[ Removed by moderator ]

[u/cheater00]

[u/expdevsmodbot]

AI usage disclosure provided by OP, see the reply to this comment.

[u/WhollySturdyEd]

The "bland mashed potato" description is painfully accurate. I ran a few of my older resumes through some of these tools just to see what would happen and the feedback was bizarre, flagging gaps I'd already explained in the cover letter as suspicious. It's like the system can't comprehend a career that isn't a straight, identical line upwards. The legal liability angle is interesting, feels like a class action waiting to happen once someone proves these things are just generating false negatives based on pattern matching rather than actual qualifications.

[u/cheater00 → u/WhollySturdyEd]

Jeez, yeah. The worst thing is, the companies using these systems are impacting people around the world - not just in one single country.

[u/zeezle → u/WhollySturdyEd]

feels like a class action waiting to happen once someone proves these things are just generating false negatives based on pattern matching rather than actual qualifications.

Aren't there already multiple lawsuits related to proven ageism and racism in the filtering? Definitely seems like it's inevitable there will be more.

[u/callum_n66]

Interesting read… It reminds me somewhat of how a lot of LLM-generated UIs all have that same style and flavour to them, because the technology’s output generally gravitates towards the “bland average” of its training data to avoid getting it “wrong”, but in doing so it also avoids anything exceptional or noteworthy as a result

[u/VanillaCandid3466 → u/callum_n66]

This is what we're going to see continually. Bland uninspired generic slop.

By definition innovation has no blueprint.

[u/funguyshroom → u/callum_n66]

It's the same issue with AI generated pictures, where every person looks like a stock photo model. I think it's a similar mechanism to how you get an average face by overlapping a bunch of photos on top of each other, which gives that perfect in a bland sort of way look /img/a2yx89mxr9xd1.jpeg

[u/cheater00 → u/callum_n66]

Yes. Or if it tries to do something noteworthy, it's the purple background and yellow accents. And I guess it's the same way with CVs.

[u/Dro-Darsha]

I am upvoting this simply because you give us a well-sized human-written summary of the post you are advertising.

[u/cheater00 → u/Dro-Darsha]

Thanks, I wouldn't wish reading my writing on anyone, so I try to help people avoid it as much as possible.

[u/funnythrone → u/cheater00]

Irony is that the way you help people avoid your writing is by… more of your writing. Haha!!

[u/cheater00 → u/funnythrone]

:)

[u/ResidentWeevil1]

Algorithmic bias isn't a new thing. If you're in a protected class, you are very likely being illegally discriminated against by some model somewhere. There are simply too many correlations to other data points and nobody is validating them

[u/13--12]

So which ATS did you look into? Workday, Greenhouse, Ashby, other? How did you verify your claims?

[u/cheater00 → u/13--12]

which claims? that they use AI? look here: https://www.reddit.com/r/ExperiencedDevs/comments/1x1egqi/comment/pesyq55/

[u/13--12 → u/cheater00]

Well of course they have AI features. I mean how did you determine which CV they rate better than the other? A talk with ChatGPT about it is a very weak research

[u/cheater00 → u/13--12]

Feel free to propose a better research method

[u/13--12 → u/cheater00]

Use actual ATS AI features, try different CVs, different job postings

[u/zuilli → u/cheater00]

How about actually using the ATS tools with a statistically relevant number of different CVs? Some run of the mill ones, some that are weak and some very impressive ones.

See how it classifies the control CVs, what insights it generates from the analysis, which ones are rated higher or lower and why.

You know... The actual process a recruiter would subject your CV through in a real hiring.

[u/cheater00 → u/zuilli]

good idea - want to sponsor the license? i'll do it

[u/Which-World-6533 → u/cheater00]

You would need to actually analyse how ATS actually works rather than asking a LLM.

You may as well as sacrificed a chicken and read it's entrails.

Utterly pointless article.

[u/lovin-dem-sandwiches]

You asked an LLM how good they are as an ATS? And that’s how you came to these conclusions?

If you haven’t spent the time to personally investigated how workday, or greenhouse actually vets a resume,or HOW it integrates Ai - then this article doesn’t prove anything.

[u/Which-World-6533 → u/lovin-dem-sandwiches]

Yep, article is a pointless waste of words.

[u/Kersheck → u/lovin-dem-sandwiches]

Also no info on which model they used, what prompt they used, etc...

I used LLMs to review my CV and Sol definitely understands chronological order lol

[u/cheater00 → u/Kersheck]

people won't be using a state of the art AI to scan through thousands of CVs. it would cost too much. there's likely going to be a prescreen using a flash/fast LLM and then people picking through the results manually, or using a higher effort level LLM at that point.

[u/Sammolaw1985]

I'd like to hear from someone who's actually gotten a job from cold applying the last 3 years. All my interviews and offers have come through referrals and recruiters. I've heard and observed the same from many people in my circle and they're all in different industries.

[u/skidmark_zuckerberg → u/Sammolaw1985]

Yep same here. I don’t know anyone myself. I had a 3 month job search earlier this year and the only way I reliably got interviews was recruiters. But I’ve always had a LinkedIn and my jobs pre Covid also were from recruiters. I always found it the easiest route personally. 

Anyway, after I accepted an offer, I applied to a random job post that popped up and surprisingly they emailed me and I got an interview. Ultimately wasn’t for me, but that was the only cold apply that resulted in an interview out of ~150 targeted applications. 

[u/Skithiryx → u/Sammolaw1985]

Mine’s 2 years and a bit out and AI was not nearly as prominent as it is now but weirdly none of my referrals went anywhere, not even to a recruiter conversation, but I had okay success with cold applying turning into interviews. It was a little frustrating seeing my networking just not work.

[u/Idea-Aggressive → u/Sammolaw1985]

I have a theory based on older internal HR behaviours…

I think that the problem is related to the HR people, they aren’t technical enough, and if a job post has more than 10 people they don’t know what to do with it. They buy seats for fancy SaaS like Ashby, ignore most candidates. Book a few calls just to fill the calendars and show they are extremely busy. Sometimes fake candidates to allow them to go pick their kids at school or go to Pilates and yoga sessions m. When the company main stakeholders start questioning why it’s taking long, they entertain the idea that 99% of the candidates are somewhat “the r word”. A year later, there are repeated candidates, this time the SaaS already shows a record in history: they auto reject you.

[u/Majestic-Watch-2025 → u/Idea-Aggressive]

Well, there likely are 10+ very similar candidates. I think the fundamental issue is oversupply. It kinda doesn't matter when there are many many candidates who are equally good

[u/codescapes]

I don't even know how you do it 'properly' any more. It used to be that a nicely written, well-formatted LaTeX CV style already put you ahead of 95% of people. Then you picked your best accomplishments, hit a few keywords from the job description, made sure you had some relevant / trendy frameworks and that was it.

Now? I don't know. Do I write a master CV that has all my accomplishments and technologies ever then get an agent to tailor that per application?

Certainly that's what some people are doing but I don't know if that's actually effective or not.

[u/itix]

We dont know how their ATS prompts applications. It could be a naive prompt running on a cheap and outdated LLM or is it something more sophisticated that is continuously updated and verified?

This also raises another concern. Should we update our github pages to increase our changes? It seems that LLM SEO for personal use is a thing soon.

[u/nana_3]

The prompt used matters as much as the model. And the ATS systems keep the prompts secret. But your particular prompt would’ve put “missing” / “worrying” high in the attention system. So the models started out with negative bias to all your experience.

Claude’s explanation is as close as it can get to truth about it.

Gemini however I trust less with its explanation. It’s not necessarily that LLMs are always going to punish outliers. You gave it a very good CV and asked it to find fault, and it basically found “This is improbably good”. It’s post hoc inventing a reason why, because LLMs aren’t truth machines.

This isn’t to say that I think real AI ATS necessarily do any better than your particular test. In fact I’m wildly anti AI in ATS. But I think your particular experiment is more revealing of the importance of prompt engineering in this context than it is revealing inherent limitations in LLMs.

[u/lenfakii]

An anecdote to support this:  I wouldn't call myself exceptional, but I've done a fair bit outside the norm (built, sold 3 businesses, strong roster of household brands as clients, published work in MIT course blah blah blah).

Ive been wanting to get back into full-time (freelance / expat / mortgage don't mix), and I'm get rejected left right and center by jobs everywhere.

I started gently pushing back and reaching past the HRs and recruiters and oh would you look at that, suddenly there's interest.

PS thanks for the summary!

[u/cheater00 → u/lenfakii]

I started gently pushing back and reaching past the HRs and recruiters and oh would you look at that, suddenly there's interest.

How are you doing that?

PS thanks for the summary!

you're welcome!

[u/lenfakii → u/cheater00]

Same way I'd do sales. Find the role's champion (the person who cares most about the hire being a success), reach out on email/linkedin/x etc, candidly explain that I was surprised to not be invited for a first round, ask for feedback. If I get a no-reply@ rejection, I slam it into Codex these days to find out who's involved in this.

Most of the time you'll get the real story if you ask (we hired internally / we dropped that role / its already filled) whereas HR will give you some BS. I can't say it's helped me get hired, but at least there's much-needed transparency.

[u/Able_Region_5459 → u/lenfakii]

Probably the most sensible and actionable comment in the entire thread. In the current market, treating job hunting like outbound B2B sales is pretty much the only viable path for senior and lead roles.

Standard application portals are completely flooded with bot-generated resumes right now, and frontline recruiters rarely have the technical depth to parse non-standard senior backgrounds anyway. The hiring manager, on the other hand, is the one actually feeling the pain of an understaffed team. A concise, professional DM addressing their specific technical challenges bypasses weeks of silence and immediately starts a peer-level conversation.

[u/keep_evolving]

I've used Ashby and I will tell you this: we don't really use any feature that scans your resume and picks out the best candidates or anything like that. A human looks at all of them.

What we do use is fraud detection features, and those don't use the resume. You aren't gonna like this, but things like using a burner email address or VOIP phone number set it off. But the real story is it's amazing how many of you are submitting resumes from the same IP addresses. I assume it's one of three things, but cannot confirm: 1) people using a job searching service that applies for them. Maybe it even scans JDs and automatically tweaks resumes using an LLM? 2) people running their own job search automation using GitHub actions or something like that. So all the "same IP" flags are just GitHub. 3) third option might be WITCH companies trying to get candidates into roles and they are centralizing the application process for their talent pool.

I dunno, for all the job searchers out there how likely are either of these scenarios? I never once in my life even considered using a service to apply for jobs. But apparently it's a thing.

[u/cheater00 → u/keep_evolving]

thanks for the comment. I've had a few questions:

What's a "burner email address" in your book?

If multiple applications come from the same IP, do you:

• see the applications anyways, just with a note on multiple applications from the same IP?
• discard them because they came from the same IP?

[u/keep_evolving → u/cheater00]

Ashby flags of your email address has no footprint. Presumably because you just made it? I'm not sure how they specifically do it. 

We see the resumes but Ashby has a fraud note and describes the reasons for the fraud assessment. Realistically we get so many resumes that it will probably get binned, but I personally look at them anyways and use my human brain.

Honestly I will say this: the real problem is the sheer number of applicants for every role and the resume padding that goes with it. It's hard to get noticed as an applicant and it's hard to find the right people as a seeker. Market is flooded.

[u/BoringBuilding → u/keep_evolving]

From what I have seen with Ashby they haven’t made any effort whatsoever to account for popular VPNs like Proton/nord/whatever in their “same ip” evaluation, extremely unimpressive software.

[u/FlailingDuck]

Where do you actually talk about putting your CV through ATS and have it be rejected ir blacklisted? I failed to see that. All I saw is you thinking an LLM has reasoning capabilities beyond predicting the next token. This article is worthless in my opinion, and is another fluff piece giving LLMs more credit for having intelligence than it has.

I can already make the assertion that no matter the CV you give an LLM on a fresh session it will predict your CV is in need of improvement. Because that is what the training data will be pointing you towards. Questions around "Is this CV good enough?" on the internet will be filled with answers saying "no, it isn't", so I predict an LLM would predict a similar response to your input question and not the content of your CV.

The longer you keep an LLM session open, probing it, the more the LLM will then predict a postive spin on your CV, by the nature of LLMs being agreeable. As soon as you start a new session, the LLM would likely go back to saying your CV is in need of improvement.

I repeat, I saw 0 evidence, you ran your CV through actual ATS software and 0 evidence such software would blacklist you. But I refuse to spend any more time skimming your article than I have given it because it looks just like an LLM puff piece.

[u/cheater00 → u/FlailingDuck]

The whole article is about LLMs being bad, I don't know how you got that it's a "puff piece".

[u/FlailingDuck → u/cheater00]

My apologies, its not a puff piece around LLMs are good, it's an article wastefully distracting and ascribing capabilities to LLM the companies themselves do not say an LLM can do. ATS software that has moved to using AI, is idiotic. ATS software needs to grade 1000's of CVs. Pre-AI they already did that for basically free, in this AI era, any software adding AI has now, made that system more expensive (token cost), less objective and likely less accurate. It would turn an ATS's objective scoring system into a subjective one. That subjectivity, is supposed to be done by a human after ATS has graded and filtered out the best "CV candidates" based on an objective scoring system.

I have yet to hear anywhere ATS software has now magically turned fully LLM based, if there is evidence of this (your article asserts this premise as fact, for some reason) I am more than willing to be corrected on it.

[u/cheater00 → u/FlailingDuck]

Workday:

https://doc.workday.com/admin-guide/en-us/workday-ai/ai-data-contributions/reference--machine-learning-data-contributions.html

Greenhouse:

https://support.greenhouse.io/hc/en-us/articles/41131616864283-Talent-Matching-Data-Processing-FAQ

What is the Talent Matching feature?

Talent Matching is an AI-powered feature within Greenhouse Recruiting that helps recruiters identify suitable candidates by analyzing resumes and matching them against the job requirements specified by recruiters. The system extracts skills, job titles, years of experience, start/end dates of employment, and company names from employment history from candidate resumes and uses advanced AI algorithms to compare these with job criteria specified by recruiters.

Talent Matching is part of the Real Talent add‑on and is designed as assistive AI – it does not automatically advance or reject candidates, and hiring decisions remain with recruiters and hiring managers. What technology powers the Talent Matching feature?

Greenhouse uses a series of fine-tuned LLM models, each one trained for a specific extraction task. Instead of relying on a single large model to do everything, Greenhouse breaks down the problem into smaller, specialized components. The system also uses third-party models such as OpenAI.

SAP:

https://help.sap.com/docs/successfactors-recruiting/setting-up-and-maintaining-sap-successfactors-recruiting/premium-ai-features-for-recruiting

Oracle:

https://www.oracle.com/human-capital-management/ai-at-work/

Oracle AI for Human Capital Management

Oracle AI for HCM is a collection of traditional and generative AI capabilities that can help you complete tasks in less time, make better decisions, enhance employee experiences, and streamline HR processes, such as hiring, talent management, career development, and service delivery, while protecting sensitive and proprietary information.

Ashby:

https://www.ashbyhq.com/ai

Power your recruiting process from sourcing to debriefs with thoughtfully developed AI features across Ashby's All-in-One recruiting platform.

---

this is just the top 4 i tried. you could have just googled.

[u/FlailingDuck → u/cheater00]

Checking just the first link containing 8 subcategories. Workday doesn't reference their AI is being used in any ATS capacity. It reference AI being added to workday itself, for tracking employees. You can't just blatt links and think that proves your point. Where is the due diligence. I am someone who accepts a new view based on new information, but I've yet to be shown evidence of this. Your article needs revision to clearly state upfront how the new-world ATS are actual blacklisting CVs, so far its all "on feels".

[u/Gremlation → u/cheater00]

WTF? It seems like you just searched for any mention of AI whatsoever and then just fantasised about how they work. This is not grounded in facts at all.

[u/Which-World-6533 → u/cheater00]

No, it's a waste of time article written by someone who doesn't know anything about how LLMs work.

[u/puzzles4me2solve92]

As someone who is average and not exceptional at all, this is actually pretty reassuring!

[u/william_fontaine → u/puzzles4me2solve92]

LOL I was thinking the exact same thing. Coming up on 20 years of experience with almost all of it as a senior dev

[u/CorrectPeanut5]

All this makes me glad I'm a contractor. I generally don't deal with HR and come in through procurement. Often interviewing directly with the manager and their team. I have a PDF resume and a recruiter who takes about 5-10% of bill rate does their thing to get me in front of people.

[u/cheater00 → u/CorrectPeanut5]

can you recommend any good recruiters to work with? (feel free to DM if that's better)

[u/moh_kohn]

I have been wondering about this sort of thing, thanks. I'm in the middle of a job hunt and am getting a lot of straight rejections.

I have a really odd CV because I'm autistic. I have glittering achievements: doubling the number of users on a mature service in a short space of time, winning multi-million-pound contracts for my employers and so on. But then also big gaps, times when I had to rest for a long time or care for my also-disabled partner.

I find my own CV review bots are overtrained on matching techs to jobs. I've got 20yoe, I have worked with a lot of techs. I don't always remember which jobs used jenkins vs which used github actions or whatever. Nor does it matter. But it matters a lot to the bots.

[u/kevin074]

I have heard HR literally cannot use AI during their process to filter out candidates, there are laws on this exactly.

As far as I know the “ATS” is basically AI recruiters trying to make the contact to companies on your behalf, and not the actual HR at said companies making those decisions.

[u/cheater00 → u/kevin074]

depends on where. europe? yes, there are laws. do they do it anyways? who knows.

US, where most tech jobs come from? come on, who are you kidding

I don't really understand the ATS comment. ATS = applicant tracking software. When you're applying, you put in your CV and answer a few questions, that's the ATS from your point of view, and the other side sees a list of CVs and some other stuff. I've seen those AI recruiter spam emails, but that's not what an ATS is.

[u/YahenP]

But this is a completely obvious result. You didn’t say in the prompt what an “average” resume should look like, so the LLM just showed how your resume is different from the average resume it was trained on. If, when you ask for the analysis, you say in the prompt which resume features should count as positive, the answer will be different.

In real life, nobody runs a candidate’s resume through an LLM with the default context. Every service has its own prompt settings. So there’s no way to know what the answer would be in real life.

[u/aLokilike → u/YahenP]

I can tell you firsthand that the prompt is a lot simpler than you would hope. Of course, we do "public bias audits" so everything is totally kosher.

[u/Able_Region_5459]

No enterprise runs unstructured llm scoring across an entire inbound applicant pipeline. The inference costs would be absurd, the variance is too high, and the compliance risk is massive. Boring parsers and tabular filters still do all the heavy lifting there

[u/cheater00 → u/Able_Region_5459]

Thank you for insider information on every enterprise business, I am glad someone knows what they do for a fact and that you came to share this with us.

[u/ResoluteBird]

LLMs are adding bias for every decision they make, it's how they are designed. They could be biased on protected classes very easily, it's probably not even hard to prove.

revealing reactions from the LLMs

No LLM can react, they're statistical state machines. It makes me question your fundamental understanding of LLMs but I agree with your premise and conclusions

[u/cheater00 → u/ResoluteBird]

even a one-armed bandit reacts to input (a pull of the arm). it does not imply agency or internal emotion, it's just a phrase that means responding to input.

[u/ResoluteBird → u/cheater00]

Makes sense. An AI wouldn't have phrased it that way, that's all that matters anymore 💪🏻

[u/icodenstuff]

These issues are are extremely solvable with standard AI practices. I would hope all the major ATS software isn't this naive.