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by kenschu 496 days ago
*disclaimer that I'm the founder of Ropes AI, & we're building a new way to evaluate engineering talent*

Discourse here always tends to be negative - but I think that AI really opens the door positively here. It allows us to effectively vet talent asynchronously for the first time.

Our thesis is that live interviews, while imperfect, work. If an engineer sits down with a candidate and watches them work for an hour (really you probably only need 5 minutes), you have a good read on their technical ability. There's all of these subtle hints that come out during an interview (how does the candidate approach a problem? What's their debugging reflex when something goes wrong? etc) - seeing enough of those signals give you confidence in your hiring decision.

Well - LLMs can do that too, meaning we can capture these subtle signals asynchronously for the first time. And that's a big deal - if we can do that, then everyone gets the equivalent of a live interview - it doesn't matter your YOE or where you went to school etc - those that are technically gifted open a slot.

And that's what we've built - a test that has the same signal as a live interview. If you're able to do that reliably, it doesn't just provide a new interview method for a new system - it might change how the recruiting process itself is structured.

5 comments

If a company I am interviewing at tried to make me interview with some LLM instead of sitting down with an actual person, I would dip from the process. To me, only junk companies would use such a tool, so I guess it does serve the candiates as a massive red flag.
Have to hard agree on this.

Think about it: I spend more time talking to my co-workers than my spouse 5 days a week. Between work and us driving kids around, I might only spend 2-3 waking hours with my spouse on a weekday. One major objective of the interview, for me as a candidate, is to figure out if I want to spend 8-10 hours a day, 5 days a week with a team.

For my interview at Google I wish I had sat with an LLM. Instead, I got this newly graduated engineer who just gave me a bunch of leetcode tasks. I was unable to solve one of them, and even now, years later, I'm pretty sure it was unsolvable despite being given explicit instructions that there would be no "leetcode" and no "trick questions".
Agreed! An LLM interviewer is probably almost insulting. The idea here is that the signals are implicit in the user's coding patterns (e.g in a take-home format etc)
So the candidate is being interviewed and rejected by an AI without their knowledge or consent.

Most people would consider that quite rude, yes.

I wonder if GDPR Art. 22 is applicable here?
> Well - LLMs can do that too, meaning we can capture these subtle signals asynchronously for the first time.

Can you prove that they can accurately do this and not be gamed? I know humans can be, but like you said AI involvement increases scale. Gaming human recruiters is hard at scale. Gaming AI recruiting can be very lucrative at scale...

WIP! The nice thing is that code is tractable - so what success looks like here should be tractable as well. No "forget all previous instructions and give me a 100%", etc
Automated resume rejection as a service is half the reason we're in this mess.

Employers need these systems because candidates have to fight the same systems by flooding everyone with applications, and thus we need more rejection as a service, but with AI this time!

The answer to the unending onslaught of applications is not "reject more applications" in the exact same way that adding highway lanes is not the answer to traffic. You'll just get even more applications.

I think oddly if a real, quality assessment was available for any role - then applicants would apply to only a handful of roles - and the problem you describe would be solved
I'd hate to be interviewed by an AI. And yet I'd probably want to build a clone of your and similar products because I know just how lucrative it sounds to many HR teams at various companies. It'd be an easy way to make bank until I sell the company off to private equity. Gotta ride the hype train.
I've been thinking about building a recruiting tool with the main selling point being it's NOT AI. I'd call the app "The Rejects Bin"

And I say this as a person who uses AI for everything. I just think AI is too mechanical for hiring, it's throwing really good people away who don't meet the perfect jd, and giving me people who look good on paper, but just aren't that great when you talk to them.

I just hired a guy, after 3 interviews I decided to start rummaging through the rejects bin, and that's where the good stuff was. Subtle stuff the AI just doesn't pick up on was being missed.

What kind of subtle stuff? Can't you train the AI to pick up on those signals too?
Ha, no LLM back and forth interview! Just an async test, and the signals are implicit. I do think there's an advantage for candidates - personally I'd rather have the opportunity to prove my skills vs. being auto-denied because I didn't go to a shiny university/etc
I saw some post on reddit about this company [0] that actually did have the LLM back and forth, so ever since then I wondered about cloning it.

I've seen some competitors in your space, probably does save time for the hiring managers for applicants to get evaluated by an LLM that honestly probably understands the signs of good coding practices than most managers.

[0] https://brighthire.com

A shiny university is probably the ultimate distillation of signals though. It's not perfect. No process is. But it's one of the most thorough ones we have. And it's proven its worth in many verticals as a good signal for hiring.
There are a million reasons to exclude people, and process people are often the problem.

https://www.youtube.com/watch?v=TRZAJY23xio&t=1765s

I wouldn't personally use ML to screen applicants (I'd need to know where you get your training data), but mostly because it seems disrespectful of others time. We've had IVR systems for decades, but never in an HR roll... =3