Blogger Pushes Back on Rich Hickey: AI Language Models Are Still a Tool
A blog post responds to Rich Hickey's October 11 article claiming that large language models are automation rather than tools. The author argues that using them well is a matter of skill and that they remain instruments a human can wield.
A debate in the technology world continues over whether large language models (LLMs), the AI systems behind text-generating chatbots, can be called tools. In a post on the blog yyhh.org, the author responds to Rich Hickey's October 11, 2026 article "'AI' is Not a Tool." Hickey's argument is that LLMs are automation rather than tools, because they cannot be wielded the way a tool is. The author agrees on one point: outsourcing work can cost people chances to learn. But he says Hickey's conclusion does not follow.
Skill and judgment
The author argues that, even by Hickey's own definition, an LLM can be something a human wields. Picking up a saw does not guarantee a straight cut, and holding a chisel does not make someone a sculptor. Tools can amplify poor judgment as readily as good judgment, and their usefulness depends on the operator's ability to direct them, interpret feedback, recognize mistakes and make corrections. Those requirements apply to LLMs too.
He acknowledges that unpredictability is a meaningful limitation. Still, he says predictability, reliability, simplicity and bounded function are qualities by which tools are evaluated, not prerequisites for belonging to the category.
Automation versus tools
The author calls Hickey's split between tools and automation a false division. A compiler does substantial work without the programmer directing each operation, and a spreadsheet recalculates results without manual arithmetic. Yet people still wield both by specifying inputs, examining results and deciding what to do next.
A programmer, he says, can ask an LLM to explain unfamiliar code, challenge the explanation, inspect the source, test a proposed change, reject it and refine the request. That is a feedback loop directed by a human with a purpose. On reading, he considers Hickey's concern valid when a summary replaces reading a paper. But a person can read the paper and use an LLM to question their interpretation or explore an objection.
Language and the key distinction
The author says he is most disappointed by Hickey's use of the AI industry's anthropomorphic vocabulary, such as "go rogue," "escape containment" and "conspire." Software can produce unexpected outputs, ignore instructions or cause harm when given access to consequential actions, he writes, but those are engineering problems, not evidence of human-like motives.
His conclusion is that the useful distinction lies between wielding an instrument with skill and delegating work without adequate understanding or oversight.
