 <h1>Congratulations! 🎉 </h1>
    <p style="color:#637381;">All done! You’ve completed another milestone.</p>

To continue, enter your details to log in.

We’ve sent a 6‑digit code to #MAIL_ADDRESS#\nPlease check your inbox or spam folder and enter the code below to continue.

Verification code sent

Thank you for the payment. You can now access {collectionName} by simply clicking the button below.

Yes, you’ve successfully ordered! 🎉

Unlock This Exclusive Course

It seems that your email address is not currently on the authorized access list. Please ensure you are using the email address that was invited, or contact the content owner for assistance.

Verification Required for Access

Course Introduction

Introduction and Overview

The Single Agent Pattern

Single Agent Pattern

Single Agent: Implementation and Demo

Single Agent: Pros and Cons

The Sequential Agent Pattern

Sequential Agent Pattern

Sequential Agent: Workflow and Communication

Sequential Agent: Pros and Cons

Parallel Architectures

Sequential with Parallel Agent Pattern

Parallel Agent: Implementation and Synthesis

Parallel Agent: Pros and Cons

🎮 Crossword: Agent Patterns Review

Course Conclusion

Summary and Future Topics

Quiz

Quiz: Single Agent Concepts

Quiz: Sequential Workflows

Quiz: Parallel Execution

Quiz: Pros and Cons Analysis

Quiz: Implementation Basics

Feedback

Course Feedback Survey

Mastering Single Agent Design Patterns for AI is a hands-on course that teaches you how to design, build, and evaluate agentic workflows with a focus on the single-agent pattern. You’ll learn when a single tool-using agent is all you need, how it differs from simple LLM calls, and how to evolve your solution toward sequential and parallel architectures as complexity grows. Through architecture diagrams, runnable demos, and real-world scenarios like trip planning and research synthesis, you’ll see how agents think-act loops operate, how tools are orchestrated, and how to keep state and context manageable. You’ll also compare trade-offs: simplicity and low latency vs. flexibility, reliability, and cost. By the end, you’ll confidently implement a robust single-agent system, understand when to modularize into sequential chains, and know when to introduce parallel branches for speed. The course includes quick quizzes, visuals, and a playful crossword to reinforce key concepts. If you’re ready to move beyond basic prompts and unlock practical, production-minded agent design, this course will give you the patterns, vocabulary, and implementation steps to ship faster and scale smarter.

Mastering Single Agent Design Patterns for AI

<div class="simple-box-wrapper">
    <div class="simple-box">
        <div class="column">
            <p>The landscape of Artificial Intelligence is rapidly evolving from simple, one-off Large Language Model (LLM) interactions toward sophisticated agentic workflows. This course provides a comprehensive exploration of AI agent design patterns, focusing on how to structure autonomous systems for maximum efficiency and reliability. By distinguishing between standard LLM calls and true agentic behaviors, we establish a foundation for building systems that can think, act, and use tools. The curriculum is centered around three primary architectural patterns: single agents, sequential workflows, and parallel execution models. Each of these structures offers unique advantages in how they handle complex queries and manage computational resources.</p>

<p>Throughout the following modules, we will dissect the Single Agent pattern, examining its tool-using capabilities and the loop mechanisms that drive its decision-making. As complexity increases, we transition into multi-agent systems, starting with the Sequential Agent pattern to understand how tasks are handed off and how state is maintained across a linear chain. We will also explore Parallel Architectures, where multiple agents operate simultaneously to reduce latency and aggregate diverse results. Beyond theoretical definitions, this course emphasizes practical implementation through demos and a critical analysis of the pros and cons associated with each design choice. By the end of this journey, you will be equipped to evaluate trade-offs between simplicity, speed, and reliability when architecting AI-driven solutions.</p>
        </div>
    </div>
</div>
