A Python-based, step-by-step tutorial with 18 progressive steps to build a lightweight AI agent inspired by OpenClaw. Includes runnable codebases per step and a reference implementation.
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What it is
A step-by-step tutorial to build your own AI agent, from a simple chat loop to a lightweight version of OpenClaw. It comprises 18 progressive steps, each with a README explaining key components and a runnable codebase. Example Project: pickle-bot.
How it works
The repository is organized into phases and steps:
- Phase 1: Capable Single Agent (Steps 0-6) covering chat loop, tools, skills, persistence, slash-commands, compaction, and web tools.
- Phase 2: Event-Driven Architecture (Steps 7-10) for multi-platform exposure, config hot-reload, channels, and websockets.
- Phase 3: Autonomous & Multi-Agent (Steps 11-15) adding routing, cron, multi-layer prompts, post-message-back, and agent dispatch.
- Phase 4: Production & Scale (Steps 16-17) focusing on concurrency control and memory. Each step includes a README and a runnable codebase.
Getting started
Prerequisites and initial setup:
- Configure API keys by copying the example config:
cp default_workspace/config.example.yaml default_workspace/config.user.yaml - Edit
config.user.yamlwith your API keys and provider choices. - See LiteLLM providers documentation for supported providers and provider examples for usage guidance.
Recent releases
RELEASES (latest 0):
- none
Traction
Stars: 1830 Forks: 320 Open issues: 3
Behind the repo
Not provided in the readme excerpt.
Caveats
License: MIT Language: Python Created: 2026-03-11 Last push: 2026-07-08