1 00:00:00,160 --> 00:00:03,199 Speaker 1: Most up, everybody will Lukea is here for my first 2 00:00:03,400 --> 00:00:06,680 Speaker 1: solo episode of twenty twenty six, and so it's going 3 00:00:06,760 --> 00:00:09,080 Speaker 1: to be a fun one. I'm gonna make I think 4 00:00:09,119 --> 00:00:11,920 Speaker 1: ten predictions today. Are going to make ten predictions about 5 00:00:11,920 --> 00:00:16,840 Speaker 1: what we're going to see with regards to AI this year. 6 00:00:16,880 --> 00:00:20,200 Speaker 1: And these are my predictions. Some of it gleaned from 7 00:00:20,360 --> 00:00:23,160 Speaker 1: things I've been seeing other people talk about, some of 8 00:00:23,200 --> 00:00:26,880 Speaker 1: it my own experiences with AI. But these are ten 9 00:00:26,960 --> 00:00:30,760 Speaker 1: predictions of things I believe we are going to see 10 00:00:30,840 --> 00:00:34,360 Speaker 1: this year twenty twenty six when it comes to AI 11 00:00:34,600 --> 00:00:37,400 Speaker 1: and this development and it becoming more and more part. 12 00:00:37,200 --> 00:00:38,000 Speaker 2: Of our lifestyle. 13 00:00:38,080 --> 00:00:40,559 Speaker 1: So before we begin, I want to set to the 14 00:00:40,640 --> 00:00:45,720 Speaker 1: table here. These are non predictions about new features or 15 00:00:45,880 --> 00:00:49,800 Speaker 1: what buttons chat GPT is going to add next. I'm 16 00:00:49,800 --> 00:00:53,920 Speaker 1: talking about power, I'm talking about work, I'm talking about culture, 17 00:00:54,800 --> 00:01:00,240 Speaker 1: about who actually wins when AI just becomes normal. Look, 18 00:01:00,280 --> 00:01:03,279 Speaker 1: some of this might make you uncomfortable, not because I'm 19 00:01:03,320 --> 00:01:06,880 Speaker 1: trying to be dramatic, but because there's a lot happening 20 00:01:06,920 --> 00:01:10,000 Speaker 1: already and we're just not talking about it yet. And 21 00:01:10,080 --> 00:01:13,319 Speaker 1: so my first prediction for this year is that AI 22 00:01:13,520 --> 00:01:17,280 Speaker 1: just becomes this invisible air, this invisible infrastructure. 23 00:01:17,720 --> 00:01:18,400 Speaker 2: So here's the thing. 24 00:01:18,520 --> 00:01:22,759 Speaker 1: By the end of the year, AI stops being something. 25 00:01:22,400 --> 00:01:23,960 Speaker 2: That you use necessarily. 26 00:01:24,360 --> 00:01:28,440 Speaker 1: It just becomes what everything runs on. And that's really 27 00:01:28,600 --> 00:01:34,480 Speaker 1: powerful because right now we still treat AI like a destination, 28 00:01:34,959 --> 00:01:37,760 Speaker 1: like I'm gonna go to chat GPT, I'm gonna go 29 00:01:37,800 --> 00:01:40,880 Speaker 1: to Gemini, like it's a tool you open, an app, 30 00:01:41,160 --> 00:01:45,160 Speaker 1: a thing you go to. But that's not where our 31 00:01:45,280 --> 00:01:48,640 Speaker 1: use of AI is headed. It's gonna be baked more 32 00:01:48,720 --> 00:01:54,360 Speaker 1: and more into everything. So Salesforce adds AI to your CRM, 33 00:01:54,440 --> 00:01:59,320 Speaker 1: your customer relationship manager. Google Sheets put AI in this formula. 34 00:01:59,360 --> 00:02:03,240 Speaker 1: Development Canva puts AI in your design workflow. Quick Books 35 00:02:03,640 --> 00:02:07,640 Speaker 1: automates the bookkeeping with AI, and that internal dashboard your 36 00:02:07,640 --> 00:02:11,400 Speaker 1: team uses, you know, that's using more AI two and 37 00:02:11,440 --> 00:02:14,920 Speaker 1: it is what's wild about this, The most you know 38 00:02:15,000 --> 00:02:19,560 Speaker 1: impactful AI won't even feel impressive. It'll feel more and 39 00:02:19,600 --> 00:02:23,720 Speaker 1: more boring and being like like electricity or the internet 40 00:02:23,760 --> 00:02:27,120 Speaker 1: even you know it's one when we stop noticing it, 41 00:02:27,960 --> 00:02:31,119 Speaker 1: which means all that AI first branding is gonna lose 42 00:02:31,200 --> 00:02:35,000 Speaker 1: value like super duper fast, like nobody says cloud first anymore, right, 43 00:02:35,120 --> 00:02:37,960 Speaker 1: or even mobile first, like nobody says mobile first anymore. 44 00:02:38,400 --> 00:02:42,040 Speaker 1: So here's what that means. If you're building an AI startup, 45 00:02:42,080 --> 00:02:44,560 Speaker 1: and then in AI standalone. 46 00:02:43,919 --> 00:02:45,920 Speaker 2: Start up, particularly like a tool. 47 00:02:45,760 --> 00:02:48,000 Speaker 1: Like it, just like an AI app that does just 48 00:02:48,000 --> 00:02:51,000 Speaker 1: one thing, you're gonna be in trouble because companies have 49 00:02:51,120 --> 00:02:52,000 Speaker 1: already won. 50 00:02:52,040 --> 00:02:54,920 Speaker 2: The software people use every day. This is gonna add 51 00:02:54,919 --> 00:02:58,840 Speaker 2: an AI layer to what they already have. So think 52 00:02:58,880 --> 00:02:59,240 Speaker 2: about it. 53 00:02:59,320 --> 00:03:02,280 Speaker 1: You're why you use Salesforce in your business, and you 54 00:03:02,320 --> 00:03:05,840 Speaker 1: manage all your customer relationships with Salesforce. Now, imagine some 55 00:03:05,960 --> 00:03:09,840 Speaker 1: startup bills an AI tool that analyzes your sales pipeline 56 00:03:09,840 --> 00:03:11,240 Speaker 1: and predicts which deals will close. 57 00:03:11,360 --> 00:03:12,520 Speaker 2: And that sounds useful. 58 00:03:12,919 --> 00:03:16,440 Speaker 1: I would give you that, But then Salesforce just builds 59 00:03:16,440 --> 00:03:20,200 Speaker 1: the same feature directly into the platform, the platform that 60 00:03:20,360 --> 00:03:23,079 Speaker 1: these people are paying for the use already. Now, why 61 00:03:23,080 --> 00:03:25,640 Speaker 1: would you go and pay for a separate AI tool. 62 00:03:25,639 --> 00:03:28,040 Speaker 1: Why would your customer, your potential customer, go pay for 63 00:03:28,080 --> 00:03:32,120 Speaker 1: a separate AI tool. They're already in Salesforce all day long, 64 00:03:32,880 --> 00:03:36,360 Speaker 1: They're already logged in, their data is already there. They'd 65 00:03:36,400 --> 00:03:38,640 Speaker 1: have to export their data then put it into this 66 00:03:38,760 --> 00:03:41,320 Speaker 1: other tool, your tool, then bring the insights back to 67 00:03:41,400 --> 00:03:45,320 Speaker 1: their salesforce, and that's friction that nobody needs. The winners 68 00:03:45,600 --> 00:03:49,480 Speaker 1: will be the companies with the coolest AI features. The 69 00:03:49,520 --> 00:03:52,360 Speaker 1: winners won't be the companies with the coolest AI features, 70 00:03:52,400 --> 00:03:55,680 Speaker 1: They'll be the companies the people are already using for 71 00:03:55,760 --> 00:03:59,840 Speaker 1: something else that have figured out ways to creatively in 72 00:04:00,080 --> 00:04:02,680 Speaker 1: to toot AI into the development pipeline. 73 00:04:03,440 --> 00:04:05,760 Speaker 2: So here's the shift. Users will stop. 74 00:04:05,560 --> 00:04:10,200 Speaker 1: Paying premiums just because something says AI in it. They'll 75 00:04:10,240 --> 00:04:12,960 Speaker 1: start asking, what does this actually do for me? What 76 00:04:13,120 --> 00:04:15,800 Speaker 1: outcome am I gonna get? We're gonna get more outcomes driven. 77 00:04:16,200 --> 00:04:19,039 Speaker 1: So by twenty twenty six, you won't feel AI anymore 78 00:04:19,040 --> 00:04:19,880 Speaker 1: as revolutionary. 79 00:04:19,920 --> 00:04:24,159 Speaker 2: It would just be required. Number two. 80 00:04:24,200 --> 00:04:27,400 Speaker 1: My number two prediction for twenty twenty six is AI 81 00:04:27,520 --> 00:04:32,000 Speaker 1: becomes aspirational. And this one is personal for me and 82 00:04:32,040 --> 00:04:35,800 Speaker 1: so I run a marketing and production agency, and you 83 00:04:35,839 --> 00:04:41,480 Speaker 1: know what my videographers get most excited about is shooting analog. 84 00:04:42,680 --> 00:04:45,760 Speaker 1: They don't get excited much anymore about new tech. They 85 00:04:45,760 --> 00:04:49,479 Speaker 1: get excited about shooting like we used to shoot twenty 86 00:04:49,600 --> 00:04:52,720 Speaker 1: thirty forty years ago. So even when they're not using 87 00:04:52,839 --> 00:04:57,400 Speaker 1: social So even when they're not using like actual Kodak film. 88 00:04:57,800 --> 00:05:01,760 Speaker 1: They're using cameras designed the field analog, like those camp 89 00:05:01,800 --> 00:05:05,520 Speaker 1: snap cameras, like limited controls, like no screens, even they 90 00:05:05,520 --> 00:05:07,520 Speaker 1: can't even see the shot that they just took, no 91 00:05:07,560 --> 00:05:11,640 Speaker 1: instant feedback at all, and that limitation, Like. 92 00:05:12,040 --> 00:05:15,560 Speaker 2: That's the whole point. And so people. 93 00:05:15,279 --> 00:05:21,640 Speaker 1: Aren't rejecting technology, they're rejecting like the constant optimization. I 94 00:05:21,640 --> 00:05:28,120 Speaker 1: feel like notifications like the abstraction, like algorithms deciding everything 95 00:05:28,240 --> 00:05:33,120 Speaker 1: for them. So physical media gives you friction, it gives 96 00:05:33,160 --> 00:05:38,400 Speaker 1: you like presence, intentionality, And so that's why vinyl isn't 97 00:05:38,520 --> 00:05:43,760 Speaker 1: just like nostalgia, like it's resistance to infinite choice. We're 98 00:05:43,760 --> 00:05:47,360 Speaker 1: seeing it everywhere, like vinyl is growing year over year, 99 00:05:47,440 --> 00:05:51,320 Speaker 1: like Taylor Swift, The Weekend, Billie Eilish, like they're all 100 00:05:51,360 --> 00:05:55,960 Speaker 1: releasing vinyl and cassette versions on purpose. Like people are 101 00:05:56,000 --> 00:05:59,880 Speaker 1: buying dumb phones legit and those light phones that barely 102 00:06:00,120 --> 00:06:03,960 Speaker 1: do anything for small businesses, it's. 103 00:06:03,800 --> 00:06:04,520 Speaker 2: Going to be huge. 104 00:06:05,279 --> 00:06:11,440 Speaker 1: So physical products become more premium. So think like a 105 00:06:11,520 --> 00:06:14,240 Speaker 1: mole skin notebook, not a Google doc. 106 00:06:14,440 --> 00:06:15,920 Speaker 2: So physical books. 107 00:06:15,560 --> 00:06:21,520 Speaker 1: From independent bookstores, not a kindle like Fujifilm cameras not 108 00:06:21,680 --> 00:06:27,360 Speaker 1: iPhone filters and experiences in person wins a cocktail class 109 00:06:27,400 --> 00:06:31,479 Speaker 1: at a local bar, a ceramics workshop, a book club 110 00:06:31,520 --> 00:06:36,839 Speaker 1: that actually meets in human form. Businesses that sell presence 111 00:06:37,200 --> 00:06:41,200 Speaker 1: start out performing businesses that only sell convenience. In local 112 00:06:41,400 --> 00:06:47,440 Speaker 1: physical experiential businesses, they will regain relevance in many ways, 113 00:06:47,560 --> 00:06:51,200 Speaker 1: especially if they're super creative, like that independent bookstore that 114 00:06:51,240 --> 00:06:55,160 Speaker 1: does author readings, that coffee shop with the vinyl collection, 115 00:06:55,640 --> 00:06:58,120 Speaker 1: or the record shop where the owner actually knows what 116 00:06:58,120 --> 00:07:01,400 Speaker 1: they're talking about, they know the music. In physical studios, 117 00:07:01,440 --> 00:07:06,240 Speaker 1: photography studios like CrossFit gems with real community like salons 118 00:07:06,279 --> 00:07:10,960 Speaker 1: where you have the same stylists every time. Psychologically it 119 00:07:11,000 --> 00:07:14,880 Speaker 1: makes perfect sense, like AI speed stings up. It speeds 120 00:07:14,960 --> 00:07:18,400 Speaker 1: up everything, and analog slows it down. And I believe 121 00:07:18,720 --> 00:07:22,280 Speaker 1: people are starting to pay for slowness the same way 122 00:07:22,320 --> 00:07:26,080 Speaker 1: they once paid for speed. And it is the economic angle. 123 00:07:26,600 --> 00:07:31,080 Speaker 1: Analog is harder to automate, like it's harder to scale 124 00:07:31,280 --> 00:07:31,600 Speaker 1: and so. 125 00:07:32,160 --> 00:07:32,840 Speaker 2: Harder to fake. 126 00:07:33,360 --> 00:07:37,480 Speaker 1: That scarcity creates margin for you. So in a world 127 00:07:37,640 --> 00:07:43,600 Speaker 1: optimized by AI, limitation becomes luxury. So for me as 128 00:07:43,640 --> 00:07:46,400 Speaker 1: a creative, like this next one number three matters a 129 00:07:46,480 --> 00:07:50,360 Speaker 1: ton because my prediction with number three in twenty twenty 130 00:07:50,400 --> 00:07:53,520 Speaker 1: six is taste will matter even more, Like if you 131 00:07:53,560 --> 00:07:56,280 Speaker 1: have really good taste and you know how to communicate 132 00:07:56,320 --> 00:07:58,800 Speaker 1: that taste, it will matter even more this year. 133 00:07:58,800 --> 00:08:00,800 Speaker 2: It'll be more valuable, is ye. And it's been in 134 00:08:00,920 --> 00:08:01,640 Speaker 2: a long time. 135 00:08:02,040 --> 00:08:05,400 Speaker 1: And so AI floods the world with competence, which makes 136 00:08:05,680 --> 00:08:11,800 Speaker 1: originality and cultural specificity scarce, like it's it's it's harder 137 00:08:11,840 --> 00:08:16,080 Speaker 1: to find. So you see AI generated content, Yeah it 138 00:08:16,120 --> 00:08:21,920 Speaker 1: can be good, but technically it's like hollow. So if 139 00:08:21,960 --> 00:08:24,560 Speaker 1: you look like AI generated content, yeah it can be 140 00:08:24,600 --> 00:08:29,840 Speaker 1: good technically, but it's hollow, like the soul is gone. 141 00:08:30,120 --> 00:08:36,440 Speaker 1: So like lived experience doesn't scale cleanly, like culture can't 142 00:08:36,480 --> 00:08:42,800 Speaker 1: be averaged without getting flattened. Culture can't be averaged without 143 00:08:42,840 --> 00:08:48,559 Speaker 1: getting also flattened. So taste becomes a form of signal filtering, 144 00:08:48,679 --> 00:08:52,679 Speaker 1: like not decoration, but filtering. So this is where black 145 00:08:52,720 --> 00:08:59,120 Speaker 1: creators specifically gain leverage. If we resist imitation, human curation 146 00:08:59,440 --> 00:09:04,679 Speaker 1: becomes a premium service. Audiences start rewarding resonance over volume, 147 00:09:04,880 --> 00:09:06,880 Speaker 1: like what does it like? What does it mean when 148 00:09:06,880 --> 00:09:08,880 Speaker 1: I feel it? When I see it? Do I feel anything? 149 00:09:09,320 --> 00:09:13,320 Speaker 1: When everything looks good. Like when everything sounds polished. 150 00:09:13,400 --> 00:09:14,280 Speaker 2: What cuts through. 151 00:09:15,320 --> 00:09:19,320 Speaker 1: What cuts through is truth and honesty. When everything sounds good, 152 00:09:19,520 --> 00:09:21,319 Speaker 1: realness becomes priceless. 153 00:09:21,760 --> 00:09:22,640 Speaker 2: So that's number three. 154 00:09:23,920 --> 00:09:28,319 Speaker 1: Number four, employment shifts to outcome contracts. This is something 155 00:09:28,480 --> 00:09:30,360 Speaker 1: I don't think it's gonna be finished in twenty twenty six, 156 00:09:30,400 --> 00:09:33,280 Speaker 1: but we'll see more of it. So workstops becoming about 157 00:09:33,320 --> 00:09:37,040 Speaker 1: time and titles and more about like deliverables. Like AI 158 00:09:37,160 --> 00:09:40,480 Speaker 1: handles a ton of things in the process, but humans get. 159 00:09:40,400 --> 00:09:41,360 Speaker 2: Judged on results. 160 00:09:42,520 --> 00:09:47,680 Speaker 1: Job descriptions will matter even less, so measurable output will 161 00:09:47,720 --> 00:09:51,640 Speaker 1: matter even more. Like so employment becomes more transactional and 162 00:09:51,720 --> 00:09:55,199 Speaker 1: less you know, like paternalistic, Like you're not like necessarily 163 00:09:55,240 --> 00:09:58,520 Speaker 1: on my team necessarily like in my building or in 164 00:09:58,520 --> 00:10:02,440 Speaker 1: my office, but like we will have a relationship, but 165 00:10:02,679 --> 00:10:04,880 Speaker 1: like you may be a contractor, you may be a 166 00:10:04,920 --> 00:10:07,280 Speaker 1: ten ninety nine instead of a W two. When the 167 00:10:07,360 --> 00:10:10,640 Speaker 1: upside of that goes to entrepreneurs, the downside of that 168 00:10:10,760 --> 00:10:14,679 Speaker 1: hits workers with you know, who have a little bit 169 00:10:14,679 --> 00:10:17,040 Speaker 1: more of a vague value proposition, and I think they 170 00:10:17,040 --> 00:10:19,520 Speaker 1: don't have value. It's just harder to quantify for a 171 00:10:19,559 --> 00:10:22,520 Speaker 1: lot of people. So if you can't clearly define what 172 00:10:22,600 --> 00:10:26,080 Speaker 1: you produce, you will lose leverage. In twenty twenty six, 173 00:10:26,960 --> 00:10:30,640 Speaker 1: the negotiation power will shift to people who can define 174 00:10:30,679 --> 00:10:34,240 Speaker 1: an outcome. So like the just rote worker who just 175 00:10:34,360 --> 00:10:37,600 Speaker 1: does a job, goes home, collects a check will have 176 00:10:37,679 --> 00:10:38,960 Speaker 1: a harder time. 177 00:10:38,920 --> 00:10:40,160 Speaker 2: As we get future. 178 00:10:40,320 --> 00:10:43,480 Speaker 1: As we walk into the future in twenty twenty six, 179 00:10:43,520 --> 00:10:46,679 Speaker 1: your job description will matter less, a whole lot less 180 00:10:46,840 --> 00:10:51,040 Speaker 1: than what you deliver. So niche will become the new 181 00:10:51,080 --> 00:10:54,920 Speaker 1: competitive advantage. This is number five. So boutiques are coming back. 182 00:10:54,960 --> 00:10:57,240 Speaker 1: I believe boutiques are coming back. And I mean that 183 00:10:57,400 --> 00:11:04,320 Speaker 1: literally and like metaphorically. You've had this long, fast speeding 184 00:11:04,400 --> 00:11:08,360 Speaker 1: car raised towards big, big box retail like you know, 185 00:11:08,720 --> 00:11:14,240 Speaker 1: online everything, Amazon, Walmart, like Sheen. Everything was optimized for 186 00:11:14,320 --> 00:11:18,080 Speaker 1: scale and low prices. But what's happening and you can, 187 00:11:18,280 --> 00:11:19,920 Speaker 1: if you pay attention, you can start to see it 188 00:11:20,000 --> 00:11:23,960 Speaker 1: like we're starting to crave the opposite. Just as human beings, 189 00:11:24,000 --> 00:11:28,640 Speaker 1: small businesses arising against again. Creative ones, particularly small businesses, 190 00:11:29,120 --> 00:11:33,840 Speaker 1: will will pop up more independent bookstores, local coffee roasters, 191 00:11:33,880 --> 00:11:38,600 Speaker 1: boutique clothing shops, specialty food stores. And the key is 192 00:11:39,400 --> 00:11:42,560 Speaker 1: they're using the technology to not replace them, but to 193 00:11:42,760 --> 00:11:47,079 Speaker 1: run smarter, not necessarily always get bigger. Bigger is a 194 00:11:47,160 --> 00:11:50,240 Speaker 1: thing that we chased with like building technology startups. But 195 00:11:50,320 --> 00:11:52,840 Speaker 1: the mom and pop who owns a bookstore or a restaurant, 196 00:11:53,040 --> 00:11:55,760 Speaker 1: it doesn't necessarily, you know, try to be you know, 197 00:11:55,840 --> 00:11:58,600 Speaker 1: a thousand restaurants across the country. They just wanted to 198 00:11:58,679 --> 00:12:03,600 Speaker 1: run their things. Small bookstore can now manage the inventory 199 00:12:03,640 --> 00:12:07,079 Speaker 1: now with AI, and that small restaurant can manage their 200 00:12:07,160 --> 00:12:11,600 Speaker 1: flow and their labor costs. With AI, they can analyze 201 00:12:11,720 --> 00:12:15,160 Speaker 1: what their specific community wants. Also, using the AI tools 202 00:12:15,200 --> 00:12:17,920 Speaker 1: that are out now, they can target Instagram as to 203 00:12:18,440 --> 00:12:21,319 Speaker 1: know book lovers within five miles of their bookstore. They 204 00:12:21,320 --> 00:12:26,120 Speaker 1: can sound personalized, They can send personalized recommendations based on 205 00:12:26,240 --> 00:12:29,079 Speaker 1: what you bought the last time because of these tools 206 00:12:29,080 --> 00:12:32,240 Speaker 1: that are being developed with artificial intelligence, so they get 207 00:12:32,280 --> 00:12:36,280 Speaker 1: efficiency out of technology without losing what makes them special, 208 00:12:36,360 --> 00:12:38,680 Speaker 1: and that's the human touch. So people are starting to 209 00:12:39,120 --> 00:12:43,120 Speaker 1: long for knowing who they're buying from and actually talk 210 00:12:43,160 --> 00:12:47,959 Speaker 1: to someone, being recognized when they walk in, somebody saying. 211 00:12:47,679 --> 00:12:50,439 Speaker 2: Hello, oh hey, you back, like how'd you like that. 212 00:12:50,440 --> 00:12:53,800 Speaker 1: Book that I recommended? Like there's the time that we 213 00:12:54,480 --> 00:12:57,400 Speaker 1: long for a time also that many of us weren't 214 00:12:57,400 --> 00:12:58,480 Speaker 1: even alive for but. 215 00:12:58,400 --> 00:12:59,920 Speaker 2: You see it in old shows. 216 00:13:00,600 --> 00:13:03,160 Speaker 1: But those things we got past them because they were 217 00:13:03,160 --> 00:13:05,760 Speaker 1: not scalable, and we went on this sprint towards scale. 218 00:13:06,280 --> 00:13:11,600 Speaker 1: And that's not efficient, you know, to say, and it's 219 00:13:11,640 --> 00:13:15,040 Speaker 1: not efficient to know everybody by name necessarily, it's not 220 00:13:15,040 --> 00:13:18,600 Speaker 1: efficient to know what everybody wants, you know, just because 221 00:13:18,640 --> 00:13:20,920 Speaker 1: you have a conversation with them. It's not efficient to 222 00:13:20,960 --> 00:13:23,520 Speaker 1: do that. It doesn't scale that way. But that's exactly 223 00:13:23,559 --> 00:13:27,280 Speaker 1: why it works. So businesses get more personal in twenty 224 00:13:27,320 --> 00:13:30,240 Speaker 1: twenty six, and technology makes it possible for small businesses 225 00:13:30,240 --> 00:13:33,720 Speaker 1: to deliver on that personal experience without drowning them in 226 00:13:34,080 --> 00:13:38,000 Speaker 1: administrative work, which it does today. And so now the 227 00:13:38,000 --> 00:13:42,200 Speaker 1: culture is shift. That matters is lifestyle businesses won't just 228 00:13:42,280 --> 00:13:45,520 Speaker 1: be dismissed anymore. And look, I speak for myself, like 229 00:13:46,240 --> 00:13:51,800 Speaker 1: we I I'll say, I used to disregard these businesses. 230 00:13:51,920 --> 00:13:55,160 Speaker 1: The boutique that there's six hundred thousand dollars a year 231 00:13:55,280 --> 00:13:58,000 Speaker 1: and the owner clears half of that, like we acted 232 00:13:58,000 --> 00:14:01,120 Speaker 1: that that wasn't a real thing, that wasn't real success. 233 00:14:01,880 --> 00:14:04,280 Speaker 1: And the five million doll a local agency that provides 234 00:14:04,360 --> 00:14:08,160 Speaker 1: jobs and shapes community, you know, shapes community culture, even 235 00:14:08,240 --> 00:14:11,760 Speaker 1: like we look past it because they weren't billion dollar businesses. 236 00:14:11,800 --> 00:14:16,920 Speaker 1: You know, we glorified unicorns, billion dollar companies, venture capital, 237 00:14:17,120 --> 00:14:18,280 Speaker 1: you know, hyper growth. 238 00:14:19,040 --> 00:14:19,960 Speaker 2: And if you. 239 00:14:19,920 --> 00:14:23,360 Speaker 1: Weren't that, then you weren't doing nothing. And listen, unicorns 240 00:14:23,400 --> 00:14:28,480 Speaker 1: are fine. I celebrate you. But one, not everybody is 241 00:14:28,520 --> 00:14:32,200 Speaker 1: pursuing that, and because it requires so much of you, 242 00:14:32,200 --> 00:14:35,080 Speaker 1: your time, your relationships, your sanity in many cases. And two, 243 00:14:35,440 --> 00:14:37,240 Speaker 1: it's not the only way to do business. And just 244 00:14:37,280 --> 00:14:40,160 Speaker 1: because you're not building, that does not mean that you're 245 00:14:40,200 --> 00:14:45,800 Speaker 1: not successful. A boutique clearing three hundred thousand dollars in profit, 246 00:14:46,120 --> 00:14:50,960 Speaker 1: that's a great life, and that's an opportunity to build wealth. 247 00:14:51,720 --> 00:14:55,280 Speaker 1: You know, for many people, that's freedom. And so a 248 00:14:55,320 --> 00:15:00,000 Speaker 1: local agency with twenty employees doing solid work for clients, 249 00:15:00,200 --> 00:15:06,240 Speaker 1: they actually know, that's impact. It's community. And so I 250 00:15:06,280 --> 00:15:11,000 Speaker 1: take responsibility for my own indiscretions in this regard, but 251 00:15:11,080 --> 00:15:13,680 Speaker 1: I challenge you to do the same. So we're starting 252 00:15:13,720 --> 00:15:16,160 Speaker 1: to respect the people who are building small again, the 253 00:15:16,200 --> 00:15:18,960 Speaker 1: people who are building and they want to service their neighbors, 254 00:15:19,720 --> 00:15:24,600 Speaker 1: we'll respect that again. So when everything is available everywhere instantly. 255 00:15:25,400 --> 00:15:28,960 Speaker 1: Scarcity isn't about access anymore. It's about connection, and I 256 00:15:29,000 --> 00:15:31,440 Speaker 1: believe that that is what a lot of human beings 257 00:15:31,600 --> 00:15:35,040 Speaker 1: are craving today. So you can buy a candle from 258 00:15:35,080 --> 00:15:38,720 Speaker 1: Amazon and two clicks, or you can buy one from 259 00:15:38,760 --> 00:15:41,560 Speaker 1: a small shop downtown where the owner tells you the 260 00:15:41,600 --> 00:15:44,760 Speaker 1: story behind each scent and you actually remember the conversation. 261 00:15:45,960 --> 00:15:48,840 Speaker 1: These are important things that got lost in our social 262 00:15:48,840 --> 00:15:50,880 Speaker 1: discourse and our social norms. 263 00:15:50,600 --> 00:15:52,600 Speaker 2: Over the last decade or two. 264 00:15:53,200 --> 00:15:55,600 Speaker 1: So which one feels more valuable buying that one and 265 00:15:55,640 --> 00:15:58,240 Speaker 1: two clicks on Amazon or talking to somebody and really 266 00:15:58,240 --> 00:16:02,560 Speaker 1: getting a feel for the spirit behind it. So you know, 267 00:16:02,640 --> 00:16:08,320 Speaker 1: AI like commoditizes the generic, which means the specific, the local, 268 00:16:08,400 --> 00:16:13,560 Speaker 1: the personal. That becomes premium. So big boxes, you know, 269 00:16:13,720 --> 00:16:15,960 Speaker 1: the big box of the world, pick On like the 270 00:16:15,960 --> 00:16:18,760 Speaker 1: best Buy is the Walmarks, like they optimize for everything. 271 00:16:19,440 --> 00:16:25,240 Speaker 1: Boutique stores optimize for someone. And in twenty twenty six, 272 00:16:25,280 --> 00:16:28,640 Speaker 1: I believe more people want and are already going towards 273 00:16:29,480 --> 00:16:32,320 Speaker 1: wanting to be someone to the people that they do 274 00:16:32,360 --> 00:16:34,640 Speaker 1: business with. They don't want to be everybody to you, 275 00:16:34,680 --> 00:16:39,040 Speaker 1: They want to be an individual. So that's so that's 276 00:16:39,040 --> 00:16:42,600 Speaker 1: another one for twenty twenty six. Number six. The real 277 00:16:42,720 --> 00:16:47,880 Speaker 1: risk is delegated thinking. This one's super important because the 278 00:16:48,120 --> 00:16:53,920 Speaker 1: danger isn't anymore an incorrect answer, it's surrendered judgment. AI 279 00:16:54,080 --> 00:16:58,480 Speaker 1: gets reliable enough that people stop questioning it, so confidence 280 00:16:58,720 --> 00:17:03,680 Speaker 1: gets mistaken for correctness, so thinking becomes outsourced by default. 281 00:17:04,760 --> 00:17:05,800 Speaker 2: So this is old. 282 00:17:05,600 --> 00:17:09,800 Speaker 1: Saying in business, like no one ever got fired for 283 00:17:10,560 --> 00:17:15,080 Speaker 1: buying IBM, and that phrase, you know, after doing some research, 284 00:17:15,080 --> 00:17:17,160 Speaker 1: it goes back to the seventies and eighties. Like back 285 00:17:17,200 --> 00:17:22,959 Speaker 1: then IBM dominated computing, like their mainframes were everywhere. If 286 00:17:23,040 --> 00:17:25,960 Speaker 1: you were an IT manager making a big purchase, you 287 00:17:25,960 --> 00:17:27,280 Speaker 1: know you were buying IBM. 288 00:17:27,440 --> 00:17:28,080 Speaker 2: It was safe. 289 00:17:28,680 --> 00:17:31,880 Speaker 1: They were the industry standard across the board in computing, 290 00:17:32,080 --> 00:17:35,760 Speaker 1: so like not necessarily the best choice, not necessarily the 291 00:17:35,800 --> 00:17:39,479 Speaker 1: most innovative, but they were the safest one. So because 292 00:17:39,640 --> 00:17:43,239 Speaker 1: if you bought IBM and something went wrong, nobody blames you. 293 00:17:43,760 --> 00:17:46,800 Speaker 1: They went with you went with the industry standard. Everybody 294 00:17:46,840 --> 00:17:49,480 Speaker 1: just IBM. Of course, of course you bought IBM, but 295 00:17:49,640 --> 00:17:51,600 Speaker 1: because you did what everybody else did, your job was 296 00:17:51,640 --> 00:17:55,760 Speaker 1: protected because you trusted the goliath. But if you took 297 00:17:55,760 --> 00:17:58,919 Speaker 1: a risk on some smaller company, that was innovative, but 298 00:17:59,000 --> 00:17:59,560 Speaker 1: it failed. 299 00:18:00,080 --> 00:18:00,639 Speaker 2: I was on you. 300 00:18:01,280 --> 00:18:04,560 Speaker 1: So the phrase wasn't really about IBM being great. It 301 00:18:04,640 --> 00:18:08,440 Speaker 1: was about covering your ass, like it was about choosing 302 00:18:08,760 --> 00:18:12,120 Speaker 1: the option that gave you plausible deniability, like I went 303 00:18:12,200 --> 00:18:15,360 Speaker 1: with the big dog, so you know what you want 304 00:18:15,400 --> 00:18:18,560 Speaker 1: me to do. And so like there's like this McKenzie 305 00:18:18,640 --> 00:18:20,560 Speaker 1: version that's like more present day, but it's like the 306 00:18:20,600 --> 00:18:24,160 Speaker 1: same principle, Like nobody ever got fired for hiring McKenzie 307 00:18:24,200 --> 00:18:27,719 Speaker 1: and so hire that prestigious consulting firm, and even if 308 00:18:27,720 --> 00:18:31,040 Speaker 1: their recommendations don't work, at least you can say you 309 00:18:31,119 --> 00:18:33,840 Speaker 1: brought in the experts. So this one's a little bit 310 00:18:33,880 --> 00:18:36,200 Speaker 1: more recent. The IBM one is a little bit more 311 00:18:36,240 --> 00:18:38,640 Speaker 1: like where it came from. So like that's where it's 312 00:18:38,640 --> 00:18:42,840 Speaker 1: headed with AI. So the AI said to do it 313 00:18:42,880 --> 00:18:48,000 Speaker 1: becomes the new McKenzie recommended it. And so we are 314 00:18:48,000 --> 00:18:52,720 Speaker 1: starting to give our critical thinking away to Claude and 315 00:18:52,840 --> 00:18:56,280 Speaker 1: Gemini and perplexity. So it's not even about being right anymore. 316 00:18:56,320 --> 00:18:58,920 Speaker 1: It's about being safe. It's about having somebody to point 317 00:18:58,960 --> 00:19:01,320 Speaker 1: to when stuff goes sideways. 318 00:19:01,960 --> 00:19:02,840 Speaker 2: That's the real risk. 319 00:19:03,640 --> 00:19:08,240 Speaker 1: So your decision making muscles atrophy, like leaders stop owning 320 00:19:08,280 --> 00:19:11,360 Speaker 1: the decisions. They just point to what the AI said. Well, 321 00:19:11,480 --> 00:19:14,080 Speaker 1: the AI recommended it, so and so, you know, it 322 00:19:14,160 --> 00:19:19,960 Speaker 1: becomes like a default excuse. Nobody feels responsible when things 323 00:19:20,000 --> 00:19:20,720 Speaker 1: go wrong. 324 00:19:20,560 --> 00:19:22,679 Speaker 2: Because hey, the AI said to do it. 325 00:19:23,600 --> 00:19:28,240 Speaker 1: Mistakes you know, become like systemic instead of like individual. 326 00:19:28,680 --> 00:19:30,440 Speaker 2: So like, the scariest future. 327 00:19:30,680 --> 00:19:33,680 Speaker 1: Isn't like AI thinking for us. It's us forgetting how 328 00:19:33,680 --> 00:19:41,760 Speaker 1: to think at all. Number seven, speed becomes a liability. 329 00:19:41,960 --> 00:19:48,600 Speaker 1: Like when speed is free, restraint becomes valuable. AI lets 330 00:19:48,640 --> 00:19:53,160 Speaker 1: you execute instantly, but it don't give you wisdom instantly. 331 00:19:53,480 --> 00:19:57,600 Speaker 1: Like fast decisions amplify bad assumptions, the cost of being 332 00:19:58,080 --> 00:20:03,920 Speaker 1: wrong will go up because found who pause outperform founders. 333 00:20:04,280 --> 00:20:08,520 Speaker 1: Founders who pause and think will outperform founders who sprint. 334 00:20:08,640 --> 00:20:13,280 Speaker 1: Timing matters more than velocity, So deliberate thinkers, people who 335 00:20:13,680 --> 00:20:16,960 Speaker 1: think about what they're doing, they think about their actions, 336 00:20:17,240 --> 00:20:21,240 Speaker 1: they will get an edge because when everybody can move fast, 337 00:20:21,960 --> 00:20:24,960 Speaker 1: being fast stops being a mote. It stops being will 338 00:20:25,000 --> 00:20:33,440 Speaker 1: protect you think number eight, we will realize that they 339 00:20:33,520 --> 00:20:38,000 Speaker 1: are in fact dumb questions. Here's what I mean by 340 00:20:38,000 --> 00:20:43,359 Speaker 1: that problem. Framing is the most valuable skill, Like AI 341 00:20:43,840 --> 00:20:47,760 Speaker 1: amplifies the quality of the question, not just the answer, 342 00:20:47,840 --> 00:20:51,560 Speaker 1: like most people are asking terrible questions. So let me 343 00:20:51,560 --> 00:20:54,520 Speaker 1: give you an example of what I mean. I've got 344 00:20:54,520 --> 00:20:57,320 Speaker 1: two people on my team both use AI. This is 345 00:20:57,480 --> 00:20:59,800 Speaker 1: this hypothetical example. By the way, I've got two people 346 00:20:59,840 --> 00:21:03,520 Speaker 1: on my team both use AI for content creation. Let's 347 00:21:03,560 --> 00:21:07,000 Speaker 1: call it in person A, person B. Person A types 348 00:21:07,040 --> 00:21:10,000 Speaker 1: in to let's pick on chat GPT. I need you 349 00:21:10,040 --> 00:21:13,320 Speaker 1: to write a script about AI tools for small business. 350 00:21:15,160 --> 00:21:15,560 Speaker 2: That's it. 351 00:21:15,600 --> 00:21:19,560 Speaker 1: They hit submit. What comes back is gonna be generic, 352 00:21:20,080 --> 00:21:22,560 Speaker 1: it's gonna be flat. It's gonna sound like every other 353 00:21:22,640 --> 00:21:28,080 Speaker 1: AI generated content you've ever seen, and it's gonna sound 354 00:21:28,119 --> 00:21:31,359 Speaker 1: something like In today's fast paced business environment, AI tools 355 00:21:31,400 --> 00:21:35,760 Speaker 1: are revolutionizing the way small businesses operate, from automation to analytics. 356 00:21:35,800 --> 00:21:37,919 Speaker 2: These powerful solutions Da da da da da. 357 00:21:38,000 --> 00:21:42,000 Speaker 1: You get The vibe is technically correct, Yeah, it's grammatically fine, 358 00:21:42,400 --> 00:21:47,600 Speaker 1: and it's completely forgettable. Person B, though, does something different. 359 00:21:49,600 --> 00:21:53,240 Speaker 1: Person B types write a ninety second video script for 360 00:21:53,320 --> 00:21:56,560 Speaker 1: a small business owner who's heard about AI but feels 361 00:21:56,560 --> 00:21:59,880 Speaker 1: overwhelmed and doesn't know where to start. They're not technical, 362 00:22:00,520 --> 00:22:04,880 Speaker 1: they're also busy, and they're skeptical the AI is actually 363 00:22:05,000 --> 00:22:08,800 Speaker 1: useful for them, and not just like hype. The tone 364 00:22:08,840 --> 00:22:13,320 Speaker 1: should be conversational and reassuring, like a friend giving advice 365 00:22:13,440 --> 00:22:16,760 Speaker 1: over coffee, not a tech company trying to sell something 366 00:22:17,240 --> 00:22:20,679 Speaker 1: open with a relatable moment, staying up late, trying to 367 00:22:20,680 --> 00:22:23,840 Speaker 1: write marketing emails after a full day of running the business. 368 00:22:24,200 --> 00:22:27,840 Speaker 1: Then introduce one specific simple tool they can try this 369 00:22:27,920 --> 00:22:31,800 Speaker 1: week that'll save them three hours. End with encouragement, not pressure, 370 00:22:32,280 --> 00:22:38,399 Speaker 1: no jargon at all. You can already probably guess the 371 00:22:38,480 --> 00:22:41,560 Speaker 1: script that came out of that one. You don't even 372 00:22:41,560 --> 00:22:42,919 Speaker 1: have to know what it's gonna say, but you know 373 00:22:42,960 --> 00:22:45,240 Speaker 1: it's gonna be better than the first one. The difference 374 00:22:45,320 --> 00:22:48,040 Speaker 1: is not the AI, because they were using the same tool. 375 00:22:49,119 --> 00:22:52,080 Speaker 1: The difference is the quality of the input. Person B 376 00:22:52,280 --> 00:22:56,879 Speaker 1: gave context. They define the audience, They specify the emotional 377 00:22:56,920 --> 00:22:59,800 Speaker 1: state of that audience. They set constraints. They told it 378 00:22:59,840 --> 00:23:02,600 Speaker 1: what not to do. They said, describe the tone they wanted. 379 00:23:02,680 --> 00:23:05,359 Speaker 1: They outlined the structure. They told them what kind of 380 00:23:05,400 --> 00:23:08,280 Speaker 1: format to put it in person ages as for a 381 00:23:08,320 --> 00:23:12,359 Speaker 1: thing in his why this matters economically? Even the gap 382 00:23:12,480 --> 00:23:17,159 Speaker 1: in output quality between those two prompts is massive person 383 00:23:17,240 --> 00:23:21,280 Speaker 1: B script is usable, it connects, it might actually convert 384 00:23:22,119 --> 00:23:26,480 Speaker 1: person as script goes into trash. It's the same tool, 385 00:23:26,720 --> 00:23:30,879 Speaker 1: the same amount of time spent prompting completely different value creation. 386 00:23:32,640 --> 00:23:36,440 Speaker 1: Now scale that across an organization, across you know, every 387 00:23:36,480 --> 00:23:40,080 Speaker 1: email written, every ad you put up, every piece of content, 388 00:23:40,400 --> 00:23:44,040 Speaker 1: every analysis, every decision and support requests a. 389 00:23:44,000 --> 00:23:45,359 Speaker 2: Scale that across all of that. 390 00:23:46,640 --> 00:23:50,120 Speaker 1: The people who can frame problems, the people who can 391 00:23:50,160 --> 00:23:52,920 Speaker 1: frame problems well, will get ten x, maybe one hundred 392 00:23:53,080 --> 00:23:55,320 Speaker 1: x more value out of AI than people who can't. 393 00:23:56,320 --> 00:24:01,560 Speaker 1: That's economic leverage. And it's not about knowing fancy prompt 394 00:24:01,800 --> 00:24:05,199 Speaker 1: engineering tricks. It's not about you know, just doing some 395 00:24:05,400 --> 00:24:07,400 Speaker 1: cool trickery that you saw on YouTube. 396 00:24:07,400 --> 00:24:07,480 Speaker 2: Like. 397 00:24:07,520 --> 00:24:11,880 Speaker 1: It's actually about thinking clearly. It's about understanding your audience. 398 00:24:11,920 --> 00:24:15,720 Speaker 1: It's about knowing what good looks like. It's about being 399 00:24:15,800 --> 00:24:19,600 Speaker 1: able to articulate constraints and context. So I'll give you 400 00:24:19,680 --> 00:24:22,840 Speaker 1: another example. It's time with like data analysis. So here's 401 00:24:22,840 --> 00:24:26,399 Speaker 1: a bad prompt. I'm gonna upload a sheet with like 402 00:24:26,440 --> 00:24:28,480 Speaker 1: a bunch of sales on it, and I tell chat, 403 00:24:28,480 --> 00:24:34,199 Speaker 1: GBT or Gemini to analyze this sales data. So what 404 00:24:34,240 --> 00:24:36,760 Speaker 1: you're gonna get back. You're gonna get a summary statistics, 405 00:24:36,800 --> 00:24:38,960 Speaker 1: you're gonna get averages, you're gonna get a chart. You 406 00:24:39,000 --> 00:24:43,440 Speaker 1: can get some technically accurate stuff, but useless stuff likely. 407 00:24:44,280 --> 00:24:49,280 Speaker 1: So a better prompt is to say something like, analyze. 408 00:24:48,760 --> 00:24:51,400 Speaker 2: The sales data for a B two B SaaS. 409 00:24:51,080 --> 00:24:54,760 Speaker 1: Company sales as a service company, and we sell project 410 00:24:54,840 --> 00:24:58,840 Speaker 1: management software with an average contract value of five thousand 411 00:24:58,880 --> 00:25:01,879 Speaker 1: dollars per year. Our sales cycle is typically thirty to 412 00:25:01,920 --> 00:25:05,000 Speaker 1: forty five days. I want to understand why our close 413 00:25:05,160 --> 00:25:08,280 Speaker 1: rate dropped from twenty eight percent to nineteen. 414 00:25:07,960 --> 00:25:09,280 Speaker 2: Percent over the last quarter. 415 00:25:09,320 --> 00:25:12,400 Speaker 1: Specifically, I want to know, are we losing deals at 416 00:25:12,400 --> 00:25:16,440 Speaker 1: a different stage than before. Has the profile of leads changed, 417 00:25:16,800 --> 00:25:20,600 Speaker 1: Are certain industries or company sciences converting worse than they 418 00:25:20,680 --> 00:25:23,840 Speaker 1: used to? Has our average deal size change? And it's 419 00:25:23,880 --> 00:25:28,800 Speaker 1: so we're correlated with that close rate. Give me actionable insights, 420 00:25:29,200 --> 00:25:34,080 Speaker 1: not just descriptive statistics. You see the difference. The second 421 00:25:34,080 --> 00:25:37,600 Speaker 1: problem has business contexts, It has specific metrics, It has 422 00:25:37,640 --> 00:25:41,240 Speaker 1: a clear question. It asks for insights, not just outputs. 423 00:25:42,119 --> 00:25:46,560 Speaker 1: That's problem framing. So yes, there are dumb questions, and 424 00:25:46,640 --> 00:25:47,920 Speaker 1: in twenty twenty six. 425 00:25:48,080 --> 00:25:49,800 Speaker 2: We will start to see. 426 00:25:49,760 --> 00:25:53,280 Speaker 1: Who's asking dumb questions. So number nine, my number nine 427 00:25:53,320 --> 00:25:56,239 Speaker 1: prediction that we'll see regarding AI in twenty twenty six 428 00:25:56,400 --> 00:25:59,720 Speaker 1: is more and more people will be seen to struggle 429 00:25:59,760 --> 00:26:03,360 Speaker 1: with imposter syndrome. It's gonna spike this year, even high performers. 430 00:26:03,640 --> 00:26:06,520 Speaker 1: So one of the least talked about effects of this 431 00:26:06,640 --> 00:26:09,680 Speaker 1: AI boom that we're in right now is what it's 432 00:26:09,720 --> 00:26:13,439 Speaker 1: gonna do to people's sense its self. So not in 433 00:26:13,480 --> 00:26:17,720 Speaker 1: like an abstract way and not even philosophically, but like emotionally, 434 00:26:18,200 --> 00:26:21,600 Speaker 1: like a lot of people, especially high performers, are about 435 00:26:21,640 --> 00:26:24,840 Speaker 1: to feel something shift and them he's what I mean. 436 00:26:25,359 --> 00:26:28,760 Speaker 1: Like for years, your value was tied to the skills 437 00:26:28,760 --> 00:26:34,760 Speaker 1: you worked hard to develop, like whether that be writing, analysis, strategy, code, execution, 438 00:26:35,560 --> 00:26:39,120 Speaker 1: And now AI can do a lot of that in seconds, 439 00:26:39,680 --> 00:26:42,920 Speaker 1: not perfectly, but convincingly and in some ways perfectly. Don't 440 00:26:42,920 --> 00:26:47,719 Speaker 1: get it twisted, but for sure convincingly. And when something 441 00:26:47,760 --> 00:26:51,960 Speaker 1: you spent ten to fifteen years mastering gets replicated instantly, 442 00:26:52,520 --> 00:26:55,520 Speaker 1: that does something to your psyche, That does something subtle 443 00:26:55,560 --> 00:26:58,879 Speaker 1: to your identity, and people will start asking questions like 444 00:26:58,960 --> 00:27:01,879 Speaker 1: they've never had to ask before, like what does this. 445 00:27:02,040 --> 00:27:02,600 Speaker 2: Mean for me? 446 00:27:02,800 --> 00:27:05,600 Speaker 1: Like what part of this is actually me? If I'm 447 00:27:05,600 --> 00:27:08,879 Speaker 1: being paid, what am I being paid for now? Like 448 00:27:08,960 --> 00:27:11,520 Speaker 1: if a machine can do this, what makes me valuable? 449 00:27:12,160 --> 00:27:14,960 Speaker 1: And so that's where imposter syndrome starts to creep in, 450 00:27:15,040 --> 00:27:18,040 Speaker 1: not because you're unqualified, but because the ground shifted up 451 00:27:18,080 --> 00:27:20,560 Speaker 1: under you. If a small business owners, this shows up 452 00:27:20,600 --> 00:27:22,920 Speaker 1: in a very specific way, like you might look at 453 00:27:22,920 --> 00:27:27,280 Speaker 1: AI handling, marketing, bookkeeping, you know, customer emails, analytics and 454 00:27:27,320 --> 00:27:30,840 Speaker 1: more and feel like weirdly unnecessary in your own business. 455 00:27:31,280 --> 00:27:34,000 Speaker 1: Not because the business doesn't need you, but because the 456 00:27:34,080 --> 00:27:38,080 Speaker 1: kind of value you bring changed to the business. And 457 00:27:38,119 --> 00:27:41,359 Speaker 1: the danger is trying to compete with AI on execution. 458 00:27:41,600 --> 00:27:44,840 Speaker 1: That's a losing game in my opinion. The opportunity is 459 00:27:44,880 --> 00:27:48,880 Speaker 1: like recognizing your real value was never speed or output. 460 00:27:49,080 --> 00:27:53,280 Speaker 1: It was judgment, It was taste, it was context and 461 00:27:53,400 --> 00:27:58,560 Speaker 1: responsibility wisdom Like AI can generate a ton of options, 462 00:27:59,040 --> 00:28:03,520 Speaker 1: but it cannot chew what matters. So this year a 463 00:28:03,520 --> 00:28:06,919 Speaker 1: lot of people are gonna have to reanchor their identity, 464 00:28:07,000 --> 00:28:09,720 Speaker 1: like not in what they do, but in how they decide, 465 00:28:10,440 --> 00:28:12,920 Speaker 1: not in how fast they can execute, but in how 466 00:28:12,960 --> 00:28:17,840 Speaker 1: well they frame problems. So the people who struggle The 467 00:28:17,880 --> 00:28:19,840 Speaker 1: people who struggle, on the other hand, will be the 468 00:28:19,840 --> 00:28:22,800 Speaker 1: ones who keep asking how do I stay relevant? The 469 00:28:22,840 --> 00:28:25,679 Speaker 1: people who thrive will ask what kind of thinker do 470 00:28:25,720 --> 00:28:28,520 Speaker 1: I want to be in this next iteration of time? 471 00:28:28,840 --> 00:28:32,640 Speaker 1: Because AI does not just automate skills, it forces us 472 00:28:32,640 --> 00:28:35,800 Speaker 1: to ask a deeper question like if my tools are powerful, 473 00:28:36,160 --> 00:28:41,360 Speaker 1: who do I become? And the answer to that question 474 00:28:41,480 --> 00:28:44,840 Speaker 1: is going to matter more this year than any new 475 00:28:44,880 --> 00:28:48,720 Speaker 1: software you adopt. And so number ten that brings us 476 00:28:48,760 --> 00:28:51,440 Speaker 1: to the last one, number ten. The number ten, number 477 00:28:51,440 --> 00:28:53,960 Speaker 1: ten thing is a realization that I believe that we're 478 00:28:53,960 --> 00:28:56,040 Speaker 1: going to have this year, and it's this idea that 479 00:28:56,480 --> 00:29:00,160 Speaker 1: AI won't replace you, only people using AI will replace you. 480 00:29:00,600 --> 00:29:03,680 Speaker 1: And that's an incomplete argument in my opinion. Like some 481 00:29:04,480 --> 00:29:08,440 Speaker 1: jobs will be could just completely eliminated outright customer service 482 00:29:08,520 --> 00:29:14,000 Speaker 1: reps trouble, like junior copywriters trouble, data intrigue trouble, pair 483 00:29:14,040 --> 00:29:18,760 Speaker 1: of legals doing document review in trouble. But here's like 484 00:29:18,840 --> 00:29:21,400 Speaker 1: the darker other side of this that we just don't 485 00:29:21,400 --> 00:29:25,400 Speaker 1: talk about is other jobs won't exist in the first place. 486 00:29:26,360 --> 00:29:30,400 Speaker 1: That's a company who just would have hired three junior marketers, 487 00:29:30,640 --> 00:29:33,120 Speaker 1: but they just don't hire them, and so they may 488 00:29:33,160 --> 00:29:35,600 Speaker 1: not have lost their job. Those junior marketers, they just 489 00:29:35,600 --> 00:29:39,360 Speaker 1: never got hired in the first place. And so the 490 00:29:39,520 --> 00:29:43,120 Speaker 1: freelance graphic designer who would have gotten you know, steady 491 00:29:43,120 --> 00:29:46,200 Speaker 1: client work, that client's now using mid journey, you know, 492 00:29:46,280 --> 00:29:48,120 Speaker 1: and doesn't even think about hiring. 493 00:29:47,840 --> 00:29:50,040 Speaker 2: Somebody that the demand. 494 00:29:49,800 --> 00:29:53,200 Speaker 1: For that labor just declines, not just the demand for skills, 495 00:29:53,200 --> 00:29:57,720 Speaker 1: but demand for the labor. So entry level roles disappeared 496 00:29:57,800 --> 00:30:01,960 Speaker 1: like they just start going away, and we're already seeing it, 497 00:30:02,520 --> 00:30:04,920 Speaker 1: you know. So we keep saying that AI won't take jobs, 498 00:30:04,960 --> 00:30:07,840 Speaker 1: but jobs will have never been created in the first place. 499 00:30:07,880 --> 00:30:11,800 Speaker 1: So economic anxiety is gonna spread, and not just junior people, 500 00:30:11,840 --> 00:30:12,800 Speaker 1: high performers too. 501 00:30:12,920 --> 00:30:14,520 Speaker 2: Some people won't lose. 502 00:30:14,280 --> 00:30:18,200 Speaker 1: Their jobs AI, they'll lose their opportunity to ever have one. 503 00:30:20,080 --> 00:30:22,600 Speaker 1: And so I want to push back on this argument 504 00:30:22,960 --> 00:30:24,440 Speaker 1: that AI is not going. 505 00:30:24,240 --> 00:30:25,000 Speaker 2: To take jobs. 506 00:30:25,040 --> 00:30:27,600 Speaker 1: It is for sure going to take jobs, and it's 507 00:30:27,640 --> 00:30:30,320 Speaker 1: also going to make jobs to have never been created. 508 00:30:30,480 --> 00:30:34,600 Speaker 1: So in closing, that was my list of ten predictions 509 00:30:34,600 --> 00:30:37,760 Speaker 1: for twenty twenty six. I hope that doesn't scare you, 510 00:30:37,800 --> 00:30:39,480 Speaker 1: Like my job here is not to scare you, but 511 00:30:39,520 --> 00:30:41,720 Speaker 1: to bring awareness to what's going on in the world, 512 00:30:41,800 --> 00:30:44,040 Speaker 1: and to help prepare you for the world that we're 513 00:30:44,040 --> 00:30:46,400 Speaker 1: walking into, because I believe the people who win in 514 00:30:46,440 --> 00:30:48,760 Speaker 1: twenty twenty six won't be the ones who are like 515 00:30:48,840 --> 00:30:51,600 Speaker 1: chasing tools. They'll be the ones who understand leverage and 516 00:30:51,680 --> 00:30:56,040 Speaker 1: judgment tastes and like restraint. And that's really it. I 517 00:30:56,080 --> 00:30:58,160 Speaker 1: really appreciate you for listening. If you've got something out 518 00:30:58,200 --> 00:31:00,840 Speaker 1: of this, please shut it with somebody. Black Tachree money 519 00:31:00,840 --> 00:31:01,520 Speaker 1: on Will Lucas