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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 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 understand the project structure.
  • Connect an LLM provider, set core configuration, and validate connectivity.
  • Run a starter agent, beginning with read-only actions, then adding 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 (e.g., 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

  • Proficiency with basic command line operations (folders, paths, environment variables).
  • Ability to install and run developer tools on your workstation (e.g., Git, Node.js).
  • Basic experience with JavaScript or scripting (reading and making minor edits).

Audience

  • Developers and automation engineers aiming to build AI-powered assistants and internal tooling.
  • IT and operations professionals looking to automate recurring support and administrative tasks.
  • Technical product owners and team leads evaluating self-hosted AI agent solutions.
 7 Hours

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