactions.

Add human-in-the-loop approval to LangGraph workflows by applying middleware control patterns for custom error handling and production safety. This middleware intercepts agent execution to enforce human approval before critical tool execution.

Enforce structured output validation and recursion limits in LangChain agents by using the standardized create_agent pattern. This pattern applies Zod schema validation and sets recursion boundaries to prevent infinite agent loops during tool execution.

LangChain works with Zod to provide structured output validation in production agents. This integration ensures reliable tool execution by validating agent responses against defined schemas before returning results to the user.

LangChain agents loop infinitely during tool execution when recursion limits are not configured. Prevent this by implementing the create_agent pattern with built-in recursion boundaries and custom error handling middleware for production safety.