LangGraph: agent building features and setup

Overview

LangGraph suits cases where an agent needs to perform a long-running process or combine predictable steps with model decisions. The process is defined as a graph, and the code determines what data is saved and how execution moves between steps. It is infrastructure for developers, not a ready-made website widget. You can also use it without building the entire system on LangChain. Its main value can be assessed through recovery, resuming work, and understanding why a particular path was chosen.

Features

• Graphs that combine fixed logic with model-driven steps.
• Mechanisms for persistent execution, state saving, and streaming results.
• Intervention points and human approval within a process.

Business uses

• A document review process that pauses for approval and resumes from the same point.
• A research agent that uses tools and then passes its result for a defined review.

Getting started

• Define a small state structure and a graph with two or three steps.
• Add state saving and test stopping and resuming the same task.
• Restrict external actions and build tests for transitions and tool failures.

What to check

• This is an infrastructure library. The application remains responsible for user authentication and permissions.
• Saving state alone does not prevent a duplicate action in an external system, so design writes to be safe to retry.