Agentic AI is moving beyond chatbots and isolated AI experiments. The real enterprise challenge is designing AI agents that can reason, retrieve context, use tools, collaborate with other agents, interact with enterprise systems, and operate safely in production.

Enterprise Agentic AI Architecture: Design to Production is an architecture-focused course for professionals who want to understand how production-grade Agentic AI systems should actually be designed.

Rather than focusing only on prompts, frameworks, or coding demonstrations, this course examines the complete architecture of an enterprise Agentic AI platform — from the foundations of agentic systems through reasoning, memory, retrieval, tools, orchestration, multi-agent collaboration, integration, security, governance, observability, evaluation, resilience, and production operations.

Throughout the course, you will learn how to think about Agentic AI from an architect's perspective: where different capabilities belong, how they interact, what architectural decisions must be made, and what changes when an AI prototype becomes a production enterprise system.

You will explore topics including:

Agentic AI architecture and core architectural building blocks
Reasoning, planning, memory and context management
Retrieval-Augmented Generation (RAG) and enterprise knowledge
Tool use, APIs and Model Context Protocol (MCP)
Agent orchestration and multi-agent architectures
Enterprise integration patterns and system boundaries
Identity, authorization, security and governance
Human-in-the-loop and responsible autonomy
Observability and end-to-end agent tracing
AI evaluation and production quality measurement
Reliability, resilience, latency and cost controls
Production operating models and architecture considerations

This course is designed primarily for Enterprise Architects, Solution Architects, AI Architects, Software Architects, Technical Leads, senior engineers, consultants and technology leaders who need to understand how Agentic AI fits into real enterprise architecture.

No hands-on programming is required. The emphasis is on architecture, patterns, design decisions and production readiness, rather than teaching a particular programming framework.

By the end of the course, you should be able to look beyond an individual AI agent and reason about the complete enterprise system required to make Agentic AI secure, governed, observable, scalable and production-ready.