Наталя ХандусенкоWork
18 August 2026, 15:16
2026-08-18
"Burned" for AI that didn't exist: it seems recruiters have invented a new excuse for rejection - the experience of a Ukrainian developer
Ignoring candidates and not providing feedback after an interview has long been a sad reality in IT. However, Full-stack Engineer Stanislav Gogulya encountered a situation that surprised even experienced professionals. It seems that recruiters have found a new convenient excuse for rejection instead of meaningful feedback.
Ignoring candidates and not providing feedback after an interview has long been a sad reality in IT. However, Full-stack Engineer Stanislav Gogulya encountered a situation that surprised even experienced professionals. It seems that recruiters have found a new convenient excuse for rejection instead of meaningful feedback.
As Stanislav Gogulya told on LinkedIn, at first everything went according to the classic scenario: a successful HR stage, two days to complete the test task, and a technical interview, where the IT professional felt confident.
Later, a letter from the company arrived in the mail, which stated: "It was a pleasure to talk to you - you made a good impression on our team! However, during the assessment, we noticed that some of the answers could have been enhanced with the help of AI tools, which made it difficult for us to objectively assess your real level of technical knowledge."
Stanislav was surprised by this wording, because he answered the interview himself.
"Silence or lack of feedback during a job search no longer surprises anyone. But this was something new, because I was the one answering," the developer shared.
When the IT worker tried to clarify with the recruiter what exactly aroused suspicions and what the "assistance of artificial intelligence" was, he never received an answer.
For him, this seems like a convenient new way to reject candidates without explaining the real reasons.
What the IT community thinks
In the comments to the post, some experts suggested that the company itself was not too concerned about the originality of the feedback. In particular, Product team lead Tetyana Tsyuk humorously noted: “It looks like they even used AI to answer you.”
Some IT professionals are convinced that the taboo on AI in development is a step backwards. Python Full Stack Developer Oleksiy Gudkov drew attention to world experience: “Giants like Google and Amazon use AI at all levels, while some company that does something locally is against it. Think about whether you should join a company that is so afraid of AI.”
Other specialists choose the path of direct dialogue. For example, QA Engineer Yevhen Skubytsky said: "When I was recently given a technical question, I immediately replied that I saw no reason not to use AI. There were no objections or surprises. However, it did not come to fruition for other reasons."
According to recruiter Anastasia Lytvyn, the use of prompts during an online meeting is often visible to the naked eye: “I noticed that during the interview, the candidate easily answers everyday questions and pauses for up to a minute for technical ones. This may look like “thinking before answering,” but these were clear time intervals, and he seemed to freeze at such moments. It seemed that the assistant was helping.”
The author of the post himself expressed doubts about whether it would be possible to use a neural network invisibly during a conversation: "It's hard for me to imagine how you could have time to ask, read, and filter out what you need in a moment. I would definitely forget and get burned on the first question."
The saddest thing about this trend is that even well-trained specialists can fall under suspicion. QA Engineer Dmytro Velikiy shares his experience: “It’s terrible. They recently told me that I was spying somewhere, and I was only well-prepared in theory… Of course, they refused. That’s the bottom.”
Instead of a conclusion
Stanislav's story highlighted a new problem in the labor market: the line between the use of artificial intelligence and one's own thorough training is becoming blurred, and the lack of clear evaluation criteria creates new reasons for unjustified rejections.
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