The Hundred and Fifty Thousand

Somewhere in a pile of 150,000 applications, there’s a person who would have been an extraordinary flight attendant.

They didn’t make it to an interview. Not because they weren’t good enough, but because no one had time to get to them.

— Sean Behr, CEO, Fountain

One airline. Six hundred open flight attendant jobs. A hundred and fifty thousand people applied.

The entire US flight attendant workforce — every attendant on every flight of every carrier — is about a hundred and thirty thousand. This one job posting drew more applicants than there are flight attendants currently working in the country.

A hundred and fifty thousand applications at five minutes each is twelve thousand five hundred hours. Six work-years of one recruiter’s life. The recruiters had two weeks.

So the applications got filtered. Keyword match, pedigree rank, the top couple hundred to a human. Everyone else is ghosted. Not deleted. Never contacted. The rejection is the absence.

This is not a failure of effort. It is physics. No company on earth has enough recruiters to talk to a hundred and fifty thousand people. The math does not bend.

Everybody calls this the new way because it has an LLM in it. It is the old way with new plumbing.

A quick note. I work at Fountain, where Sean is the CEO. We build an AI recruiter for frontline hiring. Numbers in this chapter come from our customers. The argument is not neutral. Read it with that in mind.

The resume problem

Resumes are broken in two directions.

An LLM will now generate a resume that matches a job description to four decimal places. Work history the candidate never had. Technologies the candidate has never touched. Keywords that are not lying, exactly, but not evidence either. The top of the funnel is flooded with synthetic signal.

Underneath the synthetic resumes, the real problem is older. The people most likely to get overlooked have always been the ones who did not know how to package themselves on paper. The ones who went to a school nobody has heard of. The ones whose career path looks nonlinear on a form and makes complete sense the second you talk to them.

The application was never a perfect proxy for talent. It was the only tool we had at scale.

The filter at the top of the funnel has gone to noise in one direction and bias in the other.

The shift

Skip the resume filter. Interview everyone.

Not a screened subset. Not the top five percent. Everyone.

An AI interview. Rubric. Same questions for everybody. Not video. Not facial analysis. Not the thing HireVue got sued for. Structured conversation. Open-ended questions. Transcripts scored against the same criteria whether the candidate is in New York or Manila.

Two things have to be true.

First, a deterministic screen at the door. Hard requirements only. Are you authorized to work in this country? Can you start by the date we need? Are you willing to work on-site? Right answers and wrong answers. The wrong answers are rejected immediately, in front of the candidate, with the reason shown. Nobody is ghosted on a hard requirement. You told them why. They can go elsewhere.

Second, the interview is opt-in. If the candidate prefers to wait for a human, they wait.

They overwhelmingly do not wait. They take the interview.

The time of day

The recruiter works nine to five. So does the candidate.

If the candidate works the same hours as the recruiter, every phone screen is at a bad time. The candidate is hiding in a conference room at the current job. Or taking PTO. Or doing it at the kitchen table at six in the evening after a long day, tired, trying not to sound tired.

An AI interview runs when the candidate is free. Eleven at night when the kids are asleep. Sunday morning before church. Six in the morning before the shift starts. The model does not have business hours. The candidate picks the hour.

This is not a small thing. It is the thing that disproportionately hurts hourly workers, parents, caregivers, people in different time zones. The old pipeline optimized for the schedules of the people already in the building. The new pipeline optimizes for the schedule of the person trying to get in.

The rubric

Same questions. Same scoring. Every applicant.

A recruiter looking at a resume for five seconds sees the name of the school, the last employer, the whitespace. A rubric applied to a twenty-minute structured interview sees what the candidate actually said about a problem. Different signals. The second is harder to fake and easier to audit.

You audit. You publish the rubric. You publish the pass rate by demographic. When NYC Local Law 144 or the EEOC asks, you have an answer.

The data

Applicants prefer this. Not a little. A lot.

Seventy-four percent of frontline workers in Fountain’s 2025 Frontline Report said they prefer AI-driven interviews over waiting for a human scheduler. That is not a thin margin. That is an overwhelming majority of the people the product is built for choosing the AI path over the human one.

Their logic is simple. A possible human interview next week is not a job. A structured interview tonight, on their schedule, scored against a rubric — that is a real shot. They take the real shot three out of four times.

Recruiters prefer it too. They stop sitting through two-hour Zoom calls with candidates who never matched the hard requirements. The candidates who reach the human round are already in the rubric’s top quartile.

Both sides save time. People get hired faster.

The honest part

AI hiring has a bad reputation. It has earned some of it.

HireVue’s facial analysis. Amazon’s scrapped screener that learned to downgrade anything with the word women’s in it. Every vendor that claimed to predict personality from voice.

These failures are real. They are not arguments against structured interviewing. They are arguments against the specific thing those tools did — score humans on signals the humans did not know were being recorded.

The pattern here is the opposite. The rubric is public. The questions are the same. The scoring is deterministic at the hard requirements and auditable at the soft ones. The candidate knows what is being measured. The regulator knows what is being measured. If the model’s answer fails the audit, you do not get to deploy it.

You do not get to skip the audit.

The pattern

The old way scaled exclusion. Keyword filter, ninety-nine percent ghosted, a hundred human calls to a pedigreed subset.

The new way scales dignity. Every applicant gets a real shot at a fair rubric, on their own schedule. The ones who fail a hard requirement learn why at the door. The ones who reach the interview know the rubric they are being scored against. The ones who do not fit still get a response.

Nobody is ghosted.

Letting the invisible be heard is one of the more human things AI can do.

Somewhere in that pile of a hundred and fifty thousand applications is a person who would have been an extraordinary flight attendant. The old way never found her. The new way calls her tonight.

You do not need to believe AI is better than a human recruiter to see why it clears this specific bar. You only need to notice that the alternative was silence.

And the status quo is silence.