Architect Reusable AI Agent Systems

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Architect Reusable AI Agent Systems

This course is part of Agentic AI Development & Security Specialization

Instructor: LearningMate

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2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Design and implement reusable, modular AI agent systems by evaluating architectures and defining clear API contracts for core components.

Skills you'll gain

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This course is part of the Agentic AI Development & Security Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 2 modules in this course

Architect Reusable AI Agent Systems is an intermediate course for AI engineers and developers who want to move beyond building single-purpose agents and learn to design scalable, modular agent architectures that drive business value. This course teaches advanced system design principles, equipping you to build maintainable AI systems that can evolve with business needs.

You will learn to evaluate competing reasoning-loop architectures like ReAct and Reflexion by running data-driven A/B tests to select the optimal design for a specific use-case. Through hands-on labs, you will master the software engineering best practices for creating reusable agent components—the Planner, Memory, and Executor—by defining clear API contracts with typed interfaces. You will leave this course with the ability to design, document, and implement a complete Python package of agent components, ready for integration into a production environment.

This module focuses on the critical skill of architectural selection. You will learn that not all agent "brains" are created equal. You will dive into two popular reasoning frameworks, ReAct and Reflexion, and learn how to use empirical data from A/B tests to make a justified recommendation for which architecture best suits a specific, real-world use case.

What's included

2 videos1 reading1 assignment1 ungraded lab

This module shifts your focus from being an analyst to being an architect. You will learn the software engineering best practices that enable scalable and maintainable AI systems. You will design the core components of an agent—Planner, Memory, and Executor—and define the clear API contracts that allow them to work together seamlessly.

What's included

2 videos2 readings2 assignments1 ungraded lab

2 videos Total 12 minutes

The Monolith vs. The Micro-Agent 6 minutes
How-To: Define a Clear API Contract in Python? 6 minutes

2 readings Total 10 minutes

The Anatomy of a Reusable Agent 5 minutes
AI Agents in the Wild: Case Studies 5 minutes

2 assignments Total 40 minutes

Knowledge Check: Component Roles 10 minutes
Agent Architecture & Design Report 30 minutes

1 ungraded lab Total 60 minutes

Architecting Modular Agent Components 60 minutes

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Instructor

LearningMate

210 Courses 11,134 learners

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