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Course Outline

OpenClaw Foundations and Safety Model

  • Understanding what OpenClaw is, its limitations, and ideal use cases.
  • Core concepts: agents, tools, skills, memory, connectors, and approvals.
  • Corporate considerations: data sensitivity, environment separation, and safe defaults.

Setup, Configuration, and Initial Agent Execution

  • Prerequisites check: Node.js, Git, API keys, and workspace directories.
  • Installing OpenClaw, verifying installation, and understanding project structure.
  • Connecting an LLM provider, setting core configurations, and validating connectivity.
  • Running a starter agent with read-only actions initially, then adding controlled write capabilities.

Using Built-in Tools and Reliable Prompting

  • Working with common tools: file operations, shell commands, and basic web tasks.
  • Prompting patterns for predictable execution: constraints, step-by-step plans, and confirmations.
  • Reviewing agent outputs, tool calls, and traces to identify issues early.

Practical Application of Skills and Memory

  • Adding and configuring skills for repeatable workflows.
  • Memory fundamentals: determining what to store, what to avoid, and how to reset safely.
  • Practical exercise: building a small workflow that uses memory carefully (with a defined stop condition).

Developing and Testing a Custom Skill

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

Integrations, Operations, and Next Steps

  • Integration patterns: chat and ticket workflows in a secure 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 (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 tools.
  • IT and operations professionals aiming to automate repetitive support and administrative tasks.
  • Technical product owners and team leads evaluating self-hosted AI agent solutions.
 7 Hours

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Provisional Upcoming Courses (Require 5+ participants)

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