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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.

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