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