Understanding OpenClaw by Building One

github.com

2 points·zane__chen··3 comments

I wanted to really understand how AI agents work, so I spent two weeks building one from scratch. Then I turned my learning into a step-by-step tutorial.

18 progressive steps — each adds one concept, each has runnable code. Some highlights from the journey:

- Step 0: Chat Loop — Start with the basics. Just you and the LLM, talking. - Step 1: Tools — Give your agent the ability to take actions. - Step 2: Skills — Dynamically load capabilities as needed. - Step 6: Web Tools — Agent can search and read the web. - Step 11: Multi-Agent Routing — Multiple agents, right one for the right job. - Step 15: Agent Dispatch — Agents that can collaborate with each other. - Step 17: Memory — Long-term knowledge that persists across sessions.

Each step is self-contained with a README + working code.

[https://github.com/czl9707/build-your-own-openclaw](https://github.com/czl9707/build-your-own-openclaw)

Hope this helpful! Feedback welcome.

Projects like this are a great way to understand how complex systems actually work under the hood.

Rebuilding something yourself often reveals design decisions that aren’t obvious when you only read documentation or use the tool as a black box.

Curious what parts were the most difficult to reproduce compared to the original OpenClaw implementation.

Appreciated! For me, the most difficult pieces are the pieces I haven't tried my self! The browser operation and interaction with coding agent in this case.

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