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Keep shoppingOpenClaw AI Agents: Build Your First Autonomous Agent
New
115 students
OpenClaw AI Agents: Build Your First Autonomous Agent
Learn OpenClaw fundamentals, configure LLMs, understand gateway architecture, and build your first AI agent from scratch
Created byYotta Academy
Last updated 7/2026
English
English [Auto],
What you'll learn
- Understand the evolution from AI assistants to autonomous AI agents and the AI agent lifecycle.
- Install and configure OpenClaw, initialize a workspace, and understand its gateway architecture.
- Configure LLM providers and manage model settings such as temperature, tokens, and response parameters.
- Build and test your first AI agent using OpenClaw, including agent roles, goals, system prompts, and configuration files.
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Course content
4 sections • 16 lectures • 45m total length
Requirements
- No prior experience with OpenClaw or AI agents is required.
- Basic familiarity with artificial intelligence and large language models is helpful but not necessary.
- A computer with an internet connection is required for installing and using OpenClaw.
- Basic command-line or terminal familiarity is helpful for following the setup demonstrations.
- Learners should be willing to explore AI agent concepts and follow hands-on technical demonstrations.
Description
This course contains the use of artificial intelligence.
Step into the world of autonomous AI agents and learn how to build your first agent with OpenClaw.
AI is rapidly evolving from simple chatbots and assistants that respond to individual prompts into autonomous agents capable of reasoning, interacting with tools, managing tasks, and working through multi-step objectives. OpenClaw provides a powerful foundation for building and managing these intelligent agent systems.
In this course, you'll begin by understanding the evolution from traditional AI assistants to autonomous AI agents. You'll explore the AI agent lifecycle, understand how agentic systems operate, and learn how OpenClaw fits into the modern AI development ecosystem.
You'll then dive into OpenClaw's gateway architecture and learn how its core components work together. You'll explore the background daemon, WebSockets, routing, sessions, authentication, and device pairing. Through practical demonstrations, you'll install OpenClaw, initialize a workspace, start the gateway, and inspect traffic logs.
Next, you'll learn how to configure the LLM engine that powers your agents. You'll explore different model selection strategies, connect various LLM providers, and understand important configuration parameters such as temperature, token limits, and response settings.
Finally, you'll create your first AI agent. You'll understand the agent execution flow and agentic loop, define agent roles and goals, write effective system prompts, and work with agent configuration files. The course concludes with a practical demonstration where you create and test your first working AI agent using OpenClaw.
By the end of this course, you'll understand the core concepts behind autonomous AI agents and have the practical foundation needed to start building with OpenClaw. This course also provides a strong starting point for continuing into more advanced AI agent development and automation workflows.
Who this course is for:
- Beginners who want to understand autonomous AI agents and get started with OpenClaw.
- Students and developers interested in building AI-powered agent systems.
- AI enthusiasts who want to explore how modern AI agents work behind the scenes.
- Developers and technical professionals who want to configure LLMs and build their first AI agent.
- Anyone interested in learning the foundations of OpenClaw and practical AI agent development.