# Scalable interviews help find rare high-quality experts

Markdown copy of https://realalpha.app/s/scalable-interviews-help-find-rare-high-quality-experts/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Brendan Foody](https://realalpha.app/builders/brendan-foody/) · Brendan Foody is co-founder and CEO of Mercor. · Co-founded Mercor, a labor marketplace supplying AI companies with expert data, paying tens of millions weekly.
- Host: [Molly O'Shea](https://realalpha.app/people/molly-oshea/) · Founder, Sourcery · Ex-Upfront Ventures investor; has interviewed Alex Karp and Palmer Luckey.
- Show: Sourcery
- Episode: [Mercor Raises $750M at $20B Valuation | CEO Brendan Foody](https://realalpha.app/v/xzA6lYBzmzQ/), Nov 10, 2026
- Moment: 12:09 to 15:32 of the episode (3 min), playing on https://realalpha.app/s/scalable-interviews-help-find-rare-high-quality-experts/; the episode from there: https://realalpha.app/v/xzA6lYBzmzQ/?t=729

## Quote

> “the realization we had as we scaled that up is that so much of the challenges in labor matching just come down to **scalable data collection**.”
> — [Brendan Foody](https://realalpha.app/builders/brendan-foody/) at [13:14](https://realalpha.app/v/xzA6lYBzmzQ/?t=794) · Sourcery

## Takeaways

1. Mercor built its first AI interviewer in 2023.
2. Referrals account for 70% of expert sign-ups.
3. More than seven million interviews helped scale talent evaluation.

## About this segment

Brendan Foody explains how Mercor built an AI interviewer and uses referrals, interviews, and other signals to assess candidates. The approach helps find strong talent even in low-density labor markets.

From “Mercor Raises $750M at $20B Valuation | CEO Brendan Foody”, Nov 10, 2026. [Watch the full episode](https://realalpha.app/v/xzA6lYBzmzQ/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[12:16](https://realalpha.app/v/xzA6lYBzmzQ/?t=736) Built with partners like Harvey and Cognition, see where the Frontier actually stands at merkur.com slash APEX. I have to ask, how do you find these experts and how do you evaluate them? So 70% of them come in through referrals. There's also other channels that we use, but that's the one we're most focused on because we find that people that are referred tend to be the highest quality. And then evaluating them is a really cool process.

[12:42](https://realalpha.app/v/xzA6lYBzmzQ/?t=762) And this was actually one of our first large breakthroughs because we built the first AI interviewer when Adarsh Suri and I were in college in April of 2023, right after ChatGPT came out. The first one had like seven or eight second latency. It would make an API call to GPT-4 and do some preprocessing based on the resume, make an API call, say the question, ask people, and then evaluate the interviews according to a rubric or a set of criteria to see how well people do.

[13:20](https://realalpha.app/v/xzA6lYBzmzQ/?t=800) And the realization we had as we scaled that up is that so much of the challenges in labor matching just come down to scalable data collection. And an analog for that is that if you're hiring Stanford AI PhDs, you can probably meet with five people and like one of them is going to be pretty good. versus if you're hiring software engineers from a remote place in India, you need to meet with sometimes hundreds or a thousand people to find like the really world-class engineers.

[13:52](https://realalpha.app/v/xzA6lYBzmzQ/?t=832) But they are there and many of them are on our team. And so as we were able to scale up the amount of interviews that we did to solve these differences in talent density, that was really one of the large drivers of how do we get spectacular people? and also analyzing all the different filters people might not be considering of what are who referred them of what is their what are their personal projects that they do on github on figma or whatever it is all of these things getting pulled into context then analyze so we now do over five or we do we've done over seven million interviews and it's been pretty crazy to see things scale up as we um have now created the fastest growing job category in history it's crazy yeah literally so fast it's very surreal yeah i mean i for as a frame of reference

[14:51](https://realalpha.app/v/xzA6lYBzmzQ/?t=891) so now if we're paying out call five million dollars a day as of two years ago 24 months ago we were paying out a million dollars a year so it's like um i i think that many people at the company don't fully realize just that like that that's never happened before um and that it's this very special opportunity where we found this giant market before anyone else and we've become the category leaders and how we um create this really important new category yeah that's amazing