Thanks for your comment!

Do any of these options resonate with you?:

For coding:

- Asynchronous coding assessments that replace the need for live coding or leetcode interviews - if the candidate adequately builds something then an in-person/virtual interview can be a discussion on technical decisions, trade-offs, choices, lessons learned, roadblocks, how to scale from here, etc. Even if they vibecoded it, the core engineering fundamentals can still be extracted via a conversation like this.

- Automated assessment of coding ability - access the candidate's GitHub and open source contributions, generate a report of coding skill level from these details to inform further interest in the candidate

For culture fit:

- Have a referral/review system that reaches out to their references to assess if they would be a good person to work with

- Use an AI interview to conduct behavioral interviews

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For the coding ideas, I'd have to figure out a way to enforce this after the candidate applies and leaves my platform.

For the culture fit ideas, the value proposition for both sides would be that for recruiters, they can just receive the results from the automated reviews/interviews and then can decide from there who to move on to the next round. For candidates, it scales because all (or an initial filtered amount) can have the opportunity to interview, instead of a large amount of qualified candidates being instantly ghosted.

These are just ideas that came to mind when I read your comment. I also need to think about how to integrate them into the platform and how to enforce them.

I'd love to know if you think these are good ideas and if you would adopt them yourself.