When I see the same job pop up over and over again on LinkedIn, my mind immediately goes to one of four places.
First, they’re collecting resumes.
Second, they’re building a pipeline even though they aren’t ready to hire.
Third, the business and IT can’t get aligned on what they’re actually looking for, so the search keeps resetting.
I’ve spent more than a decade in recruiting, and honestly, those three explanations usually cover it.
But after a conversation I had this week with a QA Manager leading digital transformation initiatives for a local fintech company, I realized there’s a fourth reason.
Candidates are getting through the filters, making it to interviews, and then failing to demonstrate the experience their resume claims they have.
I’ve heard job seekers complain about reposted jobs for months. “That company isn’t really hiring.” “It’s fake.” “They’re just collecting data.”
So I asked him about one of his own openings that I’ve seen reposted.
I told him exactly what candidates were saying. If they keep seeing the same role, they assume the company either isn’t serious about hiring or doesn’t have its act together.
He understood why people think that.
But he told me something I hadn’t really considered.
His problem isn’t simply “fake candidates”. His problem is resumes that have become too good.
He said candidates are using AI to optimize resumes, add skills, improve wording, etc to make sure they “get through ATS and AI filters”.
But that becomes a problem when the actual interviews begins.
As the conversation gets deeper, the experience on the resume no longer matches the experience of the person sitting across from him.
He told me he isn’t looking for someone to recite definitions or buzzwords. He’s looking for someone who can explain what they actually built, why they built it, what went wrong, and what changed because of it.
Instead of asking, “Have you used AI?”
He’ll ask: Why did you use AI? What problem were you solving? How did it improve the project? How did you measure that improvement? How did you come up with those numbers?
That’s where he starts separating real experience from polished resumes.
Another thing he mentioned that really stuck with me is that candidates often talk about implementing automation or AI, but they stop there.
For him, that’s only half the story.
He wants to know the business impact. Did testing become faster? Did bug leakage decrease? Did automation reduce story point effort? Did test coverage improve? Can you quantify any of it?
If you can’t explain the outcome, it’s hard for him to understand what your contribution actually was.
He also said he’s seeing more candidates rely on AI during interviews.
Some read textbook definitions. Some constantly look away from the camera. Some sound like they’re reading from another screen.
His point was that AI should not replace your own thinking.
One comment he made I thought was interesting: “Eventually we’re going to be looking for AI enablers, not AI users.”
Everyone “uses AI now”. That isn’t the differentiator anymore.
The differentiator is whether you know when AI is right, when it’s wrong, and how to improve what it gives you.
He also challenged something I’ve been thinking about lately which is a lot of people believe AI has made tooling less important. He disagrees.
AI can generate Playwright code. It can generate Selenium scripts. But if you don’t understand the framework, the architecture, or why the code works, AI isn’t going to save you when something breaks.
Domain knowledge still matters.
Finally, he shared something I think every experienced engineer has felt:
Years ago, joining a company meant spending your first few months learning the product, the team, and the business.
Today, companies expect output almost immediately.
AI has shortened everyone’s patience. The expectation isn’t just to learn faster. It’s to contribute faster.
When you combine that with resumes that overstate experience, hiring managers end up doing exactly what candidates hate seeing.
They pause the search. Reopen the requisition. Interview more people. Repost the job. And the cycle starts all over again.
My advice is pretty simple: If you can confidently talk through your experience, you can confidently write about it.
Use AI to organize your thoughts. Use AI to improve your wording. But don’t let AI create experiences you can’t defend in an interview.
I actually believe that AI has made it easier to get interviews for many people. It’s also made it much harder to prove you belong once you’re in the room.