Comment by genekrapivin
11 days ago
I'm working on Hiring Method (https://hiring-method.com). After ~2 years of development and two exhausting pivots, v1 is finally live.
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.
If tools like this are popular then it sounds like it'll be impossible to switch domains.
Let me disagree and explain myself.
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.
Im sure you have the best intentions. I already struggle with being pigeonholed into roles. The line about using AI wrappers to determine a fit stuck out to me.
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Yes, and what's scary is that I can easily imagine HR departments loving these tools and using them at scale.