[hansvm]

I must be missing something. 1200 real applications are hard to sort through. 1200 mostly fake applications are much easier. Hiring is a high-leverage activity, and it's absolutely worth spending a couple hours going through those by hand.

[saulpw]

For 1200 applications, a couple hours translates to less than 10 seconds per application. In the age of LLMs, why do you think you'd be able to discern whether an application was fake in 10 seconds? Remember, it's not "obviously fake", it's "designed to con you" fake.

[jofer]

^ This. Exactly. Low value comment on my part, but as the OP in this case, I feel the need to say that this is the exact issue.

The "smell test" takes longer than you think and often involves an actual interview.

[carlosjobim]

How about 50 per hour? That's just 24 hours of work and a reasonable first look at one minute for each application. Very little time to spend for an important company decision which can cost hundreds of thousands of dollars.

[Balgair]

That's a half week of work without breaks at one resume per minute-ish.

I agree that it is a very important decision, but that's also unreasonable for a manager to set time aside to look through. You've just set the other projects that you're already behind on (that's why you need to hire in the first place) back another half week or so.

It's like a reverse rocket equation here. You need time to make more time, so you take time, but that time needs time, so ...

The cost isn't really borne by the hiring manager though, it's just their budget (that they argued for) that they need to spend down. The decision makers really don't care that much about the numbers, just that they don't go over.

[carlosjobim]

How can that be unreasonable? To work at least half a week for a decision which will cost the company hundreds of thousands of dollars, or even millions of dollars in the long run. What else is the manager doing which is more important monetary wise? And if managers are really too busy with raking in the millions to the company, then it's a fine time to hire somebody who's only job will be to hire more people (not a HR person of course).

[Balgair]

The manager is responsible for $X but only gets paid their salary.

I'm their day to day, hiring is a pain. They need the extra hands, but they have to go through more work to get that person onboard. The activation energy is high, higher now with AI and automated job applications clogging things up.

Then you have onboarding and the continued costs of management of that person. Honestly, most managers would want the smallest team possible in terms of day to day workload.

This is also why AI is appealing. The promise of no sick days, no HR complaints, no chit chat. Just pure work done in plain language. Work done overnight, right, the first time. A middle managers dream worker.

The thing that is more important is the budget. It's always the budget. Nothing matters but the budget. That's the second iron law of beauraracy, of course.

[carlosjobim]

As I see it, hiring people is the most important part of running any business - by a large margin. And if you have a lot of employees, then hiring people who are good at hiring becomes your highest priority.

> The manager is responsible for $X but only gets paid their salary.

That's why somebody higher in rank makes sure the manager gets the time he needs to make the best hires. Somewhere up the line there is somebody who cares about the basics of running a business right.

> I'm their day to day, hiring is a pain.

Of course it's a pain, that's why it's a job and why people get paid for it.

> This is also why AI is appealing. The promise of no sick days, no HR complaints, no chit chat. Just pure work done in plain language. Work done overnight, right, the first time. A middle managers dream worker.

Okay, but that means the company instantly lost all customers and all income and went bankrupt. Because why in the world would a client hire your company to use an AI, when they can just use the AI themselves? And don't say that there needs to be a human who is specialized in using the AI, because then you're back at hiring and having employees again.

[staticautomatic]

The AI-written cover letters are a dead giveaway and you can often spot them in less than 10 seconds easy, but it’s still a terrible slog.

If you don’t believe me, try clustering 1,000 cover letters.

[hansvm]

I don't know which 1200 applications they saw, but IME they're a lot better at trying to con you than succeeding. LLMs aren't great for a lot of use cases (yet?), and this is one of those areas where reality doesn't match the dream:

1. ~10% of applications are over-tailored. Really? You did <hyper-specific thing> with <uber-specific details> exactly matching our job description at $BigCo 3 years before the language existed and 5 years before we pioneered it? The person might be qualified, but if they can't be arsed to write a resume that reflects _their_ experiences then I don't have enough evidence to move them forward in the interviewing process.

2. ~40% of applications have obvious, major inconsistencies -- the name on LinkedIn doesn't match the name on the resume, the LinkedIn link isn't real, the GitHub link isn't real, the last 3 major jobs on LinkedIn are different from the last 3 major jobs on the resume, etc. I don't require candidates to put those things on a resume, but if they do then I have a hard time imagining the candidate copy-pasting incorrectly being more likely than the LLM hallucinating a LinkedIn profile.

Those are quick scans, well under 4s each on average. We've used 80 minutes of our budget and are down to 600 applications. Of the remainder:

3. ~90% of remaining applications fail to meet basic qualifications. I don't know if they're LLM-generated or not, but a year of Python and SQL isn't going to cut it for a senior role doing low-level optimizations in a systems language. If there's a cover letter, a professional summary, mention of some side project, or if their GitHub exists and has anything in it other than ipynb files with titles indicating rudimentary data science then they still pass this filter. If they're fresh out of school then I also give them the benefit of the doubt and consider them for a junior role. Even with that leeway, 90% of those remaining applicants don't have a single thing in any of the submitted materials suggesting that they're qualified.

So...we're down to 60 applications. We spent another 40 minutes. In retrospect, that's already our full 2hr budget, so I did exaggerate the speediness a bit, but it's ballpark close. You can spend 2min fully reading and taking notes on each of the remaining applications, skimming the GitHub projects of anyone who bothered to post them, and still come out in 4hr for the lot.

It's probably worth noting, that isn't all to say that <5% of programmers with that skillset are qualified. I imagine the culprit is spray-and-pray LLM spam not even bothering to generate a plausible resume or managing to search for matching jobs. If bad resumes hit 99 jobs for every 1 job a good resume hits then you only expect a 1% success rate from the perspective of somebody reviewing applications.

[aakresearch]

Your take is very sensible and I agree with it 100%, but the reality is that (by my assessment) it is absolutely not present in the wall of ATS filters one's job application is up against. I've sent hundred of CV/cover letters over last ten months, none of them are touched by LLM. Most cover letters I manually tailored to re-frame in line with job ad - where I cared a lot, some I just made with my generic template - still manually - where I couldn't be bothered to care. Invariably I either received no response at all, or for remaining 10% I received a generic rejection email, identically worded and styled in almost all cases.

Here it is, if you are curious:

"Thank you for your interest in the <position> position at <company> in <country>. Unfortunately, we will not be moving forward with your application, but we appreciate your time and interest in <company>."

The Resume I am sending out is just an evolution of one that worked very well for me for 25+ years. The roles, as far as I am able to see, are 80%-95% keyword match, with the non-matched keywords being exceedingly superficial. Yes, I haven't listed "blob storage", but guess what else I have used but haven't listed: "semicolon", "variable declaration" and "for-loops". Yet in this day and age one seems to be punished for not doing so.

I am very principled in not letting any AI anywhere close to my CV, because I think the usefulness of signal it conveys rests solely on it being addressed to and read by human, hence it has to be fully authored and tailored by human too. But these days this idea has completely flipped. Desperate times call for desperate measures. Standing by principles could lead to literal dying. Personally, I made peace with dying, but I cannot allow my family to go homeless. As such, I don't see it below me to go down the path of mass-blasting heavily over-tailored Resumes. If it bumps my chances from 0.05% to 0.2%, that's a four-fold increase that may be the difference between, literally, life and death. The organic job search with my natural skills and authentic ways of presentation I relied on for twenty years is dead.

[squigz]

> Those are quick scans, well under 4s each on average. We've used 80 minutes of our budget and are down to 600 applications. Of the remainder:

4 seconds each? You are... fast.

[whycome]

It's clear your org is looking specifically at coders/programmers. That's very different from the "academic research" background that the OP suggested. It takes a different type of analysis and vetting.

And different types of jobs require skillsets that aren't adequately conveyed in a traditional resume.

[Scoundreller]

> 1200 real applications are hard to sort through.

Probably not much yield in going through more than a few hundred.

Shuffle them around, start skimming through and throw out the rest once you realize you’re just seeing more of the same.

Pat yourself on the back and mutter “you need to be skilled and lucky to work here”

[aakresearch]

> Pat yourself on the back and mutter “you need to be skilled and lucky to work here”

It would be absolutely amazing if employers and recruiters finally were doing exactly this. We are in this dead end precisely because everyone is under false illusion that their pool of candidates has a hidden gem outshining everybody else in existence, and they absolutely need to sift through the whole pool to find this gem. As a result, all pools are never exhausted and only ever spreading, with more and more desperate people sucked into multiples of them.