Most multi-agent AI tutorials hand you LangChain, AutoGen, or CrewAI and say “here you go.” You wire a few abstractions together, get something running, and never really understand what’s happening under the hood.

I wanted to understand what’s actually happening under the hood. So I built one from scratch.

This is the story of multi-agent-coder which is a system where a Planner decides at runtime which AI agent to call next, and a team of specialized agents (Architect, Engineer, Critic, TestRunner, Refactorer) collaborates to turn a plain English request into working, tested Python code.

No LangChain. No AutoGen. Pure Python.

The Core Idea

The central insight is simple: one LLM trying to do everything is worse than multiple LLMs each doing one thing well.

A single prompt asking an AI to “plan the architecture, write the code, review it for bugs, and refactor it” produces mediocre results across all four.…