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AI is a tool and using it well takes skill
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- DeepHorus
Rich Hickey’s October 11, 2026 essay, “'AI' is Not a Tool,” has drawn a detailed rebuttal over how to classify large language models. Hickey argues that LLMs are automation, not tools, because they cannot be wielded. The response agrees that outsourcing work can cost opportunities to learn, but rejects his conclusion.
The writer contends that an LLM can be something a human wields, even under Hickey’s definition. Using it well requires skill, much like using a saw or chisel. Tools amplify poor judgment as readily as good judgment.
A colleague’s observation that “AI is a mirror” frames the debate. It reflects the curiosity, judgment, and habits users bring to it. The questions asked and standards applied to answers matter.
The commentary also challenges Hickey’s tools-versus-automation divide. Automation can be a feature of a tool, as with compilers and spreadsheets. Both perform work automatically while humans specify inputs, examine results, and decide next steps.
The claim that LLM use lacks intention, feedback, direction, and expertise is hard to defend, the writer says. A programmer can ask an LLM to explain unfamiliar code, challenge the explanation, inspect the source, test a change, reject it, and refine the request. That is a human-directed feedback loop.
A concern is valid: accepting a summary instead of reading a paper can sacrifice what reading teaches. But a person can also read the paper and use an LLM to question an interpretation or explore an objection. The possibility of avoiding intellectual work does not prove every use does.
The response criticizes anthropomorphic language such as “go rogue,” “escape containment,” and “conspire.” It says unexpected outputs, instruction failures, and harm from consequential access are real engineering problems, not evidence of human motives. The useful distinction is between wielding an instrument with skill and delegating work without oversight.
