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Introduction & Course Outline

1. Five agents controlling their own browsers

2. The core agent decision loop (OTA)

The 4 main components

Example of a typical agent conversation (Codex)

3. The major players (Codex, Antigravity, Claude Code)

4. Which AI agent to use when & why

Brief walkthrough of Agent Skills

5. AGENTS.md & 6. Self-modifying agent instructions

7. Multi-agent MCP orchestration

8. Video-to-action pipelines

9. Stochastic multi-agent consensus

10. Agent chatrooms

11. Subagent verification loops

13. Prompt contracts

14. Reverse prompting

15. Multi-agent chrome usage

16. Context management

17. Optimizing AI agent & token pricing

Quiz

Quiz 1: Fundamentals of AI Agents

Quiz 2: The Core Agent Decision Loop

Quiz 3: Choosing the Right Agent

Quiz 4: Multi-Agent Orchestration

Quiz 5: Optimization and Context Management

Course Feedback

End of Course Survey

Multi-Agent Orchestration and Workflows

Understanding Multi-Agent Orchestration with Claude

Welcome to "Mastering Advanced AI Agents Using Claude," the ultimate course designed to take your AI automation skills to the next level. In today's rapidly evolving tech landscape, understanding how to build, orchestrate, and optimize autonomous AI agents is a game-changer.

Welcome to "Mastering Advanced AI Agents Using Claude," the ultimate course designed to take your AI automation skills to the next level. In today's rapidly evolving tech landscape, understanding how to build, orchestrate, and optimize autonomous AI agents is a game-changer. This comprehensive course dives deep into the core mechanics of AI agents, starting with the foundational Observe, Think, Act (OTA) decision loop. You will explore powerful tools like Claude Code, Codex, and Antigravity, learning exactly when and why to deploy each for maximum efficiency.

Beyond the basics, this course covers cutting-edge techniques such as self-modifying agent instructions, multi-agent MCP orchestration, and video-to-action pipelines where agents learn directly from video tutorials. You'll master complex workflows including stochastic multi-agent consensus, agent chatrooms for debate-driven outputs, and subagent verification loops to ensure flawless code generation. We also tackle advanced prompt engineering with prompt contracts and reverse prompting.

Finally, you'll learn how to scale your operations cost-effectively. Discover the secrets of context management using the Iceberg Technique and optimize your token pricing with the 60/30/10 model routing rule. Whether you're looking to automate browser tasks, build self-improving systems, or orchestrate a team of AI workers, this course provides the practical skills and theoretical knowledge you need to succeed. Join us and transform the way you work with AI!

Mastering Advanced AI Agents Using Claude

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            <p>The landscape of artificial intelligence has shifted from simple chat interfaces to autonomous, goal-driven agents capable of executing complex workflows. "Mastering Advanced AI Agents Using Claude" dives deep into the mechanics of these systems, exploring how agents can independently control browsers, process information through the core Observe-Think-Act (OTA) decision loop, and interact with their environments. By examining major platforms like Codex, Antigravity, and Claude Code, this course provides a comprehensive understanding of how to select, deploy, and manage the right AI agent for specific tasks. Learners will explore the foundational components that make AI agents work, moving beyond basic prompting to orchestrate sophisticated, self-directed AI systems.</p>

<p>Beyond individual agent mechanics, the curriculum explores the cutting edge of multi-agent orchestration and self-improving workflows. Participants will discover how to implement self-modifying agent instructions using AGENTS.md, build video-to-action pipelines, and establish stochastic multi-agent consensus where multiple AI personas debate and verify outcomes in dedicated chatrooms. The course also tackles critical engineering challenges, such as subagent verification loops, strict prompt contracts, and reverse prompting techniques. Finally, practical considerations like strategic context management—utilizing the "Iceberg Technique"—and optimizing token pricing through intelligent model routing will equip you with the skills needed to build cost-effective, highly scalable AI architectures.</p>
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