How a Top Podcaster Rides the AI Wave - Ep. 28 with Nathaniel Whittemore

[00:00] In the real world, the way that things work is that there is some very small number of people, the sort of super creative experimenters and tinkerers who spend hours and hours and hours figuring these things out just because they actually like the joy of tinkering. And then they share what works. And I think that part of why this isn't happening right now is that so many people are not sharing what they've figured out that they're doing. And a big part of that is actually policy in the corporate sector. So there was a study that recently came [00:30] of knowledge workers are using AI at work, but 78% of them are not disclosing it. They're not talking about it. They're basically smuggling AI into work. [00:51] Hey Daniel, welcome to the show. I'm so excited to be here. I'm psyched to have you. We've been trying to set this up for a long time. I love your podcast. For people who don't know, you are the host of the AI Daily Brief, a daily news and analysis podcast on AI, which is consistently one of the top ranked or maybe the top ranked AI podcasts in the technology charts. You do like 15 or 20,000 downloads an episode, which I am jealous. And you are also [01:21] fun and fast platform for learning AI. And I checked out super intelligence before the episode, and it looks awesome. So thanks for joining. Yeah, no, it's great to be here. I think the show is super fun. And I'm glad to be hanging out.

[01:37] Sweet. So, um, what we decided that we're going to do today is, um, [01:43] go through how you think about making a podcast every day with AI. So go from sort of show concept to actually having it out there in the world and what AI tools and prompts and all that kind of stuff you use to do that. So [02:00] So kind of maybe just lay out for us the background of how you think about this. [02:07] Sure. So, okay, so a couple things about this. One is a general framework for how to think about getting value out of AI right now. You and I were just talking about this, but one of the things we found, so super intelligent at this point, we've only been live, the platform has been live since April, but we have about 500 tutorials across just a huge range of topics. [02:37] go use the tools. And one of the things that people are regularly surprised by is that although some number of them are these like... [02:46] big capacity changing things like text to UI or write an app in five seconds, where a lot of people are going to get the most value in the short term is some random thing that's super basic that just saves them 20 minutes at a time on a thing they do every day. 20 minutes a day across an average work year is something like two and a half weeks that you could

[03:16] are kind of trained to think that's like they wake up one day and their job's gone. And it's not exactly playing out like that. And so if you think in these terms of where are these small efficiencies that I can win back, that in the aggregate make a big difference, then I think it allows you to start to think about all of your different processes and workflows through that lens and ask, is there a way to AI-ify that that is going to make something much easier for me? Or maybe it's not just a time thing, it makes it better because I hate writing [03:46] copy or whatever it is. I absolutely love that. Like, I just think the breathlessness, you're, you're so right about it. It's like, on the one hand, there's the AI companies and a lot of them are sort of branding themselves as like autonomous agents, like whatever, because it, it, it feels so sexy. And on the other hand, like, [04:03] Everyone else is like, it's going to ruin the economy and jobs and it's going to kill us all or whatever. And there's no one in the middle of just being like, hey, like, this is actually really useful. It's not going to, it doesn't do everything on its own yet. And so I think when a lot of people try AI for the first time, they're like, [04:19] well, this sucks. It's not, it's not like doing the thing I expect it to. And it's like, actually, no, it's that's because it's like a tool that you need to learn how to use. It's not like a just magical cure all for everything, but if you know how to use it, it's really powerful. And yeah, like, um, maybe it doesn't do your entire job for you right now, but like those 20 minute things here and there, like it changed, it really changes what work you can do and what you can get done in a day and in a year. And I think that's super powerful.

[04:46] Absolutely. And I think that we're still so at the beginning of, you know, we're at a stage in AI's development where we're basically asking everyone to go figure out how to reinvent their own workflows. And that's so not how things work in the real world. [05:16] actually like the joy of tinkering. And then they share what works. And I think that part of why this isn't happening right now is that [05:25] So many people are not sharing what they've figured out that they're doing, which is why I think shows like yours are so important. And a big part of that is actually policy in the corporate sector. So there was a study that recently came out, Microsoft and LinkedIn, that found 75% of knowledge workers are using AI at work, but 78% of them are not sharing. [05:46] disclosing it. They're not talking about it. They're basically smuggling AI into work because they don't want to be told that they're not allowed to do it anymore. Because this is the thing that's so magic. Like if you've ever, if you had to create [05:58] YouTube thumbnails, right? Before Mid Journey or Dolly or something like that. And then you get to use an image generator as part of that process. You are never, and I mean never, going back to the way that you used to do things. It would just be insane. They would have to pry Mid Journey out of my cold dead hands. And so the natural tendency then is for someone who has figured that out, is they don't want to be put in a position where someone's going to tell them that they can't do

[06:28] in terms of how these insights are flowing between people that is really sort of undermining how much benefit this stuff can have. But I think that that's breaking down a little bit now. And again, you know, shows like yours, I think are a big part of that. I think that's so interesting. I hadn't really thought of that, that people just actually are not sharing for like, you know, maybe there's, they don't want to get it taken away. Or there's also maybe like a little bit of a stigma, depending on what community you're a part of [06:58] what I, what I wanted to do about like with the show, like one of my little, one of my middle, my little bits I do is like, I think chat GPT is like sex in high school. Like, um, everybody is talking about it, but very few people are actually like doing it, you know? Um, and, uh, maybe, maybe what you're, the nuance that you're adding to this is like more people are doing it than you think. They're just not talking about it because they're sort of ashamed, you know? Um, and I think, I think both actually can be true depending on the, the, the community or the group of people [07:28] 100% that analogy actually completely holds. Yeah. I'm sort of curious, like, for you, you know, you're you're running super intelligent, you're teaching people how to use AI in a practical way. Like, where do you where are you seeing, you know, before we get into this specific podcast stuff, like, where are you seeing like the most power ups, the most level ups for people with the least amount of effort? [07:50] I think there are categories of roles are naturally the utility and use cases are a little bit more apparent right away. Digital marketing is probably the easiest example where they're already living inside different tool platforms. If you're using something like, you know, Facebook self-serve app platform or Google self-serve app platform, they're integrating AI for you into the, you know, the asset generation process.

[08:20] it's such an obvious place to use it for copy and things. We'll get into a bunch of this. So that's one area. I think... [08:28] Anything with writing, people are starting to figure out if and where a chat GPT or an LLM is valuable. Although I think actually this is another area where there's a little bit of nuance. If someone is primarily a writer or a primary part of their role is writing, they actually, I think, tend to use these tools less than someone who is not primarily a writer. But still, everyone has to do a meaningful amount of writing. [08:53] as part of their sort of, you know, especially knowledge worker type jobs. And I think a lot of where the benefit is, is actually now it's for people who that was like, [09:02] nails on a chalkboard for before they can make it faster, it's better. It's not going to replace someone who's a great writer. I mean, you guys write amazing essays, like how many of your people are using ChatGPT to rewrite those things? I would bet zero, maybe they're using it for brainstorming or something else. But you know, it's just it's just different. But again, this is another, I think, casualty of the fact that we're not talking about it enough is people think, well, I'm a writer and ChatGPT can't do it as well as me. It's like, no, it can't. But there's a ton [09:32] Huge benefit. [09:34] I think you're totally right. Like, um, I have someone on my team who he's incredible. Um, and when he joined, it was a couple of years ago, he was, it was much more junior and he speaks, he speaks great English, but like English is his second language. And you could kind of tell in his emails and in his writing that it was his second language. And the minute ChatGPT came out, like his emails became perfect. And it was like, um,

[09:55] It was amazing. And now he's used ChatGPT so much for that, that he can write better emails without having to use it anymore. [10:03] And yeah, and I also think you're right, I don't use ChatGPT to write my articles, but I do use it for many micro tasks in the process of writing my articles. Totally, yep. And that I think is super valuable. And honestly, probably I actually use Claude much more because I think Claude's a better writer, but ChatGPT is good for certain writing tasks, but... [10:24] I think you're right. It's back to that thing where people are expecting too much of it, to do too much all at once. Like, oh, write an article for me all at once. And yeah, if you're not a professional writer, having it do that could be really helpful because the quality level that you need to get to is lower. But if you're a professional writer and you're saying, please write an entire article for me, you're going to hate it. [10:54] help save those 20 minutes instead of going and looking up some complicated topic you have to summarize. You can just have ChatGPT summarize it for you and then put it into your article, which happens all the time. [11:04] 100%. I also think that this pattern of filling skills gaps rather than strictly augmenting things that you're already an expert at, [11:12] holds in a bunch of other areas as well. I don't know if you've ever experimented with any of the AI website generators or anything like that, but there's literally zero doubt that the results that you're going to get from a 22nd generation from Framer or something like that are not going to be as good as sitting down, customizing WordPress templates to be exactly what you want, inserting your own graphics. The difference is that

[11:40] They're instant. You're spending all of your time changing color schemes, tweaking copy. And so it's same sort of pattern. If you're not a web builder and you need to do something fast, they're unbelievable tools. However, they're not [11:54] changing, you know, the fact that the web developer or the web designer rather is still sort of super premium if you're looking for, you know, something great. Totally. So I feel like we framed up, you know, how AI can be valuable in general. I'd really love to go into like, in particular for your podcasting workflow, like, help me think about like how a podcast comes together for you, what that process is like, and then let's start getting [12:24] Absolutely. And so I think let's try to have this be, or the framework that I'll try to bring to this is so many people now are creating content. And so we'll try to abstract a little from just specifically, you know, podcast to a broader content creation process, because I think, you know, like I said, a huge number of people are doing that. Let me share... [12:47] My screen... [12:49] All right. So for the purpose of this, the AI Daily Brief, as you mentioned, it's a daily podcast and video. It's actually two videos on YouTube that come together. There's a headline news section, which is about five minutes on fast 30 seconds, one minute updates on whatever's happened that day or the day before. And then a more analysis type section that's more like 10 minutes or so where we go deeper on a particular topic.

[13:19] So that's the main episode. And then the headlines were things like Dell working with Elon on XAI, which raised their stock price, and some Chinese startups infiltrating the US for AI purposes, even though there's controversy there. So that's the show that I do. And because it's two YouTube videos that get turned into a podcast that then have to be promoted and shared everywhere, there's just a lot of work. And actually, this is one of [13:45] two daily podcasts that I do on top of running super intelligence. So I'm very much in the market for, [13:51] ways that make this faster. [13:54] And so, [13:56] I will say that I'm going to show both things that I actually use as well as things that one could use that for whatever reason I happen not to. And so the first area with this sort of a contrast is when I'm trying to figure out what I'm going to cover from the AI news perspective, it's informed by two things. One is I'm living on Twitter bookmarking things day in, day out. And a huge part of what I care about is not just the news itself, but the discussion around it, the meta sort of analysis of how people are responding to the news. [14:26] I think that's really what makes the show different than just any sort of reporting type of a thing. And I'm just bookmarking them throughout the day. There's no real way. There probably is a way to make that faster with AI. But for me, it's just something that's so integrated into my normal experience where I'm just bookmarking, bookmarking, bookmarking left and right. Can we see your bookmarks? Yeah. [14:48] Sure. I'm kind of curious, like, I want to understand a little bit more, like, what's your taste? Like, what's the, what's the thing that makes you go, Oh, I need to bookmark that for the show, you know?

[14:59] So sometimes it's going to be because... [15:03] it relates to a particular topic. So for example, Claude 3.5 comes out, artifacts come out. And I know instantly that is a topic that is going to be both, well, one, I'm going to make super tutorials about it. Two, I'm going to cover it on the show. And so I'm bookmarking both [15:23] Just the actual news itself, particularly from key players. So Mike Krieger is the new chief product officer at Anthropic, previously the co-founder of Instagram. And I'll tend to bookmark, you know, the announcement itself, but then also people interacting with it, right? [15:53] And so this is a whole category of things is just what's all of the discourse and discussion around a particular topic. So you can see today it's almost all. [16:03] uh almost all clawed for me a lot you know because i'm keeping track of so many different tools for super intelligent i will often just bookmark things that i want to go back to galileo's super cool text to ui tool just announced a partnership with replet that makes it easy to go from the code that galileo is producing to the actual ide so i don't know how i'm going to use that or even if i will but for me to some extent bookmarking is also a mental trigger you know it's

[16:33] and [16:33] What else is on here? [16:35] that might be elucidating. [16:38] Sometimes it's just big conversation. Like Elon is clearly talking about safe super intelligence when he says any given AI startup is doomed to become the opposite of its name, which is a pretty clever tweet. I have to say, even if you disagree, I promise. Is this the kind of thing where like you're bookmarking it and then right before you record the show, you're like scrolling back through to like write a little doc for yourself? Yeah. How do you come back to it? [17:08] works is I actually don't script it at all. And that's because, so I've done these sort of daily shows, both semi-scripted, fully scripted, and then completely unscripted. However, when I started the AI show, I decided that I was just going to do it completely unscripted. [17:23] One, I think it brings a different type of energy that I like that you're sort of rambling through it a little bit. But I also just from a pure time perspective with so many other things going on, it's like I can't start another show that's going to be two YouTube videos as well, if I don't do it this way. [17:53] the tabs on a window that I'm going to go through with Descript in the order roughly that I'm going to go through them. And so for the Ilya episode today, I went back through all of the conversation and discourse and started to bunch the commentary into some different themes. So some of the themes were contrast with OpenAI and whether there was going to be a talent rush from OpenAI to safe superintelligence. A second theme was excitement that Ilya is doing something and sort of, you

[18:23] Ilya for his contribution so far. A third theme was... [18:28] Basically skepticism that there was any sort of business model there that could justify whatever money was going into this or how much it was going to cost to do it. And so it's sort of these buckets of themes that I'm going to put there. Sometimes it's articles, sometimes it's tweets, but I'm really using the linearity of the tabs to talk over it and sort of do my structuring for me. [18:48] I love that. I think it's so cool that... [18:52] The person who is like doing the top, literally the top consistently AI podcast is like, I don't script it. I kind of like put my tabs in order and I just like free associate for 10 minutes and like that's the podcast. Like it's so good. It's amazing because all these people are out here being like, I got to like script it and it has to be perfect. And it's actually, it's a sort of common pattern. Like I was hanging out with Ali Abdaal like a month or two ago. [19:19] And he was talking about his, he's a really big YouTuber for anyone that doesn't know. And he was talking about his process. And he's experimented with every different kind of video, like from completely unscripted to completely scripted. And the thing that, first of all, he's found that there's no correlation he can find between like performance and like how edited and how scripted it is. But what he has found is that his top video is one that was completely unscripted. [19:49] like reeled it out for like five minutes and that was it. Um, and mostly he does basically what you do, which is like, he has an outline, which with like three points on it, um, your equivalent would be tabs. And then he just like free associates. And I think that that really kind of gives the, um, that, that really nice balance between, okay, like I kind of know an overall structure, but also I feel like I'm talking to you. You feel like you're talking to me and it doesn't have that,

[20:19] wooden and delivered, you know, which I think is really cool. The most important thing that I've found when it comes to... [20:29] just what the goal of a piece of content is, is I think that what elevates it is just having a little bit of a point of view or a theme that you're trying to convey or a point that you're trying to make. So, [20:44] It doesn't have to be a big, complex, radical point, but what people respond to, there's so many sources of news and just raw information. The difference is how people, how content creators contextualize that to help people think about how it should be. So for the Ilya show, just to stay on that example, because we've been talking about it, and I think it'll be familiar to a lot of your listeners. Part of the perspective that I wanted to bring was just the different ways, you know, these three or four different ways that people were talking about it. That's almost like I'm [21:14] my perspective on it with other people's. And that's what I try to do primarily. It's not a bully pulpit show for me. I want to show how the world is reacting to particular news. The one contribution that I made that I wanted to share as a framework for thinking was around this question of the business model and whether... [21:35] What did these investors think they were going to get? And my argument was basically that [21:40] My guess is that for some number of investors, they believe that the upside potential, the value of actually creating super intelligence is so enormously uncalculable if it actually is achieved, that in fact...

[21:57] wasting any amount of time between now and then on some intermediate business model is actually a huge distraction to the upside potential they're going to get, right? If someone is basically... [22:10] you know, putting odds on how likely to succeed a team is at achieving a trillion dollar outcome or a multi-trillion dollar outcome. And it would be a compelling argument, I think, to some that trying to win enterprise business between now and then is actually going to slow you down. And that you don't really care about the $3 billion that OpenAI is making, because the multiple trillions of dollars that that [22:35] super intelligence represents is the big prize. I don't know even if I believe this, I just think it's an interesting framework that I hadn't seen people sharing. And so I think that that's, you know, we try to do this with our tutorials as well. Instead of just having it be, you know, here's the stuff that you can do, we're trying to have thought about it, have experimented with the tool enough that we can offer a shortcut on some use case, right? So it's basically if we've spent [23:05] something out, we're going to give it to you in five minutes. So we're saving you that time. That's sort of the promise. And I think that all content to some extent follows this pattern of, you know, what's the, not just what's the thing that's being shared, but how am I supposed to think about it? Mm-hmm. [23:20] Yeah, that makes a lot of sense. So I know I completely derailed you from the original AI thing you were going to share. So let's come back to you're on Google News and you were sort of talking about, okay, here's how I gather the kinds of topics that I want to share on the show. We want to do Twitter bookmarks, but it seems like there's something you want to share specifically about Google News.

[23:46] Sure. So the funny thing is that this is actually contra to the entire way that search is evolving in the era of AI. But because I want comprehensiveness, for me, going back through pages and pages and pages of the day's news on Google is actually the most relevant starting point outside of those Twitter bookmarks. [24:16] I want to see that. And I think it shows a moment of where [24:20] AI will not always be the answer to all problems. A lot of times when people are searching, what they're looking for is the answer to a question where this sort of AI overview or what you can get with perplexity is exactly what you want. Sometimes you want long tail information that's just way out there that you wouldn't have access to otherwise. And actually a summarization is the enemy of that. And that's sort of where I am with this. However, there are AI tools that are valuable [24:50] has an AI feed feature that they've been experimenting with for a while now. You can create AI feeds. It's better if you actually customize it and get it down. But again, I've got this sort of weird use case where... [25:02] Really what I'm looking for is just everything about AI. So, you know, I'll do a search for artificial intelligence [25:11] intelligence. And it comes back and basically says, [25:15] There's way too much there. You shouldn't do it like that. But it's still valuable because they're going to kick up things that are sometimes deeper and more long tail than even I'm going to get from Google. So this is sort of this isn't based on like the things that you subscribe to in Feedly. It's just like the entire Internet.

[25:31] If you used Feedly the way that they imagined it, [25:34] Yes, you can. You can. I mean, you can use this tool in incredibly powerful ways to customize and hone in. Again, I am in this particular use case is voracious in a way that just a raw out of the box use of it is is actually good for me. [25:49] Got it. Okay, cool. That's really cool. I didn't know about that. I feel like there's this whole discourse about people should be able to create their own algorithms and all that kind of stuff, and Twitter should be replaced with blockchain where you have your own algorithms. But that feels very nascent, and we're all waiting for our algorithms. But this actually feels like you could do that with Feedly, but no one's talking about that for some reason. I really want to check this out. [26:14] Yeah, I think it's I think that there it's likely to me that there is a power user type of use case of this that could be extremely valuable for something not dissimilar to what I'm doing, but just that is a little bit more focused or refined where this type of thing could save you a huge amount of information on surfacing the actual things that you want to cover, you know. [26:36] Cool. Um, so as part of this sort of research process, uh, I will also shout out, [26:42] perplexity and AI research tools, I'm not sure exactly what percentage of time this would come up for me. But let's say that I'm digging into a technical topic. I'm coming at AI from a broad societal and business level, not a technical level. And like many people who have gotten into AI, specifically through the context of generative AI, there are concepts that people have known for decades at this point that get thrown in, bundled in with terms. Anytime that I'm looking at research

[27:12] to something like perplexity to [27:15] ask for background information on a particular topic or you know uh i will use perplexity sometime to remind myself of things so [27:24] A lot of times, or part of the value proposition, I think, of a daily analysis show like mine is the percentage of people who listen, who listen close to every day is actually very high. When people listen, they tend to listen a lot. It tends to be sort of integrated into their workflows. And because of that, I almost get to weave themes in and out over time that people have heard me talk about sort of over and over in different ways. [27:54] So I'll give you, for example, a really relevant thing that would come up quite a bit is Biden AI executive order. [28:07] to give the key details, right? And, you know, this is something I spent a ton of time on. I talked about it then, but it was, you know, more than six months ago now. It was about seven months ago now. And so going back and reminding myself of all of the different provisions they're in and, you know, something like perplexity, what's great about it, and this is the same promise of an AI overview type of a interface experience, is if what I need is just that quick summary and reminder, [28:37] It's actually a quite fast way to actually get to the original source material as well. So perplexity is a fairly common tool that I'll use in that very small prep period before I just let the thing rip.

[28:49] That makes a lot of sense. And I think this is actually broader than just podcasting. Like, I think people underestimate how much of any kind of content creation, whether it's podcasting or writing or whatever, is like actually just summarizing other things in order to get to the point you want to make. Like, because if you're tracking the theme of like, you know, how government and AI interact and like this Biden executive order is part of that, like, you might have a perspective overall about like, what the government should do or what the government's role should be. [29:19] to first explain the Biden executive order and you have to summarize it in a few sentences and know the intricacies of it. And like, that actually takes a lot of work to do, um, to like, make sure you're right. Even if you basically know it, just like, if you haven't thought about it in a couple of weeks or a couple of months or whatever, like you have to go back and like read all this stuff. And I think AI is like so good for doing that. And it's, it happens for me in my writing too, where like, [29:42] I'm often dealing with more complicated, either like technical topics, like how AI works, or I'm talking about like more like esoteric, like philosophical ideas that like maybe I studied in school or read about a long time ago. And in order to like frame up the discussion, like I have to summarize that stuff. And it always takes like a bunch of work, but like AI just does it for me in a like, yeah, in, in a sort of context or in a way, in a format where I can kind of just like

[30:12] so helpful. And I think people underestimate how valuable it is. Totally. And just building off of that, so much of it too is, even if I'm not going to, or one isn't going to use precisely what it is, as you're trying to figure out, [30:27] how to think about something, it's incredibly valuable to go back and get the gist of arguments. So I just asked, as we were talking as another example, what is a transformer in the context of AI and what are arguments about whether the transformer architecture can lead to AGI? It's a type of question that's resurfacing around, again, Ilya's safe superintelligence thing. Are we on a path? Some of the responses were the path that people are exploring fundamentally is not going to lead to superintelligence. We need something totally different. That's why I'm [30:57] Going back and getting the background on what those arguments are and where they come from and who's on what side is something that previously was enormously time consuming. You have to be a wizard and sift through so much on Google, whereas now it's just it's so hyper compressed. [31:13] That makes sense. Yeah, totally. So I guess like once, once you're, once you're kind of, you've done your research, you kind of like have your, have your set of things from perplexity, from Twitter, from Google, like what's, what's your next step? [31:27] So as I mentioned, for me at that point, I'm just off. I set things up in my tabs and I let it rip. But I think that it's valuable here again as we're trying to abstract this into a broader set of people. This is the phase at which someone might want help.

[31:42] architecting or scripting, right? So pick your LLM, whether it's Claude or whether it's ChatGPT or whatever works best for you. And there's a couple different ways that I can see people using this. One would be, [31:54] outlines, right? So you don't need it to script everything for you, but I'm going to create a show about, you know, that same Transformer architecture. Let's actually do this, where I'll pull Perplexity back up and give it a try. Um... [32:07] I'll use the same prompt. [32:10] And I'll say, I'm doing a podcast. [32:14] about this. [32:17] Thank you. [32:18] outline in... [32:20] four sections. [32:23] what I should talk about, right? Whatever it is, you know, uh, [32:30] this could be a way that you could figure out sort of roughly how to, how to architect your show. Again, this is not necessarily just strict scripting. This is a way to think about how can I, you know, frame everything. How can I sort of bring, bring some structure to this? I think stuff like this could be, you know, incredibly valuable. You could obviously also then go from here to actual scripting, right? If that was the, the approach for you. Um, you know, I think where [33:00] It's easier to not script when you allow yourself to be rambly. [33:04] Because part of the way that humans work is you... [33:09] talk enough to figure out what you were trying to say in the first place, and then you eventually get to it. If you're trying to be precise, right? If you have a limited time window, if you have 30 seconds to make your point or 60 seconds to make your point, that's where compressing

[33:20] what you're doing into something that is more scripted can be really valuable. And so I think LLMs are an obvious tool for that. I guess one more thing to flag, and I'm interested in your experience with this. I have been spending a bunch of time [33:35] exploring how good LLMs are at imitating my writing style. And I would say that I give them a [33:44] D plus to C minus so far, right? It is not a thing that I think actually works. I've, you know, I've tried with Gemini loading up a bunch of my stuff. I've tried with Claude. I did a custom GPT. And what I will say is that, [34:02] It is distinctly more like me than it is... [34:06] just the raw, normal, you know, ChatGPT basis sounding, right? So it's not that there's nothing here. It's just that if you're actually looking to replace your own voice, it's very, I think at this stage, it's very unlikely that you're going to be satisfied with the results. Yeah, I have a slightly different perspective, but in a limited way. So I actually have found that Claude, very particularly Claude, not ChatGPT, not Gemini, is good at like replicating [34:36] for specific kinds of writing tasks. And I think you should be skeptical of that because like you said, mostly LMs are not good at this. [34:47] But, uh, but I, I found that, um, if you are doing a repeat writing tasks where you're taking a piece of content and transforming it from one form to another. So like an example for me is like, I'm constantly, uh, taking a podcast I've done and taking the transcript and trying to figure out how to tweet the, tweet the episode out. So I need to turn the transcript into a tweet. Um, yeah.

[35:12] Uh, [35:13] If I have a bunch of examples of having done that in the past, where I have the transcript and then the tweet that came out of it, and I feed that to Claude along with a little bit of a style guide... [35:24] And it's actually really, really good at like getting pretty close to my voice and doing and picking out the interesting thing and ordering it in the way that I would order it and like all that kind of stuff, which is really, really hard to do. And so you just teed me up perfectly because we built this tool called Spiral that we launched like two days ago. It's been going wild, like over the last couple of days, which is really, really fun. We have like 2000 signups in the first two days, something like that. And it's basically based on this insight. [35:54] And then I just like built the first version of it, um, and started using it and shared it with my team. And they were like, wow, this actually works really well. So we just released it. And, um, I think it's like a, uh, [36:05] for that narrow-ish use case, [36:09] It's like kind of stunning how good it is. Awesome. So this is actually a perfect segue and reinforces a lot of what we talked about at the beginning, that if we're talking about sort of the gap between people's expectations and reality, general purpose, hey, just imitate my writing. [36:24] underwhelming, right? You found this very specific type of use case where it worked really, really well. And then you actually institutionalized that or built that into a specific kind of purpose-built tool that... [36:38] can do that type of a thing over and over. And this is actually a pattern that we're seeing at Super Intelligent quite a bit, which is that there was this notion, the first wave of startups that came out right after ChatGPT, you know, very pejoratively were called, you know, ChatGPT rappers and things like that. And what's interesting is that I think that you're seeing now is that

[37:01] And some number of those startups weren't ever actually chat GPT wrappers per se. Instead, what they were, were customizations for a specific use case that people have over and over and over again, that need a different either specification or sort of a customization of the model, or they need a different user experience to surround it, right? [37:31] from many different models, but really it's a triumph of designing for a specific type of use case and creating a great user experience around it, right? Rather than it just being this random chat window. Artifacts, which just came out, is basically just a different user experience that says, hey, actually, if we separated the output field from the instruction field, it would probably be a lot easier to help people use this tool. And so far, I mean, we're hours in, but I think that [38:01] That's pretty validated pretty fast. Spiral to me is a great example of this where it's like, there's a thing that a lot of people have to do over and over and over again, that in sort of Gen 0 or Gen 1 of LLMs, you're hacking together with custom GPTs, or you're just, you know, you've got prompts that you save in Notion that you copy paste every time, that now there's a purpose built tool for that. And I think why people are responding it so well is that there's a lot of people who have that same use case that you did, that it just cut out all that sort of stuff.

[38:31] to become a beloved product because of that. [38:33] Thank you. I really appreciate that. I hope so. And I think, yeah, you're totally like hitting on this thesis I have, which is like, if I think about what the best analog for AI in general and chat GPT is in terms of like the history of software, I think a really good analog is Excel. [38:48] Um, and, uh, in the same, like the, the sort of overlap is Excel is like really, uh, [38:55] easy to get started. Anyone can, anyone can start by just like filling in a cell, but like you can do things of like almost unlimited complexity with it. It just like, it progressively reveals it's like, it's complexity and you can use it at any level. Um, [39:08] And I think it taught people a new paradigm for how to think about using computers, like when it came out like 30 years ago. [39:15] And what's interesting is that Excel, like it took over the market and then it was like sort of progressively unbundled into like... [39:23] all of the SaaS tools we see today. And I think when ChatGPT came out, everyone tried to build ChatGPT wrappers, the pejorative ChatGPT wrappers. And I think many of them didn't work because ChatGPT hadn't had enough time for people to use it and get it to even know that they might want something else. And I think we're just at the point where enough people have been using ChatGPT and other tools like it to be like, oh, I have this specific workflow where you can unbundle it a

[39:53] bundle it into things like Spiral because people know what, what it is and why they'd want it. Whereas like if we'd launched Spiral a year ago, I don't think enough people would know. And so that's sort of the opportunity I see for these types of tools is like, as they get more, um, [40:08] more distributed and more and more people like learn this paradigm of computing, which is a very different paradigm, there will be more opportunities to kind of like spin out the more complicated workflows that people develop for their specific like use cases and turn them into new products. [40:23] I think that the other, at the risk of getting too off track here, the other thing is that a lot of times when... [40:30] companies or a category of companies is being referred to pejoratively, you have to understand the context of who is being pejorative about it, right? And so the ChachiPT wrapper thing is pejorative specifically in the context of whether it's venture backable, but it's only a small slice of businesses in the world that are actually venture backable because the business model is predicated on not 10X returns, but 100,000X returns. And there's just a very small [41:00] Thank you. [41:01] making more viable non-venture-backed models for even more sophisticated products, right? And so it's kind of like... [41:08] The AI is solving the problem that's creating opportunities for builders on top of AI, which is a pretty cool thing. [41:14] It is super cool. I mean, yeah, I want to get back to your workflow in a second, but we built Spiral end-to-end in two months. I built the first version in two days with AI, and it's like...

[41:26] It's unbelievable how much easier it is, how much faster it is. We probably spent like maybe 10K total to build it. You can build really amazing products and businesses really quickly with this stuff. So it's super fun. [41:38] Yeah, I think too, that there is a lot of insight in your point that we are still so early in our experimentation and our explorations of how to use these things. I don't know if you saw this tool that was just announced this morning called Auto, but basically the way that it looks like it works is it's a research tool, but it uses tables instead of a chat interface. And so let's say that you're researching NVIDIA's corporate results or something like that. What are patterns in NVIDIA's corporate results? It's going to create an agent for each [42:08] column basically in the table that then goes and fills out that information. You can give it sources in the same way that you would give ChatGPT sources. And I actually think it's fascinating. I haven't had a chance to play around with it yet, but it's notable to me that [42:23] Any sort of data analysis stuff is actually, I think, a little lagging right now. People have been so enamored of the chat-based interfaces that the Excel type of interfaces have been left behind a little bit. And, you know, as someone who interacts with workplace enterprise-y type users every day, if people start figuring out stuff that really works in formats like Excel and tables, I think it could take off. [42:46] That's amazing. Yeah, I did see that. And I need to check it out more because it looks it looks really cool. And it's I think it's a great example of like, that new paradigm of computing that we're just sort of like peeling the layers of the onion back.

[42:58] So, so we, so to get back to your, your sort of workflow, we, we've basically gone through some of the research phase we've gone through, um, if you wanted to do some outlining, like how you would do that. Um, what's, what's the sort of next step in the process? Next step is the big one. It's a recording, right? And there are, of course, a million different ways to do this. The, the tool that I use every day is to script. [43:28] I'm selecting a part of the screen that I'm recording, that set of tabs that I've set up, and my little floating head is going to be down there in the bottom, or I can do a direct on shot. So for me, I have a very specific formula. I do a direct on head shot that starts the thing. And then I sort of do the floating head screen over thing for the rest of it. And Descript is sort of a two-part thing. It's a recording tool. So that's one part of it, but it's also an editing tool. And so Descript was one of the first tools to really have the [43:58] video editing. So it's going to create a transcript of what you create and allow you to highlight parts of the transcript, delete them and do it instead of the sort of timeline based editing that's traditional in video editing. This makes it massively more accessible for people who haven't used Adobe Premiere Pro or things like that before. And actually, when I started the AI Daily Brief, for a little while, I was editing it myself because I just wanted to learn how to use this

[44:28] that I hired in the future, you know, crapped out because it's a daily show, I could just jump in. And, and so, you know, Descript or, you know, there's a bunch of things like it now, I think that this paradigm of text based editing has found its way into basically every tool at this point, make the video creation, you know, capture an editing process, I think a lot faster than it used to be. [44:47] Totally. It's I love Descript. It's so smart. I mean, we use Riverside for the show, but I think I think Descript is also also really incredible. I just have to say, like, if you can edit text, you can make videos. It's such a good headline. It just reminds me of that dodgeball quote. Like, if you can dodge a wrench, you can dodge a ball. Like, I wonder I wonder if they're referencing dodgeball. The guy that started Descript is a funny dude. His name is Andrew Mason. He started Groupon and he is a quirky guy. [45:13] A quirky MF-er relative to the world of startup CEOs, I will say. He truly, truly is. I think he wrote a really funny resignation announcement from Groupon. So if anyone's looking for good corporate humor, definitely go check that out. But yeah, I think Descript is great. I love the AI text editing to video pipeline they've built. And also... [45:37] They just have all these little things that make it nice. They'll just get rid of your ums and ahs and do a bunch of auto-editing stuff that's really helpful. [45:45] Yeah, two other AI features that I wanted to call out just for completeness. To your point, though, the ums and ahs, I think is probably the most used of any of them, the filler words, they call it. And it's really good. And I have found that it's actually, it tends not to over edit those. The one challenge is like,

[46:04] Because, you know, people say if like is your particular tick, sometimes their likes are important because you're actually talking about someone liking something. But in general, the ums, ahs, all those things, it does a really great job on. The other one that I've been experimenting with a little bit more is their eye contact tool. So with Superintelligent, we have a variety, we have a bunch of different content creators who are creating tutorials. And most of them don't do scripting in general. [46:34] that I have. It's an outline into a video. But they will often do a start part, kind of a kickoff line or two that they do script because they know exactly what they want to say. And so if they haven't got like a teleprompter set up, you can see that someone's reading something and it's a very distracting thing. And so we've played around with eye contact, which is basically a post [47:04] And what I would say is when you are, when you're the only thing in, in camera, right? If it's just the full video is you, the eye contact tool can be a little zombie-ish, just, it can be a little aggressive. However, if you are doing like in the context of a floating head, right, where you're a small little part of the corner, it's gangbusters. It is so good. So if you're doing something that's semi, you know, that's, that's scripted where you are doing the little floating head thing,

[47:34] the eye contact tool as an approach, as opposed to, you know, like a teleprompter type setup. That's really interesting, because I literally just bought a teleprompter for that exact reason, because like, I'm, I'm now doing a lot more like ad reads, and I'm doing more like scripted, you know, videos or whatever. And just even for this podcast, like I can look directly at you, because you're in my teleprompter right now. And I've been meaning to try little some of those eye contact AI tools, because I think they're descript has it, there are a couple other [48:04] It works, but only if you're not, if you're like, it's the, you're the only thing on the screen. Yeah, that's, that's, that's a really interesting little tip. [48:13] Telepromp is a great example of, you know, all of these little lines that people are figuring out that will evolve over time. It's highly likely that in two years... [48:21] It'll be as good as any sort of teleprompting. But right now, teleprompting is way better for, you know, if you want to fully maximize how good it is, you know. How does it work, though, if you're like kind of like looking like you're physically looking down, like if it fixes your eyes so you're looking at the camera like... [48:36] The more that you're bopping around, the more that you're looking down, the harder it is, right? So if you're reading, you know, something that's down on the ground where your whole head is tilted, that's going to be comparatively bad. Whereas if it's like, the way that most people do this is they, you know, they set up their thing just off the side. So it's kind of like, [48:52] resources, sign in, sign up, and you can just see that they're not looking directly at cam. Yeah. Okay. That makes sense. Cool. Yeah. Descript is awesome. [48:59] Okay, so Descript, we've edited the thing, or we've taken the video, we've edited the thing, and now we are back in doing all of the next set of stuff. And so we're back to LLMs, right? Because, you know, we want to rip transcripts out, maybe we have a transcript from Descript, but, you know, you just articulated the perfect, you know, thing that you would use like a spiral for previously a ChatGPT or something like it, to, you know, go from that transcript to potential titles,

[49:29] you know, social media tweets. And there are tons of different tools for each different, you know, piece of this, right? You could do, you know, there are SEO.ai is one of these things that's sort of powered by all those LLMs that you would work with, but is hyper-focused on just thinking about SEO content, right? So if you're creating a companion blog post, this is going to be a really good tool for getting it to rank, right? Like, you know, suggesting key terms that [49:59] in the podcast itself, but would be good to include that. There's tools like Hoppy Copy, which is totally focused on written copy. I think their specialization, their er specialization, basically the thing that they started with is email newsletters, but they also have social post copy, LinkedIn, Twitter, et cetera. And again, these are all... [50:21] purpose-built tools that are exploring, you know, really, really focused use cases or applications of LLMs. If you're comfortable inside ChatGPT, if you're comfortable inside Claude, a lot of these things, you know, you might build a process that does this for you. It's kind of just, again, you know, everyone is now figuring out which of these things work even better for them, you know? And so it may be that if, if at LLM saves you 40 minutes of this kind of writing time, something like [50:51] So, you know, I think that the writing that happens after [50:56] any piece of content comes out is one of the best areas for this, even if you are a good writer, just because it's so exhausting from a sheer human standpoint to produce something and then have to go back, live inside that world again. Remember? I mean, this is probably a little specific to me, but I will often, by the time I get

[51:18] uh, the, a video edited back from my editors or the pod, the final podcast, I'll have to go read the transcript to even remember exactly what I was talking about, because when it's done, I'm onto the next thing. And even though it's only six or seven hours later or whatever is three hours later, it's literally, you know, like dragging myself back into the world of that piece of content is, is painful. And so, you know, I like writing. I think I'm a good writer. I like, you know, thinking about titles and stuff. I still think that these, this area is one where almost everyone [51:48] is going to find benefits from using some version of these writing tools to help with the copy that comes out. [51:53] I 100% agree. I mean, you're, you're speaking my language, obviously, because I, because I built spiral for that exact reason. I was like, I have to spend all this time, like I record a podcast, and then I get an edit back a couple days later, I have to spend all this time, like, watching it and then being like, okay, what was the main idea? Like, what do you know, what I think is interesting, or actually, I had a ghost, I have a ghostwriter who helps me with this. And she has to do that. And that takes her a lot of time. And then she sends it to me. And sometimes like, I don't like it. So then I have to do it. And then it just the whole thing is like, a mess. And, um, [52:22] And it's also, it's both a mess and it's, um, and it's hard work and it's skilled work. Like it's, it's actually like not anyone can do it. Like you, it's hard to do. Um, but it's like simultaneously hard, but also a little bit brainless. Like you're kind of like doing rote work that takes a lot of skill to do. Like that combination is sort of rare. Um, and, uh, and so that's, that's why I, that's why I wanted, that's why I wanted to make Spiral.

[52:52] I'm curious, like HoppyCopy, now we're thinking about competitive research for me. So I'm really interested, like, how does it actually work? Can we do like a, I don't know, an email campaign or like a social post or something like that? Like, what's going on there? [53:08] Sure. Let's do, let's see if, uh, if we can find anything that we can do with that's still free. [53:18] Um, no. [53:20] We don't. [53:23] It looks like it. [53:24] this is the number one thing that we're finding with, with super, this is sort of as an aside, um, [53:31] On the one hand, I think that AI tools are training people to pay for software again. There's no, we'll grow at all costs and then not charge you. Every tool is charging. The problem is that there's only so many $20 or $30 a month subscriptions that you can do before you just run out of time. And we're seeing that fatigue happen with super intelligent users right now, where one of our most in-demand things is, you can see it right on the front page, [54:01] playlist because that, you know, people want to know tools that have a sufficient amount, like enough free usage that they can actually get, get value out of them. Yeah, that, that makes sense. And that's honestly what we're doing with every, like when you subscribe to every, you get every, you get spiral and you get Lex, their AI document writer app, which is so it's not free, but like you get a bunch of things bundled together. So you're not like, you know, shelling out for a bunch of different subscriptions, but yeah, that's, that's makes a lot of sense. I think it's hard. Listen, I think it's a,

[54:31] I think it's a better environment net net for things to charge enough money that they can be sustainable businesses. And then to let chips fall where they may have, like people have to try them and they stick with the ones that work and they don't with the ones that don't. I think the biggest barrier is the trying is what we're finding. You know, so we're having conversations with lots of folks around, you know, hey, we'll make some of our, you know, the content that we're creating about you free in exchange for discount codes for our users. And, you know, that that's sort of, you know, bargaining or whatever. That makes sense. [55:01] really cool okay yeah so so so we can't do we unfortunately uh can't do hop is it called hoppy copy hoppy copy yeah you can't do hoppy copy because they have a paywall um but uh but yeah curious like uh what's next uh if uh if uh if we don't want to pay for hoppy copy where do you go next [55:20] So next is my favorite part, just from a sheer personal standpoint. So everyone who's into AI now had whatever conversion experience they had, right? There's a sort of a moment where they were like, okay, well, that's going to change everything. And it's going to change about how I work or what it is. And so for me, it was actually not ChatGPT, it was image generators. And so the first place that I... [55:46] started to see this was my brother-in-law had just finished writing a fantasy novel and it had been his goal for like a couple of years. He spent a ton of time working on it. And he sent me a [55:57] off the wall cool, like just so cool. And this was probably December 2022. Um, and, um,

[56:03] He had been using an implementation of stable diffusion. That was a discord server called unstable diffusion where it's uncensored and you could do whatever. It's a very chaotic discord server for anyone who goes and checks it out. If it's, if it's even still there. And so he, [56:17] I thought that was amazing because the stuff that he was creating, you know, I was I instantly started pitching him on starting a consultancy to go help other people do that right now. I was like, you have to do this. Like people, you know, he decided he wanted to keep writing, whatever. But so that was sort of step one. And then step two, I started playing with Mid Journey and I found myself. [56:36] I would be on a plane, you know, and instead of turning on the internet, I would just create or like turn on, you know, start watching a video, I would just endlessly create, you know, I can probably find them, you know, uh, [56:52] you know, the, or that's not in mine, hold on. You know, Hemingway at the, you know, at Le Dume I Go in Paris in the 1920s, you know, and these random nostalgic images of, you know, Paris from whatever, or California in the 60s, or whatever it was, like, just for the sheer fun of it. I think that for me... [57:14] Image generation is very discreet because it's the thing that I found that most makes you feel like a wizard when you use it. You know, this capacity that you never had before that you can all of a sudden create things. So I actually, I just love using image generators. I spent a ton of time doing it just for fun. [57:30] And so when it comes to the creation process of any piece of content, you always are going to have imagery associated with it. You're always going to have thumbnails. And so if you look back through my mid-journey, huge parts of it are me experimenting with different images that are going to turn into covers for episodes. So, you know, you can see I'm trying to get at, you know, a computer reflected in someone's eye.

[58:00] was for a super intelligent YouTube cover. You know, it was like, I try this and didn't quite work. So I tried, you know, tweak the stylization settings, blah, blah, blah, blah, blah. And if you just scroll back through, I would say probably 90% of my mid journey is me experimenting with... [58:18] covers for, for, for, for thumbnails for episodes. Yeah. And what have you learned about like what prompts work and how to get a good cover or thumbnail from MidJourney? [58:31] A couple of different things. One big, huge thing that I don't think is talked about enough is the more that you are able or in a position to let AI work. [58:45] Wander. [58:47] I think the better the result is going to be. At this stage, it's still hard to get something as super precise as your imagination can make it, right? So it's like, the more that you know exactly what you want, the harder it is to get that thing, right? The more that your mind's eye has figured out, you know, the harder it is. Whereas if you're a little bit more open to [59:08] a vibe that you're trying to capture. I think that's what I find like mid journey is really, really good for explorations of. And so you start to experiment with words that that connect you to vibe. So, you know, uh, [59:22] Describing the style, illustration, you know, illustration is different than line drawing is different than. [59:30] You know, cartoon is different than, you know, a specific type of cartoon like Pixar style or something like that. So, you know, using those words that sort of get you in the style is going to be super valuable.

[59:43] especially again, if you can like be broad, like if you look at a lot of my experimentations, they're not super long prompts. Now, this is particularly based on the use case here. With a, with a thumbnail for a YouTube video, I have a ton of openness and flexibility for what I'm doing. You know, there's the brand guidelines for me are much more about the way that elements are brought together on a YouTube thumbnail than exactly what the art looks like, you know, [1:00:13] thumbnail. So that's a particular thing. If you have a more precise type of brand approach, dialing in and figuring out what's going to work or what things come back to being valuable is super important. I guess I can give you an example of something where I did try to dial in a particular style, different use case. So the only game that I've ever loved is Magic the Gathering. [1:00:43] format called cube, where you basically bring together cards from all the different sets from all time, and you kind of construct your own set that you then go draft with friends. And at some point, a couple of years ago, I started actually just designing like my own cards that were missing. And a lot of it was based on, um, uh, I, I started a project to create cubes for each season of the year. I really like seasonality and I love fall falls, my favorite season. And so I wanted something

[1:01:13] Americana themed set. And so Magic has a lot of cards that are like horror inspired, like Gothic horror and things like that. But they don't have a lot of things that are reminiscent of the Pilgrim Times and the Salem Witch Trials. And that's the vibe that I was really trying to capture for these custom cards. And there's a million custom card makers on the internet for Magic Cards. It's a hugely popular game and tons of people like making their own custom cards, but you still have to insert art for all of these things. [1:01:43] And so give us whiplash and try to get to some of these things. [1:01:51] But I wanted to dial in a style for this. And so the most important things when I was really trying to dial in a style is reference points that you can come back to. So I experimented a lot with certain phrases. Let me see if I can just find. So... [1:02:13] I experimented with a bunch of different reference points for this. Some of them were stylistic. So I tried 1700s painting. So like a time and a, you know, a style like oil painting. I tried, you know, a, [1:02:31] landscape painting, Hudson River School, basically trying to figure out something that worked. One of the things that works really well is if you have a particular artist, you can really ground a style. So Winslow Homer was one that I used to create sort of a consistent style that looked similar across a lot of this different art. And again, I was trying to create

[1:02:51] you know, images that worked together so that the feel was all similar across, you know, we've got this bucolic image of, of someone, you know, planting, uh, or, or, you know, in harvest time. But I also wanted that to work with, you know, some scary image of this weird guy. And I, and I think that, you know, by, by referencing a particular style, a particular artist, it's one of the ways that, that you can get, you know, more consistency, but consistency in, in image generation, we could have a whole, whole separate conversation on. [1:03:21] I think that's really interesting. And I just like that point you made earlier about one of the reasons why you like image generation so much is because it feels like a magic power that you just didn't have before. And I feel like, you know, we think a lot about AI as this thing that speeds up things that you already do. But and that ties back to your earlier point where it's like this, you love this because you couldn't do this before. Same thing for writing where it's like it's most useful for writers who don't are not professional writers. And I just like it just. [1:03:49] you [1:03:50] It's so beautiful that there's this like flowering of human creativity going on where it's like now we can make art and we can code and we can like do all this stuff that like... [1:03:58] All we had to do is like prompt it now instead of like spending years and years trying to trying to get good at it or whatever. And it's. [1:04:04] That's not to say that those skills are not valuable anymore, but it is to say that millions of people don't have to start at square zero anymore. They can start on first base a little bit and get the taste of what it's like to be good at this before they actually have any skill. And I think that's so cool. I'm with you. I...

[1:04:23] completely understand why in so many places there's so much backlash to this stuff but i you know i am [1:04:31] ridiculously optimistic about it. And I'm optimistic for a couple of different reasons. One is that I think net net, [1:04:39] more people being able to create more stuff, having the tools of creation is just better, right? Like it just, it just is, you know, denying the gatekeeping access to creation does not [1:04:52] make the people who can create it better. There's always going to be a spectrum of what people can do. So that's one thing. Second, when it comes to art, I very much understand why people are, you know, we have a whole set of societal conversations to have around the ethics of training and what that looks like. And it's going to be both a society conversation and it's going to be a legal conversation. And frankly, different legal systems are going to come to different answers about this. But I think that what I would say to an artist if they were worried is that [1:05:19] Ultimately, it's still going to be human artists who create the styles and approaches that people [1:05:27] riff off of and templatize. You know, it's like the... I don't believe that the relevance of human creatives goes away. I think that they become benchmark and reference points where people get to go do fan fiction for their favorite artists, basically. I think that it's going to, if anything, increase that. And the last thing is that [1:05:48] I just think in general, to the point that you were just making, [1:05:52] It would be absolutely insane to me if the way that all this played out is that...

[1:05:57] So it's pretty binary. Either we can do and create the same amount of stuff we're creating and doing now, just with less time and less money spent on it. [1:06:08] That's one possible outcome. Or we can fill in all of that time and resources just creating more stuff. And it seems very obvious to me if you look at the entire pattern of human existence, that we're just going to create more stuff. If code takes one-tenth of the time, we're not going to have one-tenth of the coders. We're going to code 10 times as much stuff. That's just, that's the way markets work. That's the way capitalism works. It's just the way that humans work. We just make more. Our appetites are voracious for more stuff. And so that doesn't [1:06:38] there'll be more good stuff proportionally. It just means that there's going to be more of everything and that'll create its own challenges. But... [1:06:45] I don't know. I think that it's hard from where we're sitting now to sort of fully project out into those futures. But I think it's just going to be very cool. It's going to be interesting. It's going to be dynamic. It's going to be exploratory. And I think that we will find a dynamic, interesting, more creative world on the other side of it. I'm 100% with you. I have exactly the same viewpoint. We will just make more and want [1:07:15] arming people with more creative powers is going to be better. Obviously, there's lots of societal conversations to have. I think we need new ethics for this kind of thing about what's acceptable and what's not. I think like there are certain people we need to take care of, like all that kind of stuff. But like generally, I think it's going to be really good and really fun. And I am definitely feeling that energy from this conversation. It's been like such a pleasure to get to talk to you

[1:07:45] and hear your podcast or check out your company? Where can they find you? Superintelligent is at besuper.ai. And that's basically the handle everywhere. So it's besuper underscore AI on Twitter, besuperai on Instagram and on YouTube. And then the name of the podcast is the AI Daily Brief. It's also at AI Daily Brief, basically everywhere, YouTube, Instagram, [1:08:15] everywhere. So any of those places is a good place to find me. Amazing. Thank you so much. [1:08:21] Yeah, Dan, it's been awesome to be here. Keep building, keep doing this podcast, and I'll be excited to come back in a year and see all the stuff that you've built. [1:08:51] about ChatGPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat. [1:08:59] craving for more. It's not just a show. It's a journey into the future with Dan Shipper as the captain of the spaceship. [1:09:07] So do yourself a favor, hit like, smash subscribe, and strap in for the ride of your life. [1:09:12] And now, without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.