OpenClaw AI Agents: Build Tools, Memory, RAG & Multi-Agent

About this course

This course contains the use of artificial intelligence.

Chatbots answer. Agents act. They reason, call tools, remember, look things up and work with other agents. In this course you build those agents yourself, with OpenClaw, step by step.

No slide-deck theory marathon. Every major concept comes with a hands-on demo you follow along with.

Who this course is for:

• Developers who want to add real AI agents to their skill set

Students looking to break into Agentic AIFreelancers and automation builders who want agents that use tools and automate workflowsAI engineers who want a structured path through OpenClaw

What you'll build, in order:

• A complete OpenClaw development environment, plus a clear picture of the OpenClaw architecture
• Your first AI agent, with roles, system prompts and different LLM providers configured
• Agents connected to communication channels
• Custom tools and reusable Skills that let your agents actually do things
• Short-term and long-term memory, with proper conversation context management
• Retrieval-Augmented Generation (RAG) apps that answer from external knowledge sources
• Collaborative multi-agent workflows where several agents work together on complex tasks

What's inside:

• Agent fundamentals and the full agent execution flow
• Advanced prompting techniques for more reliable agents
• Guardrails and prompt injection protection to keep agents secure
• Error handling so your agents don't fall over in real use

How it's structured:

We start from the ground up. First the fundamentals and setup. Then one agent. Then tools, Skills, memory and RAG. Finally, everything comes together in multi-agent workflows. Each step builds on the last, so you always know why you're doing what you're doing.

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