How to Run a Profitable One-person Internet Business Using AI - Ep. 14 with Ben Tossell

[00:00] One thing you're really good at is starting these one man profitable internet businesses that are like sneakily big. The Glassdoor is basically an anonymous site for people to leave a review on your employer. So I was like, OK, well, where did that all come from? How did that start? How do they start getting people to write reviews on a site like that? How did Glassdoor get reviews on the site initially? Do they run any incentives? So I was looking at that kind of thing. So things like that. I was like, yeah, it's just an interesting way to start exploring an idea and where it's going to go. [00:30] and how it works, how it changes over time. The thing I'm seeing you do is when you think about a company and a company that makes a product, the thing that you can see on the internet is sort of like the tip of this iceberg. If you study the tip pretty closely, you can tell a lot of things about what's underneath the water level that you might not be able to see. [00:57] So [00:58] Ben, welcome to the show. [01:00] Thank you for having me. It's great to have you. We've been friends for a while. For people who don't know, you run the Ben's Bytes newsletter, which is a daily AI newsletter that I read every day. I love. I think it's one of the best, if not the best, daily AI newsletters in the space. You also invest in AI companies, and you are an exited founder. So you previously sold a company to Zapier. So you have a ton of experience as a founder, and I think you're also just great at the content media thing.

[01:30] and it's really fun to have you on the show. [01:32] I appreciate the kind words and yeah, it was kind of an accidental, [01:36] content media. [01:37] founder's journey but yeah um that's what i am [01:41] Yeah, I just sort of remember, I think this was like a year ago, but I just started seeing this guy. Anytime someone would like launch an AI demo, there was this guy that would just like pop up underneath any one of their projects being like, hey, I just added this to like my Ben's Bytes newsletter, you should subscribe. And I was like, who is that guy? [02:11] at Product Hunt. [02:13] And I used to work at Product Hunt before I went and launched Makepad. [02:17] It was just like, hey, yeah, I'll put this. You should post this on Product Hunt. And then it must have been in my brain somewhere. [02:23] And I thought... [02:24] I then started realising that if... [02:26] Sundar from Google is posting something about the Google AI thing. [02:31] If I could be quick enough... [02:32] to just put my link underneath, it was actually a really good way to start, like, getting subscribers and... [02:39] you're reaching the right audience in the right place. [02:42] So that was a little hack that I didn't intentionally mean to be a hack, but I [02:47] it worked out well. And everyone else started doing it. I stopped doing it. But yeah. [02:54] That's amazing. Yeah. I'm curious, like, [02:56] just high level, I feel like a year ago was this...

[03:01] big hype wave for AI and, [03:04] I think you and me both rode that to a certain extent and got a lot of traffic and a lot of [03:10] I don't know, just a lot of good stuff out of that wave. And I think that that has started to dissipate, or at least it's changed. And we're starting to enter the like, it's not just AI, any, it's not just like you can, you can tweet, like some demo that you did with GPT-3 and it'll just get 1000 likes, like immediately. We're less in the fancy demo hype phase and more in the like, [03:35] I'm curious how things have changed for you or what you're thinking about right now in this current era of AI. [03:42] Yeah, I mean, on the business side, as a daily AI newsletter, I mean, I started it because there weren't any others. And at the time, this was like October 1st. [03:52] 22 it was pre-chat gbt so it was definitely early um [03:58] And then it was just riding that. [04:00] that wave that everyone else was on and seeing anything and covering everything. I want to know everything that's launched and all the new stuff every single day. [04:08] And then as we've come to sort of now, 2024, [04:12] Even my thinking of... [04:15] It is exhausting to get it out there. It's exhausting for someone who does this as a business, [04:21] to keep up with. [04:23] What's the appetite really like for everyone else? [04:26] consuming this stuff as well. [04:28] where... [04:29] like chat with your PDF product

[04:32] Number 57... [04:34] is a new thing that on Product Hemp or Hacker News or whatever, [04:38] Are we covering that again? Are we doing that kind of thing again? So there's a lot of the same stuff. So we, yeah, we've, we've sort of thinking about that internally. And, uh, [04:47] We launched Ben's Bites Pro in December. [04:50] where I speak to a sort of similar actually to what you're doing, I guess, where I chat to businesses and CEOs and things of, [04:57] how they are using AI in their business and like changing their organization and rolling out on products and stuff. Cause I just think there's not, [05:05] that much out there there's no like playbook on companies building with ai [05:10] And I think it's really interesting. So... [05:12] Yeah, we started doing that and getting some really interesting conversations. But... [05:17] Yeah, I don't know what the future holds with [05:20] all of the daily stuff like this just we always joked about the it being just this massive fire hose um [05:27] It still is. And like... [05:30] Are people's appetites changing towards... [05:33] I actually want to know how to use this thing. I don't want to just tell me a new tool every single day. [05:38] I feel that. I mean, I just love how bored you sounded talking about the next PDF tool, number 57. I mean, this still goes back to my product in the days. I was a community manager. It was my job to let companies be on the homepage and support their launches and also get in the comments and start people...

[06:04] like talking about it. [06:06] And then... [06:07] I got to a point where I must have just, it was probably a similar timeframe where I was like, [06:11] This is another dating app. This is another weather app. Why do we need this? What's the point of this? There are so many others... [06:18] Um, [06:19] And maybe I haven't. [06:21] changed all that much since then, I guess. [06:24] But I think it's just, I like seeing new things. I like seeing things that are different, or there's a reason behind doing this other than [06:32] Oh, we've just done the same kind of thing as everyone else, but it's like slightly different because of this one thing. But equally... [06:38] You see all these PDF products. There's plenty of them. [06:42] You can do it in ChatGBT.com. [06:44] And then there's companies like PDF AI making, I don't know, 200k MRR, [06:49] from just that focusing on that one thing so [06:53] it's definitely like, [06:54] a bias between I'm seeing all of this stuff. Other people are seeing maybe that one ad for that one tool and signing up and using it and finding it useful. Um, [07:03] So yeah, that's how I'm [07:05] That's why I'm biased and jaded by it, I guess. [07:09] No, that makes perfect sense. I mean, I think we're both sort of in pursuit of what is genuinely interesting. And I think we both have moved from any new AI demo is interesting into... [07:23] Like, how are people actually using it? And I think that's definitely the concept of this show is there's so much... [07:30] um, [07:31] So latent hype or latent energy around ChatGPT, like people just feel like they should be using it, but not enough people actually know how because it's such a general tool and there's so many different ways you can use it. And even just remembering to use it is like kind of hard.

[07:45] And so, yeah, I feel like we're sort of on the same wavelength there, like giving people the actual... [07:53] the real ways that you use it or I use it or lots of other smart people use it is the most valuable thing you can do at this point in the AI wave. [08:01] Yeah, and I think that [08:02] So many people come in with a question, get an answer, and they think that's what ChatGBT is. And I still do this today where I will do that. [08:12] multiple times a day and think, oh, I didn't do all these other tips and tricks and ways I can get it sort of a better outcome. Um, [08:20] Sometimes you don't need that, but I think... [08:22] knowing that you have that there. [08:24] And then... [08:25] after sort of practicing... [08:27] unintentionally some of these [08:30] tricks or whatever you'd call them [08:32] over time you start recognizing that, okay, that's a good way to get a good... [08:36] response from something. [08:39] I think I've learned some from this podcast. I think Sahil showed just... [08:44] regenerating a bunch of stuff and then just going through the answers. It's like, okay, yeah. [08:48] I know how to do that. I just think it's, if there's an error, do that. It's not really for that. [08:54] So, yeah, there's so many different ways people can use it. And it's one of those tools that, [09:00] Thank you. [09:00] I intentionally think... [09:02] If I've got something that I'm going to search... [09:05] how... [09:06] which AI tool am I going to use first and [09:09] Like, should I just use AI for this? And I don't know whether my appetite for... [09:15] Okay, I know it might take me a few minutes to go and do this on ChatGPT, on Perplexity, wherever.

[09:21] versus go to Google and [09:24] Bye. [09:26] do the work myself. Like I'd rather be sat there doing the lazy work of the prompting and asking, [09:32] Figuring out whether the answer was what I wanted rather than, [09:35] feeling like I'm doing the work, going through the blue links, going through the lists of lists of lists, [09:40] to then be like, I'm still not where... [09:42] I was trying to get to. Um... [09:45] So I'm just... [09:46] I'm using it for everything small, small. [09:49] and bigger. [09:52] at every moment. [09:53] Like of the day, I'm just always trying to default towards... [09:56] Let's use AI for this somehow. Yeah, me too. I mean, that's one of the recurring ideas on this show is, I think, starting to think of yourself as... [10:06] a model manager rather than an individual contributor is like a really powerful idea. [10:12] specifically, I think that helps in two ways. One is it avoids the problem that people have where they try one thing and then they're like, oh, it didn't work or it's not good enough or whatever. Because as a manager, if you're thinking of yourself as a manager, one of the skills of a [10:28] the employee that they're managing is good at and how to get the best out of them. And so I think that transfers very strongly onto AI. It's like, it's your job as the model manager to know what it's good for and to know how to get the best out of it and to feel like, you know, [10:43] you will get out what you put in. Um, [10:47] And so I think it's super important for that. And it's also super important, you know, you're talking about you're defaulting to not having to click through all the blue links and stuff like that. Like, yeah, that's sort of what a manager does. It's like you're not necessarily in all the details all the time, but you can go in there sometimes if you need to. But that like being in that place is, I think, a little bit more of a management headspace than it is like an individual contributor headspace. And I think that's really cool.

[11:12] Yeah, I just, when you wrote that piece and you sent it to me and I said... [11:17] I think I said something like, yeah, but I don't like being a manager. I don't want to be a manager. I just can't ever think of myself like that. I don't think... [11:25] I don't, well, I'm going to say I don't think, I'm pretty sure it wasn't a good... [11:29] manager when I ran my company. And it kind of feels like, [11:34] I don't know. I'm trying to do whatever this thing is now. Maybe don't want to call it a model manager. [11:41] But you are learning similar things, like you said. It's which tool is best for this thing versus I'm just going to default to ChatGVT for everything. [11:50] Um... [11:52] Actually, it didn't give me the right thing. Did I ask it the right thing to give me the right thing back? [11:56] and you do have to think like that but [11:59] I'm certainly not thinking of myself like a manager. Maybe it's a branding problem, but yeah. Maybe I have to rebrand it, but I'm sticking with manager because I like being a manager. That's fine, yeah. [12:10] Cool. Well, I guess on that note, I would love to just get into the show and tell portion. I know you have a bunch of stuff to show me about how you use ChatGPT, and then I think we're going to broaden into other AI tools, which I'm actually quite excited for. And the first one, it sounds like you're using ChatGPT to do research on companies. [12:29] set it up, tell me a little bit about like, [12:32] what kind of company research you're doing and why you would want to use ChatGPT for that. Yeah, I mean... [12:38] I'm just trying to scroll to find it because it's so far back.

[12:44] So I... [12:45] I'm just obsessed with business ideas, always have been. It took me 50 plus years. [12:50] ideas to get to Makepad, which is the one thing that worked. Your last company. Yeah. So that's the one thing that worked. And that was like... [12:58] byproduct of all the other things that didn't work. So I was building them with no code, [13:01] So built away [13:03] those who can't do teach. So I told people how to do that same thing. Um, [13:07] And then... [13:09] With Ben Spites, we cover a lot of interesting products, a lot of interesting news. You see trends. You see how people are using stuff and all that. And it's just... [13:20] I don't know, I just can't help but think... [13:23] that's really interesting. What if that was that for something else? Like I think most people think of startups as – [13:31] Thank you. [13:31] get on TechCrunch, get funding from YC, and sort of shoot for the moon kind of thing, where... [13:38] they're never the kind of businesses I've... [13:42] I don't say wanted to build. I wanted to build them before I started building Makebad and then realized I just like this kind of business, bootstraps. [13:49] took Angel round, but... [13:52] I'm not looking for a billion dollar outcome, probably because of the managers thing. I don't want to be a manager of 300,000 people company. [13:59] Chris Harden, I think, [14:01] The lifestyle branding on those businesses has ruined it a bit because, okay, who doesn't want a two million year lifestyle business? [14:10] That sounds great. So I just think of... [14:14] Products in terms of.

[14:15] This company is doing this thing really interestingly. [14:18] Is there a space that this for x, y, z, [14:22] could be done. Similarly, like... [14:26] Really, if you look at lots of businesses, [14:28] All the business models, all the ways that they do business, [14:32] are often... [14:33] pretty straightforward. Like you can... [14:35] C, okay, they do this thing, then this thing, then this thing. So – [14:38] It's just... [14:39] For me, I liked... [14:41] throw businesses in there, [14:43] I'd be like, what's a similar kind of business to this? And what's the different... [14:48] Like where else would this kind of thing be useful? How would you think about building that kind of company? That kind of chat is what I... [14:56] what I like to do. So I'm going to put up... [15:00] a couple here. [15:02] I'll shut my screen now. [15:04] So this was a chat I had with ChatGBT about a protocol yardstick, a stick with a Q. So from [15:16] the company CB Insights. So they... [15:19] put together a bunch of like valuation data funding fundraising [15:23] interesting things like that. But I think the product is tens of thousands of years of tens of thousands of dollars a year. [15:29] to access [15:31] I'm not paying that. They have this spin-off product... [15:37] called Yardstick. [15:40] What software buyers really think about their vendors? [15:43] And it's effectively, from what I've analyzed, I suppose, is they go to Fortune 500 companies and say, what are you using for?

[15:53] for... [15:54] X. And then... [15:56] They'll have a transcript, they record their conversations, [16:00] And then if you're... [16:01] a fellow [16:02] sort of buyer in that market. You're going to spend tens of thousands on a new product. You want to know about the integration. You want to know the pricing. You want to know [16:12] what the customer support was like, you want to know what the onboarding was like, [16:15] look at other companies similar to yours and sort of determine the, [16:20] whether you're going to go down that road. [16:23] So they have just on the landing page, it says enter a business email address, get a free trial. [16:29] And it just has a bunch of... [16:30] testimonials essentially it's effectively like a small snippet a very small snippet from the transcripts that they have [16:38] So this is... [16:40] For example, I'm showing... [16:41] There's one about Snowflake. The economics of Snowflake gave it a huge advantage. Instead of spending $15 million, [16:48] we decided we could at least probably save 70% in terms of the cost that we were expending on the [16:53] Teradata if we went with Snowflake. So something like that is [16:58] Good to know if you're going to be spending millions on... [17:02] doing one thing with one vendor and you could be looking at another. So they've got a bunch of different companies here, but there's not much else on this landing page and [17:12] Thank you. [17:12] Again, I can't pay the thousands of dollars to go and sign up for this. So, [17:18] I... [17:20] I think I did some Google searches of...

[17:24] What is... [17:25] like yardstick product images. I look back on some of the tweets from the CEO where they shared some screenshots here, there and everywhere. Um, [17:36] And then this was one of the screenshots where it shows... [17:39] Okay, this is a fraud to customer, a head of fraud at a $1 billion valuation startup. So they don't give you any identifying information. [17:48] They sort of give you a highlight of the customer, their head of fraud company, again, billion dollar valuation startup. [17:54] The role, key decision-maker, [17:57] Purchase details. [17:58] purchased in Q3 2018. [18:02] Purchase amount. [18:03] 250k a year. And then it's got this transcript underneath, which... [18:08] I assume, as a customer, you could go and read. So it has... [18:11] Subsections, introductions, evaluation structure, [18:15] Solution specific, sales experience, deployment, competitors, pricing and packaging, post deployment. [18:21] And you can sort of see... [18:22] a small snippet again of [18:25] one of those transcripts. [18:28] So I thought, that's really interesting. I wonder if I could throw that into ChatGBT, use an image search and say, like, what's in this image? And that's literally how I started the conversation. That's interesting. I want to stop you there. So you're... [18:40] You're coming across a website. [18:43] And the website is for a product that CB Insights is selling. [18:49] And you're you're curious about it. Are you curious about it from the perspective of like what we were talking about earlier where where you're thinking about, OK, could I build a product like this in a different category or like what's the what's your curiosity? What are you trying to find out?

[19:02] I think there's probably a few. One is... [19:06] CB Insights is notoriously... [19:09] Like, [19:10] Well, they've got... [19:12] a lot of revenue they've talked about it on podcasts they have big customers who spend tens of thousands on [19:19] this data... [19:20] as a product. And I'm pretty fascinated with data products as they are, I think, [19:28] It feels to me that you could build one or build versions of them with a one-person company, and you could get to 500k as a one-person company building some sort of [19:39] database products. [19:41] in a specific niche. [19:43] The part of my curiosity is... [19:45] What are the best of the best doing in this space? And then... [19:50] if I boiled up that, if I sort of, [19:52] simmered that down to... [19:54] a simplified version for a different space or a different category, [19:58] Like, how would I go about doing that? [20:01] And then... [20:03] Yeah, I just think it's... [20:05] It's kind of interesting to peek behind the scenes of... [20:09] enterprise companies that you can't ever [20:12] C without... [20:13] Jump in on the call with a sales rep. [20:15] doing the free trials, all of that kind of stuff. [20:19] And you just want to know, like... [20:22] Yeah, if you're paying 30 grand a year or whatever it is, [20:25] What does a product like that look like on the inside? And to me, it looks like, hey, here's a transcript that we... [20:32] created with someone. We did the work to interview them. We've anonymized some of the data. Here it is. And also we found many others like them. And obviously CB Insights has lots of other

[20:44] research and reports and data that they pulled together through machine learning and human analysts. But, [20:51] Like, if you cut all of that away and you just said... [20:55] I want to build something where I interview people and I sell access to these transcripts. What could that look like? That, I think, could be a business itself. That's amazing. Okay, I think I get it. One thing that's happening or one thing I'm seeing you do is when you think about a company and a company that makes a product, the thing that you can see on the internet is sort of like the tip of this iceberg. [21:19] And it's like the result of all these decisions and all these processes that a company can do. And if you study the tip pretty closely, you can tell a lot of things about what's underneath the water level that you might not be able to see. And then you can use that to figure out like, okay, what do I want to build if I want to do something like this? And it sounds like you're using ChatGPT to do a little bit of that investigation. You're gathering some starting data and then you're using ChatGPT to figure out, okay, what's under the surface here? How is this? What am I seeing? How is it constructed? All that kind of stuff. Is that right? [21:49] Yeah, definitely, because I think you can sort of make assumptions on – [21:54] Like what work is needed? [21:56] under that sort of [21:58] Tip. [21:59] to get to the point where you have something that you could sell and this could be a product and this is something that people would pay for. [22:06] Because people, I think, often... [22:08] I mean, you hear lots of companies that are tens of thousands of employees and all the rest of it. And there's lots of work that goes into whatever they put out.

[22:16] I just think if you can see... [22:18] What does the output look like? [22:21] And you can sort of figure out a way to get there or a way to get part of the way there, carving out a very small part of whatever they're doing. [22:30] Um, [22:31] And it becomes less scary to be like... [22:35] I could never start a business like... [22:37] whatever. [22:39] that charges whatever to these kinds of people where – [22:44] I just think it makes... [22:46] business less daunting to think about in... [22:49] in those terms of [22:51] I do believe that anyone can build... [22:55] like most things, not big VC-funded companies, [22:59] But most things... [23:01] to get a great [23:03] Thank you. [23:04] multi-million a year, lifestyle business. And I think even with AI, we're seeing lots of that now where lots of individuals and small teams are [23:11] are building really, really valuable projects [23:13] companies that aren't venture backable. [23:16] Nor should they be. But it's still like a great business. There's a really simple equation that goes into... [23:23] What does it take to build something that... [23:25] provide something valuable to customers [23:27] that we can get. [23:29] thousands or tens of thousands of customers signing up for this and paying us. [23:33] I love that. I love that. And so, okay, so now I think I kind of get that, like where your head's at and how you're getting into the chat. So it sounds like what you did first is you just [23:43] pasted the image in and you were like, what's in the image? And talk us through like what Chachupji said and what you did next.

[23:51] Yeah, so it says the image shows a screenshot of a webpage from CB Insights. It seems to be a customer testimonial case study from a company named Forta. [24:00] which is not true. It's a fault of customer. Main focus is... [24:06] sort of give some of those details of the customer, the purchase details, um, um, [24:11] Below this, there is a transcript of the customer's feedback divided into sections such as introductions, et cetera. [24:17] Um... [24:18] Then on the left side, there's a column listing, other customers who also purchased from Forza. So it kind of changes what it first said. [24:26] Um... [24:27] But I suppose maybe if it's a case study for a company... [24:31] Maybe I misinterpreted that. [24:35] Just like a professional business document, sort of normal chat GBT fluff at the end. [24:41] Um... [24:42] And I followed up saying, make a reasonable guess as to what questions would be asked of the customer for each of the transcript sections. You could see one question in the transcript in on the transcript in bold. [24:53] Because you can sort of see... [24:55] In the screenshot, it says, could you highlight one of the other vendors that you considered and maybe highlight what made you choose Forta in the end? [25:02] That gave it the... In my mind, it gave it the... [25:06] So one example is, [25:08] Thank you. [25:09] that it needed to then make some assumptions. [25:14] So then it came back with... [25:16] Introductions. Can you introduce yourself and tell us about your role at the company? How does fraud prevention fit to your company's operations?

[25:22] valuation structure, [25:24] What criteria do you use to evaluate fraud prevention solutions? How do you structure the process? [25:29] And then sort of there's plenty on here. Sales experience. How was your experience with our sales team during the evaluation process? [25:37] deployment, can you walk us through the deployment process of our solution? [25:41] Again, it's looking at it from a... [25:42] point of view of Falter asking these questions. Right. And did that like, I guess, so I can sort of see your reverse engineering how this transcript was created or you're trying to do that with ChatGPT. Did the response that ChatGPT gave you, did that answer your question? Like, was that what you wanted or was it off base? [26:03] Yeah, so this, I was basically getting it to start from a point of we have a... [26:09] MVP, I guess. This is our very basic form for how we would go and ask people questions like this. [26:17] And because I have no information other than what was on that screenshot, [26:21] I also don't know. Like, [26:22] All these questions could be viable. It could be the right ones. It also could be [26:27] completely hallucinated and no, that's not quite right. But I mean, given the... [26:32] subsections of evaluation structure, solution specifics, [26:35] I think that helped guide it. [26:37] in a reasonable way. [26:39] Um, [26:40] that I could see that, okay, you could... [26:43] take that and say, okay, if I'm going to do a similar kind of data company where I'm going to interview people, [26:50] people in whichever industry

[26:52] I can use this as a blueprint to start my own. [26:55] transcripts or interview people. [26:59] Got it. Okay, cool. And so you've got the basic blueprint, and then it looks like what you did is you pasted that screenshot in from Yardstick, the original screenshot with all the customer quotes. And what did you ask it? [27:29] based on what is mentioned in the image. [27:31] to sort of refining [27:33] Are there any other insights that come out of that that then... [27:36] would have... [27:38] been in response to a different question that you haven't included is essentially what I'm [27:42] Maybe I should have said it that way, but that's what I'm insinuating there. [27:48] And then it became... [27:50] Less. [27:52] detailed in the first round. [27:56] Thank you. [27:57] So introductions... [27:59] sort of similar [28:02] A lot of them... [28:04] A pretty... [28:07] Thank you. [28:08] I don't know if it actually made it any worse or any better. It kind of summarized it into one bullet point rather than two for each. [28:15] So I think if we look at just post deployment, how is our solution performed since deployment? Can you share any measurable impacts our solution has had on your operations? That was before the screenshot and afterwards.

[28:28] Since deploying the software, what have been the tangible outcomes and benefits for your organization? [28:34] It's just kind of... [28:36] Those two questions kind of fit in that one question. [28:40] So I felt like, don't know if that's enough. So then I found... [28:45] more images of more snippets of more [28:49] transcripts and I basically fed them in. So there was one, two, three, four, [28:54] Five, six, seven, seven. [28:57] seven images of transcripts. And then there's also [29:04] Something... [29:05] called a vendor scorecard, which is something from Yardstick that they put... [29:10] In this example, there's [29:12] Stripe, Checkout.com and a few other payment solutions. [29:16] Um, [29:18] And they've got the overall satisfaction score, which is blurred out. [29:21] Win reasons. So if you've got a better use experience, integration with Shopify. [29:27] So these are things that customers would have mentioned why, [29:30] They chose Stripe over any of the alternatives. [29:33] and opportunity areas. [29:35] improving non-US coverage. This is things that [29:38] People are obviously complaining about [29:41] why they didn't use Stripe or where it could improve [29:44] even though they have used Stripe. [29:48] So again, it was... [29:49] Here are more images about Yazdek. Update the questions based off the information provided in these images. Right. And again, it kind of does a similar... [29:57] a similar thing. And it does change...

[30:01] the sort of sections [30:04] Um... [30:07] So there's no, like, introductions and things like that. It sort of goes off and ignores some of the basic stuff and ignores the original... [30:18] But again, if we look at the deployment one, what was your experience with the deployment process? How did the quality timing and support meet your expectations? So I can either be thinking of this as... [30:28] I've done the same thing three times and got three very samey answers. [30:34] Or I can assume... [30:37] That's probably what the question was. [30:40] That is most likely what the question is, given all of this data, that is actually... [30:47] what it was. [30:49] Um... [30:50] And there's no real way to tell. [30:53] I think taking that instinct and deciding if I looked at all that information, I [30:59] And especially at one of the sections, say the deployment one again, [31:06] If I looked at any answers relating to deployment, [31:09] Thank you. [31:09] could I infer anything differently? Is there anything else I would add to that? Does it seem like that question would or should be [31:17] Ghana, that kind of response. [31:19] that we're seeing in the examples. [31:21] That makes a lot of sense. I mean, I think that's definitely one conclusion to take away. Another thing that pops into my head is sometimes with ChatGPT, when you're asking it to edit something,

[31:35] it doesn't do as good of a job unless you have it like – [31:40] like, first of all, like think through the what's in the screenshot first, be like, what are the questions that were that probably generated the answers in this screenshot? [31:49] have it say all that and then be like, can you modify your, [31:53] the questions you've already created. [31:55] to include the new ones that you've done. Because otherwise you're kind of like smushing together the thinking about the questions and the like editing step. And sometimes it's good at that and sometimes it's not. And it's sort of hard to know, but it's an interesting thing to try. [32:12] And then would you... [32:14] each time you then... [32:15] asking it about the information and the images, I guess two questions. One is, would you ever put multiple images in there that have different information or would you use it, you do one at a time? Let's try it. You want to try it? Yeah, sure. Cool. I mean, I would do multiple images. I think that's fine. It's more like doing both the [32:39] pushing out the like generating the questions and then compressing them together into a new a new list based on old questions is like it's sort of complicated for it right now and it may not think everything through in the way that you want. [32:54] Yeah. And then would you also re-add the original questions that it came up with? [33:04] I would wait. I would do that later. So I would you can either do it in this chat. You can start a new one. I don't know like how important this chat transcript is to you, but so I would just I would upload as many as you want. I think you can upload four total.

[33:21] And ask that original question, which is like, what are the questions that you think generated that this... [33:28] image. And I probably wouldn't use the original one because you already have good questions for that. I would use like the do the landing page one would be a good one, I think. Okay. [33:38] Thank you. [33:39] Um, [33:40] Thank you. [33:41] So I'm going to do the landing page one, and then I'm going to do... There's two screenshots here that actually have the questions in. Okay, cool. I'm going to see if it comes out with... [33:51] the actual questions. It says here, under competitors, you can see what alternatives to the vendor have you considered, [33:57] what use cases does the vendor's product or solution serve for you today? [34:05] So... [34:06] Okay, if we upload... [34:08] Okay, so we have... [34:10] We have four images, one of the Yastik homepage with all the snippets of transcripts, one we've got. [34:17] We've got two that have [34:19] a screenshot of [34:21] part of the transcript so it has the questions in bold [34:25] And then there's one that is just... [34:27] snippet of the transcript and there's no question in that image cool um so yeah what what should i ask it well okay if we're starting with something that gives it an example of question of a question i think we want to like reference that so like um it's probably something like um in in the screenshots i'm attaching [34:50] There are questions...

[34:53] that, um... [34:55] Let me think about it. There are questions that get answered by the text, right? By the transcript? [35:04] Okay. [35:05] This is not precise, but we're trying to like reverse engineer it, right? Yeah, exactly. [35:13] In this reason I'm attaching... [35:18] There are snippets of... [35:23] various transcripts with customers of software, oops, tools. [35:35] And then... [35:36] Sometimes the transcript includes a question that the customer is answering. [35:45] Thank you. [35:46] Thank you. [35:48] Would you specify that and say it's in bold in the screenshot or not? Yeah, that's cool. I like that. [35:57] Thank you. [35:59] Thank you. [36:01] So [36:04] Based on the question-answer pairs that you can see, [36:15] For any transcript... [36:18] snippet that doesn't have a corresponding question. [36:22] Please try to generate

[36:25] the question that, um, [36:29] that produced that answer. [36:32] Thank you. [36:34] Amen. [36:35] Thank you. [36:36] Thank you. [36:37] And then I don't know if you want to do like, you know, a couple of little exhortations at the end that are like, be specific, be thoughtful. [36:48] be detailed. [36:50] I'll give you $2,000. I'll tip you $2,000 if you do it right. [36:55] I've never actually tried that. I love that one. I don't know if it works, but I do it all the time. Oh, really? It's just fun. [37:03] Thank you. [37:04] Thank you. [37:07] um [37:09] Cool. Should we try that? Let's try it. [37:12] Thank you. [37:13] I'm really curious. Part of me is like a little worried that we should have broken it up where we had it think about going the principles from going the principles of going from question to answer. [37:24] based on the two examples of question-answer pairs that we have, and then had it think about new ones. But I think it'll be good enough to do it. [37:34] Yeah. I don't know if it's [37:37] Thank you. [37:39] Not working because it's an old chat. It was a bit flicky with me earlier. [37:45] Oh, here we go. [37:46] Okay, certainly for each provided answer to the general questions, from the screenshot, which is the... [37:53] Full screenshots. Okay, it's giving us the answer first. So it's giving us the actual quote from the...

[38:02] homepage. [38:04] but only two of them. There were obviously a lot on there. [38:08] Thank you. [38:09] So we use product name because it's the easiest CRM system in terms of service and [38:14] customization, customization, [38:15] et cetera, et cetera. Possible question. Could you explain why you chose product name over other CRM systems like Clevotap and MessageBird? [38:23] What do you think of that? I think it's reasonable. I think... [38:27] I would kind of guess or know that [38:30] They wouldn't put other... [38:33] I guess. [38:34] I might be guessing wrong here. [38:37] I assume, like I... [38:38] It's the other software... [38:40] Tool reviewers, they always just say, what are the... [38:43] vendors have used and why you choose this over any specific, so they give it more broad [38:48] interpretation for the [38:50] the person being interviewed. Um, [38:53] I think that's a good question. That would probably make it into the transcript question list I would set up. [39:01] The next one is the reason why we didn't go with product name, [39:05] because it was impossible to integrate Aidan with our website. Possible question. What were the challenges or limitations you faced that led you to not choose product name, [39:14] for identity and access management. [39:16] I think, again, that's pretty good. [39:19] But it's probably... [39:21] Almost the question is almost the inverse. [39:24] Um... [39:26] You're probably not asking them – or maybe that's more a follow-up question. You're asking, what products did you use and why versus what product didn't you use and why – yeah, what product didn't you use and why not? That makes sense. But it's still like – it seems like it's generating at least new questions that it may not have done before, which is kind of interesting, and I think –

[39:48] the same sort of the principle sort of holds. It's like the more you can break up the thinking steps into explicit steps that you ask it, [39:56] sometimes the better it does. I'm kind of curious for you, [40:01] once you did this exercise and so i and i think you you got a list of questions like [40:06] Where did that leave you? Like, are you going to do this idea? Like, what was your next step? Yeah, I think... [40:13] So I think I looked at it as, just looking back up, [40:18] Thank you. [40:20] isn't things like [40:22] improve the landing page, copy of yard six. [40:27] That's a good one. [40:30] Although I think Yartik actually has a really good landing page copy. So I think that's why I did it, because it was just so... [40:37] on the nose learn what software buyers really think about your vendors and chat gbt's version is [40:41] Discover the unfiltered opinions of software buyers on their vendors. That's not bad. I like the word unfiltered, you know? Yeah. Yeah, yeah. I do too. Um... [40:51] And then... [40:52] based on the below titles, group the quotes and text from all previous images into where they think best. So I think I was... [40:58] reaching a bit here. And, uh, [41:02] it just sort of gave me... [41:05] generalized, okay, any comment in the introductions, any comments where customers introduce themselves, their role of company. They didn't actually put in. [41:12] the quotes. So I think that's fair enough. [41:16] And yeah, I mean, I don't think... [41:18] Now put quotes in the relevant categories. So they did some...

[41:22] Some quotes there. [41:26] Yeah, it's just like, if I'm going to do this... [41:29] Thank you. [41:30] I'm trying to kickstart a crowdsource anonymous unfiltered review, I put user unfiltered there, unfiltered review sign for AI products. [41:38] Thank you. [41:38] What are the best ways to start that site in getting reviews? [41:43] So this is something I actually have started. [41:47] And I've started getting... [41:48] anonymous unfiltered reviews um [41:52] And I think I grouped... [41:55] I group things into four categories, which is [41:58] products [42:00] pricing, [42:02] like integration and deployment was one, [42:05] and competitors. [42:07] Um, [42:08] So I have got a list of [42:11] really interesting reviews from people using things like cursor lang chain copilot uh chat gpt um [42:19] And yet it's something I'm working on at the moment where I think it's really interesting, but who knows what kind of thing it would turn into or look like at the end of it. Because I think there's different versions of it. [42:32] who the buyer would be for this kind of thing. [42:35] Is it like a software review tool like... [42:38] G2 or something, or is it more a business tool like CB Inside, C-Hardstick? [42:44] So I just said, yeah, let me know how to get started with building this thing. And it just gives you really generalized stuff, research and planning, identify your niche. And then

[42:57] research competitors, website development, et cetera, et cetera. So I was like, okay, just focus on the content collection part. I know the rest. [43:06] Because I think that's the interesting part where, again, I can make some assumptions on, [43:10] Make a list of people you want to interview. [43:13] go on to Apollo and find their emails and then email them and then try and get on a call and then ask them these questions. Like, realistically, I know that, but I think going through this process is just... [43:26] More fun, more interesting. Yeah. And it might say something you wouldn't have thought of or, you know, for anyone who's listening that doesn't know that off the top of their head. Like, I think that's second nature to you because you're second time founder, third time founder. Like, you've been doing this for years and years. [43:41] So even that basic thing, if it gives you a basic answer, that might just be helpful for someone who hasn't done it before. [43:48] This will be live by the time the podcast comes out. It'll be requestforai.com. So I'll get this done. That's amazing. Yeah. So from doing this, I remember now from doing this, focus on the content collection part. I know the rest. I mean, I might not know all the rest, but yeah, that's the bit I wanted to focus on. [44:09] It gave me some things like... [44:11] Initial content seeding, [44:13] create a list of popular and emerging AI products to start the conversation. I did do that. Um, [44:19] hire contributors. I basically just DMed it to a bunch of people who I [44:23] trusted and would give reviews. [44:26] uh yeah user generated content encouragement be the first to review entice the users

[44:31] Um... [44:33] And then community engagement, [44:36] that's sort of a bit generic, like engages AI communities on GitHub. [44:42] incentivization, offer awards for early reviewers, [44:46] which is something I've talked about where people can get access to all the reviews if they write a review. This actually sent me down another rabbit hole, which... [44:57] I don't know if I can see it. [44:59] Yeah, I can actually. So this is... [45:01] Here, there's another chat. [45:03] Glassdoor founding story. So Glassdoor was... [45:08] is basically... [45:10] An anonymous site for people to... [45:13] leave a review on your employer. [45:16] Do you hate your boss? Is it horrible working hours? Is it good pay? All that kind of thing. So I was like, [45:21] Okay, well, where did that all come from? How did that start? How did they start getting people to write reviews on a site like that? [45:29] So I started with what's the founding story of Glassdoor. How do they monetize... [45:35] Thank you. [45:35] And... [45:37] It's really interesting that... [45:40] Yeah, they do like job advertising, employer branding solutions. So if you're a good employer on Glassdoor, [45:46] you can have like an enhanced profile and you can have, [45:49] things on your profile page that entice other people because if people are looking for a job at your company they might come across the glass or [45:57] profile and [46:00] I found that quite interesting. It feels like that's not...

[46:03] Thank you. [46:04] It doesn't feel like that fits the purpose of the site in the first base, though. Like... [46:10] I'm there to give an unfiltered review on this thing. [46:15] its company, [46:16] yet this company is also on the same page or in the same place. [46:21] it's trying to entice me to go and work there. Like, [46:23] they can be the same sort of thing being like I read this really good review I'm going to do that but also [46:30] They could be very, very opposite. [46:33] And then how did Glassdoor get reviews on the site initially? Did they run any incentives? I was looking at that kind of thing. [46:40] There's a give to get model, so their initial strategy was based on a give to get model, access to full range of information on the sites. [46:47] users have to contribute their own review or salary information. I did actually sign up [46:51] for Glassdoor just to go through the process and see [46:56] because I couldn't see anything, and then left a review, and then I could see some information. So things like that, I was like, yeah, it's just an interesting way to start exploring things, [47:05] an idea and where [47:07] It's going to go and how it changes at the time. Yeah. This is awesome. I love this. What I think this episode is about is one thing you're really good at. [47:20] is starting these sort of like one man, small, like profitable internet businesses that are like sneakily big or can get sneakily big over time, but that don't require a lot of resources. And I think the first thing that we're covering here is how do you find that opportunity? And what it sounds like you're constantly doing is you're like running into things on the internet, running into products and all that kind of stuff. And then you're kind of deconstructing them. Like, how do they work?

[47:50] How could I do that myself, maybe with fewer resources, maybe with a very small team without a lot of money? [47:56] And to do that, you're kind of like throwing it into ChatGPT. You're kind of looking what's underneath the waterline. Like, how is this made to some degree? And then you're also, it's pushing you in new directions where you're like, oh, I'm going to research Glassdoor. You know, it like, it creates this whole rabbit hole that you can go down so you can get this like clearer picture in your head of... [48:16] If I was going to execute this idea, would it be a good idea and how would I do it? And I think that's so cool. [48:22] Yeah, I think that's... [48:24] That's the bit where people get hung up. [48:26] Initially, no one needs any more information on how to start a business because it's all out there and... [48:32] If you keep doing that, you're just procrastinating on the fact that you could just do it today. [48:38] But by doing... [48:39] little exercises like this. [48:41] Almost... [48:43] Not subconsciously, but just... [48:45] as a thing that I find interesting. So I do this on all sorts of businesses because I just find it an interesting thing to know. I listen to podcasts to find the inner workings of how things started, how did they grow, all the rest of it. [48:59] And it's not necessarily that I'm going to go and start every single business that I eat. [49:03] think about and research [49:05] We might uncover something that's like, oh, that's interesting. I didn't realise... [49:10] That's how that thing started. Or then you might look at it as I'm doing with Glassdoor thinking, well, actually, a better example is like G2 or Trustpilot, any of these software review tools.

[49:23] Their monetization model is... [49:25] For the companies that are getting reviewed, [49:28] to get leads. [49:30] So you obviously want your company to be really highly reviewed so that other people will use that. And then you get basically cost per lead. [49:38] But to me, that feels like... [49:40] a really backwards way of thinking of that model. [49:44] But that model clearly works because there's three or so companies get millions, three million, four million, five million, five million, [49:51] views a month. [49:53] for that kind of thing. [49:55] But I guess in their interest as a platform, [49:59] to then promote the products that people are reviewing. [50:02] was if you were a user, [50:04] You actually just want to know... [50:06] the real... [50:07] like, [50:08] what people are thinking and what people are using this thing for. [50:11] And why is it good or why is it bad? Like, that's the thing that I'm looking at in things like this where – [50:18] I wouldn't maybe come across that if I hadn't started going down a rabbit hole of... [50:23] yardstick first and then how does that get to glass door and then how does that get to g2 um like how do they all sort of interlink and i'm just in the middle of um [50:35] Your episode with Staff Smith, who... [50:36] did internet pipes, which is great, talking about going down rabbit holes and really just [50:43] You're just sort of stuffing all this information in. [50:46] Not that it needs to all connect anywhere, but... [50:50] Some things might spark something and it's like, oh, that's...

[50:53] really interesting little piece of information that I hadn't thought about. I wonder why it is that way. And then you might go down more rabbit holes to explore that. But yeah, I'm just trying to be informed by it all and try and understand it. I love that. Yeah. I mean, that Steph Smith episode, I just think there's a lot of parallels where you're both just so curious about what's going on and you're using these tools to unpack what's going on. And yeah, most of it, maybe it's [51:23] do is it seems like we've sort of unpacked like, okay, how do you identify opportunities for these kinds of internet businesses? [51:30] using AI, what I want to do next is [51:34] Do a little bit about how you use AI to run these businesses when you are [51:39] when you found something that's valuable. Cause I think you have a lot of ways that you're running Ben's bites, which I think fits this profile of business, um, that use AI that help make that process more efficient for you. Um, [51:52] So, in particular, like one of the things you shared with me before the show is use it to like highlight transcripts and annotate them so that you can turn them into useful articles and useful stuff for pensbytes. Do you want to talk about that? Yeah, sure. So, for this, I actually use TypingMind, which hopefully you can see on my screen now. Yeah, I can. What is TypingMind? I've actually never heard of it.

[52:22] a different model of, [52:24] to use. So you can have Claude, 254, now they've got Demoni. [52:30] So you can do that, but also there's no... [52:35] token limit so you can just dump in anything any amount of information you want and it i assume will do all the chunking and stuff behind the scenes [52:44] The... [52:45] I think it tells you your... [52:48] Like it all... [52:50] I think somewhere it tells you that... [52:54] Thank you. [52:54] I can't see it now, but somewhere it tells you how much it's cost you [52:58] to have this kind of conversation. [53:00] Um, [53:01] And like if I'm happy to spend 14 cents on transcribing a... [53:06] or like getting information out of a transcript, then I'm really, really happy to do that. Okay, cool. And is that the main reason you use it? Because it does the chunking for you? Or is it also to switch models? Or what's the selling point for you? I think it is the combination of two of those things. Like I used to have... [53:24] a Claude [53:25] It must be like a... [53:26] AI influencers account that it didn't cost me anything and I could put anything I wanted in there. So often with a podcast, [53:33] I'd use a Chrome extension called [53:35] that would basically pull the whole transcript into Claude and say, summarize this, and they could just ask the podcast question saying, [53:44] where does Dan talk about this thing with Steph and pull out quotes? [53:49] But I've must have been kicked off that now. So I'm paid for that. And

[53:55] I just use it to sort of get the prompt of the whole transcript now. [53:59] copy that, bring it over here. And then sometimes I like to, [54:03] compare the two models. So instead of going to Claw, ChatGPT, Gemini, I'll do that in this one interface in like different chats. [54:13] So yeah, with what I'm doing with Benz Bites Pro, which is more long form, [54:18] probably about 2,000 words or so, [54:20] Um, [54:21] Talking with companies on how they use AI in their business. So one that is coming out this week is with the CEO of Ignite Tech, which is an enterprise company. [54:32] I basically had... [54:33] a conversation on Zoom or Google Meets with the founder, [54:39] Ask the Benz questions and they're not formatted like my research previously, but it's more like just, yeah, what are you doing and how are you doing that? And going down rabbit holes that they're talking about. [54:49] Um, [54:50] And it's a lot of information. Often it's an hour plus call, [54:54] There's a lot in there that I come away with thinking, oh my God, there's so much to write about. There's loads of stuff here. And I'm not really a writer, which is sort of ironic. But... [55:03] I'm like, okay, well, how am I going to go... [55:06] And now... [55:08] Thank you. [55:09] synthesize that information, section it into the right place, [55:13] and figure out a good structure for how I'm going to write about this thing. [55:17] other people might have better solutions or like have a... [55:21] sort of muscle that they built up over time to do that. But I think for me,

[55:25] Helps just clear it, clearly get it out. I don't want to watch myself back on a video. I don't want to hear myself back on a video. [55:33] And... [55:34] Reading through a transcript can be [55:36] a bit dry. So I use Supernormal, which is what I use to record the calls, and it pulls in my whole transcript. I cover that transcript over to [55:45] something like typing mind. I did try it with... [55:49] Thank you. [55:50] Gemini, which I'll show you because that actually is literally when Gemini just came out. This is the new one from like a couple of weeks ago. [56:00] Yeah, from... [56:03] Yeah, last week. [56:05] So... [56:06] It's... [56:08] Thank you. [56:09] What I have to do... [56:12] First, I basically tried to put the whole transcript in. Obviously, it didn't work. [56:17] Then I thought, well, actually, I can't upload any files to Gemini. So how am I going to get this whole transcript into... [56:23] the model to then ask it to sort of section up the transcript. [56:27] So – [56:28] I then thought, well, maybe I'll put it as a Google Doc. And again, this is one of those examples of I'm willing to do a thing that takes me a few more minutes to figure out than others probably are. [56:39] But I think then it's worth it in the end. So I put it in a Google Doc account. [56:43] I just pasted the transcript there. [56:45] And then I said to Gemini, I... [56:47] Find my document titled Ed Vaughan, Ben Tussle's transcript. Highlight key topics that I should write about in a blog post. I write posts about how businesses are using AI internally and in their products. Include quotes in each section of the blog post draft. And I'm showing you this.

[57:04] sort of janky screen, because for some reason... [57:08] it hasn't saved in like Google Gemini. [57:11] Um, [57:12] I said, sure, I found the document. Here are some key topics that you could write about in a blog post about how businesses are using AI internally. How Ignite Tech is using AI to drive cultural change. And then it gives me three quotes. [57:23] where Eric talks about I presented at an all hands meeting and said, I'm going to give everyone a gift. [57:29] Um... [57:30] And it's a gift of time, education, money, support, enthusiasm to learn something. So fundamentally groundbreaking, it's going to make you far better than you were before. [57:38] I was like, yeah, I wanted to touch on that section. Definitely, there was loads of stuff that we could have included there. So that's definitely now a section in the final post. [57:48] How Ignite Tech is using AI to improve its products. Again, it's given me a few quotes where... [57:53] We announced to the world, all of our customers, that we'll have an AI capability in all of our [57:58] different divisions of products that we have. [58:02] And then another one was the importance of leadership buying for AI adoption. [58:07] And then a small quote here is, "I've got to be involved as everyone else, and you've got to make this a priority." [58:14] So it doesn't write the blog post for me, so I'm not claiming that it does that, and nor would I want it to. [58:21] But what it does is like, it's this... [58:23] strange writing partner that helps me do a lot of [58:27] the work and again this is mentioned in [58:29] the episode you did with Steph where [58:32] I could sit there for six hours and do this, pull out quotes, organize it, and then...

[58:38] put it together in a certain way. [58:40] Or I could... [58:42] spend six minutes trying to get this into one of these models, Gemini, typing mind. [58:48] Um, [58:49] and actually pull out some stuff that I'm like, great. They are reasonable sections to start with. [58:55] I can start writing about those sections [58:57] And then I sort of have further conversations on... [59:00] But... [59:01] One thing I use it for quite a lot is... [59:06] here's my blog post, like towards the final edits. [59:10] Can you summarize some key takeaways for this post? So I like to sort of put that there. I'll come up with something stuffy and sometimes very generic, but again, it's a jumping off point for, [59:21] Yeah, these are the things that are important that I've mentioned in the post. And it just helps me [59:27] think about that. And then how do I ride that in the way that, [59:30] I would. [59:32] And I use a company or a tool called Lex. So Lex.page. [59:37] That's got AI built into it. Happy to show you that. Please do. I mean, I'm obviously familiar with Lex. We incubated it. [59:46] Of course you did. [59:50] So you'll be happy to know that I'm using it. I'm very happy. [59:54] So this is the post, how Ignite [59:58] techs team uses AI. So we've got takeaways here. [1:00:03] driving cultural change with AI, as you might be [1:00:06] So, I think that's a good thing. [1:00:07] Feeling familiar with that, as I just mentioned.

[1:00:11] So it helps me write these posts and put in quotes, and then I go deeper and much deeper on it. [1:00:16] Just over 2,000 words. [1:00:19] And what I really like about using this is versions. So I could dump a load of notes in. [1:00:24] I think in my version one, I've even got... [1:00:29] like AI drafts. So this is like, this is where Claude pulled out the transcript stuff and mentioned sections that I could talk about [1:00:37] And then here is GPT-4 doing the same thing. Here is Gemini doing the same thing. That's cool. And I sometimes put in... [1:00:45] How are they drafting it? And... [1:00:47] Like, it's just a way to... [1:00:50] bounce things off with someone else when I if I feel like I'm not a writer, and I'm always staring at a blank screen or blank section, [1:00:57] How do I get? [1:00:58] How do I get that thing written? It's always better to go from, for me anyway... [1:01:03] Something really horrible that kind of says the same thing that I want to say. [1:01:06] But actually, I'm... [1:01:07] I'm going to say that in my own way now. Thanks for the help. I don't need you anymore. But that's... [1:01:13] And again, this is sort of the same with business. I don't need to think of a whole new business model, a whole new brand new idea that's never been heard of or done before. [1:01:21] What works somewhere, take it, remix it, and make it your own then. [1:01:26] Um, [1:01:27] So, yeah, I put a bunch of these drafts in here. [1:01:30] And then version two... [1:01:32] is actually my written version. And then... [1:01:35] My favorite part of all of this... [1:01:38] is at the end I'll do this [1:01:40] AI run checks. Right, I was going to ask you about checks. Yes, so I do use them. I only use them for

[1:01:48] gravity and readability. [1:01:50] So effectively... [1:01:51] I'll do it now. It'll run through. [1:01:54] And so, okay, you shouldn't say... [1:01:58] today you shouldn't say radically um [1:02:02] modernizes it'll change to American which is not what I'm doing so I'm from the UK um [1:02:10] It really helps me, at the end, think of... [1:02:15] I could have said this so much shorter. Like, this is so many... Because I kind of write how I speak. So... [1:02:22] you can probably tell if you're listening to this that I kind of speak all over the place and [1:02:26] And that's just how I do it. So whatever that means... [1:02:30] for my writing, it needs to be also clear enough for the reader. So I think just having these checks really helps me like, flip through, what can I say here? Okay, well, [1:02:39] That's how I introduce a post. I like saying, and today. So I'm going to leave that. And then it doesn't need radically changing their company in there, but... [1:02:49] it is radically changing their company. So I'm actually just going to keep it. And there's, [1:02:52] You can just ignore them. You can accept them. You can change them. I do this a lot. And then, yeah, that's how it sort of ends up as a final post. There's, there's a lot of AI baked in there in different places. Um, [1:03:06] Yeah, so that's interesting. [1:03:08] That's awesome. I love it. I mean, um, [1:03:11] Uh, like just to sort of, I don't know, put all of this together. There are all these different parts in this process of, of creating this product, which is Ben's Bytes Pro that.

[1:03:23] requires like a decent amount of drudgery. Yeah. It's not all like roses and butterflies. It's not all exciting stuff. And especially if you're like a one man or couple person business that you're trying to, you're trying to scale, you're trying to make it really profitable, but you're not going to go higher. Like, [1:03:41] a thousand people to do all the work for you. These kinds of tools, whether it's, uh, Gemini or Claude or Lex, which incorporates all of those things are typing minds. Um, [1:03:51] They allow you to produce the product that you're going to produce much more quickly at a higher level of quality by yourself than you could otherwise. And that's like an incredibly important and valuable tool for anyone who wants to start profitable Internet businesses. I think it's really cool. Yeah. And like I said, I just try and bake it in everywhere where... [1:04:10] I want to be the one that's written this post. I don't want to go and give it to... [1:04:14] an editor. I don't want someone else to do a first draft. [1:04:17] and then me come to it, because... [1:04:19] None of my thinking has gone into creating that. [1:04:22] that structure, that format. [1:04:24] um the exciting part is having the call having the conversation that's really easy and that's [1:04:29] Great, if I could just [1:04:31] one click that goes to exactly what [1:04:33] how I would write it, then fine. But I don't think... [1:04:36] That's reasonable to think. I think it's... [1:04:39] I also like to try and [1:04:41] put a spin on it or put some commentary around all of the things we talked about or [1:04:46] takeaways for other people reading this to be like okay cool how should I maybe think about that [1:04:51] like doing that similar thing in my company.

[1:04:54] Um, [1:04:55] And it's just... [1:04:57] I could have maybe done this... [1:04:59] A few years ago, [1:05:01] I wouldn't have ever dreamt of it, I think. And I think I only... [1:05:04] Decided to do pro... [1:05:06] Now, which is one of these long posts a week, [1:05:09] is because I actually can. [1:05:11] get it out, I can get it to a decent quality level, [1:05:14] that people are signing up for and people are really loving... [1:05:18] Like it's all done with me. Like I'm the only one who touches pro. [1:05:22] And... [1:05:24] I don't know. It just doesn't feel like... [1:05:27] that drudgery anymore. There's still like... [1:05:30] issues with writing and figuring out [1:05:33] what you're going to write next week and the week after and all the rest of it. But, um, [1:05:37] The actual process of creating a post is so much more fluid now [1:05:42] And having these like AI sparring partners makes it so much... [1:05:45] easier and more enjoyable to actually put together. Totally, totally. That makes a lot of sense. And I know, like, you know, we started with this sort of [1:05:53] "Using AI for Business Identification." [1:05:55] And then we kind of got into this middle section where we're talking about using AI to, once you've identified the business, to run it in an efficient way where it's still your voice. It's still you doing the work, but it's taking out some of these micro tasks that take a long time and are sort of drudgery and it's helping you improve the quality of the output. And I know you have one more thing, which I would I would sort of put in this other bucket, which is like once you have a product out there. [1:06:19] Figuring out how well it's doing so that you know what to change is really important.

[1:06:25] And it sounds like you're using ChatGPT to do some of that analysis for you, which is to like gather some feedback, gather some survey data, and then try to understand, okay, like what do customers think of the product and like how can I improve it, which I think is also really cool. [1:06:41] Yeah, so we did this recently... [1:06:45] And obviously there's probably some emails in here that, [1:06:49] might come through. I know it looks like it's okay. We had a survey of subscribers and asked them [1:06:57] while they continue to stay subscribed. [1:06:59] Their answers were in a CSV that I attached, focused on the information in column A, and [1:07:04] Read the answers and summarize how the majority of people feel. [1:07:09] You can ignore any outliers or anomalies. [1:07:12] I don't think it really did that bit. But, um... [1:07:17] Yeah, so it sort of talks about people – [1:07:19] Really appreciate the content, especially in using new tool sections, which... [1:07:24] are the main sections that we have, so that makes sense. [1:07:27] Accessibility and format people value the newsletter's ability to keep them reformed in such a quick, easy to understand way. [1:07:35] Um... [1:07:36] Staying updated... [1:07:38] All right. [1:07:39] The fact that the newsletter is free is a factor for staying subscribed. Can't beat free. [1:07:47] Yeah. And then... [1:07:48] This is what I would count as an anomaly on Outlier, but... [1:07:52] Inertia, at least one respondent mentioned inertia is a reason for staying subscribed. I think it's so funny when people take the time to answer a survey like that, and then they just like totally put you on blast. And they're like, I'm a subscribe because of inertia. Yeah, I know. It's so bizarre. I mean, I then said run a sentiment analysis on data in that column. So it gives some mean sentiment analysis.

[1:08:20] generally positive sentiment across the responses, standard deviation, showing a moderate spread in the sentiment scores, minimum sentiment, [1:08:30] is... [1:08:31] minus 0.7. So I think [1:08:34] There must have been, there was obviously some people in there who put [1:08:37] It's called something... [1:08:39] off the scale that we wanted them to score, which was... [1:08:42] I guess, 1 to 10 or something. But this is where something I could have followed up with and said, what does that actually mean? This is really just a pulse check on, [1:08:52] can we do a analysis on subscribers in this way? Um, [1:08:57] And then... [1:08:58] Yeah, so it was... [1:09:00] It was interesting to see, but another thing that analyzing data – [1:09:05] to help run the business. [1:09:07] So not only from subscriber data, but I also use... [1:09:10] Something called Julius, which is what I tend to use for more [1:09:14] data, [1:09:15] like based stuff. And I'm an investor. [1:09:20] And obviously there's emails here to, [1:09:23] As you are in Lex, I think, right? [1:09:26] Yes, yeah. [1:09:29] So I had an issue with, this was for Pro, where there was people in Stripe who signed up for Pro. I could see it with subscribers. People in Beehive who'd signed up. [1:09:40] for premium [1:09:41] but there was some mismatch between the two. So I essentially just downloaded each CSV from Stripe and Beehive, [1:09:49] So check the emails in both of these files, identify the ones that are not in both files.

[1:09:53] Let's say there's 27 people not in each file. [1:09:57] And I said, turn all 27 emails and tell me which file has each name. So then I could see, okay, I know that in this certain file, [1:10:08] They have this email. [1:10:10] So I could actually just know, instead of trying to look through both... [1:10:16] like databases, bus spreadsheets, [1:10:19] Where is that? Where's the one that's missing? Is it in this one? Is it in that one? [1:10:23] So I did that. And then I... [1:10:25] I then went on to sort of say, like... [1:10:28] I try to do things like, are there any reasonable... [1:10:32] ways to correlate because essentially it was people who have [1:10:35] asked to have their email changed. So it was just more or less... [1:10:40] Someone on there had... [1:10:42] A personal email, wanted it to be a business one. [1:10:45] I've changed it. It doesn't reflect in Strife and Beehive the same. [1:10:49] So just making sure that [1:10:51] Are people paying and not getting access to it? Like, are we doing that? So things like that, which... [1:10:56] you [1:10:57] It's just like, okay, where do I start trying to do this? Is this a... [1:11:00] two-hour task, is this a two-minute task? And it turns more into a smaller task than... [1:11:06] than if I was trying to do this manually. I think for people who are watching or listening to this and haven't run a business themselves, it might be surprising to learn how many of these tasks there are, whether it's resolving who's actually paying you in Stripe or it's trying to understand, okay, what do customers actually think of us from the survey? All of those tasks, there's many, many, many tasks like that that pile up in a day to run a business. And all those tasks either require your time as a founder

[1:11:36] to do it for you, which costs money. And that's what makes, in a lot of ways, running these small, profitable businesses, [1:11:43] internet business's heart is you have to be able to like prioritize that stuff. You have to be able to know like which things you can do yourself and which things to, which things to farm out and which things to just not do at all. Like I know that cause I, I have to do that every, like we have five employees and it's, it's like this constant thing to figure out and it, [1:12:03] AI is, I think what we're seeing here is it's such a leverage point for running these kinds of businesses and it allows you to do so much more and, um, [1:12:14] and potentially scale more with much less cost either in money or your time. I think it's awesome. Yeah, I do too. I think it's more that you spend less time doing the things that you don't want to be spending any time on. [1:12:25] Um, [1:12:26] And it helps you [1:12:28] with the things that you want to spend time on, [1:12:30] do them more efficiently as well. So, [1:12:33] Like, that's a win all around. Like, obviously, I still get distracted with all other things and rabbit holes where AI is just there to help you go down all of them. But... [1:12:42] It's just... [1:12:42] Something that I think... [1:12:44] I kind of think back to if I was running MakePad 3, [1:12:47] today how differently would that business have looked [1:12:51] And would I have done things any differently would have a – [1:12:54] different bigger outcome, um, [1:12:57] any of those things and, [1:12:58] I think it's just, okay, well, it doesn't matter. I'll just try and think of that in this business now. [1:13:04] And there's just so much of it. I would have never dreamed that I would do a daily newsletter, never mind any newsletter. I never dreamed that I would be writing long-form content

[1:13:15] week in, week out, and like all of these things I'm doing now, [1:13:19] because I find the topic so interesting, and I think that other people do too. [1:13:23] And they tell me they do, like, obviously from surveys and all the rest of it. But – [1:13:29] It's just... [1:13:31] it's not that hard to do that stuff anymore. Like it's a lot easier to do most of the stuff that you need to do [1:13:36] to make something like this work. And AI just, it's also knowing which tool is right for you to do the right job. So like I showed a few different things there and sometimes it takes me, [1:13:47] a few tries in a few different places, but I've got the perseverance to do that because I know [1:13:51] the outcome is so much better than... [1:13:53] I'm going to sit here. [1:13:55] just bang in my head and then go to Twitter and scroll that for a bit and then just be distracted either way. I may as well try and hammer it out with... [1:14:02] a few different tool options rather than [1:14:04] None. [1:14:05] Totally. Totally. I love that. Well, I thought this was awesome. I honestly learned a lot. I've never actually seen typing minds. I've never seen Julius before. I'm so glad that you brought in Lex because you've never actually covered that on the show. So that's amazing. [1:14:35] I love Ben's Bytes Pro. Thank you so much for coming on, man. It was really great. [1:14:40] Yeah, I really appreciate it, and thanks for the love. And, yeah, it was real... [1:14:44] authentic moment of mentioning Lex because I do use it all the time. I forgot that you guys did incubate it. So that's a happy accident for everyone. Yeah, that's great. Love it. Cool. Well, see you around. Cheers, man.

[1:15:09] Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure, unadulterated knowledge bombs about chat GPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat. [1:15:27] 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 [1:15:35] So do yourself a favor. Hit like, smash subscribe and strap in for the ride of your life. [1:15:41] And now, without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.