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This program focuses on running agentic AI systems in the real world.
You’ll learn what changes when an agent leaves the notebook and starts interacting with real users, real data, and real failure modes. The emphasis shifts from “does it work?” to “does it work reliably, safely, and at scale?”
This lesson gives you a high-level view of how the curriculum is organized and how each unit builds toward a production-ready capstone. For specifics, jump straight to the curriculum map below.
The program is organized into four units, each addressing a core responsibility of production-grade agentic AI.
Each unit reflects problems teams actually face after deployment, not hypothetical best practices.
The program culminates in a capstone project where you deliver a production-ready agentic AI system.
You’ll take an existing agentic application and:
The goal isn’t polish for its own sake — it’s operational credibility.
You’ll work with tools commonly used to ship and operate agentic AI systems, while focusing on principles that generalize beyond any single stack.
Testing, Safety, and Security
Deployment & Interfaces
Monitoring & Observability
Core Considerations
Where relevant, you’ll learn not just how to use these tools, but when and why they matter.
Building agentic AI systems is only half the challenge.
Operating them safely, reliably, and responsibly is what makes them real.
This curriculum is designed to help you make that transition with confidence.
When you’re ready, continue to Unit 1: Testing, Security, and Safety for Agentic AI to begin.
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