AI Agent Architecture: Design Effective Agentic Systems

About this course

AI Agents Are Redefining What Software Can Do. Are You Ready to Design Them?

If you’re fascinated by AI agents and want to truly understand how intelligent systems are architected, scaled, and controlled, then you are in exactly the right place.

AI Agents Design Blueprint: Architecting Agentic Systems is a comprehensive course that teaches you how modern AI agents actually work and how to design them for real-world use.

You’ll start with the foundations of agentic AI, clearly distinguishing between agentic workflows and full AI agents. From there, you’ll master the core building blocks of agentic systems, learn when to use agents (and when not to), and understand why architecture is the difference between a demo and a reliable system.

As the course progresses, you’ll go far beyond theory. You will learn:

• How to design robust prompting systems for agents
• How to implement agentic workflows such as routing, parallelization, orchestrator–worker, and evaluator–optimizer
• How to build single-agent and multi-agent architectures
• How to enable planning, decomposition, and reasoning
• How to design memory systems, including short-term context buffers, vector-based RAG, and entity-level memory
• How to ensure reliability, performance, and error recovery
• How to implement human-in-the-loop control, self-reflection, and oversight
• How to apply governance, guardrails, cost control, bias detection, and A/B shadow testing
• How to evaluate and benchmark AI agents properly in production

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