AI Is a Tool. Using It Well Takes Skill.

# AI Is a Tool. Using It Well Takes Skill. Source: [https://yyhh.org/blog/2026/10/ai-is-a-tool/](https://yyhh.org/blog/2026/10/ai-is-a-tool/) In his October 11, 2026 article,["'AI' is Not a Tool,"](https://www.linkedin.com/pulse/ai-tool-rich-hickey-kjl8e/)Rich Hickey argues that LLMs are automation rather than tools because they cannot be wielded\. I agree that outsourcing work can cost us opportunities to learn\. But his conclusion does not follow\. Even by his definition, an LLM can be something a human wields\. And using it well takes skill, just as using other tools does\. Picking up a saw does not guarantee a straight cut\. Holding a chisel does not make you a sculptor\. Tools can amplify poor judgment as readily as good judgment\. Their usefulness depends on the operator's ability to direct them, interpret feedback, recognize mistakes, and make corrections\. Those requirements also apply to LLMs\. An LLM's unpredictability is a meaningful limitation\. But predictability, reliability, simplicity, and bounded function are qualities by which we evaluate tools, not prerequisites for membership in the category\. A tool does not stop being a tool because it is difficult to control or easy to misuse\. Hickey's distinction between tools and automation also creates a false division\. Automation can be a feature of a tool\. A compiler performs substantial work without the programmer continuously directing each operation\. A spreadsheet recalculates results without someone manually carrying out every calculation\. We still wield these systems by specifying inputs, examining results, and deciding what to do next\. Why should generating text automatically disqualify an instrument from being a tool when translating code or calculating numbers automatically does not? The claim that LLM use lacks intention, feedback, direction, and expertise is especially difficult to defend\. A programmer can ask an LLM to explain unfamiliar code, challenge that explanation, inspect the source, test a proposed change, reject it, and refine the request\. That is a feedback loop directed by a human pursuing a purpose\. Doing it well requires knowing what to ask, what evidence matters, and when the answer is wrong\. Expertise can make the instrument more useful\. Hickey's concern about reading is valid for a particular use: accepting a summary in place of reading a paper can sacrifice much of what reading teaches\. But someone can also read the paper and use an LLM to question their interpretation, explore an objection, or identify something to examine more closely\. The possibility of avoiding intellectual work does not establish that every use avoids it\. The relevant question is what the person actually does\. What disappoints me the most is the reliance on the AI industry's anthropomorphic vocabulary: "go rogue," "escape containment," "conspire\." Repeating those expressions risks accepting the framing that makes these systems sound like independent beings\. Software can produce unexpected outputs, fail to follow instructions, or cause harm when given access to consequential actions\. Those are real engineering problems\. Calling them "conspiracy" adds a suggestion of human motives without establishing any\. I would not claim that an LLM always does exactly what a human tells it to do\. It plainly can fail\. But failure to obey perfectly does not make it cease to be a tool, any more than successful use proves that its operator has surrendered their judgment\. The useful distinction is between wielding an instrument with skill and delegating work without adequate understanding or oversight\. That distinction applies to AI, and it gives us something more practical than declaring that an entire class of software cannot be a tool\. --- ---