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Duration 7 hours
Course Outline
OpenClaw Foundations and Safety Model
- Understanding what OpenClaw is, its limitations, and when it is suitable
- Core concepts: agents, tools, skills, memory, connectors, and approvals
- Corporate considerations: data sensitivity, environment separation, and safe defaults
Setup, Configuration, and Initial Agent Run
- Prerequisites check: Node.js, Git, API keys, and workspace directories
- Install OpenClaw, verify the installation, and understand the project structure
- Connect an LLM provider, set core configuration parameters, and validate connectivity
- Execute a starter agent with read-only actions initially, then add controlled write capabilities
Utilizing Built-in Tools and Effective Prompting
- Working with common tools: files, shell commands, and basic 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 fundamentals: determining what to store, what to avoid, and how to reset safely
- Practical exercise: build a small workflow that uses memory cautiously (with clear stop conditions)
Developing and Testing a Custom Skill
- Skill structure, inputs/outputs, and how OpenClaw discovers and executes skills
- Implement a business-oriented skill (example: summarizing a folder of reports into a brief)
- Testing approach: sample inputs, expected outputs, error handling, and documentation
Integrations, Operations, and Next Steps
- Integration patterns: chat and ticket workflows within a secure sandbox environment
- Designing repeatable automation flows: trigger, action, review, approvals, and handoff
- Operational fundamentals: logging, auditability, configuration management, and pilot readiness checklist
Requirements
- Familiarity with basic command-line operations (folders, paths, environment variables)
- Ability to install and run developer tools on your workstation (Git, Node.js)
- Basic experience with JavaScript or scripting (reading code and making minor edits)
Audience
- Developers and automation engineers looking to build AI-powered assistants and internal tooling
- IT and operations professionals aiming to automate recurring support and administrative tasks
- Technical product owners and team leads evaluating self-hosted AI agent solutions
