This article was originally published on AI Study Room . For the full version with working code examples and related articles, visit the original post.

Building Custom AI Agents with LangGraph: A Practical Guide

LangGraph extends LangChain with graph-based state machine orchestration for building reliable, multi-step AI agent workflows. Unlike traditional linear chains, LangGraph lets you define cyclic graphs with conditional routing, persistent state, and human-in-the-loop checkpoints.

Why LangGraph?

Most agent frameworks chain LLM calls linearly: call LLM, parse output, call tool, repeat. This breaks for complex tasks requiring loops, branching, or manual approval.…