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Duration 7 hours
Course Outline
OpenClaw Foundations and Safety Model
- Defining what OpenClaw is, what it is not, and identifying scenarios where it is a suitable solution.
- Exploring core concepts: agents, tools, skills, memory, connectors, and approval mechanisms.
- Addressing corporate realities: data sensitivity, environment separation, and establishing safe defaults.
Setup, Configuration, and Initial Agent Execution
- Verifying prerequisites: Node.js, Git, API keys, and workspace folder structure.
- Installing OpenClaw, confirming the installation, and comprehending the project layout.
- Connecting an LLM provider, setting core configurations, and validating connectivity.
- Executing a starter agent with read-only actions initially, followed by the addition of controlled write actions.
Leveraging Built-in Tools and Effective Prompting
- Operating with common tools: file management, shell commands, and basic web tasks.
- Applying prompting patterns for predictable execution: defining constraints, step plans, and confirmations.
- Reviewing agent outputs, tool calls, and traces to identify potential issues early.
Applying Skills and Memory in Practice
- Adding and configuring skills to establish repeatable workflows.
- Understanding memory basics: determining what to store, what to avoid, and how to reset safely.
- Practical exercise: constructing a small workflow that utilizes memory carefully, including a clear stop condition.
Developing and Testing a Custom Skill
- Understanding skill structure, inputs and outputs, and the mechanism by which OpenClaw discovers and executes skills.
- Implementing a small business-oriented skill (e.g., summarizing a folder of reports into a brief summary).
- Testing approach: utilizing sample inputs, defining expected outputs, handling errors, and documenting the process.
Integrations, Operations, and Future Steps
- Integration patterns: managing chat and ticket workflows within a secure sandbox environment.
- Designing a repeatable automation flow: defining triggers, actions, reviews, approvals, and handoffs.
- Operational fundamentals: logging, auditability, configuration management, and preparing a pilot readiness checklist.
Requirements
- Familiarity with basic command line operations, including folder navigation, path management, and environment variables.
- Ability to install and execute developer tools on a workstation (such as Git and Node.js).
- Foundational experience in JavaScript or general scripting, including reading code and making minor edits.
Target Audience
- Developers and automation engineers seeking 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 evaluating self-hosted AI agent solutions.