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This article provides essential architectural guidance for building scalable AI systems by distinguishing between interactive "skills" designed for human-in-the-loop conversations and autonomous "sub-agents" optimized for batch processing. The core insight is that selecting the correct delivery shape—rather than just choosing a specific model—is critical to ensuring reusability, simplicity, and long-term maintainability in production environments.
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Azure and Community Guidelines on Choosing between a Skill or a Sub-Agent

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In a recent Azure Architecture blog article, Azure lead engineer Kishorekumar Pattabiraman outlines practical criteria for choosing between skills, sub-agents, and other approaches when building AI systems, emphasizing reusability, simplicity, and long-term maintainability. By Sergio De Simone

In a recent Azure Architecture blog article, Azure lead engineer Kishorekumar Pattabiraman outlines practical criteria for choosing between skills, sub-agents, and other approaches when building AI systems, emphasizing reusability, simplicity, and long-term maintainability. According to Pattabiraman, teams often begin with the wrong question, focusing on which is the right model to use. The "first real fork" though, is not the model,…

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