Episode 120

Guy Nicholson Defining the Best and Worst Interviews and Balancing Tech and Humanity in Hiring Practices

TIM: We are live on the Objective Hiring Show today. I'm joined by Guy. Guy, thank you so much for joining us. Welcome to the show.

GUY: Thank you very much, Tim. Yeah, nice to be here.

TIM: It's absolutely our pleasure. And I'd love to start just by hearing a little bit more about yourself. I think this will help our audience understand who they're listening to today.

GUY: Yeah, absolutely. I'll try not to go on too long. Yes. So I've been involved in data analytics and data platforms ever since I left university too many years ago to count now. But yeah, I've been involved with data and data systems from Oracle 7, up to Hadoop and Snowflake and cloud technologies and everywhere in between. So yeah, a good background and spread on technologies infrastructures and the uses of data in, in, in different organizations from banking to retail to healthcare. And many more in between.

TIM: and throughout your career. I imagine you've experienced a lot of interviews on both sides of the table as a hiring manager and as an interviewee. I'm wondering. Do any particular experiences stick out in your mind throughout that your career so far is especially good or especially bad?

GUY: Yes, yes, there is a starting with this one. So yeah, I have a. An example of the worst interview I've ever had, as in I attended, but it was also the best interview I ever had.

TIM: Oh wow.

GUY: cases. Yeah, it was interesting. So I was applying for this many years ago now, but I was applying for a database data services manager role. A company and I turned up for my interview, and I met my hiring manager, and any usual welcome, shake hands, pleasantries seem to seem like a very nice, personable bloke. So that was a good start. Then they went to an interview room, a small room, probably big enough for two, maybe three. And all that was in there was a small table and a whiteboard. And as soon as I saw that whiteboard, I knew I was going to get asked something. Now this is a really, a top tip for people that do That are hiring out there that may be watching this. You can't do this. You should never do this. You should never let a candidate come unprepared and unaware of what you're going to ask them to do. It's not fair. So at that point, my heart dropped at that point because I didn't know what to expect. And before I even sat down, he handed me a pen, a marker pen. And he goes, I'm just going to grab the room for 10 minutes. I want you to think about something, anything, and present it to me. And I guess it's like most things, and it left at that point. I'm there holding this pen, and I'm looking at this whiteboard, and absolutely nothing would come into my mind. I think it's when you're under that kind of pressure you go, What on earth? Yeah, it was very interesting. So about five minutes of those 10 minutes. I could not think. of a thing to do. My anxiety levels went up. I was thinking, do I even continue this? Do I walk out? I was not happy. And then I grabbed onto a bit of an abstract idea. For my sins, I'm a Sunderland fan. And at that time Paolo De Canio was our manager, and he was On the verge of getting the sack, and there was a lot of rumours and stories coming out of these very strange eccentric management styles of the players. And coming into an interview to be a data services manager, I'd be managing a crew of BI analysts and engineers. There's a lot about that management. So I decided to title my presentation The Madness of Caolo de Paneo, and I focused on how bad management practices and the lack of bringing synergies and how not to treat everyone the same and how everyone is different and to keep those synergies together. So basically an entire presentation in less than five minutes on that premise and reflected that and how I wouldn't do that managing my own team. So I managed to scribble some bits and bobs on the whiteboard, and in comes this guy, which I managed to present. And I managed to, yeah, pull it round, and they offered me the job without me walking out of the building. Best and worst interviews. That, that was it. One for, worse because it was the most unprepared and very stressful situation to be put under, but good because I managed to pull it off and managed to get the job. So yeah, that was my best and worst 2.

TIM: Even knowing that you had been a Sunderland fan, I didn't think you were going to tell a story about Paolo Di Canio. Now, was the interviewer some mad Sheffield Wednesday fan? Did he just happen to mention his god from his childhood or something?

GUY: No, I don't think the chapter of him was a particular football fan. I don't think so. And luckily wasn't any rival supporter. So I got away with that one. Yeah, that was, it was an interesting interview.

TIM: And this was quite a while ago in your career. If I remember when Di Canio was in charge of Sunderland. It was more than ten years ago, was that right?

GUY: Yes, it must have been about 10 years ago now. Yeah, indeed. Yeah, I learned several things from that. One, never to do that to anybody else. Okay. I always ask, is there going to be any tests or presentations or anything asked from me when I attend an interview to make sure I try and avoid that in the future?

TIM: Now, as you've alluded to, Paolo De Canio may be a bit of a mad genius in some ways. A bit crazy, for sure. Maybe more crazy than genius. Is there anything to be said for the craziness of this interview question? Is it, or the interview style, does it have any merit in, I don't know, maybe if they're interviewing for a super creative role or something like that, would then it make sense, or do you feel like it's not just, we shouldn't be interviewing this way?

GUY: Now, I don't think there's anything particularly wrong with the ask being able to tease out what they were trying to tease out of me: what's my communication skills like? What's my presentation? Can I communicate up? I'm assuming they must have. Actually getting the role, being in the role, I found out that they had problems with somebody doing that and being able to do that. There's nothing wrong with that premise. What I think was the wrong way to approach that was having a candidate underprepared, not expecting that at all. Yeah, a brief give, give some prep time, I think, is only fair, I think.

TIM: Yes, I agree, and certainly that's how we run interviews. As soon as you start telling that story, though, I thought of a kind of similar experience I had as a grad going for consulting, like a management consulting position with, oh, it's one of the big ones, Bain or someone like that. And I remember getting into the interview room and the two interviews were in there sitting down in a big boardroom and they just handed me a small piece of paper with all these colored lines going on in various directions. They handed it to me; they said, You got five minutes. Tell us a story. You get a point for every interesting thing, and they're standing next to the whiteboard, and they tallied up points. Now, I somehow out of nowhere pulled out this story about Mardi Gras because Mardi Gras was about to happen in Sydney. It was all these colored lines, and I went through this whole story about this person coming out, and their whole life improving and all this kind of stuff. After five minutes, I was a champion. I had that job. I'd gotten like 30 points from all this stuff I'd come up with. But then the rest of the interview, unfortunately, was a case study around the strategic ATM placement, which I completely bombed on. So I had the opposite experience from you, where it started really well and then nosedived from there.

GUY: Yeah, it's quite, it's from a candidate's perspective, it is quite interesting how sometimes during the interview, but certainly afterwards, it's been my experience that when you come away thinking, I've nailed that, I've done really well. Actually, it hasn't been the case. The ones I've come to, that was really tough. I struggled there. I don't think I came across very well. Actually, I've done right, I've done really well, and I've had positive feedback. So it's, you never can tell no matter what you feel, whether you've done well or not. Getting that feedback is the only way to really confirm it.

TIM: Yeah, funny you say that as well. Again, if I think back, the last job I went for, which was 10 years ago, I called the recruiter afterwards. I said 100 percent no, like they hated me. He said, Oh, they're pretty cagey guys. Like they don't show their cards. Like, I wouldn't really write it off yet. I'm like, No, seriously, death in there. It was like a funeral. No chance. I've got the job. I got the job. I worked there for four years. Those people are now my investors. So you really can never tell just based on that. The kind of characteristics of the interviewer, but yeah, when it comes to interviews then,

GUY: moment,

TIM: your experience as an interviewer. So we're talking about giving the candidate some time to prep, not having some ridiculously anxiety-inducing, stressful experience, or anything else that helps to get the most out of the candidates. Because I feel like part of the job in an interview is to almost unlock what's there because they're going to be so nervous. They're not going to be showing themselves immediately. They need to feel comfortable. Like, how else do you think about. it? Doing a great interview as an interviewer,

GUY: It's a great question, right? And looking back on the way I've done it, how I did it once upon a time, it's not necessarily how I do it today. It It evolves and it changes, but the kind of golden rule of thumb that I try and use is to try to make it as informal and as relaxed as possible. That's not always, you can never not, always accomplish that, but it's. The way I'd like to do it is, and I've seen some of the following similar patterns from other people, is that usually there's a, if you like the look of somebody's CV, you think, yes, that might be worth the conversation. I always, and I've seen others do this as well, have an initial, very short conversation with the candidate just to see whether they translate and how they get on. And within five minutes, whether you want to call this person to an interview, I won't be going through their CV, and I won't be asking them questions. It really is just sit down, try, and relax them. And the first thing I always say is this is informal to a process. Ask me what you want to know about the position. I'll give you some background from that conversation there. I have to see whatever interests me from the CV. I'll call them in then for face-to-face, and that face-to-face, always try and make it to be as relaxed and informal as possible. That's, yeah, that's it. It helps. It helps.

TIM: and it helps because you're getting closer to the truth of who the candidate is and who they actually are as a person and their actual skills rather than seeing this kind of masked version of them.

GUY: Yeah, absolutely. People always have a guard; they always have an expectation from reading a job description, what it is that you're after, and quite often, more often than not, the job description doesn't tell you what gives you a flavor, doesn't give you the context. It's about, yeah, creating a rapport quickly because no matter what skills and experience a person has got, and obviously you're looking for some of those to be able to fulfill the role, it is so much about an individual and how they can communicate. It's more of that than the skills, and quite often. I find that is what people are looking for because it's such a hard thing to find, that balance of being able to be personable, being inquisitive, being confident in communicating, as well as being able to understand the data analytics structures and coding. Yeah.

TIM: So yeah, part of the goal is to help the candidate relax, just having a conversation, all chilled out. I was chatting to someone else about this just last week and they mentioned something that I hadn't really thought much about before, which was In an online interview, the candidates normally at home, maybe in the home office in their bedroom, whatever it is, pretty relaxed environment compared to What this person described is, a lot of interview offices or interview rooms in large corporates at almost like a sterile environment. He thought of them as feeling almost like a doctor's waiting room or something, which is not the vibe you want to go for. If you want to have a relaxed candidate, is there almost something to be said for them? The benefit of an online interview, certainly at the early stages, is just to help a candidate chill out, relax, and be themselves.

GUY: I think so. I think it's so important. I wouldn't do that. I wouldn't do any interviewing without doing that process first. So now when we come to our second one, I always set the expectation at the end of it about what the next stage is going to be and what my expectations are and try and put them at ease as much as possible. They know what we're walking into; they've now known me; they've talked to me, so they have that report once again when we meet, and we can chat, and hopefully that just takes those anxiety levels off a little bit. Very, everybody's different in what their anxiety levels are, but if you can help reduce that, it just makes the next step of getting to know them and drilling down a little bit easier, I find.

TIM: There's something to be said also for interviews themselves, which I think most hiring processes would have interviews at their core. As an evaluation tool, I'd say mainly interview performance is the dictator of whether or not the candidate gets hired. Yes, the skills test, psychometric test, and maybe the CV, but really you need to do well in the interview to get the job interviews. There's a certain segment of candidates for whom interviews are just going to be hard, and a segment for whom it's going to be really easy. Extroverts, very personable people who are very beautiful, are on average going to perform better in interviews than crippling introverts who aren't really the most sociable people. Is there a danger that we almost over-index on interviews as a tool, thereby sometimes marginalizing a really valuable segment of candidates who might be amazing individual contributors, super smart, but just a little bit awkward, a little bit shy, a little bit antisocial? What do you think?

GUY: It. Yes. And it's something I'm always really super conscious of. Typically, and I am being stereotypical a little bit here, in data and data engineering especially. You've just described the majority of people that are in those jobs. And some of those people are so good, so talented that my experience is you can't, you've, that's the bit you've got to draw out in an interview and being a candidate, it's the bit you've got to let go and show, don't be frightened to show a little bit of vulnerability because you do have to sell yourself a bit, but hopefully the person that's interviewing you has a similar background and will be aware of this and dig in because, yeah, I've had a few, I can think of a few people straight off the top of my head while the first 10 minutes has been such an awkward, really difficult time. introduction to the interview, not getting good feedback, very short, succinct answers. And I've kept at it because there are certain things that are coming out that are really true. And a little bit of digging, a little bit of persistence, some of those people I went on to hire and rehire as I've moved on. It's very hard. It's very hard because if you take it at face value, you might be missing a trick of someone absolutely golden, but it's, yeah, it's the interviewer's responsibility to try and tease that out. But as a candidate, you've got to be willing and able to show that bit of vulnerability and just be honest and be yourself because that's what a lot of people want to see through, really.

TIM: If you noticed, if, and talking in broad generalizations here, teasing that out is just inherently going to be easier for you as an expert in the domain you've worked in for many years in data.

GUY: Absolutely, I do, yeah, and I wouldn't. Follow that as a particular practice. I know I've worked In organizations where they have their own recruitment process and some of them are quite militant about it even about following that process, but it Where I would bring that on board is at the very end; I would make sure that it's a candidate. I'd want to I'd want to put forward for a HR interview or a non technical person interview especially if it's around fit and culture that they might have some great feedback but in terms of, is this a good candidate? Yeah, it has to be that domain knowledge has to drive that forward a hundred percent.

TIM: I'm struck by an anecdote about our CTO, who has actually been with us for years. He used to. Head up technology at a substantial business in Southeast Asia, and he just joined this company, and he's going to do recruitment, a lot of recruitment of a lot of particularly software engineers. And it's got the HR team internally there, and they said, Oh, like we'll take care of the initial screening for, we'll do the CVS screen. We'll do the first interview. Okay. Yeah, sure. But like, how are you going to screen them? What are you going to be looking for? How are you going to do this? And they pushed back a bit, and they eventually said, Look, we're going to filter out the weirdos. So you don't have to speak to them. That's what they said. And his point was like, hold on, these are software engineers. What are you talking about? They're probably the best ones. That's the last thing you want to do. And so I can only imagine how many technically brilliant candidates might have fallen by the wayside through time by going through interviews. With interviewers who just didn't have the knowledge or skills, or even maybe the empathy in that sense, to really find those amazing candidates.

GUY: I would be surprised if anyone follows that process that managed to recruit well, yeah, absolutely. It's not something I would do.

TIM: What about AI? It's the buzzword of buzzwords. You mentioned you've been working in data for a long time. You've seen some big trends; you've seen big data, this and that. Is it overhyped or underhyped? What's your kind of general view of large language models, let's say, just to drill into that element of AI?

GUY: It's an interesting one; I get asked a lot. I get asked a lot about both from friends and people in the industry, and it's a difficult one to answer. So I get asked, Oh, you're going to be out of a job; coding is going to be done by AI. No. I can't see that happening, to be blunt, not in my working lifetime anyway. Can it help? Can it make engineers and coders more efficient? Absolutely. And I can testify to that firsthand. Being able to solve a problem, being able to get a second idea, especially in a world now where a lot of work is remote, you don't have a chap to your left and a lady to your left, to your right, who can, you can ask. Being able to have these AI assistants, large language models, definitely does accelerate and enhance. Productivity. Yes. And will that improve? Yes, I think it will. Will it get to a point where it is replaced? I, not in my work, in my time. I don't think. Can it? They can create programs, but they'll always need maintaining. And you'll need someone with that expertise to be able to maintain debug it and, and improve that. I cannot see that landscape being able to do yet.

TIM: For the coding use case, which seems like probably one of the leading two or three use cases of large language models that I've seen, probably content generation would be another; maybe not the best quality content, but still can write a lot of stuff. What do you see as the gap now in the code generation specifically? Like, why wouldn't we be in six months? Just here you go. This entire product was written in AI code. A human hasn't read anything except the prompts. The actual code has been written by Claude or what have you. What do you feel is the sticking point at the moment?

GUY: I think it's been being able to use those effectively. I think there's still a very small. percentage of people that know how to interrogate these modules to get a prompt, if you like, to be able to train the model to be able to get the output. Effectively, I think people are still finding their feet and learning the best phrases to use, the best terminologies to use. It may even result in you getting a very niche. A set of skills and candidates that can interact with it. They know how to do it. It's almost like opening a Word document and writing it, writing something yourself. It becomes that natural to them. But I think, I don't think we're there yet. I think a lot of people that I work with and talk to as of yet don't have that. Experience and exposure to be able to effectively prompt to be able to do that, to high quality and to a standard where I think you would be, you could release it, self-made from the model itself. I think the skill sets are still being defined, and we're not there yet, at least from my experience anyway.

TIM: I wonder if one of the challenges also is context. Like in a big code base, in a massive system, you've got many files that an LLM would struggle to really bring into that full context to make any change. Maybe it's going to be better off with a kind of simple little tasks in a really simple microservice kind of program, but some huge thing, it's just, it would need such a huge improvement in its context window, whatever it's called, to be able to do anything effectively. Perhaps that's part of the limitation.

GUY: I think that's a fair comment. I think you're right. I think in small modules, self-contained microservices perhaps can have more legs than some very tightly integrated, big, large code bases. You could ask it to change a certain function, but it might not understand the dependencies or the impacts of those changes. Very well, I don't feel. So yes, I would agree with

TIM: I have to say I did see a video today of Claude's new coding tool. So they, I know they integrate into the cursor and it's been part of that platform, but now they've built out their own, I don't know, called Claude coding or something. It looks amazing. I know every demo looks amazing, but it did seem to be a substantial breakthrough, not that I've used it myself. And I'm also conscious of the fact that technology is just moving so quickly; seemingly, improvements are really very fast. So maybe we will get a sudden breakthrough. What about AI and hiring specifically? Have you had an opportunity to dabble with? Are there any kind of AI tools as part of the hiring process, or have you seen perhaps candidates use them when going for jobs?

GUY: It's a great question. Have I noticed candidates? Have I looked at a CV and gone, This is ChatGPT, this is not so much, not yet"? I haven't, or if it's there, I've not picked it up. Have I used AI to whittle down initial candidates again? Not so much. I've resisted it. Even though I have been recruiting and I have a large number of candidates, which. We'd say we're going to a different conversation where I think that's going, but I try and resist because I've been on the other side of it as well, where I know I've read, I've researched a job description, I've researched what they're after, and I would, I'm just such a good fit, I'd fit that, I cannot understand if I wouldn't, somebody wouldn't want to talk to me because my skills, my experience tie so well to that. And then you get a standard rejection, and you know from that rejection that it has come from an AI model. So something has gone through your CV or your covering letter and not scored you high enough to warrant a conversation. And I think they've missed a trick. So I'm conscious of that on the other side of the fence as well, where, again, going back to that experience of using and understanding AI, we have not yet mastered what we need to say, how we need to pronounce it, and how we need to structure it for the AI models to be able to pick it up and reflect it. It's a definite miss. I can see it being really beneficial if a lot of larger organizations really do have thousands of applicants or hundreds of applicants. You do need to whittle it down to usable. A usable amount, but you're going to miss decent candidates doing that. Definitely, it is something to be very aware of.

TIM: What about later on in the hiring process, for example, like an interview assistant? So maybe you're still doing the interview, but it helps with transcription, summarization, and maybe pre-filling the scoring template based on what it thought the candidate performed against certain questions. But you're still in control of things. What about something like that?

GUY: That would have value, especially for perhaps a second or third line interview for transcripts. Yes, definitely. Absolutely. Absolutely. Saving one of the first great instruments Frustrating things for me when I often interview somebody, especially if I think they're coming across well, are that I'm writing notes, my head's down, rather than engaging and looking up with the candidate. And I know from being on the other side of the fence that when that happens, you don't know whether I'm writing positive things or negative things, and it stops that interaction, and it can cause anxiety and other things as well. So having. If you're doing a remote session, similar to what you and I are doing now, talking, something is recording our conversation, and then at the end of it, summarizing it. I've actually used this. Yes, absolutely, that's 100% a win. And things like that we should be making real active use of, definitely.

TIM: Yeah, I agree. That's a total no-brainer. It's also just saving you some brainpower. I don't know about you, but it's pretty hard to really focus on what somebody's saying and their body language. Remember what you're trying to be asking them, write notes, keep an eye on the time, and evaluate their answers. It's actually a really hard cognitive load in an interview as an interviewer or interviewee for that matter. And yeah, just passing off one of those jobs to AI seems like a no-brainer, and having a recording, actually having a transcript, how good are our memories at remembering what people said at best 50 percent properly accurate? So we've always got the transcript to go back to. I tell you what, I would love that as a candidate, actually, if I ever got access to that, because. I don't know about you, but how many times have you been in an interview process and hiring managers maybe describe the role in a certain way or floated a few carrots in your direction that might not actually eventuate? But having an actual record of that would be, I think, quite compelling to candidates, not that companies would necessarily give it to them.

GUY: Yeah. You make an interesting point there, and one, I think, where we, it does take some consideration, especially where my head of data hat is using these AI tools and transcripts, yes, can be beneficial and used correctly and used responsibly is something we should be embracing, definitely. However, you've got to be careful because the transcripts are recordings; it's personal data, and that needs to be treated accordingly from wherever you use this. And if you don't, you don't have that defensive setup or at least thought process. You might get unstuck, especially if you get someone who's taken exception to perhaps something you've said or the way it's come across. It can be very dangerous as well, and that kind of thing. And that's, although there's a rush and a clamber to use these AIs, we've got to be careful and remember that we've got to treat this data responsibly. And also, what defensive posture we need to do. It is important that we keep that in mind. Good.

TIM: It's that way because suddenly then I thought from that kind of defensive mindset of let's make sure we treat candidates right, let's make sure we treat them right. We don't ask them anything we shouldn't ask them. Let's make sure we don't discriminate within an interview. Actually having a recording of the interview then removes the he said, she said kind of issue. I know in the United States, it's apparently reasonably common for a candidate to get rejected through the hiring process for some reason and then pursue the company through the particular government body they go through. Like, it's a standard thing that a big company would be dealing with. I don't know, five or 10 of these at the same time. But if you had a recording, maybe then you would have the evidence to prove, hopefully, that you haven't done anything wrong. So maybe there's some kind of

GUY: Ay.

TIM: perspective.

GUY: Yes, there is. There is some upside that you just, I think it's just a case of being prepared and making sure that you're using this technology in a way that you can control and understand, but yeah, you're right on that side of things. It could help, and being able to have, how long am I going to hold this for? And, if someone does ask for it, is it handled? Is it to go through a life cycle? There are things like that. You do have to consider. And I think it's easy to forget with these technologies that you do have to have that responsibility as well around the data itself. So you use it but think about it and be careful as well.

TIM: Yes, and it is such a complicated legislative landscape because there's all the data privacy frameworks for one, but then there's all the hiring frameworks as well. Even down in some cases to a city level in New York City, they have their own. Automated employment decision tool rules, which basically means if you're a company and you have a job ad and it's shown to any candidate in New York City and they apply, you're beholden to those laws, which is most multinationals in the world probably fit that category. And it basically says, if you have in any part of your hiring process any kind of automated decision tool. For example, a CV screener, automatic interview screener, AI interviewer, and skills test sometimes. Suddenly, you're subject to this law. If you don't do certain things, it's like ridiculously high penalties. And that's just one city in one country. So yeah, I'm sure a lot of companies are probably reluctant to dive into AI hiring tools, even if they are actually technically great. I'm sure they're coming along because it's just such a complicated framework of laws they have to adhere to.

GUY: And I think that'll get more complicated as this goes on. I wouldn't be surprised, and I can see companies out there using AI CV screening tools and capabilities. Now, I do foresee at some point that you are going to have to give feedback on that. process. I could see that happening. And that might be a good thing because, like I mentioned before, when you think, she's such a close fit, this sounds like this job description has been written for me. And you don't even get conversation. It's not an initial chat. You can't understand why getting that feedback or scores in the AI engine scored you at 70 percent because you've not covered x, y, and z. What great feedback to have. Yeah, I don't think the infrastructure and the capabilities for that exist yet, but I can see that being a case where they're going to have to do that at some point. And that'll be, if you use the tools, you've got to, you've got to be able to feed back to a person. I definitely can see that coming.

TIM: Yes. And I feel like from my perspective, that actually is one of the big upsides of moving away from human-based resume screening, which is still far and away the predominant. Style to some kind of automated screening, because then, of course, the system has to have some kind of rule logic that it knows about, and it's exposing to its users. Is it not just a case then of also sharing some of that feedback with a candidate who's been rejected? As opposed to the current scenario now, where it's like a human logs into the system, checks the CV for six seconds, and presses reject. Or, the company gets halfway through the process, shuts down the role, and auto-rejects a thousand candidates. You would have no idea as a candidate why you've been rejected, to your point before. If we're actually recording that and the AEI has done some kind of scoring, then just pass it on to the candidate as well. Wouldn't that be amazing?

GUY: It would, and I'm hopeful. I think it will end up going that way, but I'm hopeful it will as well. I think that would be a good thing to do, especially at the minute where the market is so competitive. And you see a lot of a lot of a high number of candidates applying for roles; it must be really frustrating and disappointing for a large number of those candidates that don't even get any feedback whatsoever of what they need to adjust to change or move forward. Absolutely. That would be encouraged.

TIM: Yes. Speaking of that actually, so yeah, a lot of candidates are seeing the LinkedIn roles with a ridiculous number of applications and a lot of competition. It's very challenging out there. If you were going for a role now yourself, it's going to be tough. Would you still be applying through LinkedIn into job boards, or would you be trying to, I don't know, leverage your network and kind of get a foot in through some other means?

GUY: Actually, I was thinking about this morning, Tim, this very subject. I was thinking about that, and LinkedIn has just made it so easy to apply for jobs. The downside to that is it's become a bit too easy. And that, we're talking about AI models and CV screening automation as a result of that, which, again, we've talked about, has its pros and cons. Yes, I would be more reluctant now to apply via LinkedIn. I would rather find that somewhere else, be it a network or a different job. Advertising avenue. Absolutely I would, because I would; it would make me feel that. I, a person, am going to at least look at my CV, and I'm at least going to have a fair crack at talking to somebody, which is key. That's the first big hurdle of any interview process: getting that face-to-face communication. So yeah, it would put me off. It really would. And it would also put me off advertising the roles I had on there as well. And I only see, at the minute, I only see that getting worse. So maybe there's something else out there because there's not something for an opportunity somewhere. Yeah.

TIM: Yeah, I feel it's great to have these open platforms where, in theory, anyone can apply, which is great because then it's not as old boys or girls club, where you just like jobs for the mates or whatever. So that's fantastic. But if anyone can apply. And so then I'm sure you're on the receiving end of a lot of highly irrelevant resumes from people on other planets almost that have no relevant experience at all. It's just almost like dealing with spam. And so that's not helping you as a hiring manager find the great candidate either.

GUY: Indeed, I find, and I find that really strange, even to this day when I've had that happen, someone's applied for a data engineering job in PostgreSQL, and somebody's applied that, that's done HTML. Coding. Yeah, I don't get it. I don't understand it, but it happens, and I think all it's doing is making the process for someone to find that position much more difficult.

TIM: Yes.

GUY: And I don't see it as the current situation. I don't see it as sustainable; something does need to change, I think.

TIM: Yes. Yes. Something needs to change. Could be AI; could be something else. We shall see. Guy, if you could ask our next guest one question about hiring, what would you ask them?

GUY: Good question, difficult question. I mean it; I would probably ask them. Do you see your hiring process changing from how you've done it in the last 12 to 18 months? And like I mentioned before, how I used to recruit, how I used to interview, it's changed so much because of the landscape, because of the social landscape, because of the technology landscape. How do they see it? I'm really super interested to know, I think, how they're going to adapt in the next 12, 18, or 24 months. I guess that would be my question. That would be something I'd like to know.

TIM: Excellent. I will level that at a guest sometime probably early next week, and I'm also keen to hear what they'll say. Guy, it's been a great conversation today. I've really enjoyed it. Thank you so much for joining us and sharing your insights with our audience.

GUY: Gotcha. Thanks, Tim. Thanks very much.