Get in Touch

Course Outline

OpenClaw Foundations and Safety Model

  • Understanding what OpenClaw is, its limitations, and appropriate use cases.
  • Core concepts: agents, tools, skills, memory, connectors, and approval mechanisms.
  • Corporate considerations: data sensitivity, environment isolation, and safe default settings.

Setup, Configuration, and First Agent Run

  • Prerequisites check: Node.js, Git, API keys, and workspace directories.
  • Install OpenClaw, verify installation success, and understand the project structure.
  • Connect an LLM provider, set core configurations, and validate connectivity.
  • Run a starter agent with read-only actions initially, then introduce controlled write operations.

Using Built-in Tools and Reliable Prompting

  • Working with common tools: file systems, 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.

Skills and Memory in Practice

  • Adding and configuring skills for repeatable workflows.
  • Memory essentials: determining what to store, what to avoid, 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 (example: summarize a folder of reports and produce a brief summary).
  • Testing approach: 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 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 proficiency in JavaScript or scripting (reading code and making minor edits)

Audience

  • Developers and automation engineers seeking 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 leaders evaluating self-hosted AI agent solutions.
 7 Hours

Related Categories