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This guide distinguishes between workflows and agents in AI, breaking down the agentic AI stack from model to system using a coding agent example to illustrate the loop and layers.
This paper argues that AI agent performance depends more on the harness (control layer) than on prompts alone, proposing natural-language agent harnesses to make design choices inspectable and portable.