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Duration 7 hours
Course Outline
OpenClaw Foundations and Safety Model
- Understanding what OpenClaw is, what it is not, and when it fits best
- Core concepts: agents, tools, skills, memory, connectors, and approvals
- Corporate considerations: data sensitivity, environment separation, and safe defaults
Setup, Configuration, and First Agent Run
- Prerequisites check: Node.js, Git, API keys, workspace folders
- Install OpenClaw, verify installation, and understand project structure
- Connect an LLM provider, set core configuration, and validate connectivity
- Run a starter agent with read-only actions initially, then add controlled write actions
Using Built-in Tools and Reliable Prompting
- Working with common tools: files, shell commands, and simple web tasks
- Prompting patterns for predictable execution: constraints, step plans, and confirmations
- Reviewing agent outputs, tool calls, and traces to identify issues early
Skills and Memory in Practice
- Adding and configuring skills for repeatable workflows
- Memory basics: what to store, what to avoid, and how to reset safely
- Practical exercise: build a small workflow using memory carefully (with clear stop conditions)
Building and Testing a Custom Skill
- Skill structure, inputs/outputs, and how OpenClaw discovers and runs skills
- Implement a small business-oriented skill (e.g., summarize a folder of reports and produce a brief)
- Testing approach: sample inputs, expected outputs, error handling, and documentation
Integrations, Operations, and Next Steps
- Integration patterns: chat and ticket workflows in a safe sandbox environment
- Designing repeatable automation flows: trigger, action, review, approvals, and handoff
- Operational basics: logging, auditability, configuration management, and pilot readiness checklist
Requirements
- Familiarity with basic command-line usage (folders, paths, environment variables)
- Ability to install and run developer tools on your workstation (Git, Node.js)
- Basic experience with JavaScript or scripting (reading and making small edits)
Audience
- Developers and automation engineers looking to build AI-powered assistants and internal tooling
- IT and operations professionals seeking to automate recurring support and administrative tasks
- Technical product owners and team leads evaluating self-hosted AI agent options
