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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 is a suitable fit.
- Core concepts: agents, tools, skills, memory, connectors, and approvals.
- Corporate realities: data sensitivity, environment separation, and safe defaults.
Setup, Configuration, and First Agent Run
- Prerequisites check: Node.js, Git, API keys, and workspace folders.
- Install OpenClaw, verify the installation, and familiarize yourself with the project layout.
- Connect an LLM provider, set core configuration, and validate connectivity.
- Run a starter agent initially with read-only actions, then introduce 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: determining what should be stored, what should not, and how to reset safely.
- Practical exercise: build a small workflow that uses memory carefully (with a clear stop condition).
Building and Testing a Custom Skill
- Skill structure, inputs and outputs, and how OpenClaw discovers and executes skills.
- Implement a small business-oriented skill (example: summarize a folder of reports and produce a short 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 a repeatable automation flow: trigger, action, review, approvals, and handoff.
- Operational basics: logging, auditability, configuration management, and a pilot readiness checklist.
Requirements
- Familiarity with basic command line operations (folders, paths, environment variables)
- Ability to install and execute developer tools on your workstation (Git, Node.js)
- Basic JavaScript or scripting experience (reading code and making minor edits)
Audience
- Developers and automation engineers looking to build AI-powered assistants and internal tools.
- IT and operations professionals seeking to automate recurring support and administrative tasks.
- Technical product owners and team leads evaluating self-hosted AI agent solutions.
