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Duration 7 hours
Course Outline
OpenClaw Fundamentals and Safety Framework
- Understanding what OpenClaw is, its limitations, and identifying suitable use cases
- Key concepts: agents, tools, skills, memory, connectors, and approval mechanisms
- Addressing corporate considerations: data sensitivity, environment isolation, and secure default settings
Setup, Configuration, and Initial Agent Execution
- Verifying prerequisites: Node.js, Git, API keys, and workspace directory structure
- Installing OpenClaw, confirming the setup, and analyzing the project structure
- Connecting an LLM provider, establishing core configurations, and testing connectivity
- Launching a basic agent with read-only capabilities initially, followed by the addition of controlled write permissions
Leveraging Built-in Tools and Effective Prompting Strategies
- Utilizing standard tools for file operations, shell commands, and basic web tasks
- Employing prompting patterns for consistent results, including constraints, step-by-step planning, and confirmation steps
- Analyzing agent outputs, tool invocations, and execution traces to detect issues proactively
Practical Application of Skills and Memory
- Adding and configuring skills to create repeatable workflows
- Memory management fundamentals: determining what data to store, what to exclude, and how to reset safely
- Practical task: developing a minor workflow that utilizes memory cautiously, with defined stopping criteria
Developing and Testing Custom Skills
- Understanding skill architecture, input/output handling, and the process by which OpenClaw detects and executes skills
- Creating a business-focused skill (e.g., summarizing a directory of reports into a concise brief)
- Testing methodologies: using sample inputs, validating expected outputs, managing errors, and documenting the process
Integrations, Operations, and Future Considerations
- Integration strategies for chat and ticket management workflows within a secure sandbox environment
- Designing a reproducible automation cycle: triggers, actions, reviews, approvals, and handoffs
- Operational essentials: logging, audit trails, configuration management, and a readiness checklist for pilot projects
Requirements
- Familiarity with fundamental command line operations, including directories, paths, and environment variables
- The capability to install and execute developer utilities on your local machine (such as Git and Node.js)
- Basic proficiency in JavaScript or general scripting (sufficient to read code and make minor modifications)
Target Audience
- Developers and automation engineers seeking to create AI-driven assistants and internal productivity tools
- IT and operations specialists looking to automate repetitive support and administrative duties
- Technical product owners and team leads assessing self-hosted AI agent solutions
