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The AI Gold Rush Is Loud. Impact Is Quiet · Fractional Frequency

• Erin Todus: But the time just flies. And thanks for being flexible rescheduling. Last week, we I think we were supposed to record and we ended up having some business travel around an event. So it would have been ⁓ pressed on our side, but really excited to get into the conversation today. so we've got our brief up, but I think I saw you in the dock ⁓ just a few minutes ago. So you've probably had a chance to take a look through it, but we'll we'll just take a quick swag through, and then if you have any edits. Ahryun Sone Moon: Yeah. Whoa. Erin Todus: ⁓ please feel free to chime in and we can we can make those. So we'll start with the intro. I I'll take this part and I'll probably mostly read it word for word, but I may throw in that I have worked ⁓ with a couple of companies that have used Good Time and just ⁓ make it a little bit more conversational if if you're okay with that. And then we'll dive into the first segment, which is all about your founder story. So we've got a few just kind of broad questions in there. That get at your inspiration and some of the maybe big sweeping lessons learned so far. And then we'll spend a little bit of time next on the economic climate and sort of your adaptation and what you've had to ⁓ maybe flex or change in terms of your thinking and how you're running the business to stay ahead in this market. and then Amy will dive in and ⁓ have a couple of questions for you on the AI sort of hype ⁓ phase that we're in right now and ⁓ pick your brain a little bit on that, ⁓ and then transition into like real impact. So there's so many ⁓ players or people attempting to be players in this space right now. Like, what's the difference between something that looks good on the surface and something that's actually effective? ⁓ so we've got a few questions there. And then at the close, we'll do something a little bit different. We'll typically ask a few quick hit questions that are centered around like leadership advice and things like that. But given you have this one click scheduling ⁓ vision that is upcoming on your roadmap, we thought we would make the last few questions all about that and just get your thoughts on like what's that going to going to look and feel like once it is live. Are you okay with that? Okay. Ahryun Sone Moon: Yeah, that one's Erin Todus: Anything, ⁓ any questions, anything we haven't covered that you would like to cover in the conversation? Ahryun Sone Moon: ⁓ No, I think it's comprehensive, so it's good. And since this is recorded, you can edit it if there's a portion that I go back and do it again type of thing, you can edit that, Okay. Amy Crook: Yeah. Yeah, we can do that. Erin Todus: Yeah. We have we have an editor that will automatically pull out the ums and ahs and stuff like that. So don't worry about those things. If you say something that you really don't want to say, just say, can we scratch that? And then ⁓ we can kind of pick up the conversation and cut that little bit out. Ahryun Sone Moon: Yep, sounds good. Erin Todus: Okay. All right. ⁓ well, I think we have started the recording already. ⁓ so I will just do like a little three, two, one and we will just get into the conversation beginning with the intro. If everyone's ready to go. Amy Crook: Ready to go. Erin Todus: All right, three, two, one. Today's guest is Arian Moon, founder and CEO of GoodTime. GoodTime is a company that helps organizations transform recruiting through automation. And I've had the pleasure of working with her platform in a couple of different capacities with various clients. So really excited to learn more about that today. ⁓ Under Aryan's leadership, Good Time has built technology that dramatically improves recruiting efficiency by eliminating scheduling bottlenecks and streamlining interview coordination at scale. Aryan is passionate about the future of work and has dedicated her career to simplifying complex processes through technology. We'll talk about how automation is reshaping talent acquisition, what recruiting leaders should be thinking about as AI becomes more embedded in hiring. And how organizations can create more efficient and effective candidate experiences. So without further ado, welcome Arjen. really excited to have you. And and as we usually begin in these conversations, I would love to dig into your founder story. ⁓ so tell us what originally inspired you to build good time. Ahryun Sone Moon: Welcome. Yeah, definitely. So I'm Ahryun one of the co-founders and CEO of GoodTime. We started building GoodTime early on, I think it was back in 2016, so it's almost a decade ago. The three founders were really into automating processes, which really bogged the team down. And at that time, one of our co-founders, Jasper, who's our chief public officer, So working, that was me, right? I'll go again. Yeah. So the three founders who were the three founders were very passionate about automating processes that really brought the team down. And one of our co-founders Jasper, was our chief product officer used to work at Yelp. Back in 2016, Yelp was really tiny. was like 150 people. Erin Todus: Okay. Ahryun Sone Moon: thousands of employees. He was kind of along that journey at the beginning for a few years and he really saw recruiting team really struggling with the amount of interviews that they had to deal with and just so much manual work that had to be done. And that became an inspiration and we did something stupid. I don't know if I would do it again, but all three of us were living in San Francisco at that time, decided to quit our full time job. Jasper actually quit Yale Paul. So we decided to really ⁓ focus on this problem and bring a solution to the market. So that's how GoodTime was born. Early on, was in order for, because none of us actually came from recruiting background, we decided to embed one of us in early customers. So I worked for three of our early customers and actually worked as a recruiter, worked as a recruiting coordinator and talent operations. Yeah, in order to kind of learn the day to day pain, which we translated into our product eventually, and that became good time. Erin Todus: And it is very painful without a product like Good Time. ⁓ for anyone who's not ⁓ had a go at scheduling an interview with no good tooling or platform, it's a web of emails, calendar appointments, Excel spreadsheets, et cetera, et cetera. It's very hard. I love that you just embedded and rolled up your sleeves to do that job for several months. That is such a cool ⁓ start to your journey. Ahryun Sone Moon: Absolutely. Erin Todus: ⁓ and so this kind of leads me to my next question and and maybe something or some things that you learned during that time. What were maybe ⁓ an early assumption or two that did not hold up in the early days as you were building? Ahryun Sone Moon: Yeah, that's a great question. So early on, this may not be true now, but early, early on, what we decided to build was more automation, more hand-off type of automation. And we thought by building more of a hand-off type of automation, it will bring even more time back to the team and so on. But we realized actually the software actually has to build trust with the users. over time. So we actually built in different workflows within the system that is there's obviously, you know, maximum automation, but also there's kind of kind of gradual workflows where ⁓ the users can actually have more control over. And then once they gain enough of trust in the system, then they can eventually get to the full automation. But we realized that change management was actually really huge. And without that, it's really hard for people who are using, like you mentioned, Excel sheets, Gmail, calendars, and so on, to jump from that to full automation without really having trust in the system. that was the assumption ⁓ and mistakes that we made early on. And we kind of built different workflows. where it gives different varying level of control to users. Erin Todus: Yeah, that's genius. ⁓ you know, and I think there's maybe not enough credit given to the weight of some of those interactions, even simple ones where you're interacting with a candidate, it builds the experience, one ⁓ sort of interaction after another. And it's actually really delicate in a lot of cases. And so I can understand where the user would be sort of hesitant to give up ⁓ the reins on that and love how you've thought about that. It's almost like from a human psychology angle and the way that you've you've designed those touch points. Ahryun how would you say your identity has evolved? You said it's, you know, it's been 10 years now, which is, you know, I think forever in a lot of these contexts where you're building and scaling a business. what has changed about your identity ⁓ over those 10 years as a founder? Ahryun Sone Moon: That's a great question. ⁓ Something that's evolving constantly, frankly. Early on, actually, I worked with the three founders. We had our roles. So I did front-end engineering, So I made all the UI and UX and stuff like that. Jasper did product and design, and Peter did more of the backend coding at that time. ⁓ I love that, actually. I love using technology. I love building something with my hands. And then that really evolved over time. And I think really my identity has become someone who, this actually I share to another CEO that I talked to, he kind of share a similar sentiment that you end up becoming someone who spots a problem and then helps the team get over those hump and kind of brainstorm and solve those problems together with the team. And then you move on to another problem and another problem, because the company is full of challenges and problems that you must solve for and overcome in order to get to the next level. And there's really no defined role for CEO. think at the end of the day, you kind of define your own role at the moment that you are in and in the situation that your company is in. And the most dire problem that you must solve, you must help your team. solve that together with them. So I think sort of that's become my identity of like someone who's kind of investigating and solving problems with the team. Erin Todus: Mm, that's so interesting. I think that, you know, from outside looking in, people might assume that a CEO gets to decide maybe where they spend their time or what problems they work on, but it sounds like it's it's just the opposite, right? You're following ⁓ sort of the direction the company takes and and responding and anticipating as quickly as you can. Ahryun Sone Moon: Totally. that also, but also you're kind of setting the direction of the company, also building relationships with customers. Those are kind of given, but I realize I spend a lot of time. There's a really big issue that we need to solve together. Let's huddle. Kind of like, what is the Toyota way of kind of solving problem? Like if there's a big problem, we kind of pause everything, huddle, solve it together type of thing. I think I spend quite a lot of time on that. Erin Todus: Mm-hmm. I love that. And I think, you know, there's there's no shortage of problems to solve really in any environment. But ⁓ most listeners would agree that the economic climate today and and certainly for the past one to two years has been really complex and different from what we've seen ⁓ certainly in the 10 years before. So I'd love to pick your brain a little bit on that. What has maybe changed about your decision making in this climate as compared to previous ones? Ahryun Sone Moon: Yeah, that's a great question. You're in a really interesting environment, I would say, because before it was either predictably bad or predictably good. You can kind of see where things are going and the progression of the economy was kind of forecastable, unpredictable. So in that situation, you can make decisions. Like if it's predictably bad, okay, let's spend less, right? Let's, you know, tighten your belt. Let's spend less hunker down. If it's predictably good, let's invest. Let's take some risks, right? Let's do products that you will not have done in a bad, you know, ⁓ worse environment. Now what's really making it difficult for business owners to make decisions is because of the uncertainty. You just never know what's coming next. What makes it even worse is it feels like you're bracing for impact and then the worst doesn't happen. Amy Crook: except the cums. Ahryun Sone Moon: Yeah, it's okay. It's just so weird. It's like you're bracing for a punch and it just never comes. Then you brace for a punch and it never comes. things are actually not bad. But it almost feels like something bad will happen in the future. And that uncertainty makes it so difficult for business owners to try to expenses because something bad will happen. Amy Crook: Yeah. Ahryun Sone Moon: Or should I invest more and take some risks because the bad things will never happen? It's kind of hard to those decisions. I think how we operate is we assume really anything can happen. ⁓ We are actually taking some risks, not as much as we would have in a ⁓ really predictably good economy. Erin Todus: Mm. Ahryun Sone Moon: But also I'm very, very mindful of our expenses also so that we can always keep profitability in mind so we can grow on our own merit. So really kind of dual minded. You have to be kind of dual minded to kind of operate and navigate this type of environment, I would say. And I've never been in this type of economy before. I'm sure it's weird to everyone and it is really an interesting time for us too. Erin Todus: What are you noticing about customer mindsets in this in this climate? Is there ⁓ are there any themes that you would share ⁓ or has the customer mindset maybe shifted in ways that have surprised you? Ahryun Sone Moon: I think our customers are going to operate in the same type of mindset. You cannot take full maximum amount of risks. But also at the same time, you cannot afford to not take risks now either because of the AI and all these technology changes that are coming. And also what's inevitable is you've seen with COVID, right? When things, you know, when people got laid off and everything, seems like the worst and doom and gloom is there. we'll never get out of it and then we got out of it. And then when we got out of it, all the TA teams who shrunk inside significantly, they couldn't keep up with the change, right? And so I think TA leaders have learned from that past experiences during COVID, so they cannot significantly reduce their expenses either. And they know there will be some search coming in the future as like with the economy, it's a pendulum, right? When people lay off and the next thing you know is people are hiring like crazy. But I think the TA leaders have that in mind. That's why I think AI becomes a really crucial thing, a tool in their toolbox that they must get really good at. Because when the search comes, they need to be able to use AI. And with their smaller team now, They have to equip the team with the AIs so that they can handle the higher volume in the future. So I think that's the expectation that we are seeing from our customers. I don't see like huge reduction in headcount or workforce anymore, but they're thinking about, how do I actually equip our smaller team to handle 10X of volume in the future when it comes? Erin Todus: Yeah. Yeah. It's a huge opportunity for TA teams because to your point, you're sort of at the front of the boat, like you're the first to fall when things are bad, but the first to be called back and ⁓ highly valued when things are on the upswing again. And so figuring out that scale and and preparing for that, I think all all organizations understand that you can't just solve for it after things have swung back because you will you will lose and you'll be behind. You have to prepare for it ahead. Ahryun Sone Moon: Yeah, absolutely. Erin Todus: Is there anything, you know, sort of last question on on just operating in this climate before we ⁓ dig into ⁓ a little bit of AI AI hype here, is there anything you've had to say no to ⁓ because of the climate that we're in? Ahryun Sone Moon: Yeah, yeah, there were a few projects that ⁓ we wanted to work on, frankly, if we actually, we did actually expand our engineering team, but we could have expanded the team even more to take on more of the product lines that we really wanted to bring to our product, but we had to be really selective in what we pursue. And whatever we pursue, we have to do a good job instead of pursuing 10 different things and do a really mediocre job at everything. So we had to say no to some project. ⁓ But I think we're thankful that things are not, things are actually pretty good. It's just so weird. Things are good. It's feels like it's, you know, we're in a terrible economy, but actually things are pretty good. we will. continuously take more risks and bring those projects that we wanted to work on into our product roadmap in H2 and ⁓ early next year. yeah, we had to say note and be really selective, but I think we will actually start taking some ⁓ additional risks and bringing even more product lines. Erin Todus: That's encouraging. Amy Crook: Yeah, it definitely is. I just want to jump in here because it's just, you know, talking about the economy. A big part of the economic uncertainty is the wave of AI products that are on the marketplace now. What are you seeing ⁓ when it comes to like your customer base and the kind of AI tools that are being presented to them? as potential competitors or add-ons? Because it feels like there's 20 new products a week coming on the market. So how does that feel from your perspective? Ahryun Sone Moon: Yeah, definitely. think ⁓ at the end of the day, ⁓ what ⁓ AI and especially agent AI ends up solving for is business problem. There's a business problem that you're trying to solve for. And for good time, for example, over the last 10 years, about a decade, we actually built up a lot of tools that could solve that. very, very complex business problem. And those tools are used by recruiting coordinators and recruited full-size recruiters and so on, and talent operations. Now with the agentic AI, because of all those tools that we've built up over the decade, the agentic AI can actually use those tools to do more of the business automation. ⁓ So with AI, there are a lot of companies that create something you know, like a thin wrapper around open AI or, you know, entropic. ⁓ and, know, like that kind of without understanding the depth of the business problem that they're solving, they create something really kind of thin and, but really cool looking. think in reality, when it's actually put it in operation, it actually doesn't solve the depth of the problem. that you really need a solution to solve for. So yes, there are a lot of AI products and add-ons and so on. I think my concern is without really having that deep understanding, the solutions that you end up buying that looks really cool and that just came on the market, it may not deliver the results that you're looking for. It may look cool, but really the business results that you're looking for, you may not get. I think software companies, there's all, you know, there are talks about, you know, all the SaaS companies are struggling, you know, that to SaaS, you know, SaaS market and so on. But I'm kind of now hearing that the trend is somewhat reversing that these SaaS companies that are now adopting AI. ⁓ ⁓ What's happening is they're using AI to control the tools that they have built up over the last decade or two decades. And they're actually more effectively able to solve business problems. That's sort of my take on it. Amy Crook: Yeah, I think I think that's, I agree with you completely. There is a gap between, you know, what looks impressive, and sounds impressive, and what actually delivers the business results that companies need. And maybe we're coming towards the end of that season. But for a time there, it felt like companies weren't necessarily thinking about the problem they were trying to solve. They just had this pressure to have AI, know, let's, let's integrate AI with that. It's like, okay, for what though? Like, what are you trying to solve? Do you feel like that's maturing a little bit or is there still some of that around? Ahryun Sone Moon: Bye. I think last year it was more of let's have AI. And that pressure is also coming from the top also. And I totally understand the pressure. ⁓ know, as in, you know, probably investors are looking for, you know, more expenses, more profitability. And therefore it seems like AI is the promise land where, okay, now we, of hiring more headcounts, let's use AI and have our current. in the workforce actually be even more effective, which I think is the right promise. And that's what AI is delivering. But the pressure of having to have AI definitely comes from the top. I've actually had a customer whose policy is to use $1,000 cloud credit per month per person. And you get in trouble if you don't use up all $1,000 per month. Yeah. Erin Todus: Interesting. Ahryun Sone Moon: Which I don't think is necessarily a bad thing. ⁓ if that thousand dollars used really well, but otherwise, you know, it's, it becomes a really undue pressure on the team. ⁓ so yeah, but this year, I think I'm seeing more of maturing of that customers are really thinking about, okay, I've utilized multiple different, I've bought a lot of different AI tools. Some. gave me the benefits that I was looking for, some didn't, and then they are really kind of introspecting and thinking, okay, what's the problem that I'm trying to solve for, and I'm gonna buy AI for that, AI to afford, AI is a means to an end, AI cannot be the end. So I'm definitely seeing the economy or the market maturing and better adoption of AI. Amy Crook: Yeah, I think that's such a great point that it's the means to the end, not the end. think, yeah, that's important to remember. So you have your own tech stack as an organization. How do you personally evaluate whether a new tool is worth adopting or not? Ahryun Sone Moon: Yeah, great question. think at the end of the day, it always comes down to ROI. So return in the numerator and then what is the investment on the denominator? ⁓ And also having someone who can be dedicated to that AI tool and someone who actually has time to mastermind it, put it in place and to change management and all that. It's like any software. ⁓ So how we evaluate it is really depending on, okay, what is the amount of results that we are looking for? First of all, we have to define what is the business results that we are looking for? And then what does that translate to from return perspective? And what is the investment? And if that's worth it, then we end up investing it. We've had some really good success. with obviously non-good time products. And that when we had success was when we really knew exactly what we were looking for. And then there's someone who was in charge of it. ⁓ And also investment was not something that would break our bank. Amy Crook: Yeah, that definitely helps. You kind of touched on this a little bit, but I'd like to just dig in a little deeper. When you are embedding a new tool into an organization, who needs to be involved to make that successful? And who gets missed out that ultimately could result in the integration breaking down? Ahryun Sone Moon: Totally, absolutely. think there are some, a few stakeholders that are very important for good time for example, and I'm sure they're relevant stakeholders for other AI products. For us, it's IT. IT needs to be involved from the very, very beginning, even before signature. And they need to fully understand ⁓ what technical changes that need to happen on their tech stack. ⁓ so that implementation can go up, you know, ⁓ Sometimes IT actually doesn't get involved until implementation or the team who gets involved pre-signature is different than the team actually that gets involved after signature. And, ⁓ sometimes what happens is the IT team says, okay, I never put this. What was the other thing? And now they want to actually do the analysis and evaluation all over again with jazz to implementation. I think having it or whoever will be involved ⁓ during the implementation in the know, even before signature and early, early on is super important. ⁓ They sometimes they do get left out. ⁓ And also I think for our product recruiting coordinators and also recruiters that will be end users. Amy Crook: Yeah. Ahryun Sone Moon: Um, sometimes it, uh, we, it's really important for them to be excited about it in the know about, um, the AI product that's coming in their way and also knowing the benefit of it. It is sometimes scary, right? Uh, will this, you know, replace what I do is, you know, obviously a very natural question mark in their head, knowing the benefit and also knowing, okay, if I get 70 % of the time back. What can I, what projects can I work on? What else can I do? What strategic initiatives can I take on with the 70 % of my day? I think kind of flushing that out before you implement any sort of AI tool is really critical. What did they buy in? They don't resist it. They fully understand. And also they become like, they're part of the masterminding implementation and the implementation of the software instead of. it happening to them. I think to me, would say users as well as IT are two very important stakeholders. Amy Crook: Yeah. Yeah, I think the people who are actually gonna use the product should be part of the conversation as soon as possible. That makes perfect sense to me. And I really like what you pulled out there in terms of the leadership role that needs to take place in terms of here's the benefit, here's how it's gonna work, here's my expectations of the... the time that you're going to get back to and how we're going to use that time. So you just mitigate those concerns straight away. I think that's a really good call out. So in today's world, everything is valued around speed. Speed is the currency. How should companies factor in like governance and compliance and risk and you know all the all the new legal cases that are popping up around AI use like what's how should leaders evaluate that for one and then maybe we can talk a little bit about the risks of going too fast or too slow. Ahryun Sone Moon: Yeah, absolutely. Yeah. Um, I think first of all, you, uh, definitely you should work with vendors who have kind of thought it through, but the aspect and the risks through and following all the laws and are there like, you know, up to date on any new laws that are coming, uh, with AI, are just new laws that are coming in your way in Europe and different states. It has their own law and you know for for certain stage that are more forward about AI and so on so The vendor really has to do the due diligence and know what's coming and really complying with those laws so that as a customer You don't have to think about it That's first thing and then governance wise I would say it also boils down to really ROI when it comes to our governance because the return in the numerator and also risks in the denominator where we see some companies going just too slow or they get blocked from AI council, you know, and they, don't get to use any sort of AI or, ⁓ it just, you things are super slow because of all the red tape. And I think that I typically see there's like one governance body in the company and they actually are very detached from actual business. departments, like for example, if it's an HR AI solution, they actually don't really fully understand AI, the benefit of the HR solution because they don't understand the business problems. And sometimes those, that body minimizes the reward ⁓ and overcalculates the risks. You get small reward and really big risks and which means You don't get that, right? You got to know. ⁓ So I've actually seen a really innovative structure, which I actually never even think about. Actually, one of our customers mentioned that the team that calculates the risks and approves AI product is decentralized. IT person or a team rolls into each department and they become subject matter expert in that department. They fully understand the benefits so they can accurately calculate the reward. And also they're trained to calculate the risks correctly also for that context. And I think you can have the governance and also you can move fast. Erin Todus: Mm-hmm. Ahryun Sone Moon: So I thought that was a really interesting creative structure, but I'm sure there's different structures that work for the companies to have both. But it's really critical that you comply with the governance, but also move fast in this type of environment. You don't get to be left behind, right? So yeah. Amy Crook: Right, so true. Okay, so we're switch gears for this final set of questions. I wanna talk a little bit more about the future of scheduling and recruiting. So you've talked in the past about ⁓ an aspiration for one-click scheduling. What does that actually look like in practice? Ahryun Sone Moon: Yeah, definitely. Yeah. So we actually rolled out one click scheduling how it works. It's, and we are layering AI, agent AI on top of that. But right now on click scheduling, how it works is as the candidate comes in, our AI actually, ⁓ evaluates the candidate's resume as well as their application, how they answered the initial application questions and so on. And then based on that, can, and also comparing that to hiring manager's requirements and recruiter's requirements, we can actually kind of stack rank those candidates and sort the candidates in a way that we wouldn't auto reject anyone. That's left up to the human decision, but we will actually help recruiter to look at the most bidding candidates first so that they can utilize their time better. For the ones that are really good fit, the system is smart enough to actually move them to the next stage. Schedule the interview automatically also. So from recruiter's perspective, they post a job on Friday. Monday, you have candidates that are relevant, booked on your calendar. And then let's say the recruiter said, thumbs up, this person is good. Based on that feedback, the system is smart enough to move the candidate to the next stage. and schedule the next interview and so on. So eventually for the top candidates who are really good fit for the job, ⁓ really there's no, once you actually, once the candidate moved into the application, everything just happens automatically. Technically that's zero click, but that's what we are going for. And the agent AI that's laid on top of it, to handle all the edge cases if someone needs to reschedule and there's no alternative and so on. The AI, the agent actually handled all the edge cases throughout the journey. And that way recruiters, what ends up happening is they spend the majority of their time talking to the candidates and then the rest of the time, they still have time left to be able to spend time with those less obvious candidates, give them enough view. And if some of them are really good, then you move on to the next stage and so on. So it really makes their day more efficient. hopefully, click to, no to one click is what we are going for from our product perspective. Amy Crook: That's awesome. I'm just thinking about, you know, the various talent acquisition teams that I've worked in over the years. And what do you think needs to be true from like a, you know, an operational perspective and a technical perspective for that to work well in organizations? Like, is there a perfect environment that this, this is particularly successful in? Ahryun Sone Moon: Definitely, yeah, I think it's very successful if you have a very standardized interview process. ⁓ If every candidate ⁓ goes through a unique process, it's probably more difficult to make that happen, even though I think our agent is actually learning from user behavior and will be able to handle those more unique cases too. before that kind of zero-click automation to happen at extreme scale, which some of our customers are actually highly, highly utilizing that product and doing everything at scale with really, really small team without having to click anything. For those teams, I realized they've actually thought through the process. And then the process is designed. And that design is embedded in the system. And then we can follow that design. ⁓ And they've gotten the ⁓ agreement from the interviewers hiring managers in terms of calendar hygiene and so on so that they don't the recruiting process is really smooth sailing and that design is built into the system. Everything happens automatically. I think the opposite case is, you know, interview process is not standardized. The design is sort of up to each person. Very, very centralized. It's harder. to make automation really happen smoothly. Erin Todus: Hmm. Amy Crook: Yeah, yeah, that makes that makes a lot of sense. I mean, it's music to my talent leadership ears that standardize process, that's have some consistency, you know, it's just so much better for everyone to have that clarity of process all the way through and not be changing it for each individual position. just it makes it really hard to like bench your, bench match your talent because the measuring ⁓ mechanism is different in every single one. So I think just from like a pushing people down the path of best practice perspective, like I think that's, I think that's great. And has the potential to, you know, change and probably has already honestly, the job. Ahryun Sone Moon: to Amy Crook: ⁓ description of like a recruiting coordinator. You know, they're now able to take on more higher level challenges because this repetitive task has been taken off of their play. Ahryun Sone Moon: Yeah. Definitely. think definitely RSC recruiting coordinators role has changed from like 90 % of their day scheduling interviews. More of like, I would say, I think it's evolving into more of an AI manager. Like you have the AI tool and especially for RSCs and recruiting coordinators are really the smartest people that I've seen. And once they, they tend to be also technically Definitely on the younger side, more technical also. So once they really adapted technology and AI well, they really fully understand, then they become more of an AI manager. So they sit in between basically humans and AI. They understand the business needs and what hiring managers are looking for, what recruiters are looking for. They can design that using AI. think it's kind of like. kind of evolving into that role than just like 90 % of their day scheduling. And also I definitely see recruiting coordinators while taking on technology and like really learning AI and so on, become way more data driven, more strategic, very special project focused also. That's sort of, think what I'm seeing evolving into and also some leaders are very good at having this really pivotal discussions with the recruiting coordinators now. And some leaders are kind of falling behind. Some leaders are just really good at having these really difficult discussions. They're really up-leveling them and up-skilling them and really getting them to become the AI managers. ⁓ That's sort of what I'm seeing in the market. Amy Crook: Yeah. Yeah, and I think that's completely spot on. It's not going to work if you just try and layer on, you know, brand new technology until your old way of doing things. Like you have to have a real shift in how you operate and opt and that gets the best out of the technology and the best out of your people. I really do believe that. Ahryun Sone Moon: Right. Excellent. Amy Crook: I just have one last question just for Fonzie's, because this is something that I'm just personally interested in. What is your LLM of choice? Ahryun Sone Moon: I actually do use both OpenAI and Cloud. ⁓ And yeah, they both, they serve very different purposes and I do different projects with. ⁓ Amy Crook: They are so different. They just like... They do things. What's your top? So what's your top thing to use chat GPT for? Ahryun Sone Moon: Yeah, it's. FetchPT, I usually use it for rewriting emails. More simple, like writing. FetchPT is really good at. Cloud is definitely way better at creating a product, a small little project that I want you to do, ⁓ and so on. And also recently, I got into video creation using the right tools. So, ⁓ well, our marketing team has to approve it. Erin Todus: Mm. Amy Crook: I'm so sorry. Hahaha Ahryun Sone Moon: But it's just, there's just so many AI technologies out there that we, you can kind of do on your own the side. And yeah, so video tool, I think is another AI tool that I've been really into recently. Erin Todus: Okay. Amy Crook: Yeah, they're definitely fun for sure. Well, it was so great chatting with you today and lovely to meet you. And we're big fans of your tool. We're definitely good time users at Strativus. So we're cheering you on and hope to keep in touch as we get through this next season of The Economy. What you were saying just really makes me laugh. It's like you're bracing yourself for a punch in the face that never comes. Ahryun Sone Moon: Thanks. Erin Todus: Yeah. Ahryun Sone Moon: like there's war, there's know, oil plant flag inflation, you just see doom and gloom in the news and you never, I mean you can kind of like Amy Crook: Thanks. Erin Todus: So true. Amy Crook: You know the words and it's just the same. Ahryun Sone Moon: It's all same. What is going on? It's really hard to figure out what's really happening. Things are good. Which means... ⁓ Amy Crook: Yeah. Things are good! Yes! Erin Todus: Yeah, one foot in front of the other. I think that's you know it's like you have to just focus ahead and and try not to get caught up in it. That's our perspective at least. Yeah. But such a good conversation. Thank you so much for taking the time and letting us pick your brain. It's been so fun and really looking forward to sharing the episode. Ahryun Sone Moon: Thanks. Yeah, same, same. Yeah, well thank you for having me. had a lot of fun ⁓ answering these questions. So appreciate it. Amy Crook: Awesome. We'll get over your media kit. We'll plan to have this go live next week for go live, right? And so we'll send over all the tiles and episode details so that you can take a look, ⁓ even though I'm sure you have a very busy schedule. But we'll be definitely pushing this out next week and sharing all your words of wisdom. So thank you. Erin Todus: ⁓ huh. Ahryun Sone Moon: Yeah, I appreciate it. I had a lot of fun. Amy Crook: Good. Okay. See you soon. Bye. Erin Todus: All right. Bye bye.