Drawing on the Critique of Agent Model paper, this article argues that many modern AI agents are better described as agentic workflows than genuinely agentive systems. It explores the distinction through concepts like persistent goals, adaptive identity, self-regulation, world models, and continuous learning, offering a more rigorous framework for evaluating autonomous AI.