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Why Most Automotive AI Projects Fail with John Coles · Auto Collabs

• 0:00
  [upbeat music] We need to align our spend, our time, talent, resources with the product objective and the customer objective that we are trying to accomplish.
• 0:09
  If you're misaligned on those, yeah, you'll burn millions of dollars in tokens and half-ass ideas that aren't gonna come to fruition. [upbeat music] This is Auto Collabs.
• 0:26
  I'm excited 'cause today we're talking to John Coles. New friend for all of us. VP of Data Analytics, something like that, at ACV.
• 0:34
  So I always start conversations like this as in I'm gonna have very little in common with this person. [laughs] So I can't wait to see how this pans out because...
• 0:43
  But when I know I have Kyle and Michael next to me, I'm like, "I'm sure I'll find something to talk about." I think Michael's gonna be the nerd on this one. You think? You think so? Yeah, I'm calling it.
• 0:52
  Michael's just, he's the closet- Michael's, I don't know if you know this, Paul- He's the closet nerd... but Michael- Yeah...
• 0:55
  Michael's been showing me more stuff about being nerdy than I have, you know- So- Every time I talk to Michael, he's like, "Kyle, gotta show you something." [snorts] This is my thesis on Michael, right?
• 1:04
  [laughs] Whenever... It's almost like this compensatory thing. When you post yourself in a pickup truck with a motorcycle in the back- [laughs]... you're trying to convince people that you're not a data nerd.
• 1:15
  That I didn't- Right... 3D print it all. [laughs] No, Michael's started to 3D print, print- Guys-... printing things... it's a problem. If I'm not creating something 24/7 in that thing, I feel like I'm wasting time.
• 1:29
  It's ruined my life. Oh, my goodness. It's downtime. That downtime's gonna- Have you gotten the carbon fiber print stuff yet? What? No, but- That's when it'll, you're gonna lose your mind now. Now you're gonna be- Yes...
• 1:37
  on Amazon buying the carbon fiber stuff- Oh... instead of the little plastic stuff. I, you know what? Too much. Hey, well, at first my wife rolled her eyes at me. She was like, "I can't believe this is who I married."
• 1:46
  And then you shipped her a little clip- I shipped her a little clip... and a thing to hold the other thing. And then a little koozie, and then- Yeah...
• 1:51
  the next thing, and then, and now she's sending me reels of things that I need to 3D print. Yeah, she's like, "And here's-" That, that thing is printing things now... "the print list this afternoon." Yeah.
• 1:57
  It's, uh- What's it printing right now? It is printing a four-can cooler- [laughs]... that you can fill with water so the whole cooler then can be frozen- [laughs]... for the pool. That's silly. It's called a pooler.
• 2:11
  [laughs] Oh. Oh. Put that- Well, that is the first... put that out there and sell it... folks. Done. It's gone. I'm like- Hey, well, that, that- I'm like Mr. Wonderful. I'll take a royalty deal on that.
• 2:20
  That little Etsy deal had n- nothing probably to do with this conversation. Doubt it. But we hope you us, enjoy us hanging out with John Coles. [upbeat music] All right, John, it's so good to be with you here today.
• 2:33
  Thanks for joining us. Thanks for having me on, Paul. I'm excited to get to, the time together. Okay. So I, I'll pretend that we didn't just have, like, 10 minutes- [laughs]...
• 2:42
  of really lively conversation in the pre-show. [laughs] Uh, because, uh, I just really appreciated the energy going into the call.
• 2:48
  You know going into an episode, uh, like, what, what the expectation and the level set's gonna be, so, uh, you're ready to go.
• 2:55
  And I wanna start by asking you a question about leadership because you have held leadership roles, um, in a, in a lot of different areas and, um, you know, kind of different industries, which is always very interesting to us.
• 3:07
  So could you give us a little background on the leadership journey that brought you to where you are today? Oh, man, Paul, this, this is a fun way to start. So- Yes... um, look, grow, I grew up overseas.
• 3:19
  I, my, my dad is a pastor, and I learned a lot about leadership, uh, from, you know, the environment, the community we were in.
• 3:28
  And a core part of how I think about leadership is who is it that I'm leading, and where are we going? Hmm.
• 3:35
  And if you look at those two things, then you start to understand who the people on the journey with you are and what your objective are.
• 3:43
  And then anytime I'm leading, I think about, like, what are ways I can remove barriers between the people I'm leading and the objective we're trying to get to?
• 3:53
  And that translates from healthcare, disaster relief, counter-terrorism. We're gonna have so much fun. There's so many areas to cover. And automotive, right? You think about automotive space.
• 4:05
  There's so many people doing so many jobs, and data and other things we'll get through today, they can be used as barriers or as barrier removers to get to that shared objective. All right.
• 4:20
  So this- So that's how I think about it... see, see now, this is a pastor's- [laughs] This is a nerdy pastor's kid. [laughs] So you, you, Paul, and you, MC, you see yourselves out of this conversation- [laughs]...
• 4:31
  'cause us two nerdy PKs are about to get after it. [laughs] Dude, all right. Now, all right, Kyle, let's go, man. [laughs] I'm like, which one of you likes minivans more? Yeah. [laughs] Oh.
• 4:42
  Well, um- Dude, me and minivans are so tight. Kyle, still- I've been growing, I was in the OG minivan, which was called a station wagon. Okay. Do you ever have a station wagon, John?
• 4:53
  No, they didn't make those in Indonesia. Oh. [laughs] They made all kinds of other fun stuff to jam families into, and we enjoyed those. [laughs] That is- I mean-... unbelievable...
• 5:04
  I was kinda gonna go back to the counter-terrorism comment, but, um- [laughs]... I'm gonna, instead, instead, because we only have a 20-minute show, I'm gonna, I'm gonna, I'm gonna...
• 5:15
  I'm usually not the one to do this, by the way. Um, John just- Yeah, are you gonna corral us? Kyle just got- Oh... super excited.
• 5:21
  No, but, uh, I've gotta go back to the leadership thing because I already know we need to have follow-up episodes on this. Um,
• 5:27
  you said, you know, "I, I need to, like, who are I lead- who, who am I leading, where are we going, and what are the barriers?" Can you identify some common barriers?
• 5:35
  'Cause you named so many different areas and so many different sectors, but l- you know, I think hu- humans are humans. Can you identify some of the barriers?
• 5:43
  And then we'll try to tie that back to what's happening right now as we're trying to lead an industry into this, like, data and technology future.
• 5:49
  What are the common barriers that you've seen across your leadership roles that you need to, like, [pops mouth] take that out of the way so we can go somewhere? Yeah, yeah.
• 5:58
  Common barriers, um, especially, especially when you look at who the people are, right, who's in the bus with you, and try and identify where you're going, a common barrier is- How do I contribute to our journey?
• 6:12
  That's a common barrier people get stuck on. Hmm. Sometimes they try and jump in, add value based purely on what they know, but not on where we're going.
• 6:21
  They, they'll use whatever framework they have in the past and say, "I've done stuff in the past, so I assume it has value today," right? So figuring out- Dope...
• 6:31
  how they contribute to the journey, what is their part to play in nailing that as a team. That's probably the biggest barrier run headlong into when you're leading. Hmm.
• 6:43
  The second is, okay, let's say I'll, I, we align as a team this, me and whoever this teammate is, on what they can contribute. Okay, how do I measure that?
• 6:56
  And this is where data is either a bludgeon or an accelerant, right?
• 7:00
  [laughs] How do I measure success in using it as something that empowers the teammate to be self-motivated versus an external factor that you're just beating them down with? Mm. Mm-hmm.
• 7:13
  So those are two things, especially on the data side, that I think about as common challenges that you gotta hit out of the gate. I think about so often you just hear,
• 7:26
  "Well, I did this, so I sh- so we have to do that," or, "My experience is so the only way to do this here is this way." Mm-hmm. And that becomes a roadblock so often when the context of a group allows for flexibility.
• 7:42
  Now, the context of that group, they, they, everyone I think needs to bring themselves to the table and all that they've learned, but, but kind of like holding stakes in the ground because of your context can, can...
• 7:54
  What I'm hearing you, and now that I'm, I'm like running through my history of like leadership and realizing all these places where either myself or others have kind of said like, "Well, it's the only way because I saw that it worked," or, "It's, it's never gonna work because I saw it didn't work," right?
• 8:12
  And those two positions to hold are so absolutist and don't take into context the current team, the current culture, the current situation, the current vision, the current sta- Like, you, you talk about like being in Indonesia or being in a wartime or any of those places, the context is completely different, and it's okay, right?
• 8:32
  Yeah. Yeah, absolutely, Kyle.
• 8:34
  And, and kind of one important component, anytime I bring somebody new into a team, one of the things I reinforce is, "We hired you because you add, but not because you're supposed to tell us all how to do," right?
• 8:49
  Mm-hmm.
• 8:49
  You're supposed to add to the journey your insight, your experience, but just because you did something in the past doesn't mean it's the only way to do it, but it's definitely a needed new perspective that then refines- Hmm...
• 9:03
  our collective journey towards that objective, right? Sure. You go out and you say, "Hey, I need a spare tire." Let's get automotive for a minute. "I need a spare tire 'cause I'm going on a long journey."
• 9:14
  That person needs to understand their role versus saying like, "Let's get out there. Let's add a tire. Everybody needs to be..." You know, what is it? It's like insane, 70 psi or whatever spare tires are at.
• 9:27
  [laughs] Don't put your normal tires to 70 psi. [laughs] Um, so those kinds of things, where, why did you add people? What do they add to your team to get to that objective? I'm like Dr.
• 9:41
  Cole's just solved newlywed problems across the globe. [laughs] No, because it's like, think about that. You, you- [laughs] Just 'cause you lived a certain way before doesn't mean it's gonna work now, you know? Oh.
• 9:57
  And, but I also think about- It's universal. Yeah... I, I also think about how to reconcile that today with, with the, the rapid pace that technology is evolving.
• 10:07
  You've got AI that can give you a quick answer about something, a quick analysis about something, but then there's power in the doing. There, there's- Mm-hmm...
• 10:16
  power in the journey of exploring the possibilities, and, and I see that equivalent to anytime a new team member joins the team. It introduces a new possibility. It's a new context window.
• 10:26
  It's, it's, it's a new thing to morph into. Ooh.
• 10:29
  And if you don't, if you don't like move in that direction, then you're gonna miss a critical piece, which is all of the like AI guys out there who get all the answers but don't have any lived experience become walking encyclopedias, and then there's the truly wise who- Worse.
• 10:45
  Worse... move into like... Worse than worse. It's worse. Yeah. Or worse. It's worse than a walking encyclopedia. It's like- Well, you know what I mean though? It's like that's what I'm hearing... a zero ego.
• 10:52
  [laughs] Yeah. That, that's what I'm hearing you say is like I can get an answer from AI, but I still have to explore the possibility through lived experience. Yeah. Oh, 100%. You know what?
• 11:02
  I'm gonna pick on that marriage analogy for a minute. I've been married for almost 15 years. I, I'm gonna stay myself out. How many? Almost f- almost 15 years. There you go. All right. All right. Long enough.
• 11:10
  Um, almost 15 years. It's like 400 in celebrity years. What- [laughs] What you're... [laughs] By God's grace, I will always stay below that threshold of celebrity. Um- Yeah. [laughs] So the...
• 11:23
  Look, when you think about early marriage, what you're describing, right, with, with you, you go to Gemini, it gives you a quick answer. You wanna know what pissed off my wife more than anything else?
• 11:35
  [laughs] Me listening to half the context and immediately telling her eight things that'll solve the problem. Here's how you can do it. Here's how you can fix this. It didn't solve the problem.
• 11:44
  [laughs] So when you- It created three new ones, actually. [laughs] It created some new ones, right? Yep. So I, I think there's an apt analogy in there.
• 11:52
  When you're introducing a new teammate, you're introducing a new technology. We'll call it a large language model AI for the sake of today's conversation. Mm-hmm.
• 12:01
  When you introduce it and you don't allow the team to guide it with context- Mm-hmm... you're introducing a new ignorant, strong voice. Ooh. And that's not how you go faster. Right?
• 12:15
  So how do you refine- You don't want ISV. You don't want that. [laughs] Yeah, a- and there we go. You need an ignorant- We're gonna do-... strong voice... a new three-letter acronym out of this.
• 12:23
  [laughs] That, that ignorant strong voice joining a conversation, joining a team meeting, joining a customer conversation- Ooh... that breaks- Wow... the relationship. Mm. Right? [laughs] Oh my God.
• 12:39
  We're going so much- I'm like, I'm like- Right? Oh, AI... we could take so many threads right now. [laughs] We need an ignorant strong voice panel at ASOTU Con. [laughs] Ignorant strong voice. That is so genius.
• 12:50
  [laughs] How many times have I- I'm like, I-... showed up and an ignorant strong voice is present on a call? I mean, it's absolutely unbelievable.
• 12:57
  Well, I'm thinking about all the times in the past when I've showed up as an ignorant strong voice. I have as well. Right? Right? It's like that's what happens- Fair... when I... [sighs] I'm writing it down...
• 13:08
  a lot of people that we work with, right? And in the auto industry, right, we have a lot of type A people in general, right? Name them. So, uh, we want to adopt stuff and then, like, know a little bit, and then, like,
• 13:19
  go deploy and try. I think it really is kind of both sides of the line of being entrepreneurial-minded and being willing to do stuff and execute.
• 13:27
  Like, in this day when there's a lot of new technology, it takes twice as much work to not be an ISV. Yeah. It would just, like it, it really does. John- But-... go ahead.
• 13:38
  I, I, I, I wanna bust in because your, your, your w- work history is CTO, CPO, which is kinda, that's...
• 13:47
  We could, like, spend a minute on that, the fact that you, like, went between those two roles because I think that a lot of times they're very separate, but then they can come together.
• 13:55
  It's a beautiful marriage when they work together. Um, but
• 13:59
  now that you're kind of running, you're l- really leading the AI practice for ACV, the, the scrutiny of anybody that's leading that practice for any organization right now is, like, at an all-time high because there's so much intense focus on it.
• 14:19
  And you,
• 14:21
  y- like, a lot of times everybody that is kind of, like, a little bit ahead of the curve, right, or leading that practice almost acts like an ISV, an ignorant strong voice, because it's, it's like you, you almost have to.
• 14:35
  Like s- everyone's looking to you to be like, "So what do we do about AI?" You know? Mm.
• 14:39
  How are you balancing that personally and then within the organization to make sure that you're making the right decisions moving forward and not just, like, kinda coming in guns a-blazing and going like, "Well, 'cause everybody else is, we have to."
• 14:52
  You know? Whatever it is. Well, I, I think the advantage of, of some of those components of work history, and I'll, I'll answer the question a few different ways on the work history side.
• 15:02
  Like, having had the pleasure of being automotive for the last seven years, when I joined ACV, right, we, day one I was pulled out to do an interview. We were growing so fast. Everything was happening.
• 15:14
  But at the end of the day in automotive, like, I'm not gonna kill somebody if I do the data thing wrong.
• 15:21
  Like, in defense, in counter-terrorism, healthcare, like some of those spaces, you have to learn the practice of assessing the risk, of really thinking through your decision, taking into account all the strong voices, refining it a little bit, and then making a call.
• 15:39
  And you gotta find a way to listen well, make a call, and then always be willing to take in new information.
• 15:47
  And so when I think about that foundation, then it goes to that question of, okay, today, in this moment when token maxing and all these hot trends in AI are all over the place, one of the things that I focus on is we need to align our spend, our time, right, our time, talent, resources with the product objective and the customer objective that we value, that we are trying to accomplish.
• 16:15
  If you're misaligned on those, yeah, you'll burn millions of dollars in tokens and half-ass ideas that aren't gonna come to fruition.
• 16:24
  But if you listen through your product vision, your customer needs, and solve pain points in their journey, then yeah, spend well, invest well, um, but don't get caught up in the m- the, the, what everybody else is doing in AI.
• 16:40
  Um, if you apply... I, I joke with people, if you apply AI, it's just like in Captain America, it's the serum. You, you apply AI to Captain Rogers, you get awesome- [laughs]... strong, excellent processes.
• 16:58
  You apply AI willy-nilly to half-baked processes, not thought through stuff, and the wrong objectives, you get Red Skull. For those of you listening- That's a great way-... if you haven't followed- God...
• 17:08
  that is an analogy. Supervillain. Come on. Go watch it. That's a great analogy. Or, or you get Captain America watched in reverse where he goes into the thing and comes out scrawny. [laughs] No, that's what you do...
• 17:22
  That's what happens if you spend all your money without a plan. Yeah, you'll- Yeah. [laughs]... you'll go in, spend all your- Yeah. [laughs]... come out scrawny.
• 17:29
  Yeah, no, when you have good process and you listen well to your product leaders- Mm-hmm...
• 17:36
  your customers and their true pain points, and then you apply AI to targeted solutions, just like we said in the beginning, who's in the bus? Who's on the team? Where are you going?
• 17:48
  If you don't have those two things, you'll miss. Mm. That's true of any leadership journey, and especially true right now when there's so much pressure. Spend faster, make decisions faster. Mm.
• 17:59
  What is the customer pain point we are solving, and how do we delight them along the way?
• 18:05
  Apply AI to help that be true, and that will align with your product, your tech vision, and your business and financial objectives- Oh... no matter what pressure you're put under. So- How is that- Oh, yeah...
• 18:16
  how is that focus and that feedback loop kinda working within ACV right now? Like, because you're dealing with, with that- What are you hearing?
• 18:25
  Because there's so much noise in the industry, the signal is a- almost hard to see. But what are you hearing that's rising to the top that you guys are creating out of? Yeah.
• 18:35
  I, I mean, um, things that we're really focused on, like, my, my background is, you know, you, you called me Dr. Coles earlier, right? So my PhD is in operations research. Core fundamental machine learning and OR.
• 18:50
  That's where most of the value and true, um, optimization or refinement is being created today.
• 18:57
  And so doubling down on areas in machine learning and connecting vehicle valuation, which you use machine learning for consistent, high quality, repeatable, and fast, those pieces are needed to get into a customer's journey well.
• 19:17
  You think about if your webpage doesn't load in less... Let's say y- this webpage loaded in 10 seconds. Oh, my goodness. You, you wouldn't even show up, right? That is our customer's experience.
• 19:30
  When we put things in front of a customer, be it ACV's customer or us empowering our dealers with our tool set, we need to get in front of a consumer something that loads as fast or faster than today's webpage.
• 19:45
  That is where the value is. It's in speed, consistency, and trust. How do you get- Yeah-... the consumer- Speed is trust-... to trust?... bro. Speed is trust. Ah. No, no, no, no.
• 19:55
  I'll talk to you about that for a minute. That's the... No, that's the lie in automotive we've all gotten hopped up on. The faster I say something, the more true it is. That's baloney, man.
• 20:06
  I was gonna say something stronger, but- [laughs]... that- that's baloney, right? You can't just proxy speed so that people can't think fast enough.
• 20:16
  We've gotta give them quality results fast and build trust underneath it. Thank you. One of the best cases for- For sure... large language models, explain why. Mm. That's what it's phenomenal at. Don't make up a number.
• 20:32
  You use a large language model to make a number up, oh, my goodness, dude. You'll have all kinds of interesting- [laughs]... different numbers. You explain why the number is the way it is,
• 20:43
  now you're cooking with gas- Ah... with the dealer, with the customer. I, I- Mm... I'm gonna, I'm gonna argue with you here real quick. Yes. I think- All right, Kyle.
• 20:50
  Uh- I, because- Paul, what did you have for lunch today? [laughs] Because, because speed, speed is equivalent to trust. People trust at a higher rate naturally, right? What becomes more apparent...
• 21:06
  Like, imagine you walk into a room and, and- Yep... you just, like, ask, you know, a really hard question. If someone answers confidently and quickly, there's a higher level of trust.
• 21:17
  Which means, which means the onus is on the conversationalist to approach with honesty, right? Trust is broken when honesty is not preserved, and that's the problem that auto has. Hmm.
• 21:35
  If auto presents speed as trust, which is true, it's naturally true, right? Where at, whatever I get the fastest answer from, I trust the most, right? The broken trust is what we've done a bad job with.
• 21:48
  We- we've, we've brought dishonesty behind any level of speed or a promise that we have, and so that creates broken trust. Interesting. We, I, we are gonna need to, I am sure, have a full follow-up podcast.
• 22:04
  It's perfect 'cause Kyle's start- Kyle's starting a podcast, it's called You're Smart, and I feel like you should be the first guest. [laughs] Bro, you and I are going for an hour. Like- Done. I think- Done...
• 22:13
  this has to be episode one, Kyle. I just helped you get a little further up the hill- [laughs] Roll that-... to roll the boulder over... roll that boulder.
• 22:18
  You c- here's what, Kyle, you fly into Syracuse, John, you come over, we'll have a in-person podcast. You guys can just- It's gonna be magical... roll down the windows. Shorts and T-shirts in November. Yes. I'll show up.
• 22:28
  [laughs] I'll be the last one- We're doing it outside. [laughs] I'll be the last one to speak, and we'll see where the trust lands. Beautiful. We're gonna have so much fun.
• 22:37
  All right, tell me this before we run out of time. Uh, what are you working on right now?
• 22:41
  Like, you just laid out all these beautiful leadership principles and this very well-thought-out approach to AI and data and what it can do. Uh, what are you working on right now? Like, what are you making better?
• 22:52
  What- Yeah, so one of the things that, you know, at, at ACV, one of the things we've invested so heavily in is our teammates. Our teammates and our partners.
• 23:03
  And so one of the things I get really excited about right now is actually rolling out suites of skills, they're called, in Claude, to our frontline teammates. Hey.
• 23:14
  And that, to me, is one of the things when I think about who should you give the best tools to, it's the people who are on the front line. Mm.
• 23:23
  And there's a whole other philosophy we have to cover someday, I learned from disaster management, but you push decisions as close to the work as possible. Mm.
• 23:31
  To do that effectively, using AI tooling to get the skills and the repeatable processes at the front line, I get so excited about empowering those teammates at the front line.
• 23:44
  Can you give us an example of one that you like, you're like, "This one crushed"? Yeah. So one of the things, you know, we're...
• 23:51
  I, I gotta be careful here 'cause I'm excited about these, but we're also public, blah, blah, blah, blah, blah. [laughs] It's all right. Is- We won't tell anyone... getting, getting... [laughs] Yeah.
• 24:01
  Getting, uh, policies, industry standards, current information on recalls, damage, all of that, can you imagine if a chat, just anybody using it in a front line, just said, "Hey, I'm looking at this exact car," and it perfectly read AAA policy, it perfectly read the company policy, it perfectly understood current recall information and then said, "Hey,
• 24:30
  this is common wear and tear on this car." And if you're a buyer, here's how you can dra- in a wholesale environment, here's how you prep that vehicle for a consumer in an ethical way.
• 24:43
  If you're a seller, hey, here's how you disclose it appropriately- Love that... in these marketplaces. Like- Yes... empowering them through our teammates and tools, that's what we're all about.
• 24:53
  It's like empowering them to be more honest. I, it's like really a beautiful thing. Um, I mean, this time flew by. What- I'm already like- What a dream. Man, John- [laughs]...
• 25:02
  I think we've all just, like, when Michael's writing notes, I'm waving my hands, and Paul's looking off in the distance. And I'm corralling us. You've done a great job. [laughs] Thanks for hanging out with us.
• 25:13
  We're gonna do this again on the- You are... Your Smart podcast. Now everybody knows what the title is. We can't put it back in the hopper now. [laughs] Uh, and it's gonna be a bunch of fun. John, thanks for joining us.
• 25:22
  [upbeat music] Okay, I stand corrected. I couldn't be more wrong. He's, he's totally revolutionized the, my, my perceived data nerdiness of what I expect in an interview.
• 25:36
  Fir- first of all, but like before the data thing, 'cause, like, it's clear he thinks deeply about this, did you see how him and Kyle perked up about minivans? [laughs] Right. God, tell a- Right.
• 25:47
  See, that goes back to my initial comment about you and the pickup truck and the motorcycle. Tell a pas- tell a pastor's kid about a minivan- [laughs]... and it's on. It's on.
• 25:55
  It brings up all kinds of- You get this cousin who rides a scooter... all feelings. Yeah. [laughs] Yeah. All the feelings come up.
• 25:59
  How cool is it to have somebody like him with the purview and the amount of access he has to data and analytics, and thinking about the approach in such a human way?
• 26:08
  Like, it just solidifies the thesis that inside retail auto we have a chance to set the tone for other industries when it- Yeah... comes to new technology. Period. I was- Full stop. I mean, I, I was impressed.
• 26:19
  Again, here we have a really practical example about the inside workings of a o- organization and how they're using AI.
• 26:25
  Like, "Hey, let's just use it internally to bring all of our information together so that our reps can handle things more efficiently."
• 26:33
  That, like, I think a lot of people struggle with that because it's not necessarily, like, shiny and oh my God- It's not the sexiest thing. Yeah, it's not the sexiest thing.
• 26:40
  Paul, do you know, actually last week Paul posted, uh, uh, last week, uh, time of recording, Paul posted something about, like, what, what does a fired-up employee mean? Yeah, an ROI on a fired-up leader.
• 26:49
  You can only imagine, like, a well-equipped, fired-up employee that has what they need to do the job and communicate well, what that does that you don't need AI for. That's right. Hm. I love it. Oh, so good.
• 27:01
  What a, what- Oh. What a surprise. [laughs] I should still be surprised. Now my brain is all sideways, and I need to go make things. I know. Need to go make things- Yeah...
• 27:10
  and hopefully they're things that are actually productive, but you know, roll the dice. You never know. Roll the dice. Well, listen, we hope you enjoyed this episode of Auto Collabs. Thanks so much for joining us today.
• 27:19
  On behalf of Kyle Mountsier, who's over here, Paul Jay Daly, myself, Michael Cirillo, we hope to see you on the next episode. [upbeat music] Welcome to Auto Collabs. Welcome to Auto Collabs.
• 27:35
  [laughs] Kyle, are we recording yet? Are we rolling yet? Not yet.