AI CV reviews flatter candidates by grading against what they already have

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A software developer writing for DEV Community found that AI tools tend to evaluate CVs against the skills a candidate already possesses, rather than against the full implicit expectations of a hiring manager. In a structured test using two job postings and three fictional candidates, the standard AI prompt consistently favoured a candidate whose titles and tech keywords matched the job ad, while overlooking a stronger but less obvious fit. The author argues this happens because the model reads the CV before forming its evaluation criteria, anchoring its judgment to what is already present. A two-step prompting approach — first extracting the hiring manager's unwritten expectations from the job ad alone, then scoring the CV against that list — produced significantly more accurate assessments. The finding suggests that how a prompt is structured can materially affect whether AI feedback is genuinely critical or subtly flattering.

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