Most AI 'Agents' Are Just Fancy Functions, Engineers Warn

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A practitioner working in the AI industry argues that the term 'agent' is being applied so broadly that it has lost engineering precision, leading teams to over-build simple pipelines or under-build complex ones. A true AI agent, the author contends, must set its own next steps, recover from failures, and know when a goal is complete — not merely follow human-directed instructions. In practice, most successful agent deployments observed are narrow and purpose-built, handling specific tasks like customer support triage or document extraction rather than general reasoning. Teams achieving strong results focus on clean tool design, robust failure handling, and full observability of agent decision-making. Those chasing the latest frontier model without rethinking their broader system architecture are reported to see little improvement.

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