Transcript: How to Run a Profitable One-person Internet Business Using AI

The transcript of How Do You Use ChatGPT? with Ben Tossell is below for paying subscribers.

Timestamps

1. Introduction: 01:02
2. How to use ChatGPT as a business strategist 14:40
3. Ben builds an MVP with ChatGPT 23:45
4. Use ChatGPT to kickstart your business 41:31
5. Ben uses AI to extract valuable information from internet rabbit holes 44:54
6. How to turn interview transcripts into compelling articles 54:51
7. Ben refines his blog post with Lex 59:34
8. Use ChatGPT to analyze business data 1:06:52
9. Offload time-consuming tasks to AI 1:09:11
10. How AI is enabling people to run profitable businesses with not a lot of resources 1:11:09

Transcript

Dan Shipper (00:00:00)

One thing you’re really good at is starting these one-man profitable internet businesses that are sneakily big.

Ben Tossell (00:00:06)

So Glassdoor is basically an anonymous site for people to leave a review on your employer.So I was like, 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? How did Glassdoor get reviews on the site initially? Did they run any incentives? I was looking at that kind of thing. So, things like that. It’s just an interesting way to start exploring an idea and where it’s gonna go and how it changes over time.

Dan Shipper (00:00:32)

One thing I'm seeing you do is when you think about a company that makes a product, the thing that you can see on the internet is sort of the tip of this iceberg, and it's 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. 

Dan Shipper (00:00:00)

Ben, welcome to the show. 

Ben Tossell (00:01:01)

Thank you for having me.

Dan Shipper (00:01:02)

It's great to have you. We've been friends for a while. For people who don't know, you run the Ben's Bites newsletter, which is a daily AI newsletter that I read every day. I love it. 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. And it's really fun to have you on the show.

Ben Tossell (00:01:33)

I appreciate the kind words and, yeah, it was kind of an accidental content media founder journey, but yeah. That’s what I am.

Dan Shipper (00:01:43)

I just sort of remember. I think this was a year ago, but I just started seeing this guy. Anytime someone would launch an AI demo, there was this guy that would just pop up underneath any one of their projects being like, hey, I just added this to my Ben’s Bites newsletter, you should subscribe. And, I was like, who is that guy?

Ben Tossell (00:02:02)

Yeah. That was another intentional thing that then other AI newsletters started copying as well. And I didn't realize it at the time. Actually, that's what Ryan Hoover did at Product Hunt. And I used to work at Product Hunt before I went and launched Makepad. It was just like, hey, yeah, you should post this on Product Hunt. And then it must have been in my brain somewhere. And I then started realizing that if Sundar from Google is posting something about the Google AI thing, if I could be quick enough to just put my link underneath, it was actually a really good way to start getting subscribers and you reaching the right audience in the right place. So that was a little hack that I didn't intentionally mean to be a hack, but it worked out well and everyone else started doing it. I stopped doing it, but yeah.

Dan Shipper (00:02:54)

That's amazing. Yeah. I'm curious, just high-level. I feel like a year ago was this big hype wave for AI and I think you and me both rode that to a certain extent and got a lot of traffic and a lot of—I don't know—just a lot of good stuff out of that wave. And I think that has started to dissipate, or at least it's changed and we're starting to enter—it's not like you can tweet some demo that you did with GPT-3 and it will just get a thousand likes immediately. We're less in the fancy demo hype phase and more we're actually starting to use this. I'm curious how things have changed for you or what you're thinking about right now in this current era of AI.

Ben Tossell (00:03:43)

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 ‘22, it was pre-ChatGPT. So it was definitely early. And then it was just riding 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. And then as we've come to sort of now 2024. Even my thinking of this is exhausting to get it out there. It's exhausting for someone who does this as a business to keep up with what's the appetite really like for everyone else consuming this stuff as well, where chat-with-your-PDF product number 57 is a new thing on Product Hunt or Hacker News or or whatever. Are we covering that again? Are we doing that kind of thing again? So, there's a lot of the same stuff. So, we're sort of thinking about that internally. And yeah, we launched Ben's Bites Pro in December where I speak similarly to what you're doing, I guess, where I chat with businesses and CEOs of things how they are using AI in their business and changing their organization and running it on products and stuff. ‘Cause I just think there's not that much out there. There's no Playbook on companies building with AI. And I think it's really interesting. So, yeah, we started doing that and getting some really interesting conversations. But, yeah, I don't know. I don't know what the future holds with all of the daily stuff like this. We always joked about it being just this massive firehose. It still is. And, are people's appetites changing towards, I actually want to know how to use this thing. I don't want, just tell me a new tool every single day.

Dan Shipper (00:05:39)

I feel that. I mean, I just love how bored you sounded talking about the next PDF tool. Number 57.

Ben Tossell (00:05:50)

I mean, again, this still goes back to my Product Hunt days. I was a community manager. It was my job to have companies be on the homepage and support their launches and also get in the comments and start people talking about it. And then I got to a point where it was probably a similar timeframe where I was like, 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 and maybe I haven't changed all that much since then, I guess, 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, oh, I've just done the same kind of thing as everyone else, it's slightly different because of this one thing. But equally, you see all these PDF products. There's plenty of them. You can do it in ChatGPT. And then there's companies like PDF AI making, I don't know, $200,000 monthly recurring revenue from just focusing on that one thing. So it's definitely 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 so yeah, that's why I'm biased. I'm jaded by it, I guess.

Dan Shipper (00:07:10)

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, how are people actually using it? And I think that's definitely the concept of this show is there's so much latent hype or latent energy around ChatGPT—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 kind of hard. And so, yeah, I feel we're sort of on the same wavelength there, giving people 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.

Ben Tossell (00:08:02)

Yeah. And I think that so many people come in with a question, get an answer. And they think that's what ChatGPT is. And I still do this today where I will do that multiple times a day and think, oh, I didn't do all these other tips and tricks and ways I can get sort of a better outcome. Sometimes you don't need that, but I think knowing that you have that there and then after sort of practicing unintentionally some of these tricks or whatever you'd call them, over time, you start recognizing that okay, that's a good way to get a good response from something. I think I've learned some from this podcast. I think Sahil showed just regenerating a bunch of stuff and then just going through the answers like, okay, yeah, I know how to do that. I just think, if there's an error, do that, but it's not really for that.

So, yeah, there's so many different ways people can use it, and it's one of those tools that I intentionally think of if I've got something that I'm going to search, which AI tool am I going to use first? And, should I use AI for this? And I don't know whether my appetite for, okay, I know it might take me a few minutes to go and do this on ChatGPT, on Perplexity, wherever, versus go to Google and do the work myself. 

I'd rather be sitting there doing the lazy work of prompting and asking and figuring out whether the answer was what I wanted rather than feeling like I'm doing the work, going through the blue links, going through the lists of lists of lists to then be like, I'm still not where I was trying to get to so I'm just using it for everything small and bigger at every moment of the day, I'm just always trying to default towards, let's use AI for this somehow. 

Dan Shipper (00:09:59)

Yeah, me too. I mean, one of the recurring ideas on this show is, I think, starting to think of yourself as a model manager rather than an individual contributor is a really powerful idea. 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 if you're thinking of yourself as a manager, one of the skills of a good manager is to know what 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 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 will get out what you put in. And so I think it's super important for that.

And it's also super important, you're talking about defaulting to not having to click through all the blue links and stuff like that.Yeah, that's sort of what a manager does. You're not necessarily in all the details all the time, but you can go in there sometimes if you need to. But being in that place is, I think, a little bit more of a management headspace than it is an individual contributor headspace. And I think that's really cool.

Ben Tossell (00:11:13)

When you wrote that piece and you sent it to me, I think I said something like, yeah, but I don't like being a manager. I don't want to be a manager. I can't ever think of myself like that. Well, I'm going to say, I'm pretty sure I wasn't a good manager when I ran my company. And it kind of feels like—I don't know—I'm trying to do whatever this thing is now. Maybe I don't want to call it a model manager, 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 ChatGPT for everything. Actually it didn't give me the right thing. Did I ask it the right thing to give me the right thing back? And you do have to think like that, but I'm certainly not thinking of myself like a manager. Maybe it's a branding problem, but yeah.

Dan Shipper (00:12:05)

Maybe I have to rebrand it, but I'm sticking with manager ‘cause I like being a manager. 

Cool. Well, I guess on that note, I would love to just get into this sort of 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. So to set it up, tell me a little bit about what kind of company research you're doing and why you would want to use ChatGPT for that.

Ben Tossell (00:12:39)

Yeah, I mean, I'm just trying to scroll to find it because it’s so far back. So, I'm just obsessed with business ideas. Always have been. It took me 50-plus ideas to get to Makepad which is the one thing that worked.

Dan Shipper (00:12:54)

Your last company.

Ben Tossell (00:12:55)

Yeah. So that's the one thing that worked and that was a byproduct of all the other things that didn't work because I was building them with no code. So I built a way, those who can't do, teach. So I told people I'd do that same thing. And then, with Ben's Bites, 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, I don't know, I just can't help but think, that's really interesting.

What if that was that for something else? I think most people think of startups as get on TechCrunch, get funding from YC and sort of shoot for the moon kind thing where they're never the kind of businesses I’ve—I don't say I wanted to build, I wanted to build them before I started building Makepad and then realized I just like this kind of business. Bootstrapped, took angel round, but I'm not looking for a billion-dollar outcome, probably because of the manager thing. I don't wanna be a manager of a 300,000-person company. But it's hard. 

And I think that the lifestyle branding on those businesses has ruined it a bit because okay, who doesn't want a $2 million year lifestyle business? That sounds great. So just think of products in terms of this company is doing this thing really interestingly, is there a space that this for X, Y, Z could be done similarly. Really, if you look at lots of businesses, all the business models, all the ways that they do business, are often pretty straightforward. You can see, okay, they do this thing, then this thing, then this thing. So it's just, for me, I like to throw businesses in there. I'd be like, what's a similar kind of business to this? And 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 like to do, so I put up a couple here. I'll share my screen now. 

So this was a chat I had with ChatGPT about a product called Yardstiq from the company CB insights. So they put together a bunch of valuation data, funding, fundraising. interesting things like that. But I think the product is tens of thousands of dollars a year to access. I'm not paying that. They have this spinoff product called Yardstiq about what software buyers really think about their vendors. 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 X? And then they’ll have a transcript, they record their conversations, and then if you're a fellow 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 what the customer support was like, you want to know what the onboarding was like. Look at other companies similar to yours, and sort of determine whether you're going to go down that road. So, they have just on the landing page, it says, “Enter a business email address, get a free trial.” And it just has a bunch of testimonials, essentially. It's effectively a very small snippet from the transcripts that they have. So, for example, I'm showing this one about Snowflake. “The economics of Snowflake give a huge advantage. Instead of spending $15 million, we decided we could at least probably save 70 percent in terms of the cost that we were expending on Teradata if we went with Snowflake.” 

So something like that is good to know if you're going to be spending millions on 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, again, I can't pay the thousands of dollars to go and sign up for this. So, I think I did some Google searches of Yardstiq product images. I looked back on some of the tweets from the CEO where they shared some screenshots here, there, and everywhere. And then this was one of the screenshots where it shows, okay, this is a Forta customer, a head of fraud at a $1 billion valuation startup. So they don't give you any identifying information. They sort of give you a highlight of the customer, their head of fraud; company, again, billion-dollar valuation startup; the role, key decision maker; purchase details, purchased on in Q3 2018; purchase amount, $250,000 a year; and, then it's got this transcript underneath, which, I assume as a customer, you could go and read. So it has subject subsections, introductions, evaluation, structure, solution, specific sales experience, deployment, competitors, pricing and packaging, post-deployment. And you can sort of see a small snippet again of one of those transcripts. So I thought, that's really interesting. I wonder if I could throw that into ChatGPT using image search and saying, what’s in this image? And that's literally how I started the conversation.

Dan Shipper (00:18:38)

That's interesting. I want to stop you there. So, you're coming across a website and the website is for a product that CB Insights is selling and you're curious about it. Are you curious about it from the perspective of what we were talking about earlier where you're thinking about, okay, could I build a product like this in a different category or, what's your curiosity? What are you trying to find out?

Ben Tossell (00:19:03)

I think there's probably a few: One is CB Insights is notoriously—well, they've got a lot of revenue. They've talked about it on podcasts. They have big customers who spend tens of thousands on this data as a product, and I'm pretty fascinated with data products as they are. I think it feels to me that you could build one or build versions of them with a one-person company, and you could get to $500,000 a year as a one-person company building some sort of database product in a specific niche.

The part of my curiosity is, what are the best of the best doing in this space? And then, if I boiled out that, if I sort of simmered that down to a simplified version for a different space or a different category, how would I go about doing that? And then, yeah, I just think it's kind of interesting to peek behind the scenes of enterprise companies that you can't ever see without jumping on the call with the sales rep, doing the free trials, all of that kind of stuff. And you just want to know if you're paying $30,000 a year, or whatever it is, what does a product like that look like on the inside? And to me, it looks like, hey, here's a transcript that we 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 research and reports and data that they pull together through machine learning and human analysts. But, if you cut all of that away and you just said, 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.

Dan Shipper (00:21:07)

That's amazing. Okay, I think I get it. And so, one thing that's happening or one thing I'm seeing you do is when you think about a company that makes a product, the thing that you can see on the internet is sort of the tip of this iceberg, and it's 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, okay, what do I wanna build if I wanna 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? What am I seeing? How is it constructed? All that kind of stuff. Is that right? 

Ben Tossell (00:21:05)

Yeah, definitely. Because I think you can sort of make assumptions on what work is needed under that sort of tip 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 because 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. And I just think if you can see, what does the output look like? And you can 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. And it becomes less scary to be like, I could never start a business like whatever that charges whatever to these kinds of people where I just think it makes business less daunting to think about in those terms of— I do believe that anyone can build most things, not big VC-funded companies, but most things to get a great 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 building really, really valuable companies that aren't venture backable, nor should they be, but it's still a great business. There's a really simple equation that goes into what does it take to build something that provides something valuable to customers that we can get thousands or tens of thousands of customers signing up for this and paying us.

Dan Shipper (00:23:33)

I love that. I love that and so now I think I kind of get where your head's at and how you're getting into the chat. So it sounds like what you did first is you just pasted the image in and you were like, what’s in the image. And talk us through what ChatGPT said and what you did next. 

Ben Tossell (00:23:52)

Yeah. So it says, “The image shows a webpage from CB insights. It seems to be a customer testimonial or case study from a company named Forta,” which is not true. It's a Forta customer. Main focus is sort of “gives some of those details of the customer, the purchase details. Below this, there is a transcript of the customer's feedback divided into sections such as introductions,” et cetera, “then on the left side, there's a column listing other customers who also purchased from Forta.” So it kind of changes what it first said, I suppose maybe if it's a case study for a company—maybe, I misinterpreted that looks like a professional business document. So normal ChatGPT fluff at the end and then 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,” because you can sort of see 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?” That, in my mind, gave it the sort of one example that it needed to then make some assumptions, so it came back with, “Introductions: Can you introduce yourself? Tell us about your role at the company. How does full prevention fit to your company's operations? Valuation structure? What criteria do you use to evaluate fraud-prevention solutions? How do you structure the process?” And then sort of there's plenty on here. “Sales experience: How was your experience with our sales team during the evaluation process? Deployment: Can you walk us through the deployment process of our solution?” Again, it's looking at it from a point of view of Forta asking these questions.

Dan Shipper (00:25:47)

I can sort of see you're 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? Was that what you wanted or is it off-base?

Ben Tossell (00:26:05)

Yeah. I was basically getting it to start from a point of, we have a minimum viable product, I guess, this is our very basic form for how we would go and ask people questions like this. And because I have no information other than what was on that screenshot, I also don't know. All these questions could be viable, it could be the right ones, it also could be completely hallucinated and no, that's not quite right. But I mean, given the subsections of evaluation structure, solution specifics. I think that helped guide it in a reasonable way that I could see that you could take that and say, okay, if I'm going to do a similar kind of data company where I'm going to interview people in whichever industry, I could use this as a blueprint to start my own transcripts or interview people.

Dan Shipper (00:27:00)

Got it. Okay, cool. And so, you've got the basic blueprint and then it looks like what you did is you pasted that original screenshot in from Yardstiq—the original screenshot with all the customer quotes. And what did you ask it?

Ben Tossell (00:27:15)

Yeah. So I went and I took a whole screenshot. So the full screenshot of the page with all of the quotes and I said, “Now look at the quotes on this image. They are snippets of other responses from different customers, talking about different software. Tweak the questions you just wrote based on what is mentioned in the image.” So just sort of refining. Are there any other insights that come out of that then would have been in response to a different question that you haven't included is essentially what I’m—well, maybe I should have said it that way, but that's sort of what I'm insinuating there. But it became less detailed than the first round. So, introductions, sort of similar. A lot of them are pretty—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, so I think if we look at just post-deployment, how has 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, since deploying the software, what have been the tangible outcomes and benefits for your organization?” So it's kind of those two questions kind of fit in that one question so I felt like, I don't know if that's enough. So then I found more images of more snippets of more transcripts. And I basically fed them in. So there were one, two, three, four, five, six, seven—seven images of transcripts. And then there's also something called a vendor scorecard, which is something from Yardstiq that they put in this example. There's Stripe, Checkout.com, and a few other payment solutions and they've got the overall satisfaction score, which is blurred out, win reasons, so you've got a better user experience integration with Shopify. So these are things that customers would have mentioned why they chose Stripe over any of the alternatives and opportunity areas, improving non-U.S. coverage. But these are things that people are obviously complaining about why they didn't use Stripe or where it could improve, even though they have to use Stripe. So, again, here are more images about Yardstiq, updated questions based off the information provided in these images. And again, it kind of does a similar thing. And it does change the sort of sections. So there's no introductions and things. It sort of goes off and ignores some of the basic stuff and ignores the original format.

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 I've done the same thing three times. I got three very same-y answers, or I can assume that's probably what the question was. That is most likely what the question is, given all of this data that is actually what it was, and there's no real way to tell I think taking gut instinct and deciding if I looked at all that information. And especially at one of the sections, say the deployment one again, if I looked at any answers relating to deployment, could I infer anything differently? Is there anything else I would add to that? Does it seem like that question would or should garner that kind of response that we're seeing in the examples.

Dan Shipper (00:31:23)

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, it doesn't do as good of a job unless you have it like, first of all, think through the what's in the screenshot. First, be like, what are the questions that were probably generated the answers in this screenshot? Have it say all that and then be like, can you modify the questions you've already created to include the new ones that you've done, because otherwise you're kind of smooshing 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.

Ben Tossell (00:32:13)

And then each time you're then 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 one at a time? 

Dan Shipper (00:32:27)

Let's try it. You want to try it?

Ben Tossell (00:32:28)

Yeah, sure. 

Dan Shipper (00:32:30)

Cool. I mean, I would do multiple images. I think that's fine. It's more like, generating the questions and then compressing them together into a new list based on old questions is sort of complicated for it right now. And it may not think everything through in the way that you want.

Ben Tossell (00:32:56)

Yeah. And then would you also re-add the original questions that it came up with?

Dan Shipper (00:33:05)

I would wait. I would do that later. So you can either do it in this chat or you can start a new one. I don't know how important this chat transcript is to you. I would just upload as many as you want—I think you can upload four total. And ask that original question, which is, what are the questions that you think generated that image? And I probably wouldn't use the original one because you already have good questions for that. I would use—the landing page one would be a good one, I think.

Ben Tossell (00:33:38)

Okay, 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. I'm going to see if it comes out with the actual questions. It's because it says here under competitors, you can see, well, “Alternative to the vendor: Have you considered what use cases does the vendor's product or solution serve for you today?”

So we have four images, one of the Yardstiq homepage with all sorts of snippets of transcripts. We've got two that have a screenshot of part of a transcript. So it has the questions in bold. And then there's one that is just a snippet of the transcript and there's no question in that image. So yeah, what should I ask it?

Dan Shipper (00:34:35)

Well, okay. If we're starting with something that gives an example of a question, I think we want to reference that. So it's probably something like, in the screenshots I'm attaching there are questions that get answered by the text, right, by the transcript. This is not precise. In the screenshot I'm attaching, there are questions that get answered by whoever is— We’re trying to reverse-engineer it, right? 

Ben Tossell (00:35:24)

Yeah, exactly. “In this case, I'm attaching snippets of various transcripts with customers of software groups, tools and then—”

Dan Shipper (00:35:48)

Sometimes the transcript includes a question that the customer is answering.

Ben Tossell (00:36:03)

Would you specify that and say it's in bold in the screenshot or not?

Dan Shipper (00:36:19)

Yeah, that's cool. I like that. 

“Based on the question answer pairs that you can see, for any transcript snippet that doesn't have a corresponding question, please try to generate the question that produced that answer,” and then I don't know if you want to do a couple little exhortations at the end that are like, “Be specific. Be thoughtful. Be detailed. I'll give you $2,000. I'll tip you $2,000 if you do it right.”

Ben Tossell (00:37:10)

I've never actually tried that.

Dan Shipper (00:37:11)

I love that one. I don't know if it works, but I do it all the time. It's just fun.

Ben Tossell (00:37:24)

Cool. Should we try that?

Dan Shipper (00:37:24)

Let's try it. I'm really curious. Part of me is a little worried that we should have broken it up where the principles from going from question to answer 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.

Ben Tossell (00:37:49)

Yeah. I don't know if it's not working 'cause it's an old ChatGPT 

Dan Shipper (00:37:55)

Is ChatGPT down?

Ben Tossell (00:38:05)

It was a bit finicky with me earlier oh—here we go. Okay. “Free each provided, generate questions from the screenshot, which is the full screenshot.

Okay. It's given us the answer first. So it's given us the actual quote from the homepage, but only two of them. There were obviously a lot on there so we use product name because it's the easiest CRM system in terms of service and customization, et cetera, et cetera. Possible question: “Could you explain why you chose the product name over other CRM systems like CleverTap and MessageBird?”

Dan Shipper (00:38:40)

What do you think of that?

Ben Tossell (00:38:42)

I think it's reasonable. I think I was kind of guess or knowing that they wouldn't put others—I guess I might be guessing wrong here. I see other software tool reviewers, they always just say what other vendors have used and why you choose this over any specifics. So we give it a more broad interpretation for the person being interviewed, but I think that's a good question. That would probably make it into the transcript question list I would set up. The next one is the reason why we didn't go with the product name. Because it was impossible to integrate Aiden with our website. Possible question: “What were the challenges or limitations you faced that led you to not choose product names for identity and access management?” I think again, that's pretty good but the question is almost the inverse. You're probably not asking them, or maybe that's more of a follow-up question. You're asking what products did you use and why versus what product didn't you use and why not?

Dan Shipper (00:39:57)

That makes sense. But 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 the same principle sort of holds. It's like the more you can break up the thinking steps into explicit steps that you ask it, sometimes, the better it does. I'm kind of curious for you once you did this exercise, I think you got a list of questions. Where did that leave you? Are you going to do this idea? What was your next step?

Ben Tossell (00:40:27)

Yeah. I think I looked at it as just looking back up, some things improve the landing page, copy off Yardstiq, that's a good one. Although I think Yardstiq actually has a really good landing page copy. So I think that's why I did it. It's because it was just so on the nose. Learn what software buyers really think about your vendors. The ChatGPT's version is, “Discover the unfiltered opinions of software buyers on their vendors.” That's not bad.

Dan Shipper (00:41:02)

I like the word unfiltered, you know?

Ben Tossell (00:41:04)

Yeah. I do too, and then, “Based on the below titles, group the quotes and text from all previous images into where they think best.” So I think I was reaching a bit here and it just sort of gave me generalized, okay, any comments where customers introduce themselves, their role or company, they didn't actually put in the quotes. So I think that's fair enough. And yeah, I mean, I don't think now, put quotes in the relevant categories. So if I'm going to do this, I'm trying to kickstart a crowdsourced anonymous, unfiltered review. I put user unfiltered there and filter review site for AI products or the best way to start that site and getting reviews. So this is something I actually have started and I've started getting anonymous unfiltered reviews and I think I grouped things into four categories, which is products, pricing, integration and deployment was one, and then competitors, so I have got a list of really interesting reviews from people using things like Cursor, LangChain, CoPilot, 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 who the buyer would be for this kind of thing.

Is it like a software review tool like G2 or something? Or is it more a business tool like CB Insights’ Yardstiq?

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, identifying your niche, researching competitors, website development,” et cetera, et cetera. So I was like, okay, just focus on the content collection part. I know the rest because I think that's the interesting part where again, I can make some assumptions on making a list of people you want to interview, 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. Realistically, I know that, but I think going through this process is just more fun, more interesting.

Dan Shipper (00:43:46)

And it might say something you wouldn't have thought of, or for anyone who's listening that doesn't know that off the top of their head, I think that's second nature to you because you're a second-time founder, third-time founder, you've been doing this for years and years. 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.

Ben Tossell (00:44:05)

Yeah, exactly. Do you know when this podcast is gonna go out?

Dan Shipper (00:44:09)

No. Probably in three or four weeks-ish.

Ben Tossell (00:44:14)

Okay. Well, this will be live by the time the podcast comes out, it'll be requestforai.com. So I'll get this done.

Dan Shipper (00:44:24)

That's amazing.

Ben Tossell (00:44:26)

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 a bit I wanted to focus on. It gave me some things like “initial content seeding, curating a list of popular and emerging AI products to start the conversation.” I did do that. “Hire contributors.” I basically just DMed it to a bunch of people who I trusted and would give reviews, yeah, user-generated content encouragements, be the first to review, “entice your users and then community engagement,” that's sort of a bit generic, “engage with AI communities on GitHub incentivization, offer awards for early reviewers,” 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, I don't know if I can see it. I can actually. So this is here. There's another chat about the Glassdoor founding story. So Glassdoor is basically an anonymous site for people to leave a review on your employer. Do you hate your boss? Is it horrible working hours? Is there good pay? Or that kind of thing. So I was like, 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 so I started with, “What's the founding story of Glassdoor? How do they monetize?” And it's really interesting that, yeah, they do job advertising, employer branding solutions. So if you're a good employer on Glassdoor, you can have an enhanced profile and you can have 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 Glassdoor profile.

And I found that quite interesting. It feels like that doesn’t not feel like that fits the purpose of the site in the first place, though. I'm there to give an unfiltered review on this thing, this company, yet this company is also on the same page or in the same place. It's trying to entice me to go and work there, they can be the same sort of thing being. I read this really good review. I'm going to go and do that. But also they could be very, very opposite. And then how did Glassdoor get reviews on the site initially? So were they running any incentives? So I was looking at that kind of thing. There's a give-to-get model. So their initial strategy was based on a give-to-get model access to a full range of information on the sites users have to contribute their own review or salary information. I did actually sign up for Glassdoor just to go through the process and see, ‘cause I couldn't see anything, and then left a review and then I could see some information. So things like that, it's just an interesting way to start exploring an idea and where it's going to go and how it works, how it changes at a time.

Dan Shipper (00:47:40)

Yeah, this is awesome. I love this. What I think this episode is about is— One thing you're really good at is starting these sort of one-man, small, profitable internet businesses that are sneakily big—or can get sneakily big over time, but that doesn'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 running into things on the internet, running into products and all that kind of stuff. And then you're kind of deconstructing them. How do they work? And how could I do that myself? Maybe with fewer resources? Maybe with a very small team without a lot of money and to do that, you're kind of like throwing in a ChatGPT, you're kind of looking at what's underneath the waterline. How is this made to some degree? And then also, it's pushing you in new directions where you're like, oh, I'm going to research Glassdoor. It creates this whole rabbit hole that you can go down, so you can get this clear picture in your head of, 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.

Ben Tossell (00:48:51)

Yeah. I think that's the bit where people get hung up initially, no one needs any more information on how to start a business because it's all out there. And if you keep doing that, you're just procrastinating on the fact that you could just do it today. But by doing little exercises like this, almost—not subconsciously, but just 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? And it's not necessarily that I'm going to go and start every single business that I think about and research. We might uncover something that's like, oh, that's interesting, I didn't realize 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, their monetization model is for the companies that are getting reviewed to get leads. 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. But to me, that feels like a really backwards way of thinking of that model. But that model clearly works because there's three or so companies that get millions—3 million, 4 million, 5 million—views a month for that kind of thing. But I guess in their interest as a platform, to then promote the products that people are reviewing ‘cause if you're a user, you actually just want to know the real what people are thinking, what people are using this thing for, and why is it good? Or why is it bad? That's the thing that I'm looking at in things like this, where I wouldn't maybe come across that if I hadn't started going down the rabbit hole of Yardstiq first. And then how does that get Glassdoor? And then how does that get to you? G2, how do they all sort of interlink? 

And I'm just in the middle of your episode with Steph Smith, who did Internet Pipes, which is great talking about going down rabbit holes and really just stuffing all this information in, not that it needs to all connect anywhere, but some things might spark something that's like, oh, that's a really interesting little piece of information 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.

Dan Shipper (00:51:35)

I love that. Yeah, I mean, that Steph Smith’s 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 just fun, but some of it becomes really valuable. What I think I want to do is it seems like we've sort of unpacked, okay, how do you identify opportunities for these kinds of internet businesses using AI? What I want to do next is do a little bit about how you use AI to run these businesses when you found something that's valuable, because I think you have a lot of ways that you're running Ben's Bites, which I think fits this profile of business that use AI that help make that process more efficient for you so in particular, one of the things you shared with me before the show is use it to highlight transcripts and annotate them so that you can turn them into useful articles and useful stuff for Ben’s Bites. Do you want to talk about that?

Ben Tossell (00:52:36)

Yeah, sure. So for this, I actually use TypingMind, which hopefully you can see on my screen now.

Dan Shipper (00:52:44)

Yeah, I can. What is TypingMind? I've actually never heard of it.

Ben Tossell (00:52:46)

So it's basically a ChatGPT tool, but you can choose a different model to use. So you can have Claude, GPT-4, now they've got Gemini, so you can do that. But also there's no token limit, so you can just dump in any amount of information you want and, I assume, will do all the chunking and stuff behind the scenes. I can't see it now, but somewhere it tells you how much it’s cost you to have this kind of conversation and, if I'm happy to spend 14 cents on transcribing,  or getting information out of a transcript, then I'm really, really happy to do that.

Dan Shipper (00:53:41)

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?

Ben Tossell (00:53:48)

I think it's the combination of two of those things. I used to have a Claude AI influencer’s account that it didn't cost me anything. And I could put anything I wanted in there so often with a podcast, I'd use a Chrome extension called Glasp that would basically pull the whole transcript into Claude and say, summarize this. I think you just ask the podcast question saying, where does Dan talk about this thing with Steph and pull out quotes, but I've must've been kicked off that now. So I haven't paid for that and I just use it to sort of get the prompt of the whole transcript now—copy that, bring it over here. And then sometimes I'd like to compare the two models. So instead of going to Claude, ChatGPT, Gemini, I'll do that in this one interface in different chats. So, yeah, with what I'm doing with Ben's Bites Pro, which is more long-form, probably about 2,000 words or so talking about talking with companies on how they use AI in their business. So one that is coming out this week is with the CEO of IgniteTech, which is an enterprise company. I basically had a conversation on Zoom or Google Meet with the founder, asked a bunch of 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 I'm going down rabbit holes that they're talking about and it's a lot of information. Often it's an hour-plus call. There's a lot in there, but 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 so ironic, but I'm like, okay, well, how am I going to go and now synthesize that information section it into the right place and figure out a good structure for how I'm going to write about this thing. Other people might have better solutions or muscle that they've built up over time to do that. But I think for me, it helps just 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. And reading through a transcript can be a bit dry. So I use Supernormal, which is what I use to record the calls and it pulls in my whole transcript. I copy that transcript over to something like TypingMind. I did try it with Gemini, which I'll show you, because that actually is literally when Gemini just came out.

Dan Shipper (00:56:25)

This is the new one from like a couple of weeks ago?

Ben Tossell (00:56:30)

Yeah. From last week. So what I had to do first. I basically tried to put the whole transcript in. Obviously it didn't work. Then I thought I can’t upload any files to Gemini, so how am I going to get this whole transcript into the model to then ask it to sort of section up the transcript? So 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 then than others probably are but I think then it's worth it in the end. So I put it in a Google Doc. I just pasted the transcript there. And then I said to Gemini, “Find my document titled ‘Eric Vaughan-Ben Tossel’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 sort of janky screen because for some reason, it hasn't saved in my Google Gemini but I said, “Sure. I found the document. Here are some key topics that you could write about in a blog post about how businesses using AI internally, how IgniteTech is using AI to drive cultural change.” And then it gives me three quotes where Eric talks about, “I presented an all hands meeting and said, ‘I'm going to give you everyone a gift. 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.’” 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. 

“How IgniteTech is using AI to improve its products.” Again, it's given me a few quotes where we announced to the world, all of our customers that we'll have an AI capability in all of our different divisions of products that we have. And then another one was, “The importance of leadership buy-in for AI adoption.” 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,” 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. What it does is it's this strange writing partner that helps me do a lot of the work. And again, this is mentioned in the episode you did with Steph where I could sit there for six hours and do this, pull out quotes, organize it, and then put it together in a certain way. Or, I could spend six minutes trying to get this into one of these models—Gemini, TypingMind—and actually pull out some stuff like, great, they are reasonable sections to start with, I can start writing about those sections. And then I sort of have further conversations on a good one. One thing I use it for quite a lot is here's my blog post towards the final edits, 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, yeah, these are the things that are important that I've mentioned in the post and it just helps me think about that and then how do I write that in a way that I would. And I use a tool called Lex, so Lex.page. That's got AI built into it. I'm happy to show you that if you do.

Dan Shipper (01:00:11)

Please do! I mean, I'm obviously familiar with Lex. We incubated it.

Ben Tossell (01:00:16)

Of course you did, so you'll be happy to know that I'm using it.

Dan Shipper (01:00:22)

I’m very happy.

Ben Tossell (01:00:23)

So this is the post, “How IgniteTech's team uses AI.” So we've got takeaways here, “driving cultural change with AI,” as you might be sort of feeling familiar with that, as I just mentioned. So it helps me write these posts and put in quotes. And then I go deeper—and much deeper—on it.

Dan Shipper (01:00:46)

Yeah, just over 2,000 words.

Ben Tossell (01:00:47)

And what I really like about using this is versions. So I could dump a load of notes in, I think, in my version one, I've even got AI drafts. So this is where Claude called out the transcript stuff and mentioned sections that I could talk about. And then here is GPT-4 doing the same thing. Here is Gemini doing the same thing and I sometimes put in how are they drafting it and it's just a way to bounce things off with someone else. If I feel like I'm not a writer and I'm always staring at a blank screen or a blank section, how do I get that thing written? It's always better to go—for me anyway, something really horrible that kind of says the same thing that I want to say, but actually I'm going to say that in my own way now, thanks for the help. I don't need you anymore. But, again, this is sort of the same with the business. I don't need to think of a whole new business model, a whole brand new idea that's never been heard of or done before. What works somewhere, take it, remix it and make it your own then. So yeah, I put a bunch of these drafts in here. And then version two is actually my written version. And then my favorite part of all of this is at the end, I'll do this, AI run checks.

Dan Shipper (01:02:10)

I was going to ask you about checks.

Ben Tossell (01:02:12)

Yes. So I do use them. I only use them for gravity and readability. So effectively, I'll do it now. It'll run through and show, okay, you shouldn't say, “today.” You shouldn't say, “radically.” “Modernizes,” it'll change to American, which is not what I'm doing. So I'm from the UK, okay. It really helps me at the end, I think, I could have said this so much shorter. This is so many, ‘cause I kind of write how I speak. So you can probably tell if you're listening to this, that I kind of speak all over the place and that's just how I do it. So whatever that means for my writing, it needs to be also clear enough for the reader. So I think just having these checks really helps me flick through. What can I say here? Okay. Okay. That's how I talk. That's how I sort of introduce posts. 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 it is radically changing their company. So I'm actually just going to keep it. And 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 a lot of AI baked in there in different places, so I hope that's interesting.

Dan Shipper (01:03:37)

That's awesome. I love it. I mean just to put all of this together, there are all these different parts in this process of creating this product, which is Ben's Bites Pro, that requires a decent amount of drudgery. It's not all roses and butterflies. It's not all exciting stuff and, especially if you're a one-man or couple-person business that you're trying to scale, you're trying to make it really profitable, but you're not going to go hire 1,000 people to do all the work for you. These kinds of tools, whether it's a Gemini or Claude or Lex, which incorporates all those things, or TypingMind, 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 an incredibly important and valuable tool for anyone who wants to start profitable internet businesses. I think it's really cool.

Ben Tossell (01:04:34)

Yeah. And I try and bake it in everywhere where I want to be the one that's written this post. I don't want to go and give it to an editor. I don't want someone else to do a first draft and then me come to it because none of my thinking has gone into creating that structure, that format. The exciting part is having the call, having the conversation. That's really easy. And that's great. If I could just one-click that goes to exactly how I would write it and fine. But I don't think that's reasonable to think. I also like to try and put a spin on it. I'll put some commentary around a lot of the things we talked about or takeaways for other people reading this to be like, okay, cool, how should I maybe think about doing that similar thing in my company? And it's just, I could have maybe done this a few years ago. I wouldn't have ever dreamt of it. And I think I only decided to do Pro now, which is one of these long posts a week because I actually can get it out. I can get it to a decent quality that people are signing up for and people are really loving. It’s all done with me, I'm the only one who touches Pro and—I don't know—it doesn't feel like that drudgery anymore. There's still issues with writing and figuring out what you're going to write next week, and the week after, and all the rest of it. But the actual process of creating a post is so much more fluid now and having these like AI sparring partners makes it so much easier and more enjoyable to actually put together.

Dan Shipper (01:06:16)

Totally. That makes a lot of sense. And we started with this using AI for business identification. And then we kind of got into this middle section where we're talking about using AI 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 sort of put in it in this other bucket, which is, once you have a product out there, figuring out how well it's doing so that you know what to change, is really important and it sounds like you're using ChatGPT to do some of that analysis for you, which is to gather some feedback, gather some survey data and then try to understand, okay, what do customers think of the product and how can I improve it, which I think is also really cool.

Ben Tossell (01:07:10)

Yeah, so we did this recently. There's probably some emails in here that might come through. It looks like it's okay. We had a survey of subscribers and I'll ask them why they continue to stay subscribed. Their answers were in a CSV that I attached, “Focus on the information in Column A, read the answers, then summarize how the majority of people feel you can ignore any outlier outliers or anomalies.” I don't think it really did that but yeah, it sort of talks about how people really appreciate the content, especially in using new tool sections, which are the main sections that we have. So that makes sense. “Accessibility and format: People value the newsletter's ability to keep them informed in such a quick, easy-to-understand way staying updated cost. The fact that the newsletter is free is a fact of a stay and subscribe.” And then, this is what I would count as an anomaly or outlier, but at least one respondent mentioned inertia is a reason for staying subscribed.

Dan Shipper (01:08:28)

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 subscriber because of inertia.

Ben Tossell (01:08:36)

Yeah, I know. It's so bizarre. I then said, run a sentiment analysis on the data in that column so it gives some mean sentiment—generally positive sentiment across the responses, standard deviation, showing a moderate spread in the sentiment scores. Minimum sentiment is minus 0.7. So I think there were obviously some people in there who scored something off the scale that we wanted them to score, which was, 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, can we do an analysis on subscribers in this way? And then, yeah, it was interesting to see, but another thing that analyzing data to help run the business. So not only from subscriber data, but I also use something called Julius, which is what I tend to use for more data-based stuff and I'm an investor and obviously there's emails here too.

Dan Shipper (01:09:52)

As you are in Lex, I think, right?

Ben Tossell (01:09:55)

Yes. So I had an issue with this for Pro where there were people in Stripe who'd signed up for Pro. I could see it with subscribers, people in Beehiiv who'd signed up for Premium, but there was some mismatch between the two. So essentially just downloaded each CSV from Stripe and Beehiiv, said, “Check the emails in both of these files, identify the ones that are not in both files,” and I said, right, “There's 27 people not in each file.” 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, they have this email. So I could actually just know, instead of trying to look through both databases, both spreadsheets, where is that? Where's the one that's missing? Is it in this one? Is it in that one? So I did that. And then I then went on to sort of say, are there any reasonable ways to correlate with, because essentially it was people who have asked to have their email changed. So it was just more or less, someone on there had a personal email, wanted to be a business one, I've changed it doesn't reflect in Stripe and Beehiiv the same, so just making sure that people paying and not getting access to it, are we doing that? So things like that, which is just, okay, where do I start trying to do this? Is this a two-hour task? Is this a two-minute task? And it is more into a smaller task than if I was trying to do this manually.

Dan Shipper (01:11:37)

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? There's many, many, many tasks that pile up in a day to run a business. And all those tasks either require your time as a founder, or you have to hire someone to do it for you, which costs money. And that's what makes, in a lot of ways, running these small, profitable internet businesses, hard if you have to be able to prioritize that stuff. You have to be able to know which things you can do yourself, and which things to farm out, and which things to just not do it all. I know that ‘cause I have to do that at Every—we have five employees. And it's just this constant thing to figure out and AI, 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 and potentially scale more with much less cost either in money or your time. I think it's awesome.

Ben Tossell (01:12:48)

Yeah. I think it's more that you spend less time doing the things that you don't want to be spending any time on and it helps you with the things that you want to spend time on, do them more efficiently as well. So, that's a win all around. 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 it's just something that I think, back to if I was running Makepad today, how differently would that business have looked? And would I have done things any differently? Would it have a different bigger outcome? Any of those things and I think it's just okay. Well, does it matter? I'll just try and think of that in this business now. 

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'd be writing long-form content week in, week out. And all of these things I'm doing now, because I find the topic so interesting, and I think that other people do too. And they tell me they do, obviously, from surveys and all the rest of it. But it's not that hard to do that stuff anymore. It’s a lot easier to do most of the stuff that you need to do 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 I showed a few different things there and sometimes it takes me a few tries in a few different places, but I've got the perseverance to do that because I know the outcome is so much better than, I'm going to sit here just banging 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 a few different tool options rather than none.

Dan Shipper (01:14:34)

Totally, totally. I love that. Well, I thought this is awesome . I honestly learned a lot. I've never actually seen TypingMind. I have never seen Julius before. I'm so glad that you brought in Lex because we've never actually covered that on the show. So, that's amazing. And I just love being able to see the kinds of opportunities for starting businesses that AI is opening up and I think you're the perfect person to show that to people. I love Ben's Bites. I love Ben's Bites Pro. Thank you so much for coming on, man. It's really great.

Ben Tossell (01:15:09)

Yeah, I really appreciate it. And thanks for the love. And yeah, it was a real 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.

Dan Shipper (01:15:20)

Yeah, that's great. Love it. Cool. Well, see you around.

Ben Tossell (01:15:23)

Cheers, man.