AutoGPT is the project that put autonomous agents in front of everyone. You state a goal, and it plans, executes and loops on its own. It is the most ambitious end of the spectrum, and the one that needs the most guardrails.
Reach for it when
- You are exploring what fully autonomous agents can do
- The task is open ended and hard to specify as steps
- You can tolerate a wrong answer and a retry
Look elsewhere when
- The task has a known sequence. Write that sequence
- Errors are expensive and need approval gates
What the lessons will cover
- 01Install and setup
- 02Goals and constraints
- 03The agent loop
- 04Blocks and components
- 05Memory
- 06Running safely
- 07Cost control
- 08A guarded agent
Others in autonomous
AgnoFast, lightweight agents with memory built in.
LettaAgents that manage their own memory.
GriptapeStructured agents, pipelines and workflows.
smolagentsA tiny agent library that writes Python.Common questions
Is AutoGPT free to use?
AutoGPT 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 AutoGPT?
Basic Python is enough. Functions, dictionaries and imports cover most of what AutoGPT asks of you.
When should I not use AutoGPT?
The task has a known sequence. Write that sequence. Errors are expensive and need approval gates.
Lessons for AutoGPT 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 →