Do The Things You Told Yourself You Would with Nick Askew

Michael Cirillo: 0:00I feel like Nick needs to wear a shirt that says, I'ma ask you something.

‍Unknown: 0:12

This is Auto Collabs.

Kyle Mountsier: 0:16

Oh, the way you started that. Like, you know that, like, like, that 50 millisecond Are you gonna pause? And say that right now. Okay,

Paul J Daly: 0:25

no, that's amazing. Let me ask you a question. I'm gonna ask you some ask you a question that's really good, but like,

Kyle Mountsier: 0:35

accent, please ask you it's all of a sudden gonna turn like Texas Canadian, and it

Michael Cirillo: 0:42

turns into, like, old monocle wearing top hat. I'ma ask you become king the monopoly

Unknown: 0:49

man. That's unbelievable. I

Paul J Daly: 0:50

don't know, but I'm never gonna look at Nick's last name again without thinking of that. It's a problem,

Unknown: 0:55

guys. I'm sorry, no, I mean, you

Paul J Daly: 0:57

see the world in a way, this

Kyle Mountsier: 0:59

guy also, just as a note, like, he's a consummate musician, and he has the perfect name to be a musician. He really does like Nick, ask you, put that on a CD and sell it. Man, he's

Paul J Daly: 1:11

got the accent too. It's unbelievable in the studio. It's kind of frustrating. And he's smart and he's talented, and, I mean,

Michael Cirillo: 1:18

nobody, why does he hang out with us again. What that says? Nick that says Michael Cirillo, you know, I'm saying you don't go on Apple Music and be like. That sounds like

Paul J Daly: 1:28

I'm looking for like a cover band of the classics. I might do it like polka. Like, no, no, like,

Unknown: 1:34

Sinatra. Oh, Sinatra,

Paul J Daly: 1:37

I could definitely see you like in a polka band. Now that you mention it. That's fair.

Michael Cirillo: 1:41

Well, you know, like, I recently, not, not too long ago, I had Nick on our other show, the dealer playbook. And what I what I realize, is that he is a really deep thinker. I don't know if it stems from the musical,

Paul J Daly: 1:55

yeah, but have you listened to his music? It's not necessarily bubble gum pop. It's like

Kyle Mountsier: 2:01

feeler music. He can turn bubble gum pop into introspective music. I don't know how he does it. Well, hey, maybe you'll get some bubble gum pop, maybe you'll get some introspective music. But we hope you enjoy this conversation with Nick ASOTU. Nick, thanks for joining us again. Man, excited to chat with you. Always good to catch up and just see what you're doing in the world, for sure.

Paul J Daly: 2:27

Amy, besides, besides, just like walking off a movie set, yeah, like, if you can watch, if you're, if you're only on the audio version of this, he's sitting in a director's chair. He's got a full sleeve on his right arm. He's got headphones on. There's like a little light peeking out in the back. There's like, a psych so you can't even see the corner of the room, but he's like, Oh, this. I just threw this on, right?

Kyle Mountsier: 2:50

Well, okay, but this is this that actually transitions to what I wanted to ask you about, because I haven't really been able to talk with you about it since it happened. If you're not following Nick on, I'm gonna call it Instagram, don't you can follow Nick on LinkedIn, but you gotta follow Nick on Instagram because it like it pairs personal and professional, really, really well. Yeah, you went through this time when you recorded a song that you learned, and then recorded later that day, every single day, for how long? A whole month, right? Yeah, full 30 days. I because obviously, you're a musician. We know that about you, you're you're not just a musician, but I would consider you like an artist, like you think about the world creatively, right? What when you were going through that, what did you learn about yourself and what that gave you in in your life and your business and things that like maybe you didn't expect coming out of just like trying something like that?

Unknown: 3:53

Good question. That

Nick Askew: 3:54

is a great question. So I think first of all, the thing I found out about myself was I like to set really big goals, and then about halfway through, the pain sets in. So prevalence through, through self inflicted pain. But you know, like halfway through, I got my voice gave out, like I did a song that I really wasn't prepared to do, my voice gave out, and I still stuck with it anyway. And I think, for being a startup, right? How many companies? I mean, we know the success failure rate of software startups, it's, it's no secret that, you know, most of them don't make it past their first couple of years, right? So I think for me, one of the things was, you know, commitment to doing something that was hard and proving to myself that I could do it no matter what it was that was a portion of it, adaptivity in the moment, like even sitting there going, Okay, so I've prepared this song. I'm getting down to record it, and I'm just not. Feeling it, or I actually can't do it, or I didn't learn it well enough, so I've got to pivot in the moment. And I think that's just something I was able to figure out about myself, is like that, adaptivity and then also the perseverance of, you know, I said I'm going to do this every day for 30 days. And whether it, you know, kills me. Unfortunately, my wife, if you're watching, like, you know, she wasn't a big fan of me going to spending and doing that when I was supposed to be there. I know, you know, it was like, Oh, you're recording your song again. I can't wait for this month to be over. And it's like, but she had a point. But like, it was a, you know, I'd made the promise that I was going to do it to myself, so I've really felt good about following through. And I think that was the perseverance part was the biggest for me.

Paul J Daly: 5:48

I was just watching a video, a Casey Neistat video he released a few months ago. It just popped up in my feed. And I think the title of the videos do hard things, and in his very, you know, quintessential storytelling method. You know, it kind of shows early morning, him waking up the alarm clock, and he starts, he's like, waking up is hard. You know, waking up early is hard. He's like, and then going to run is hard. He's and then he goes into this whole, like, monolog on doing hard things and what it actually conditions you to do in all the other areas of your life, because you decide to do the hard things and and I think as an entrepreneur, and as an entrepreneur in the auto industry, there's, they're always going to be hard things, like all the time, yeah? And if you expect that, there won't be, or aren't conditioned to handle it like, you will wash out very, very quickly, and especially if you're trying to build something new.

Kyle Mountsier: 6:43

Well, and that's what, like I wrote on LinkedIn the other day that, you know, we, I entrepreneur 17 hours. I love that post, right? That one, and it's only be, and the only reason is, it's that it's less is because I can't remember my dreams. That's the only reason, right? And like, there is this, there is this thing where, like, it doesn't matter what aspect of my life I'm always entrepreneuring. I'm always creating or crafting something new. And that's the like, you know, I can, I can hear my wife like, because I commit to dumb things like that too. Don't worry, Nick, we're all, I think, in that corner. But I can hear my wife being like, again tonight, right? But it is that, that constant push and pull of like, how much can I create, and how much do I have to, like, get resolved and stay steady and be be available for my team that's living in this, like, right now scenario, and sometimes I'm just living in this, what's next scenario, right? And that's, yeah, that's a constant balance. Well, that

Nick Askew: 7:44

is a constant, especially when, you know, and that communication, I mean, I bring that back to work in my team, right? Because, you know, in unless I communicate those kind of goals, it can sometimes seem, you know, that, Oh, Nick's got this new, fresh idea, right? And it's like, oh, that's his. That's his idea of the week. And it's like you're just thinking so far ahead and making these big picture commitments that unless you are very strong in your communication about your intent to do those things, it can come across off as just impulsive, which I to be fair, you know can be but yeah, it's fair. But yeah, I think do hard things, right? It's like, I you do those things because I told myself, I would, you know, and sometimes you don't feel like doing that. It's sometimes you don't feel like getting out of bed, getting up early, having those meetings, but you do it anyway. Yeah,

Kyle Mountsier: 8:44

the conversation that you and I were having when we were talking about, actually, ASOTU CON is actually, it's very akin to this. Because when you think about the things that the world is building right now, and, you know, I'm gonna go straight to AI because it's, it's kind of like the hot topic. You know, earlier this week, at time of this recording, we we saw GPT have a million new subscribers in less than an hour, just because they released image generation, right? Like the pace and the availability and the understanding and the ad the adoption is, is pacing up in an all time record. But there is this kind of point we're at right now where AI is like, it looks like this sexy, easy thing, but it's also this very hard unknown, like, have to get in the ground, and then there's a bunch of people like, AGI is coming. Uh, no, maybe not yet, maybe not yet, right? And, and so there's always this vision and what the practicality is right now, you're implementing a lot of these, a lot of solutions when it comes to AI and thinking about how they become practical in a dealership operation. How are you balancing that? Like. Yeah, oh, I had this vision for what it can look like and what we're gonna what we can practically accomplish today with the way the tools and and the capacity of AI is right now, I think that's

Nick Askew: 10:10

just how science works, right? It's in general, it's like we're always 10 years. For the last 40 years, we've been 10 years away from nuclear fusion, right? Like self driving cars? Yeah, we're always 10 years away from self driving cars, 10 years away from nuclear fusion, 10. I mean this, this is how it's going to be. But any practical part of science in general is that you've got to create, you got to create test cases first. And if you think about the practical use of AI today, AI has very specific jobs. And you mentioned open AI releasing the image generation. Well, if you think about all the little things that our brain has to accomplish, right, you know, we've got image generation, you know, in the fact that we can close our eyes and imagine something, we've got, you know, optical recognition and the processing of that auditory we've got long term memory, we've got short term memory, we've got motor functions. And what you're seeing right now in AI is all of these little pieces becoming useful. So, like, there's a lot of practical applications for like the chat, GPT style knowledge, text based LLM, that is a useful thing because we need to comprehend, store and understand information. What we're going to see right now is a lot of these individual AI applications be built to where it's image recognition, audio recognition, it's going to get faster and better, and all of these little pieces, much like how our brain works and the way we're trying to implement that is jobs to be done with inside automotive and harnessing the power of what actually is available today, and segmenting them down into even further, which is, how can we utilize LLM? How can we utilize image restoration recognition, how can we utilize data analysis? How can we utilize all of these things and make them into little, practical agents that just take the monotony out of doing the job and make car buying experience a little bit better. So I think for the AGI thing to finally happen, you know, we've got, there's several parts of artificial intelligence that we have to master, and then we have to tie that together, like all of our sections that we have in our own brain, if that makes any sense?

Paul J Daly: 12:44

No, it makes a lot of sense. Yeah. And one, and one of the things that I worry about the fact is the fact that a lot of the tech companies and a lot of the people who live and they love to live over the horizon, right? And then they come back and they tell us what's over the horizon. They talk about it a lot. Most of the people, 80% plus, live right here and are looking at the horizon saying, like, I can't quite see what's out there. And everything that they come back and tell me, I don't know what to do with it right now. And so, I mean, that's going to be a lot of what we're talking about at ASOTU CON and and you're going to be coming in and sharing a lot about like, yes, that's what's on the horizon, but this is what the now looks like to prepare for it. Yeah.

Nick Askew: 13:29

And look, we're in the such baby stages of AI, right? So there are practical applications that we can use today, but what we can't do is, is, is, is sit here and look into the future and say, This is the vision of the future. One day we'll get there, because we the steps that we take today in order to test and create actual, you know, real life scenarios that either help or assist, you know, in any industry, not just automotive, are going to be the learning experiences that paved their way to that big horizon of AGI and and that thing that people think that just, you know, AI is going to be one day like these are the natural, scientific steps we have to take in order to eventually get there.

Paul J Daly: 14:21

So what are you saying? What are you saying right now to your dealers. You have a lot of dealer customers. What are you saying to them, even from and you obviously run in like a singular lane, as far as your products and things like that, you know, within a certain portion of the business. But what is your general coaching to your dealer clients about all of this new stuff, about what they can be doing today in order to make sure they're prepared for the future, or they're building a house today that will actually be effective tomorrow as well.

Nick Askew: 14:54

There's a couple of things. So I first of all be curious and learn about it. I mean that i. Think that every you know, one of the things that I'm speaking about at some, some other conferences, is, is, is kind of like AI for the everyman, right? Is how you know how to generate a bunch of different reports and generate a few prompts to be able to ask you reports some things, and ask the data questions, right? I think that everybody, no matter if they're a GM, they're a sales manager, they're, I mean, they're a BDC manager, and analyzing scripts and what worked and what didn't work. Be curious and use these tools, because it's not just waiting for the vendors as much as I'd love to sign more dealers up and solve that problem for you, like, unless you're curious about it and understand how this works yourself. You're you're never going to be able to fully understand to strategize that for your business. Because I think the the GM of the future is able to take you know, they are in charge of their own. They are the CDP, right. Come on, right. It's, it's not go out and buy a CDP and figure out how to harness it. It's, you have to understand and control that. So if you've got, you know, ancillary, you know, products, you've got an F and I company, you've got a body shop somewhere, you've got whatever that may be, you have to be your own dealers, be harnessing your own deal as CDP and build your AI on top of that central brain, right? But the only way that you can do that is actually understand it and be curious about it in the first place.

Kyle Mountsier: 16:41

I love that you say that to be curious about it. Because I know some people, I've actually, I've sat in dealerships and with other people that are starting to use AI. And I think what, what the common belief right now is that, like, I can just ask it anything, in any way, and it'll come back with the right thing. And what, what I've learned, and what we've learned on our team, is actually the way you ask it, how you clarify the expectation, what you clarify as, as the the output you know, what, what you know, additional feedback and additional data you you feed into it is extremely important. What, what's actually happening is, it's making me a better communicator, because I love how, you know, we're using this word agent a lot, and when it comes to AI, and it really is an agent, and that agent needs inputs to give you the right output. And that's the same thing with an employee. It's like, Oh, if I'm really curious about AI, it gives me the proving and training ground in how to approach an employee with my clear expectations on inputs and outputs, right? And like, you actually said CDP a couple times there. If you go to a CDP and you look at it like, tell me the segments that we have. It doesn't like, there are CDPs with like, here's our core basic segments. This is what we set up for everybody. But there's some like, like, very human level things that we have to understand about querying that CDP and saying, I want to extract this data out now that I've put all together in order to operationalize it over here. And those are like, those are still the movements that we have to make as the oper, as the overarching operators of these new tools.

Nick Askew: 18:28

Yeah, and if not, you're just relying on the base level reporting, or you're relying on base level automations. You're not really optimizing anything. You're just you're just connecting data without a purpose. And, you know, that's the thing about prompt engineering. I think everybody should learn how to prompt engineer properly. You know, we do so much experimentation internally, just for for ourselves. We've, I can't actually remember what we call them. They're basically phantom settings. So you've got this, like, uh, this distance between words, and you've only got so many tokens that you can put in. And what we found is, you know, in creating a prompt, is that, you know, if you say, for example, tell me all of the customers that I have that have bought a car within the last two years, or have been interested in a Ford f1 50, like your your distance between your the object that you're trying to create and query, and the you know the information is Like, the sentence is so long and it's so, it gives the AI, well, it gives AI more room to make

Paul J Daly: 19:47

assumptions and the thinking, yeah, you met, yeah,

Nick Askew: 19:51

yeah. It's so what we actually end up doing is figuring out how to to to optimize that. Then it. Went a step further in some of our optimizations. Did you know that even in like, GPT, when you're getting something back, you can say like, you can make up settings, and you could say, return markup equals false, and it would just export normal text, and you could say, return markup equals true, and it will format your text for you with headers and everything. And you just make up the settings. And those are, yeah, that's, that's a practice that we use, is just create these ghost settings that really help us refine certain prompts and certain things just like you're saying, and they don't, they just interpret that. So you know that when I say be curious, it's like, when we're trying to figure those kind of things out, is like, this is all such new tech, and it's our job in any industry, not just people developing technology, to go and, like, kick the tires on it and make it better.

Paul J Daly: 21:00

Well, I think there's a huge opportunity, and I don't think it's being leveraged enough. It's one of the reasons we created the auto industry.ai site and email, because we use AI super extensively within our in our organization, from for everything you can imagine, right? Like, it's, it's not like creative things only. It's everything, and we use it so much, we feel like there is real value and responsibility for the tech players. And I'll consider us a tech player. Even though we don't build a tech product, we operate a lot like a tech company. It's our responsibility to bring everyone along, and there's so much value in just sharing the little things like you just shared as we're kicking the tires for all the people who are out there on the front lines who don't have time to kick the tires, right, you know? And so I love that you're saying this. And I think, like, more of that, just like this is what I've been learning with AI is useful to, you know, a much broader audience. And I actually think it's, it's a great, it's actually a great opportunity to bring people from outside the industry to pay attention to this industry and be like, oh, like

Kyle Mountsier: 22:07

they are. They're leading the charge on how to operate. Yeah, let

Paul J Daly: 22:11

me get in on some of that. Yeah.

Nick Askew: 22:14

I think auto motive has the opportunity to lead the charge on AI in practical applications, because it is so complex. We have so many jobs to be done. And if you think about agents, right, what is an AI agent? It is just something with a specific job, right? Whether that agent is, hey, do equity mining for me and give me a list of all customers that I should call today and organize them in a way that is, you know, the the absolute best in terms of profitability, you know, likelihood to answer equity. You know, the relationship the sentiment of their response. Did they tell us to go ourselves, or did they, you know, have a nice conversation with us, like you could take all of these different data points. That is one agent, if people just started thinking and understanding an agent is a job to be done, you could start looking at your business holistically and go, How many jobs to be done are there? Think about them as roles and responsibilities. I have a CFO that has a job to do, and build me these reports once every week. Let's automate that. And that is a job to be done. And I think anybody in any role should be, you know, looking at their own job and utilizing these tools to be able to create their own mini agents to to help make them more efficient, because it's

Kyle Mountsier: 23:42

just a toss before we before we roll out. I'm going to toss a challenge. If anybody's listening to this podcast right now, do us a favor. Find a job in your sphere of influence that could potentially be replaced with an AI agent. Either begin building that agent, or let us know if you're having trouble with that, and between the three of us, at least, we'll figure out either the path to get you there, or the person to talk to, or something like that. Because I think that that would be a really cool outcome from this conversation. Nick, always great to chat with you. You're filled with just creativity and insight and vibes and vibes, full vibes, Director vibes, I can't wait to see you at ASOTU CON. You're gonna be doing some podcasting with us. You'll be on stage. It's gonna be a really fun collaboration.

Nick Askew: 24:32

Looking forward to it as always. Great to see you both.

Paul J Daly: 24:40

I'll tell you what his studio game is really stepping up on LinkedIn and everything. I'm watching all these things. I'm like, he got that production bug, and he just went back into it. Yeah, no, you know, because I think, I think all of us have kind of wandered in and out of that, you know, I'm just gonna make content and but he's, you know,

Kyle Mountsier: 24:58

what? I think, actually, this is right? To the conversation about AI, I think that there is this wonderful balance of people that are leveraging technology like at an extreme level, but also still creating very natively and personably. And I think it's enabling like this, left, right, blank brain unlock in some people that are able to do both within a single day. And, you know, maybe it's just because we're all musicians too. Like, I think it's something that a musician or a creator or something like that that is tuned into technology is having much more of an unlock, because there has been this like, what can I create with this? What can I do? What really

Paul J Daly: 25:50

good observation here, right? I think that the creative minded people are naturally ones that are good at taking, I won't say chaos, but taking elements and putting them together. Even think of how creatives are natural, like musicians are naturally better at language, yeah, making up languages and things like that, because they can kind of hear, it's almost like they they see and hear the music in it, oh, yeah. And it's almost like that's kind of what Nick's doing with AI and tech, and what the creatives are doing with the tech, how they see the music in the tech.

Kyle Mountsier: 26:21

There's another that's a post, that's a podcast, that's whatever, yeah,

Michael Cirillo: 26:25

well, well, as you're saying it, I'm thinking about this, and I'm like, Yeah, this rings true because, I mean, I know we've all written song music, uh, we've all probably sung in choirs. We all know how to do the harmonies and all of that. And there's something to this where you can hear the whole and I think, are we all sound engineers too? Yes, okay, so, like we're all sound engineers at the same time, there's something to this ability to hear the whole song at once, yes, and also simultaneously hear pick out all of

Kyle Mountsier: 26:58

the individual things. Yes, yes. Oh, see now you just done got me fired up.

Paul J Daly: 27:05

Well, listen, we hope you enjoy that conversation. We hope you enjoy listening to us. Just pat ourselves on the back at the end of this podcast. On behalf of Kyle Mountsier, Michael Cirillo and myself, this would be the perfect time to sing a three part harmony if we rehearse, but we are not so. Thank you for joining us here on Auto Collabs.

Unknown: 27:25

Welcome to Auto Collabs. Sign up for our free and fun to read daily email for a free shot of relevant news and automotive retail media and pop culture. You can get it now@asotu.com That's asotu.com if you love this podcast, please leave us a review and share it with a friend. Thanks again for listening. We'll see you next time. Welcome to Annika.

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