00:18:14 · Guillaume Moubeche, Daniel Chait
[00:18:14] S1: And when you look at it, like, do you want basically to do a one plus one equals three, like your revenues, their revenue plus additional cross sell that you could do to your user base, or how exactly do you stress test it? [00:18:28] S0: I think that's one way that those deals happen. I think that's not always it, and I don't think that's been the majority of the the things we've done. Because we've typically done earlier stage acquisitions where... Like, if you take the acquisition we did of Ezra AI Labs, right, to bring our voice AI product to market, that was a product that had proven itself with some really demanding customers in a very cutting edge technical space with lots of know how involved. [00:18:55] S1: Can you explain maybe what the product does?
00:18:58 · Daniel Chait
[00:18:58] S0: Yeah. So it's a Voice AI interviewer. So, basically, the idea is we can automatically deliver a really relevant, very user friendly interview at the top of the funnel. So, like, as part of the job application, finding out stuff about you as a candidate is simply not on your... Resumes are are getting increasingly, like, it's just AI slop. Like, it's hard to know what's... What the person can really do. And as a result, candidates are left out of the process. Candidates are really struggling right now, which we should talk about that too. The job market's really busted in a bunch of ways because of AI. And if you talk to job seekers, which we do a lot of, what you hear is they're just flinging the resumes into the black hole. They're never hearing back. You apply to a job. There's a thousand people in line in front of you. You're never gonna get seen. And so this is a way to provide everyone the opportunity to have a shot, to take the first step in the process, have a conversation, prove your skills out, and get seen on that basis versus what keywords are on your resume. So that was a theory, and we had conviction that the world was headed in that direction. But it wasn't about, oh, you have this much revenue, and we think we can get that much revenue. It was more like, this is a fundamental enabling technology to a whole new way of working, to reimagining hiring in the era of AI in some very different ways. And so it's less about, yeah, let's get our bean counters, you know, to look at a spreadsheet and and do some multiplication, and more about, this is a bet we're making on the future of hiring and the future of software.
00:20:22 · Guillaume Moubeche
[00:20:22] S1: And so far, like, how exactly have you seen the market evolved? Because I I think you're saying that it's kind of like getting screwed on on both sides for the candidates, but also from the recruiter? Can you maybe expand?
00:20:36 · Daniel Chait
[00:20:36] S0: Yeah. So, you know, we've described it as the AI doom loop, which is the idea that, you know, in the sort of last few years, you've had everyone on both sides of hiring using tons of AI, but they haven't been given the tools to make things better. So candidates facing a downward job market, a tough job market, have been using AI to apply to more and more jobs. And secondly, to give themselves a shot at each job to customize their content to that job. So if I'm gonna submit a resume to apply for a job as a candidate, I'm now using AI to read the job description, take my resume, and merge my resume to look more like the job description it's looking for, put in all the right keywords, and send it in, which sounds smart, and I don't begrudge individual candidates doing that. But when everybody does that, what ends up happening is everybody's pipeline fills up with more and more applications because they're all getting sent out automatically, and they all start looking more and more of the same. And so I've heard it described as you're trying to find a needle in a stack of other needles. And so for a company, what they end up doing is now they open up a job, and they'll get many hundreds or even thousands of applications for that job, and they all start to look the same. And so they're stuck with this problem of the signal. Like, I don't know where to start. I'm not gonna read 2,000 resumes. I'm not gonna talk to 2,000 people. What do I do? And so they also turn to AI and say, Build me an AI filter. ChatGPT, tell me which 25 people I'm gonna call. ChatGPT will certainly happily tell you 25 people to call, but is that the right 25 people? Is it introducing or reinforcing existing biases? Is it actually looking beyond the resume and finding out anything important about the person? So the answer is no. And so that then deprives the company of needed talent. The other nine seventy five people that are never getting a look, probably the right one's in there, and it's making the job market harder for those applicants, so they respond by sending out more resumes, and the cycle continues. So that's sort of the place we've been in. And if you're in the job market as an applicant or as a hiring manager, you certainly recognize that it's not easy right now. It feels bad.
00:22:43 · Daniel Chait, Guillaume Moubeche
And so what we've done is tackle that problem head on and say, This is not a sustainable solution. AI has so far made things worse, not better. We need to fix this. And so voice AI is a piece of the puzzle, but basically what we said is, if we can find ways for candidates to give better information about what they're good at and what they want, that'll help. That'll help those candidates stand out and get a fair shot at a job. It'll help the companies identify the right talent to focus on. And so we're looking for all kinds of ways to surface better signal, more trustworthy signal to help fix this problem. And sort of my hope is that we can play a meaningful role in sort of unwinding the AI doom loop and helping make jobs and hiring better. [00:23:24] S1: And down the line, have you already like sort of becoming some sort of marketplace of talent? Because if you start like interviewing, you know, like with Voice AI or any AI setup, like thousands or hundreds of thousands or millions of candidates, you eventually like gather a lot of data about specific people. And let's say that they apply for company A, you ask them like a set of questions, etcetera, but you realize like they're not gonna be a fit, however, they might fit for a company like C, D, or E. Are you gonna push that company, that profile or not? Like, is that something you've considered or or not I
00:24:06 · Daniel Chait
[00:24:06] S0: think you're onto something. I would think about it slightly differently. Like, first of all, just marketplace to me is kinda like, I don't Yeah. Yeah. Yeah. Is like kind of where you're selling, like, meat and toasters. Like, I don't think of people. Like, these are humans. And, like, behind every number at Greenhouse, there's a human being trying to get a job, and I think a lot about that. And so... But I think what you're saying that I do agree with is the hiring process has some fundamental assumptions built into it based on the way we've always done things that I think we can reimagine. I think we can sort of question, why do we have resumes and job applications? And these things are like, you know, most... Like, resumes are still on a white rectangle this shape because we used to print them out on paper and put them in envelopes. Like, we don't do that anymore. And so why do we have these limitations, and how can we rethink it? And so if you step back and you're like, oh, this process could work so much better, I think one of the ways that you're talking about that I very much agree with is candidates are putting in a ton of effort into trying to get a job. They're answering a bunch of questions. They're approving their skills. They're choosing which companies they're interested in and which ones they're not. They're doing all this stuff. Can't we make all that more useful to more candidates, to more companies? Can we make the process give better ways to stand out and showcase who you are? Better ways to find among the billions of online profiles, who's the set of people I should be talking to if I'm hiring someone? I think there are some real basic assumptions in how that's always worked that we don't have to be so caught up in anymore.