The future of AI isn't a single powerful model — it's teams of specialized agents working together. Multi-agent systems (MAS) can divide complex problems, debate solutions, critique each other, and deliver better results than a single LLM prompt. In this tutorial, we'll build a complete multi-agent system from scratch using Python, focusing on core concepts before using any fancy framework. What We’ll Build A research and content creation team consisting of 4 agents: Planner Agent — Breaks down the task Researcher Agent — Gathers information Writer Agent — Creates the content Critic Agent — Reviews and improves output Prerequisites Python 3.10+ OpenAI API key (or any LLM provider) Basic understanding of Python classes and APIs `Step 1: Define the Agent Class Pythonfrom openai import OpenAI from typing import List, Dict import json client = OpenAI() class Agent: def init (self, name: str, role: str, tools=None): self.name = name self.role = role self.tools = tools or [] self.memory = [] def think(self,…