Understand Agentic AI Fundamentals
Learn what makes an AI system an 'agent' and why agentic design is crucial
Apply Core Agentic Patterns
Implement key patterns like prompt chaining, planning, memory management, and tool use
Build Robust & Adaptive Agents
Design systems that handle exceptions, learn from feedback, and collaborate effectively with humans
About the Course
Calling all AI Practitioners, Data Scientists, Product Managers, Tech Leaders, and Advanced Learners! Dive into the world of Agentic AI Design. Gain practical skills in agent design while understanding core agentic patterns and applying them to real-world scenarios. By the end of this course, you'll be equipped to design safe, reliable, and adaptive AI systems with hands-on experience in agentic frameworks and coding exercises.
About the Creator
Meet Sam Zamany, founder of AI Engineering Academy. With over a decade of experience across AI, data engineering, and software engineering, Sam leads global AI Engineering, strategy and innovation at Boston Scientific—designing scalable systems that power real-world impact. Passionate about empowering others, Sam is dedicated to helping learners master modern AI engineering and build intelligent systems that shape the future.
Course Curriculum
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1
Prompt Chaining
- The Limitations of Single-Prompt Strategies and the Emergence of Prompt Chaining Free preview
- Designing Effective Prompt Chains — Sequential Decomposition and Role Assignment Free preview
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Ensuring Data Integrity in Prompt Chains Through Structured Outputs
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(Included in full purchase)
Practical Application Patterns for Prompt Chaining
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Implementing Prompt Chains in Code — A Technical Exploration of Sequential LLM Workflows
- Context Engineering and Strategic Deployment of Prompt Chaining Free preview
- Podcast: Prompt Chaining Deep Dive Free preview
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2
Routing
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(Included in full purchase)
Why Routing Exists in Agentic Systems
- What Routing Is and How It Works Free preview
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The Core Routing Approaches in Agentic Systems
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Where Routing Happens Inside an Agent Workflow
- Practical Applications and Use Cases of Routing in Agentic Systems Free preview
- Implementation Models of Routing Using LangChain/LangGraph and Google ADK Free preview
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3
Parallelization
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Why Parallelization Exists in Agentic Systems
- What Parallelization Is & the Core Concept of Concurrent Execution Free preview
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How to Identify Tasks That Can Run in Parallel
- Practical Applications and Use Cases of Parallelization Free preview
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(Included in full purchase)
Framework Support for Parallelization in Modern Agent Systems
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Implementation Examples of Parallelization Using LangChain, LangGraph, and Google ADK
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4
Reflection
- Why Reflection Exists in Agentic Systems: Motivation and Purpose Free preview
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(Included in full purchase)
What Reflection Is: The Reflection Loop and Core Mechanics
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The Producer–Critic Model: Structured Roles for Reflection
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Reflection in the Larger Agent Architecture: Goals, Monitoring, Memory, and Trade-Offs
- Practical Applications and Use Cases of the Reflection Pattern Free preview
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Implementation Examples of the Reflection Pattern
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5
Tool Use (Function Calling)
- Conceptual Foundations of Tool Use Free preview
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From Function Calling to Tool Calling & Framework Support
Ready to Dive Into Agentic AI Design?
Join now to gain practical skills in building intelligent, agent-based systems that are safe, efficient, and adaptable. Don't miss out on this opportunity to elevate your AI design expertise!