Most "AI agents" are just engineered workflows, not truly autonomous systems. A key research distinction—"agentic" (task-completing pipelines) vs. "agentive" (goal-driven)—argues that mislabeling obscures where intelligence resides and hinders genuine autonomy development.

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Most systems called "AI agents" are really just engineered workflows wrapped around language models — not true agents. A research paper distinguishes "agentic" (task-completing pipelines) from "agentive" (internally goal-driven) systems, arguing that mislabeling hides where intelligence actually lives and prevents builders from developing genuinely autonomous AI.

Most AI Agents Aren't Really Agents At All

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