Hacker News Reader

Comment by genekrapivin | Hacker News Reader

I'm working on Hiring Method (https://hiring-method.com).

After 1.5 years of development and two exhausting pivots, I’m incredibly happy to finally have our v1 live!

While most of the HR tech is rushing to use black-box AI, I built the exact opposite. It's a transparent, math-driven fitness engine. It extracts objective data from CVs and calculates how well applicants match requirements, letting you see the reasoning behind why someone scored an X%.

If anyone here builds in the HR space or regularly hires engineers, I would absolutely love your feedback or a roast of the landing page.

PS This is a project of immense importance for me, I've been working on for past ~2 years, I'd appreciate to know why this comment is flagged.

View on HN

I'm curious how you're addressing any legal aspects about this:

> No black-box AI. Every candidate gets a detailed match receipt explaining exactly why they scored an 85%, complete with contextual evidence from their CV.

HR teams like to play dead when they actually have a file with detailed feedback on a candidate. Yet, they choose to keep that to themselves out of baseless legal fear. I wonder how that works out when somebody proves a company's filter consistently proves a specific bias gets rejected systematically.

and

> Automated assignment validation

which is particularly troubling for devs: companies scaling assignments as first screen. How do you get around "AI evaluating AI" loops especially about assignments ?

Recruiters aren’t afraid to give feedback, and there are often no legal grounds for withholding it in Europe (I’m not counting FAANG companies or certain sectors like fintech). Usually, they simply don’t have the time (and enough motivation) to provide individual feedback to every applicant. This leads to ghosting and transitively to the brand reputational damage. Hiring Method allows you to send feedback to almost everyone!

In our software, the candidate being assessed does not know all the assessment criteria. Furthermore, this assessment is merely a starting point for discussion during the technical round. I need to update the description of this feature.

Thanks for the valid points!

For EU residents at least the HR data should be accessible via subject access request (though enforcement is poor)

We are GDPR compliant. We are striving for EU AI Act compliance as well (once the final version is accepted).

How do I object to automated decision making?

Hiring Method helps recruiters take decisions backed by numbers and transparent analysis, we do not take human out of the loop.

For a while a "cv2vec" lingered in my mind, but abandoned it due to the sheer volume of PII I'd need.

How do you deal with CVs like mine that refuse to list every <fancy keyword> I'm familiar with because it's pointless clutter? In that sense, and IME, the companies that only hire perfect fits are, more often than not, toxic.

Hiring Method is an auxiliary tool that does not take any hiring decision. The vector it builds has few dozen parameters, with hard skills (eg plain old technology list) constituting a mere fraction. In this way you do not have to have all fancy buzzwords – the software also checks for neighboring stacks and transferrability level, among other fitness criteria.

Everyone is building scoring with AI and everyone is providing clues like: These are the 5 things we will score each candidate on, and here is how the candidates scored against each item. And here is the total score because of it.

P.S I work in an hrtech company.

As someone who worked on HR Tech in 2024-2025, I think you're really solving a problem here. Cat is out of the bag already it's not like HR can go back to the pre-AI world ... I'm also puzzled by the flags. Congrats on your project :)

I like the landing page.

Any usefull tips how to get through the initial filters? :D

I sort of wish employers would use this and also the applicants could see the metric. How much time would be saved if neither side bothered with bad fits?

fewer than 2–3% of the 300–500 applicants for a software engineer role progress to the next stage after CV screening (to put it very broadly). at this stage alone, Hiring Method saves between a few hours and several days per role, whilst maintaining impartiality and processing 100% of applicants

Interesting, but given an easy access to AI, employers would get hundreds if not thousands of wonderfully written, properly suited CV. And everyone will have cool Github portfolio (with AI-generated projects). Good luck finding the right person in such environment.

So I am wondering what kind of tooling would be able to somehow spot the right people among flood of AI slops.

flags or downvotes probably come from people being skeptical about automated CV evaluation. in europe this is also legally questionable.

also matching requirements should be secondary to experience. someone who has done a few react websites will not be as qualified for your react job as someone that has done 10 years of angular and vue and can learn react in a short time.

Reply on news.ycombinator.com