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When an interviewer asks whether you use AI, the useful answer is about your work: what you use it for, how much responsibility you give it, and how you check what it produces. Treating the question as a challenge to your identity as an engineer can sound defensive while leaving those practical details unanswered.
What the question is really asking
In a DEV Community opinion post, Fuyuki0 frames “Do you use AI?” as a question about working method. The author’s concise distinction is: “The interviewer asked about a tool. The candidate defended an identity.” That is the post’s interpretation of the exchange, not a proven account of how interviewers generally use the question.
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The distinction matters because an interviewer may be trying to understand how you approach coding tasks and assess generated output. A broad defense of AI—or a defense of your legitimacy as an engineer—does not tell them what you actually do.
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What happened in the reported interview story
Fuyuki0 says the story came from someone else, so the exchange should be read as a secondhand anecdote rather than an independently verified interview. In the reported version, the candidate responds to the question with, “Are you going to use a stove instead of a microwave?”
#1 Best Overall
The author argues that the comparison is unhelpful because a stove and a microwave do different jobs. Rather than clarifying the candidate’s process, the analogy can shift attention toward whether they can choose the right tool for a task. That is Fuyuki0’s reading of the exchange, not an established hiring rule.
Answer with use, scope, and checks
The post recommends replacing a general defense with specific information. Explain what tasks AI supports, what remains your responsibility, and how you verify its output. Fuyuki0 offers an illustrative answer in which AI drafts code, the engineer reviews it, and extra care goes to authentication or financial logic. The example also mentions checking imports after AI invents a library function. It is the author’s sample, not a documented candidate response or a tested script.
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- Use: Name the kind of work you ask AI to help with, such as drafting code.
- Scope: Explain where your own judgment and responsibility remain central.
- Checks: Describe how you look for errors, with particular attention to consequential logic and unsupported APIs or imports.
Keep the answer accurate to your own practice. A concrete example is more informative than saying you review everything if you cannot explain what that review involves.
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Why the distinction is useful—and what it does not prove
The post’s central advice is to make your process visible rather than turning a tool question into an argument about professional identity. Its closing emphasis is on where a candidate places checks and whether they can recognize incorrect AI output. As Fuyuki0 puts it, “Specificity is the entire product.”
This is commentary, not interview research: the post presents no hiring dataset, study, or controlled comparison showing that its suggested answer improves interview outcomes. It offers a way to make an answer more informative, not a guarantee of how an interviewer will respond.
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