ZubinVoice: [00:00:00] Hello everybody and welcome back to The Easier Said Than Done podcast. And I am so excited 'cause today I've got Aline Lerner on the show. Now Aline is someone that I've been following for a while not just in social media but through a fantastic platform interviewing.io.
ZubinVoice: I used interviewing IO back in the day when I was getting ready for the FANG interviews. And I dare say, that was a while ago. So, you know, it was probably quite a different product back then. But I'm so excited to have Aline on the show because of all the people out there who talk about you know how to get into big tech or how to get into tech, generally.
ZubinVoice: Aline's the real deal because not only is she an engineer by background, she's, you know, moved into the recruitment space, but she uses data. And if you guys haven't checked out the interviewing.io blog, I recommend you do it. Just paying attention to that blog, we'll help you extract the 10% signal you need from the a hundred percent noise out there in the world today.
ZubinVoice: You know? So you can go by Aline's stuff. So Aline, thank you for your time. Welcome to the show.
Aline: Thanks. What an amazing intro.
ZubinVoice: Well, it's all true. I, you know, this is, this is the benefit from having actually followed you for years and [00:01:00] years and years and, you know, appreciate everything you do. Is it, it's effortless.
ZubinVoice: To give you the intro, introduction, I think that you deserve, I probably under baked it as well, to be honest, because just the amount of value outta your blog in your platform is tremendous. So, I will, of course, for those of you excited to, to connect with Aline put Aline's LinkedIn in the show notes.
ZubinVoice: But you know. I did do a very, very quick overview, but I, I think everyone would love to hear from you. You've got one heck of a story. You've been around the traps a while. You've got some real experience. You started well before the world became so tech heavy and influencer heavy.
ZubinVoice: You know, which means you were grounded in reality, the, the world before Instagram, which is a valuable branding. Take us through your journey. Take us through, you know, who you are and how you came to be where you are today.
Welcome to Easier Said Than Done with me, Zubin Pratap, where I share with you the tens of thousands of dollars worth of self development that I did on my journey from 37 year old lawyer to professional software engineer. The goal of this podcast is to show you how to actually do those things that are easier said than done.
Aline: Thanks. I [00:02:00] would love to, so, it's a nice way of calling me old, but that's okay.
Aline: 'cause I am so, I one thing that a lot of people actually don't know about me, that's a fun little tidbit is you know, I, I went to MIT for undergrad, but then I took a bit of a left turn and worked as a cook for three years. And I only really mentioned that. Well, it's, I'm proud of it, but I also mention it because.
Aline: Hiring in professional kitchens is so different than hiring in the corporate world. Mm-hmm. You basically show up in the morning and you know, you bring your knives, they invite you to show up, but like once you, you show up you bring your knives and they show you how to set up the station and they show you the dishes, and then you just work.
Aline: Right? They watch you chop stuff. They watch you prep, and then when service starts, they watch you. Put up the dishes and then at the end of the night, if you did well, they offer you a job. And if you didn't, maybe they feed you and send, send you home. Sometimes they don't feed you. It depends on how, how poorly you did, I suppose.
Aline: But I just thought that was amazing and you know, I, I didn't make that my [00:03:00] career. I wasn't that good at it, frankly. But I went back to engineering and, you know, when I reentered like real work, um mm-hmm. I was really surprised by how hiring happened and I was really frustrated by it. I remember at the company where I spent much of my engineering career we had a guy who worked with me refer one of his high school friends and.
Aline: The guy who made the referral looked great on paper. His high school friend did not. In fact, I think he had dropped out of college and maybe he did community college for a little bit, and then I think he dropped out of that. I, I don't remember the details. It wasn't a resume that a recruiter would probably love, but the two of them had spent, you know, years coding together and writing games.
Aline: So the. Guy doing the referral, had a really good idea of what this candidate could do, and I remember there was so much resistance to even interviewing him because he didn't finish college, and that was just such a turning point for me. So I ended up kind of falling into [00:04:00] recruiting 'cause I just kept noticing these things that irked me.
Aline: Mm-hmm. And I was also surprised that many recruiters weren't technical. Like I thought technical recruiter didn't mean recruiter who hires engineers. I thought it meant a recruiter who is technical. Yeah. And I realized, no, that's, that's not, that's not the case. So. I thought, you know, maybe I can do something cool here.
Aline: I think there's an opportunity. It's clearly broken. So I worked as a recruiter for a few years to kind of learn what they do and understand why it's hard. I ran recruiting at a couple companies. Udacity is is the one you probably would've heard of. Then I started my own recruiting business, and then as I started that I.
Aline: Also noticed that many of my clients would not engage with candidates unless they looked a certain way on paper. Even though, you know, I had, I had started interviewing my own candidates, right? Because I'm like, if I'm gonna put my name, stamp you with my name, I wanna make sure you're good. And I. While I was doing this one, I learned that companies don't care about interview results.
Aline: They didn't care what I thought, which kind of makes sense, who cares what I think? But what [00:05:00] was even more interesting is that candidates really appreciated being able to get feedback during an interview. So that's where the idea for interviewing IO came from. It's like, it seems like engineers want to practice.
Aline: There's so much information asymmetry out there. They don't know what to expect in interviews. They very rarely get feedback in the wild, and I thought. How can we trick companies into talking to the people they should be talking to rather than the people they think they should be talking to? So what if we do practice interviews?
Aline: We'll make them anonymous, and then if people are top performers, we'll make companies talk to them anonymously as well. That's where the idea came from. I've been at this now for. Well, interviewing IO have been out for a decade, recruiting and engineering even longer than that. But the sad to say, like in some ways the world today is even worse than the world was in 2015 when the company started.
Aline: And I can rant about how like, AI is great, but it's also terrible and it's ruining hiring. We can get to that. A lot of the same problems persist today. So we're still at it. Trying to chip away at [00:06:00] this. Giant beast and trying to make hiring efficient and meritocratic and fair.
ZubinVoice: Yeah. You know? So, couple of questions now just going back to the cooking era.
ZubinVoice: You know, you mentioned how it was an amazing thing to watch how they were hiring, you know, and now obviously you'd get thrown outta the building if you came to a tech interview without knives. That's understandable.
ZubinVoice: Contrast the features of what you observed in that, you know, in, in the chef environment selection process and the tech interview selection process to give listeners a sense of why that was amazing, whereas the tech one isn't, you know, let, let's analyze why that is the case.
Aline: Yeah. So there's some similarities and some differences.
Aline: I think both processes started with a resume, but there wasn't really the same obsession with name brands. In the culinary world. I think that as long as you looked like you had experience doing the thing you were supposed to do, you would probably get an [00:07:00] interview.
ZubinVoice: Right.
Aline: And, you know, we you said some really nice things about our blog.
Aline: One of the studies we published that to me was at once a source of a lot of pride, but also very frustrating to see the results is a study where we had recruiters look at resumes and try to figure out which candidates. They should interview and they were terrible at this task. I think that they were only slightly better than a coin flip.
Aline: And we can, if, if you don't mind, we can maybe put the link in the show notes. But the other thing that was wild is you know, then we tried to figure out, well, what do resumes of the candidates that recruiters want to talk to have in common? And. It was just name brands. It was just name brand. Bingo.
Aline: Right. So, they looked at resumes for like, oh, that's, that's not quite the right one. Let. That I have angry posts. Let me find that one, one second.
ZubinVoice: Is this the one that's why your resume is bad, how to fix it?
Aline: Nope.
ZubinVoice: I've gotta say the one that's on the screen, the snake oil, while oil one apps [00:08:00] soly resonated with me.
ZubinVoice: In fact, that's what prompted this podcast. 'cause I'm like, okay, it's time. I have to reach out, lean, like the data is clear. I've been saying this for years to my students. You know, and if you do find the other one absolutely. Lemme know.
Aline: Right? I dropped it in the, in the chat, so you can put that one.
Aline: But I'll, I'll, I can segue into talking about this one as well because there's, the findings from that one kind of inspired the snake oil. And so basically, you know, we saw recruiters are looking at resumes for like a median of around 30 seconds. And in that time they're basically just looking for name brands.
Aline: Mm-hmm. And kitchen's not really the case. One kind of fun. Parallel between the cooking world and the tech world is culinary school is kind of a scam. In the same way that coding boot camps are a scam. Like that was really cool to see. Like, I almost went to culinary school 'cause I didn't know.
Aline: And then this chef that I worked for was very kind and just said like, look, you're just gonna go into debt. And then when you graduate. You're gonna be paid the same as somebody that just walked in off the street. And in fact, you'll probably get [00:09:00] fewer interviews because it's a negative signal, because it means that you're like precious and you think you're like, you know, you don't have the knife skills, but you wanna like influence the menu and it's annoying.
Aline: And I. I think bootcamps are, are kind of similar. In fact you know, I think a semester at culinary school at the time was like the same as a semester at MIT and I'm like, this, this doesn't make sense except when you graduate from culinary school, you get paid like $11 an hour. Well, back in, you know, maybe it's a little more now, but so one of the other big differences is, in culinary interviews, you're just doing the job, right? And at most companies, you can't just bring in a bunch of engineers and have them build features. I think that the. Set up costs for that are prohibitive and it's a distraction and it's not the same. There's a reason why companies don't do it instead, right?
Aline: Many companies have you do these toy problems which I, I have a lot of mixed feelings about. But I think there's just this. Honesty and just can you do the job? We don't care who you are. If you [00:10:00] have the experience, come in, try to do the job. You do the job, you get the job. And I, I wish we could do more of that in tech.
ZubinVoice: Yeah, it's, it's a really interesting challenge. And, you know, I share the bootcamp skepticism. So what people don't realize is, you know, when I was, I was a 36, 37 lawyer at this point in time, in, in. 2017, 20 18, and I came to San Francisco. I borrowed a huge amount of like $50,000 against my mortgage left
ZubinVoice: my family here went to San Francisco for a top rated bootcamp, and I quit after the first week. And I talked about it quite publicly in some of my podcasts, and I quit after the first week.
Aline: I didn't know that about you. That's wild.
ZubinVoice: Yeah. So I, because I was that committed, like I, I, I was leaving the law.
ZubinVoice: My startup had failed. I'd lost so much money in the startup and I'm like, I could go back to the world that I'm safe in you know, and lick my wounds or I could continue down this path and see where it takes me and believe that eventually I'm gonna make it. And by this time I'd been trying to learn to code on and off like everybody else jumping around three to four, you know, years by this time.
ZubinVoice: So I went to the BA bootcamp, San Francisco. So expensive back then, you know, still is, [00:11:00] is it cost me an arm and a leg. And I was at the bootcamp and I looked around and I said, none of these guys. Have actually been on the hiring side. Mm-hmm. None of these folks I looked around at them and said, none of them actually understand how hiring works or how the real world works.
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ZubinVoice: And I was at the bootcamp and I looked around and I said, none of these guys. Have actually been on the hiring side. Mm-hmm. None of these folks I looked around at them and said, none of them actually understand how hiring works or how the real world works. Yeah. And they think shoving a bunch of theory down my throat or, you know, a bunch of really rush coding exercise is gonna make me a programmer. Like there's a big difference between literacy and skill and are not gonna get skill in three months. And so I quit, I lost a bit of money and I came back after the first week and I, and I got myself a non, and I.
ZubinVoice: You know, talk myself here. And that's why the program that I run with my partner Brian, we call it the Anti Bootcamp because there's a whole segment of people out there who are older who can't leave work. Yeah. Who've got kids who've got a busy schedule and they have these ridiculous expectations about what's possible, you know, and how they can earn 150 K straight [00:13:00] up.
ZubinVoice: And I'm like, no, no, this is gonna take longer than you realize. And so we do the private coaching thing where we like. If you are, if you are thinking you're gonna do this in three to six months, you're wrong. Don't join us. This is a long walk because you are doing it part-time. You know, and even then your risks are very high.
ZubinVoice: Even if you were doing
Aline: it full-time, it would still be a long walk. I think that the, the industry absolutely propaganda that all these boot camps spewed really harm the industry. Right.
ZubinVoice: Very harmful to and, and harm futures like there were so many people who tried and quit for the wrong reasons. You know, when all the reason they quit was because they had the wrong expectations of the process and weren't prepared for that, for that journey.
ZubinVoice: You know, and, and it's, it's, it's just tragic. So, you know, which is why I really like your sort of no-nonsense, complete, honest truth. A, a, a approach to it and, and as much of the world will rail against the fact that, oh, you know, if I don't, you know, I don't have a big brand name. I mean, the reality was, I, I, I kind of didn't as well when I moved to, when I moved to Google and even before that, but I had to choose a strategy, very different.
ZubinVoice: I did not go for the big brands. [00:14:00] I went, rode my bicycle around Melbourne looking for the most for the comp, for the software agencies and jobs and dev shops that nobody else wanted to work at that had high churn. Because I figured they needed the people. I needed the opportunity. They had churn.
ZubinVoice: They needed to take a risk in someone to fill the seat and I need, and you know, and they were gonna take a risk in me. And so that's how I found my first opportunities. People who couldn't find other talent. I went there and I became a software engineer for a while. I. Right. I mean,
Aline: that's, that's the way, that's the way what, when I started cooking, I didn't know anything.
Aline: I went to some like raw vegan restaurant that has since become a source of scandal. That's a whole other story. But like, I, I mean, I was like, okay, I'm just gonna go work in this place. I'm not a raw vegan, but I'm gonna learn how to chop vegetables and I'm gonna work for free. And like, that's, you gotta do that.
Aline: Actually, I, as you were talking about law school, you know, I think one of the sad things is. There's kind of this continuum of no credentialing to full credentialing, right. And law is such an established [00:15:00] industry and mm-hmm. It sucks that I think software engineering is sort of headed in the same place.
Aline: Like I, I really want our industry to be meritocratic. You, you know, you have some experience, you walk in off the street, you can do it, do the job. You, you shouldn't have to attend one of three law schools to be able to get a job and to ever have a chance of working in a decent firm. Right. And. Yeah, I.
ZubinVoice: Yeah.
Aline: Hope some of that change in my lifetime.
ZubinVoice: Yeah. You know, it's, it's interesting you say that's a, I mean, when, and obviously my hiring is limited to, you know, my very small corner of the world and my limited experience. And you know, I'm, I'm proud to say we don't sort of go by the credentialing system.
ZubinVoice: Obviously it helps. And the way I try to explain it to students is when they don't know anything about you, some information that rules you out. Is more valuable than information that may rule you in, 'cause it's kind of harder to rule you in. And ultimately, like you look at these DSA processes, you know, the data structures and algorithm stuff, [00:16:00] it, it's not really measuring programming skill.
ZubinVoice: And I think anyone who thinks it is, is, is making mistake, you know, misunderstanding what programming. It's really a filter to say, should we be talking you further? Yeah. Mm-hmm. That's it, you know? Do you have the cognitive ability or the basic understanding that it makes sense to. To try and rule you in for the next round.
ZubinVoice: It's a filter. It's not really an examination of skill in that sense. You know, and, and so lemme ask you, and I'm
Aline: like, I'm, I'm okay with these interviews. I think that they've gotten a little bit theatrical and like commoditized, but like I. My biggest problem isn't with the interviews, it's with everything that happens before you get the interview.
Aline: Like, I wish anybody could, you know, have a chance to like show what they can do. And the fact is that the people that even get to like go through the gauntlet these days Yeah. Be more, much more credentialed in this market. And with the advent of some of the AI screening tools that, that we're seeing.
ZubinVoice: And so given you all these very strong experience and experience based and empirical views, Aline you know, [00:17:00] if you sort of survey your last.
ZubinVoice: In the last 10 years of doing interviewing io with all your recruiting experience, what have you learned? Like, I think you guys in interviewing IO have done what, 200,000 mock interviews. Like, there's a ton of stuff you've got there. So can you give us an overview of what you've learned, what you observed, your hypothesis, and how you try to solve it with interviewing IO and everything else you do?
Aline: Yes. Some of it is gonna be, like a precursor to the interview and, and a little more about job search mistakes. Some of it will be about the interviews themselves.
ZubinVoice: Yeah.
Aline: I think probably the biggest mistake that I've seen candidates make, I. Is not postponing their interviews when they're not ready.
Aline: And I know that has nothing to do with mock interviews or interview practice, but the reason we know this is we often have candidates, so we have a bunch of different offerings. And one of our offerings is something called dedicated coaching. It is the crown jewel. I think in our suite of products, it's amazing.
Aline: Like if you want a specific job title, you can just say, I want [00:18:00] to practice with the person who has this job right now at the company that I want. They're gonna assess where I'm at. They know exactly what the interviews are like. And then they're gonna work with me to systematically fill in the gaps in my knowledge.
Aline: Of course, they're not gonna like give away questions. It's not like gross, but it's like, Hey, you need to have this foundation. You need to know these things and I'm gonna help you figure out, I think there with it, interview practice, it's not just like drilling on stuff. You don't know what you don't know.
Aline: So the reason I mention all of this is we often have our users come to us and say, well, my interview with meta is in three days. Get me a coaching package and we're like, well, why, why are you doing this now? We, we can try, sometimes we can pull that off, but like, that's not a good idea. And then we say, did you know that You can actually email them and say, Hey, I need some time to prepare.
Aline: And most candidates don't know that. And then they're terrified that if they actually try to ask for more time, the [00:19:00] interview is gonna get taken away from them.
Aline: But the reality is that except for like 2022, where we saw a bunch of hiring freezes. That's not really, it's a black swan event. That doesn't really happen.
Aline: These companies are hiring all the time.
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Aline: But the reality is that except for like 2022, where we saw a bunch of hiring freezes. That's not really, it's a black swan event. [00:20:00] That doesn't really happen.
Aline: These companies are hiring all the time.
Aline: Recruiters of course, are gonna apply pressure because they get rewarded for putting butts in seats and it's their job to apply pressure. But if you push back and you're like, look, I just wanna put my best foot forward, I wanna be prepared. They will be okay with it.
Aline: Some, some exceptions, like if you're talking to a really small company and they literally have one open head count and they need to fill it, they're gonna fill it without you. But you can get a feel for that and ask some questions. Which brings me to the second biggest mistake, which is for some reason candidates are scared to ask recruiters questions or, or whoever they're.
Aline: Whoever their contact point is, like ask what's gonna be covered in the interview. A lot of our users are like it's a technical interview. Okay, great. Especially at smaller companies where there isn't a stand, we know all the. We know processes for like 50 different companies like that, but some of them are not on our list, and they're like, well, it's a technical interview.
Aline: Well, okay, is it gonna be system design? Is it gonna be algorithmic? Is it gonna be a code review? Is it, I, I don't know. Like, well, you can ask. Yeah, absolutely. [00:21:00] Yeah. So those, those are the big mistakes. There are a lot of. Negotiation mistakes that people make that I won't get into here 'cause I can probably talk about that for like two hours.
Aline: But I would love it if we could link to a blog post about the mistakes people make. And most of them are before you negotiate, basically you shouldn't tell recruiters anything. You should ask them all the questions, but don't answer their questions. Like there's I can actually drop the
ZubinVoice: that's all right.
ZubinVoice: I'll find it. Oh yeah. If you have it. If you know exactly.
Aline: So. Please read that. And if you're inter, actually, if you're interviewing with meta like if you do nothing else, just please, please read this blog post. Please, please, please. So negotiation aside, when it comes to the actual interview I think people are generally under prepared.
Aline: Yeah. And I think they underestimate. The value of practice or they're too scared to actually start practicing because they know they're gonna fail their first few interviews. One of the [00:22:00] surprising, well, when you think about it, it's not that surprising, but senior engineers actually do worse in their first mock interview on our platform than juniors
Aline: by a lot because chances are juniors just did an algorithms class or they've been drilling when you've been in the workforce for years, you're not doing this stuff unless you have a very specific kind of job. And I think people often stay in jobs they hate for a really long time just because they're dreading having to do these interviews.
ZubinVoice: Yeah.
Aline: So I think just like practice, it's not that bad. Everybody fails. Yeah. I wanna say about a quarter or a third of like, the very top performers on our platform fail their first interview. It's just
ZubinVoice: a hundred percent. When I was leaving Google, and I've been very public about this, I, I failed my first two or three 'cause I was just not warmed up.
ZubinVoice: I just did. And also they were looking for very different things and I'd gotten to the Google way of doing things and, and all that. And pretty much everyone I knew who was [00:23:00] leaving Google at the time, and people who, you know, a year after that got made redundant. Okay. All one, all the engineers I knew didn't do so well in their first couple of interviews as they got warmed up again.
ZubinVoice: 'cause they hadn't done it for two or three years, you know, and, and they didn't practice properly. They needed some warmup rounds and that's fine. Like, you know, the odds are I keep telling my students this. I said, the odds are all, and if you take one interview, the odds are always significantly against you.
ZubinVoice: Mm-hmm. The more interviews. Yeah. It's like flipping a coin. The better you all get and the better you get at handling it and the more warmed up you get and that's okay. That's just normal, you know.
Aline: I think on average, depending on the candidate, I mean it's different, but across all of our users it takes anywhere from like five to 10 interviews to start consistently passing.
Aline: Sure.
ZubinVoice: For sure. And that's very
Aline: self-serving to say, 'cause we sell mock interviews, but we also have free mock interviews on our platform. We have like peer to peer-to-peer, which are surprisingly good. Yeah. And. I don't care. You do those right. Don't, don't give us a dime. But if you're, if you're gonna interview for real, like over, but [00:24:00] you know, like there's this saying where, if you're trying to get a message across to a group of people, repeat it like three times and then repeat it like three more times. And then maybe like, and I think interviews are the same way where just over, over budget. Not financially necessarily. Just in terms of time investment. Yeah.
ZubinVoice: Well, and that, that's exactly what, and I keep telling my students exactly what you say about, you know, I know the kind of interview.
ZubinVoice: 'cause I'm like, you know, depending on how you slice it, there are about nine to 14 different types of interviewing processes and, and flavors to this. And you have to know which game you are appearing to. 'cause if you, you know, turn up to a billions game thinking you're gonna play, you know, a pool, you're gonna be in trouble.
ZubinVoice: You know, it may look the same, but it's not, it's actually quite different. And, and likewise with interviewing, I, I tell my, my, my mentees, what we try to get them to is between two to three interviews per month. And then I'm like, and that's a three month process. If you can maintain that run rate. Then you're doing fine because you need that level of velocity.
ZubinVoice: But to get two to three interviews a month when you're, you don't come from a no name brand or you know, when you come from a no name [00:25:00] sort of background, you don't have the big brand is extraordinarily hard to do. And to do that, you need to build your credibility and signal in the market. And even then, a lot of people are gonna say like, you don't have the big brand behind you, or you don't have the big college behind you.
Aline: That actually reminds me of another mistake. And ties back to resumes and credentialing a little bit. I think so many people agonize over what their resume looks like, like fonts, and you know, layouts and whatever. And the reality is that if you have big brands on your resume, or in some cases niche skills, like if you have machine learning experience, just make sure that's really visible to recruiters.
Aline: That's all you need to do. If you don't have those things, don't spend time on your resume because it's not gonna get you in the door. And then just change all your. Put all your effort into outreach instead. Yeah. And outreach.
Aline: You
ZubinVoice: said that this, I think you said that in this blog. Yeah. From right spot on.
ZubinVoice: So inspired by that I put a LinkedIn post el Sorry, I didn't mean to interrupt you there, but you, [00:26:00] I put a LinkedIn post then and I think I tagged you in it as well. And even now. It was half and half. About 50% of people thought that optimizing your resume, resume would, would keep improving. And I phrased it very clearly.
ZubinVoice: I'm like, you know, at some point in time is optimizing your resume kind of pointless versus getting out there and doing outreach, 50% of people thought the resume is the answer. You know? 'cause it, yeah, we
Aline: do that a lot. And I think it's not helped by the fact that when recruiters do resume reviews, they're like, oh, you need this skill.
Aline: It's about skills. But when they say skills, it's actually code for brand. And that, that sucks and it takes time to figure that out. Like we've worked with many recruiters in the past who've hired through us, and they're like, and we, part of the reason we've always insisted that hiring be anonymous is because recruiters will start saying, oh, your candidates don't have the skills we're looking for.
Aline: Well, which skills? Oh, oh, you mean brands? Sorry. That's what you mean by skills.
ZubinVoice: Right.
Aline: So it, it sucks. I'm trying to think of like mistakes people make when it comes to the actual technical interview. I think, one of the biggest ones is [00:27:00] trying to memorize. I mean, I think memorizing questions will get you through phone screens.
Aline: Yeah. Probably. Especially at companies where you can find the list of questions. Yes. If you memorize all of those, you will probably get through the phone screen. Yeah. But you will not do well in the onsite if you don't understand. And in fact that was one of the main drivers for. Writing a sequel to cracking the coding interview.
Aline: Because the original CTCI was huge. Yeah. But at the end of the day, it's a list of problems and questions. Correct. And you need more. You need more in this market, you need more,
ZubinVoice: a thousand percent. And I, I, I've had a, I've been on a podcast where I have the, the original cracking the coding interview.
ZubinVoice: And I said, to be honest, I didn't really go through it because I found that what we needed to do in the market that I was in is quite diff, you know, was a few notches above that. So, and we will talk about your work on beyond cracking the coding interview. Question for you though, because you know, having been on the hiring side, I have a view on this and that is, [00:28:00] you know, how hard is it to I.
ZubinVoice: If you were to try to get candidates to empathize with how hard it is to actually go through 600 resumes, right? And, and to think about that when they're trying to apply it, what would your advice be to them?
Aline: Do outreach, like it's a, it's a losing battle. I. At the top of our discussion, I kind of alluded to AI being harmful and, and one of the main ways that I think there, I mean, AI is amazing, right?
Aline: But I use, I use all sorts of things every day to make me better at my job, but when it comes to hiring, I. I think it's being used in the worst ways to perpetuate the status quo. So what I've been seeing, and this is not all companies, large companies, actually, I think one of the misconceptions is there's some kind of like a TS filter you have to get through.
Aline: And at many large companies it's just people looking at resumes. But ironically, at some smaller companies where there's less oversight, right? And less worry about compliance, they are using AI [00:29:00] tools to potentially stack rank candidates and. What they look for is you know, before it was, you could maybe like.
Aline: Search the PDFs for specific skills, but now you can dig your heels in and say, show me candidates who have worked at fang or FANG adjacent companies who have been on this specific team, who have had this many promotions in this many years. And it's idiotic because these smaller companies are not getting these candidates applying, but they just think that if, if we can just filter this pool of people better and better and better, we're gonna make these hires.
Aline: And what ends up happening is that. You take all your existing biases, which, you know, we've done analysis where you worked matters a little bit. Not that much. Not that much. That's not a thing. Yeah. Oh yeah. When we looked at the resumes of our, and LinkedIns of our users and tried to see which attributes were the most predictive of strong interview performance, surprisingly it was doing a lot of MOOCs like.
Aline: Not [00:30:00] just, you know, having certifications, but actually like listing. I've taken all of these classes, like, so if you've done a lot of computer science classes on Udacity and Coursera and you're serious about it, that's generally a much stronger predictor than having worked at a thing. Another one was like, not having typos on your resume was a stronger predictor than where you've worked.
ZubinVoice: Aline can
ZubinVoice: also said. Listing a bunch of certifications. Certifications, yeah. Al.
Aline: Yes. So, what I'm referring to isn't necessarily certifications, but like some people will just list the courses that they've done and that's a little bit different. I also think some certifications are created differently than others.
Aline: I remember the triple bite certification if if you remember them
ZubinVoice: yeah.
Aline: Was actually like a positive signal. And they were one of our big competitors, so it pained me to admit it, but we admitted it. They did a really good job of vetting candidates. But the problem isn't even necessarily with the certifications themselves, it's [00:31:00] that the candidates who list certifications, not just courses, but certifications
ZubinVoice: Yeah.
ZubinVoice: Tend
Aline: to be candidates that don't have other things. And. There is some correlation between never having worked at a good company and, and you know, not being as strong. But I think the, so we certainly like AWS certifications a my a plus, like all of those are garbage. A lot of the, and I used to work at Udacity, but like a lot of their like career boosting certificate, like they used to teach students and then they changed to like doing ongoing learning.
Aline: Yeah, like those, those are not very good. But what ends up happening when you list certifications is recruiters. Start looking at them and they're like, oh, this person is listing all this stuff. It means they don't have anything else.
ZubinVoice: So even if the
Aline: certifications are good, it actually ends up perpetuating yet another bias.
ZubinVoice: Yeah. Yeah, a hundred percent. So, and, and this is, this is why I tell folks, guys out there, please keep [00:32:00] reading the engineer I blog because you are gonna get so much data driven insight that is counterintuitive and these are the potholes that you need to try and avoid. Or the, the flaws in thinking that seem obvious enough, but.
ZubinVoice: And could be quite harmful to your, to your effort to, you know, get into it, whether it's a top tech company or any tech company. Understand how, you know, human beings work. Psychology does interplay with this. Celine, question for you. Now, you are working on an or have built the AI interview. Would you wanna tell us about that?
ZubinVoice: And given your mixed feelings about AI's impact on the, you know, human behavior and recruiting, what's your vision here? What's your hypothesis and what have you done?
Aline: Yeah well, so. First, I don't think that AI interviewers are going to replace human interviewers anytime soon. Not just because they're not as good as a good engaged human, but because I.
Aline: Everyone's so obsessed with making vetting more efficient when they, and they forget that hiring is about selling, right?
ZubinVoice: Mm-hmm.
Aline: So much of getting to talk to a human and a peer and [00:33:00] another engineer in the interview process is like learning what they're working on and learning what kinds of people work at this company and what they value not.
Aline: Mm-hmm. You know, in the corporate value sense of the word, but engineering values, like is it more pragmatic? Is it more, you know. Hacky and that's, you know, different people want different things. So I think that the best engineers even in this market are just not gonna be okay with doing completely asynchronous assessments.
Aline: I think they're gonna wanna talk to a human and smart companies will let them, because that's a selling vehicle.
ZubinVoice: So let's just context for the folks a little bit. When you say an AI interviewer, what, what are you envisioning or what, what, what comes to mind?
Aline: Yeah. I think it's a great practice to, and that's, that's where we're that's where we're putting some of our effort right now.
Aline: We. We did this as part of writing the book. But we also had a version of it before we started the book. I think that so much of asynchronous practice these days is lead code. Yeah. And people are so, and lead code is a wonderful tool. Like, I mean, anybody that's preparing for these interviews should spend some time on lead code.
Aline: [00:34:00] Like, it's silly not to, but I think people overuse it and they grind way past the point of diminishing returns. And they also get really, really used to having test cases written for them and having something evaluate their code.
ZubinVoice: Mm-hmm.
Aline: We actually, so when we built our AI interviewer, which we're trying to make it like a midpoint between lead code and a good human, and I think we've gotten there and now our AI interviewer has every problem from beyond cracking the coding interview and it's free.
Aline: And I would love to share that link, like anybody can.
Aline: When we shipped it originally, our intent was let's have something that feels like a human fang interviewer. So the AI interviewer will ask you to explain your thought process. It will ask you follow up questions. You're gonna have a discussion before you ever write code. Maybe then you implement a Bruteforce solution.
Aline: It'll ask you, you know, if you can optimize it. It'll mirror the steps of company technical phone screen, and when we first [00:35:00] shift it. Users were irate that it didn't provide test cases for them. And it was like a fun UX puzzle for us to solve. And we changed it from practice with ai interviewer to interview now and making some of those copy changes.
Aline: And then just saying at the beginning, this isn't lead code. This is meant to Really? How
ZubinVoice: interesting. Again, expect Yeah. So the expectation was more, hey, this is more like a lead coach as opposed to you like, no, no, this is a, a simulation of a real world interview. Every other
Aline: piece of feedback we got was, where are my fucking test cases?
Aline: It was legitimate because we, like, people had a certain expectation based on other AI interviewers they had seen. But we are trying so hard to get away from that and to have people practice. Explaining their thought process and to write code, ask questions.
ZubinVoice: And I wanna tell people this. What Elenes saying here is so important, folks, because a lot of people think that just [00:36:00] practicing on lead code is a simulation of the deeper process.
ZubinVoice: And I can tell you now. Having done this so many times and having interviewed so many people, there's a huge jump between what you do from the comfort of your study and armchair on lead code and what you have to do in an interview process. In fact, the best, the, the best way to illustrate this was, I can't remember who it was, there, there was a, I think, some competitive bodybuilder or something who said that it spent two years training in front of the mirror doing his squats or his lifts, and on on, on game day.
ZubinVoice: He had to face the audience, and that completely threw him off because he didn't have the visual feedback. And he's like, I didn't do a great job. My form was not great. And so the next year he spent, he didn't do well, and the next year he spent practicing without looking at the mirror. Right. And, and the reason I'm giving this example Alene and, and for the others is you have to, if use the AI interviewer to practice.
ZubinVoice: How you would go in a real human kind of interaction, not just how you would go lead code, because there is a another step [00:37:00] past lead code, which is your, your cognitive state during an interview, your interactive index. During the interview and I, when I interview, I'm always looking for people who show their collaborative as opposed to people just like, yeah, yeah, I can do that.
ZubinVoice: This crank out stuff quietly. I'm looking to know how you think, how you involve me, the kind of questions you ask. Are you happy to admit that you're not quite sure about something and you like some input? Because that's a signal to me, because then I can trust that you will ask for help and you need it, and I'm happy.
ZubinVoice: My job as an interviewer is to help you do well, not screw you over, not try and, you know, cancel you out in any way. My job is to say, Hey, can you do this job? And I'm gonna help you try and show you can.
Aline: About interviews is that it's a collaborative exercise meant to see if we can be smart together.
ZubinVoice: Yeah.
ZubinVoice: If it's a, if you're a good interviewer, that's what, if you're a good
Aline: interviewer. The, and, and you know, we talked earlier about how like the technical interview format gets a lot of flack, and I said I have mixed feelings about it. I think the biggest reason we get so much vitriol is because interviewers are [00:38:00] bad.
Aline: And that's, that's a whole other can of worms. But there so many interviewers that are not engaged that. Yeah.
ZubinVoice: Yeah. And I've never seen any company properly incentivize good interviewing. They train for it, but they don't incentivize it. They incentivize it.
Aline: Yeah. We've actually, we spent like a year coming up with the right metrics to track because our livelihood as a business depends on having the best interviewers.
Aline: You know, there are a lot of other mock interview sites now. We were the first, but now there, there's a ton. And our MO is like, our interviewers are the most senior. They're the best, but then we have to. Walk the walk. So we track engagement and calibration and all of these other things because we are financially incentivized to do that, and we throttle out bad interviewers.
Aline: I, I wish companies like I've published, I'm like, Hey, these are the metrics. Here's how you do it. Anybody can do this. Like, we figured it out. You, you to make some adjustments for real interviews, but it's, you can do it. Companies track stuff where like. It comes from the top and [00:39:00] there's some kind of engineering leader that is just passionate about interviews.
Aline: And you find those people sometimes and they like get into the a TS and they're like, okay, close rates on this and this, and then downstream upstream. And they, they, they, they get into it and it's so rare, like most know which of their interviewers are scaring candidates away. Which of their interviewers are too strict or too lenient?
Aline: Yeah.
ZubinVoice: I, I've seen this at Google as well, and I've told people, I said there, there I, I've shadowed interviews when I was training for interviewing the, in the Google Way, and I've shadowed interviews and I'm like, there is no way I would've got through if this person was interviewing me there, you know, way too hard, way too pedantic, or the bar is not, can you do the role?
ZubinVoice: The bar is, can you do what I can do? Which is not the bar for hiring. You know, this is not a, can you, do you know what, I know this is, it should be a, can you, can you do this role effectively as opposed to doing what I can do? But no, a lot of interviews do that. And, and then frankly, a lot of interviews don't like taking the time out for them.
ZubinVoice: It's an interruption, it's a burden, you know, and that influences their psychology during the [00:40:00] interview, their attitude during the interview. They're
Aline: not engaged. Like you're, you're not gonna get good signal. You're not gonna get the candidate's best work. And you're not gonna sell, like you're, so you, you've done like, it's probably better to just not do anything at that point.
Aline: At that point. It's probably better to send them to an asynchronous ai.
ZubinVoice: Exactly. Exactly. So, so look, I'm, I'm really looking forward to having that link and sharing it with folks. Any advice for what. To set their expectation on how to use the AI interview. Like, you know, what sort of timeframe, what sort of cadence what sort of practice loop should they be doing with it and, and how to get the most outta,
Aline: I would say like if somebody's starting from scratch, start on the code, right?
Aline: Get to the point where you're crushing EAs and you know, you can kind of do mediums. And I'd say at that point, probably move to an AI interviewer. I. And start combining that with doing mock interviews with other people. Mm-hmm. I think [00:41:00] that a week on lead code by yourself is probably equivalent to one interview with an excellent, well calibrated, engaged professional interviewer.
Aline: These interviews aren't cheap. You know, you can, again, get a lot of the way there with a peer not, not as well, but at least like do a few professional interviews sooner rather than later. Because you're gonna get that feedback. They're gonna say, okay, spend a week you know, working through like these hash map problems spend, and like, you're weak on this, you're strong on this, you're actually not gonna see these kinds of, you know, people are obsessed with dynamic programming.
Aline: And I know right?
ZubinVoice: Less, not
Aline: that much. Like I think meta is prohibited from asking them, if I remember correctly. Or people get upset with upset obsessed with like. Red black trees, and it's like, you're never gonna see that. You're never gonna see that. So just like talking to an expert is good, but start with lead code.
Aline: I'd say use our AI interviewer sooner rather than later. Because it's gonna give you a feel for what [00:42:00] it's like for realsies without the pressure and without the financial investment. And then move to human on human mocks.
ZubinVoice: Yeah. And, and also Aline, given your vast experience in this space. A, a very sort of threshold question for, for people is, I guess, guess it's kind of depends on geography, but the question is, should everybody be assuming that DSA is part of the interview process or not?
Aline: You should not assume that. I think that it's not always the case for two reasons. One is smaller companies. Often don't do that and for good reason. And it's a shame when very small startups blindly copy what the fangs do, expecting the same results. It's a cargo cult. Yeah. But I think clever, smaller companies will maybe do a little bit of algorithmic stuff and then most of the interview will be not that.
Aline: So that goes back to like, just ask, just ask what, what to expect. And they will, they will tell you if you do interview with [00:43:00] large top tier companies, you should still expect a good amount of data structures and algorithms questions. But with the advent of cheating tools, I think companies are moving away from maybe not the format, but they're moving away from asking questions verbatim, right?
Aline: From, you know, some. Popular question list on, on lead code, and I think that's actually a very good thing.
ZubinVoice: Yeah, a hundred percent. I, I think the more sort of, higher up the totem pole. The tech companies, the more program or the more effort, internal effort goes into not recycling questions. Mm-hmm.
ZubinVoice: You know, like at Google there's, you know, lists and list of questions. We couldn't, couldn't ask because they'd been leaked. They'd not, you know, stuff for that. Like, it was, it was very much, people are coming up with questions on the fly pretty much every month just to say, we can ask it this way, we can ask it this way.
ZubinVoice: You know, just to add the variance. And, and that sort of, you know, it's the competitive arms risk between the knowledge that that leaks out into the world and, and the, you know, the hiring bar they need to have. Now, one last thing [00:44:00] for you before I let you go, 'cause I've taken up quite a bit of time is
Aline: actually before we do the last thing, there's one thing I forgot to say that I think is important.
Aline: We talked a lot about DSNA questions, but that's generally the phone screen in a small part of the onsite, right? A lot of the onsite is system design and behavioral questions
ZubinVoice: and
Aline: those. Unless you perform really poorly on them then you won't get an offer. But if you perform okay, they're not gonna be used to determine if you get an offer, they're gonna be used for leveling.
Aline: Yeah, correct. And there's so much down leveling happening. So like I would just make sure to budget time in your prep for system design, but I'd say like, do your DSNA prep bundle all your phone screens together, then tell the company I need time to prep. Then you practice for the onsite and then you do the onsite.
Aline: And the onsite is gonna be SIS design. And you know, behavioral needs less practice, but you gotta have good stories. Yeah. We have all the, like we've, we've seen the gamut of, you know, people preparing and most people just prepare DSNA and then they're blindsided by [00:45:00] some of the other things.
ZubinVoice: Yeah. You know, it's, it's interesting you say that.
ZubinVoice: So I'll just put this link up here as well. When I was preparing for Fang, I wrote a basically my, all my study notes in detail into a system design book. And I swear it was because of this that Google said, we need another round with you to level you. Exactly. They said, just, just 'cause Shirley knows what she's talking about.
ZubinVoice: They did another round to level me and bumped me up a level based on my system design. In a performance, right? Because I've done this sort of in intense handbook for myself and then I publish it. And that's just to go, folks, don't overindex on adjust the DSA stuff. Like I, I'll be i'll, I said this publicly, I did not actually finish my DSA.
ZubinVoice: Portion in the 45 minutes I was given for Google. I didn't finish it, I came close. But the interview and I spent a lot of time talking about edge cases and, and possible ways to sort of solve this problem. And I think that's the signal my interview was looking for is I don't care if this person completes it.
ZubinVoice: What I care is, does this person know enough to intelligently approach the problem and [00:46:00] evaluate it? You know, you a good interviewer. I've often said that, and so much of this is luck. Like. I had a great mother. I had a great education. You know, on the day that I went to Google, other people who would kick my butt weren't there.
ZubinVoice: You know, I didn't show up for the interview. I had a great interview. Like, it's so much lock stacks up into this, right? Like, that's just life, you know? So, what can you do? So yeah, so tell us about beyond cracking the coding interview, your you know. Your involvement in the project, what prompted that?
ZubinVoice: And, and, and why it's now timely?
Aline: Would love to. So CTCI is a classic but it's increasingly outdated. I think when it first came out, having that list of problems and solutions was revolutionary. Yeah. Completely revolutionary. You know, as I got to know Gail on working on this project, she's like, yeah, I wrote this PDF, and then it just like took off and I was like, what?
Aline: So. Unfortunately for today's market, we need more, maybe [00:47:00] fortunately for us 'cause we got to write a great book. But I think there are a few things that are different. One is it's not enough to just apply to companies anymore. It's so much more competitive. You have to know not only how to get in the door at companies, but how to actually manage your job search.
Aline: How do you time prep? Right. How much solo practice do you do? How do you time outreach to companies with actually doing your prep? How do you think about negotiation? And negotiation actually starts before you ever have a recruiter conversation. It's not just the stuff at the end. All of these things are, are so much more important because the market is much more competitive.
Aline: So the part of the book that I wrote was kind of what we call the squishy stuff. So it's the first a hundred. 50, 160 pages and it's everything. We actually have nine chapters. Chapters,
ZubinVoice: I was gonna say that. Yeah, I did go through that. Yeah.
Aline: And they include seven of my chapters and then two technical chapters, which are slightly when in binary search.
Aline: Hopefully that's the correct link. Let's check. [00:48:00] Yes. Okay. So that one reason was just like, Hey, let's p put people in the driver's seat of their job search and let's teach them like what companies are actually thinking and, and how to manage it. The other reason. Is my coauthors. Were really passionate about teaching people to think instead of memorizing.
Aline: And that was the main thrust of the book. It's really, even with their non-technical chapters, it's teaching people how to critically think about interview processes and hiring, and then also teach them how to critically think about data structures and algorithms. It's a long ass book. I think it's like 640 pages, if I'm not mistaken, but is.
Aline: I think it is the best in depth resource on data structures and algorithms, interviews and managing a technical job search. It doesn't have system design in it. Maybe we'll do a follow up book on that, but we wanted to write it because we. The original just wasn't cutting it in, in this [00:49:00] tough market.
Aline: Yeah, a
ZubinVoice: hundred percent. And, and what's your view on, on the ability to update books fast enough to reflect the market? How do you feel about that?
Aline: I. One interesting thing, thing that I learned in the process of writing this book is you can actually, you know, Amazon is our printer, publisher, whatever, right?
Aline: And you can update, you can make small changes to the book. Like, so as people have started reporting bugs. We've been able to make changes in real time to the PDF and then as new, you know, they print it just in time. So, of course the bigger stuff, you know, I think you, you put out follow up additions.
Aline: I, one of the questions we get a lot is, well, is everything going to be out of date? Because AI is completely going to change interview processes. I don't think so. I think that learning how things work under the hood is going to be. More important now than ever before because AI advances. Yeah.
ZubinVoice: No, and I, I, I, I share the same view.
ZubinVoice: So either we both right, or we both wrong. But I shared the same view that, you know, it's there are certain [00:50:00] fundamentals and meta principles that have more to do with economics and that explain the job search process. It's all, all market force. Correct. Exactly What I tell people, this is a market dynamic.
ZubinVoice: This is not a technical thing. This is not a, you know, this is pure market dynamic and Exactly. You said it's sales. It's sales for both sides. Right. Both sides are selling in an interview, and this is why I keep telling my my students. I said, you have to think of this as you are a startup in a competitive market.
ZubinVoice: You're launching yourself as a product and they have alternatives. This is a market dynamic at play, right? This is pure market dynamic and you have to market yourself the right way. And so, you know, so great that CTCI has got that update because I, the squishy stuff is absolutely critical because too many people dive into action and busy work without laying out the plan.
ZubinVoice: And it kind of doesn't matter if you're directionally wrong, no matter how much work you do, if you're heading south when you need to head east, you're not gonna get there. It doesn't matter how fast you run, right? So, fantastic. I really, yeah.
Aline: One thing I'll say about it too [00:51:00] is we have, the book has, I think 250, 230 or 250 problems in it.
Aline: None of them are in the original CTCI. Maybe there are a few classics in there, like N Queens, but they're all original problems just for this book. And the really cool thing is that we've opened it up. So without buying the book, anybody can get all the problems in the book and the solutions just by logging into interviewing io.
Aline: And of course you can work them all with our AI interviewer. And there are like another 50 secret problems that AI interviewer has that the book does not.
ZubinVoice: That's fantastic. See, this is actually freely accessible now.
Aline: Yes. So if you go to the second URL, I link you to BCCI slash problems. Yeah. All yet, like you have to make an account.
Aline: But then you can access all the supplemental materials for the book and all the problems and solutions that are in the book
ZubinVoice: as well.
Aline: Wow. Isn't that sick?
ZubinVoice: Okay. Sorry. Let me just, I [00:52:00] think I accidentally pasted it back to you instead of putting it as a bank. Wow, that's fantastic.
Aline: There it is. Yeah, like I, I'm so proud of the work we did here and I hope people find it.
Aline: Valuable all the problems and solutions in the book.
ZubinVoice: And I, I've gotta say, you know, yes, at one level it's harder to, you know, the market's different, it's more compared true. But look at the kind of tooling we have now compared even seven years ago when I was starting out. Like it's just the opportunity and the problems grow together, you know, it's fantastic.
ZubinVoice: I get excited about stuff 'cause I'm like, for every problem there's a new or better solution now. And this is clearly tremendous, you know, it's tremendous. It's well done. Good.
Aline: Thanks. It was awesome to work on this and I'm, I'm so excited that people seem to like it so far.
ZubinVoice: Yeah, no, it's, it's fantastic.
ZubinVoice: It's, I'm really impressed that, you know, folks can actually get access to the problems. There are a new class of problems. There's more meta, meta principles involved. The AI interviewer now helps you actually interact with them rather than just reading them or typing them out, [00:53:00] like it is a completely different rehearsal.
ZubinVoice: I, I, I keep thinking about how, you know, in the fifties. Sports people used to be just physically fit, work out a little bit, you know, do that, do that sport and go back. And now they're doing blood work and they're doing nutrition and they, you know, calibrating everything. Like everything's changed. The sport is more competitive, excellence is higher today.
ZubinVoice: That's a really
Aline: good analogy. Yeah, absolutely.
ZubinVoice: You know, and you need to calibrate across the process, which is, you know why Brian and I spent 12 months of people calibrating how they think, calibrate, you know, because thinking is really important. The wrong thinking with the right effort will s produce the wrong results.
ZubinVoice: You know, sometimes so, and I mean, it's unlikely we'll do the right effort with the wrong thinking anyway. But we have to calibrate everything, their mindset, their, their, their moods about things, their expectations about the things their, their time audits. Like how are they using time? Most people are so surprised by how poorly they end up, you know, using time and they're already busy with kids and family.
ZubinVoice: You know, like you have to calibrate all those things and then you have to do the right things at the right time in the right order to the right degree so [00:54:00] that you then can compete. Like there is so much calibration involved and people don't realize it, you know, so it's great. I'm so excited about this.
ZubinVoice: You may actually have made, been the first person in the last seven years to temp me to get back to you to doing some of these problems. Aline. I never thought I'd say that. Alright. Let us know how it goes. I'll, I'll well, thank you so much for your time. You've been so generous with it. And most importantly, thank you for all the work you've done in the last eight years.
ZubinVoice: I personally have benefited from, from that a lot. So this is a personal thank you, but also on behalf of the audience thank you for this because those who are lucky enough to, to learn this and I gen, I mean this genuinely. We'll have an edge simply because it'll fix some of the incorrect expectations assumptions that are so, so dangerous and so lethal to so many people's plans.
ZubinVoice: Because what you don't know, what you, what you don't know, you don't know is likely gonna trip you up much more. And now you know that a little bit. So thank you Elaine. Thank you for your time and thank you for this work. I'm really excited for what happens and beyond the CTCI. Thank you. Thank you.
ZubinVoice: Alright. Thanks for joining the show and I'll see you next time.
Aline: [00:55:00] Alright.
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