OpenClaw: Beginner to Expert
OpenClaw: Beginner to Expert
OpenClaw is an open-source, local-first personal AI assistant, created by Peter Steinberger. This book provides a comprehensive guide from getting started to production deployment, with deep dives into the underlying mechanisms and implementation principles.

Highlights
Note: this English page is currently an overview. The full chapter-by-chapter content is maintained in Chinese; for complete reading, use the Chinese README and table of contents.
Hands-on: Build a minimal working loop from scratch, with ready-to-use configuration templates
Deep Dives: Detailed analysis of Gateway, Agent Loop, tool system, sessions and memory
Production-Ready: Focus on reliability, security hardening, monitoring and troubleshooting
Target Audience & Prerequisites
Target Audience: Individual users interested in AI agents, AI application developers, LLM engineers, system architects, etc.
Prerequisites: Basic backend development familiarity is expected, such as Node.js or Python fundamentals. If you are new to LLMs and AI agents, see AI Beginner Guide and Agentic AI Guide.
Book Structure
Part 1: Getting Started
Ch 1–4
Overview, setup, first conversation, configuration & model access
Part 2: Advanced Usage
Ch 5–8
Tools & skills, context memory, multi-agent collaboration, automation & ops
Part 3: Internals & Engineering
Ch 9–12
Gateway protocol, Agent Loop internals, reliability, plugin extensions
Part 4: Practice & Optimization
Ch 13–16
Case studies, performance & cost optimization, troubleshooting, AI ecosystem integration
Appendix
—
Glossary, config templates, troubleshooting checklist, API reference, command cheatsheet, version mapping, further reading, environment self-check tool, naming history, volatile facts table
How to Read
Online
Local Preview
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5-Minute Quick Start
New to OpenClaw? Just three steps:
Install (1 min):
curl -fsSL https://openclaw.ai/install.sh | bash -s -- --no-onboard(locked-down environments should download and inspect the script first, or use the official manual/npm path)Initialize (2 min):
openclaw onboard --install-daemon→ follow the wizard to configure your model API key and install the background serviceChat (2 min): Run
openclaw dashboard, type "hello" in the Control UI chat, receive an AI response — you're done! 🎉
See Chapter 2: Setup and Chapter 3: First Conversation.
Learning Paths
Different readers can choose their path:
Individual User
1→2→3→5→7
3-4 hours
Build a personal WhatsApp/Telegram AI assistant
App Developer
1-7→12
8-10 hours
Develop custom tools, skills and multi-agent systems
Ops Engineer
2→3→8→11→14→15
6-8 hours
Production deployment, security hardening & troubleshooting
Architect
1→9→10→12→16
6-8 hours
Understand internals, design enterprise-grade agent architecture
Related Books
This book is part of an AI technology series:
Zero-to-one AI introduction
Agent prompt design fundamentals
Context management & memory architecture
Claude MCP protocol, tools & Agentic Coding
General agent architecture & multi-agent patterns
Agent security design & attack/defense practices
Deep dive into LLM architecture
Contributing
Welcome to submit Issues or PRs. Especially welcome: typo fixes, broken link repairs, case study additions, and reusable templates.
License
This book is licensed under CC BY 4.0.
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