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- Hacker News
- Feels like "I Don't Hire Unlucky People" all over again, but with extra tokenmaxxing steps.
https://neonrocket.com/2014/05/rescued-from-the-ashes-i-dont...
by a4isms - This insanity only exists because the tech industry is standard-less. No formal education needed, no formal training requirement, no apprenticeship, no software building code, no professional organization. Resumes have never been a good predictor of success - and why would they be?? Even if they're truthful and it's "impressive looking", that doesn't give you any assurance of knowledge, of who they learned under, what they learned, that they passed some minimum criteria. We might as well be rolling dice. So why not an LLM that randomly assigns scores?by 0xbadcafebee
- Do you think fields that have formal criteria don’t use resumes with keywords? I bet Lawyers look for school names and big law firms all the time.
Credentialing helps maintain a quality floor. Does this person have basic employable skill? Nothing more. It actually doesn’t help you identify levels of talent and skill which is a universal hiring problem.
We do have a credential - a CS degree. And you can see it is a mixed signal. Employers can choose of their own free will to take risks on employees that do have this credential, or not.
Mandating by law that you must have a CS degree doesn’t seem to help our field as we famously have high performers across the spectrum of formal education.
- I have no data to lean on other than my experience and intuition but I’d say that’s not the case. My domain is corporate finance, which encompasses a lot of structured roles and certifications, yet I consistently feel the Resume is just a poor device for making any judgement calls. Having people summarize their career into 1-2 pages of bullet points just doesn’t mean much. Especially now that keyword packing is a thing. It’s just meant as an introduction/sniff test to open the door for a conversation. Then it allows for deeper more probing questions to be asked. This where you’ll assess how impactful their contribution to a project actually was. Were they really living up to your definition of a manager, or were they more so an IC that had a lot responsibility. Stuff like that.
> Resumes have never been a good predictor of success
Applies broadly to the world, it’s not unique to tech
by conductr - I tried this with my CV, and it somehow scored me bonus points for GSoC!
Even though I've never done this, and don't claim to have done it in my CV.BONUS POINTS: 5.0 ------------------------------ Google Summer of Code (GSoC) participation: +5 - Happened to me as well. It is a known hallucination https://github.com/interviewstreet/hiring-agent/issues/240by fernandopj
- I ran the ATS myself and had a similarly quirky experience. I was in the 70s because it couldn't find my GitHub profile, and then it didn't like some of the popular Ruby libraries I'm the author of.
After a few runs it picked things up appropriately. I always got dinged on formal education though.
This stuff is gross.
by joshmn - Similar to my experience. Put me around 65 in some runs, because it didn't like I don't have contributions to OSS.
Also, it doesn't pick up certifications or awards. I tried some PRs people are suggesting with enhancements (https://github.com/Zem-0/hiring-agent), it helps, but overall their ATS is hugely biased towards people with large GitHub contributions to OSS.
by fernandopj - This word (determinism) has a magical effect of warping any online posts it touches. Once you hear it you can almost guarantee it's going to be misguided. At least this time it's actual determinism (same input = same output), not arbitrary unrelated things.
Determinism matters for reproducibility, but do you really want these outputs to be reproducible in this particular case? Making LLM outputs deterministic is relatively trivial, you have to use batch-invariant kernels (if you use batching) and either set the temperature to 0 (don't do that, randomized sampling is here for a reason) or fix the seed (better). It's readily available in a few systems. But this won't make the result more useful, it will just obscure the fact that the agent is genuinely not sure about it - look at the range of the scores it gives! It still won't predict anything but the score will stay the same each time. Do you really want that?
What happens here is they're supplying too little information (just a resume, which is almost at the noise level) and expecting a reply with too broad implications. This is a basic design mistake regardless of whether it uses LLMs. All surveys, tests, laws, and voting systems are extremely sensitive to framing because they work off too little information. But they also don't exist in vacuum, unlike this thing.
- Nondeterminism is also a feature, not a bug. If you don't want people to optimize against your filtering process, you have to make it somewhat nondeterministic. For example, better candidates are exponentially more likely to pass the filter, instead of a hard cut-off at the top-100. Then it becomes no longer worthwhile to Goodhart the filtering process, because it barely increases your chances and there are so many more places you can use your time better.by programjames
- This. Human judges and examiners are famously not deterministic even though we would wish it were so - we've probably all heard the thing of harsher sentences being given in the hour before lunch.by RugnirViking
- I made a similar comment on a different post. Non-determinism does not necessarily mean it cannot reliably reach the correct output (although sometimes it does mean that). Las Vegas algorithims are non-deterministic and 100% accurate. The tradeoff is the time it takes to reach the correct answer is highly variable.
To contextualize this insight in your post and basically just repeat what you are saying: The mistake is not using a non-deterministic system. The mistake could be, in some sense, using it too little. Re-evaluating the same resume 5 times and seeing a high variance in scores is a more useful signal than evaluating it once.
by nonethewiser - It's always amazed me that a tech company will pay $300,000+ for a good engineer, because talent is so hard hard to find... meanwhile their recruiter operates unsupported, has a very different idea about what good looks like. Their ATS black-holes >50% the resumes because it's filtering heuristics are garbage because recruiting selected the ATS system because it has a google Gmail integration or something, and the ATS's filtering technology was not reviewed by anyone in the engineering or data teams.by seanieb
- > The default model is gemma3:4b
That’s a tiny model. No LLM is going to be a perfect and repeatable judge, but a tiny 4B model is like plugging an RNG into this system.
This whole exercise feels like someone vibe coded an ATS and got it to the point where the tests were passing because they decided they should have an open source ATS project.
by Aurornis - This sort of model is fine for small problems, when used in the right way. I think there's probably a version of Resume analysis that would work well with this model, but "hey clanker, what projects has this person done" is not the way. You need extraction, cleanup, probably OCR to compare and further clean up, multiple analysis passes per signal with LLMs, judges, etc. None of that needs to be large models, you'll get marginally better performance, but there's very little context, these models will perform well when used correctly.by danpalmer
- I think what's more worrying to me (if other systems work like this ATS) is that it seems to judge based on a bunch of factors that will probably disqualify a ton of decent to good participants.
For example, 65 points are given for a mix of personal projects and open source contributions. Which is great if your one and only interest is in tech, and you don't have a family, dependents or a second/third job. If you have any of those other things, well the odds seem like they're incredibly stacked against you.
And it makes me wonder how many of these systems are stacked in favour of wealthy people with a near special interest level of obsession with tech and no worries outside of going to college/working a single job in their industry of choice.
by CM30 - I agree with you, the whole AI thing is a distraction, even with perfect AI the whole methodology is wrong.by gcampos
- In my experience personal projects are the greatest indicator of IC competence, especially for young people. You may not like it, but turns out that when you do a thing in your free time because you like it, you get better at the thing than the people that only do it because they have to.by fireant
- Yeah, the over valuing personal/open source projects is worrying and kind of sucks. I can use myself as an example, I don't do personal projects really, outside of work. My only actual programming work experience is during work hours for my employer. My hobbies are tech-adjacent (3D printing, some hardware/arduino stuff, photography) but they aren't "make a bunch of projects and put them on github" type hobbies. I'm certainly not going to make some BS fake CRUD or SaaS apps just to show off for potential employers, what a waste of time.
I, intentionally, have zero online presence in that regard. You won't find any public repos on my github, I don't blog, etc. Its even infected the ops/syadmin side of the field (where I work), and that's somehow even worse. Like of course I don't have a bunch of environment specific scripts on my GH, why would I? It's irrelevant to anyone that doesn't work in my department at my current employer.
by thewebguyd - > I fail 65% of the time. Same exact resume, different luck.
As someone who’s run hiring pipelines for technical roles in the past few years, that’s actually a fantastic number. I objectively hate saying that, but it’s true.
35% chance of elevating a technical individual to the next stage with no effort? I’ve seen as many as 100+ applicants an hour even when including a domain specific screener question. That’s 35 “screened” applicants in an hour. Were valid candidates screened out? Yes. Does you still have a candidate pool 35x larger than you need? Unfortunately, also yes.
The volume of applicants is SO HIGH such that your chances of getting moved to the next stage are actually markedly worse if AI isn’t involved. If you didn’t apply immediately (using an AI bot) there’s 50+ people ahead of you, and an exhausted technical leader if they ever make it to your resume.
Referral bonuses exist for a reason.
- there have got to be better ways to optimize pipelines. maybe set a limit on number of applications for a role based on the number you/your team can reliably go through them. if more are needed then open the role for another wave of applications.by spike021
- I wonder if you could solve this for programming specifically as follows:
1. Give them some easy leetcode questions. Nothing that a competent programmer would have any problem with.
2. If they pass, ask for a deposit of like $20. Shouldn't be an issue for people who are actually serious.
3. Do more simple leetcode questions but this time on zoom so you can tell if they are using AI. If they pass that they get the deposit back.
(Yeah I know there are real-time interview cheat AI programs but based on what I've seen on demos of them it's super obvious when they're being used.)
Probably not practical but just a thought!
by IshKebab - Sounds like you're pretty bad at hiring pipelines.by mrhottakes
- One of the first things you do when hiring is to set a period and randomize order of resume when reviewing because early application is not a strong signal.by wodenokoto
- If you have no requirements for accuracy, you can just advance 35% of applicants at random.
If the first 50 people who apply are all bots, why are you reading resumes in order of submission?
- So the logical solution is for candidates to submit multiple applications with slight variations to their contact info, "John Schmidt", "John J. Schmidt", "John J. J. Schmidt", "John Jacob J. Schmidt", "J. J. Jingleheimer Schmidt", etc.
- Is it? Or is it a 65% chance of a resume getting ignored before a single human sees it, reducing your pipeline's likelihood of catching qualified candidates by the same?
Gates that reduce resume flow-through are only useful if their reduction is correlated with quality. Otherwise they're just dragging out your hiring process or unnecessarily causing you to ultimately lower your hiring bars.
by kyralis - In that case, I have a pre-screening system to sell you. Through state of the art technology, it only lets through the best* 1% of applications.
*According to our proprietary, undisclosed, non-deterministic metric, which may or may not be Math.random
by PufPufPuf - At this point we might as well adopt that joke where you blindly throw away half the resumes because you don't want to hire unlucky people.by ryukoposting
- May be LLM resume screening is a symptom of a bigger problem - with tens of candidates per vacancy employers can screen resume badly and even throw half of the resumes away and still hire someone qualified.by citrin_ru