บทถอดความฉบับเต็มของ Why This Business Model is Losing to AI and What You Should Do Instead | Scott Rewick

worlds of advising direct response companies and that you know, I look at that as a very selfish endeavor in the sense that, you know, when you stop pushing the buttons, running your own thing, you slowly get further away from what's happening on the ground level. So I'm lucky in that the people that I do advise, they're on the ground level running ads, creating product, thinking about scaling issues. So it keeps me really glued to the space in terms of what's going on. And then to be able to apply that to new company that I started with a partner. and really everything that's happening in the AI driven, agent driven space is is really an honor for me to be able to to to do this stuff in real time. So I feel very lucky in that respect as well. Shmuel: Cool. Awesome. Yeah. So we'll we'll get into the AI space a little bit and and talk about that. Let's let's unpack what what you're seeing and kind of like the thesis for that post not just advising and hearsay and what you you know what you might think, like actual, you know, facts of what you're seeing that's really making an influence. on company's bottom line and revenue. Scott Rewick: Yeah, I mean, you know, I I would say there's there's two big trends that are really both being affected by AI. the direct response space over the years has changed quite a bit from when I was buying ads on the front page of MSN, you know, back in ninety-eight, ninety-nine, we were dealing with you know, seven twenty by ninety, four sixty by sixty banners to where it is now has obviously changed a whole ton. so so you have that trend going on. The the f the the face of direct response will always be changing, whether it's new ad formats, whether it's VSLs or, you know, quiz funnels or abatorials. I think t that th that space has always been evolving and changing. I think what What really added fuel to the fire is what happened back in November with this agent driven approach. I think Hermes is one of the first that people started paying attention to. And I like so many people, you know, used AI for searching things and prompting it and asking what the weather is like and, you know, doing some basic tasks. But I think that for me at least, last year the the space really started to shift with agent driven models that became available and those are just only getting better. So I think that the, you know, you kind of had mentioned earlier a lot of people struggling. And I really do think that there are a lot of companies that have grown up in the traditional direct response space using a lot of people leveraging systems, copy, design, engineering that have a lot of outflow of capital to support that. And so I think that what I'm seeing is there are a collection of I would say midsized firms, and that's debatable how you wanna define that, but call it say five million to a hundred million dollars a year in business that are really struggling with the huge amount of operating expenses. So relative to this new wave of marketers that are able to compete with them with a tenth, a hundredth of the operating expenses. And so I think that's really happening quickly. much more quickly than people realize. The ability for a one, two, five person team to effectively compete and have greater output than say a mid-sized firm that supports 30, 40 people is really happening. and making that mid-range and even the high range a lot more difficult to to compete with small firms. Shmuel: Yeah, and we're seeing that as well when companies are trying to, you know, make money. You you know, you can make money, obviously sell more products and stuff like that. But then bottom line revenue could also be expanded by how much money you keep in the company, you know, based on your operations and and and your overhead count, you know, keeping the lights on and stuff like that. But with that, there's only so much you could actually trim away. you know, like Scott Rewick: Yeah, no, I see I mean, I see firms that have been around for decades now, going away or or or really, you know, flatlining in terms of their revenue or their ability to scale for this reason. Shmuel: Mm-hmm. Scott Rewick: the fact is that, you know, if if if you're armed with this set of tools, agent driven set of tools, which seem to only get better on a week by week basis, right? If you follow the space As closely as I like to think I follow it, there are new models, new capabilities being launched almost every week that affect almost every aspect of the direct response space. So whether it's creative output, whether it's supply chain support, whether it's reporting, whether it's ad creation, landing page development, customer service. So these agents are really affecting every last. inch of our space in in really positive ways. However, you know, if you've if if you are a company that's been around for a while and doing it the same way, you know, for years, it can be very difficult to adopt that model. So I'm seeing that you know across the board. companies in that mid-time mid-sized space really struggling. I think the other part that I hit upon is just this agent-driven piece, which allows small teams to essentially, you know, 10x, 100x their output using this collection of LLMs followed by, you know, agents that typically come along with those. So I think that part is growing exponentially as well. So you have this, you have this, you know, multiple waves happening. The internet space, in terms of our ability to advertise, is getting bigger. Right. So AppLovin and Native and Meta's getting bigger, and Google and all these places are getting more interesting and bigger. And your ability to market to a worldwide audience has never been easier. At the same time, you know, you're seeing, you know, small companies be able to compete very, very effectively against huge companies because of the amount of support you're given with agent-driven models. and so we really wanted to test that. I wanted to test that with a

partner of mine myself back in late December. and so we applied the agents and the models that were existing there to create a small direct response site just to kind of see if in fact you could create companies using using agents. And so that's really been really exciting for me to be able to try to recreate what I've built in the past with a tenth of the Shmuel: Okay. Scott Rewick: Human power. Shmuel: And this this is called skcommerce dot AI? Okay. Cool. Yeah, so tell us Scott Rewick: That's right. Yeah. That's right. Yeah. Yeah. Shmuel: about it. Like who who who's your partner on that? Scott Rewick: So he's a gentleman that I met at a four rooms event probably three years ago. His name is Kenny Aronson. And Kenny Kenny was a copywriter that had been in the space for five or six years and and you know really jumped on the AI thing as quickly as he could. And so when I met him, I kind of described what I saw happening in the space relative to AI coming into our world, he got really excited about it. He had been using, you know, kind of these early models very, very quickly and was like, hey, we should actually see what these models can produce from a creative landing page, checkout, integration. so the company itself really is operating under the premise that, you know, in the past, if you had an idea around a product. You know, it the typical flow would be, you know, start a company, hire a media buyer, not so much a media buyer yet, but hire a designer, hire a copywriter, get a team of engineers to create something for you. And you might be, you know, if you get a great copywriter, a designer, an engineer to test your idea with product might cost you twenty thousand, thirty thousand dollars before you even sold a single product. So we wanted to test the idea that with very limited capital, and I'm talking about like under a thousand dollars, could you create something similar in a tenth of the time? So whereas Shmuel: Okay. Scott Rewick: in the past, if you had an idea you'd hand it over to three or four people to hack away that you might have something workable, say within a month. we've obviously honed our model over the last six to eight months, but we can create all of that in less than an hour. So we wanted to test that theory for a single site. And then the the kind of the bigger picture is could you do that with 10 sites or 100 sites or a thousand sites each selling something online. Shmuel: So before we get to a thousand sites or even a hundred sites, let's talk about like one site. So you know, to product test and get everything, you know, all your docs lined up in a row in the past would be like a twenty thousand dollar minimum investment before you even sold a single product. Here you're you're investing much less capital. And so what are you getting? Is like the AI kind of like pressure testing your your thesis to make sure that it it it works or is it actually coming up with the actual product? Scott Rewick: Yeah, it's coming up with the actual product. I mean, you know, depending on how you use AI, and there's obviously, you know, thousands of use cases for it, but it took what I would normally have done in companies in the past, ideas that we have around what's selling online, what's a great product that you can either get through you know, private label or on demand, and it took all of that. and admittedly, I mean I think our system was quite a bit different back in February than it is now. It's I would say it's ten times more advanced. But we we had this, you know, we wanted to be able to test this theory on a particular vertical. We took the pain vertical, big one, you know, we all have pain and yeah, yeah, chronic Shmuel: Chronic pain? Okay. Scott Rewick: pain. And we we had agents that were researching, you know, what was selling online, how were they selling it, which products were they using, kind of like landing page theory, LTV, AOV considerations on checkout. And we threw this together in probably less than a week. we had a working Shopify ready checkout champ ready site to be able to throw a couple hundred bucks a day at Meta to test this theory to see whether or not in short order, we could create a site from scratch and get it running and testing. So that was the machine that we wanted to build. and obviously the machine's iterated a ton since then. But Shmuel: Yeah, for sure. Scott Rewick: from ad copy to landing page to design to customer service to supply chain to really creating all of the reports necessary To be able to look at this stuff on a daily basis and then make adjustments based on what you were seeing. Shmuel: Yeah, you know, you Tim Ferris, the four-hour work week book, his famous book, he came to that title. he mentions it because he basically split tested all these Google GDN, Google, Google Display Network ads. well, actually, I don't know if it was GDN back then, maybe it was Microsoft, whatever it was. And he basically tested copy and design to see what would garner the most amount of eyeballs and clicks and stuff like that and engagement. and that's how we settled on on the book's title. So is that is that what you were doing? Or did your AI actually make a real product? Scott Rewick: So it's it's you know, it's so funny you mentioned Tim Ferris's book. Tim Ferris's book for me a decade ago was the bane of my existence because I think it was really a decade too early. Because while it while it has a very it brought a lot of people into the space, the idea that you could make a lot of money working four hours a week was not what anything that I saw happening with myself and colleagues in the space, it it just really defied logic because you know, my experience was you have an idea, you're in there 80 hours a week, giving it birth and giving it life. And so it r this idea that you could compete with folks that were bigger than you putting in 80 hours a week and you were only putting in four just seemed laughable. Now fast forward, I

think that reality is actually true because Shmuel: With AI. Scott Rewick: with AI. You have you know, you have an army, and by army it's, you know, small army. I've got maybe six agents running at the same time. that's a lot more true than it has ever been today because you know, if you understand this this agent-driven model, these agents are working 24-7. As an example, I ran a company with my partner Chris called Native Path. We scaled it quite a bit. But I would rely on several humans to give me a synopsis of the previous day in terms of how we did, right? So it would be this complex spreadsheet in Google or, you know, which would outline every part of the business from impressions, clicks, and costs and units sold and this type of thing. And when I got that report, you know, say at 10 a.m. on Monday or every day, I would have a sense of how the business did. Now, you know, those reports are being generated with high degree of accuracy every single morning. Not only just the data is aligned lined up for me. So as a marketer, you can read this stuff, but you know, there are also suggestions and things you really haven't thought of that you might be able to do to improve it. And then you can test those very, very quickly and see if if they were right and they were wrong. so I think that that's where AI is really. really good at is organizing a lot of data across disparate channels. So, you know, impressions, clicks, AOV, LTV, supply chain, customer service, mid management, you know, all of that stuff kind of like it one-shots all of that stuff. So I really do think the four hour work we complies much more today, albeit I'm spending way more time. I mean if I could spend eighty, ninety hours a week doing this stuff, I would. So that's the that's that's how small teams can compete with big, big companies because of the leverage that this stuff gives you. Shmuel: Yeah, that's such an interesting point and observation that you said about the four hour work week. I came across that book like around twenty something years ago. And to your point about how AI has really made that a possibility, and a reality, that's that's Scott Rewick: Yeah, yeah. Yeah. Shmuel: so true. Scott Rewick: It brought a lot of people in the space. I mean, I I think the idea of working for four hours a week and making a p ton of money brought a whole influx of people into the space to see if that was true. and I think to some degree it was true back then because the fact is creating these companies over the last twenty years don't really evolve a ton of CapEx. The opex tends to be pretty low. So you can start these things with not a ton of capital. but I think it's just much more true today than ever before. but I think that there are people that c are applying that four hour work week and making it forty and eighty hour work week because they truly see the potential of this stuff. But yeah, no, I I I think you know, Tim was credited with bringing a lot of people into the space. and I think His theory is much more true today than it ever has been before. Shmuel: Mm-hmm. Yeah. Yeah. So you mentioned in you mentioned that you launched this pain relief product earlier on in the year from zero from scratch. And and not just in the traditional sense that you launched in you're like, okay, we're gonna build out a team and you know it's gonna be hard to recoup the initial investment. You built it pretty much with AI and then you let it roll. Can you tell us a little bit about the results? Scott Rewick: Yeah, I mean, you know, on the occasion that I do advise startups, what I typically tell them or people that are just starting out is, you know, learn to bleed for 90 days and just get absolutely annihilated in 90 days when you start hitting it with media, because the likelihood is that you're going to lose on a number of fronts. so whether it's the channel, whether it's the product, whether it's claims. and so I try to like forewarn people that in my experience, launching something new usually involves a lot of testing where it's much more likely you'll be losing than winning. And the game there is to figure out why you're losing and then make adjustments, retest it, have the presence of mind to look at the data and to continually make improvements until you can break even. Shmuel: Yeah, absolutely. I mean like a venture capital firm is like in the same position where they're not looking, you know, to have a portfolio of 10, 20, 30 companies that, you know, do like a one, one point five X. They're willing to make those bold investments where a lot of them, maybe even the majority of them, will will lose and close up. But then you'll also have, you know, your Googles and your, you know, your your your metas and stuff like that, which will make just a, you know, a hundred X and return the whole fund. Scott Rewick: Right, that's right. That's right. So that's I mean, that's typically how it's been done. it's also being applied to bigger companies that try new products out. usually they can test take the best of what they know about creating a product, apply it to new product, and they will usually have the same type of output. so we kind of knew that going in. I think the the the the agent along with a lot of human helped create created what we believe to be the most likely product to win on Facebook that we could. So we like a lot of people, hit it with 200 bucks a day in traffic. And I was kind of gearing myself up for the the 90 day walk through hell where nothing was working and we were continually upgrading it to see if we could get it to work. But lo and behold, you know, 200 bucks a day spit out 300 bucks a day in revenue almost from day one. So that was really encouraging that we could short Shmuel: That sure is. Scott Rewick: we could shorten that ninety day window, really eliminate that ninety day window and really out of the gate at very low ad spend have a product that was ROIing. So that was the first sign that

hey, this is not only maybe a space that we want to be in, but we can create a product, a company for less than a thousand dollars and have it making money almost immediately. So that was really the first sign or at least the first proof of my thesis that you could create companies like this, one-shot them for under a thousand bucks, put them in the marketplace, and they can actually survive. so Shmuel: Yeah. Scott Rewick: that was that was really exciting for us to to be able to to make money profitably almost out of the gate. Shmuel: Yeah, that's really that's really encouraging. I mean, like you said, like a lot of times it takes 90 days for people to really see things. You really need that like stomach of steel to you know to to have that gumption and to wherewithal to stick through it, conviction to make that long arduous investment into your company and especially but here to hit those returns right away. And and I mean they're they're small returns. you know, no one's retiring over those returns. But again, I think what you're doing and you're saying is you're kind of like adapting to the market. You're saying like scaling is not, you know, this you need this big machine and it's only a few companies. I think what you're what you're trying to say, I think and give hope is that like what we're gonna be seeing in in the AI age and you know, next year and the coming years is that we're gonna see like these micro companies, just like, you know, small teams, single digit teams, and they're gonna be able to compete. with. I I so I guess a lot of these bigger companies are gonna either shrink or close. Scott Rewick: That's right. Shmuel: so I mean it's gonna be a different playing field. Scott Rewick: Yeah, I mean it's i you know, several things are compounding, right? When you start a company, you know, you're you're at your weakest, and as you let it ride for a bit, the you know, the winds compound, the structure gets better, you might even hire your first person, but there's a lot of compounding that happens when you start a company over enough time if you kind of shelter and cultivate this thing. And so that the company that you have back in February is quite a bit different than the company you have back in say in August or September. of this year. So we've seen that the company get a lot stronger. you know, I I joke that that oftentimes small the smaller companies are held together by duct tape and hopes and dreams! And so, you know, that's to a large degree true, but if you give it enough runway, that company begins to take shape and have some defensibility. And you learn a lot along the way. I think perhaps the more important thing, at least the way V we view it, is that the AI systems are also compounding. So the agents that we had running in February are quite a bit different than the ones we have today. Because really everything that we're doing along those lines is recursive. So agents that we had making advertorials back in February.

Are significantly different than the ones we have making advertorials today or pushing out new content or you know, even in the customer service realm, the answers that our agents are giving customers today are quite a bit different than what we saw back in February. So there's really compounding happening on both sides of the plate. one from a here's this company that we're growing, and also here's the underlying support. to this company that allows it to leverage agents and systems that are far more advanced than they were back in February. And in part it's because we use them so much, but in part because, you know, what you have now relative to February in terms of a tool set given to you either by Anthropic or OpenAI or Grok or any of these amazing AI driven companies are in themselves ten times better. So it's this compounding effect on I think those three front fronts that make it, you know, you kind of alluded to my post, for me at least the most exciting time ever to be a marketer. And I don't say that with hyperbole, I've been doing this for twenty five years, but the opportunities now I see really just are mind blowing in terms of your ability to create companies and scale them, and compete with big, big brands. in a way that you could never do before. Shmuel: Yeah. So yeah, I was just actually going to ask, like, where do you think we're going with this? But it sounds like you're very bullish on this and you don't see this as being like another internet, you know, a dot com boom or anything. You think this is the real deal and and and we're gonna see tremendous growth? Or or is it or is there going to be kind of like a leveling, you know, somewhere in the middle of the world that will be like some sort of AI, you know, bust or something where Scott Rewick: Well, I think it'll level out in that. I think as more marketers like myself and you and certainly the whole family of marketers begin to adopt these agents. Like, look, we're not the only ones that are leveraging anthropic or open AI to create these things. So we realize that. So I think that there's gonna be a number of people who also realize that unless you are have AI as a component of your business, you'll go you'll go out of business. There there are a lot of people that are catching up. But I but I but I do really believe, I mean, you know, my thesis is like, you know, two man company doing fifty million dollars a year. You know, we've already seen it with, you know, example after example of companies that with very, very small teams can create huge amounts of revenue. So I think there's gonna be a window of time. how long I'm not sure where You'll see these small companies that are AI first go out there and build either big brands if that's the goal, or you know, in our case, the idea was could we create 10? And we just really made that number up, but 10 Shmuel: Okay. Scott Rewick: brands that were smaller brands, each doing five million dollars a year. and could all of those be run on a central system which creates ads, does research. looks at the numbers, plugs into supply chain, centralized customer service, mid management. and so that's the theory that we're we're trying. And we're, you know, we're six months into our first brand. We're about to launch our second brand here pretty shortly. but that's that's the theory that we're trying to test out. Shmuel: Very cool. So it it's not you know, it's not like you might need like that one massive company. Like you can kind of have these micro companies that are generating a a bunch of revenue for you and you you know, you cobble that together and you have, you know, a nice a nice healthy return on them. Scott Rewick: Yeah, no, you know, it it might be the case that one of these out of the say horse race of ten horses really takes off. Shmuel: Mm-hmm. Scott Rewick: you know, I think most marketers trick themselves into thinking that they have a quote brand that I'm going to sell to Unilever for a hundred million dollars or something along those lines. I think most of us, you know, if you ask people what their goal is, it's to sell a company or to sell to a brand. Now, the reality is most of these are not brands. They're just really effective ways of making money. So I think you can hold both to be true, which is can you create multiple brands quickly? some scale, some don't scale, some fail, and then either end up with a portfolio, whether it's one or two or ten or a hundred or a thousand brands. or you know, if your goal, depending on the founder's desires or needs to, you know, what they really want to do, can you dump all that focus on one single brand that if your goal is to sell, you can sell. So it gives you optionality in terms of whether you want to be you know, kind of behind the scenes and not have any interest in creating this big brand that you potentially sell, or if you do have something that you catch fire on that you could sell down the road. anyone looking at these companies are gonna find, you know, almost very little operating expenses, really healthy balance sheets, highly profitable businesses. So it gives you optionality, I think is the cool thing. Shmuel: Yeah. Yeah. We recently had people on the podcast that their thesis was about making businesses sellable, that basically every business has two options, you close down or you sell. and obviously you want you you want to be in the the bucket of where your your your business is primed to sell. and when you when when you said said I just want to go back a little bit, you said that window is closing. Is is that is that because you feel that like AI is just gonna get too advanced for people to just catch up? Or or it's gonna be Scott Rewick: Well I think and I don't know it well, I don't know if it when it really closes, but I think that the tools are so available to most marketers that, you know, you can with with a single prompt begin to engage AI in a way that if you prompt it enough, gets

you really good output. So I think that, you know, I wouldn't say that we are ahead of the curve. by any stretch of the imagination. I think we're two guys that really study this stuff night and day and try to figure out how to apply it in the direct response space. But we're clearly not the only ones. you know, there are people also using AI to generate huge amounts of creative output to analyze pages quickly. So what I mean is that I think the models and the agents are exponentially getting bigger. So it creates a huge opportunity. But I think there are more people, whether they whether through inspiration or desperation, realize that if they are not incorporating these tools, they're gonna get left behind. So what I mean is that there we aren't the only ones with this idea. in fact, I would say that we are, you know, freshmen in the game here. We we are, you know, the people that I look at now and try to study, I I think are probably three or four steps ahead of us. and even though I think we're we're we're but we are we are probably a hundred steps ahead of, you know, most people that are just starting to use it for the first time and understand how to, you know, install claw Shmuel: Yeah. Scott Rewick: or set these things up. So I think it's really exciting. Shmuel: Yeah, do you have any funny anecdotes, stories, embarrassing stories maybe, when you were just kind of like learning fresh in the AI game that you could share with the audience? Scott Rewick: Well, you know, I'll it's fair to say that that you cannot take the output that is generated as the final word, right? So, you know, they call it AI slop. So when you run and you create your first advertorial, you know, and you're excited because you took something that might have taken a designer or copywriter a month and twenty thousand dollars later, and you have it in your inbox in five minutes, you know, there's this euphoric feeling like, my gosh, I have to crack the code. And I have this advertorial that works. Now, you know, certainly early on, you know, the the output was really horrible. You'd have mismatches on images, you'd have AI generating extremely weird content on pages. It would generate very unusual ad creative So there's gonna be a ton of mistakes. So I I say all of this AI stuff and you know only to say that a human element has to always be involved. because there are some things it's really good at. I would say data analysis and data crunching and organizing it, but there are a lot of things that it's still not that good at. So we we we generated some god awful advertorial ad creative almost out of the gate that we We had to go back and look at it and go, my gosh, right, like this advertorial completely sucks. Shmuel: Yeah. Scott Rewick: so you know, that was a that was a big mistake. we allowed AI to do some mapping on SKUs, which did not do a good job. So we had a a three-bottle checkout on our page that ended up being a 30-bottle checkout. So we began to get customers saying, Well, I appreciate the 30 bottles you sent me, but I ordered three. So You know, there there are just gonna be mistakes along the way that when you completely trust AI you might run into. So there's always gonna be I call it kind of the wizard of oz or the the master chess player that needs to sit on top and really look at the output because if you take it on face value, you could end up making really bad decisions almost out of the gate. I was talking to my agent this morning. And it said, you know, you had the best day ever yesterday. Your ROAS was two point five and you did this. And I said, wait a minute, like I think May 15th was our best day ever. Because we did this and this. I look back and you're right. I'm so sorry. Shmuel: You're right. Scott Rewick: You're totally right. I will update the rules. I will make sure this never happens again. So so you're gonna see mistakes from AI, I wouldn't say on a daily basis, but a lot. And I think your your job is to be able to catch it and then train it to do better next time. So I do a lot of training on these agents because while they do work for pennies on the dollar for tokens, while they are on twenty four seven, early on they need a lot of hand holding. because they're gonna do their thing and oftentimes it's completely the wrong answer. So that's that's a Shmuel: Yeah, and at the end of the day Yeah, and at the end of the day they're only gonna be good as the person who trained them. Scott Rewick: That's right. That's right. That's right. And you know, I mean, I think for me, I I took a lot of shortcuts. I take a lot of shortcuts because I've done this so long that I oftentimes really aren't I'm not that good at slowing down and breaking down each process. I've as a marketer, I just say do this, do this, but the more specific you can be with it and the more you can sit with it and train it early on, I think your outcomes become considerably better. And this is one of the things that I've had to I mean, look, it's really intimidating over twenty five years to feel like you're a student again in this space. Shmuel: Yeah. Yeah. I mean I'd venture to say that every everyone really had to learn this. It wasn't like, you know, everyone all of a sudden knew how to prompt their LLM, you know, and and understood, we need to do this in baby steps, because you know, if you do it, you know what you're thinking. It doesn't know what you're thinking and it's just gonna Scott Rewick: Yeah. Shmuel: use all your tokens in one go and Scott Rewick: Yeah, and you you know, you know, the models now we have agents now talking to agents and doing recursive back and forth. So there's all these different interrelationships between you as the operator managing agents. But the way this is going is that agents now will talk to other agents who will talk to other agents. So we have a series of agents when we look at launching new products that all work together on here's the idea. Here's the creative strategy. Here's the supply chain available. Here's, you know, so so that's that's the second fold of this is that this where this evolves is you'll have agents essentially just working with other agents and you'll take even a further step back and let them interact. so it's for a marketer like me, it's completely fascinating stuff. Shmuel: Amazing. Well, thank thank you so much. I mean, I appreciate it. everything you said, especially the the you know, opening up. you know, you were very candid about mistakes and stuff and and your learning curve on on AI, but it's definitely an eye opening discussion and and topic that people really need to get into, or else they're gonna miss the boat. So w where can people find you? Where do you hang out these days? Scott Rewick: Okay. Shmuel: I'm I mean on social media. Scott Rewick: Yeah, Shmuel: or Scott Rewick: I mean I'm I'm on Facebook. I think people can find me there. skcommerce dot AI is is our our company that people can find us on. But I'm usually pretty easy to find. I give people my email address. I've helped hundreds of hundreds of people over the years and so I'm happy to give advice or at least tell people what I'm working on. So I'm usually pretty easy to find. Email is Scott Rewick Shmuel: Excellent. Scott Rewick: at gmail dot com. Shmuel: Excellent. Well, thank you so much for coming on the Built to Scale podcast and telling us what it takes to scale in the AI world we live in. Scott Rewick: Appreciate it. Shmuel Herschberg: Thanks for listening to the Built to Scale podcast. If you enjoyed this episode, make sure to subscribe to the podcast so you never miss a conversation about what it really takes to build and scale in today's market. For more information about Built to Scale and how we help companies grow, visit builttoscale.co. If you have suggestions for future guests or topics, send us a note at podcast at builttoscale.co. We'd love to hear from you. Until next time. This is your host, Shmuel Herschberg, and remember to keep building, keep testing, and keep scaling.