1 00:00:00,080 --> 00:00:04,797 idea of the superpowered individual uh where if if I'm a coder like you know I 2 00:00:04,880 --> 00:00:07,517 mean step one is like I need to make sure that I really understand AI coding 3 00:00:07,600 --> 00:00:10,477 and like what that means and what how coding is going to change in the future 4 00:00:10,560 --> 00:00:13,997 you know that that I need to you know specifically how to go from being a 5 00:00:14,080 --> 00:00:17,357 coder who writes code entirely by hand to being a coder who you know 6 00:00:17,440 --> 00:00:21,597 orchestrates you know a dozen instances of of you know coding bots you know you 7 00:00:21,680 --> 00:00:24,477 know there's there's a change in the actual job of coding itself which is 8 00:00:24,560 --> 00:00:27,917 which is happening right now but the other part of it is okay how do I become 9 00:00:28,000 --> 00:00:31,277 that superpowered individual how how do become a coder that also then harnesses 10 00:00:31,360 --> 00:00:34,477 AI so that I can also be a great product manager and I I can also be a great 11 00:00:34,560 --> 00:00:38,157 designer, right? And then the same thing for the product manager which is how do 12 00:00:38,240 --> 00:00:40,957 I make sure that I can now use coding tools? How do I make sure I can also you 13 00:00:41,040 --> 00:00:44,957 know do AI AI based design? And the same thing for the designer which is how do I 14 00:00:45,040 --> 00:00:48,397 use AI to be also become a coder and also become a product manager. And then 15 00:00:48,480 --> 00:00:52,797 what you get is maybe the maybe the those individual roles change like maybe 16 00:00:52,880 --> 00:00:55,837 those are not anymore sort of stovepipe roles the way that you know they have 17 00:00:55,920 --> 00:00:57,597 been for the last 30 years or whatever. 18 00:00:57,680 --> 00:01:01,037 Uh but what happens is the the talented people in any of those roles become 19 00:01:01,120 --> 00:01:04,237 superpowered and they become good at doing all three of those things. Um and 20 00:01:04,320 --> 00:01:06,957 then and then those people become incredibly valuable because then those 21 00:01:07,040 --> 00:01:10,477 are people who can actually like you know build and design right new products 22 00:01:10,560 --> 00:01:13,277 right from scratch which is like the you know which is which is the most valuable 23 00:01:13,360 --> 00:01:17,117 thing. And so I I think I think that's I think I think that's the opportunity. 24 00:01:17,200 --> 00:01:20,557 >> So I love this answer. So what I'm hearing is essentially uh if you're 25 00:01:20,640 --> 00:01:23,997 amazing at any of these three roles you will do well. Number one, if you're 26 00:01:24,080 --> 00:01:25,837 amazing at these roles, that's great. 27 00:01:25,920 --> 00:01:29,597 But also, you part of being amazing in these roles is also being being able to 28 00:01:29,680 --> 00:01:31,757 fully harness the new technology, right? 29 00:01:31,840 --> 00:01:35,437 So, if you're if you're a master coder today and you you don't ever get to the 30 00:01:35,520 --> 00:01:38,157 point where you you figure out how to use AI to leverage your coding skills, 31 00:01:38,240 --> 00:01:41,357 you know, and and do more, right? Like at some point, you are going to hit an 32 00:01:41,440 --> 00:01:46,477 issue, right? Here's another way economists talk about this, which is 33 00:01:46,560 --> 00:01:50,157 there's the concept of the job, but the job is not actually the atomic unit of 34 00:01:50,240 --> 00:01:52,397 what happens in the workplace. The atomic unit of what happens in the 35 00:01:52,480 --> 00:01:56,157 workplace is the task. And so and and then what what the way the economists 36 00:01:56,240 --> 00:01:59,997 think about it is a job is a bundle of tasks. And everybody wants to talk about 37 00:02:00,080 --> 00:02:01,357 job loss, but really what you want to 38 00:02:01,440 --> 00:02:04,397 look at is is task task loss, right? 39 00:02:04,480 --> 00:02:07,837 Tasks changing. I mean the the the the 40 00:02:07,920 --> 00:02:11,437 classic the classic example of task changing. Classic example of task 41 00:02:11,520 --> 00:02:15,517 changing was once upon a time executives never used typewriters or personal 42 00:02:15,600 --> 00:02:18,877 computers themselves, right? You know, if you were a vice president of a 43 00:02:18,960 --> 00:02:21,997 company in 1970 or whatever, you did not have like a typewriter or a computer on 44 00:02:22,080 --> 00:02:25,517 your desk typing things. You had a secretary who you dictated memos to, 45 00:02:25,600 --> 00:02:28,077 right? And then there and then there was this change where like emails started to 46 00:02:28,160 --> 00:02:31,357 show up. And what would happen was the job of the secretary then went from, you 47 00:02:31,440 --> 00:02:34,397 know, it went from, you know, the the job of the secretary changed from 48 00:02:34,480 --> 00:02:37,437 sending out letters with stamps on them to like sending or receiving emails with 49 00:02:37,520 --> 00:02:40,717 the other admins. And then and then that the secretary would print out the email 50 00:02:40,800 --> 00:02:43,357 and bring it into the executive's office. And the executive office would 51 00:02:43,440 --> 00:02:47,997 read the email and paper, scroll scroll the reply. um and and and and give and 52 00:02:48,080 --> 00:02:50,477 give that message back to the secretary who would go back and type it into the 53 00:02:50,560 --> 00:02:54,797 computer on on on on his or her desk and send it as an email. Fast forward to 54 00:02:54,880 --> 00:02:58,877 today, none of that happens. Now executives just do all their own email. 55 00:02:58,960 --> 00:03:02,957 They still have secretaries or admins, but they're now doing different tasks. 56 00:03:03,040 --> 00:03:06,077 You know, they're travel planning and orchestrating events and like doing all 57 00:03:06,160 --> 00:03:09,677 these other things, you know, that that you know that the great admins do. And 58 00:03:09,760 --> 00:03:14,237 then that and then the task the task set ironically of the executive has expanded 59 00:03:14,320 --> 00:03:17,517 to do actually more of the clerical work themselves actually like sit there and 60 00:03:17,600 --> 00:03:20,637 like type their own memos which again 50 years ago they never never would have 61 00:03:20,720 --> 00:03:24,077 done that. And so the executive job still exists the secretary job still 62 00:03:24,160 --> 00:03:28,157 exists u but the tasks have changed and and I think that's like a great example 63 00:03:28,240 --> 00:03:31,037 of what's going to happen in coding. The tasks are going to change it's product 64 00:03:31,120 --> 00:03:33,517 management the tasks are going to change. designer tasks are going to 65 00:03:33,600 --> 00:03:36,557 change and so the the the job can p the 66 00:03:36,640 --> 00:03:38,477 job persists longer than the individual 67 00:03:38,560 --> 00:03:41,437 tasks and then as the tasks change 68 00:03:41,520 --> 00:03:46,237 enough then that's when the jobs change and so at the at the level of individual 69 00:03:46,320 --> 00:03:49,757 you kind of want to think of like okay I have this job the job is a bundle of 70 00:03:49,840 --> 00:03:53,277 tasks I need to be really good at making sure that I can like swap the tasks out 71 00:03:53,360 --> 00:03:56,877 right I can I can really adapt use the new technology you know get really good 72 00:03:56,960 --> 00:04:00,077 at AI coding for example um I can you know and then and then you want to kind 73 00:04:00,160 --> 00:04:03,117 of add skills I can also get really good at I can also get really good at product 74 00:04:03,200 --> 00:04:06,477 management because I've got this new tool. So you want to kind of pick up 75 00:04:06,560 --> 00:04:09,997 more and more scope as you do that. And then you know 10 years from now is your 76 00:04:10,080 --> 00:04:12,717 job title coder or coder designer 77 00:04:12,800 --> 00:04:17,197 product manager or is it just I build products or is it just I tell the AI how 78 00:04:17,280 --> 00:04:20,397 to build products? It's like whatever that whatever that job is called who 79 00:04:20,480 --> 00:04:22,797 even knows what it's going to be but it's going to be incredibly important 80 00:04:22,880 --> 00:04:25,917 because the people doing that job are going to be orchestrating the AI. And so 81 00:04:26,000 --> 00:04:29,837 that that that's the track that the best people are going to be on. Um, and and I 82 00:04:29,920 --> 00:04:32,477 think that that's the thing to lean hard lean heart into. 83 00:04:32,560 --> 00:04:35,997 >> I think people aren't fully grasping just specifically software engineering 84 00:04:36,080 --> 00:04:40,317 and how much that is changing. Like it's pretty clear we're going to be in a 85 00:04:40,400 --> 00:04:43,997 world soon where engineers are not actually writing code which I think a 86 00:04:44,080 --> 00:04:47,037 year ago we would not have thought and now it's just clearly this is where it's 87 00:04:47,120 --> 00:04:49,997 heading. It's like there's going to be this artisal experience of sitting there 88 00:04:50,080 --> 00:04:54,237 writing code which is so crazy how much that job is going to change. 89 00:04:54,320 --> 00:04:56,397 >> Yeah. So again here I go back and again 90 00:04:56,480 --> 00:05:02,077 pardon maybe the history lesson but like I go back like coding. So the first you 91 00:05:02,160 --> 00:05:04,637 may know that do you know that the original definition of the of the term 92 00:05:04,720 --> 00:05:07,037 calculator? Do you know what that referred to? 93 00:05:07,120 --> 00:05:10,237 >> No. >> It referred to people. 94 00:05:10,320 --> 00:05:14,157 Right. So back there were like electronic calculators or computers or 95 00:05:14,240 --> 00:05:18,237 any of these things. um the way that you would actually do computing, the way 96 00:05:18,320 --> 00:05:20,637 that you would do calculating like the way that insurance company would 97 00:05:20,720 --> 00:05:23,677 calculate actuarial tables or the military would like calculate you know I 98 00:05:23,760 --> 00:05:27,357 don't know whatever troop logistics you formulas or whatever it was the way that 99 00:05:27,440 --> 00:05:30,477 you would do it is you would actually have a room full of people um and by the 100 00:05:30,560 --> 00:05:33,117 way these like big rooms you could have hundreds or thousands or tens of 101 00:05:33,200 --> 00:05:36,237 thousands of people doing this and you would actually you would actually figure 102 00:05:36,320 --> 00:05:38,877 out you have somebody at the head of the room who was like responsible for like 103 00:05:38,960 --> 00:05:42,397 whatever the mathematical equation was and then they would parcel out the 104 00:05:42,480 --> 00:05:45,277 individual mathematical calculations to people sitting at desks who were doing 105 00:05:45,360 --> 00:05:48,957 them all by hand, right? And and those that that that job title was those 106 00:05:49,040 --> 00:05:53,757 people were calculators, right? Um and so we've gone from a world in which you 107 00:05:53,840 --> 00:05:58,157 literally have people doing mathematical equations by hands by hand. Then we got 108 00:05:58,240 --> 00:06:00,717 the first computers. The first computers of course didn't have programming 109 00:06:00,800 --> 00:06:04,317 languages, right? They they only had machine code, right? So the first 110 00:06:04,400 --> 00:06:07,837 computers were programmed with ones and zeros. And so the task of the programmer 111 00:06:07,920 --> 00:06:11,997 became do the ones and zeros. And then that became punch cards. And you can 112 00:06:12,080 --> 00:06:14,637 still, you know, there's still people, you know, kicking, you know, today who, 113 00:06:14,720 --> 00:06:17,757 you know, whose job as a programmer was to like deal with the punch cards. And 114 00:06:17,840 --> 00:06:20,397 then you got actually this big breakthrough which was called assembly 115 00:06:20,480 --> 00:06:23,917 language, which was basically the way to do machine code, but like with some 116 00:06:24,000 --> 00:06:27,437 level of like English kind of added to it. And then the best programmers did 117 00:06:27,520 --> 00:06:30,237 assembly language. And then, you know, when I was coming up, it was higher 118 00:06:30,320 --> 00:06:33,677 level languages like C that compiled into machine code. And that's what 119 00:06:33,760 --> 00:06:36,957 programmers did. And then I still remember when when scripting, you know, 120 00:06:37,040 --> 00:06:39,277 when scripting languages, you know, we developed JavaScript at Netscape and 121 00:06:39,360 --> 00:06:41,437 then, you know, Python took off and Pearl and these other scripting 122 00:06:41,520 --> 00:06:44,797 languages. When scripting languages, you know, took off in the in the in the in 123 00:06:44,880 --> 00:06:48,717 the in the 2000s, there's this big fight in the technical community, which is is 124 00:06:48,800 --> 00:06:51,597 scripting real programming or not, right? Because it's it's like it's kind 125 00:06:51,680 --> 00:06:54,877 of cheating, right? Because real programmers write code that compiles to 126 00:06:54,960 --> 00:06:58,317 machine code and like real programmers like do like memory management 127 00:06:58,400 --> 00:07:01,277 themselves and they do all you know this this this whole craft of writing writing 128 00:07:01,360 --> 00:07:04,397 uh you know writing writing C code and you know these these JavaScript or 129 00:07:04,480 --> 00:07:06,717 Python programmers are just doing this kind of lightweight thing and does it 130 00:07:06,800 --> 00:07:09,357 even really count as as coding and of course the answer is yes it very much 131 00:07:09,440 --> 00:07:13,037 counted and now most coding is done with the scripting languages right um which 132 00:07:13,120 --> 00:07:17,437 have you see my point the scripting languages have abstracted away like five 133 00:07:17,520 --> 00:07:20,237 layers of detail underneath that that people used to do by hand and they don't 134 00:07:20,320 --> 00:07:24,237 anymore and then and then there's and to your point like AI coding is the next 135 00:07:24,320 --> 00:07:27,037 layer on that AI coding actually abstracts away the process of actually 136 00:07:27,120 --> 00:07:31,197 writing the scripting code right and so in one sense this is a really big deal 137 00:07:31,280 --> 00:07:33,917 for all the obvious reasons but on the other hand it's like okay this is the 138 00:07:34,000 --> 00:07:36,477 next layer of the task redefinition 139 00:07:36,560 --> 00:07:40,157 under the job of programmer right now 140 00:07:40,240 --> 00:07:43,917 what's the job of the programmer it's to your point it's not necessarily to write 141 00:07:44,000 --> 00:07:46,957 the code by hand but what it is now is all right now you know if you talk to 142 00:07:47,040 --> 00:07:50,157 the world's best programmers today what they'll tell you is oh my job is I'm 143 00:07:50,240 --> 00:07:53,837 sitting there and I'm orchestrating 10 code bots, right? Coding bots that are 144 00:07:53,920 --> 00:07:56,317 running in parallel, right? And literally they sit there and they shift 145 00:07:56,400 --> 00:07:58,797 from browser, you know, browser to browser or terminal to terminal and 146 00:07:58,880 --> 00:08:01,597 they're and they're they're watch they're their their day their day job 147 00:08:01,680 --> 00:08:04,397 now is kind of arguing with the AI bots to try to get them to like write the 148 00:08:04,480 --> 00:08:07,277 right code, right? And then and then debug it and and fix the problems and 149 00:08:07,360 --> 00:08:10,717 change change the spec and and do all these things. And so now now the job of 150 00:08:10,800 --> 00:08:14,157 the programmer is to argue with the coding bots. But like if you don't know 151 00:08:14,240 --> 00:08:17,037 how to write the code yourself, you don't know how to evaluate what the 152 00:08:17,120 --> 00:08:18,637 coding bots are giving you, right? 153 00:08:18,720 --> 00:08:21,677 Right. And so, you know, you asked about the 10, you know, our 10-year-old is, 154 00:08:21,760 --> 00:08:24,317 you know, super into computers and super into programming. And what I'm what I'm 155 00:08:24,400 --> 00:08:27,597 tell, you know, he's he's using Claude and ChatgPD co-pilot and all these 156 00:08:27,680 --> 00:08:30,237 things. What I'm telling him is like, look, and by the way, he loves vibe 157 00:08:30,320 --> 00:08:32,957 coding. He's on Replet all the time doing vibe coding, you know, doing game 158 00:08:33,040 --> 00:08:35,597 doing games, you know, he's sitting there, you know, it's hysterical, right? 159 00:08:35,680 --> 00:08:37,677 Because he's sitting there, it's a 10-year-old basically who's, you know, 160 00:08:37,760 --> 00:08:42,717 spends two hours at dinner arguing with an AI for fun, right? Um, right? But but 161 00:08:42,800 --> 00:08:46,077 what I'm telling him is, no, look, you need to still fully understand and learn 162 00:08:46,160 --> 00:08:50,397 how to write and understand code because the coding bots are giving you code. If 163 00:08:50,480 --> 00:08:53,117 it doesn't work or if it's not doing what you expect or it's not fast enough 164 00:08:53,200 --> 00:08:55,997 or whatever, like you need to be able to understand the results of what the AI is 165 00:08:56,080 --> 00:08:58,877 giving you, right? In in the same way that somebody who's writing scripting 166 00:08:58,960 --> 00:09:01,997 language code does need to understand ultimately how the microprocessor works. 167 00:09:02,080 --> 00:09:06,317 Um, and so again, it's it's kind of this upleveling of capability where you 168 00:09:06,400 --> 00:09:09,757 actually want the depth to be able to go down and be able to understand what the 169 00:09:09,840 --> 00:09:12,717 thing is actually doing, even if you're not spending your day actually doing 170 00:09:12,800 --> 00:09:15,757 that by hand. And again, I look at that and I'm like, okay, now programmers are 171 00:09:15,840 --> 00:09:18,797 going to be 10 times or 100 times or a thousand times more productive than they 172 00:09:18,880 --> 00:09:22,237 used to be, right? And and that and and that is overwhelmingly a good thing. 173 00:09:22,320 --> 00:09:25,837 That the the the tasks are definitely changing. The nature of the job is 174 00:09:25,920 --> 00:09:28,157 changing. Um, but are human beings going 175 00:09:28,240 --> 00:09:33,277 to be involved in like in the coding process and overseeing the the AI coding 176 00:09:33,360 --> 00:09:37,357 and all that? And and the answer is of course absolutely 100%. Like no question. 177 00:09:37,440 --> 00:09:40,077 >> So you're in the camp of still learning to code. Still a valuable skill. 178 00:09:40,160 --> 00:09:43,437 >> Oh yeah, totally. Well, again, if you want to be one of these super look look, 179 00:09:43,520 --> 00:09:47,117 if you just want to put your like self in autopilot and like I can't be 180 00:09:47,200 --> 00:09:49,357 bothered and I'm just going to have AI write the code and it's going to 181 00:09:49,440 --> 00:09:51,837 generate whatever it does and that's fine and I'm going to be, you know, I'm 182 00:09:51,920 --> 00:09:56,557 going to be if if the goal is to be a mediocre coder, then just let the AI do 183 00:09:56,640 --> 00:09:59,197 it. It's fine. The AI is going to be perfectly good at generating infinite 184 00:09:59,280 --> 00:10:00,877 amounts of mediocre code, no problem. 185 00:10:00,960 --> 00:10:04,237 It's all good. If if if the goal is I want to be one of the best software 186 00:10:04,320 --> 00:10:07,197 people in the world and I want to build new software products and technologies 187 00:10:07,280 --> 00:10:11,437 that like really matter then yeah you 100% want to still be you want to go all 188 00:10:11,520 --> 00:10:13,997 the way down you want your skill set to go all the way down to the assembly to 189 00:10:14,080 --> 00:10:17,277 assembly and machine code you want to understand every layer of the stack you 190 00:10:17,360 --> 00:10:19,997 want to deeply understand what's happening at the level of the chip right 191 00:10:20,080 --> 00:10:23,597 and and and the network and so forth by the way you also really deeply want to 192 00:10:23,680 --> 00:10:27,037 understand how the AI itself works right because you want to right because if 193 00:10:27,120 --> 00:10:30,557 people who understand how the AI works are able to they're clearly able to get 194 00:10:30,640 --> 00:10:33,117 more value out of it than somebody doesn't understand how it works, right? 195 00:10:33,200 --> 00:10:35,677 I mean, you're always more productive if you know how the machine works, right, 196 00:10:35,760 --> 00:10:39,437 when you use the machine. And so, yeah, the the super empowered individual on 197 00:10:39,520 --> 00:10:42,317 the other end of this that wants to do great things with the new technology, 198 00:10:42,400 --> 00:10:45,517 yes, you 100% want to understand this thing all the way down the stack because 199 00:10:45,600 --> 00:10:48,557 you want to be able to understand what it's giving you, right? And and and when 200 00:10:48,640 --> 00:10:50,797 something doesn't work or when something isn't right, you want to be able to 201 00:10:50,880 --> 00:10:52,637 really quickly understand why that is. 202 00:10:52,720 --> 00:10:57,197 Um, by the way, again, this goes back to education. AI is your best friend at 203 00:10:57,280 --> 00:10:58,317 helping you learn all that, right? 204 00:10:58,400 --> 00:11:00,797 because it's like, oh, I need to understand, I don't know, like this 205 00:11:00,880 --> 00:11:04,557 isn't fast enough. Um, I need to go I need to figure out as a coder, I need to 206 00:11:04,640 --> 00:11:06,797 figure out how to do a different approach to memory management or 207 00:11:06,880 --> 00:11:09,517 something. And you can be like, well, you know, like I, you know, I 208 00:11:09,600 --> 00:11:13,437 don't quite know how to do that. Okay, AI, let's spend 10 minutes. Teach me how 209 00:11:13,520 --> 00:11:17,437 to do this, right? Teach me what this all means, right? So, all of a sudden, 210 00:11:17,520 --> 00:11:20,077 you have this like incredibly synergistic relationship with the AI 211 00:11:20,160 --> 00:11:22,477 where it's also helping you get better at the same time as it's doing a lot of 212 00:11:22,560 --> 00:11:24,557 work for you. >> By the way, I was going to say I was a 213 00:11:24,640 --> 00:11:27,917 big Pearl uh programmer. I was an engineer for 10 years and that was my my 214 00:11:28,000 --> 00:11:30,557 language of choice. >> You do you remember I don't know when 215 00:11:30,640 --> 00:11:33,277 you were doing it but do do you remember at the at least early on do you remember 216 00:11:33,360 --> 00:11:36,957 did you ever did you ever hit this where like coders were like looking down their 217 00:11:37,040 --> 00:11:39,677 nose at you being like >> for sure for sure it's like this is so 218 00:11:39,760 --> 00:11:41,757 slow it's not going to scale what are you what are you spending all your time 219 00:11:41,840 --> 00:11:43,997 on this thing? Yeah, >> exactly. And of course, you know, and 220 00:11:44,080 --> 00:11:46,477 again, it was sort of this thing where, you know, they were they were sort of 221 00:11:46,560 --> 00:11:48,957 correct, which is at the beginning it wasn't, you know, fast enough or 222 00:11:49,040 --> 00:11:52,397 whatever. By the end, they were definitely wrong, right? Which is it got 223 00:11:52,480 --> 00:11:55,757 much better much faster and, you know, it swept the world. Uh, you know, most 224 00:11:55,840 --> 00:11:58,877 coding today happens in scripting languages. And and then, by the way, the 225 00:11:58,960 --> 00:12:01,757 people along along the way, the people who really understood the scripting 226 00:12:01,840 --> 00:12:04,637 languages and the people who understood all the lower level systems, they were 227 00:12:04,720 --> 00:12:06,877 the ones who were able to actually make the scripting languages actually work 228 00:12:06,960 --> 00:12:10,157 really well, right? And so that that was that was a great example of this kind of 229 00:12:10,240 --> 00:12:13,597 adaptation. And then and then again the result of that was you know a far higher 230 00:12:13,680 --> 00:12:15,997 number of people writing code with scripting languages than were ever 231 00:12:16,080 --> 00:12:19,280 writing code with lower level languages.