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Agentic AI Solution Communication Architectures

Agentic AI Solution Communication Architectures

55mIntermediate2025-08-20

Authors

Thomas Erl

Thomas Erl

Course details

In this course, Thomas Erl—an AI and technology education specialist—dives into agentic AI communication architectures, including asynchronous messaging, event-driven communication, and batch processing. Explore how AI agents work with microservices and how synchronous communication is managed in agentic AI. Learn about state data communication and the role of messaging fabric platforms in these architectures. Delve into message queues and event hubs, using sample scenarios for practical insights. Find out how batch processing is orchestrated within AI systems, with a focus on queue management. Discover how mastering communication architectures can lead to more efficient and intelligent AI solutions. This course enables you to build a comprehensive understanding of communication strategies in agentic AI applications.

Skills covered

Software ArchitectureAI for Business FoundationsAI Productivity ToolsArtificial Intelligence for BusinessNetwork AdministrationNetwork and System AdministrationBusiness Software and ToolsSoftware DevelopmentOne-Off

Concepts

0. Introduction

  • 01 - Introduction
  • 02 - What you need to know

1. Agentic AI Communication Basics

  • 03 - AI agents with microservices
  • 04 - Synchronous communication in agentic AI
  • 05 - State data communication in agentic AI
  • 06 - Messaging fabric platforms
  • 07 - AI agent roles

2. Asynchronous Messaging Communication with Agentic AI

  • 08 - Asynchronous messaging architecture for agentic AI
  • 09 - Inside the message queue
  • 10 - Asynchronous communication with agentic AI sample scenario

3. Event-Driven Communication with Agentic AI

  • 11 - Event-driven architecture for agentic AI
  • 12 - Inside the event hub
  • 13 - Event-driven communication with agentic AI sample scenario

4. Batch Processing with Agentic AI

  • 14 - Batch processing architecture with agentic AI
  • 15 - Inside the batch queue
  • 16 - Batch processing with agentic AI sample scenario

Conclusion

  • 17 - Next steps

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