The article critiques the misuse of the term "agent" in the context of AI, arguing that most so-called AI agents are actually just sophisticated workflows. It highlights the confusion in the market where vendors label simple API calls as agents, claiming they can autonomously execute tasks. The author points out that true agents can make independent decisions and adapt based on outcomes, while workflows operate on predefined rules that always lead to the same results. According to Gartner, fewer than 5% of enterprise applications currently feature actual AI agents, with many projects likely to be canceled by 2027 due to high costs and unclear value. The author presents a clear framework: workflows are deterministic, allowing for auditing and predictable failures, while agents are autonomous but can behave unpredictably. In practice, workflows enhanced with AI components are often more effective. For example, in document processing, a workflow can leverage AI for specific tasks while maintaining a controlled structure, ensuring reliability and oversight. The piece emphasizes that most businesses should prioritize building these structured workflows that integrate AI where it makes sense, rather than chasing the allure of autonomous agents. It suggests that while agents have their place, they should be used sparingly and with strong oversight, especially in scenarios involving significant risk or compliance requirements.