Hiring in the AI era: Greenhouse CEO Daniel Chait

Daniel Chait is the co-founder and CEO of Greenhouse, the hiring platform behind thousands of companies. Before Greenhouse, he co-founded Lab49, a technology consultancy for Wall Street. He's also the author of Talent Makers. In this episode of Summation, Daniel and Auren discuss: The AI doom loopWhy "tell me about a time when" beats "what are your weaknesses," Why HR quality depends on the CEO, and what Netflix got rightWhy "never quit" is bad founder adviceYou can find Auren Hoffman on...

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  It's that I apply to a job and I'm 2,000th in line. I'm never even getting looked at. You know, because of all the spam, they don't want to just turn over all their judgment to chat GPT and say, I throw my hands up, tell me who I should look at. I think there's a venture capital industry that's highly incentivized to tell you to keep going no matter what. And I think as a founder, you got to decide, is your time better spent chasing this one or stop, pause, regroup and try something else?

• 0:26Auren Hoffman?

  Hello, fellow data nerds. My guest today is Daniel Che. Daniel is the co-founder and CEO of Greenhouse. Before Greenhouse, he co-founded Lab49, a technology consultancy for Wall Street. Daniel, welcome to Summation.

• 0:40Speaker 00

  Thank you. I'm excited to be here. It's looking forward to a great conversation.

• 0:43Auren Hoffman?

  Now, you coined the phrase, the AI doom loop. And you know, candidates now spam applications with AI recruiters, filter the AI, all sides potentially lose. Like, how do we solve this and get out of the doom loop?

• 0:58Speaker 00

  I mean, that's the question of the hour, and I think maybe it'll help to define a little bit of what we mean and kind of what's going on, right? So, look, I think the problem is not AI. Let's just start there. I'm an AI optimist. I think there's a lot we can talk about the power of AI. But but also there are risks and downsides to using AI, and I think we're seeing that in the job market today. So, you know, anybody that's in the job market or that has, you know, people that they know that are trying to get jobs. You know how challenging it is out there right now. It can feel hopeless. It can feel like the system isn't really made to work for you. And and that feeling is backed up by our data. We see a massive increase in application volume, largely driven by automation, but also changes in the in the, you know, hiring conditions themselves.

• 1:44Speaker 00

  But candidates are basically using AI to try to help themselves, to try to figure this system out that doesn't feel like it's really working for them by sending out as many job applications as they possibly can in the hopes to try to get someone to respond to them. And and generally what they see is the more applications that candidates are sending out, the, you know, the worse the problem is getting. And then on on the company side, as they're faced with this real increase in volume that beyond sustainable amounts. I just saw a post on LinkedIn the other day that said, in an attempt to help the job seeker, thanks for your application. We received 2,030 applicants for this role. We're going through them and we'll get back to you when we have something to say.

• 2:27Speaker 00

  Like, no one's going to read and give due attention to 2,000 applicants for for one job. It's just not physically possible. And so what companies have done is use AI to kind of cram that back down into a into a box that they can handle and say, hey, chat GPT. Like, tell me the 25 or 30, you know, resumes I should look at out of this enormous pile, leaving the vast majority of applicants unread. And and so because that limits who gets looked at, it makes it harder to get seen. And then response job seekers understandably send out even more applications and the cycle has perpetuated. So that's what we mean when we talk about the AI doom loop. It's it's people using this sort of first generation of AI tools they had available to them to solve their own problem.

• 3:12Speaker 00

  But when they do that, it makes the overall system worse, not better. And so that's sort of the position that we find ourselves in here in in 2026.

• 3:20Auren Hoffman?

  And eventually, like, I mean, I could go all the way down where it's just spam all the way down. Or we can get to a a better world where the candidates are only having to apply for the job to really fit them. And and people are really going to talk about the ones that, so where do we, how do we go from here?

• 3:40Speaker 00

  Yeah, that's right. And look, I think, you know, the the problem isn't that getting a job is competitive. I think job seekers expect and understand that for, you know, a well-paying prestigious job that offers a lot, that there's going to be interested applicants. And you have to be at the top of your game and work hard to get those jobs. I think what they're feeling is that's not the case right now, that there's no way that they can sort of spend more time, be better and get a better chance at a job. It just feels like hopeless. And for companies, it's kind of the the flip side. It's like, you know, for years, for decades, companies wanted to get in front of top talent for the jobs that they were that they had open. And now all they have is like an inundation of of of interest and applicants to every job.

• 4:23Speaker 00

  It doesn't make it any easier to find in that ever larger haystack like the needle that they're that they're looking for. And so, yes, I agree with you that the the goal here should be that it should make sense to try to get a job. It should feel like when you go to get a job, that you're being given a reasonable chance to compete and win for jobs that you ought to, you know, be qualified for. That you should hear back in a reasonable timeframe, that you should be judged sort of fairly and accurately according to your capabilities. And those are the things that candidates really want to see happen to get faith back in in the job market. And it turns out that those are the very same things that companies want to be doing in order to find the talent that they have.

• 5:07Speaker 00

  They don't want to just turn over all their judgment to chat GPT and say, I throw my hands up, tell me who I should look at. They want to know that they're actually getting a look at the right at the right talent, at the best people for their jobs. And so the way out of this, ultimately, to me, has to come from a place of solving this market failure problem for both sides. Of making it more relevant to each job seeker. The skills and capabilities that they bring to the table as to what job opportunities they get and make it easier for companies to look through all the noise, look through all the scams and fakes and get to the real job applicants that very much want to work at their companies and hire great people.

• 5:51Speaker 00

  So that's kind of where it's where we're trying to bring it.

• 5:54Auren Hoffman?

  Now, in my world, most of the talent is very happy in their jobs. They're not usually actively looking for a job.

• 6:03Auren Hoffman?

  Except maybe at the very highest level, like you just left your CFO job and you're kind of like having a bespoke search or something. But like the average software engineer in my in my world is usually very, very happy. And and they're almost getting like inundated with people asking them to interview. And they have to selectively decide when they want to passively start looking. Like, how does that, how do we make the job experience better for that type of job seeker?

• 6:27Speaker 00

  The job market always goes through ups and downs in different industries and different places, and that's always been the case.

• 6:34Speaker 00

  And historically, you had, you know, software jobs were in, were in were in short supply of talent. And that's been the case for for decades. And so, yeah, for a long time, and you referred in the opening, you know, my my start in this whole field was hiring tech talent on Wall Street 25, 30 years ago. And back then, it was the same issue, you know, it's like, oh, if we could just get in front of that one, you know, that one person we're looking for and get anyone to respond to us. Maybe we could hire an engineer and companies were going to extraordinary lengths, paying, you know, referral bonuses, outsized referral bonuses, hosting events. You know, I mean, I used to throw pizza parties for programming, you know, jams, just to get people to show up and sort of get their names.

• 7:16Speaker 00

  You know, people did all kinds of things to try to get, you know, engineers, contact information and attention. So you could pry them away from their their well-paid, you know, cushy cushy jobs. And look, that's still going to be the case. And even today, whether it's, you know, AI engineers, whether it's certain areas of like healthcare and, you know, that are in that are in that sort of demand. And on the other hand, what you're also seeing is because the market isn't working well, because it seems so hopeless to try to get a job, that you're seeing people not leave jobs that they otherwise might for a better job, because they don't have a whole lot of faith that doing anything to try to get a job is is going to work.

• 7:54Speaker 00

  And so I do think that unlocking that market, unblocking that market and making the opportunities just more sensible for everyone, you know, will will will will pay a dividend.

• 8:04Auren Hoffman?

  It does seem today, though, that when I, at least when I talk to people across the stack, whether it's at the dentist office or at at a high-tech firm, that the people they are looking for are AI native people. And so it does seem like very, very easy to get in the top 10% of people. When they talk about AI native, it's like you've used an agent or something, right? So it it seems pretty like if you want to really up your game, like just just like showing somehow that you're AI native will. And if you had an agent absolutely help you find a job, that might actually be one of those things you could talk about in your interview.

• 8:48Speaker 00

  Yeah, I think I think there's some truth to that. I think, you know, I was at LinkedIn's Talent Connect Conference. So their big kind of annual customer and market conference last last week here in New York City. And on the main stage, they talked about this. They talked about the idea that in this era of AI, like in previous technology revolutions, like the set of skills that people are looking for, that companies are looking for, is changing really fast. And in fact, they pointed out a stat that the skills companies are looking for are changing about twice as fast as the skills people are saying they have. So if you compare the sort of skills that people are claiming on their LinkedIn profile versus the skills that are listed in in job description openings, you know, they're they're evolving about twice as fast as the available skills.

• 9:31Speaker 00

  And so, yeah, I think if you are looking for a job, clearly companies are looking for people that are going to be skilled in this kind of new AI world. Showcasing that's going to help you. The question is, what what do you showcase? I mean, you can't very well say you have five years' experience with Cloud Code, because it's only been out for a year.

• 9:49Auren Hoffman?

  I think the simple thing is like, show me something you built.

• 9:53Speaker 00

  Right.

• 9:53Auren Hoffman?

  Right? Just show me something you built. Did you build something? What did you build in the last two months? And by the way, like, and you know, and what did you build that like you can show me? So if it's like something super proprietary for your company, like maybe you built something for yourself. Maybe you built something for your family. Maybe you built something that like, I don't know, do an agent for your kid's baseball game or something, right? Just show show me what you did. And if like, if you didn't do anything in the last few months, that's a very good indication you're not AI native.

• 10:18Speaker 00

  So I think that's right. And I think that also points to some of the problems in the market today. Because all that show me, at the end of the day, like, what do most people have to represent themselves in the job market historically? A resume.

• 10:32Auren Hoffman?

  Resume.

• 10:33Speaker 00

  Never been great at showing what you're good at, showing what you've done. It's a listing of your sort of job titles. And famously, the biggest thing on everyone's resume is their name. At the top, and that's been shown to drive a huge amount of bias and unfairness in and of itself. So yeah, I agree with you that if people could do a better job, a more fulsome job of showing what they're capable of and get past just what's on the resume, I think it's better for everyone. I think it's better for job seekers and I think it's better for companies. And so I talked at the outset of like, the, the problem with AI doom loop isn't AI per se, it's the, it's the sort of way that AI has been used. I think that also points to a solution because after all, AI is extremely good at giving

• 11:17Speaker 00

  people new creative ways to showcase what they're capable of. And I think if we think about in this AI era, moving beyond the old ways of doing things, it's not just a resume, it's not just a job ad like it used to be, but it's actually, there's new ideas, new paradigm for, for trying to get a job and try to hire someone. I think it opens up a lot of those possibilities. And wouldn't it be great if everybody had a way to showcase exactly what they're capable of so that job seekers could stand out on their merits and that companies could have a real sense of the skills, you know, available in the market? I think that'd be a huge win.

• 11:54Auren Hoffman?

  Now, we're at Flux Capital, we, you know, we have all these meetings with founders and so obviously like a venture capitalist meeting with a founder. We think almost all of our first meetings within the next six months are going to be agent to agent and then think of like a first date and then the next date, assuming that goes well, will be person to person. I assume the same thing will happen with many job searches as well, right? Where, you know, right now you can't interview all those 2,000 applicants, but you know, maybe in the future you can do agent to agent, do a quick interview, hey, show me what you're doing, whatever the agents decide they're talking about. And then if that goes well, you could then have a second, human to human, and that could get rid of some of the biases, it could get rid of a, you know, maybe I thought I only want

• 12:39Auren Hoffman?

  to interview people from Harvard, but now I'm opening it up a little bit more, et cetera.

• 12:43Speaker 00

  So some of that's already started to happen. So we released a voice AI interviewer earlier this year, and it's based on some cutting edge research around voice AI and how to have real naturalistic, human-like conversations with AI, but also-

• 12:59Auren Hoffman?

  But that's interviewing humans, you're having agent to human.

• 13:02Speaker 00

  Exactly. So it's like saying, it's going down that road, but also based on, you know, this understanding that, you know, of, of the failures in the marketplace. So the idea that, you know, people's just applying today, going into the black hole and what would be better than that. And so what we see is that resume review step is really, that is really a resume black hole step is most people don't get past it. Thousands of people apply, a couple doesn't get an interview, everybody else gets thrown in the trash or not looked at at all. And wouldn't it be great if everybody who applied, no matter what it said on their resume, no matter what their name was or where they went to college, or if they went to college, you could have an interview. And what our customers are seeing is the power of saying, well, I don't just have to deliver 25 human to

• 13:47Speaker 00

  human interviews, I can deliver hundreds or thousands of AI to human interviews, give everybody a chance to show what they're, what they're capable of.

• 13:53Auren Hoffman?

  There probably are some people for sure, you can screen out with a resume, but today we may be screening out 98%, maybe in the, in the future, we're only screening out 20% or something, right? Like obviously like, okay, this in-person job and someone lives in Kazakhstan, like it's going to be hard to actually do this job, right?

• 14:11Speaker 00

  And, and literally you're, I mean, I don't know if that's a real example that you gave, but I literally had a conversation with somebody that owns a pet food manufacturing business in Wisconsin, and they literally were saying that they were getting applicants to work in the pet food factory, making pet food in Wisconsin, who lived in Southeast Asia. And so, yeah, you know, technology can, can do a good job of saying like, this person is not a legit applicant for this role. But that's not really like, when people complain about the job market, that's not the problem they have is that I, I really want to move to Wisconsin and make pet food and no one's letting me. It's that I applied to a job and, and I'm 2,000th in line, I'm never even getting looked at, you know, because of all the spam. So getting rid of the spam, I think helps legitimate job seekers, you

• 14:55Speaker 00

  know, rise, rise to the top. People, but I want to be clear here too, because people are really skeptical about AI in all kinds of contexts, maybe no more so than in hiring. I mean, the EU AI Act has labeled AI as a high risk, as hiring as a high risk activity for AI. I think when you look at the conversation online, people are really skeptical that AI will unfairly, you know, make decisions about who does and doesn't qualify for a job. And so as somebody who's in the business of building hiring tools to help people get jobs, I have to be really conscious and thoughtful of the fact that AI does have risks, does have downsides, can produce unfair outcomes.

• 15:35Auren Hoffman?

  And by the way, humans do too. Like humans also have their own biases and make a lot of stupid mistakes.

• 15:41Speaker 00

  So do humans. And, and that's, that's, that's my starting point is like, I think the current state of, of hiring is so bad and so broken that the possibility to be less bad than that seems like falling off a log, seems like a no-brainer. And actually, if you're a little bit creative, the possibility to make things radically better, to open up entirely new possibilities and to think about entirely new ways of getting a job that are much fairer, that are faster, that feel good, that work for both sides. Like I think that's the real opportunity here.

• 16:14Auren Hoffman?

  To me, if I think of like, what, what, what's the goal of a great recruiting interaction? It's like, okay, for the company, it's finding someone that will have a long-term impact to my company. And then for the candidate, it's finding a place where I can have long-term growth potential and really grow. And then if, if for whatever reason that doesn't happen, ideally, like during that process, like you at least have a good experience, right? If I'm a candidate, I should have a good experience with the company because like I, I should still think favorably, I should still want to refer people to it. If it's a pet food company, I still might want to buy their pet food, right? And know about the products. So there's all these different things that, that happen. Like, how do we get to like that end goal?

• 16:55Speaker 00

  Well, I think what needs to drive that is, first of all, the process itself has to make sense. Like, I know it sounds basic, but when you look at the complaints, like when people are going online and complaining about their job search and how hopeless it feels, what do you, one of the things you hear out of that is like, I, I applied to a job that I'm perfect for. Like I read this job description, it is literally describing me and I applied and I never even heard back.

• 17:24Auren Hoffman?

  I never heard back, yeah. So at least like, why don't, yeah, let's get up, let's get a, I should hear back within 24 hours.

• 17:30Speaker 00

  Do you know what I mean? And like, to me, like the basic thing of, look, if I'm applying for a stretch job and I don't get it, I, that's fine. Or if I apply to a job and I make it to the finalists and there was someone else that, that beat me up.

• 17:41Auren Hoffman?

  I have been applying for the point guard of New York Knicks forever, but they never called me back.

• 17:45Speaker 00

  They never, right? Like people get, people get that. What they, what they don't get and where the, where the real, you know, hopelessness comes from is this sense that like, I'm right there, I applied to this job that I'm perfect for, I never even got a, got a response. If that's not going to happen, what hope is there? And so I think it does have to start with a candidate-centric point of view.

• 18:04Auren Hoffman?

  That seems really easy though. Like if you really did apply for a job that you are perfect for, like they should be able to get back to you within a few hours. Like that, that seems very, very easy. Well, and yet. Yes. I mean, and obviously, obviously it's not easy or you wouldn't be in business. Like it's obviously very, very hard.

• 18:22Speaker 00

  You can go back 20 years or more and you can look at candidate experience surveys. And for as long as I've been in this business, by far the number one complaint that candidates have had is I never heard back. Is I applied to a job, even I interviewed, I never heard back. And so it, it, you know, you'd think it, it's a simple thing, but you know, simple does not always necessarily mean easy. And there are, there are structural issues and there, and there are systematic issues in the way of making that happen universally. I agree, it absolutely should be the case and it should be the standard, you know, for a good process. The second is how the decisions are made. And, you know, once you get past that and you get into a hiring process, I think candidates have a real expectation,

• 19:06Speaker 00

  or they should have a real expectation to, to your question of like, what would good look like? They should have an expectation that they're assessed in ways that are relevant to the job trying to be hired for and that are equal across candidates, that I'm going to be assessed the same way you are for the same job. And again, I think that's an area where when you look at how hiring has been done historically by humans, those things don't happen. Historically, people make extremely idiosyncratic decisions about, about who to move forward with and who not to, based on all kinds of personal preference. The classic thing, an interviewer and a candidate are talking about their hobbies and, you know, you and I went to the same college or we both have the same sports team, you're going to be, you know, you're, you know,

• 19:50Auren Hoffman?

  You have the affiliation for that person.

• 19:53Speaker 00

  You know, outgoing, personal candidates have a better chance of getting hired than introverted, shy candidates, whether or not that has anything to do with the job, you know, or not. And, and so again, there's all this, there's all these challenges that humans bring to the problem. And again, where I think the possibility, one of the biggest possibilities AI can bring is-

• 20:14Speaker 00

  Is you can deliver, you know, an equivalent assessment experience to every candidate without regard for some of these irrelevant characteristics. AI doesn't care what your favorite sports team is, or, you know, it can be, it can be told to think about the words you're saying and not, you know, whether you seem, you know, outgoing or have a nice smile.

• 20:34Auren Hoffman?

  And when you are ready for the interview and when the interview is ready for you, like, it should be, the other, the other thing I think people have problems with is they're being interviewed by somebody who literally walked into the interview room and didn't prepare at all. And then, and then vice versa, sometimes the interviewer is interviewing a candidate and like they've never, they didn't do any research on the company. They didn't do research on the interviewer. Like when I interview founders, in some ways it's similar, right? Like I'm talking founder, they're talking to me. Like I, I will do at least 30 minutes of research and hopefully a lot more about their company, about their, their background, everything like that before I meet with them. Like I'm not going to waste their time

• 21:15Auren Hoffman?

  and I expect them to do the same. I expect them, we don't do intros. We're not going to be, oh, here's my bio. Here's what we do. Like ideally, right? When we're talking, we're already done all that. Like we know that we prep work. And like now we're talking about like the good stuff that you can only talk about in a conversation.

• 21:29Speaker 00

  I think that's right. Yeah. I'll, yes, and you on that. Cause I also, also, wouldn't it be great? If there was an, if there was a venue where the candidates could ask whatever they want without judgment and learn about the company, the opportunity, the hiring manager. And often they're very constrained and limited. If I ask about benefits or working culture, you know, it's like, I don't know, this person sounds like, you know, they, they all, they only care about money or they don't want to work hard. It's like all these bad, you know, impressions. But when they talk to our voice AI.

• 22:01Auren Hoffman?

  Yeah, they can ask all that stuff.

• 22:03Speaker 00

  They can ask all the questions and the company can just load up all their, all their, you know, here's all about us. Here's our, and you, you ask for an hour, all the questions you want and it's not going to judge you. And so I think providing people that venue is just another way to get to what you're saying, which is like, can we make them feel more welcome? Can we help them find out more about our company?

• 22:20Auren Hoffman?

  It's just doing your research at a time. Like you, you should be doing your research, however you do it, whether, and the company should allow you to do that research. So it should make as much of that available.

• 22:28Speaker 00

  And whether, and whether the company hires that candidate or not, can that candidate walk away with a positive experience about the company, learning more, you know, and, and becoming a fan. Like that, that I think is a great untapped opportunity. And likewise, you know, if you're, you know, you talk about assessing founders and of course hiring, like, have you ever thought about the fact as to why everyone's resume is still an eight and a half by 11 white rectangle? But what?

• 22:54Auren Hoffman?

  I mean, but by the way, like I, I haven't even seen a resume in, I don't know.

• 22:59Speaker 00

  You look at LinkedIn profiles, right?

• 23:00Auren Hoffman?

  I just see a LinkedIn profile today, right? So I don't, I don't even know what that is.

• 23:03Speaker 00

  But it's the same idea. It's your, it's your name followed by sort of a chronological listing of the companies you've worked at and your job titles. Like there's a lot more to it than what's on a LinkedIn profile or a, a resume. And I would argue, just like you're, just like we're saying, wouldn't it be great if there were new and better ways for the candidates to find out about the company? Wouldn't it be great if there were new and better ways for the companies to find out more about what that candidate is capable of? And just like this very static kind of chronology. And if you can showcase portfolio work you've done, you know, visual design work you've done, AI work you've done, analytical work you've done. We're all so much more capable now of producing independent work than we were a generation ago, whereas like,

• 23:46Speaker 00

  you kind of, you kind of work within a factory structure and, you know, the corporation had all this infrastructure you didn't have. Like we all have powerful supercomputers in our pocket and access to this AI that you never had before. We can create stuff independently. That's incredibly powerful. Wouldn't it be amazing if you could tell those things about the talent you're assessing, you know, in, in better, in better ways. And so I just think we're in this moment of, of, of being able to stop and reimagine hiring for the AI era as something a lot more three dimensional and human that helps bring a lot new signal to the, to the party that just isn't, hadn't been there before.

• 24:21Auren Hoffman?

  One of the reasons that sometimes even when people do get hired, that they're not as successful in that company as they should have been, is that there's a culture mismatch. It's not necessarily the candidate is, is the candidate is great. The company's great. It's just like, it's like dating, like two great people might not, shouldn't get married necessarily, right? There's, there's some sort of culture mismatch that happens. It does seem like AI could really help both sides with understanding that. And it, I, I know it gets into like the weird discrimination stuff as well, where, okay, like what is culture? But it does seem like we could probably do it in the right legal way.

• 25:01Speaker 00

  I think that's right. I mean, the way I think about it is when you look at a great hiring process, the candidate has a lot of information in their own head that is super relevant to that question of like, will they succeed in this job? That there's hard, it is hard to get out, but what, what type of culture are you most successful at? What type of leader have you worked for? That was the best leader for you? What don't you want? What do you want? And even basic stuff like, are you, are you interested in working remotely or in an office environment? You know, what size team, what size organization? Do you do better with more independence or more clarity? Like there's all kinds of very specific types of questions

• 25:46Speaker 00

  that are, that are, that are in your head, that are not on your resume, that are not on your LinkedIn profile, but that matter a lot. And wouldn't it be great if everyone had an AI advisor helping them get a job? That knew that stuff about them. Hey, sit down and tell me for 20 or 30 minutes, what it is that really unlocks you at work? And then when that AI agent you talked about earlier is out there in the job market looking at jobs, it's not just reading want ads. Hey, you know, accounts payable clerk needed, you know, $30 an hour apply here, but like, okay, what's the culture like? What are the problems that this person's going to be asked to solve? How are they going to want to work with their peers? What are the growth opportunities and challenges? What kind of folks are successful in this environment? What are the core values that are espoused?

• 26:32Speaker 00

  Like really understand what makes it tick beyond the sort of, you know, keyword, technical headlines that are on a, on a job post. I think getting at that ground truth, that real signal underneath, what is the hiring manager really looking for to unlock this role? And what is this person's really highest and best purpose? Like getting that stuff together? I think that's the possibility in the AI era that hasn't existed before. It's just too hard to do. That I'm really excited about. And I think sort of AI first conversations are the way to get there.

• 27:00Auren Hoffman?

  And how does one like, like, cause I may, maybe the culture of this company is like, everyone's an athlete. And like, if you're not a serious athlete, it wouldn't, you wouldn't fit in as well. Cause maybe they really need that weird competitive type of grinder. And again, some of these things do get on, they get a little, get to the closest, like in the dating world, you can discriminate all you want. You're allowed to discriminate, right? Almost everyone known they're dating discriminates on gender, right? You're allowed to discriminate on height, you know, you're allowed to discriminate on political leaning or religion, or all these other random things you can't discriminate on for, for the jobs stuff, right? And, you know, just like these things that look really, really tiny micro things that might come in there about like what, what culture.

• 27:44Auren Hoffman?

  But in reality, like it is still the right thing for you to, you, you want to be successful. The company wants you to be successful. So they do, your agents do need to negotiate about these like tiny little things that like get on that edge.

• 27:57Speaker 00

  Yes and no. I think, you know, when you think about a lot of the things you just mentioned, and let's leave dating aside, because I think there's a lot of problematic avenues to go down.

• 28:05Auren Hoffman?

  Obviously dating doesn't work out that well either.

• 28:07Speaker 00

  You can't get too caught up in job, job searches like dating, because I think it leads you to some bad places. So leaving that aside for a minute, I think there are a lot of these ideas that people have when they're looking for the right hire that are at best rough proxies for what they really mean. So you talked about, oh, we hire athletes, which is something you do here, you know, on, on, on certain, you know, hiring teams. And there's probably something they're really getting at, unless you're, unless you're building a sports team, unless you're, unless you're hiring an athlete. Like what do you really need? It's somebody that's going to perform in certain ways under certain conditions. And like, you might've thought with maybe even some evidence behind it, that hiring an athlete is like a sort of rough proxy for how you can get at that.

• 28:51Speaker 00

  But it's not really what you need to get at. What you really need to get at is how is this person going to behave in these? And I think what most people would be surprised at is like, gosh, there's a lot of people out there that are going to perform really well in that circumstance, that for whatever reason aren't an athlete. And wouldn't it be better for everyone? Wouldn't it be better for company if you could uncover those people? While your competitors are busy trying to hire athletes, you actually found the diamond in the rough. That's going to be a lot more of a competitive hire. That's going to perform better at the job, but that for whatever reason, didn't make the sports team. I mean, I'm not a D1 athlete and I never have been. But, you know, maybe I have that, you know, killer drive for, for some other reasons.

• 29:31Speaker 00

  And so I think getting at more of the underlying human and the, the real behavioral results that they can drive can help us in a lot of ways look past some of these, some of these, you know, credentials. And so that, that's how you get an edge as a, as a hiring team. And it so happens that that's also how you make the, the hiring market more fair. So I personally have long been of the belief that these are one in the same problem and making it more, focusing more on the job relevant criteria and finding the people that are the best at the job, not the best at interviewing, is the, is the job of hiring and it's how you make the market work best.

• 30:12Auren Hoffman?

  It's interesting that like as companies are also now recording a lot more information that's happening internally, right? They're recording their internal meetings and they're getting better processing emails and Slack and all these other like intercommunication within the company. And obviously recording a lot of external meetings. If you're a salesperson or whatever, you're meeting with customers. So to bring that in. And that should give them a lot of insight into the types of people that were, are more successful in their company and that. Cause I, I think it might be hard even for companies to articulate that the culture or who's successful. And they'll always say, oh, you, we have a, a growth mindset. They'll, they'll have these like very big words where like really what you're looking for is like,

• 30:53Auren Hoffman?

  why is my successful company so much different than other successful companies?

• 30:59Speaker 00

  Yeah, look, I mean, I, I'll tell you my own story on that. Cause you know, when I got, again, going back to my start. In this world, going back to the early 2000s, I was hiring engineers on Wall Street and I was struggling to understand, you know, what was making it successful or unsuccessful. We'd have wins and losses. I couldn't tell what was happening. And to your point, those were not recorded, you know, experiences available as data. They were just ephemeral, like a person would go into a conference room with a job seeker, they'd come out with a yes or no, like poof, it just went away. And so I literally, I mean, this is going to age me a little bit, but I went to Radio Shack, I bought a tape recorder and I gave it to my team and for months, they would go into job interviews with a tape recorder put on the desk.

• 31:41Auren Hoffman?

  Wow, okay, this really does age you.

• 31:43Speaker 00

  And I would listen to them, I would listen to those recordings on my commute home and like, it was horrifying. I mean, like, what was happening in those rooms? First of all, the questions that, that, you know, folks would ask when they weren't prepared, we were like, why are we asking that? And then the answers they would give when a candidate would ask about the company or the project or the team, like, you're like, what is happening in this room?

• 32:07Auren Hoffman?

  Why is that?

• 32:07Speaker 00

  And we were, it was, it was bad. And so having those recordings available made it so much easier to make the process faster, more streamlined, more sensible, more fair, all the things. But it was really hard to do. I mean, I had to literally buy physical hardware, hand it out. It was a mess. It wasn't really scalable. But you fast forward to today and we've got,

• 32:28Speaker 00

  you know, automatic note taker in greenhouse that records every interview, transcribes it, fills in the scorecard. Like, that is all data that is now subject to analysis and optimization. And so the company can automatically look for patterns of where are we missing out? Where do we need to be asking better questions? What are the things we're asking that are kind of a waste of time? We're over interviewing. Conversely, what are the things we're missing out on that we need to spend more time on? How do we make our process more efficient? Like, all of that stuff that used to be ephemeral, passing activities, candidate outreach used to happen on phone calls, right? Now it's sophisticated email outreach campaigns and recorded calls. Interviews used to happen in conference rooms behind a closed door, one to one. Now they

• 33:11Speaker 00

  happen in recorded videos with transcripts and scorecards. Like, all of the hiring decisions used to be done in a meeting on a piece of paper are now recorded and tracked and subject to analysis. And so, yeah, I think the idea of today's modern AI-enabled hiring team, it's a lot more of an automated, tech-heavy, operationally intensive process than it used to be. And it generates, you know, there's a lot of benefits to doing it that way.

• 33:41Auren Hoffman?

  In my career, there's been a small number of people that I have hired that turn out to be absolute superstars, absolute 10x people, right? The vast majority have worked out great. And then, but every once in a while, there's someone who just works out in an insane way, who's just, and I don't know if I had looked back in the interview that I could have a priori predicted. Obviously, I hired them, right? So I hired them for a reason. I thought they would be good. But I don't know that those are the people I could have predicted would have been the absolute superstars. If I could have predicted it better, I'm sure that means I've lost some people. Maybe I would have paid up for those people, or I would have more aggressively pursued

• 34:21Auren Hoffman?

  them, or whatever. Like, how could companies better predict who would become like those true 10xers?

• 34:28Speaker 00

  I would argue, for most organizations, that is less of a data question. I don't think the answer's there in the data. I think it's more a judgment question. Here's why I say that, is most organizations, you're dealing with really small numbers, and you don't have enough of a large data set to predict. So let's take even, you know, a moderately sized company. Let's say it's a 10,000-person organization, right? Pretty big compared to most organizations.

• 34:58Auren Hoffman?

  Yeah, any given role, it's very tiny.

• 35:00Speaker 00

  What makes a successful salesperson? And you go back and you look at what data do we really have available? It's like, okay, we have a thousand sales reps, but the truth is, we've had three sales leaders in the last 10 years. And so the structure has changed. And by the way, we've opened up new territories and we've launched a new product. We've changed our pricing. Like, what's really consistent among those?

• 35:19Auren Hoffman?

  Right, right. And somebody in Mexico might be different than somebody in Atlanta and, you know, okay, yeah.

• 35:24Speaker 00

  I just said-

• 35:25Auren Hoffman?

  So it's very, very hard.

• 35:27Speaker 00

  You know, and so you can look at like, a handful of jobs where there is true scale longitudinal data, you know, the US Army Accenture, right? It's like, yeah, okay, they've hired, like, you know, hundreds of thousands of people in the exact same job for many, many years, under varying conditions. There's a lot more you can say. I think most startups, like, the goal is, how do you avoid the bad, like, the truly-

• 35:53Auren Hoffman?

  The truly bad ones.

• 35:53Speaker 00

  Failed hires. Like, there's definitely stuff you can do in an interview process to avoid making huge mistakes, to avoid costly lawsuits, discrimination, overlooking top talent that may be as great at the job and not great at interviewing, and give yourself an edge. But at the end of the day, it's going to be, it's going to be pretty probabilistic and rely on some judgment.

• 36:15Auren Hoffman?

  Okay, that makes, that makes a lot of sense. The, no, no, okay, you've talked about these interview questions.

• 36:24Speaker 00

  Yeah.

• 36:24Auren Hoffman?

  What are some common interview questions you think are like, the least predictive?

• 36:28Speaker 00

  Tell me about your strengths and weaknesses. Well, look, I think, I mean, that's the classic one, right?

• 36:32Auren Hoffman?

  That's a classic one. You think that's just not a good one, or?

• 36:35Speaker 00

  Here's the, here's the wisdom, is, by and large, questions that focus on past behavior are the most predictive of future behavior. Stereotypically, it's-

• 36:51Auren Hoffman?

  Walk me through, why'd you do this?

• 36:52Speaker 00

  Tell me about a time when.

• 36:53Auren Hoffman?

  Okay, yeah, okay.

• 36:54Speaker 00

  Yeah. Tell me about a time when. And then, a lot of detailed follow-up. Like, I want to know exactly about that situation. So tell me about a time when you solved a difficult problem, blah, blah, blah.

• 37:03Auren Hoffman?

  Yeah, exactly.

• 37:04Speaker 00

  Why'd you do that? Why'd you do it that way? What is it about you that made you act that way and not someone else, et cetera, et cetera?

• 37:08Auren Hoffman?

  A very predictive thing of people who do well in companies is agency, right? If you, the more you have agency, assuming the company allows people with agency to work, maybe some companies don't. So, you know, there might be some big bureaucracies where agency could be like, anti-predictive. But at least in a startup where I'm in, like, you want people with agency and then so you can ask a lot of questions to get into, like, why, if this didn't work, what did you do about it? How'd you do it? Like, what'd you do, et cetera?

• 37:35Speaker 00

  That's right. So your key is, exactly. So first, start with what helps predict success. And in a startup, high agency is, and in other cases, it may be something different. But if your theory is, I need people with high agency and, you know, grit, and whatever these things are that you're looking for, tell me about a timeline is a way to get at it. And unfortunately, often what people come into is, they'll do a resume walk. Hey, tell me about what you did at this job. Which, like, then you're listening for whatever. Or, how would you? Sort of a hypothetical, which, if you tell me how would you, you know, yeah, I could tell you whatever I want. I can kind of guess what you're looking for, tell you how I would. And to use your cheeky example, like, how would you win the NBA Finals if you were the point guard for the Knicks?

• 38:19Speaker 00

  Like, yeah, I'd choose the winning shot. Like, does that mean I can?

• 38:22Auren Hoffman?

  Yeah, exactly.

• 38:23Speaker 00

  Have I? Like, very different, very different question. And so I think, I think focusing more on, you know, past behavior as a predictor, like, what have you actually done? And why did you actually do it that way? And then relating that specifically to the factors I can identify about success inside of the organization, like, that's the, that's the most predictive thing to do.

• 38:43Auren Hoffman?

  There's been so much talk about AI taking jobs and stuff like that. And you hear every day, some, something forward and something against it. And what is really happening in the, let's say, the entry level and white collar market right now?

• 38:58Speaker 00

  Yeah. And, sorry, one more thing on the interviewing question, because it's a big topic. People have, and then let's get to it, let's get to that, is, the other thing you hear a lot online are these, I call like, sort of like, secret trick questions. There was a famous one that blew up on social media last week about iced coffee. You know, if you bring an iced coffee to an interview, that's a terrible signal.

• 39:17Auren Hoffman?

  What? Why would that be? I don't understand.

• 39:19Speaker 00

  You hear these things like, oh, I take the candidate out to a meal and I look at how they treat the server. And it's like-

• 39:24Auren Hoffman?

  Right. This was like the Henry Ford, like, he didn't want people who salted their stuff before they tasted it or something.

• 39:30Speaker 00

  Don't set up a secret trap, right? It's like, if there's something you really need to know-

• 39:34Auren Hoffman?

  Very dumb, yeah.

• 39:36Speaker 00

  Figure out a way, figure out a way to do it directly.

• 39:38Auren Hoffman?

  They're not going to hire me because I like iced coffee? Like, what's, what's up with that?

• 39:41Speaker 00

  There could be a million reasons why the person did or didn't act a certain way, you know, in that context. And I think it's, I think it's a problem if you try to like, sneak, sneak test a person.

• 39:51Auren Hoffman?

  Yeah, exactly. Plus, like, I mean, do you really want to work, like, I remember back in the day, like, you'd hear about the, I don't even know if these were true, these rumors where they'd be like, you know, investment banking jobs, like, open the window and the window is shut and you can't open it or something like that. And they wanted to see how the candidate reacted. It just seems like a little mean, too.

• 40:08Speaker 00

  Yeah.

• 40:09Auren Hoffman?

  Because I don't want to work for a company like that.

• 40:10Speaker 00

  Or like famously in Men in Black, when they put all the, you know, cadets through this test and Will Smith like drags the table over and that's the sign that he thinks outside the box. Like, that makes for a fun movie scene. Don't hire that way.

• 40:22Auren Hoffman?

  Yeah, yeah.

• 40:23Speaker 00

  So that's my thing on that, is like, don't, don't try to trick test people. Just actually, like, do a, you know, straightforward assessment of what you're looking for and figure out how to find it. Okay. So is AI going to take everyone's, look, I was like, making predictions, I think, in the world of AI has proven to be a little bit of a fool's game. So I'm going to be a little bit humble here and say it's hard to know for sure.

• 40:42Auren Hoffman?

  Tell me what's happening today, at least, right?

• 40:44Speaker 00

  Um, I think we went through a big period, you know, we went, we've gone through these periods where, you know, AI is going to take all the jobs. AI is going to make work irrelevant. AI is going to take all of the soft, you know, there's not going to be any software companies anymore because everyone's live coding everything. Look, I think where I am now is, the one thing I, we can be sure of, is that AI is going to change dramatically the skills needed to be valuable in the workforce and what the work is. Why? Because it already has, and it's going to continue to do that. Just like every technological revolution has in the past. I don't know about you, but in my, in my, in my organization, we don't employ any typesetters or, you know,

• 41:29Speaker 00

  horseshoers, or, you know, these kinds of jobs that used to be, you know, farmers, right? Used to be very prevalent. And so I think there's a lot of jobs that the work is going to change dramatically and already is. I mean, entry level, legal work has largely been taken over by AI. Review a thousand contracts and tell me which one has this clause is a perfect job for AI. And used to be something that a first-year, you know, law associate would do all day. That's going to continue happening. And at the same time, there's all kinds of new jobs and new work that's going to come up, that people are going to have to figure out how to go do. And that's, that's happening faster than ever. And so my basic theory on how this is all going is, is that this idea of like, the sort of technical skills that

• 42:12Speaker 00

  you have are becoming less and less durable.

• 42:17Speaker 00

  And the intrinsic skills that you have, people used to call soft skills, you know, of, you know, learning and agility and determination and, you know, these kinds of things are becoming more and more durable. And in fact, more relevant because whatever tools are going to come out tomorrow, none of us know, however, my job is going to change next year like none of us have have any experience doing. And so the thing I need in a company is people who can adapt quickly to change and, and, and figure out new ways of working better than, better than ever. So I think that an emphasis, when you think about an AI ready workforce, to me, it's less about, oh, I want to, I want people that have used this one,

• 43:01Speaker 00

  you know, AI model for a month longer than everyone else, which like, who cares? And more about, I want people who have the intrinsic durable capabilities to learn and grow and thrive in a changing, in a changing world.

• 43:13Auren Hoffman?

  There are different types of jobs that like, there are some jobs which are like, where there's like a very clear operating manual and you're, for whatever reason, the, the employee is supposed to be very much within the lines of that operating manual. Um, and those seem to be, and to me, those are like real, those jobs often have already been outsourced. Right? Those are the BPO jobs that are out there. Those seem to like, to me, the easiest ones to attack with AI because there's already a manual. There's already clear understanding. There's usually a clear way of measuring how people have done, et cetera. And then there's the, you know, the jobs without the manual, which is probably still most jobs today. Don't have a manual, not really clear what lines people should be.

• 43:56Auren Hoffman?

  They're going across things. They're interacting with stuff. They're, they're, you know, they're messy or things. And those, you know, AI has not yet attacked those types of things.

• 44:06Speaker 00

  I don't know if it's that simple. I mean, I think there's truth to that. Don't get me wrong. But I don't know if it's that simple because there's a lot of jobs where that sort of mechanistic part doesn't necessarily describe it.

• 44:20Speaker 00

  But where AI is doing a huge amount of the heavy lifting just in the last year. Think about everything from software development, which is effectively a completely different job than it was a year ago.

• 44:30Auren Hoffman?

  That's right. It's completely different. Yeah.

• 44:32Speaker 00

  But, you know, imagine a creative job. If you're a sound editor.

• 44:36Auren Hoffman?

  If you think of people who've been, and there's not very many software developers that have been replaced with AI. But do you think of the ones that have been replaced? Those are mostly the BPO types and less likely the people who are like doing all the, you know, and, and similar like law, law, law, law job that you mentioned, like mostly it was, it's like a lot of those, lot of the, a lot of the, the, the junior law jobs were already BPO'd in the past, and those are the ones that are like more likely to have been attacked.

• 45:05Speaker 00

  Again, I think we're like, we're getting into like, who knows territory here. So I, but it's a fun, it's a fun conversation. I think like, yeah, that I, I'm a yes and on that. Like, yeah, I think that's true. And like, if you're a law firm, here's my question to you, like, do you think in a year or two or three, the law firm looks like two or three senior partners and a bunch of AI doing all the busy work? Or do you actually have like a bunch of technologically savvy, maybe even earlier career, younger people, building and managing AI agents doing all the work? Like, I don't know, but that's a new job. Like, so there's all kinds of new stuff happening. It's like, not so simple. And again, if you're in these other jobs where, you know, if you're a,

• 45:45Speaker 00

  you know, if you're an FPNA person, if you're a sound editor or, you know, photographer, a musician, an investor, like, there's whole different things happening right now. And like a bunch of that stuff is definitely being replaced by AI. And a bunch of stuff that didn't used to be possible at all is now someone's job. So I, I don't think the story is as neat as, hey, like, the more a headset's telling you what to do, the more AI is taking over. I think it's, I think there's a lot of cross currents happening all at the same time.

• 46:16Auren Hoffman?

  Yeah. By the way, even with the BPO jobs, there hasn't been a lot of job displacement. Even like, you would think like India, Philippines, they would have been hit really hard by now. And to the best of my knowledge, like, there hasn't been that much job loss there. And you would, at least I would have expected they would see the job loss way earlier than you would see it in the US.

• 46:36Speaker 00

  Yeah, yeah. I look, I think also, you know, as someone who myself, you know, I'm leading a, you know, a global organization and we're trying to adapt ourselves to new ways of working. How are we using these tools? Like, it is really challenging to re-engineer your company to be entirely different and to say, great, like, a lot of this work is going to be done agentially. Whether it's, um, you know, uh, how do you identify the parts of the work that are better done by machine? How do you retrain your team to take advantage of that and do entirely new things? And how do you build those, those business processes and business cases? So some of this also might be, you know, these things take a few years to really set in at scale and to show up in the job market.

• 47:21Speaker 00

  And especially in a world where the AI is changing so fast. I mean, Claude Code has not been out that long. And, you know, the ability to, to write code is completely, I mean, we have an autonomous engineer here at Greenhouse that can take an idea out of Slack and turn it into production software, more or less independently.

• 47:39Auren Hoffman?

  Yeah.

• 47:39Speaker 00

  I still hiring engineers.

• 47:41Auren Hoffman?

  Yeah, of course.

• 47:42Speaker 00

  So, uh, they're doing different stuff. It's like, it's, it's, it's, it's,

• 47:49Speaker 00

  it's a complicated dynamic right now, which makes it interesting.

• 47:52Auren Hoffman?

  Now, I want to talk about HR because in some ways, like, it should be the most strategic place in the company. It's so important and companies are, you know, and, uh, but in general, and you may disagree with me here, but in general, I have found that the, that, the, most people in HR, if you just think of a high performing company and you stack rank the people, often the bottom, people in the bottom 25% of like their capabilities are in the HR department. And, and I have a friend who's like super passionate about HR and she's a leader and she's been offered a couple of like, you know, HR roles. But she's been reluctant to go into those roles because she thinks, well, no one ever gets promoted to CEO

• 48:36Auren Hoffman?

  from the head of HR, uh, type of thing. So how do we get HR to becoming a much more strategic piece of the company?

• 48:45Speaker 00

  Right. So I don't think you can just stack rank all humans on earth and say, this is the best, this is the worst in order. It's a lot more nuanced than that. I definitely agree that HR in most organizations historically has been undervalued, under leveraged, and as a result, not as attractive, not economically, you know, um, you know, as, as rewarding. Um, and that has really impacted.

• 49:08Auren Hoffman?

  Probably the average pay is much lower than the sales org or something.

• 49:12Speaker 00

  But I very much, but I very much agree with your, with your, with your point that there's a huge amount of potential if you have uh, an effective HR organization to unlock the organization. I think it's, comes down to, I wrote a book about this called Talent Makers, which looked at what is the difference between companies where their HR and talent organization is really effective and the ones that isn't. And it turns out, it has very little to do with what happens inside that department. It has almost everything to do with leadership. It has to do with, does the leadership of the organization see it that way? Value it that way and partner effectively to make it that way? Or do they go, hey, like, HR person, do my, you know, find my person, fire my person, pay my person. Like, that's your job. And I,

• 49:56Auren Hoffman?

  Compliance.

• 49:57Speaker 00

  When they take a hands off role, when they disempower, when the leadership disempowers themselves, that, that's where those come from. And, and I think to, to, to put a capstone on this point, here at Greenhouse, our own internal AI transformation journey is being led from within the HR department for exactly that reason. It's like, this is one of the most important things you need to do as a company.

• 50:19Auren Hoffman?

  Because that's what you would think, like, because AI and HR are to me, completely linked to one another. Yet I would say very few companies, the AI has been driven or even, even, or even HR is even being a big stakeholder in the AI transformation.

• 50:34Speaker 00

  I think, I think, I think I agree with you. Most organizations, HR is disempowered, held at arm's length and told, look, your job is to, you know, pay people right, make my,

• 50:43Auren Hoffman?

  If you ask the average person, let's say, product manager, engineering, and you ask them about HR, they usually have negative feelings about their own HR, you know, people or something or, you know, like, I don't like those guys over there, you know?

• 50:55Speaker 00

  I think descriptively, that's true. And I think when I talk to, to executives and founders about that, I point to them as I, the problem starts with you.

• 51:04Auren Hoffman?

  Of course. Yeah. You didn't hire the right people or you, or you didn't empower them or you didn't, you didn't, you don't care about it enough or, you know, whatever.

• 51:11Speaker 00

  And I get it. Look, when I talk to those people about this, which I do a lot, what you hear is they often don't have, they, they have that sense that there's this problem. What they don't have is a picture of what great looks like. Most people haven't seen it. So they're left with this wanting like, God, HR seems terrible. I wish it was better. But they don't have a clear enough vision of what great HR would do for them to then build that department and, and bring them in as that partner. And so it is a tricky issue for that reason, as I think like, most of them just don't have the vision of what great looks like. And so they're stuck with complaining about it.

• 51:44Auren Hoffman?

  And it's also just like, can you get the right, you know, the right action oriented person? Is it the same thing with like, you know, legal, like you could get someone who's really proactive and really helping your company? Or, you know, there's also the people stereotypically who say no all the time. And you want the person, okay, how do we get to yes in a way that, you know, both protects the company and like gets the business objective done, right?

• 52:09Speaker 00

  I think if, if the founder, the CEO, the leaders had that vision of what they want and, and knew what it looked like, it's a lot easier to get it. And I think a lot of what the struggle is, when you talk to them is they haven't seen that. They don't have the vision of what it looks like. They know, they don't, they know they don't love it, but they, they kind of assume that nothing can, can be done about it. And one of the hallmarks that I see is often,

• 52:34Speaker 00

  There's this chain of thought that goes, well, HR stinks at my company. Therefore, let's just not do it. I'm going to fire my head of HR. We're not going to have any rules. You know, we're not, you know, you see this like people experiment. Oh, we're not going to have managers are bad. We're not going to have managers.

• 52:49Auren Hoffman?

  Right, right.

• 52:50Speaker 00

  The vision of like having great managers is kind of like not really a thing. So we're just going to not have any managers. Everyone's going to figure out. And of course, those always end in tears. Those are always disasters. We're going to get rid of legal because we don't think they help. You're going to get sued. We're going to get rid of HR completely. It's like your company is going to turn into a train wreck. And so I do think it's worth a leader's time to think about what would great look like? And how can you get it? And if you think that situating your HR leader as a strategic partner, someone that's charged with real responsibility and real accountability for making your company great, you can have that. You just have to, you just have to want it and actually commit to doing it.

• 53:28Auren Hoffman?

  Companies where they really have to think about their people, Costco, Walmart, et cetera. Like they have really strategic HR because that is such an important part of what they do.

• 53:39Speaker 00

  Isn't that the same when you look at the companies that are historically like you'd think like, oh, a big company's bureaucracy and a small company is like innovative. You're like, I think there is a pattern. If you look at HR departments, you're like, think of these companies PepsiCo, Netflix, Walmart. I mean, these are companies that have really innovative, you know, in a lot of ways, HR practice. I'm not saying they're perfect and I'm sure someone's going to look in the comments and say, oh, they did this thing. I'm sure they did, but a lot, a lot of that innovation does come out of these larger organizations. For that reason, I agree.

• 54:08Auren Hoffman?

  Yeah. And sometimes it's just asking like, why do we do this? Or like, you know, Netflix famously in the early 2000s said, okay, why are we tracking vacation? Like, that just seems weird. Like, what's the, why, why have these weird hour? You get X number of hours per the week or like, it's just, it's like an odd thing.

• 54:26Speaker 00

  And if, you know, and you, and you listen to Patty McCord talk about what she was doing. They're famously their, their, their head of HR at the time. And she'll tell you these stories like, look, like, uh, you know, hiring manager would come to us with an opening and HR would say to them, okay, here's the way to be successful as a hiring manager. I need you to do these things. I need to think really carefully about the job requirements. And you think really carefully about how you're going to succeed, collaborating these ways. And I was like, that seems like a lot of work. I'm not going to do all that. Can't you just hire for me? And she would say, you don't have to do it our way. You can hire however you want, but if you want my team to do it, this is how we do it. It was like, okay, you know, so if you think you can do it better on your own, that's fine. But what HR provides and it's this great product, but you got to do your part.

• 55:11Speaker 00

  And so it was like, that's a real accountability relationship. And I think she couldn't deliver that level of quality without the, without the support of leadership to committing first to saying, this is how we're going to do things. And Patty and her team were empowered to say that and to back it up. Most organizations aren't that way. I talked to like, I talked to heads of recruiting. They're generally terrified of the business. They're generally, you know, on the back foot. You know, the, the CTO is shouting at them, hey, like, why haven't you filled these roles yet? Oh, sorry, I'll send you over some more candidates as quick as I can. I was like, it's a bad spot to be in as I mean, so it's a tough spot to be in when you're not

• 55:53Speaker 00

  positioned as an equal partner, yet your input is needed to deliver an excellent result. And that's where I think a lot of the problems stem from.

• 56:00Auren Hoffman?

  All right, that's good. Two personal questions before we leave. The first one is how are you personally using AI like day to day?

• 56:06Speaker 00

  One of the funner examples. So I'm a big getting things done. David Allen with this book, Getting Things Done, sort of personalization system.

• 56:13Auren Hoffman?

  Similar, yeah. I have a similar system, yeah.

• 56:16Speaker 00

  So I had written a blog post, gosh, like 10 years ago about how I use that getting things done approach in Trello. I've got, you know, columns and cards and I drag them around and I sort of manage my ADHD with this like approach. And I wrote this like, you know, three page long blog post about it. And that was 2016 and.

• 56:35Auren Hoffman?

  Appropriate. You can just train the AI bot with that.

• 56:37Speaker 00

  That's right. So I literally like aimed Claude at that old blog post. I said, here's the way I do things. Here's my Trello board. Can you automate it? And now I have a set of Claude skills that use what I wrote 10 years ago. And that was literally like a programming language for this bot that now helps me manage my, my getting things done in a much more automated way. It's super interesting.

• 56:56Auren Hoffman?

  All right, we, next time I'm in the same town as you, we got to meet up and like, show some systems and nerd out on this stuff. I've done some similar things as well. Our last question, we ask all of our guests, what conventional wisdom or advice do you think is generally bad advice?

• 57:10Speaker 00

  As a founder, to me, it's knowing when to quit. I think too often there's this founder advice of never give up, never quit. I think that's wrong. I think I personally, you know, I had my first startup failed at the dot com crash. And had I not given up on it, I never would have done my next thing. I too often see founders where it's just never going to work. And the hard part is of course, sometimes you're that founder that powered through and made it work. And famously, there's a lot of examples of the ones that powered through and made it work big. So I think there's a venture capital industry that's highly incentivized to tell you to keep going no matter what. And I think as a founder, you got to decide, is your time better spent chasing this one? Or stop, pause, regroup and try something else.

• 57:55Auren Hoffman?

  But I still think it's very hard to know, right? Because you may have like, oh, you've assembled this group of people you really like working with. And you've got, you know, some, obviously if like everything's going terrible, it's very easy to stop. It's probably a scenario where like some things are going, okay, some things are going bad. It's like you're in this local maxima and you're not sure how to get out of it. That's usually where like the founders keep going. And then sometimes they just keep going forever and never get out of that local maxima.

• 58:21Speaker 00

  It's hard to know. So I'm a big, I'm a big believer in, uh, you got to be brutally honest. Is this your highest and best path? And if not, um, it's hard to imagine when you're in that startup mania in the early days, that you could do something else. It truly is. I've been there and I've seen a lot of people be like, no, this is what I'm doing.

• 58:43Auren Hoffman?

  Like if anyone else in the company leaves, it's fine. But if the founder CEO leaves, like the company goes under.

• 58:48Speaker 00

  And you sort of, and you sort of push it all in.

• 58:50Auren Hoffman?

  The end of the company. So you, you, you do have a lot riding on your shoulders. And so it does make sense that you're less likely to quit.

• 58:57Speaker 00

  Yeah, but I can tell you, I've had a number of time. I've given this advice to lots of startups that I've advised and worked closely with. And most of them don't take it. And the couple, the few times that they have is like, wow. Like they went on and did incredible things very, very shortly after that they never could have imagined if they were too buried in the, in the day to day grind of what they were trying. So think about it.

• 59:20Auren Hoffman?

  This has been awesome. Thank you, Daniel Che, CEO of Greenhouse for joining us on Sumation. This has been really eye opening and really interesting.

• 59:27Speaker 00

  Thanks a bunch.

• 59:34Auren Hoffman?

  One more thing before we go. I read a blog called Sumation. It's the same as this podcast. The blog is about non-obvious idea sharing on business, talent, data, longevity and random contrarian takes. If you like the conversations on this show, you'll probably like the blog. It's free. New content comes out twice a month. You could subscribe at orin.substack.com. That's orin.substack.com.