1 00:00:00,560 --> 00:00:04,400 Maintain your integrity. I mean, have fun. Get out there 2 00:00:04,480 --> 00:00:07,200 and find what your personal 3 00:00:08,000 --> 00:00:10,720 AI training plan is in 2026. 4 00:00:12,160 --> 00:00:15,760 Try different tools, get out there, push boundaries. But 5 00:00:15,760 --> 00:00:19,080 along the way, maintain your professionalism, maintain your 6 00:00:19,080 --> 00:00:22,720 integrity, and just show up better for yourself 7 00:00:22,720 --> 00:00:26,400 and for your business or whoever you support. Good 8 00:00:26,400 --> 00:00:30,120 morning, good evening, good afternoon, wherever you are, wherever you're watching from, Matt Pierce 9 00:00:30,120 --> 00:00:33,460 here from the Visual Lounge, we've got our friend Josh 10 00:00:33,460 --> 00:00:37,300 Cavaliere. We're talking and diving into his new book, which if you 11 00:00:37,300 --> 00:00:40,980 don't have Applying AI in Learning Development, you should go check it 12 00:00:40,980 --> 00:00:44,740 out. It is fantastic. In fact, there's so much here I have not read 13 00:00:44,740 --> 00:00:48,220 it all. Sorry about that, Josh, but Josh has been a longtime friend of the 14 00:00:48,220 --> 00:00:50,900 show and we just want to jump into you because we've got so much to 15 00:00:50,900 --> 00:00:54,340 talk about here. So welcome to the Visual Lounge, Josh 16 00:00:54,340 --> 00:00:57,900 Cavaliere. Hey, Josh, I'm so glad that you're here. 17 00:00:58,460 --> 00:01:02,260 First of all, congratulations on the book. What a huge accomplishment to do 18 00:01:02,260 --> 00:01:06,040 that. Why don't you give us some, a quick high level overview? What, 19 00:01:06,200 --> 00:01:10,000 what are we looking at here? Yeah, so when 20 00:01:10,000 --> 00:01:13,320 I first got into doing workshops and 21 00:01:13,640 --> 00:01:17,480 consulting around AI and L&D in 2023, 22 00:01:17,720 --> 00:01:21,400 I began noticing patterns that were happening in the marketplace, 23 00:01:21,800 --> 00:01:25,160 like the maturation of a prompt into a prompt library. So notice all these 24 00:01:25,160 --> 00:01:28,920 tactics. But then it became evident that there was going to be significant 25 00:01:29,160 --> 00:01:32,810 impact with our profession and then also 26 00:01:32,810 --> 00:01:36,330 the tools and platforms that we use. And it's a lot, it's a lot to 27 00:01:36,330 --> 00:01:39,770 process when you have all these new 28 00:01:39,770 --> 00:01:43,450 capabilities that are impacting development tools and 29 00:01:43,450 --> 00:01:47,170 video tools and all these things that we've been using for decades. But then 30 00:01:47,170 --> 00:01:50,650 you also have all these, you know, how does this capability 31 00:01:50,650 --> 00:01:54,370 work? How does AI work? And so as 32 00:01:54,370 --> 00:01:58,170 I began interfacing with other professionals and doing 33 00:01:58,170 --> 00:02:01,880 these workshops, I realized where all the gaps were at. And so the 34 00:02:01,880 --> 00:02:05,640 book really is an output of recognizing that one, 35 00:02:05,640 --> 00:02:09,200 the profession is changing, our platforms and tools are 36 00:02:09,200 --> 00:02:12,360 changing, and the way that we work with AI is really 37 00:02:12,360 --> 00:02:16,040 instrumental in moving everything forward. And that, that essentially is the 38 00:02:16,040 --> 00:02:19,680 book. So what? One of the questions I have is, 39 00:02:19,760 --> 00:02:22,200 you know, I, like I said, I haven't had a chance to read it all. 40 00:02:22,200 --> 00:02:26,040 It's been a busy couple weeks since, since it arrived. But thank you for 41 00:02:26,040 --> 00:02:28,240 the, the copy for sure. 42 00:02:29,920 --> 00:02:33,560 One of the things I wonder about in terms of, you know, 43 00:02:33,560 --> 00:02:37,400 people diving into AI, if I was new 44 00:02:37,400 --> 00:02:41,200 and I'm struggling with maybe the approach to AI, or I'm just trying to wrap 45 00:02:41,200 --> 00:02:43,120 my head around it, Inside of my organization. 46 00:02:44,880 --> 00:02:48,680 High level. What, what's something that, like kind of big 47 00:02:48,680 --> 00:02:52,480 takeaway that I could, I could get here that's going to maybe change 48 00:02:52,640 --> 00:02:56,400 the, my. Either my relationship with AI or change the way my organization 49 00:02:57,130 --> 00:03:00,250 is looking at applying AI in, in the jobs that we do. 50 00:03:02,490 --> 00:03:06,290 Well, I would say go read the whole book, but if you had to, if 51 00:03:06,290 --> 00:03:10,050 you had to like really focus in on just a few chapters 52 00:03:10,050 --> 00:03:13,810 and what those topics are. One is the front matter, like 53 00:03:13,810 --> 00:03:16,970 the first couple chapters. One is how did we get here? 54 00:03:17,370 --> 00:03:21,090 Chapter one, Chapter two is the transformation of a 55 00:03:21,090 --> 00:03:24,770 learning development professional to a human machine performance analyst. What does 56 00:03:24,770 --> 00:03:28,600 that mean? What, what skills do you need? And then it's getting into 57 00:03:28,600 --> 00:03:32,320 the ethics and governance and security as we 58 00:03:32,320 --> 00:03:35,960 move forward. But then the rest of the, 59 00:03:36,680 --> 00:03:40,520 I guess the chapters four through seven get into the 60 00:03:40,840 --> 00:03:44,480 platforms and tools and how does 61 00:03:44,480 --> 00:03:48,120 that show up? And then there's tactics in the back in regards to prompts and 62 00:03:48,120 --> 00:03:51,160 the maturation all the way to an agent and chatbots. So 63 00:03:51,880 --> 00:03:54,950 to peg it, I mean, if I had to like, okay, if somebody is like 64 00:03:55,350 --> 00:03:58,950 really just getting into it new and they can only read or get through a 65 00:03:58,950 --> 00:04:02,670 few chapters is one and two, like, how 66 00:04:02,670 --> 00:04:06,390 did we get here? What's the transformation? And then I would jump right 67 00:04:06,390 --> 00:04:10,110 to eight, which is how to prompt, like, how, how can 68 00:04:10,110 --> 00:04:13,230 I start being like, I know where I sit, I know where I need to 69 00:04:13,230 --> 00:04:16,630 go now, I need to be productive tomorrow. Right. 70 00:04:16,950 --> 00:04:19,270 And that's going to go ahead and give you the base 71 00:04:20,150 --> 00:04:23,980 understanding of, you know, your trajectory, where you're 72 00:04:23,980 --> 00:04:27,820 headed. But then you can show up so much better tomorrow if you 73 00:04:27,820 --> 00:04:31,620 have access to some type of model. And then how do you start working 74 00:04:31,620 --> 00:04:35,420 with it? Yeah, well, I appreciate that kind of overview. Right. Because 75 00:04:35,420 --> 00:04:38,700 I do think there's, there's a lot in AI. I think a lot of people 76 00:04:38,700 --> 00:04:42,100 are just feeling their way through the systems there. 77 00:04:42,340 --> 00:04:45,820 Maybe they've experimented with it, they've tried one. Maybe their company's brought in 78 00:04:45,820 --> 00:04:49,540 Copilot or Gemini or something, depending on their back end system. 79 00:04:52,340 --> 00:04:56,180 One of the challenges I think our industry is facing and everyone who's listening 80 00:04:56,580 --> 00:05:00,260 just faced with the reality of AI is that it's changing 81 00:05:00,580 --> 00:05:04,380 incredibly fast. I know. I've seen stuff that you've posted and 82 00:05:04,380 --> 00:05:07,420 Sam Rogers have been posting about. I'm not even sure if I'm going to say 83 00:05:07,420 --> 00:05:11,180 this right. Nana Banana Pants. I don't remember. I don't even know 84 00:05:11,180 --> 00:05:14,860 the name of it. Nano Banana. Yes. Yep. Nano Banana. It 85 00:05:14,860 --> 00:05:18,660 seems like everything is just moving at speed where, I mean, look, technology 86 00:05:18,740 --> 00:05:22,580 has always changed. It's always changed rather rapidly. But this seems like at a 87 00:05:22,660 --> 00:05:26,380 magnitude faster, you know, scale a couple 88 00:05:26,380 --> 00:05:29,980 times faster than we, I think we've seen before. So particularly as you're, you know, 89 00:05:29,980 --> 00:05:33,459 you're thinking about, like, this information, I'm guessing this is pretty evergreen 90 00:05:33,460 --> 00:05:36,260 content in terms of solid concepts. 91 00:05:37,060 --> 00:05:40,180 But what do you say to us trying, to those of us who are just 92 00:05:40,180 --> 00:05:44,030 trying to keep up with our day jobs and follow along and maybe 93 00:05:44,190 --> 00:05:47,710 be a little bit productive with AI? I get that question all the time, 94 00:05:47,710 --> 00:05:51,390 like, how do I keep up with what's going on? 95 00:05:51,550 --> 00:05:55,270 And you have to find your sources of truth. Like, you have to sort 96 00:05:55,270 --> 00:05:58,910 through all of the noise that's out there and get signal as to, 97 00:05:58,990 --> 00:06:02,670 as to what's happening in the marketplace and 98 00:06:02,910 --> 00:06:06,710 be able to understand that whatever happens in the marketplace, how is it going 99 00:06:06,710 --> 00:06:09,640 to impact you as a professional? How does, what does that look like? How does 100 00:06:09,640 --> 00:06:13,440 it show up? And so for myself, I 101 00:06:13,440 --> 00:06:17,160 have my YouTubers that I'll watch either in the morning or while I'm 102 00:06:17,160 --> 00:06:20,720 working out or whatever. I have a couple newsletters. I 103 00:06:20,720 --> 00:06:24,439 have people that I subscribe to their 104 00:06:24,439 --> 00:06:28,280 substack because they're extremely intelligent and they write all kinds of 105 00:06:28,280 --> 00:06:31,760 great content. So you have to find your signals out there 106 00:06:32,560 --> 00:06:36,280 again. When the sands shift, as they did last 107 00:06:36,280 --> 00:06:39,620 week with Gemini, you know, Gemini 3 nano 108 00:06:39,620 --> 00:06:43,060 banana pro, the. The 109 00:06:43,060 --> 00:06:46,500 definition of work outputs changes. 110 00:06:47,060 --> 00:06:50,700 Like, how do we get to this work output? You start having new 111 00:06:50,700 --> 00:06:54,020 conversations around, how do we get to 112 00:06:54,260 --> 00:06:57,700 a slide deck, how do we get to this job 113 00:06:57,700 --> 00:07:01,140 aid? And when, when the, when the sands shift, 114 00:07:02,260 --> 00:07:06,100 how are you going to react to that? Like, can we get this technology 115 00:07:06,340 --> 00:07:10,100 in house so that we can reconstitute 116 00:07:10,100 --> 00:07:13,540 or rethink our workflows to support the business 117 00:07:14,100 --> 00:07:17,940 at a different level? Right. And that takes effort. Like, you 118 00:07:17,940 --> 00:07:20,980 have to be incredibly intentional. And I think one of the 119 00:07:21,540 --> 00:07:25,180 skills that everyone needs to acquire, if you 120 00:07:25,180 --> 00:07:28,820 don't already have it, is adaptability is being 121 00:07:28,820 --> 00:07:32,650 flexible. And some people don't operate like that. And 122 00:07:32,650 --> 00:07:36,250 I get it. You know, you get you enjoy what you 123 00:07:36,250 --> 00:07:39,490 do. You love going in deep and doing the work, 124 00:07:40,290 --> 00:07:44,090 but the world is changing around you at an exponential rate, and you 125 00:07:44,090 --> 00:07:47,850 have to respond accordingly. And I know that makes individuals very 126 00:07:47,850 --> 00:07:51,570 uncomfortable, especially when they've been doing their job 127 00:07:51,570 --> 00:07:54,690 or their role for a decade or two decades. 128 00:07:55,500 --> 00:07:59,260 So this adaptability and the notion 129 00:07:59,260 --> 00:08:02,460 or the thought of work is changing. 130 00:08:02,860 --> 00:08:06,580 If you lean into it, it's going to be a much easier ride. Than 131 00:08:06,580 --> 00:08:09,420 if you push away and say, 132 00:08:10,780 --> 00:08:12,860 no, I don't think this AI thing is for me. 133 00:08:14,620 --> 00:08:17,980 So I want to talk about that for a minute because I do think, 134 00:08:18,140 --> 00:08:21,500 let's assume someone listening is feeling like, well, I feel 135 00:08:21,840 --> 00:08:25,280 fairly adaptable. Like it's not maybe my strongest. But I'm not, Not 136 00:08:25,280 --> 00:08:28,920 completely. Ludi Clankers. 137 00:08:28,920 --> 00:08:32,640 Sorry. Robots. Sorry. I. You 138 00:08:32,640 --> 00:08:35,520 know, and they're making the changes. But there's. 139 00:08:36,560 --> 00:08:40,280 I know I've experienced it. Sometimes there's a mismatch between my willingness to do 140 00:08:40,280 --> 00:08:43,840 something, my organization's willingness to do something. Sometimes they're ahead, 141 00:08:43,840 --> 00:08:47,680 sometimes I'm ahead. So what advice would you 142 00:08:47,680 --> 00:08:51,220 give someone to. To help them, particularly with 143 00:08:51,300 --> 00:08:55,100 this case? I mean, there's lots of times we've had to be adaptable, but with 144 00:08:55,100 --> 00:08:58,660 AI again, we've got a couple of things I think are happening. We've got the 145 00:08:58,660 --> 00:09:02,500 speed, we've got. We haven't settled on necessarily. There's lots of 146 00:09:02,500 --> 00:09:05,740 platforms. Right. We could talk about Gemini. We can talk about things that OpenAI is 147 00:09:05,740 --> 00:09:09,140 doing. We could talk about Claude. You know, like, there's, 148 00:09:09,140 --> 00:09:12,980 there's, then there's a million other things that are integrating 149 00:09:12,980 --> 00:09:16,700 AI in different ways. So it feels like there's also this kind 150 00:09:16,700 --> 00:09:19,800 of flood of, of choice option. 151 00:09:20,280 --> 00:09:24,000 You know, it's, it's nice when one is in the lead because then 152 00:09:24,000 --> 00:09:26,680 I feel like I can have some confidence, but usually it's not clear. 153 00:09:27,640 --> 00:09:30,680 And so how does someone just. 154 00:09:31,720 --> 00:09:35,240 I almost want the therapy is to be a therapy session, like, how do I 155 00:09:35,240 --> 00:09:39,080 change? How do I change and adapt so quickly? But particularly when it's AI, 156 00:09:39,160 --> 00:09:42,760 Is this something that, like, would you recommend and maybe in your workshops you do 157 00:09:42,760 --> 00:09:46,510 this to. Should people be going out and should they just be making stuff 158 00:09:46,670 --> 00:09:50,390 like, how do we make this practical for people who are listening? 159 00:09:50,390 --> 00:09:53,870 This particularly in L and D. But also, you know, I think about the people 160 00:09:53,870 --> 00:09:57,470 who are doing imagery or videos. I mean, this is changing 161 00:09:57,470 --> 00:09:59,150 everything that we do in some way. 162 00:10:01,070 --> 00:10:04,670 It's a big question. Yeah. So, you know, for 163 00:10:04,670 --> 00:10:08,190 me, it's about understanding your 164 00:10:08,190 --> 00:10:11,620 expertise, you know, getting back to the human, like, 165 00:10:11,620 --> 00:10:15,180 knowing where you are at as a professional and being, being honest about, like any 166 00:10:15,180 --> 00:10:18,940 kind of deficiencies and whatnot. Like, maybe I need to up my skills 167 00:10:18,940 --> 00:10:21,860 and data and analytics. Maybe I need up my skills in business acumen. 168 00:10:23,380 --> 00:10:26,420 If I'm a videographer, maybe I, I want to go ahead and learn how to 169 00:10:26,420 --> 00:10:29,380 shoot with a new piece of equipment or whatever the case may be. Right, 170 00:10:30,340 --> 00:10:33,700 that's. That's the one that's so there you're, you got your own identified gap. 171 00:10:34,100 --> 00:10:37,730 Then you have, you want access to multiple models. 172 00:10:37,810 --> 00:10:40,930 That is the key. I say this to all of my 173 00:10:41,170 --> 00:10:44,850 customers, even individual students, that you need 174 00:10:45,410 --> 00:10:49,250 access to multiple models. You cannot park yourself 175 00:10:49,250 --> 00:10:52,850 into one ecosystem of just OpenAI or just a 176 00:10:52,850 --> 00:10:56,610 Google shop or anything like that. So how like, oh 177 00:10:56,610 --> 00:11:00,450 wow, I don't have a budget. Let's say I 178 00:11:00,450 --> 00:11:04,150 got 20 bucks like a month, right? To invest in yourself. 179 00:11:04,470 --> 00:11:08,070 Well, that's when you go to like po.com 180 00:11:08,070 --> 00:11:11,750 you get access to all of these different models, text based, 181 00:11:11,750 --> 00:11:15,150 right. Or you get access to 182 00:11:15,150 --> 00:11:18,950 Firefly from Adobe and then you have access to all of these 183 00:11:18,950 --> 00:11:22,750 various models. Right. And as opposed to like double down saying, 184 00:11:22,750 --> 00:11:26,270 oh, I'm just only using Google, some of the 185 00:11:26,270 --> 00:11:30,050 customers that I work with, they give their associates access 186 00:11:30,130 --> 00:11:33,850 to 14 or 15 different large language models and 187 00:11:33,850 --> 00:11:37,410 some video and some image models. I mean they're watching 188 00:11:37,410 --> 00:11:41,010 their budget around that. But it's all secure, 189 00:11:41,090 --> 00:11:43,810 it's all through Microsoft Azure via APIs. 190 00:11:44,850 --> 00:11:48,530 And it's wonderful because they can go ahead and test and pressure test 191 00:11:48,530 --> 00:11:52,330 all of their workflows against various models as those models 192 00:11:52,330 --> 00:11:56,180 change. That's where you want to be, right? So when 193 00:11:56,180 --> 00:11:59,900 you think about your workflows and doing tasks at the atomic 194 00:11:59,900 --> 00:12:03,460 level, there's going to be these radical shifts that happen in 195 00:12:03,460 --> 00:12:06,540 regards to capabilities and your awareness 196 00:12:07,500 --> 00:12:11,340 of those capabilities and how they impact what you do day in and day 197 00:12:11,340 --> 00:12:15,060 out is essential because the conversation is going 198 00:12:15,060 --> 00:12:18,900 to shift and change about that work output and how it's 199 00:12:18,900 --> 00:12:22,390 accomplished. And, and if you have your head in the sand and you come up 200 00:12:22,390 --> 00:12:26,190 after six months, you could, you could find yourself in a world 201 00:12:26,750 --> 00:12:30,390 that these particular outputs or capabilities have 202 00:12:30,390 --> 00:12:33,630 radically changed and you have to play catch up, right? 203 00:12:34,270 --> 00:12:37,790 So that adaptability and 204 00:12:39,710 --> 00:12:42,990 understanding that we're in a constant state of change. 205 00:12:44,270 --> 00:12:47,740 Preparing yourself for that and investing in yourself, 206 00:12:47,900 --> 00:12:51,580 like what is your personal Learning 207 00:12:51,580 --> 00:12:55,420 plan for 2026 in AI? You may have your workout plan 208 00:12:55,420 --> 00:12:59,260 set in January, New Year, New Me, but what does it look like with AI? 209 00:12:59,260 --> 00:13:02,900 And I mentioned that to everybody, like use whatever 210 00:13:02,900 --> 00:13:06,060 model, copilot, whatever you got access to to help you make that plan. 211 00:13:06,620 --> 00:13:09,980 Where are your sources of truth? What are the videos you watch, should watch every 212 00:13:09,980 --> 00:13:13,440 morning or once a week on Fridays? I know I do. 213 00:13:13,600 --> 00:13:17,360 I'm watching Matt Wolf, I'm watching Matthew Berman, I'm watching 214 00:13:17,520 --> 00:13:21,200 Nate B. Jones because they're great thinkers, they're 215 00:13:21,200 --> 00:13:24,880 pragmatic and they give you some guidance as far as what's happening out there. 216 00:13:25,120 --> 00:13:28,960 So it's a shift. It's most definitely a 217 00:13:28,960 --> 00:13:32,400 shift. But I think once everyone 218 00:13:32,560 --> 00:13:34,400 gets used to this pace, 219 00:13:36,240 --> 00:13:40,040 they'll begin to understand the relationship with the technology better and how they 220 00:13:40,040 --> 00:13:43,850 need to show up. Yeah, I guess I should be listed 221 00:13:43,850 --> 00:13:47,690 in all the mats. Maybe not great thinker, but I appreciated how many 222 00:13:47,690 --> 00:13:51,450 mats you listed out there. Josh, I want to talk a little bit 223 00:13:51,450 --> 00:13:55,250 about the work is changing because I do think on this show particularly, we 224 00:13:55,250 --> 00:13:58,850 talk a lot about images and video and the creation and from a learning 225 00:13:58,850 --> 00:14:02,290 development perspective primarily. But it is interesting 226 00:14:02,770 --> 00:14:06,290 the things AI is looking, it's looking more and more the things that 227 00:14:06,450 --> 00:14:10,300 you would do as an instructional designer traditionally or 228 00:14:10,300 --> 00:14:13,900 if you're, you know, training specialist or video producer or 229 00:14:14,380 --> 00:14:17,900 fill in role is starting to shift 230 00:14:17,980 --> 00:14:21,420 already, which I think is really interesting. Right. Like, and you said something to me 231 00:14:21,420 --> 00:14:24,979 before we got on the call about the bar raising. Can, can we 232 00:14:24,979 --> 00:14:28,540 revisit that? Because I do think, I do think that it's, it's 233 00:14:28,540 --> 00:14:31,500 interesting for us to think about. One, it's a, I think it ties back to 234 00:14:31,500 --> 00:14:34,780 the adaptability. But two, I think fundamentally, 235 00:14:35,640 --> 00:14:39,280 as you've said now, I think twice, work is changing and I think that's 236 00:14:39,280 --> 00:14:43,040 maybe not clear yet to everyone how 237 00:14:43,040 --> 00:14:46,720 that might be or what that might manifest itself like. Any 238 00:14:46,720 --> 00:14:50,440 thoughts? Yep. So when, 239 00:14:50,440 --> 00:14:54,200 you know, when this, when AI first came out, you know, we're getting 240 00:14:54,200 --> 00:14:57,920 reports in regards to AI's impact on tasks across various 241 00:14:57,920 --> 00:15:01,640 roles and people became very, very apprehensive, like, 242 00:15:01,860 --> 00:15:05,660 oh my gosh, this is going to completely take my job. And I think what 243 00:15:05,660 --> 00:15:09,300 we're actually seeing is a redefinition 244 00:15:09,940 --> 00:15:13,620 of the work output and what you do and how you get 245 00:15:13,620 --> 00:15:16,580 there. And because this technology 246 00:15:17,940 --> 00:15:21,620 is increasingly like it's constantly creating 247 00:15:21,700 --> 00:15:25,020 better, highly qualified, actionable 248 00:15:25,020 --> 00:15:28,820 outputs, then the bar gets raised for everybody. 249 00:15:28,900 --> 00:15:32,610 So for novices that are, maybe I'm not a graphic designer, 250 00:15:32,610 --> 00:15:36,290 but my gosh, last week with Nano Banana Pro, I 251 00:15:36,290 --> 00:15:40,050 can create an infographic in 10 seconds that is absolutely 252 00:15:40,050 --> 00:15:43,810 perfect and I can use it in my slide deck that has 253 00:15:43,810 --> 00:15:47,650 never happened before. So the bar is now set for those individuals 254 00:15:47,650 --> 00:15:51,050 to create picture perfect infographics. Now, let's say I'm a graphic 255 00:15:51,050 --> 00:15:54,730 designer. Well, now in my mind the 256 00:15:54,730 --> 00:15:58,390 bar is raised and I'm creating content pipelines, meaning 257 00:15:58,630 --> 00:16:02,150 I can go ahead and create an infographic that then feeds into a 258 00:16:02,150 --> 00:16:05,830 slide deck that then feeds into a video script that then feeds into 259 00:16:05,990 --> 00:16:09,750 a multimedia interactive presentation. Because I have 260 00:16:09,750 --> 00:16:13,510 all that experience and I know exactly how I'm solving The problems, 261 00:16:13,749 --> 00:16:17,590 it just shows up different because you have that experience. That's 262 00:16:17,590 --> 00:16:21,310 what we're getting at. And when it comes to specifically learning 263 00:16:21,310 --> 00:16:24,870 and development, it's the propagation of learning experiences at 264 00:16:24,870 --> 00:16:28,450 scale into work. And as an expert, 265 00:16:28,610 --> 00:16:32,370 there are many things that you need to know to make that happen 266 00:16:32,370 --> 00:16:36,050 at scale. Regardless of what other agents and 267 00:16:36,450 --> 00:16:40,170 platforms and what tools do you have to run policy on these 268 00:16:40,170 --> 00:16:44,010 things, you have to vet it out, you have to make sure that 269 00:16:44,010 --> 00:16:47,770 it's effective. So, you know, the 270 00:16:47,770 --> 00:16:50,690 rising tide lifts all boats. I think with technology 271 00:16:51,750 --> 00:16:55,390 it's the same thing. We're going to have so many professionals that 272 00:16:55,390 --> 00:16:59,030 were. And Matt, you and I have, we've done video workshops together 273 00:16:59,190 --> 00:17:02,910 where people are just apprehensive about video. Like there's, oh my gosh, 274 00:17:02,910 --> 00:17:06,550 there's so many different things that we have to learn. But when 275 00:17:06,550 --> 00:17:10,270 you can have a system that can do the lighting, that 276 00:17:10,270 --> 00:17:14,070 can do the characters, that can go ahead and set up the scenario, you're getting 277 00:17:14,070 --> 00:17:17,510 to the end product that you want, which is a great scenario based 278 00:17:18,010 --> 00:17:21,730 exchange or video and which, which is awesome. I mean, it's 279 00:17:21,730 --> 00:17:25,450 such an empowering feeling for people when they know they can go ahead and create 280 00:17:25,610 --> 00:17:29,330 a pointed solution that impacts the business, that impacts 281 00:17:29,330 --> 00:17:33,050 their associates, and that's where they're at to where 282 00:17:33,450 --> 00:17:37,130 now we have a baseline of how professionals are going to show up in regards 283 00:17:37,130 --> 00:17:40,970 to media creation. But for experts, the bar is going to 284 00:17:40,970 --> 00:17:44,500 be raised also as far as what they can create and 285 00:17:44,660 --> 00:17:48,500 you know, what the marketplace or what their business expects out of them. 286 00:17:49,300 --> 00:17:53,100 Yeah, I've often imagined that as we go through this change, it's like artisans of 287 00:17:53,100 --> 00:17:56,860 old, right? They would build, build, build. But now there's, there's 288 00:17:56,860 --> 00:18:00,580 boutiques, right? Like you have craftsman's crafts 289 00:18:01,060 --> 00:18:04,660 people who are doing things at a boutique kind of. It's a very special 290 00:18:04,660 --> 00:18:08,500 thing. It's, you know, very high quality. It's, you know, you get it 291 00:18:08,500 --> 00:18:12,170 because. Not because it's maybe perfect or mass produced, you get it because 292 00:18:12,170 --> 00:18:16,010 it's unique, it's special. And I do wonder there's going to be 293 00:18:16,010 --> 00:18:19,850 that kind of lane of traffic from an AI 294 00:18:19,850 --> 00:18:22,210 perspective that there's going to be things like, yeah, I just need to, I need 295 00:18:22,210 --> 00:18:25,450 the thing that's like ikea. I just need to assemble it. And then I also. 296 00:18:26,010 --> 00:18:29,490 But I want that piece over here to be the perfect piece. I want that 297 00:18:29,490 --> 00:18:33,210 to be the one that really speaks to the heart, not the fact that I 298 00:18:33,210 --> 00:18:36,980 need a cabinet. Yeah, I think there's 299 00:18:36,980 --> 00:18:40,500 gonna be plenty of room for that. And you're talking about 300 00:18:40,500 --> 00:18:44,340 massive creative unlocks for all kinds of different content 301 00:18:44,500 --> 00:18:48,340 at scale for individuals that they may have premeditated some 302 00:18:48,340 --> 00:18:52,060 type of book or some type of video or a movie 303 00:18:52,060 --> 00:18:55,620 or a TV show, but they had no way or the economics to 304 00:18:55,620 --> 00:18:59,420 produce anything. That's all changing. And 305 00:18:59,420 --> 00:19:02,100 I believe that's gonna go ahead and, and push 306 00:19:03,620 --> 00:19:07,060 all kinds of different media 307 00:19:07,140 --> 00:19:10,900 channels and in how outputs 308 00:19:10,900 --> 00:19:14,660 are created and who's part of that story and who can be 309 00:19:14,660 --> 00:19:18,260 included as part of that, whether it be on the small screen on 310 00:19:18,260 --> 00:19:21,820 YouTube or you're on some kind of cable or whatever, whatever the case may be, 311 00:19:21,820 --> 00:19:24,340 or just on an, in a learning environment. 312 00:19:25,780 --> 00:19:29,390 And that excites me because now 313 00:19:29,550 --> 00:19:32,670 we're being more inclusive as far as 314 00:19:33,230 --> 00:19:37,070 who can help tell that story or who can solve that 315 00:19:37,070 --> 00:19:40,750 problem. So one of the concerns with AI, Josh, 316 00:19:40,750 --> 00:19:44,110 and again, I would love to hear if you have 317 00:19:44,110 --> 00:19:47,710 perspectives or if you talk about this in the book at all, is we 318 00:19:47,710 --> 00:19:51,470 saw in the last couple months, channels like YouTube 319 00:19:51,470 --> 00:19:54,770 are cracking down on AI slot. People are generating, you know, 320 00:19:55,010 --> 00:19:58,530 these voice or faceless videos, we'll call it, with AI voice 321 00:19:58,610 --> 00:20:01,810 by cranking them out. Sometimes, you know, just 322 00:20:02,930 --> 00:20:06,690 we'll question the value of what they're. They're creating. And, and obviously we 323 00:20:06,690 --> 00:20:10,530 know that AI can get things wrong. You know, it does say very clearly we're 324 00:20:10,530 --> 00:20:13,410 responsible to make sure there's no mistakes in the information. 325 00:20:14,690 --> 00:20:18,210 When, when we look at our profession, we look at the changes that are happening, 326 00:20:18,210 --> 00:20:22,020 obviously move with the speed there, there's likelihood that things are 327 00:20:22,020 --> 00:20:25,020 gonna be wrong in the system. 328 00:20:25,980 --> 00:20:28,860 So what, what advice do you give to people who are out there? And that's 329 00:20:28,860 --> 00:20:32,620 the concern. And how do you, how do you make sure you're treating the stuff 330 00:20:32,940 --> 00:20:36,380 well, but not also maybe taking it just as is. 331 00:20:37,580 --> 00:20:41,140 Maintain your integrity. That's it. That is the word, 332 00:20:41,140 --> 00:20:44,820 integrity. Are you putting something 333 00:20:44,820 --> 00:20:47,590 out in the world that is noise or is it signal? 334 00:20:48,390 --> 00:20:52,110 And what is the, what is the process for vetting that 335 00:20:52,110 --> 00:20:55,710 information out? Are you just copying, pasting from the model and putting it out there 336 00:20:55,710 --> 00:20:58,950 on LinkedIn as a post, or using AI to make a comment? 337 00:20:59,750 --> 00:21:03,550 It doesn't resonate. Right. Humans are, I mean, we're 338 00:21:03,550 --> 00:21:07,190 really good at reading, you know, information 339 00:21:07,270 --> 00:21:10,990 that's in front of us and whether it's truly having an emotional 340 00:21:10,990 --> 00:21:14,610 connection. And that's where a lot of the AI content, whether 341 00:21:14,610 --> 00:21:18,290 you're reading it, whether you're viewing a video or even listening to 342 00:21:18,290 --> 00:21:22,010 music, you don't have those emotional 343 00:21:22,330 --> 00:21:25,890 attachments. Now that is changing though, right? So that is one of the 344 00:21:25,890 --> 00:21:29,290 unique things, is that we see this in some of the latest 345 00:21:29,290 --> 00:21:32,650 models and the way that they respond. I know that for myself 346 00:21:32,650 --> 00:21:36,010 personally, if I'm in an environment, like if I'm driving or something, I'll just flip 347 00:21:36,010 --> 00:21:39,830 on, chat GPT and have a conversation. Right? And 348 00:21:39,830 --> 00:21:43,390 it's kind of shocking how now there's more emotion in it. 349 00:21:43,470 --> 00:21:46,830 Same thing with audio specifically around. 350 00:21:48,830 --> 00:21:52,190 Not to name any vendors, but there's like some music creation tools that are out 351 00:21:52,190 --> 00:21:55,990 there that blow me away. Like we are at 352 00:21:55,990 --> 00:21:59,310 the cusp where you cannot tell it's AI, 353 00:21:59,710 --> 00:22:03,560 right? But for, and this is a 354 00:22:03,560 --> 00:22:06,840 perfect example of what I'm talking about, raising the bar for 355 00:22:08,600 --> 00:22:12,360 musicians to where they're like, oh, am I out of a 356 00:22:12,360 --> 00:22:14,680 job? No, they're not out of a job. They have a new tool that's going 357 00:22:14,680 --> 00:22:17,800 to allow them to play a riff and then that riff can go into AI 358 00:22:17,800 --> 00:22:21,200 and then they can orchestrate a whole new song within minutes. That would have taken 359 00:22:21,200 --> 00:22:25,000 them studio time and additional artists and bass players and 360 00:22:25,160 --> 00:22:28,680 all this other stuff. They're getting to their vision, to their end product 361 00:22:28,680 --> 00:22:31,800 faster, maintaining their integrity. Right, Going back to that word. 362 00:22:33,350 --> 00:22:36,710 And so that will eventually happen with video. So I think, 363 00:22:37,910 --> 00:22:41,710 you know, for the effort that we're putting out there, to put something out in 364 00:22:41,710 --> 00:22:45,350 the world, maintaining your integrity and maintaining 365 00:22:45,750 --> 00:22:49,270 the professionalism and consistency is critical 366 00:22:49,750 --> 00:22:53,550 because we're going to have these false. A false sense of security as 367 00:22:53,550 --> 00:22:57,190 far as the quality of an output. And you're going to put it out there 368 00:22:57,600 --> 00:23:01,160 and it's not going to resonate. Like you're going to get some negative feedback. And 369 00:23:01,160 --> 00:23:04,800 so I think having like rubrics of evaluation 370 00:23:05,120 --> 00:23:08,720 are critical even for your own personal self or if you're 371 00:23:08,720 --> 00:23:12,400 putting some kind of output for your company, if it's AI generated, 372 00:23:12,720 --> 00:23:16,520 what does that look like? Like, what is that evaluation rubric? What is the QA 373 00:23:16,520 --> 00:23:19,360 around it? Then when you put that out there, 374 00:23:20,160 --> 00:23:23,200 do your consumers understand that it was generated by AI, 375 00:23:24,510 --> 00:23:27,670 Right? What kind of transparency are you going to put out there? You put a 376 00:23:27,670 --> 00:23:31,230 little note saying, hey, these videos were created by AI or not. 377 00:23:32,430 --> 00:23:36,230 Because once an individual understands that it was created by AI, the way that they 378 00:23:36,230 --> 00:23:39,910 consume it is completely different than if they start consuming it and they're like, 379 00:23:39,910 --> 00:23:43,750 wait, this isn't a human. We get that a lot with avatar 380 00:23:43,750 --> 00:23:47,150 technology, right? Not naming any vendors, but 381 00:23:47,390 --> 00:23:51,110 you and I both know that with these avatars, if they're on the screen 382 00:23:51,110 --> 00:23:54,440 for too long, they don't resonate anymore. But 383 00:23:54,920 --> 00:23:58,080 if you bring them on the screen for about six to eight seconds for an 384 00:23:58,080 --> 00:24:01,720 emotional fence post and then you take them off the screen and you go to 385 00:24:01,720 --> 00:24:05,440 B roll, it's very effective. You don't even have time 386 00:24:05,440 --> 00:24:08,720 to process was that a real human or not. You're already on to the next 387 00:24:08,720 --> 00:24:12,440 thing and you know, it leaves your short term memory. So 388 00:24:13,240 --> 00:24:16,680 yeah, I keep going back to integrity. Well, I 389 00:24:16,920 --> 00:24:20,570 love that answer. And it makes me think that, you know, there's, 390 00:24:20,570 --> 00:24:24,410 there's obviously opportunities to really succeed there. And there's opportunities because 391 00:24:24,410 --> 00:24:27,770 people, you, you know, not everyone will have the same level of 392 00:24:27,770 --> 00:24:31,410 integrity that they'll do things that maybe make shortcuts and, 393 00:24:31,490 --> 00:24:34,970 but, and that's okay, right? People are going to figure this out. And humans are 394 00:24:34,970 --> 00:24:37,810 lazy, Matt. We are, we're so 395 00:24:38,610 --> 00:24:42,330 lazy. And I'm there with them at times. You know, and so, 396 00:24:42,330 --> 00:24:46,050 but I am too. But, but I love that, like having those, those check 397 00:24:46,390 --> 00:24:49,350 points in place makes a lot of sense to me, 398 00:24:50,310 --> 00:24:54,070 you know, And I did think with your comment about the music, right, Like I'm 399 00:24:54,070 --> 00:24:57,870 not looking forward to seeing the robots on stage anytime soon. So there's 400 00:24:57,870 --> 00:25:01,430 still opportunities for the humans, we hope. Although Chuck E. 401 00:25:01,430 --> 00:25:05,190 Cheese been doing the robot for a long time. Long 402 00:25:05,190 --> 00:25:08,910 time. Well, I can't wait to see how that evolves with AI. Well, Josh, 403 00:25:08,910 --> 00:25:11,510 I have two more things I want to just talk to you about. 404 00:25:12,890 --> 00:25:16,730 One is I want to get just your reaction to a stat and I don't 405 00:25:16,730 --> 00:25:20,090 have the exact numbers. We're going to release this research coming soon, 406 00:25:20,490 --> 00:25:23,850 but I want to see are you surprised or not surprised? So we did 407 00:25:24,010 --> 00:25:26,170 research, 600 people in the study about 408 00:25:27,850 --> 00:25:31,530 US or English speaking, but multiple countries, US UK. 409 00:25:31,690 --> 00:25:35,210 So not just a US audience. These are professionals, 18 410 00:25:35,210 --> 00:25:39,010 to whatever who were asked to watch a 411 00:25:39,010 --> 00:25:42,650 video. And they were asked and they got. There was four variations of video. 412 00:25:42,650 --> 00:25:46,450 There's one that was a, like 413 00:25:46,450 --> 00:25:50,170 an avatar. Like. No, it's a, like a static image 414 00:25:50,170 --> 00:25:53,930 with a visual, like visual graphic. Right. That moves with the audio. 415 00:25:53,930 --> 00:25:57,530 Right. So as metoxic moves, you got a, a human 416 00:25:57,690 --> 00:26:01,530 picture in picture, an actual human talking. You had an 417 00:26:01,530 --> 00:26:05,130 avatar picture in picture and then you had like a full screen 418 00:26:06,650 --> 00:26:09,810 avatar. Actually I think there was a full screen human in there. They were asked 419 00:26:09,810 --> 00:26:13,530 to watch this video, had these different kind of setups and 420 00:26:13,530 --> 00:26:16,010 then they were watching it. It was a task based, 421 00:26:17,370 --> 00:26:21,170 task based thing like do this thing, learn how to do this 422 00:26:21,170 --> 00:26:24,490 thing in Google. The research that we got back 423 00:26:25,770 --> 00:26:29,530 basically indicated that the Avatars, 424 00:26:29,850 --> 00:26:33,530 the performance that people did. So we'll call it, whether it's comprehension 425 00:26:33,530 --> 00:26:36,970 or capacity to do a task after the fact, 426 00:26:37,210 --> 00:26:39,690 the avatars both, they actually did better. 427 00:26:40,810 --> 00:26:44,650 But then, as you said, like, size of the avatar actually mattered. 428 00:26:44,810 --> 00:26:48,650 So does humans doing better on a task that involved 429 00:26:48,650 --> 00:26:51,050 avatar versus a human surprise you? 430 00:26:52,250 --> 00:26:55,890 Not at all. So again, it 431 00:26:55,890 --> 00:26:59,530 depends upon the composition of the window and cognitive load. 432 00:26:59,850 --> 00:27:03,650 Right. So if you go back to the empirical evidence of a human in the 433 00:27:03,650 --> 00:27:07,450 bottom left or right hand corner, sometimes it's a wash, depending upon 434 00:27:07,450 --> 00:27:11,130 the content that's being shown. As far as B roll or additional information 435 00:27:11,130 --> 00:27:14,409 in the background, I'm not surprised at all. If 436 00:27:15,850 --> 00:27:19,450 there are emotional pools that are happening during the knowledge transfer 437 00:27:19,450 --> 00:27:23,290 that maintains a human's attention on the screen to get 438 00:27:23,290 --> 00:27:26,890 that concept, that is a win. If you have information, 439 00:27:26,890 --> 00:27:30,710 and we both know this, if you have a human or an av, the screen 440 00:27:31,190 --> 00:27:34,950 and it's a distraction, people are going to not pay as much 441 00:27:35,030 --> 00:27:38,710 attention in the moment. Right. They're going to. Their mind's going to 442 00:27:38,710 --> 00:27:41,630 drift or they're going to think about how weird or odd the media is as 443 00:27:41,630 --> 00:27:45,350 opposed to being immersed in the experience. So 444 00:27:45,510 --> 00:27:49,270 what you orchestrated there, if the experience is 445 00:27:49,350 --> 00:27:53,030 immersive and it's not causing cognitive 446 00:27:53,030 --> 00:27:56,150 load, that's the reason why you're probably getting better 447 00:27:57,210 --> 00:28:00,410 scores or retention off the back end. Because it's a superior 448 00:28:01,290 --> 00:28:05,090 experience. Yeah, I like the emotional pull. Right. So 449 00:28:05,090 --> 00:28:08,450 the content was all the same base, basically just changing the delivery 450 00:28:08,450 --> 00:28:12,250 mechanisms. Right. But yeah, if the, like, it's less, could be less 451 00:28:12,250 --> 00:28:15,850 distraction. Like, I move a lot, I twitch, I move forward, you know, like, 452 00:28:15,850 --> 00:28:19,690 so that. That could absolutely play into it. Maybe it's my voice. Maybe 453 00:28:19,690 --> 00:28:23,330 it's the voice. Right. Was there more modulation or not as much 454 00:28:23,330 --> 00:28:27,040 modulation? So I do love that, that resonance. Okay, so that's one thing. 455 00:28:27,040 --> 00:28:30,720 It's just a. More. More data to come. There's some other interesting things. I 456 00:28:30,720 --> 00:28:34,360 can't wait. I'm looking forward to that. But definitely some. Some interesting 457 00:28:34,360 --> 00:28:38,160 things there because I know a lot of people. Avatars are definitely 458 00:28:38,160 --> 00:28:41,400 one of those things. And since you brought them up, very mixed bag. Right, people? 459 00:28:41,640 --> 00:28:45,320 Yeah, yeah, we want them, we want to use them. Or. Gosh, this is 460 00:28:46,200 --> 00:28:50,040 an uncanny valley. A lot of the way. The second thing I wanted to chat 461 00:28:50,040 --> 00:28:53,710 with you about is we recently released our human framework. You 462 00:28:53,710 --> 00:28:57,190 know, we did a podcast episode of it recently. So for those who maybe missed 463 00:28:57,190 --> 00:29:00,990 it, I'll just re. Let me just recap and Josh, refresh your memory as 464 00:29:00,990 --> 00:29:04,830 well, so it's human is just an acronym. So harness your 465 00:29:04,830 --> 00:29:08,470 expertise, understand your audience, make it authentic, not 466 00:29:08,470 --> 00:29:12,310 artificial, aim for better, not just faster, and never skip reviews. 467 00:29:12,310 --> 00:29:15,670 And I'm curious because you've, you've done way more thinking about 468 00:29:15,910 --> 00:29:19,590 applying AI and I'm curious how this resonates with 469 00:29:19,590 --> 00:29:23,380 you as a kind of approach to the work that we do, since we've 470 00:29:23,380 --> 00:29:27,100 been talking a lot about how work is changing. I don't know, everything you 471 00:29:27,100 --> 00:29:29,380 just said sounds like maintain your integrity. 472 00:29:30,900 --> 00:29:34,180 It sounds exactly like that, yes. 473 00:29:34,500 --> 00:29:38,219 All of it. You know, you just basically listed out a 474 00:29:38,219 --> 00:29:41,780 checklist of maintaining your integrity when creating video based 475 00:29:41,780 --> 00:29:45,380 media. And all of those elements are extremely 476 00:29:45,380 --> 00:29:48,100 important. They're all part of that process of 477 00:29:49,290 --> 00:29:52,730 maintaining your expertise, maintaining your integrity, 478 00:29:53,290 --> 00:29:55,610 being able to go ahead and put something out in the world that's going to 479 00:29:55,610 --> 00:29:59,450 resonate, that's truly going to have impact. You need those checklists, 480 00:29:59,690 --> 00:30:02,970 whether it be a mental checklist or something that you have to go through a 481 00:30:02,970 --> 00:30:06,770 few times manually so that you get it down, you have 482 00:30:06,770 --> 00:30:10,170 to go through them. I know that for myself that I go through so many 483 00:30:10,170 --> 00:30:14,010 different mental checklists and even before I put something out in the world, I 484 00:30:14,010 --> 00:30:16,290 may go back to a peer in the industry and say, what do you think 485 00:30:16,290 --> 00:30:20,020 about this through their lens and what do they think about, you 486 00:30:20,020 --> 00:30:23,780 know, about whatever content I'm putting out there. So, yeah, I absolutely 487 00:30:23,780 --> 00:30:27,260 love the human framework that you have there 488 00:30:27,420 --> 00:30:31,100 as far as video creation. So 489 00:30:31,180 --> 00:30:34,740 one of the things I think that I've heard, particularly in 490 00:30:34,740 --> 00:30:38,460 conversations I read a lot of LinkedIn, one of the promises 491 00:30:38,460 --> 00:30:42,100 of AI is faster. And there's nothing in here in our 492 00:30:42,100 --> 00:30:45,940 integrity that says we can't go faster. But I do get a sense 493 00:30:45,940 --> 00:30:49,460 that kind of broadly, when we say something 494 00:30:49,540 --> 00:30:53,260 like aim for better, not just faster people, I get a little bit like. But 495 00:30:53,260 --> 00:30:57,100 that's not the promise of AI. AI is faster. And I guess I just 496 00:30:57,100 --> 00:31:00,740 love your hot take. Is faster the outcome we're going for, 497 00:31:01,060 --> 00:31:04,700 or is it yes and faster and 498 00:31:04,700 --> 00:31:07,940 better? Yes. And so 499 00:31:08,900 --> 00:31:11,620 nobody knew AI was going to show up though it was going to show up 500 00:31:12,290 --> 00:31:16,050 three years ago, right? Nobody did. And 501 00:31:16,050 --> 00:31:19,810 so if you think about how AI is 502 00:31:19,890 --> 00:31:23,650 being implemented in orgs at scale, it shows 503 00:31:23,650 --> 00:31:27,410 up wildly different. And so what is happening in the meantime? 504 00:31:27,410 --> 00:31:31,090 In the meantime, there are goals, there are 505 00:31:31,090 --> 00:31:34,850 problems to be solved, there is deep work being done on initiatives 506 00:31:34,930 --> 00:31:38,370 that never stopped. And so all of those things 507 00:31:39,560 --> 00:31:43,000 need to happen. Why not lean in to make it faster? 508 00:31:44,520 --> 00:31:48,320 Right? I mean, obviously maintain your integrity and There was 509 00:31:48,320 --> 00:31:52,120 so many. You know, here's the thing. I read those posts too. And 510 00:31:52,120 --> 00:31:55,840 so many of my peers, well, maybe 511 00:31:55,840 --> 00:31:59,640 a few, A few peers be like, we shouldn't be focusing in on content 512 00:31:59,640 --> 00:32:03,480 creation. There's bigger stories here, I get it. 513 00:32:04,040 --> 00:32:06,410 But work needs to get done. 514 00:32:07,850 --> 00:32:11,530 That six month training build, if we can knock a month off of it 515 00:32:11,530 --> 00:32:15,250 and we can get back on schedule, my gosh, let's use this AI 516 00:32:15,250 --> 00:32:19,090 tool to streamline this workflow. I am 517 00:32:19,090 --> 00:32:21,690 all for the 518 00:32:22,650 --> 00:32:26,450 reconfiguration of workflows, of being able 519 00:32:26,450 --> 00:32:30,090 to go ahead and create content faster as long as the integrity is 520 00:32:30,090 --> 00:32:33,710 maintained and the intention is still there and you're just not 521 00:32:33,710 --> 00:32:37,270 checking a box and I think that's a qualifier there. That's really important 522 00:32:37,830 --> 00:32:40,390 because yes, you do have the 523 00:32:41,430 --> 00:32:45,070 abuse of the capability and that's 524 00:32:45,070 --> 00:32:48,710 happened forever. Where people just go and copy and paste and call it done. Or 525 00:32:49,110 --> 00:32:52,230 and you hear stories in the marketplace of lawyers losing their 526 00:32:52,550 --> 00:32:55,990 license because they're referencing case law that doesn't exist. Or 527 00:32:56,990 --> 00:32:59,310 you know, companies that get out in front of their skis and they do, 528 00:33:00,830 --> 00:33:04,630 you know, a drive through AI and next thing you know, it's ordering 20,000 529 00:33:04,630 --> 00:33:08,430 Chicken McNuggets. And you know, I mean, we, we, we try 530 00:33:08,430 --> 00:33:12,150 to improve what's going 531 00:33:12,150 --> 00:33:15,550 on out there, but as I mentioned before, humans are just lazy and they will 532 00:33:15,550 --> 00:33:19,070 go ahead and take advantage of the technology and think 533 00:33:19,070 --> 00:33:22,830 they're implementing a solve when actually they're creating friction. 534 00:33:23,610 --> 00:33:27,410 And I think that's what's happening is the content creation part 535 00:33:27,410 --> 00:33:31,250 gets a bad rap because one, it's been implemented 536 00:33:31,250 --> 00:33:34,970 probably improperly for a long period of time 537 00:33:34,970 --> 00:33:37,690 as far as an educational experience solve. 538 00:33:38,890 --> 00:33:41,690 And so the thought was, oh, we're going to go ahead and create a whole 539 00:33:41,690 --> 00:33:45,370 bunch of crap at scale. Right. But I think 540 00:33:45,370 --> 00:33:48,970 that we have to go through these pain points. 541 00:33:49,050 --> 00:33:52,190 Like we need to go through these 542 00:33:53,070 --> 00:33:56,750 moments to where there's a realization of more 543 00:33:56,750 --> 00:33:59,910 is not better, of that we have to have rigor, that we have to go 544 00:33:59,910 --> 00:34:03,630 ahead and have like a human framework to vet all this stuff 545 00:34:03,630 --> 00:34:07,230 out so that yes, we can go ahead and do these solves for the business. 546 00:34:07,550 --> 00:34:11,230 We're maintaining our integrity, we're putting great learning 547 00:34:11,230 --> 00:34:14,910 experiences out there for our associates and it's a win for everybody. 548 00:34:15,070 --> 00:34:18,660 But along the way, we are going to run through these periods where 549 00:34:19,060 --> 00:34:22,820 AI is going to get a bed rap for creating AI slop and creating 550 00:34:22,980 --> 00:34:26,740 poorly executed content. Yeah. Well, Josh, 551 00:34:26,740 --> 00:34:30,500 this has been a fantastic conversation. I'm looking forward to digging 552 00:34:30,500 --> 00:34:34,220 in more into the book and learning more. If 553 00:34:34,220 --> 00:34:37,660 people want to find the book, they want to learn more about you, connect with 554 00:34:37,660 --> 00:34:41,420 you. Where should they turn? Yeah, they can go right. Oh, right 555 00:34:41,420 --> 00:34:44,979 here over on Amazon. So yeah, Amazon 556 00:34:45,139 --> 00:34:47,699 is a great way to find the book. You can also get on ATD Press, 557 00:34:48,339 --> 00:34:52,179 JoshCavalier.com and soon to be JoshCavalier AI. I have to 558 00:34:52,179 --> 00:34:55,659 go and change those DNS settings here shortly to flip the book 559 00:34:55,659 --> 00:34:58,899 webpage up. The companion website can't wait. 560 00:34:59,058 --> 00:35:02,339 That's going to be amazing. The book website, so many 561 00:35:03,059 --> 00:35:06,699 additional pieces of content to support your journey 562 00:35:06,699 --> 00:35:10,190 as you read the book. Fantastic. 563 00:35:11,310 --> 00:35:14,870 I have you labeled as JoshCavalier AI. So maybe I'll just keep it in 564 00:35:14,870 --> 00:35:17,670 hopes that put some pressure on you, Josh. Push the pressure on you. Right, right, 565 00:35:17,670 --> 00:35:21,430 right. That's what we do over Thanksgiving holiday. That's right. Well, as 566 00:35:21,430 --> 00:35:24,270 we wrap up, we'd like to end the way we always do, Josh, which is 567 00:35:24,270 --> 00:35:28,070 with our final take as quick, fast summary. So, Josh, what is 568 00:35:28,070 --> 00:35:31,870 your final take for today's episode? Maintain your integrity. 569 00:35:31,950 --> 00:35:35,310 I mean, have fun. Get out there and 570 00:35:35,880 --> 00:35:39,520 find what your personal AI training plan 571 00:35:39,520 --> 00:35:43,120 is in 2026. Try different 572 00:35:43,120 --> 00:35:46,720 tools, get out there, push boundaries. But along the 573 00:35:46,720 --> 00:35:50,040 way, maintain your professionalism, maintain your integrity 574 00:35:50,360 --> 00:35:54,160 and just show up better for yourself and for your business 575 00:35:54,160 --> 00:35:57,760 or whoever you support. Fantastic. Well, 576 00:35:57,760 --> 00:36:01,180 Josh, always, always glad to have you here in the visual lens and thank you 577 00:36:01,330 --> 00:36:04,570 you again for, for sharing your book with us where hopefully a lot of people 578 00:36:04,570 --> 00:36:08,090 will take up the opportunity to read that and gain more wisdom and insight from 579 00:36:08,090 --> 00:36:11,850 you. Thanks, Matt. Appreciate it. All right, everybody, you hear 580 00:36:11,850 --> 00:36:15,610 it like, we've got, we've got lots of interesting challenges ahead. We gotta 581 00:36:15,610 --> 00:36:19,130 make sure we're focused on our integrity. We gotta make sure we're understanding the 582 00:36:19,130 --> 00:36:22,690 systems, playing with them, learning what's going to work for us, creating new, 583 00:36:22,770 --> 00:36:25,490 we're creating new work, new opportunities and that is.