We, the people, love transparency, numbers, and analyzing bootstrapped business models.

What is your current project? Share your wins, losses, and tech stack. Share monthly recurring revenue (MRR) if you feel like.

Comments URL: https://news.ycombinator.com/item?id=49922837

Points: 1

# Comments: 2

It builds a scorecard from job description and mathematically matches candidates against it on every interview step, so that you know candidate fitness at all times.

My honest opinion, take it with the pinch of salt:

The website is oversaturated with text and is lacking some spaces (air) and visuals.

Why not monetising it? Not from the job seekers but from employer side. You could check what the offering from big projects is. Besides, you do have pricing for the API, what about it?

I also remember there were big product doubts originally as it was stepping into the field dominated by hugely powerful players.

We, the people, love transparency, numbers, and analyzing bootstrapped business models.

What is your current project? Share your wins, losses, and tech stack. Share monthly recurring revenue (MRR) if you feel like.

Comments URL: https://news.ycombinator.com/item?id=49590656

Points: 30

# Comments: 44

And good luck on the journey.

I did the first Show HN a few days ago (https://news.ycombinator.com/item?id=49083987) but it was sadly left without attention.

Cannot leave unattained the fact ppl openly share metrics in various “those making X$/month” threads.

We, the people, love transparency, numbers, and analyzing bootstrapped businesses.

What is your current (solo) project, and what is your monthly recurring revenue? Share your wins, losses, and tech stack.

Comments URL: https://news.ycombinator.com/item?id=49181766

Points: 13

# Comments: 9

I did the first Show HN a few days ago (https://news.ycombinator.com/item?id=49083987) but it was sadly left without attention.

My partner and I got tired of nontransparent hiring processes and "AI-native" HR software that just wrap an LLM around CVs (or even simply claims doing so) so we built Hiring Method to do the opposite.

It converts CVs and job requirements into structured data, then uses a transparent math engine to score the match. Instead of trusting a black box you get a clear, audit-ready scorecard that shows exactly why a candidate is a good fit. We are currently building a sourcing feature to help find those candidates in the first place.

We have been working on this for 1.5 years, and after a couple of idea pivots we finally pushed it to prod a month ago.

A quick note: signups are currently put behind an onboarding call as it's a B2B tool. I know Show HN prefers immediate open access so I hope it's still okay to share our project here!

Would love your feedback on the technical approach.

Comments URL: https://news.ycombinator.com/item?id=49083987

Points: 5

# Comments: 0

When an HR is using Hiring Method, they are getting a fitness score for all applicants.

In case a backend engineer is seeking frontend roles – yes, the fitness will be low – but it will neither be zero nor will anyone be rejected anyhow automatically. HR will have an option to compare applicants visually and in detailed mode at all times.

I am building Hiring Method to augment people, not to remove them from decision making process.

I see a lot of new (and, to be frank, a lot of mature ones) HR tools are just wrapping Chatgpt around resumes (almost like "OK, now match this resume against this job posting and tell me if applicant fits"), which introduces a massive bias/inference problem.

I decided to build the exact opposite – a deterministic, math-driven fitness engine. It extracts structured scorecards from both CVs and job requirements and mathematically matches them, so you can actually review the exact reasoning behind why a candidate scored a, say, 85%. This fitness value is specified at every interview step – as applicant goes through an interview process their scorecard is updated at all steps.

If anyone here builds in the HR space, I’d love your feedback.