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Course Outline

OpenClaw Foundations and Safety Model

  • Understanding what OpenClaw is, what it is not, and its ideal use cases.
  • Core concepts: agents, tools, skills, memory, connectors, and approval processes.
  • Corporate considerations: data sensitivity, environment separation, and safe default configurations.

Setup, Configuration, and First Agent Run

  • Prerequisites check: Node.js, Git, API keys, and workspace directories.
  • Installing OpenClaw, verifying the installation, and navigating the project structure.
  • Connecting an LLM provider, setting core configuration parameters, and validating connectivity.
  • Running a starter agent with read-only actions initially, then progressing to controlled write operations.

Using Built-in Tools and Reliable Prompting

  • Working with standard tools: file manipulation, shell commands, and basic web tasks.
  • Prompting patterns for predictable execution: constraints, step plans, and confirmations.
  • Reviewing agent outputs, tool calls, and traces to identify and resolve 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 utilizes memory carefully (including clear stop conditions).

Building and Testing a Custom Skill

  • Understanding skill structure, inputs/outputs, and how OpenClaw discovers and executes skills.
  • Implementing a business-oriented skill (e.g., summarizing a folder of reports to produce a brief).
  • Testing methodology: sample inputs, expected outputs, error handling, and documentation.

Integrations, Operations, and Next Steps

  • Integration patterns: chat and ticket workflows within a safe sandbox environment.
  • Designing repeatable automation flows: triggers, actions, reviews, approvals, and handoffs.
  • Operational essentials: logging, auditability, configuration management, and a pilot readiness checklist.

Requirements

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

Audience

  • Developers and automation engineers looking to build 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.
 7 Hours

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