MetaGPT gives each agent a job title: product manager, architect, engineer, reviewer. Work moves between them the way it would in a company, and each hands the next a real artifact rather than a chat message.
Reach for it when
- The task genuinely decomposes into professional roles
- You want documents and diagrams, not just code
- You are exploring what structured multi agent work looks like
Look elsewhere when
- You want one agent doing one job
- You need tight control over each step
What the lessons will cover
- 01Install and setup
- 02Roles and actions
- 03The software company flow
- 04Custom roles
- 05Memory and environment
- 06Tools
- 07Cost control
- 08A full run
Others in multi agent
CrewAIAgents with a role, a goal and a backstory.
AutoGenAgents that solve problems by talking to each other.
CAMEL-AIStudying how large agent societies cooperate.Common questions
Is MetaGPT free to use?
MetaGPT is open source and free to run yourself. You still pay whichever model provider you point it at, and this tutorial is free with no signup.
Do I need to know Python to use MetaGPT?
Basic Python is enough. Functions, dictionaries and imports cover most of what MetaGPT asks of you.
When should I not use MetaGPT?
You want one agent doing one job. You need tight control over each step.
Lessons for MetaGPT are being written. Meanwhile the LangGraph tutorial covers the same ground: state, tools, loops, memory and human approval. Most of it carries straight over.
Start the LangGraph tutorial →