Jason Cohen Built Two Unicorns. Here’s The Only AI Startup He’d Build in 2026

AI doesn't really work. What do we do AI doesn't really work. What do we do with that? Um because people say, "Well, with that? Um because people say, "Well, with that? Um because people say, "Well, over time it'll get better." Like, "All over time it'll get better." Like, "All over time it'll get better." Like, "All right, but you're building a company right, but you're building a company right, but you're building a company now." now." now." >> That's Jason Cohen. He's built two >> That's Jason Cohen. He's built two >> That's Jason Cohen. He's built two billion dollar companies, WP Engine and billion dollar companies, WP Engine and billion dollar companies, WP Engine and Smart Bear. He's been writing about Smart Bear. He's been writing about Smart Bear. He's been writing about startup strategy at a smartbear.com for startup strategy at a smartbear.com for startup strategy at a smartbear.com for almost 20 years, and he's one of the almost 20 years, and he's one of the almost 20 years, and he's one of the sharpest thinkers I know on what sharpest thinkers I know on what sharpest thinkers I know on what actually works in startups. I sat down actually works in startups. I sat down actually works in startups. I sat down with Jason to talk about AI. Not the with Jason to talk about AI. Not the with Jason to talk about AI. Not the hype, but the real question founders are hype, but the real question founders are hype, but the real question founders are dealing with right now. If he were dealing with right now. If he were dealing with right now. If he were starting a new company today, how would starting a new company today, how would starting a new company today, how would he think about [music] it? He didn't he think about [music] it? He didn't he think about [music] it? He didn't give me a simple answer. He broke it give me a simple answer. He broke it give me a simple answer. He broke it into three types of AI products. Which into three types of AI products. Which into three types of AI products. Which one he'd bet on, which one he'd avoid, one he'd bet on, which one he'd avoid, one he'd bet on, which one he'd avoid, and why he thinks most founders are and why he thinks most founders are and why he thinks most founders are framing the whole thing wrong. Jason's framing the whole thing wrong. Jason's framing the whole thing wrong. Jason's been doing this for 25 years. been doing this for 25 years. been doing this for 25 years. Bootstrapped, venturebacked, started Bootstrapped, venturebacked, started Bootstrapped, venturebacked, started companies, sold companies. So, I asked companies, sold companies. So, I asked companies, sold companies. So, I asked him, if you were starting from scratch him, if you were starting from scratch him, if you were starting from scratch today, how would you approach AI? today, how would you approach AI? today, how would you approach AI? >> Yeah, it's a big topic. First of all, I >> Yeah, it's a big topic. First of all, I >> Yeah, it's a big topic. First of all, I separate how I use AI operationally to separate how I use AI operationally to separate how I use AI operationally to do stuff like write code or write do stuff like write code or write do stuff like write code or write marketing from AI that's in the product marketing from AI that's in the product marketing from AI that's in the product that the customers use whether directly that the customers use whether directly that the customers use whether directly or indirectly. So, first of all, take or indirectly. So, first of all, take or indirectly. So, first of all, take all that operational stuff. Let's set all that operational stuff. Let's set all that operational stuff. Let's set that aside cuz I I don't think that's that aside cuz I I don't think that's that aside cuz I I don't think that's what you were asking. But I find that in what you were asking. But I find that in what you were asking. But I find that in conversations sometimes people start conversations sometimes people start conversations sometimes people start confusing that. It just makes it more confusing that. It just makes it more confusing that. It just makes it more difficult to deal with an already difficult to deal with an already difficult to deal with an already complicated or complex question, right?

complicated or complex question, right? complicated or complex question, right? So, let's just ignore that. It is true So, let's just ignore that. It is true So, let's just ignore that. It is true that corporate budgets now are heavily that corporate budgets now are heavily that corporate budgets now are heavily biased toward things that are AI, biased toward things that are AI, biased toward things that are AI, whatever that means. And it's a fuzzy whatever that means. And it's a fuzzy whatever that means. And it's a fuzzy thing like the companies themselves are thing like the companies themselves are thing like the companies themselves are not clear on what that means. So, we not clear on what that means. So, we not clear on what that means. So, we have to be fuzzy. That tells me that have to be fuzzy. That tells me that have to be fuzzy. That tells me that whatever I do does need an AI component whatever I do does need an AI component whatever I do does need an AI component somehow because that's where the budgets somehow because that's where the budgets somehow because that's where the budgets are. That doesn't tell me what to build, are. That doesn't tell me what to build, are. That doesn't tell me what to build, but the idea of like, well, it just but the idea of like, well, it just but the idea of like, well, it just won't have AI at all. It'll just be a won't have AI at all. It'll just be a won't have AI at all. It'll just be a typical thing. That could be a good typical thing. That could be a good typical thing. That could be a good idea, by the way. Um, but I would worry idea, by the way. Um, but I would worry idea, by the way. Um, but I would worry that that I'll be fighting a budget that that I'll be fighting a budget that that I'll be fighting a budget battle and an attention battle. And so battle and an attention battle. And so battle and an attention battle. And so that doesn't feel like the easiest path. that doesn't feel like the easiest path. that doesn't feel like the easiest path. >> So if AI is where the budgets are, >> So if AI is where the budgets are, >> So if AI is where the budgets are, shouldn't we all just be building AI shouldn't we all just be building AI shouldn't we all just be building AI products? Here's where Jason sees products? Here's where Jason sees products? Here's where Jason sees founders going wrong. founders going wrong. founders going wrong. >> The wrong way to think of it is I need >> The wrong way to think of it is I need >> The wrong way to think of it is I need an AI product. That may be how the an AI product. That may be how the an AI product. That may be how the budget is. So you may, you know, that budget is. So you may, you know, that budget is. So you may, you know, that may be down the line how you, you know, may be down the line how you, you know, may be down the line how you, you know, sometimes how you talk about, but this sometimes how you talk about, but this sometimes how you talk about, but this is another thing I see people doing is another thing I see people doing is another thing I see people doing wrong constantly, which is thinking of wrong constantly, which is thinking of wrong constantly, which is thinking of AI as if people want AI as the problem AI as if people want AI as the problem AI as if people want AI as the problem they're solving. So let me let me put they're solving. So let me let me put they're solving. So let me let me put that differently. People have the same that differently. People have the same that differently. People have the same problems today as they've always had. problems today as they've always had. problems today as they've always had. Marketers want more leads. Sales wants Marketers want more leads. Sales wants Marketers want more leads. Sales wants to convert more leads to a sale that to convert more leads to a sale that to convert more leads to a sale that stay. Customer service wants to do have stay. Customer service wants to do have stay. Customer service wants to do have good customer service and get good, you good customer service and get good, you good customer service and get good, you know, results from from customers. You know, results from from customers. You know, results from from customers. You know, engineers want to write code that know, engineers want to write code that know, engineers want to write code that doesn't have bugs that's maintain doesn't have bugs that's maintain doesn't have bugs that's maintain manageable. Product managers want to manageable. Product managers want to manageable. Product managers want to build. Okay, everyone wants the same build. Okay, everyone wants the same build. Okay, everyone wants the same crap that they've always wanted. What crap that they've always wanted. What crap that they've always wanted. What you don't say is like I need AI in you don't say is like I need AI in you don't say is like I need AI in sales. What you do you do say is if I sales. What you do you do say is if I sales. What you do you do say is if I could 10x my outbound volume with the could 10x my outbound volume with the could 10x my outbound volume with the same conversion rate, that would sure be same conversion rate, that would sure be same conversion rate, that would sure be nice. So people talk about AI like it's nice. So people talk about AI like it's nice. So people talk about AI like it's part of the problem to solve or that part of the problem to solve or that part of the problem to solve or that people want AI. False. AI is part of the

people want AI. False. AI is part of the people want AI. False. AI is part of the solution space. How is it that I can solution space. How is it that I can solution space. How is it that I can deliver more of what they already wanted deliver more of what they already wanted deliver more of what they already wanted because of AI. AI has made something because of AI. AI has made something because of AI. AI has made something possible that was previously impossible possible that was previously impossible possible that was previously impossible that they already wanted. So as soon as that they already wanted. So as soon as that they already wanted. So as soon as it's like it's an AI voice thing, I'm it's like it's an AI voice thing, I'm it's like it's an AI voice thing, I'm like I don't know what that means. like I don't know what that means. like I don't know what that means. Whereas if you said for restaurants, we Whereas if you said for restaurants, we Whereas if you said for restaurants, we take over their phone tree because we take over their phone tree because we take over their phone tree because we can do the menu, we can do the ordering, can do the menu, we can do the ordering, can do the menu, we can do the ordering, we can do hours, but we do it on the we can do hours, but we do it on the we can do hours, but we do it on the first ring and in 40 languages. Now first ring and in 40 languages. Now first ring and in 40 languages. Now behind there is voice AI. That's what's behind there is voice AI. That's what's behind there is voice AI. That's what's behi that otherwise that's not possible. behi that otherwise that's not possible. behi that otherwise that's not possible. But the thing you're solving is your But the thing you're solving is your But the thing you're solving is your phone. Your phone calls are are now phone. Your phone calls are are now phone. Your phone calls are are now automated and awesome. And so I think uh automated and awesome. And so I think uh automated and awesome. And so I think uh when you stay focused on the problem when you stay focused on the problem when you stay focused on the problem that already existed and AI is why you that already existed and AI is why you that already existed and AI is why you can do something that was never done can do something that was never done can do something that was never done before or better. That's the right way before or better. That's the right way before or better. That's the right way to think of it. So I'd be thinking of AI to think of it. So I'd be thinking of AI to think of it. So I'd be thinking of AI as the solution space, not as people say as the solution space, not as people say as the solution space, not as people say and they even say in their pitch decks and they even say in their pitch decks and they even say in their pitch decks as the problem space. Another thing I as the problem space. Another thing I as the problem space. Another thing I would do is I would say look AI doesn't would do is I would say look AI doesn't would do is I would say look AI doesn't really work. I know we it's like but really work. I know we it's like but really work. I know we it's like but when it does it's amazing. Oh I know. when it does it's amazing. Oh I know. when it does it's amazing. Oh I know. when it does is a pretty big qualifier. when it does is a pretty big qualifier. when it does is a pretty big qualifier. When I research stuff for the book, I When I research stuff for the book, I When I research stuff for the book, I would say at least half the time it's would say at least half the time it's would say at least half the time it's simply wrong. Even when you do the deep simply wrong. Even when you do the deep simply wrong. Even when you do the deep summary, the deep, you know, research, summary, the deep, you know, research, summary, the deep, you know, research, it sounds good when they say it and then it sounds good when they say it and then it sounds good when they say it and then I go read the primary sources and it's I go read the primary sources and it's I go read the primary sources and it's like completely wrong half the time. And like completely wrong half the time. And like completely wrong half the time. And so what do we do with that? Um cuz so what do we do with that? Um cuz so what do we do with that? Um cuz people say, well, over time it'll get people say, well, over time it'll get people say, well, over time it'll get better. Like, all right, but you're better. Like, all right, but you're better. Like, all right, but you're building a company now.

building a company now. building a company now. >> This is the tension every founder is >> This is the tension every founder is >> This is the tension every founder is dealing with right now. You can't wait dealing with right now. You can't wait dealing with right now. You can't wait for AI to be perfect, but you also can't for AI to be perfect, but you also can't for AI to be perfect, but you also can't ignore that it's unreliable. I asked ignore that it's unreliable. I asked ignore that it's unreliable. I asked Jason how he thinks about what's Jason how he thinks about what's Jason how he thinks about what's actually buildable today. To me, there's actually buildable today. To me, there's actually buildable today. To me, there's three kind of categories of AI products three kind of categories of AI products three kind of categories of AI products right now. One is AI that the incumbents right now. One is AI that the incumbents right now. One is AI that the incumbents are inserting into existing products. are inserting into existing products. are inserting into existing products. This is like notion and you can talk to This is like notion and you can talk to This is like notion and you can talk to notion and sheets. You can talk to notion and sheets. You can talk to notion and sheets. You can talk to sheets. That's not going very well. Like sheets. That's not going very well. Like sheets. That's not going very well. Like it's not very useful, right? Okay. it's not very useful, right? Okay. it's not very useful, right? Okay. Whatever. But of course, they're doing Whatever. But of course, they're doing Whatever. But of course, they're doing that. What else are they going to do? I that. What else are they going to do? I that. What else are they going to do? I would do it too. But okay. The second would do it too. But okay. The second would do it too. But okay. The second kind is AI for experts. I'm already a kind is AI for experts. I'm already a kind is AI for experts. I'm already a software developer. Here's AI that helps software developer. Here's AI that helps software developer. Here's AI that helps me write code. I'm already a marketing me write code. I'm already a marketing me write code. I'm already a marketing writer. here's AI that helps me write writer. here's AI that helps me write writer. here's AI that helps me write articles or do social media or articles or do social media or articles or do social media or something. I'm already a designer. something. I'm already a designer. something. I'm already a designer. Here's AI that helps me design. So, AI Here's AI that helps me design. So, AI Here's AI that helps me design. So, AI for professionals. Bad news is that for professionals. Bad news is that for professionals. Bad news is that you're selling to only those you're selling to only those you're selling to only those professionals, not like the whole world professionals, not like the whole world professionals, not like the whole world or something. Um, and you're up against or something. Um, and you're up against or something. Um, and you're up against the incumbents. Okay. But if as a the incumbents. Okay. But if as a the incumbents. Okay. But if as a startup, that's what you are. The good startup, that's what you are. The good startup, that's what you are. The good news is it's okay that the AI isn't news is it's okay that the AI isn't news is it's okay that the AI isn't perfect because it's an expert. So, when perfect because it's an expert. So, when perfect because it's an expert. So, when the code is wrong, the expert can fix the code is wrong, the expert can fix the code is wrong, the expert can fix it. When the writing's bad or wrong, the it. When the writing's bad or wrong, the it. When the writing's bad or wrong, the marketer can fix it and so on. So, it marketer can fix it and so on. So, it marketer can fix it and so on. So, it handles the fact that the AI is not handles the fact that the AI is not handles the fact that the AI is not perfect. This is why I like this perfect. This is why I like this perfect. This is why I like this category. The third category is AI for category. The third category is AI for category. The third category is AI for noobs or AI for muggles, I like to say, noobs or AI for muggles, I like to say, noobs or AI for muggles, I like to say, right? I'm not a software engineer. I right? I'm not a software engineer. I right? I'm not a software engineer. I want to make an app. I'm not a writer. I want to make an app. I'm not a writer. I want to make an app. I'm not a writer. I want to write a book. I'm not a want to write a book. I'm not a want to write a book. I'm not a designer. I want a website. Now, that's designer. I want a website. Now, that's designer. I want a website. Now, that's good. I'm not saying like that's bad. I good. I'm not saying like that's bad. I good. I'm not saying like that's bad. I get it. Like, it's empowering. It's get it. Like, it's empowering. It's get it. Like, it's empowering. It's good. Like, I'm not against it by any good. Like, I'm not against it by any good. Like, I'm not against it by any means, but we're talking about what means, but we're talking about what means, but we're talking about what business I would build, right? And the business I would build, right? And the business I would build, right? And the problem here is you get 70% 80% and then problem here is you get 70% 80% and then problem here is you get 70% 80% and then you're stuck. And as a noob, you are

you're stuck. And as a noob, you are you're stuck. And as a noob, you are actually stuck. when I vibe code the SAS actually stuck. when I vibe code the SAS actually stuck. when I vibe code the SAS and I don't know anything about code and and I don't know anything about code and and I don't know anything about code and I'm like 80% I can't build a SAS company I'm like 80% I can't build a SAS company I'm like 80% I can't build a SAS company and I don't you know there's a lot of and I don't you know there's a lot of and I don't you know there's a lot of like I did this like I know but it's not like I did this like I know but it's not like I did this like I know but it's not a SAS company right if that's what you a SAS company right if that's what you a SAS company right if that's what you were going for that didn't happen and were going for that didn't happen and were going for that didn't happen and you can go down the line like if you're you can go down the line like if you're you can go down the line like if you're not this or that it it's not going to not this or that it it's not going to not this or that it it's not going to and you can't fix it you can't take it and you can't fix it you can't take it and you can't fix it you can't take it down the line you can't cuz you're stuck down the line you can't cuz you're stuck down the line you can't cuz you're stuck so the good news is the market's bigger so the good news is the market's bigger so the good news is the market's bigger because there's you know hundred times because there's you know hundred times because there's you know hundred times or thousand times more people that want or thousand times more people that want or thousand times more people that want a website than people that can build a a website than people that can build a a website than people that can build a website so hooray but here's here's the website so hooray but here's here's the website so hooray but here's here's the biggest problem is that the fact that AI biggest problem is that the fact that AI biggest problem is that the fact that AI doesn't really work is like a mass doesn't really work is like a mass doesn't really work is like a mass passive hindrance, possibly a 100% passive hindrance, possibly a 100% passive hindrance, possibly a 100% hindrance. So, that's okay. Like, if hindrance. So, that's okay. Like, if hindrance. So, that's okay. Like, if that's what you want to do, like take that's what you want to do, like take that's what you want to do, like take that. If you like that trade-off, go for that. If you like that trade-off, go for that. If you like that trade-off, go for it, right? I'm not I'm not I'm not it, right? I'm not I'm not I'm not it, right? I'm not I'm not I'm not judging. I'm just saying what I think judging. I'm just saying what I think judging. I'm just saying what I think the trade-offs are. For me personally, the trade-offs are. For me personally, the trade-offs are. For me personally, I'm always a problem solution sort of a I'm always a problem solution sort of a I'm always a problem solution sort of a entrepreneur. Like, everything I've done entrepreneur. Like, everything I've done entrepreneur. Like, everything I've done is like, oh, I can make this better, you is like, oh, I can make this better, you is like, oh, I can make this better, you know, whatever. Like, there's this know, whatever. Like, there's this know, whatever. Like, there's this corporate thing that that needs to be corporate thing that that needs to be corporate thing that that needs to be done or could be done. I can make it done or could be done. I can make it done or could be done. I can make it better. The typical B2B mindset. So, better. The typical B2B mindset. So, better. The typical B2B mindset. So, that's what I have. AI doesn't work yet. that's what I have. AI doesn't work yet. that's what I have. AI doesn't work yet. So, let's give it to people who for whom So, let's give it to people who for whom So, let's give it to people who for whom that's that weakness is not a that's that weakness is not a that's that weakness is not a dealbreaker.

dealbreaker. dealbreaker. >> In a minute, Jason's going to talk about >> In a minute, Jason's going to talk about >> In a minute, Jason's going to talk about what he would do if he was building a what he would do if he was building a what he would do if he was building a new company using AI. But first, Tiny new company using AI. But first, Tiny new company using AI. But first, Tiny Seed applications for our spring 2026 Seed applications for our spring 2026 Seed applications for our spring 2026 accelerator batch are open now. Tiny accelerator batch are open now. Tiny accelerator batch are open now. Tiny Seed is the year-long accelerator that I Seed is the year-long accelerator that I Seed is the year-long accelerator that I run for ambitious B2B SAS companies that run for ambitious B2B SAS companies that run for ambitious B2B SAS companies that are looking for the right amount of are looking for the right amount of are looking for the right amount of funding, a community of like-minded funding, a community of like-minded funding, a community of like-minded founders, and mentorship from a roster founders, and mentorship from a roster founders, and mentorship from a roster of world-class mentors. Jason is both an of world-class mentors. Jason is both an of world-class mentors. Jason is both an investor and a mentor in Tiny Seed and investor and a mentor in Tiny Seed and investor and a mentor in Tiny Seed and is kicking around in our private Slack, is kicking around in our private Slack, is kicking around in our private Slack, occasionally dropping the kinds of occasionally dropping the kinds of occasionally dropping the kinds of insights you're hearing in this insights you're hearing in this insights you're hearing in this conversation. If you're building B2B SAS conversation. If you're building B2B SAS conversation. If you're building B2B SAS and have at least $500 in MR and you and have at least $500 in MR and you and have at least $500 in MR and you want founders like Jason in your corner, want founders like Jason in your corner, want founders like Jason in your corner, apply at tiny seed.com/apply. apply at tiny seed.com/apply. apply at tiny seed.com/apply. All right, back to Jason. All right, back to Jason. All right, back to Jason. >> So, if I were doing a company, I would >> So, if I were doing a company, I would >> So, if I were doing a company, I would be solving a real problem that already be solving a real problem that already be solving a real problem that already existed. Of course, that has budget, existed. Of course, that has budget, existed. Of course, that has budget, probably budget for AI. Okay, fine. I probably budget for AI. Okay, fine. I probably budget for AI. Okay, fine. I get it. I would use AI to make something get it. I would use AI to make something get it. I would use AI to make something possible that was previously impossible possible that was previously impossible possible that was previously impossible and I would do it for for experts so and I would do it for for experts so and I would do it for for experts so that the fact that AI didn't work well that the fact that AI didn't work well that the fact that AI didn't work well would did not mean the product was would did not mean the product was would did not mean the product was useless or or bad. Picking the right useless or or bad. Picking the right useless or or bad. Picking the right category is one thing, but Jason says category is one thing, but Jason says category is one thing, but Jason says there's another filter. One he learned there's another filter. One he learned there's another filter. One he learned building WP Engine.

building WP Engine. building WP Engine. >> You know, WP Engine from the beginning >> You know, WP Engine from the beginning >> You know, WP Engine from the beginning and even now, we say like, "Oh, we make and even now, we say like, "Oh, we make and even now, we say like, "Oh, we make your site fast." And of course, a fast your site fast." And of course, a fast your site fast." And of course, a fast website is good. Search engines rank it website is good. Search engines rank it website is good. Search engines rank it higher. People don't bounce off of it as higher. People don't bounce off of it as higher. People don't bounce off of it as much. There's data that shows e-commerce much. There's data that shows e-commerce much. There's data that shows e-commerce sites that are fast, convert better. Uh sites that are fast, convert better. Uh sites that are fast, convert better. Uh media sites get more hits, which means media sites get more hits, which means media sites get more hits, which means more money. Like perhaps it goes without more money. Like perhaps it goes without more money. Like perhaps it goes without saying, but I just said it. Why fast saying, but I just said it. Why fast saying, but I just said it. Why fast sites are better. Okay. And literally sites are better. Okay. And literally sites are better. Okay. And literally make more money for people like make more money for people like make more money for people like e-commerce and media. So, okay, that's e-commerce and media. So, okay, that's e-commerce and media. So, okay, that's that's good. But if your site is 30% that's good. But if your site is 30% that's good. But if your site is 30% faster, is that enough to motivate faster, is that enough to motivate faster, is that enough to motivate someone to care to search to migrate someone to care to search to migrate someone to care to search to migrate their site to, you know, to not migrate their site to, you know, to not migrate their site to, you know, to not migrate away later? Like, is that good enough? I away later? Like, is that good enough? I away later? Like, is that good enough? I don't know. It's it's pretty weak. The don't know. It's it's pretty weak. The don't know. It's it's pretty weak. The reason we said four times faster is we reason we said four times faster is we reason we said four times faster is we had customer after customer where that had customer after customer where that had customer after customer where that that they had literally data showing that they had literally data showing that they had literally data showing that. And anyway, when it's that much that. And anyway, when it's that much that. And anyway, when it's that much faster, you can just feel it. You can faster, you can just feel it. You can faster, you can just feel it. You can just see like, holy crap, what the just see like, holy crap, what the just see like, holy crap, what the hell's going on? If that's the reaction, hell's going on? If that's the reaction, hell's going on? If that's the reaction, that's all you have to know. like, "Yep, that's all you have to know. like, "Yep, that's all you have to know. like, "Yep, that's so when it's not just quote that's so when it's not just quote that's so when it's not just quote unquote better or faster, more unquote better or faster, more unquote better or faster, more efficient, cheaper, but five times efficient, cheaper, but five times efficient, cheaper, but five times better, three times cheaper, D, right?" better, three times cheaper, D, right?" better, three times cheaper, D, right?" Where you could measure it, but like you Where you could measure it, but like you Where you could measure it, but like you don't even need to to see like holy don't even need to to see like holy don't even need to to see like holy crap. Like when it's that much, then crap. Like when it's that much, then crap. Like when it's that much, then something mundane and commodity like something mundane and commodity like something mundane and commodity like hosting and how fast it is, how secure hosting and how fast it is, how secure hosting and how fast it is, how secure is even a commodity thing. If it's a not is even a commodity thing. If it's a not is even a commodity thing. If it's a not 30% but 3, 5, 10x, it's no longer a 30% but 3, 5, 10x, it's no longer a 30% but 3, 5, 10x, it's no longer a commodity thing. That's now a commodity thing. That's now a commodity thing. That's now a substantially different thing. busting substantially different thing. busting substantially different thing. busting you out, differentiating, earning a you out, differentiating, earning a you out, differentiating, earning a higher uh price and etc. So I say that higher uh price and etc. So I say that higher uh price and etc. So I say that in general that's part of why we went in in general that's part of why we went in in general that's part of why we went in the commodity market and WP just because the commodity market and WP just because the commodity market and WP just because we had a couple of things like speed and we had a couple of things like speed and we had a couple of things like speed and scale and security and service which scale and security and service which scale and security and service which were like that but it's also I would were like that but it's also I would were like that but it's also I would bring back to the AI conversation when bring back to the AI conversation when bring back to the AI conversation when the AI helps me write but like in the the AI helps me write but like in the the AI helps me write but like in the end of the day like I'm I'm still

end of the day like I'm I'm still end of the day like I'm I'm still writing an article a day just like a writing an article a day just like a writing an article a day just like a little bit faster. I don't know that's little bit faster. I don't know that's little bit faster. I don't know that's something but I'm not terribly compelled something but I'm not terribly compelled something but I'm not terribly compelled but when I go from writing one article a but when I go from writing one article a but when I go from writing one article a week to two articles a day and they're week to two articles a day and they're week to two articles a day and they're good. Okay, that's like dramatically good. Okay, that's like dramatically good. Okay, that's like dramatically changing what's going on now. Do I want changing what's going on now. Do I want changing what's going on now. Do I want I personally don't want to do that, but I personally don't want to do that, but I personally don't want to do that, but like okay, that's a product, right? Or like okay, that's a product, right? Or like okay, that's a product, right? Or um I couldn't respond to this many I um I couldn't respond to this many I um I couldn't respond to this many I don't know posts on Twitter, what don't know posts on Twitter, what don't know posts on Twitter, what whatever you're supposed to do in social whatever you're supposed to do in social whatever you're supposed to do in social media, right? But now with this, you media, right? But now with this, you media, right? But now with this, you can. Okay, so if it's in this like can. Okay, so if it's in this like can. Okay, so if it's in this like multiple of saving money, increasing multiple of saving money, increasing multiple of saving money, increasing time, having outcomes now maybe that's time, having outcomes now maybe that's time, having outcomes now maybe that's really valuable and I'll be interested really valuable and I'll be interested really valuable and I'll be interested in that. So that's another thing I would in that. So that's another thing I would in that. So that's another thing I would expect from my AI. If AI is supposed to expect from my AI. If AI is supposed to expect from my AI. If AI is supposed to be so revolutionary, how come it's only be so revolutionary, how come it's only be so revolutionary, how come it's only increasing my performance by 20%. Right? increasing my performance by 20%. Right? increasing my performance by 20%. Right? It's just not worth the hassle and the It's just not worth the hassle and the It's just not worth the hassle and the wonder about where this is all going. So wonder about where this is all going. So wonder about where this is all going. So I would also be looking for something I would also be looking for something I would also be looking for something where the AI can really make me 10x like where the AI can really make me 10x like where the AI can really make me 10x like in coding it's not right like all the in coding it's not right like all the in coding it's not right like all the studies in real engineering departments studies in real engineering departments studies in real engineering departments is not that AI makes them 10 times is not that AI makes them 10 times is not that AI makes them 10 times better. The only people who claim that better. The only people who claim that better. The only people who claim that are the people selling AI products the are the people selling AI products the are the people selling AI products the users of it you know there might be users of it you know there might be users of it you know there might be individuals claiming that on Twitter individuals claiming that on Twitter individuals claiming that on Twitter because it's something to say but all because it's something to say but all because it's something to say but all the studies show that's not true. What I the studies show that's not true. What I the studies show that's not true. What I find in coding though is there are find in coding though is there are find in coding though is there are certain places where it absolutely is 10 certain places where it absolutely is 10 certain places where it absolutely is 10 or 100x like if I'm need to use a or 100x like if I'm need to use a or 100x like if I'm need to use a library I've never used before to do library I've never used before to do library I've never used before to do something and it's like oh just use this something and it's like oh just use this something and it's like oh just use this and it does it just works. I'm like, and it does it just works. I'm like, and it does it just works. I'm like, okay, you definitely, you know, in in 10 okay, you definitely, you know, in in 10 okay, you definitely, you know, in in 10 minutes, you definitely saved me a minutes, you definitely saved me a minutes, you definitely saved me a couple of days. Like, there's no doubt, couple of days. Like, there's no doubt, couple of days. Like, there's no doubt, right? But there's other areas like a right? But there's other areas like a right? But there's other areas like a big code base with 100 developers where big code base with 100 developers where big code base with 100 developers where it's just like, I mean, it's just wrong it's just like, I mean, it's just wrong it's just like, I mean, it's just wrong so much. It's just you're wrestling with so much. It's just you're wrestling with so much. It's just you're wrestling with it. It's actually kind of slower than it. It's actually kind of slower than it. It's actually kind of slower than just doing it. So, to me, it's just doing it. So, to me, it's just doing it. So, to me, it's contextual. The question is when is AI contextual. The question is when is AI contextual. The question is when is AI coding a big 10xer and when is it not is coding a big 10xer and when is it not is coding a big 10xer and when is it not is is actually the question. So, I'm saying is actually the question. So, I'm saying is actually the question. So, I'm saying that again because that's also part of

that again because that's also part of that again because that's also part of my answer of what would I build? I would my answer of what would I build? I would my answer of what would I build? I would build something like that where like build something like that where like build something like that where like contextually AI really can be like that. contextually AI really can be like that. contextually AI really can be like that. So something as broad as coding that's So something as broad as coding that's So something as broad as coding that's too broad and it's not even true that AI too broad and it's not even true that AI too broad and it's not even true that AI in that broad of a context is a 10xer. in that broad of a context is a 10xer. in that broad of a context is a 10xer. So I try to find a product where it So I try to find a product where it So I try to find a product where it really is true that AI today even you really is true that AI today even you really is true that AI today even you know with its failings really is 3xing know with its failings really is 3xing know with its failings really is 3xing something. Hopefully 3xing more value something. Hopefully 3xing more value something. Hopefully 3xing more value for the customer not just saving money. for the customer not just saving money. for the customer not just saving money. Saving money is a much weaker titch. Saving money is a much weaker titch. Saving money is a much weaker titch. Hopefully, it's 3xing the value and it Hopefully, it's 3xing the value and it Hopefully, it's 3xing the value and it really does and the weaknesses and the really does and the weaknesses and the really does and the weaknesses and the failings are are fixed by the customer failings are are fixed by the customer failings are are fixed by the customer where we've picked a domain where AI where we've picked a domain where AI where we've picked a domain where AI really is much better, not like general really is much better, not like general really is much better, not like general AI, I guess. So, these are the kinds of AI, I guess. So, these are the kinds of AI, I guess. So, these are the kinds of things I would go through as I would things I would go through as I would things I would go through as I would tick through it. tick through it. tick through it. >> At this point, I noticed Jason hadn't >> At this point, I noticed Jason hadn't >> At this point, I noticed Jason hadn't mentioned competition once. Turned out mentioned competition once. Turned out mentioned competition once. Turned out that's intentional. that's intentional. that's intentional. >> My assumption is that every market of >> My assumption is that every market of >> My assumption is that every market of any reasonable size will be flooded with any reasonable size will be flooded with any reasonable size will be flooded with AI products. Maybe it already is, but AI products. Maybe it already is, but AI products. Maybe it already is, but [laughter] my assumption is if it isn't [laughter] my assumption is if it isn't [laughter] my assumption is if it isn't already, it's going to be. So, oh well, already, it's going to be. So, oh well, already, it's going to be. So, oh well, what am I supposed to do about that? And what am I supposed to do about that? And what am I supposed to do about that? And what moat do I have? Like nothing. what moat do I have? Like nothing. what moat do I have? Like nothing. Because we all have we all use the same Because we all have we all use the same Because we all have we all use the same models. We're all making prompts like models. We're all making prompts like models. We're all making prompts like and as you say, tech is usually not a and as you say, tech is usually not a and as you say, tech is usually not a moat. Okay, if you have very very very moat. Okay, if you have very very very moat. Okay, if you have very very very you know, we can all pick out special you know, we can all pick out special you know, we can all pick out special cases where the tech is the moat. But cases where the tech is the moat. But cases where the tech is the moat. But that's the point that that's why it's that's the point that that's why it's that's the point that that's why it's usually not. So there's no moes there.

usually not. So there's no moes there. usually not. So there's no moes there. Everyone's doing this stuff. So like Everyone's doing this stuff. So like Everyone's doing this stuff. So like what am I supposed to do when the market what am I supposed to do when the market what am I supposed to do when the market is crowded with the same kind of we all is crowded with the same kind of we all is crowded with the same kind of we all using the same tech more or less? And using the same tech more or less? And using the same tech more or less? And and again, I think, well, then I've just and again, I think, well, then I've just and again, I think, well, then I've just got to have such a great vision for my got to have such a great vision for my got to have such a great vision for my product, my ideal narrow customer, how I product, my ideal narrow customer, how I product, my ideal narrow customer, how I build for them, how good it is for that build for them, how good it is for that build for them, how good it is for that particular customer, because not particular customer, because not particular customer, because not everyone's going after that particular everyone's going after that particular everyone's going after that particular customer. So, how can I just make an customer. So, how can I just make an customer. So, how can I just make an absolutely amazing product for that? absolutely amazing product for that? absolutely amazing product for that? Trusting in the thing we talked about Trusting in the thing we talked about Trusting in the thing we talked about earlier that other people will also like earlier that other people will also like earlier that other people will also like that and want to join in. And so, how that and want to join in. And so, how that and want to join in. And so, how can I find things like that adhere to can I find things like that adhere to can I find things like that adhere to those other criteria? There's a lot of those other criteria? There's a lot of those other criteria? There's a lot of vent circles here, right? But of course, vent circles here, right? But of course, vent circles here, right? But of course, there are because we just said all these there are because we just said all these there are because we just said all these things have to go right for the company things have to go right for the company things have to go right for the company to work. So yeah, that's right. It's to work. So yeah, that's right. It's to work. So yeah, that's right. It's going to be a vend diagram with lots of going to be a vend diagram with lots of going to be a vend diagram with lots of circles and a center that might not even circles and a center that might not even circles and a center that might not even be there. [laughter] be there. [laughter] be there. [laughter] There might not even be a center, which There might not even be a center, which There might not even be a center, which is kind of the point, but those are the is kind of the point, but those are the is kind of the point, but those are the kinds of things I would look at. Now, kinds of things I would look at. Now, kinds of things I would look at. Now, again, not not trying to imply there's again, not not trying to imply there's again, not not trying to imply there's no other way to build a company, right? no other way to build a company, right? no other way to build a company, right? Of course, there will be successes that Of course, there will be successes that Of course, there will be successes that don't do what I just said, like like don't do what I just said, like like don't do what I just said, like like we've been saying. But in the spirit of we've been saying. But in the spirit of we've been saying. But in the spirit of that uh bootstrap machine where you that uh bootstrap machine where you that uh bootstrap machine where you know, these are the things I would do know, these are the things I would do know, these are the things I would do that I think increase your chance of that I think increase your chance of that I think increase your chance of success or remove some kind of risk or success or remove some kind of risk or success or remove some kind of risk or at least lean into some kind of strength at least lean into some kind of strength at least lean into some kind of strength you have or go with the grain of what's you have or go with the grain of what's you have or go with the grain of what's going on instead of against the grain going on instead of against the grain going on instead of against the grain and therefore just like hopefully make and therefore just like hopefully make and therefore just like hopefully make all these little probabilities be a all these little probabilities be a all these little probabilities be a little bit better than maybe they would little bit better than maybe they would little bit better than maybe they would have been. That's what I would do. And have been. That's what I would do. And have been. That's what I would do. And of course, no matter what I thought, as of course, no matter what I thought, as of course, no matter what I thought, as customers actually used it, I would customers actually used it, I would customers actually used it, I would discover I was right about some things discover I was right about some things discover I was right about some things and wrong about some things and stuff I and wrong about some things and stuff I and wrong about some things and stuff I didn't think of, you know. So, of didn't think of, you know. So, of didn't think of, you know. So, of course, I would have to be following my course, I would have to be following my course, I would have to be following my nose after that. But this is what I nose after that. But this is what I nose after that. But this is what I would start with and then, of course, be would start with and then, of course, be would start with and then, of course, be following my nose as soon as I could following my nose as soon as I could following my nose as soon as I could intersect it with real customers. I'm intersect it with real customers. I'm intersect it with real customers. I'm always struck by how deeply Jason has

always struck by how deeply Jason has always struck by how deeply Jason has thought through pretty much any question thought through pretty much any question thought through pretty much any question I can throw at him. He's got a book I can throw at him. He's got a book I can throw at him. He's got a book coming out soon called Hidden coming out soon called Hidden coming out soon called Hidden Multipliers. I already pre-ordered my Multipliers. I already pre-ordered my Multipliers. I already pre-ordered my copy and you should, too. And if you copy and you should, too. And if you copy and you should, too. And if you haven't seen his microcom talk on this haven't seen his microcom talk on this haven't seen his microcom talk on this channel, it's our most viewed video of channel, it's our most viewed video of channel, it's our most viewed video of all time. And you'll understand why all time. And you'll understand why all time. And you'll understand why about 2 minutes in. Go watch it next. about 2 minutes in. Go watch it next. about 2 minutes in. Go watch it next. Thanks for watching. We'll see you next Thanks for watching. We'll see you next Thanks for watching. We'll see you next time.