OpenClaw Training Course
OpenClaw is an open-source autonomous AI agent capable of executing actions on your behalf through integrated tools and services.
This instructor-led live training, available online or onsite, is designed for intermediate-level developers and technical professionals looking to leverage OpenClaw to create and deploy practical AI agents that automate tasks via chat and tool integrations.
Upon completing this training, participants will be able to:
- Describe what OpenClaw is and its role within automation and AI assistant architectures.
- Install and configure OpenClaw, link an LLM provider, and execute an agent with appropriate safety controls.
- Utilize and customize tools and skills to automate routine workflows, including file operations, web searches, and team messaging actions.
- Implement guardrails and operational best practices for responsible deployment in a corporate setting.
Course Format
- Interactive lectures and discussions.
- Guided exercises and hands-on practice.
- Practical implementation within a live-lab environment.
Course Customization Options
- For a customized training session, please contact us to arrange your requirements.
Course Outline
OpenClaw Foundations and Safety Model
- Understanding OpenClaw: its capabilities, limitations, and ideal use cases.
- Core concepts: agents, tools, skills, memory, connectors, and approval workflows.
- Corporate considerations: data sensitivity, environment separation, and secure default settings.
Setup, Configuration, and Initial Agent Execution
- Prerequisites verification: Node.js, Git, API keys, and workspace directories.
- Installing OpenClaw, verifying the installation, and navigating the project structure.
- Connecting an LLM provider, setting up core configurations, and validating connectivity.
- Running a starter agent with read-only actions initially, then introducing controlled write operations.
Utilizing Built-in Tools and Effective Prompting
- Working with common tools: files, shell commands, and basic web tasks.
- Prompting strategies for consistent execution: applying constraints, step plans, and confirmations.
- Reviewing agent outputs, tool calls, and traces to identify and resolve issues early.
Implementing Skills and Memory in Practice
- Adding and configuring skills for repeatable workflows.
- Memory fundamentals: determining what to store, what to avoid, and how to reset safely.
- Practical exercise: developing a small workflow that leverages memory carefully, including clear stop conditions.
Developing and Testing a Custom Skill
- Skill structure, inputs and outputs, and how OpenClaw discovers and executes skills.
- Implementing a small business-oriented skill (e.g., summarizing a folder of reports into a brief).
- Testing methodology: using sample inputs, verifying expected outputs, handling errors, and documentation.
Integrations, Operations, and Next Steps
- Integration patterns: managing chat and ticket workflows within a secure sandbox environment.
- Designing repeatable automation flows: defining triggers, actions, reviews, approvals, and handoffs.
- Operational basics: logging, auditability, configuration management, and a pilot readiness checklist.
Requirements
- Proficiency in basic command-line operations (e.g., managing folders, paths, and environment variables).
- Ability to install and run developer tools on your workstation (including Git and Node.js).
- Basic experience with JavaScript or scripting (able to read code and make minor edits).
Audience
- Developers and automation engineers aiming to build AI-powered assistants and internal tools.
- IT and operations professionals seeking to automate repetitive support and administrative tasks.
- Technical product owners and team leads assessing self-hosted AI agent solutions.
Open Training Courses require 5+ participants.
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