AI Operating System Bootcamp: OpenClaw + Claude + Clawdbot

Build a full AI OS using Claude, multi-agent systems, memory, and automation with real-world projects

What you’ll learn
Build a complete AI Operating System by combining agents, memory, and automation into one unified system
Design and deploy intelligent AI agents using structured prompts, reasoning, and multi-step workflows
Create and manage multi-agent systems with supervisor-worker architectures and task orchestration
Implement memory-driven AI systems using vector databases, embeddings, and context injection techniques
Develop tool-calling and automation pipelines to connect AI with real-world APIs, workflows, and data systems
Build long-running autonomous AI systems with event-driven execution, scheduling, and feedback loops
Optimize AI systems for performance, cost, and scalability including token efficiency and latency reduction
Apply skills through real-world projects like personal AI assistants, business automation systems, and research agents

Requirements
Basic understanding of programming concepts (Python or JavaScript is helpful but not mandatory)
Familiarity with using web applications and APIs is a plus, but everything will be explained step-by-step
No prior experience in AI or machine learning is required — this course starts from fundamentals
A computer or laptop with a stable internet connection
Willingness to learn by building real-world projects and experimenting with AI systems

Description
“This course contains the use of artificial intelligence”

Are you ready to go beyond using AI tools and start building complete AI systems?

This course is your step-by-step guide to designing and building a full AI Operating System using Claude, multi-agent architectures, memory systems, and automation pipelines. Instead of learning isolated tools, you will learn how to combine them into scalable, real-world systems.

You will start by understanding the foundations of Agentic AI, including how modern systems evolve from simple prompts to intelligent, autonomous workflows. Then, you’ll dive deep into building intelligent agents, designing multi-step reasoning systems, and implementing multi-agent orchestration.

One of the most powerful aspects of this course is learning how to build memory-driven AI systems, enabling your agents to retain context, learn from interactions, and make better decisions over time. You will also learn how to connect AI with real-world tools through function calling, APIs, and automation pipelines.

As you progress, you will build long-running autonomous systems, implement feedback loops, and optimize performance for cost, latency, and scalability.

Finally, you’ll apply everything through high-value capstone projects, including

• A personal AI operating system

• A business automation pipeline

• An autonomous research agent

By the end of this course, you won’t just understand AI — you’ll be able to design, build, and deploy real-world AI systems like an AI Architect.

Who this course is for
Developers who want to transition into AI Engineering and learn how to build real-world AI systems, not just use tools
Students and beginners who want a structured path into AI, starting from fundamentals to advanced system design
Professionals looking to automate workflows and increase productivity using intelligent AI systems
Founders and entrepreneurs who want to build AI-powered products, SaaS tools, or automation businesses
Anyone curious about how modern AI systems work and wants to go from prompt user → system builder