Get Inside the Mind of your Team’s Best Interviewer, with Vercel’s Viet Nguyen [from 10X Recruiting]
episode
“HR Heretics” | How CPOs, CHROs, Founders, and Boards Build High Performing Companies
32 min
2 speakers
8 chapters
transcribed 16 days ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the core idea behind using AI to analyze top interviewers’ transcripts?
Today we're dropping a killer episode that Nolan recorded with Viet Wen, head of global recruiting operations at Vercell for his 10X recruiting podcast from MetaView. Please enjoy.
What's up everybody? Welcome back to another episode of Ten X Recruiting brought to you by MetaView. We have my boy Sile. Sil, you're looking good. The hair's flowing, baby. How you doing? I'm
good, man. I got a new barber actually. I got a new barber. So I'm glad I'm glad you glad you mentioned. Yeah, you look like a model. You look like a I don't know about that. This is uh only only for the people who listen without the video are gonna believe you. I think uh it's called having a voice
for radio.
Uh
So anyway, on today's episode, we had Viet Wen on, who leads recruiting operations at Brussel. Viet and I go way back. This guy is an absolute legend. Um, I tried to hire him at Doordash. He tells a story in the pod that I like didn't I didn't I alright I rejected him and I was like, I don't think that's actually true. But anyways, what were your takeaways from the episode of Viet?
I was pumped by this episode because I feel like I speak a lot about the importance of unstructured data in the world in the world of AI. And I feel like finally there was someone who was sort of like, although he didn't use the phrase, he was basically talking about how he throws a ton of unstructured data at ChatGPT to help him run a more effective recruiting operation, which is just sick. So you'll see here the specific example he talks about, but uh I think it's just it it's it's such a clarifier for a lot of folks, I'm sure. of what we mean when we say, Hey, chuck the unstructured data at the LLM, work with it to make sense of it. But like, you know, don't don't obsess so much about refining that context.
Just get get it get it in the mix. So yeah, you'll you'll see in the example in a second, but
I had a couple. The first one is progress, not perfection. So everybody we talk to, Syle, this is where you and I like will hate slack each other about getting guests on the pod. It's like everybody in recruiting like wants to have this like perfect product that's like fully finished and like ready to go. And the first example Viet uses, uses a couple on the pod, is like it took him three hours. You know, it spits out this like deck, and it's basically just kind of like analyzing this guy, Gaspar, who has these like amazing abilities to identify top talent. And like, what is exactly Gaspar doing in the interview process? Well, like, let's just throw the transcripts into Chat GPT and ask it, and then see what it comes up with, and then use for sell to build a quick deck.
Like, it's not. This whole like, oh, I went away and I had a tiger team for six months and these are our learnings. Like in the era of AI, I really think it's just like these like little experiments. And Viet does a great job of describing that. The second one was create leverage where possible. So his automated back channel example, I can't tell you how many times at every company I've ever worked at where people are like, Well, is there anyone inside the company who knows this person?
How does Viet’s three‑hour experiment reveal the “Gaspar Effect” in interviewing?
And instead of like, you know, trying to like, you know, basically every single time looking through the employee database, which I have certainly done, and I'm sure many people listening to this pod have done. That's the moment where it's like, I'm doing this. thing a ton of times, where can I use technology to create leverage? And how can I do this without a human in the loop? Again, even if this is going back to the first insight, which is like it doesn't have to solve all of the problems, but if it solves even 50% of the problems or at least makes progress on them, then it's something worth doing.
When people use that phrase in general, like progress over perfection, it's often not like, hey, choose which one is it? Do you want to make progress or do you want perfection? Because if you just have those two options and obviously okay, I'll choose perfection then. Really what you're saying is in a world where you're not going to do it at all unless it's perfect, it's better to make progress.
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Chapters
8 chapters
1
What is the core idea behind using AI to analyze top interviewers’ transcripts?
0:03–3:00
2
How does Viet’s three‑hour experiment reveal the “Gaspar Effect” in interviewing?
3:00–7:28
3
What specific behaviors make a great interviewer great according to the AI analysis?
7:28–13:12
4
How did the automated back‑channel reference tool create leverage in recruiting?
13:12–19:39
5
What is the RAG database and how does it know every employee’s history?
19:39–24:16
6
Why is it okay when AI says “No connections found” and how is that handled?
24:16–28:37
7
How can interview debriefs be automated for real‑time summaries?
28:37–31:32
8
Where can listeners find Viet Nguyen and follow his ongoing projects?
31:32–32:47
Speakers
2 identifiedMore from “HR Heretics” | How CPOs, CHROs, Founders, and Boards Build High Performing Companies
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