u/enhancvapp

Maybe a bit random but I wanted to hear what people in the industry think about this. 125,759 tech workers laid off so far this year. That’s already more than all of 2025, and August isn’t over…

Zillow, TikTok, Etsy, and Google all announced cuts within days of each other. Almost every one of them used something along the lines of “cost discipline” or “reorg.” But more importantly nobody mentioned AI!

Then Oracle. Reportedly planning another round this month, some teams facing double-digit percentage cuts, right after a fiscal year where its AI infrastructure capex hit $55.7 billion (more than double the year before).

Oracle’s own filings already tied part of last fiscal year’s 21,000-person headcount drop to AI adoption. So one company will say it out loud and basically no one else will.

Makes sense from a comms standpoint. “We automated the role” sounds worse to investors and press than “organizational realignment,” even if the severance math and internal headcount planning tell a more consistent story.

If you’re evaluating offers or thinking about a move right now, I’d weight the roles being cut more heavily than the stated reason. Support, ops, content moderation, anything adjacent to what a model handles decently well this year.

Texas AG just opened an investigation into LinkedIn for allegedly running "ghost jobs" — up to 1 in 3 postings might not even be real. Meanwhile people are paying $40-70/month for Premium specifically to get "priority access" to these listings.

So the recruiter InMail credits might've been buying access to jobs that don't exist. Incredible business model.

Will this be picked up by AGs in other states?

We've been going through some hiring-timing and ATS research lately, plus things we've noticed on our side, and "apply early" turns out to have more behind it than just the usual career advice. So we've put together a few pointers that may prove to be helpful.

Why timing matters right now. The flood of AI-generated applications is pushing a lot of ATS setups toward hard volume caps and pure chronological sorting just to stay manageable. One survey put the share of recruiters reviewing applications in the exact order they arrive at something like 52%, and plenty of dashboards default to most recent.

The windows that seem to matter. Apply within 24 hours of a posting going live and callback rates reportedly jump around 32%. Stretch that to the first 96 hours (about 4 days) and one analysis put the interview-chance multiplier as high as 8x versus applying later. After that, a chunk of listings hit their applicant cap, 300 to 500 seems to be the common threshold before a posting gets paused or hidden from new applicants entirely. Doesn't matter how good the resume is if it never gets seen!

Day and time seem to matter almost as much as the window itself. Monday and Tuesday mornings, roughly 6 to 10 AM in the employer's local time, is when recruiters are actually planning out their week, with about a 13% higher response rate showing up in that morning window. Tuesday specifically had something like a 20% higher interview rate in one dataset. Friday afternoons, weekends, and anything sent between 7 PM and 1 AM tend to just sit there until Monday's pile devours it.

One thing worth separating out... none of this works if the resume itself is generic. What actually does is having a setup ready ahead of time. Real-time alerts instead of checking job boards once a day. A master resume with 3 or 4 pre-built summary and bullet variations. 5 minutes pulling keywords from the posting, 5 swapping in matching bullets, 5 proofreading, then submit, so tailoring takes fifteen minutes instead of two hours (yes, I know this is very general but you get the idea).

We tend to see the same education section mistakes pretty constantly, so here's the short version of the advice we give :)

GPA. Include it if you graduated in the last 2-3 years and it's 3.5 or higher. Lower than that... drop it. Recruiters read a GPA on a senior resume as "nothing better to show." Nobody really checks it past your first job anyway.

Major and minor. Major always goes in. Minor only gets a spot if it's relevant to the role. Data science minor on an analyst application, yes. Philosophy minor on a sales resume... just taking up space.

Graduation year. Fine for the first decade of your career. Past 15-20 years, plenty of people drop it, and that's pretty reasonable. The year tells hiring teams your age, and age bias still happens even unconsciously.

Honors. Cum laude, dean's list, scholarships, all worth listing as a new grad when you don't have much work history yet. Once you have other... professional accomplishments, they can become excess.

The bigger pattern: the education section shrinks as your career grows. New grad, it can sit close to the top with these details. But ten years in, one line at the bottom is probably enough. Degree, school, done :)

What's the education question you're never sure about? Drop it below and we'll answer. Anything we might be missing?

Our resume reviewers see the same education section mistakes constantly, so here's the short version of the advice we give :)

GPA. Include it if you graduated in the last 2-3 years and it's 3.5 or higher. Lower than that... drop it. Recruiters read a GPA on a senior resume as "nothing better to show." Nobody really checks it past your first job anyway.

Major and minor. Major always goes in. Minor only gets a spot if it's relevant to the role. Data science minor on an analyst application, yes. Philosophy minor on a sales resume... just taking up space.

Graduation year. Fine for the first decade of your career. Past 15-20 years, plenty of people drop it, and that's pretty reasonable. The year tells hiring teams your age, and age bias still happens even unconsciously.

Honors. Cum laude, dean's list, scholarships, all worth listing as a new grad when you don't have much work history yet. Once you have other... professional accomplishments, they can become excess.

The bigger pattern: the education section shrinks as your career grows. New grad, it can sit close to the top with these details. But ten years in, one line at the bottom is probably enough. Degree, school, done :)

What's the education question you're never sure about? Drop it below and we'll answer. Anything we might be missing?

The actual resume, details redacted. Note where your eyes go first, that's where the pivot happens.

Different kind of win this time: a career changer. Eight years in marketing analytics and consumer insights, interviewing for an entry-level IT support role, at the company he already works for. Internal applications still go through the ATS, and Best Buy runs an in-house one, not an off-the-shelf platform. Single column, [template name]. He used Resume Tailoring, the Checker [scored XX], Content Improvement, the Content Analyzer, and the AI bullet rewriter.

What works

The most recent role is doing all the pivot work. "Resolving product catalog, order, payment, shipping, and platform inquiries across email, chat, and phone channels" is support-desk language, tiered channels and all. Whoever screened this saw a person already doing frontline technical support in everything but title. When you're changing directions, the top third of the resume has to already live in the new field, and his does.

The technical literacy is on the page without being claimed. SQL, Power BI, Tableau, data modeling. None of it is IT support, but together it reads as "comfortable in systems," which for an entry-level IT role is most of the ask.

And the overqualification reads as intentional, not desperate. Senior analyst roles stepping into a support job usually triggers a "why" from recruiters. An internal candidate moving toward the company's technical side answers it before it's asked.

What we'd fix

The summary is fighting the application. It opens "data-driven customer experience and marketing professional" and spends seven lines positioning him for a job he isn't applying to. For a pivot resume, that's the one section that has to be rewritten per target, and this one wasn't. He got the interview despite it, likely on the strength of the internal referral path, not the summary.

The skills section lists Excel three times. "Advanced Excel," "Excel," and "Microsoft Excel," all in the same block. That's what an untended keyword dump looks like, and it's carrying marketing terms (Brand Awareness, Paid Search Marketing) that do nothing for an IT screening.

The chronology is broken. Coborn's (2020–2021) is listed below Carlson Wagonlit (2018–2020). Reverse-chronological order is the one structural rule parsers and recruiters both rely on, and a custom ATS is exactly where a scrambled sequence can garble the work history. This one parsed anyway. That's luck, not license.

The current role is thin: two bullets, both starting "Managed," in the spot that gets the most reading time. And the oldest role says "conducted market research" twice in three bullets.

Overall: proof that a resume doesn't have to be clean to work if the top third tells the right story to the right reader. But this one got an interview with its summary pointed at the wrong career. Imagine what it does once that's fixed.

Two numbers worth sitting with.

Around half of job listings right now are ghosts. Never getting filled, posted for optics, pipeline building, or a budget that disappeared.

Also around half of applicants get rejected without saying anything. No email, no update. The ATS filtered them and nobody ever paid attention...

Stack those. Out of 100 applications, ~50 went to jobs that don't exist. From the rest, half vanished into a black hole with no signal back. You're really competing for maybe 25 real chances, and you'll only hear about a fraction of those.

"Just apply more" doesn't fix this. More volume into a broken funnel is still a broken funnel.

What to do? Networking only? Volume play with automation? Stop applying and wait it out?

Robert Half data via CNBC this week: 32% of US hiring managers say they eliminated a role primarily due to AI, then later rehired for the same or a similar position.

Some big-company examples back it up. like when IBM's AI handled 94% of routine HR requests but then fell apart on the rest, and now they're planning to triple US entry-level hiring in 2026. Or when Ford brought back hundreds of engineers to fix quality problems the automated systems kept on missing...

The practical takeaway of this is that if "AI" or "automation" appeared anywhere in your layoff justification, keep an eye out for your old company's job postings. Roles are coming back, sometimes within months, sometimes at an even lower salary band!

And if your old role does reappear, that's useful in interviews elsewhere too. "The position was eliminated in an AI restructuring the company has since reversed" is a much stronger answer to "why did you leave" than something defensive ;)

Anyone here had their eliminated role come back?

Quick read on last week's BLS release, since the headline number and the actual picture point in different directions.

57,000 jobs added in June, against a forecast of 115,000. April and May were revised down by a combined 74,000. Unemployment fell to 4.2%, but mostly because labor force participation dropped to its lowest point since March 2021. Fewer people working and fewer people counted as looking.

Where the jobs actually were: professional and business services (+36k), social assistance (+25k), healthcare (+22k). Leisure and hospitality lost 61,000.

What this means practically: openings are concentrated in a few sectors, so if yours isn't one of them, expect a longer search. That's the market, not your resume. Hiring slows across the board in stretches like this, and search timelines stretch with it..

One thing worth watching: slow hiring months tend to produce more stale and speculative postings, since companies leave reqs up without urgency to fill them.

This one landed its owner an interview at HCA Healthcare in Nashville, one of the largest hospital systems in the US. Lead Software Engineer, backend / AI & cloud. Details anonymized.

Worth noting before the teardown: HCA runs an in-house ATS, not Greenhouse or Workday. Custom parsers are the ones people worry about most, and this went through fine. Template is our Ivy League, single column, Volkhov headings with PT Sans body. The user ran it through Resume Tailoring and the Resume Checker (scored 77, not a perfect score, still got the interview) and used Content Improvement and Improve Text along the way.

What works

The headline does the positioning in eight words. "Lead Software Engineer | Backend Systems | AI & Cloud" gives a hiring manager the level, the specialty, and the two keywords half the job descriptions in this space are screening for right now. For a hospital system actively building out AI capability, that third term is probably what got this pulled from the pile.

The numbers are front-loaded where attention actually goes. The current role has five metric-carrying bullets (50% faster response times, 40% latency cut, a legacy API taken from 15s to 1.5s), then detail thins out as the roles get older. That's the correct shape. Recruiters read top-down and spend most of their time on the most recent job.

The "Key Technologies" line under each role handles keyword matching without a bloated skills dump.

And the education section tells a story without narrating it: a Mechanical Engineering bachelor's, then a CS master's finished while working full-time as a lead. That reads as a deliberate pivot someone followed through on.

What we'd fix

The summary closer ("Seeking impactful roles in innovative product teams tackling real-world challenges") is copy-paste. Five hundred other applicants are saying the same sentence this week.

Two proofing misses: the skills labels have double colons ("Languages & Frameworks::", three times) and one bullet reads "Troubleshoot and resolved bugs," a tense mismatch. Neither kills an application at this level. Both are what gets noticed in a tie-break between two finalists.

The oldest role carries one filler bullet ("Examined business, functional and technical requirements to make sure project met expectations"). It says nothing. At three roles deep, cut it and let the automation POC bullet stand alone.

Overall, a resume that understands where scrutiny lands and puts its best material exactly there. A 77 on the checker with two typos still in it, and it worked.

Japan still hires huge numbers of people through the rirekisho, a standardized one-page form you can buy at a convenience store (the template is literally a national standard). Every applicant's document looks identical. No formatting decisions, no wondering if your bullet points stick out, etc. The form is deliberately boring so the interview actually does all the work.

Korea went even further. Since 2017, public institutions run blind hiring. No photo, no age, no university name on the application. Early research found more hires coming from outside the top Seoul schools.

Germany sits in the middle... The Lebenslauf is a strict reverse chronology, often with a photo and birth date, and gaps get questioned in a way US recruiters would consider invasive.

Then there are markets where the document barely matters at all. In the Gulf, hiring runs on referrals and visa status. A lot of hiring in China happens inside chat apps, you message the hiring manager directly and your profile is just a screen they scroll through.

It's easy to see that the anglo resume is the only version that treats the document itself as a skill test. Format it right, beat the parser, and you get an interview someone with identical experience doesn't.

Anyone have experience outside of these places? It's interesting to. hear stories from outside our usual stomping grounds.

Here's something we keep seeing. The format rewards people who can narrate well under pressure. Specific, confident, structured story on demand. Some people are great at that. A lot of very competent people aren't!

Had someone come through our platform recently, a software engineer with a strong track record, kept getting to final rounds and losing. Feedback was always some version of "didn't demonstrate impact clearly." His work was solid. His answers were just reading like a job description instead of a result though.

The fix that actually helped: stop describing what you did and describe what changed because of it. "I managed deployments" versus "deployment failures dropped by 40% in the first quarter after I restructured the rollout process." Same experience, but an absolutely different signal to the interviewer.

Doesn't require being extroverted. Requires thinking about your work differently before you walk in.

Do you think that the actual format is even fixable or if it's just a sad tax introverts have to pay to get through hiring?

In 1921 Edison gave applicants a 146-question trivia test to screen for executive positions. Questions like "where is Byzantium?" and "what is copra?" Of the 718 people who took it, 57 passed. Albert Einstein reportedly failed it. So did Edison's own son, who was at MIT at the time. Edison's response was to guarantee his son a job anyway :) Sound familiar?

He also had a separate screen for research assistants. He'd take candidates out for soup. If they salted or peppered the bowl before tasting it, they were out! His reasoning: he didn't want people who operated on assumptions.

So the foundational logic of modern hiring has been, from the start: design a process that filters for the behavior you think you want, watch it immediately produce absurd results, and then quietly exempt the people you already like.

Nothing about that has changed. The trivia test became the brainteaser. The brainteaser became the behavioral round. The soup became "tell me about a time you demonstrated ownership." Different props, same idea...

What's the modern equivalent of the soup test is in your industry. Because every field seems to have one.

Start with the first clause. In April 2026, we surveyed 1,066 U.S. job seekers. Half had been rejected in the past year without a single word from a human person. Of that group, 64% believed a machine made the call. Only 9.7% said an employer ever clearly told them AI was involved. Everyone else was guessing, and sadly most still are.

The second clause. Nearly 1 in 3 employers admits to posting jobs with no current intent to hire, according to a Clarify Capital survey of 1,000 employers. A separate ResumeUp analysis of LinkedIn put the ghost job share at 27.4% of all U.S. listings. Since the start of 2024, job openings have outnumbered actual hirings by more than 2.2 million per month. The labor market looks busy but a ton of that is just show.

The third clause is the angry one. The people running these systems aren't oblivious. Dan Chait, CEO of Greenhouse (a hiring platform used by tens of thousands of companies) called it an AI doom loop in 2025, "It's getting easier and easier to apply for jobs and harder and harder to get a job."

A separate Enhancv study of 25 U.S. recruiters found 92% say their ATS doesn't auto-reject anyone, it ranks them! Qualified candidates don't get rejected. They get buried so deep that no one scrolls all the way down to them.

So the system isn't broken by dumb accident. The incentives all point in the same direction. Job boards reward activity over accuracy. AI adoption gets measured by time-to-hire, not quality-of-hire! Posting a ghost job costs nothing, buuuuut closing it requires someone to remember to do it :(

What replaces this? Or have we just accepted that this is hiring now.

Leonardo da Vinci wrote the first one in 1482. A personal letter to the Duke of Milan listing what he could build, what he could design, and what he could do. One person proving their worth to another Specific, personalized, human. And it worked.

For the next four centuries almost nothing changed. Resumes stayed close to that simple origin. Then came the Great Depression, forcing documented work history into the administrative system. Corporate America scaled up in the 1950s, and the resume became a sorting mechanism for volume it was never designed to handle.

So they built ATS to manage the volume. Candidates learned to game the keywords. Then AI started writing resumes en masse. Now we're at the point where a Robert Half executive is telling HR Dive that qualified candidates are getting auto-rejected because their application "doesn't look as good as one created by AI." The tool that exists to discover talent is filtering by prompting skill.

It wasn't super surprising when I read in the Willo 2026 Hiring Trends Report that only 37% of employers still consider credentials and work history among reliable indicators of talent. On top of all that, 40% are moving away from resume-first hiring completely.

Here's where I think the discussion becomes an argument. There's a lot of recruiter energy right now around spotting and rejecting AI resumes, as if that's a problem that will ever get solved! It doesn't. Nobody debates whether Word-processed resumes are cheating. Resisting AI-written content is the same argument, just earlier in the cycle. The format changes and everyone needs to and WILL catch up. Eventually it's just assumed.

The more useful question is what makes an AI-assisted resume actually work in the interim. A couple things seem to resurface consistently.

A resume that says "led a team" tells a screener and a recruiter the same amount of nothing. The ones that make it have real numbers in them: ramp time, headcount, revenue, something that couldn't have been invented (at least easily:)).

AI can generate the structure, but the specifics still have to come from somewhere real. And they need to hold up under a LinkedIn cross-check, since that's happening pretty routinely now. Generic language that looks refined but doesn't match anywhere else kills applications that would have otherwise gotten through.

The resume probably ends up as a formality that everyone treats like a cover letter... technically required, rarely decisive. The interview and the skills test do the actual work. The document just gets you in the door. Which is basically da Vinci's letter again :)

What are you seeing on the hiring side? Are skills assessments replacing the resume screen or is it still resume-first with more skepticism layered on top? And do you think the "we can tell it's AI" rejection phase has a shelf life, or does it stick around?

It became known as the Friedman Doctrine. And it rewired how American corporations thought about everyone who wasn't a shareholder.

Before 1970 the dominant model was stakeholder capitalism. The idea that a company had obligations to employees, customers, and communities, not just investors. It wasn't perfect. But it produced a labor market where long tenure was rewarded, pensions were real, and layoffs were a last resort rather than a line item on a quarterly report.

The shareholder primacy model flipped that. Labor became a cost to be optimized. Loyalty became a one-way street. And every mass outsourcing wave, benefits cut, and "we're a family" layoff since then has been the logical downstream of one guy's opinion piece.

I study resume and career trends, and the overemployment numbers in our latest research surprised me. It's not just early-adopter tech workers anymore. Finance, ops, consulting, healthcare admin. The practice has spread into roles nobody expected.

The pandemic is where it started shifting. Remote work proved, at scale, that presence and productivity weren't the same thing. Then the 2021-2022 hiring boom created a window where companies were desperate, remote-first, and not asking too many questions. That's when a lot of people ran the experiment for the first time.

The 2023-2024 layoff wave took out people with a decade or more of tenure, good performers at companies that just didn't care. Real wages kept falling behind inflation. And somewhere in there the loyalty contract stopped feeling like a real contract, because companies made it very clear it wasn't one for them either.

The ethics debate around OE annoys me juuust a tiny bit. It frames this as a worker integrity problem. But workers have been watching companies optimize their labor costs aggressively for years. This looks like people optimizing back!

So where do you actually stand.

Quick poll. Drop your letter in the comments or send them to me telepathically:

1. Yes, already doing it or actively looking for job #2
2. Seriously considering it
3. No. It's an ethical line for me
4. No. It's too much risk

What I'm less confident about is how much any of that actually reflects what gets someone hired vs. what the recruiter added just because the last job description had it.

So question for the senior level people: what was the thing that really made a difference? Not what the posting said, but what the hiring manager actually seemed to care about when you were in the interview process.

I've seen a few patterns in the data we look at. End-to-end ownership comes up a lot (design through deployment, not just "I wrote the feature"). So does distributed systems depth, not just "I've used microservices" but actual replication, consistency, failure modes. Observability and chaos testing show up quite a bit as well.

But I'm also curious about the softer stuff. Did architectural fluency matter more than specific cloud vendor experience? Did anyone actually care that you'd done RDMA or NVMe work, or was that just a nice-to-have they forgot to remove from the job ad?

What was real vs. what was stuff nobody actually tested you on.

A recruiter who hires for Fortune 500 companies told us, more or less:

>"I understand why candidates don't trust it. It makes mistakes. It's not going away, though. We're going to keep using it because it helps us."

That came out of our 25-recruiter interview series. Then in April we surveyed 1,066 US job seekers about the other side of the desk, and the numbers are a clear sign of the distrust.

Half (50.5%) got at least one rejection in the past year with zero human feedback. Of that group, 64% believe a machine made the call. Only about 1 in 10 were ever clearly told an AI was involved in evaluating them.

The uncomfortable part is what the recruiter interviews add. 92% of recruiters said their ATS doesn't auto-reject resumes. What's usually happening is volume: hundreds or thousands of applications, a human fills the shortlist and stops reading. The silence feels algorithmic. Often it's just somebody who doesn't have the time.

But from the candidate point of view, you can't tell the difference, so the algorithm takes the blame either way. And the recruiters know it. They just can't fix it from the inside, the tools and the application volume sit above their pay grade.