The three tells of an AI-tailored resume

Some hiring managers say the resumes they get now look perfect and identical. Job seekers who tailor every application with a chatbot (an AI app that answers what you type) say they get rejection after rejection, and some think the polish itself is the problem.

When thousands of people paste job posts into the same tools with the same request, they get back the same kind of resume. The words change a little. The shape doesn't. A recruiter reading a stack of applications for one role spots that shape fast. It won't get you rejected by a rule, but it makes your resume blend into the pile, and a resume that blends in gets skimmed and forgotten.

The fix isn't to stop using AI. Give it your real material, set rules it has to follow, and do the last edit yourself.

The three tells

1. Generic verbs and stock phrases. Spearheaded, orchestrated, championed. "Results-driven professional with a proven track record." "Detail-oriented." You met some in Write strong resume bullets. When every bullet uses them, nobody can hear you. Use the plain verb you'd say out loud (led, built, fixed, ran), and delete stock phrases so a real result shows it instead.
2. Made-up metrics. Ask AI to make your bullets "more impressive" and numbers appear: "improved efficiency by 30%", "cut costs by 25%". Round percentages with no source are the clearest tell, and the riskiest, because an interviewer may ask how you measured it. Use your real number, or the result in words.
3. The same structure as everyone else. Every bullet the same length, built as "verb, task, resulting in X%". A summary that opens with years of experience and a list of adjectives. The job post's sentences pasted back word for word. Each one alone is fine, but together they look machine-made. Vary the length, lead with what matters most, and use the ad's key terms only where they're true.

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