Over the past few months, I’ve been building an AI-powered resume optimization platform.
The original goal sounded simple:
Help people tailor their resumes to specific job descriptions.
But after analyzing thousands of resumes and job descriptions, I realized something interesting.
Most resumes don’t get rejected because candidates lack skills.
They get rejected because recruiters—and increasingly ATS systems—can’t easily identify those skills.
The biggest mistakes I keep seeing
- Generic summaries copied from templates.
- Bullet points that describe responsibilities instead of achievements.
- Missing keywords from the target job description.
- Poor formatting that breaks ATS parsing.
- Applying with exactly the same resume to every company.
Most people believe ATS is some mysterious AI that randomly rejects resumes.
In reality, modern ATS software is mostly designed to organize candidates, search keywords, and make recruiters’ jobs easier.
The real problem is that recruiters often spend only a short time reviewing each resume before deciding whether to continue.
Building the solution
Instead of creating another resume template generator, I wanted something different.
The platform analyzes:
- Resume structure
- Keyword coverage
- Skills alignment
- Missing sections
- ATS compatibility
- Resume vs Job Description matching
The idea is to provide actionable feedback instead of just assigning a score.
What surprised me
Many resumes that looked “good” visually actually performed poorly when compared against specific job descriptions.
Meanwhile, some simple-looking resumes matched significantly better because they communicated relevant experience more clearly.
That completely changed how I think about resume writing.
I’d love your feedback
If you’re a recruiter or engineer who’s been involved in hiring:
- What resume mistakes do you see most often?
- Do you think ATS is overblamed?
- What would you improve in tools that help candidates optimize resumes?
Top comments (1)
you can try it on cvboosta.com