SEASON 2 - EPISODE 0101 - MAR 20, 2024

How We Work: Finding the Right Team

37signals is hiring! However, the traditional resume and formal education credentials don’t rank as high as you might think in their hiring process.

In this episode of The REWORK Podcast, host Kimberly Rhodes chats with co-founders of 37signals, Jason Fried and David Heinemeier Hansson about reviewing potential job candidates. You’ll hear them discuss why a personalized cover letter can tell a lot more about a potential hire than chronological work history, and why AI isn’t always a dependable author for those details.

Watch the full video episode on YouTube

Key Takeaways

00:45 - Resumes are basically piles of lies.
02:27 - Cover letters should explain why you want the job.
05:07 - Test driving final candidates.
11:05 - Jason and David’s involvement in the hiring process.
18:59 - Finding employees that are the right cultural fit.

REWORK is a production of 37signals. You can find show notes and transcripts on our website. Full video episodes are available on YouTube and X.

If you have a question for Jason or David about a better way to work and run your business, leave us a voicemail at 708-628-7850 or email, and we might answer it on a future episode.

Links & Resources

Transcript

Kimberly (00:00): Welcome to REWORK, a podcast by 37signals about the better way to work and run your business. I’m your host, Kimberly Rhodes, and I’m joined as always by the co-founders of 37signals and the authors of REWORK, Jason Fried and David Heinemeier Hansson. We’ve talked a lot about 37signals being a small company, about 70-ish or so employees. We don’t hire very often. We’re actually in the process of hiring a programmer right now and we’ll soon be hiring a designer. With all of this happening, I thought it’d be a good time to talk about how we work at 37signals in terms of hiring. So Jason and David, you guys have talked a lot about this in rework several essays about it, and one of them is about formal education not being important and resumes being ridiculous. Who wants to jump in on this, Jason?

Jason (00:44): Yeah. Resumes are basically piles of lies, essentially, and you almost can’t blame people because you’re asking them to basically come up with the greatest hits of their career in the most positive possible light, and it’s not that they’re lying. I went to this school and I didn’t mean that could be a lie, of course, or I did this job and didn’t. That’s a lie, but it’s more like the claims are personalized in a way that aren’t typically accurate. People typically would work with a team on something, so someone’s like, I increased revenue from this to that. It’s like, well, you probably didn’t do that alone, and there’s probably other reasons why things may have happened this way, and maybe the product changed too, and maybe the marketing change, who knows, right? But they’re kind of just picking cherry, picking these highlights and putting 'em on the resume.

(01:38): So lies is maybe a strong term, but I would just take them with a grain of salt and go like, okay, whatever. Let’s look at the cover letter instead because the cover letter is actually something that hopefully you wrote, although these days, who knows who wrote anything, but let’s assume that you wrote it and we can get a good sense of who you are and how you describe yourself and the kind of things you want to pick out. Not in a formulaic way, but actually in a conversational way. So that’s why resumes are handy for a minute just to check something sort of, kind of, but they don’t really have a lot of weight here at 37signals.

David (02:12): I think the other thing with resumes is they’re not specific at all to this application. They’re not specific to our company, they’re not sometimes even specific to the role. They’re a generic account of what someone has done over the years. And what I like about the cover letter is that it requires someone to think specifically about why do you want to be here? Why do you want to work on these projects? What excites you about HEY or Basecamp or ONCE? And you get a better sense of someone’s personality, what drives them, what inspires them, what gets them fired up, and it also gives you a clear sense of whether they can write. Again, as Jason says, these days, maybe it’s going to start getting harder to do this now that you can get AI to write things for you. But most of the things seen written by AI, I think at least for the hot moment here, I’d be able to smell because it has a certain AI-ish quality to it.

(03:10): Maybe that’s about to disappear and in three months it’s going to sound amazing. But the thing is, it’s not the end of the line. What are you going to do if you get AI to write your cover letter for you and you proceed to a conversation or even better, you proceed to a test as we like to do and you can’t hack it? What’s the upside? What’s the purpose here? I think the idea that you can use someone else’s work, AI or otherwise, to sneak in and then that’s going to pan out. I’ve never seen that actually happen. I think fake it until you make it as something for entrepreneurs to hoodwink investors wi maybe. But once you start here as a programmer, you’re expected to program, you’re expected to deliver software, you’re expected to ship, and if you can’t actually do those things, what good is it to have had a leg up?

(04:06): In fact, if anything, it’s going to look worse. Say you get all this assistance, you get the job against all these odds and obstacles we just discussed, and then you’re fired in three months because you can’t cut it. Now you’re going to have that gap on your resume or you’re going to have that short stint. I don’t think that actually pans out, but we will see. We have actually not had an opening for a programmer since the advent of general AI. We’ve not hired someone after Chat GTP became a thing that everyone used. So I’d be surprised if we don’t get some applications that use that and to some extent, do you know what, there’s also some of that that’s fine. Not even just in the job application, but in the test we do or whatever. I use AI all the time. I don’t use it for writing, but I do use it in programming. It is a tool in the toolkit, but it’s going to be a fine line between where are you faking it, where are you plagiarizing things, and where are you using it as a tool.

Kimberly (05:07): Okay, David, you mentioned test driving or testing employees or potential candidates. Talk me through that process. Obviously we’re going to get hundreds if not a thousand plus resumes for this one position once they get through that round, what happens next?

David (05:27): For the finalists, usually that’s between 10 and 20 candidates, so there’s already been quite a rough culling by then, which is interesting. When we talk about hundreds of applicants or a thousand plus, it sounds higher than it is because about half of them you can throw out right away. Half of them put in no effort. They don’t even finish reading the job opening. They don’t fulfill the most basic asks that we have in that listing. So you can just go right away, this is not a credible, serious candidate. Then from there, obviously it does get more tricky, but then we get all the candidates who might’ve read through the whole thing, but go like, yeah, I know you’re asking for Rails program. I haven’t actually done Rails, but I’ve done other things. And you can go, okay, you can sound very nice in all sorts of other regards.

(06:15): That’s just not what we’re hiring for this role. We’re not hiring someone who does not have any familiarity with Ruby on Rails because that’s what we use. And more importantly, there will be other candidates who have those skills. And I think that’s to me actually the most important point of all of this. If we get say, a thousand applicants, each individual applicant will, of course, because it’s a human thing, think very myopically about their chances to get the job. They will think about it in terms of whether they did the right thing or the wrong thing. But that’s not how we’re thinking about it when we look at the applications. We look at the applications and employ perhaps the skill humans are best at, comparison. Who amongst these candidates looks more promising? Who has, where’s the hook? Where’s just the right things that add up?

(07:06): And it’s not so much that we’re saying this candidate is discarded. Actually, that’s usually never what happens. What we do is, oh, here’s 20 candidates that look really good. These are the ones who will get an opportunity to have a take-it-home test. And that to me, at least in the past, has been the very successful final filter of bullshit. There are people who are very skilled at telling you what you want to hear in the right tone and can write a great cover letter, can do all those things, can be persuasive on the phone, can really charm people. Those are very important skills. But if you’re a programmer here, you got to be good at programming. You got to be very good at programming. And the only way for us to see that is to look at code that you’ve written, which require us to ask you for some of that code.

(07:57): And we’ve changed our approach over the years back and forth. These days, we actually pay those finalists a small sum to conduct the final test. Interestingly enough, I’m not sure how I feel about that. I know we’re doing it and I know it sends a good vibe that we’re not asking someone to do frivolous work that we then don’t care about. I do think there’s a positive there, but I also think there’s, I mean, I wrote a blog post two days ago about being too precious. It’s a little precious to me that the idea that someone might spend four hours say on a take home test is completely sort of out of the norm or is too much to ask for a small group of finalists. Where I think a lot of the negative feedback on at home tests come in is when companies uses them as the pre-filter.

(08:50): When they ask a thousand people to spend four to six hours or even longer on a take home test, knowing that the majority of these candidates, we won’t perhaps even look really at their application. We will filter them out at some earlier stage because of something else. By the time you get a take home test at 37signals, you will have already pre-qualified as a promising candidate. We’re not asking anyone who we would rule out for these other criteria to do a take at home test. And then we do the take at home test and we look at the code. That’s the other thing that comes in is it’s actually, I don’t know if it’s surprising, but it’s a large amount of work to evaluate candidates. And this is again, one of those things that come in, each individual candidate thinks, well, I put a lot of effort into this cover letter.

(09:37): I put a lot of effort into this take home test. Can you give me some specifics of why I didn’t make the cut? No, I can’t. If you’re evaluating a thousand candidates and you’re just spending, let’s say five minutes, which is not even realistic, five minutes giving people detailed feedback, you’ve just spent 5,000 minutes on that What? That’s not a thing. We can’t spend a hundred hours just telling people why they didn’t make the cut. So anyway, all of that is to say in the end, you won’t get a job here unless we’re convinced that you’re a very good programmer and we’re not even convinced, actually, I should retract that — unless we have high faith in the fact that you could be a good programmer. Because the other sort of thing here that should apply to everyone hiring is you won’t know. The best thing we can do is an educated guess.

(10:28): We will never ever have a hundred percent batting average, and it goes in both directions. We’ve hired programmers where I went under a take home test. You know what? It’s alright. It’s good. I had a few points, whatever. That person gets hired, it’s three months in. I’m like, holy smoke, this person is amazing. They just needed to align a little bit and boom. And then there’s been other cases where someone just aced to take home test and we hire them. And you know what? I don’t have the same experience after three months. So best things we do is educated guesses. You can’t make an educated guess unless you look at the work.

Kimberly (11:05): So I’m curious, Jason and David, when in the process do you guys get involved as the founders of the company? I know Jason, we’re going to be hiring a designer at some point soon. Are you guys in the first culling through resumes and cover letters or are you in the very final stages? Are you interviewing these candidates? Where do you guys stand on that?

Jason (11:26): I think, well, it definitely depends on the role. Like Kimberly, when we hired you, I was very much involved in that process from the beginning because the pool of candidates was smaller and it was a brand new role that we’d never hired for before and I made the role up, so that should be my responsibility. Like, visual storyteller. What is this? I don’t know. We’ve never had one, but we think we have an idea of what we want here. So in that case, yes. In the case of designers I used to be involved with at every stage, and I’m not anymore. It’s more like right at the final point now in the last few and only frankly if the team feels like they want my opinion. So I don’t necessarily get involved there anymore unless again, there’s a tiebreaker or someone wants to have my take on it, or if I just feel like wading in and being like, I’d love to kind of go through the final candidates or there’s three people or whatever it is.

(12:22): In fact, the last person we hired, the last designer we hired a guy named Andy. I wasn’t involved at all really because someone here knew him and had worked with him in the past and vouched for him and all the other designers thought he was great, and so who am I to say he wasn’t? So it just kind of made sense that that was the case. So it does depends. On the COO role, David and I, it was just us completely involved because that was someone we were hiring as a peer essentially. And we also worked with an agency or a recruiting firm or whatever they call that executive, whatever that title is.

Kimberly (12:59): Headhunter.

Jason (13:00): There you go. Yeah. So they would bring us candidates and we would review every single candidate that they brought us. So it kind of does depend. Yeah, that’s at least my current exposure to that now.

David (13:14): It’s similar on the programming side. I’m not involved in the initial phase of evaluating the candidates. Actually, now that we have both Bethany and Andrea who are like, this is their role. This is one of the things that they do. They do the initial culling. Again, because a lot of this isn’t even technically specific. You can discard candidates who don’t read your job opening. I have no qualms about that. If you have not read and fulfilled the very basic requirements that we ask for offhand, you will not be qualified for this job. So that culling happens. But then also we have senior programmers at the company do the initial sort of culling it down. And if I’m getting involved, I’m getting involved for the final finalists. I’ll look at the code of maybe five to 10 people at most. And that is for me where I want to get involved. By the time we’ve reached the stage where there’s code for me to look at, I get excited about that, that I can use that, and then I will lean on the assessment of the rest of the team for the other aspects of the role.

(14:24): And I think that also puts pressure on the fact that you should be setting standards for what it requires to be a programmer here at this company all the time. I actually feel like I’m doing the hiring work right now when we’re updating our employee handbook about what’s the difference between a senior programmer and a lead programmer, what’s the difference between a program and a senior programmer? Really digging in on that level and getting aligned with the rest of the team of the rest of senior programmers on what the bar is here is the kind of hiring work that I’m interested in. Then I totally trust that once we see eye to eye on what the definition of a senior programmer is, then that team can apply those boundaries, guidelines, heuristics to finding the right candidates. But I will also say, again, I’ve really come to appreciate the fact that we are making calculated bets and that I can be excited about a candidate that does not pan out, and I can also be lukewarm on a candidate that then does pan out.

(15:35): And seeing that that is actually true across the entire industry, I think is a calming measure that you’re not going to know. You are not going to know. This is why we’ve developed an emphasis on rehiring. So we will hire a candidate by looking at all these maybe thousand applicants, and then the best person that we have, the highest, whatever good feelings, trust in will pan out will get hired, and then we will set it up from the beginning knowing that one year later at the latest, we will do a rehiring decision. Was this the right hire? Would we hire this person again? We’ve also called this Hell yeah, that the bar for staying employed at 37signals, it’s not like, yeah, they’re fine. It’s okay. No, it’s hell yeah. Oh yeah, hell yeah I want to work with that person. No way you’re taking this person off my team.

(16:33): If I go to another company, I’m going to fight to try to get this person on my team. You should be really excited about your colleagues. And having that known upfront by the hiring team I think also gives it a little bit of leeway in the sense that we’re not going to get all of it right. It’s a little bit like software where in software you can try to envision in specific detail exactly what the final product is going to be and you’re going to fail. That’s not a good piece of software. The only good piece of software you’ll find is by writing and interacting with running code. Oh yeah, this thing, this thing, whatever. It’s a little bit like candidates. You got to have good sort of direction on where you’re going and feel good about a candidate, but also have the humility of knowing you can’t pick winners if we define it as someone who will stay at the company long term, you can’t pick winners every single time.

(17:26): No one is that good. No one has that much of a crystal ball. No one knows how someone will transport from one context to the other. This is the other thing that gives me sort of some sense of calm about this. It’s not that we hire someone who looks promising and then for whatever reason doesn’t work out here means that like, oh, we totally misread that person. They’re actually a terrible programmer or not a good designer, whatever. It’s whether it works here. And we are a peculiar company, most companies are peculiar. In some ways, I think we are perhaps more peculiar than most in many ways. And being able to transform yourself from like I worked in a different context and I was able to get traction and make things happen and have an impact there to take those skills and applying them here, you’re going to be a manager of one. You’re going to be asked to run to problems. You can do all these other things where there’s an extreme probably in comparison amount of autonomy here that also comes within the obligation that you got to deliver. Not everyone’s going to gel with that, even if they’re totally fine, great programmers, maybe even or designers that would work out very well somewhere else.

Kimberly (18:34): And on that note, I think when there’s hundreds of applicants, it’s very probable that many of them could do the job. So my question is how do you guys go about finding someone who’s the right cultural fit? 37signals is very unique, and I think anyone who’s listening, who’s a business owner would say, my business is very unique. Finding that person who fits within the culture I think is important. Any tips on that?

Jason (18:59): I think this is why conversations are important with people and also the sample work. Projects aren’t just about the work. They’re also about how does someone respond to the work? You don’t just get the work, evaluate and hire you talk to the person typically about the work they did and why they approached it this way and why they didn’t do it that way. And did you think about this and what if this and what if you had more time? What would you do differently and what do you unhappy about with the work that you’ve done? What would you tweak if you could? If you had a second chance now, what would you change? And you get a sense as best you can of how someone thinks and how someone receives criticism. This is the hardest thing about work is sometimes you’re not going to do a great job and nobody’s perfect.

(19:46): And being able to take criticism is really, really important. I would say that the challenge we’ve had with employees in the past who are really good but couldn’t take criticism well in those situations, it never ends well. You end up walking around on eggshells. Everyone’s afraid of each other. You don’t really want to give someone actual feedback because they’re going to take it the wrong way. And then you’re just sort of tiptoeing around things. It’s not a good scene. It’s not a good place to be. So I think, again, as best you can with a conversation or two, you can get a pretty good sense of how someone is. What would someone be like to work with? How someone handles criticism and critique, how someone can riff and flow, and then you make the best call you can. This is never about certainty, as David was saying, you don’t get it right all the time.

(20:31): We’re not trying to be certain. You want to have a good feeling about somebody. I’m excited to work with this person. They seem very competent, really like their solutions. They’re clever. We’ve had a good conversation. That’s pretty damn good. If you can hit those marks, you got someone I think who’s worth taking a shot on. It’s about playing the odds, but it’s not about numbers. It’s not like the odds are 92%. It’s just like, yeah, have a pretty good feel for this person. And after you’ve been doing this for quite a while, you develop your feel and 20 years in, you hope that you have a pretty damn good radar and the kind of person you’re looking for. And when you find them, you know.

David (21:11): I think there are a handful of techniques you can employ though to increase your gut feeling, your good feeling. One of the flips I’ve made when I’ve talked to candidates is don’t talk about the future. Don’t talk about what would you do so much as talk about the past and specific circumstances. Talk to me about a project that didn’t work out. Let’s go into that. And then you can dive into something that is less speculative, more based on reality. And I find that this is one of those tricks like be backwards looking rather than forwards looking. Again, not that you can’t ask questions about the future, but don’t ask where do you see yourself in five years? Just ask about where were things hard? What was the last project? When did you deal with a difficult project or coworker or client? Try to suss something out about how those interactions went and reveal something about people’s approach, their attitudes as Jason says, can they take criticism?

(22:17): Can they own failures? Are they constantly pointing fingers at other people’s? Are they able to self-diagnose where they were contributors to something that didn’t pan out? And on the upside too, were they able to pan out where they were instrumental or where they really helped and could they be specific about it? I find a lot of the times I get most impressed by candidates who get specific. Again, the whole thing when you do an interview is a bit of a bullshit dance. The applicant is constantly trying to gauge what does this person want to hear? And it’s easier to do that dance if you’re up here in the stratosphere. You’re talking about generics, you’re talking about big, lofty, fluffy concepts. As soon as you get into the nitty gritty, it’s much harder to bullshit. It’s much harder to constantly calibrate what does this person want to hear?

(23:14): Because I’m being asked about something specific. I’m being asked about something that happened. You actually have to be an exceptional good bullshitter to be able to, in real time, alter and tweak every bit of reality as you’re recounting an anecdote or otherwise. And I just find that that has a tendency to expose both the good and the bad and the medium and all this stuff. And then finally, I’d say again, we’re not evaluating individual candidates. We’re evaluating a pool of candidates, and it’s sometimes difficult to articulate why is this candidate really good? What is much easier to articulate, at least from the gut is, is this candidate better than the other? Am I more excited about this candidate than the other candidate? I actually find, which is remarkable, one of the last hiring openings we had for programmer, I think we had 860 applicants. We went through the whole thing.

(24:09): We had 20 finalists. And when it got down to the last three or five that I really looked at in detail, it wasn’t actually that close. I was able to quite quickly look at five candidates and go like, yep, prefer this, prefer this cover letter more than that cover letter, prefer this solution more than that solution. The human mind is such a finely tuned weighing machine. Oh, is this candidate heavier than this candidate? And if you just trust that, instead of having this abstract ideal of, do they meet the bar? What bar? No, no. Your job is not that. Your job is to look at the applicants you got. And unless the search is a total bust, I mean, if we made a programming opening and 10 people applied, you might go like, okay, you know what? That was a failed search. We’re not going to find someone. But if you got a thousand applicants, there’s going to be a handful that are good. And in that handful trust your gut that you can discern which is better or more promising.

Kimberly (25:09): Okay. All great advice. That job position is still posted through March 25th. You can find information on 37signals.com/jobs. And like I said, we don’t hire often, but there’s also a list if you want to get informed anytime there is a new opening. That’s actually how I got my job here is by being on that email list.

David (25:27): Oh really? I didn’t know that you were on the mailing list.

Kimberly (25:29): I was, yeah.

David (25:31): No, that’s cool.

Kimberly (25:31): Wasn’t really looking for a job, and then got that email.

David (25:32): I think there’s like a hundred thousand people on that mailing list now.

Jason (25:35): It’s a big list.

Kimberly (25:35): It’s good.

(25:38): REWORK is a production of 37signals. You can find show notes and transcripts on our website at three seven signals.com/podcast. Full video episodes are on YouTube and Twitter. And if you have a question about, not about for, Jason or David, about a better way to work and run your business, leave us a voicemail at 708-628-7850. You can also email us at rework@37signals.com.