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Course Outline

OpenClaw Foundations and Safety Model

  • Understanding what OpenClaw is, what it is not, and when it is a suitable choice
  • Core concepts: agents, tools, skills, memory, connectors, and approval processes
  • Corporate considerations: data sensitivity, environment separation, and safe default settings

Setup, Configuration, and First Agent Run

  • Prerequisites check: Node.js, Git, API keys, and workspace folders
  • Installing OpenClaw, verifying the installation, and understanding the project structure
  • Connecting an LLM provider, setting core configuration, and validating connectivity
  • Running a starter agent with read-only actions initially, followed by 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: building 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
  • Implementing a small business-oriented skill (example: summarizing a folder of reports and producing 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 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 create AI-powered assistants and internal tooling
  • IT and operations professionals seeking to automate repetitive support and administrative tasks
  • Technical product owners and team leads assessing self-hosted AI agent solutions
 7 Hours

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