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Duration 7 hours
Course Outline
OpenClaw Fundamentals and Safety Model
- Understanding OpenClaw: its capabilities, limitations, and ideal use cases.
- Core concepts: agents, tools, skills, memory, connectors, and approval mechanisms.
- Corporate considerations: data sensitivity, environment isolation, and safe default settings.
Setup, Configuration, and Initial Agent Execution
- Verification of prerequisites: Node.js, Git, API keys, and workspace directories.
- Installing OpenClaw, validating the setup, and understanding the project structure.
- Integrating an LLM provider, configuring core settings, and confirming connectivity.
- Running a starter agent with read-only actions, progressively introducing controlled write actions.
Leveraging Built-in Tools and Effective Prompting
- Utilizing common tools for file management, shell commands, and simple web tasks.
- Prompting strategies for predictable execution, including constraints, step-by-step plans, and confirmations.
- Reviewing agent outputs, tool calls, and execution traces to identify issues early.
Skills and Memory in Practice
- Adding and configuring skills for repeatable workflows.
- Memory management: determining what to store, what to exclude, and how to reset safely.
- Practical exercise: constructing a small workflow that utilizes memory with a clear stopping condition.
Developing and Testing Custom Skills
- Understanding skill structure, input/output requirements, and how OpenClaw discovers and executes skills.
- Implementing a small business-oriented skill, such as summarizing a folder of reports into a concise brief.
- Testing methodologies: using sample inputs, verifying expected outputs, handling errors, and documenting the process.
Integrations, Operations, and Future Directions
- Integration patterns for chat and ticket workflows within a secure sandbox environment.
- Designing repeatable automation flows: defining triggers, actions, reviews, approvals, and handoffs.
- Operational fundamentals: logging, auditability, configuration management, and a pilot readiness checklist.
Requirements
- Proficiency with basic command line operations, including folders, paths, and environment variables.
- The ability to install and run developer tools such as Git and Node.js on your workstation.
- Familiarity with basic JavaScript or scripting, including the ability to read code and make minor edits.
Audience
- Developers and automation engineers looking to create AI-powered assistants and internal tools.
- IT and operations professionals aiming to automate recurring support and administrative tasks.
- Technical product owners and team leads assessing self-hosted AI agent solutions.
