# Hands-On, Practical Demo of LangGraph Supervisor Architecture

> Source: <https://pub.towardsai.net/hands-on-practical-demo-of-langgraph-supervisor-architecture-fef08825281f?source=rss----98111c9905da---4>
> Published: 2026-07-31 05:58:26+00:00

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# Hands-On, Practical Demo of LangGraph Supervisor Architecture

## A simple, step-by-step guide to how a Supervisor-agent routes tasks between specialized-agents, with complete working code.

## Introduction

As an AI application grows, it often makes sense to ** divide** responsibilities across multiple specialized AI agents. Instead of having one agent handle every type of request, you can create separate agents, each designed for a specific task.

**For example**— one agent might calculate the

**square** of a number, while another calculates its

**cube**.

But once you have multiple agents, a new question comes up: **How does the application decide which agent should handle a user’s request?**

The simplest approach is to write **conditional statements**:

**1] If the user asks for a square, send the request to the Square Agent.**

**2] If the user asks for a cube, send the request to the Cube Agent.**

This works for **small** applications with only a few agents. But as more specialized agents are added, the routing logic becomes **harder** to maintain. At the same time, users can phrase the same request in many different ways, making rule-based routing **less reliable**.

The **Supervisor pattern** in LangGraph solves this problem. Instead of relying on hardcoded rules, you create a **Supervisor-Agent** whose job is to decide which specialized agent should handle…