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A potential issue could be ensuring accuracy and fairness in the instant feedback, especially when using AI to analyze voice and text responses.

For example, speech recognition might misinterpret accents or speech patterns, leading to incorrect feedback on clarity or confidence. Similarly, the AI might misunderstand the content or tone of answers, giving feedback that’s either too harsh or too lenient. This could frustrate users or reduce their trust in the tool.

Handling diverse industries and roles also poses a challenge—building adaptive questioning that feels relevant and realistic across all selected options without becoming overly generic or repetitive.

I don't think tone is one of the biggest problems, but I think one of the problems to solve is consistency in the answers, for example. If the AI ​​asks something, the answers should always be somewhat the same, because if User 1 answers X and User 2 does too, but the AI ​​recognizes User 1's answer as correct and User 2's as incorrect, then there is a problem.

The AI analysis says this:
This interview simulator aims to help users practice and improve their interview skills through realistic mock sessions and AI-powered feedback. Baldur O.'s feedback highlights a critical flaw: inconsistent evaluation of user answers. This directly impacts the core functionality of providing accurate and reliable feedback, making the feedback valid and reasonable. The developer should prioritize debugging the AI's response evaluation algorithm to ensure consistent and fair assessment of similar answers.

This requires reviewing the AI's logic and potentially incorporating more robust natural language processing techniques. I don't know how actually