AI & Ads in 2025: What Every Growth-Minded Brand Should Know — with Hikari Senju

Hey, what's going on everyone? Welcome back to Mastering Tech Growth, where we chat with industry leaders to bring you big ideas on how to grow. I'm Mike Sirius, and today we are talking AI advertisement. Does it save founders' time and money? Where it truly delivers and where it falls short. Joining me is Hikari Senju, founder of Omnikai, AI platform powering ad campaigns across TikTok, Meta, and beyond. Hikari is on a mission to make advertisement faster, smarter, and more accessible. It's great to have you, Hikari.

Thank you, Mike. Really excited to be here.

So we love to kick off with this one. When I say mastering test growth, what comes to mind?

Gosh, I think of growth loops. I think of these like funnels. I think mostly loops and funnels really when it comes to thinking of mastering tech growth.

Okay, well give us a little bit, what is growth loop for you?

Well, growth, a growth loop is essentially a user journey that like compels new users to sign up. And so whether it's having, you know, incentivizing users to invite their friends, incentivizing users to use the product more. Um, and it becomes this virtual cycle where, you know, almost like a flywheel of, um, of, as you get more users, the product gets better, uh, the company gets better. And then it, um, and then, uh, and then they're also incentivized to invite more of their peers and friends to use the tool. And that creates momentum, kind of like a snowball effect, uh, to, um, you know, create a competitive advantage, uh, as as you're growing the business. And so that's what I think in growth loops. In terms of funnels, it's really about, um, you know, you have top of funnel, which is the total number of people who know about your brand and your company, and then there's people who go to your website, and then there's people who sign up, and there's people who end up paying you, and then there's, uh, then there's people who end up, um, kind of retaining over the long term, and then, and then upselling and, and using the product more and, and paying you more. And so that's kind of the way I think of funnels. And so I think when it, when it comes to mastering tech growth, it's, it's Understanding both the growth loops of, you know, how do you incentivize users to invite their friends and how do you incentivize users to make the platform better as you grow? And then, and then it was like in a flywheel. And then the second is how do you get more people efficiently into that loop and in the most cost-effective way possible and in an ROI way positive.

So is the growth loops effectively another word for network effect or is it more? Scientific in its delivery.

Yeah, I mean, I think a growth loop can definitely include network effects. And so definitely there's— and I think there's a lot of, uh, especially like, you know, online communities and platforms have network effects, um, that, you know, kind of create a compounding advantage to the player that's growing the fastest and has the most users. Um, you know, just, you know, very quickly in terms of network effect, you know, basically the idea is every additional node is like— creates more exponential value for, um, that network. Uh, and so, um, um, and it was kind of initially kind of thought in terms of, for example, like telephones and the kind of a telephone network, things along those lines. Also, I think you can even think of it in— and I think of, you know, even prior to, uh, the, the tech boom, uh, you know, you can think of like railroads as this almost like a network effect business. And, and, and, and railroads back in the 1800s were a humongous, you know, venture-backed venture capital kind of, um, you know, highly financed endeavor where it was like winner-take-all and you had these huge booms and busts in late 1800s both in Europe and in the United States powered by, you know, these winner-take-all network effect businesses which were railroads at the time. So it's not anything new, um, but, uh, but I think now there's kind of a speed and scale to it, uh, with internet, uh, that, um, you know, creates opportunities for all kinds of entrepreneurs.

Okay, I love that. It's a great explanation. Funnels is, yeah, that's an interesting game. I'm still looking for a great guest to unpack the funnels as a topic, but it's such an essential setup to actually do well, to expect success. Let me rephrase this a little bit, that question for you, Hikari. So we have this concept of first-order effect and second-order effect when it comes to growth. So first-order is something which really, really gets that top line up like sales and marketing. And second order effects could be things which are very important, such as hiring good people, right? And, you know, having a good management and things like that. So from all the different things, if you would choose what has the most influence on growth and you can choose only one, what would be your choice?

Well, it's definitely second order effects. I mean, you know, the first order effects or kind of, you know, the outcomes are just results of the improved processes. And I think you can even say like the secondary order effects isn't just, you know, people, but it could be certain metrics associated with uniquely your product that drives increased revenue, which is the outcome. So, um, you know, it could be— if you're a social network, it could be, you know, monthly active users or daily active users or monthly active users. And that kind of ties ultimately into advertising revenue, for example, for a social business. And so, um, um, yeah, you want to think of like almost the, um, you know, first principles, like most distilled value metric of your product It could be usage, it could be amount of ads generated, it could be ad spend for us, it could be, you know, number of brands, it could be, and then that then fuels kind of the outcome, which is revenue, but you're more focused on the first order, you know, like kind of the core metric that is unique to your product that drives and creates value versus kind of the outcome metric, which may be sales. And then, and then yeah, I mean, team, You know, I mean, company ultimately is an organization of people. And so that is, you know, the core building blocks of building a great company is having a great culture with great people.

What would be your choice, Hikaru? Like if you can only choose one from all that what you just mentioned, what do you think is for you, what is the most important one?

I mean, I think, you know, it's kind of hard to say, right? Because I feel like if you just choose one metric, you tend to kind of, you can hack that metric. And I think at least you need at least two metrics that kind of balance each other to that, like, so that you're not like overly kind of overtraining or like kind of overfitting a certain metric. And so, you know, for me, I think of, yeah, I mean, I think of like, ultimately, I think of like, you know, the, how are customers using the product, which is based on usage. Time spent in the app, the number of ads generated, uh, the number of people who are signing up. And then I think of, um, and then I think of ultimately our team and how is our team, um, kind of structured and, um, uh, you know, skilled and, uh, to, to, to help serve our customers in the best way. Uh, and so, um, but yeah, I mean, I, I may— maybe I'm not sure if this is the exact kind of metric you're seeking, or maybe you're looking for even more concrete metric, which is like—

no, no, no, it's, um, I think you're saying is the customer obsession is, would be at the top for you, right? Because, yeah, I mean, it's almost like self-explanatory in a way because the customer is who paying you. So you want to be obsessed that they're getting value from the tool and that as a result is something you track, whatever metrics goes into that. But the notion is that from your point of view, the customer obsession is what drives growth as a number one choice.

Yeah. And it sounds almost kind of like trite to say, because I think everyone says this, but I think it is. Yeah, that is like the fundamental truth of business is like the customer is—

Yeah, there's a lot of customer, Hikaru, but you would be surprised. We had very interesting answers, you know, from sales, because ultimately, you know, cash flow is what keeps business alive, to lowest denominator, which is the people, to market fits to timings, you know, everyone has their own view. What is the number one most important metric for growth? And I love that question because you can only choose one. So it's like, it's great to see what, what, you know, different founders care most about. So let's go into advertisement, right? Did I actually say your platform correctly? Is it Omnikai?

It's OmniKey. Omni, like Omni, like all, and then key as in kind of like knowledge or kind of secrets or things like this. Okay.

Oh, right. So it's a key as a— okay. Okay.

Yeah.

Okay. OmniKey. I love that. There's a, yeah, there's some thinking behind the name. I mean, it always is, right? But yeah, it's cool to know OmniKey. Okay. So let's paint a picture before AI came into advertising and space. What did running ads look like? Let's say like this. What did running ads look like before AI was there to help?

Well, so it has been in advertising for some time. Machine learning, you know, has been used in delivering ads since at least 2010s. But before that, even that, I mean, essentially people used to just straight up buy banner ads on the web. And, you know, you like, you know, you choose certain websites you wanted to run those ads on. Maybe there were certain user IDs that you'd want to kind of target, and then there would be an auction to make sure that your ad was being shown to the right person, you know, on the right platform at the right time. And there's a very robust, you know, ad tech infrastructure that was built out there. And then AI definitely was involved in terms of making sure that the ads are being personalized and served to the right person. And I think platforms like Meta did a really, you know, kind of was an innovator in terms of highly incorporating machine learning to serve ads in a personalized way. And then now obviously for us, it's generating the creative and personalizing the creative itself that we've been focusing on.

So what, and that's where I was going as well, the creative piece, because I run ads myself, you know, for the podcast. You know, I'll be honest, I'll run only on YouTube, which is effectively, you know, Google Ads. They ask for images, right? They ask for videos like a, you know, like a trailer, ads, text and stuff like that. And they don't really help you with that. They just go like, upload your creative. And I'm like, come on. Like, you know, can I just give you a prompt and you just do that for me? So I need to go back into something like Canva and do that myself, which is quite time-consuming. You know, if I'm not doing that myself, then I'm hiring an agency or a freelancer. So I'm paying for these creatives, right? So effectively, what kind of time, money, and resources did it actually take to run a decent campaign, you know, before AI actually can help you?

Yeah. And so it's precisely the way you're describing it, which is like you'd have a team of designers and marketers. Create designs by hand and then upload those ads and, and then run those ads targeted to certain users or certain keywords or certain, um, you know, search terms, etc. And so, um, oftentimes, uh, these are very, um, human-intensive processes, especially if you're, if you are a massive company, a massive brand, massive multinational company with thousands of SKUs, and you're running these ads across dozens of different ad platforms of different, you know, different dimensions. You need video, you need square images, you need horizontal and vertical images. It needs to be a certain, like, 5 seconds, 10 seconds, and then you need to do that for all your SKUs. Oftentimes you outsource that to some third-party contractor or some multiple vendors usually when it comes to creative, or you try to make all this content in-house. But yeah, very time intensive, organizationally becomes actually incredibly complex. The more SKUs and audience, more markets you're operating in. And so it was a highly inefficient system that, and that's why I think people have this famous quote, which is like, I know my marketing is working, but I don't know which half of my marketing is working. You know, generally half of marketing budgets are wasted on ineffective content and ineffective creative. And that's the world we've been living in. Even, even, you know, today you're still describing a world where someone's manually creating content and uploading it onto, for example, Google. And so, you know, AI has data, real-time data regarding what people are clicking on and what people's interests are. And then it can personalize that creative to that person at that time for that product, for that brand. And so it's more likely that that individual ends up clicking on the ad and buying the product or signing up. And that for us in particular, it's, you know, to orchestrate those personalized campaigns across the dozens of platforms you may be running ads on. We don't, you know, there are numerous opportunities for buying media today. That's not just Meta and Google. But you know, streaming is a big, increasingly big, I think now more people watch streaming than television. In fact, I think YouTube makes more money than all the, all 4 major broadcast companies combined per year. You have Netflix, you have, you know, all the other streaming platforms. And on top of that, you have all the different social platforms. So obviously, you know, there's TikTok, there's Snapchat, there's Pinterest, there's Reddit. And then you have all the You have gaming platforms and mobile platforms like AppLovin, you have television platforms like Trade Desk. And so, you know, as an advertiser, you want to, you know, connect with your customers where your customers are, and they're not just on 2 apps, they're on, you know, dozens of different apps. And so then when you're buying media and you're running media on those platforms, you wanna make sure that that brand experience is consistent. So that they're not seeing one message on Instagram and seeing a different message on Netflix or seeing a different message on Amazon Prime, uh, or seeing a different message on, on, um, on, on Reddit, for example. And so that orchestration challenge is something that AI can do very well. And that personalization of content is something that AI can do very well. And so we represent the brand to help make sure that their brand is safe. And as they're generating creative, that their brand is, and their content is personalized and data-driven. And ultimately, you know, advertising serves the advertiser, not necessarily the publishing platforms.

Okay, so let me land this point with this quote from, from, from Guardian. So according to Guardian, the UK advertising market was worth just over £3 billion in the '80s. So that's like 45 years back. Now it's £45 billion. So that's 15 times growth. But agency leaders admit much of that spend still goes to slow inefficient creative processes that drain brands' time and budget, right? So effectively, anyone who has advertisement agency potentially listening right now, they're probably nodding their heads going like, yep, that's exactly what the problem is, right? And we effectively saying that potentially AI comes in and changes that. And to your point about where you want to meet your customers or potential customers, there was a very good keynote speech from Gary Vaynerchuk where he basically said like the next big market, the next trillion market will be on social selling, right? So a lot of upcoming generation which are entering labor markets and effectively becoming employees, which means they're going to make money to spend money, their habits is not watching television or listening to radios. Their habits are social media, you know, being on YouTube, being in social. So their buying habits is very similar like that. They have people they like, you know, channels they follow. And if those channels, you know, start selling to them, they will most likely listen a lot more, right? Or at least that, you know, if advertisement comes through that channel. So that's a very, you know, puts us in a perspective of like, okay, well, we know that works. You know, we know there's an efficiency. We know we want to go there. Now it's a question of, okay, well, how AI can actually help with that. So my question is, how do you actually generate a creative with AI which, you know, works? Because anytime I try to do this with something like Midjourney, I'll be honest, man, it just goes nowhere. Like, I'm always frustrated. I can't make it, you know, to land where I want it to land. You know, the text generation is very off as well. If I try to do videos, you know, Like, again, I don't get something which I could believe is an ad. So can you just sort of walk us through the process of like, you know, tactically speaking, what is AI helping you to create?

Absolutely. There's definitely, so, you know, we were talking about the old problem, which is you have massive teams of designers and now you have the new problem, which is people are trying to use AI, but it's not personalized, it's not on brand, it's generic. And people also, you know, right now at least, you know, like have this expectation that it's 100%, 100% of the time. And that, you know, these, that the AI is fundamentally, it's a probabilistic model, you know, and so it's like rolling the dice and, you know, you have to roll the dice a couple of times to get the number you want. And that is the proper expectation to set when it comes to utilizing AI. And so, especially when it comes to creative. And so the way we do it, and we have a free trial, it's a 7-day free trial, anybody can use, sign up our tool. Sign up for our tool free and start generating creatives. We generate, you know, dozens of variations in one go if you want it. And ultimately, you know, generate that. And the idea is you'll generate thousands of ads on our platform and run them as, as, as you know, on these channels. And so one go, one click, generate an ad. We number one, first train on your brand. So we scrape your brand information, we get your brand guidelines, your font, your brand colors, your product assets. I mean, we need all that information first to make sure that the content is relevant for you. So it's not just some random image that you generate in some image generation tool. There's a lot of that, but actually personalized for you and for that brand. So our goal is the first time you sign up and you start seeing those ads, you say, wow, like those ads are exactly the way I envision them and the way I always envisioned my brand. We want to understand your brand.

Ricardo, sorry to jump in. What exactly do you expect when it comes to the brand guidelines? You mentioned the font, the colors, but that's like very surface level, like, are we talking about a lot of text, textual content like blog posts, or do you actually want some images, you know, maybe our office images or maybe products we're selling images? Like, what is a decent package where you could expect the creatives to be good?

Yeah, so as part of our onboarding process, we also ask you to select— we've scraped thousands and thousands of reference ads, we've collected thousands of reference ads in all different languages for all different product categories, for all different industries, and we will actually recommend you some reference ads, inspiration ads.

All right.

Okay. You can select from, and we already personalize that recommendation for you. So when you sign up, we've scraped your brand, we've scraped your website, we've taken screenshots of your homepage, we've taken, you know, we've kind of extracted brand aesthetic information from your brand book. We've, taken, downloaded photos from your website, etc. So we have a generalized idea of what your brand is about and the aesthetic of your brand. And we also know what industry you're in. And if you're a beauty brand, that's distinct from if you're a SaaS company, if you're a gaming company, there's all distinct kind of aesthetics. And then, and then based on all this information, we'll like show you hundreds of ads you can choose from, say which, you know, reference ads, which aesthetic speaks most to you.

Does the reference— do you like when you get the reference ad, do you know how well they perform? Can you offer me a reference and say, like this is, this is killing right now in like Facebook?

Yeah. So for now, the reference ads initially is just to make sure that the brand is along the lines of what your, you know, your brand, the way generally content's aligned with your brand. So initially the reference ads is more just to get a sense of what is the, what are you trying to aspire to be first? Like, who do you want to be? Like, what is your general, you know, guardrails for what is your brand about and what is it? Because the first thing we need to do is convince you that our ads are worth running. And so, uh, and that means that we need to understand your brand better than, than, you know, or just as well as you understand your own brand. And so that, that is our first goal. And so when we, we're talking about customer obsession to usage and time spent in app is we know that we're more likely to retain that customer if that first set of ads is as on point as possible. And in fact, more on point than even your website is, right? Because we understand that website making is kind of annoying and kind of use all templates and your website may not even speak to you, your brand as well, as much as you kind of envision your brand.

And so the first— What if I don't have that? What if I'm just starting and I'm like, you know what, I don't have a website. Like I'm just thinking about myself. I mean, if you go to the, you know, our community and podcast, I mean, it's going to be a couple of pages, right? But there's, there's really not—

Yeah. And then, you know, so, you know, like, then you don't need to upload all, you know, like, then, then, then it's fine. You don't need to, if you don't have all, if you don't have a brand book, that's fine. Like, provide as much information as you can provide us that is within, you know, what do you have. And so, and we make selecting reference ads easy. So we have all this library of images you can choose from, and you can just say, these are the kind of, this is the kind of aesthetic that I've got going. For. And then we ask to connect with your ad platforms. So we ask to connect with your Meta, your Google, your TikTok, your, your other social platforms. And we start ingesting data from these platforms regarding, well, what actually is driving performance on these channels. Now, if you have never run ads before, that's fine too. And, and you can connect it later, or you can just connect and create an account as part of the onboarding flow. So as part of onboarding, you can actually create a Meta account or Google Ad account or TikTok account and connect an empty account, which is totally fine. And then we'll start generating ads for you. And then you will— from there you can edit the ad so you can edit with chat, so you can prompt the AI and be like, hey, I want to re-edit this ad, but, you know, more like this. And you can actually kind of direct the AI to regenerate the ad to your liking. You can edit the ad through our editor tool. So we automatically layer the ad. So we take the, you know, the copy, the product photos, the background assets, and separate them so that then you can edit each element individually. You can resize the ad, you can turn it into a video. You can turn the video into a much longer video, and then you can launch those ads through our platform. You can launch the ads through a new— as a new campaign. As a sales campaign or an awareness campaign, as a performance marketing— sorry, like a Performance Max campaign or— and, and, and that's really the goal. The next metric we're trying to really optimize for is, you know, have we created ads and created and enabled tools for the user to edit the ads or get the ads to the point where they feel confident running those as ads on, on these various ad platforms?

Okay, there's a very clear, there's a very clear win on time saving, and that's effectively where, you know, majority of the market is getting this efficiency. And I have this quote from McKinsey, which did the survey, and they found that companies using AI in marketing achieve 10 to 20% improvement in cost saving and efficiency, you know, proving that AI effect is not a hype, it actually works. But what I'm really interested is Do you have, you know, as a service provider, do you did any use cases or any sort of data to prove that the ad creatives actually perform as well or better than the human creatives?

Yeah, absolutely. And so once we've convinced you to run the— once you've, you know, we've built ads, you feel convinced to run ads, then the next metric— once the metric is first, you know, did you sign up, did you launch the ad? And then the third metric is, did the ad perform? and did the ad perform better than the ads that you were running previously? And generally what we've seen, I think across on average across all of our customers is that our ads, um, and AI-generated ads and this kind of process of generating many variations and kind of, um, almost brute forcing performance from these ad platforms delivers a 2x return on ad spend higher than the existing previous system. So usually, you know, to your point, Right. You described the typical use case, which is customer creates, uses some image editing tool, creates 1 or 2 or 3 ads, and then runs it on YouTube, for example. Those ads don't perform as well as creating, maximizing the number of creative you can run in that ad set, whether it's images or videos and letting these, and then, and then, and not only, not only are you just creating tons of content that's random, but like actually personalized to your brand. And incorporates real-time data regarding performance regarding the elements of that creative that have been shown to perform. So maybe it's, you know, we've realized a certain value props within the brand or correlate with driving more conversions and we can, we can measure that. We can see, okay, well, this ad speaks about how fast your product is and this ad talks about how cheap your product is and this ad talks about, you know, how it improves, you know, the results. Of your product. And then we will, you know, run— you can actually go to Analytics dashboard and see, okay, well, how did this ad perform versus that ad? And then say, okay, well, the ad that talks about time savings, for example, is correlated with driving higher conversions. And so let's keep creating more variations of ads that focus on time savings. And then so you can have the maximum number of ads that are focused on time savings targeting a specific audience. And in that system, is definitely, you know, 2x higher performative than just creating 1 or 2 ads that are, you know, could be speaking to some about some random value proposition that, and then kind of hoping that those ads perform. So when we say like value prop and effectively, you mentioned time saving, are we talking this being a text on your ad, which basically, you know, I mean, so for example, you know, even when it comes to time savings, I think there's different ways of visualizing time savings that, you know, that, and there's also secondary effects as well, like secondary visual aesthetic elements that could convert better. So for us, for example, you know, well, you can have a young person on a laptop looking like they're, you know, enjoying their work, or you can have an older person on a laptop looking like they're enjoying work. You can have a person wearing a blazer, you can have a person wearing something more casual, you could have different ethnicities. You could have different genders, it could be a woman, it could be a man, and like all those different visual elements, you could, the color of the creative, the background color of the creative can have, you know, especially in conjunction with the different elements I'm describing in the creative itself, whether it's a person or type of person or what they're wearing, all have an impact in terms of click-through rates and in terms ultimately of conversion rates. And so And so like you want to quickly find, well, maybe it's a woman wearing a blazer on a laptop that is, you know, that drives a higher, you know, conversion rate and signup rate than, you know, a dude wearing a hoodie or something. And so those, but this is, you only really know this through multiple rounds of A/B testing and exactly. And it's hard for a human to come up with all those ideas themselves, but an AI can quickly generate those ideas and create those creatives for you that makes it, you know, all you need to do is just approve the running of that ad. Say, hey, we came up with this, like, you know, almost think of it as like a portfolio of creative, right? Kind of like you have a portfolio of stocks in any given time, you know, stock, you know, you want to have a balanced portfolio of stocks to deliver outsized consistent performance. For advertising too, you want to have a portfolio of creative and a more diversified portfolio of creative is more likely to deliver consistent results for you than just one or two creative. And so, and then by running this portfolio of creative, you're more likely to also discover like, well, you know, a woman wearing a blazer, you know, on a laptop is gonna drive more conversions than something that isn't that. And so that's, yeah, I mean, and so that's like, you know, for example, of, you know, what a personalized creative campaign may look like.

Okay, so let me ask this. Is there a natural format or a platform which basically makes the AI ads perform better? So I'm talking about, you know, maybe they work better on TikTok than they work on Meta. You know, maybe they work better for something like, you know, selling the, I don't know, vitamins or something like that compared to selling shoes. Like, do you guys see any trends where AI just does better in a certain industry or format or a platform?

Well, you know, for example, you know, we, we have a fairly diversified customer base, uh, and but I would say, you know, the biggest segments are things like e-commerce, beauty brands increasingly, um, uh, there's definitely a significant cohort of gaming ads. I would say these direct-to-consumer companies that have, um, like lots of, where the conversion happens online and ideally has high volume of those conversions, definitely perform better with an AI system because there's more data for the AI to work with versus say just a brand campaign where you're running, you know, kind of, it's like, it's like, you know, bunch of billboard ads and like there's not a lot of data and, you know, at that point, it's really more of a judgment in terms of what your brand is about and that, you know, you can probably do better in some ways than, than, you know, but if it's in the realm of data and there's more volume data and more conversions happening and you're running ads on performance advertising channel that's focused on delivering, say, creative, delivering display ads, we definitely see better performance. So, you know, say Instagram ads or You know, and again, also I would say that generally today I think images— AI does a better job generating images than video when it comes to performance ads. So I would say therefore right now I think, you know, platforms like Instagram and Meta probably do a better job with running AI generative content because AI does a better job with images than say even TikTok because video is still you know, you can kind of tell when AI generates video still. It's, you know, yeah, the avatars, uh, you have the kind of the AI UGC content, but you can still kind of tell that it's not a human. And versus with graphic design, increasingly it's almost indecipherable from a human, and so, uh, therefore more likely to perform.

So we're saying people care then when it comes to conversion? I mean, we don't know, uh, if they do or not, but if the ad creative is done with AI and people see that it's done with AI, we basically saying that click-through rate or conversions is just not the same 'cause people probably see this as being AI. Is that, is like a right assessment or is it just a pure guess on my end?

I think there's a novelty to AI generative creative, but I think people are quickly getting tired also of seeing AI generative creative, especially bad AI generated creative. And I think ultimately a brand is about trust and authenticity.

right?

And so if you seem fake, then unless your brand is about AI like us, like our brand is about AI, we should run, you know, we like, we run AI ads and that's— makes sense. But if you're like, you know, a high-end beauty brand about like authentic beauty, uh, AI woman, AI-generated woman, then like that's probably, you know, contradictory to your brand about authentic beauty and being real. And being, you know, like, you know, I mean, there's a set— there's, for example, I would say a certain set of attributes associated with certain types of brands about being natural and beautifully natural and, uh, or naturally beautiful and, you know, like, just authentic and, uh, and trust, you know, and trustworthy and, um, and just being real, right? And I think that AI might detract from that. And so you don't want necessarily people to think that the ad was AI generated.

So if I flip, uh, had the question about where AI ads actually AI and do well, if I flip this and say, where do they struggle? Is the, is the conclusion is that they will struggle where they don't have data on? As a result, the creatives will not just be as good, or there's something else where AI advertisement is just not performing that well? Right.

So I would say, yeah, I mean, definitely at highest level, I would say, yeah, like non-digital platforms probably don't perform as well. I would say second, I would say AI still isn't as good at video as graphic design. I think AI does an incredibly job, incredible job with graphic design. I think AI is probably better than the average graphic designer. I think AI-generated graphic design increasingly is indecipherable from human-generated graphic design. And so, um, and so I think, uh, if it's— if you're running an ad that's about an image, if you're running an image ad, I think Even if you're a beauty brand or you're a brand about authenticity, having AI incorporated into your workflow and generating creative with AI and maybe doing some light editing or things like this, but, you know, can definitely result in real time savings and scale and personalization than just relying on the previous method. And so I think graphic design and kind of is, is an area that is, uh, very, very increasingly automated by AI. I think video, it's still kind of, you can kind of tell when it's AI generated. And so there is that element of, there's that uncanny valley still where You know, it's your brand about AI. Is your brand okay? If you're a SaaS company, maybe it's— if you're a SaaS tech company, you should run AI ads all day because, you know, it's like you're all about innovation and the next thing and you want to seem creative and trying new things. But if you're like a, uh, if you're like more of a, you know, old school brand about authenticity and things like this, maybe, you know, harder to run video ads with AI. And so unless there's that novelty again, and that's also you know, you're a heritage brand, but like, it's about, you know, you're like a tech-oriented or tech-centric, or you want to seem innovative or something like this. But I think that said, though, in the next couple of years, or in the next year, I think video will also become indecipherable from AI. And at that point, then it's, you know, all, you know, like, game on also for all content being video, digital video content being AI-generated as well.

I'm just thinking you might get pushed out simply because of that, right? So it's like, it almost becomes that the market will dictate who will run this cheaper and who will run this more effectively. And then if you one of these brands which gonna continue doing this manually because of authenticity, you just gonna probably start losing some market share to, to, to someone. Yeah.

I mean, it, it, it's, it's a great point. And so I think there's been a trend towards personalized products, you know, for the past decade, right? I mean, you can say that social media platforms and personalized advertising, social media has created platforms like Shopify that have fueled the next generation of brands that compete directly for niche markets versus the historic incumbents that were more broad in appeal. And so like, um, and so like, you know, the rise of, of, uh, you know, uh, of, you know, platforms like, you know, like, I don't know, Allbirds or Glossier or things, you know, powered by the personalized advertising, um, uh, and, and kind of, you know, enabled by social media and the personalized targeting that's enabled, you know, that social media enables. But at the same time though, I do think, and I think you're gonna see more of that, you're gonna see more personalized brands, you know, 'cause it's not even cheaper to generate ads and run ads and to even, you know, create products and things like this. And at the end of the day, I think, you know, finding your audience is one of the most important things for kind of a D2C brand. And so you'll probably see more of a rise towards this increasing fragmentation of, brands for niche audiences. I think AI just fuels that further, um, to the point where you even have like the Shine model, which is literally, um, you know, you don't, you don't even generate the product, you don't even have the product, you create the ad first and then you see like what gets clicks. Yeah, then you make the product once you like A/B test the image of the ad itself and then you see what's getting orders and then you actually produce it after you got the order. So like, um, and so therefore you can say that therefore there's actually kind of advantage towards the platform, weirdly enough, that has the most data, which is actually the big brands, uh, because they have scale, they have the most data, and they can quickly, uh, and they also have the supply chains to quickly, you know, produce this type of content and, and you, and, and kind of have bulk data that they can analyze in a deeper way to get insights about, you know, what, what are the consumer buying preferences. And so, um, So I think, you know, so like on one end you have personalization and kind of personalized niche brands, but then you have data, uh, and you have scale, and you also have brand value. And I think brand value is going to also be more and more important in the era of AI, because as there's more and more fragmentation and competition for attention, um, because it's cheaper and easier to create, you know, product and, and run those ads, uh, people are going to be drawn to legacy brands and things that feel comfortable and things that feel comforting and things that feel trustworthy. And, you know, they're— and so I think you're going to see a lot of value returning to legacy brands that kind of figure out this next shift because, okay, in a world where, in a world where there is increased noise and confusion and just competition for attention, people are drawn to things that are long-lasting and trustworthy.

And that's what you're saying here, right? Yeah. Let me ask this. Do you think, you know, Google's product called Veo, which generates, you know, videos, very popular right now. I know people took it to the next level and, you know, probably the most successful things I've seen where they're generating dad jokes with these videos because, you know, you get like 7 to 12 seconds and that joke is, you know, quite sure. So they're doing this faceless channel is just, you know, pushing out these. I mean, it's very well done. They're talking, you know, looks fairly real. You know that product, right?

Yeah, with Veo. Absolutely. It's great. Yeah, it does. And it does an amazing job with matching sound to video, which is very unique to them.

So the question is, do you think they trained this on YouTube videos or not?

I mean, I don't know. Have they said that they have?

No, they can't because, because so I'm just interested because, you know, you guys have your own engine where you generate videos. So where I'm coming from is that you can't because YouTube and everything we upload is ours. And in theory, if they take this data, our videos, and, you know, use that to train their modules, they should be sharing the revenue they get from view. So of course they're saying it's not. But there was a couple of people, you know, going to very deeply into this rabbit hole, sort of trying to prove that they are training on YouTube videos. So that's why I just wanted to see your professional opinion of how would you be able to build an engine like this, like Veo, so good, you know, without actually utilizing so much data?

Oh, I can't speak for Google in terms of what they train their data on or how they go about training the data or what's in the fine print of the terms and conditions when people sign up or if they've recently changed the terms and conditions. I think that is up for them, but I think YouTube is a massive treasure trove of data owned by Google. It is a massive competitive advantage for Google to own YouTube and have all that content. And I would be surprised if, you know, they didn't feel pressure to— in a world where they are facing, you know, in some ways an existential threat due to AI, or, or at least have felt that way for some time, uh, why they wouldn't be, uh, you know, using every advantage they have to compete and, and, uh, and stay relevant.

And so how do you guys then do videos? How do you generate video? So let me give you an example, right? So I want to protect my, you know, brand. So someone does a creative, right? And that creative is generated by AI. So I like, I don't know, like, you know, what the video is showing. Everything seems fine. So I take it and use it, right? But then let's say a woman in a video, you know, was wearing a t-shirt and it had some logo. I have, you know, I have no idea that logo is a real logo. And I, you know, I put it as up my, as my own creative and then company sees that and goes like, like, like, you know, what's up? You just infringing on our brand with your creatives. Is that like a real possibility? Yeah.

I mean, so yeah, gosh, you mentioned a couple of, you know, questions there. So first, I would say that, yeah, I mean, it is a real concern, you know, stealing someone's artwork, stealing someone's brand and monetizing that without their permission. I think, you know, there is, you know, like that is a real risk and real concern. And I think, you know, when working with customers, this is something that you need to discuss with them about that risk and who holds liabilities in these instances or if there's an issue. I think that said, there is more clarity being created in terms of, the law and kind of precedent being set regarding, you know, certain instances where people are liable and certain instances where people aren't liable. But it's still kind of a gray area in terms of like, you know, the legal risks associated with AI generative content. And I'm sure there will continue to be that kind of ambiguity, you know, in the near future. And this is why it's important to, you know, like Um, you know, if you're using one of these AI tools to definitely check for yourself the AI-generated content. Again, for us, I wouldn't speak, you know, like definitely other tools, read their terms and conditions in terms of who's taking the risk when running AI-generated content. Um, um, uh, and, and yeah, and just be like, you know, cognizant of, of the risk you're taking. As an individual. In terms of how we're creating these videos, we use, you know, we create our own models. We also use the best models out there, and Veo is a great— Veo 3 is a great model, but there's also a lot of other great video gen models as well. You know, SeedDance is, for example, a great video gen model right now, and there are many others. And so we are constantly incorporating the best models to generate video content, and that is constantly changing on a week-by-week basis, truly, both for image generation and graphic design and for video. And I think also depends on the domain of the, the kind of content you're looking to generate. So if you're looking to generate video with sound and you really care about the, the, the voice matching this, the image, the video, you know, maybe you care, you know, V03 is the model for you. But if there are other constraints or other kind of goals you're optimizing for when it comes to VideoGen, then there are other models as well, VideoGen models that may be better or cheaper or faster. And so like, it's constantly kind of a calculation regarding, you know, how are we generating this content for customers? And then I guess, you know, yeah, I mean, I would say things like, yeah, the output quality, you know, the domain, whether it's video or music or sound, I would say definitely the speed. The price, the legal— I mean, each model also has its own distinct legal risks as well, um, as well. And so actually, into your point, which you, like, you brought up, which is— so, you know, there's a lot of different considerations, concerns regarding, uh, which model to utilize or which model to make in-house or which models or series of models to combine to deliver an output for the customer. And so, uh, those are things that we're constantly kind of thinking. And so we, we don't necessarily have a consistent base in terms of the underlying model that we're utilizing to deliver creative. It is constantly changing on a weekly basis based on the ever-changing nature of the power of these models. And, you know, and I think it should be changing because, you know, AI is truly exponentially improving, you know, at an incredibly fast rate. And so, you know, our model should constantly also be changing to stay up to date and deliver the best technology for our customers.

I love that. And the growth of this area of technology is just ridiculous. I mean, every week something new is something better and you're like, you know, I'm tired of trying to keep, you know, be up to date with everything. It's just, it's very interesting where, you know, the world will be in a couple of years just because of this technology.

You know, so I grew up, you know, on like with Moore's Law, my grandfather worked at IBM and so kind of, you know, it's like every 18 months, you know, these transistors that become twice as powerful. And so therefore every, you know, basically like the world changes every 6, you know, like you got to keep innovating to stay relevant. And that's the world, that's the world the technology has been in for some time. Um, um, you know, uh, with, with, you know, with, with Power BI Semiconductors and, and, um, the kind of increasingly smaller size of these transistors. What you're seeing now is actually even acceleration because you're seeing across the entire stack from the transistor up optimizations being done. And then also you see more capital investments as well into more transistors and more power. And so you're seeing, I think it was some research done that was like the power, you know, it used to be the power would double every, I don't know, 18 months or something, but now power is doubling every 6 months, if not. Yeah, I think that's generally what's been shown. And so the pace of progress is accelerating, or at least the power of these, the power of computers or power of AI is accelerating. And so definitely people feel that. And it's a trend that's going to continue because, you know, there's massive resources. It's an international competition regarding, you know, people think it's, companies and countries think it's existential that they stay up to date in terms of, and they stay at the very top of this technology. And so the amount of investments is only increasing into this field, which means more semiconductors, more power. Uh, people are literally building nuclear reactors, uh, for this technology to funnel more power into these models. Um, a lot of these things aren't even online yet, and they're going to come online in the next couple of years. And so, uh, progress is only accelerating as people view it to be more and more of an existential thing for their companies and for for, you know, for nation states, etc. And so, and so that's what you're seeing in terms of the insane progress being made. And I think you're going to continue to see acceleration in terms of this technology, you know, for the foreseeable future.

Are we going to see TV ads which is going to be full AI? Like, how many years, you know, are we giving here, Kairos? Like 2, 5 years? Less, more?

I think within 5 years.

Within 5 years. So we're going basically looking at YouTube, there's going to be an ad playing you know, things you see right now, I mean, Grammarly is pushing a lot of ads. If you're part of YouTube, it's pretty much everywhere, you know, this real actors, you know, doing this skit, which is like 60 seconds ad, right? We're basically saying that that just gets AI'd eventually, like in—

Well, I mean, I think you already, I think people are already seeing video. And then you mentioned actually probably some people are, you know, seeing a lot of AI video content on YouTube. I think people were already running video ads on YouTube that are AI-generated. We already have tools enabled for customers to launch ads on YouTube, um, with AI, uh, that are AI-generated. Now, that said, I think today, um, it's still a little bit— you can still kind of tell when it's AI-generated. But yeah, I think so, so like we live in a world today where people are running TV ads on— that are AI-generated. What I would say is that you'll see it becoming almost indistinguishable from, you know, the video ads that you're describing Um, you know, the human-made ones with the live actors and, you know, all this definitely within the, within the next 5 years, 3 years. And yeah, soon I think, you know, television ads in general, I mean, as people move from number one from television to streaming, which is kind of a trend that's happening and kind of accelerating and kind of now streaming is bigger than television, like historical cable television. Um, and so as people move to streaming, that means now anybody can run personalized targeted ads like you could run on social platforms on television. And yeah, all that, probably the majority of that content is going to be AI generated in the next couple of years and it'll be indistinguishable from human generated content.

We'll see what the actors do, the ad actors do. I mean, it's just disrupting all the markets.

See, I think, you know, you— I think the value of brand— I don't know about the value of acting per se. I think, I think at the very pinnacle, the very top 1% of actors will continue to make more money than ever, uh, and probably continue to actually have more scale than ever. And yeah, probably be more profitable, successful than ever, probably. Like, the ones are really, really great at their craft that AI cannot mimic, that skill will probably be even more valued in the future. Uh, but yeah, the average actor that's doing the, you know, that's doing the ad for the 5-second commercial or 30-second commercial, I mean, yeah, probably an AI is cheaper than that. Uh, and so, um, uh, and so yeah, I mean, that would probably be replaced by now. I think the average work will be automated, but like, yeah, any domain, I think ultimately, you know, the top, you know, 0.1% of skill in that domain will continue to make potentially even more money today— or sorry, in the future— than they, than they do now because it's so rare and so value that skill. Um, I also think that the value of brands, like, you know, because an actor is also a brand, and so that brand value will also only improve, increase over time. And so, um, uh, uh, you know, because people, you know, if there's an actor that is just famous because they're so skillful and everyone respects this person because this per— and, you know, kind of adores this person and is a fan of this person because of their unique skill, that brand is going to be more valuable than ever as well. And they can use that brand to sell all kinds of products and sell, you know, other things. And so, um, I think the idea of, yeah, like that, like superstar actor, famous actor with unique skill will continue to exist and continue to be more lucrative in the future as they figure out.

I understand what you're saying, Hikaru. So, yeah, I mean, the gap will just, um, will be the best at the top, then it's just basically AI which can fill the low and mid-tier. And we'll see that in a lot of industries which will get affected by AI. Right. Okay, let's go back into AI advertisement. So I'm keen to understand what you believe is core metrics to assess if your AI campaigns are doing well. Is it literally the same as you would do it right now?

I mean, we talked about efficiency and speed and ability to A/B test much The most important metric in advertising is return on ad spend, which is, and this is the metric we care the most about as well for our customers, which is for every dollar you spend on an ad, did it deliver? How much dollar in sales did it deliver? And so you can measure this now with attribution, with really great attribution. So you can see, okay, I spent $1 on ads and it will, I see this for our own ads for sure as well. It's something, like did it deliver $2 in sales? Like did the person see the ad? Did they go to the website and they buy $2 worth of products or do they buy $1 worth of product or do they buy no product? Uh, and then you can measure that sales over, you know, attributed sales due to an ad to the amount of money you spend on the ad. Uh, and what's great and beautiful about advertising technology is it's kind of an even playing field. If you can deliver superior return on ad spend, you have an advantage over the biggest incumbents. For example, a company like AppLovin, uh, you know, really created a niche for itself versus a humongous company like Google because ultimately, at least, you know, they, well, also because they convinced advertisers that they deliver a superior return on ad spend than Google because of their unique inventory of users, their AI. and the way their AI is mapped to their unique inventory of people who view these ads. And so, um, uh, and so any startup, in some ways, like, you know, a startup can go and compete against the biggest companies in the world if you can prove that you deliver superior return on ad spend. And that, you know, is powered by unique inventory, that's powered by unique technology, that's powered by, um, having great product. And so the metric we care about for our customers is, do we deliver a high ROI for their advertising spend, return on ad spend?

So there's, of course, a lot more metrics. But ultimately, if that's the one, if any of the founders listening and thinking, I mean, clearly advertising their products or a service, you know, that they do whatever they do right now, they probably know very well what return on ad spend is. And we basically saying, if you never tried AI advertisement, you want to go ahead and give it a go, continue looking at this metric and you should be seeing not only that metric being better, but at the same time, you're just spending less time to get these creators up, right? And that's a, that's a big value proposition. It's a very, very tasty one.

Exactly. It's 3 metrics. Time savings, cost savings, and increased return on ad spend.

I love that. Still, there's plenty of founders which goes like, nah. So when we talk with skeptics, right? And it's usually people who didn't play, didn't experience, didn't see it, you know, don't use, you know, ChatGPT or some, you know, generic, very accessible GenAI tools. You know, they have these doubts, right? So the mind shift, you know, like needs to happen. Like if you're talking with the founder like this, um, what are you saying?

Um, like, like, you know, I think some people are right to be skeptical. Um, um, and you know, there's that kind of crossing the chasm and you have the early adopters and you have the late adopters and you know, and that's just the reality of any distribution of people is you can have late adopters and have early adopters and you know, if someone's a late adopter and that's just the personality, you know, they're, that's just like it's going to be hard to convince them. Like they're just, they're not in the mindset to try new things. And maybe it's because of the business model. Maybe it's because of the risks associated with the brand. Maybe they have more to lose from using AI. And again, I've mentioned a couple of industries that are like this and certain types of brands that are like this where they may feel more disinclined or disincentivized to use AI. And that's totally fine. And I think they will ultimately utilize AI. When they feel ready to use AI. Um, that said, it might be too late, but you know, I think there's that, you know, there's that adage which is, you know, you know, there's too late but also too early, and you know, you can die both ways. And so, um, and so, you know, again, I, I respect some of these companies, you know, a lot of these companies, the, the decision-making, and you know, some of them will, I'm sure, move at the right time. Um, And, uh, but one thing, you know, to be said is ultimately, you know, you're not going to be replaced by AI and your company is not going to be replaced by AI, but your company has been replaced by a competitor that's using AI more effectively. Uh, and so, you know, if there's new technology and there's a new tool and it's a very powerful tool like AI, and if you aren't utilizing AI, uh, and your competitor is, uh, then you're giving them a head start. Uh, and, and, uh, and, and also I think AI is kind of like, requires a cultural shift within the company to incorporate AI into your— so it's not just like, it's kind of like the internet, right? Like, you know, yes, Borders could always build a website, but their culture was not in their, their organization was not structured to be an internet company, and that's why they got their lunch eaten by Amazon. And so similarly, I think it's not just of like, oh, are we going to run this POC with AI? But like, really think, okay, what does that mean for distribution? What does that mean for my business model? What does this mean for the way I interact with my customers, in the way I develop relationships with my customers, and how do I utilize this technology to develop a closer relationship with my customers, to get more trust from them, to be more relevant for them, to be more helpful for them. Uh, and, and that may require cultural shift, that may require a business model shift, that may require an organizational shift. And so, um, you know, that big, big legacy business may need to pivot their, uh, you know, business model or strategy. And so, you know, like, I think there's almost, you know, we ran a POC with AI, okay, we're good. You know, that's not sufficient either, right? Like, I think ultimately it's important to be deeply thoughtful about how this technology impacts your industry and your relationship with customers. And then for what does that mean for your company? And then, you know, thoughtfully make the right strategic decisions to transition into a different kind of world. That we're entering, and we are already kind of increasingly in due to AI. And so, um, I think there's the kind of speed in which maybe you want to equip this technology, but I think there's also the thought in kind of, you know, you want to also be very thoughtful, I think, as well in terms of how you incorporate this technology. And maybe it's better to be more thoughtful, be a little bit late and do it right, than to rush and do it early and do it wrong. Uh, and so like, I think, um, um, You know, I, I, you know, like, I totally understand, you know, the hesitancy that some of these companies may have. And I think there's also still a lot of ambiguities regarding the legal concerns and risks. There's also concerns regarding data. Like, you don't want to rush and just hand your data over to some startup that then, you know, captures all that value or creates a ton of value, you know, or actually extracts value from you in, in the wrong disincentivized way. And so, uh, I understand there's a lot of concerns as well when it comes to data and brand and legal risks. Associated with embracing this technology too soon. And so generally what we've seen across our customer base is a higher adoption of this technology with consumers in consumer price and other startups than incumbents in enterprises. Um, and that generally the enterprise company has, I think, been slower to really embrace this technology, though they're running little POCs here and there. But I think the research done, right, that most of these enterprise POCs have not been that successful. Versus widespread adoption and growth from the consumer price and consumer segment side of the market, which is actually quite interesting also, because I think historically sometimes enterprises have been leaders in terms of technology shifts versus consumers. But today I think consumers are more of the innovators when it comes to embracing this technology.

So if I'm a founder, how quickly can I expect results from from AI advertisement. So I'm just thinking from, you know, I'm skeptical. I don't want to try it. It's like, hey man, you only need X days to actually capture the value and understand the value. So are we talking like a week or 14 days? I go in, generate, launch an ad, see return of ad spend. Like, what's that time horizon to actually understand, you know, the help AI brings here?

Well, I think hopefully you understand that time value in the first couple of minutes of signing up for the tool. And definitely a couple hours of using the tool, you'll see the time savings and like, wow, like this thing that used to take months now takes me minutes. And we see again, our, you know, our average user, not only average, just the average session is very long. Like we have highly engaged users in our platform. Um, and, and, uh, and so I would say. Like definitely in the first hours, I think you'll definitely find, you know, you'll see like—

So that's like an easiness and time effectiveness and then return on ad spend, you probably still run your campaign.

Yeah, and for ad spend, I think generally people say it takes like a month to like see the return on ad spend increases just because it takes a while for the platforms to also optimize the creative and optimize deliver that creative and find the right audience for your creative and things like this. And also it's a function of your ad spend as well and what your advertising budget is and how much data you're quickly giving to these platforms to optimize for a certain conversion event. But I would say generally like a month in terms of return on ad spend. But in terms of time and cost savings, I think it should be imminent in the first couple of minutes, the first hour, the time, the value that's being created in terms of time and cost savings.

Okay, let's say I'm listening, I'm a founder and I'm like, you know what, another service I need to pay for money, I'm not even sure. Would you give any advice to people like this in the sense of not trying Omneky, but potentially, you know, do-it-yourself type of approach? Is that even possible to reach, you know, with open source module? And if you're a little bit of technical, like how much effort we're talking about here to actually be in a point where you can get a creative, a decent creative? It's never going to be level of, you know, Omneky, but you know, I'm cheap, you know, I just want to do it myself type of guy.

Precisely for that type of user and person, our product is free. 7-day, first day, 7-day, first 7 days is free, free trial. So it's up, we understand that people are skeptical and people are cheap, for sure. I understand that, especially if you're an entrepreneur, you have to be cheap. And so, you know, like I think like that's what we offer, free trial. Like try out for yourself, see, try the tool, generate the ads for free, Launch the ads for free, get the insights for free, and see for yourself the value. And I think you'll realize that the product is worth paying for. And at least that's what we see in terms of our trial to conversion rate, paid, you know, free trial to paid rate is, is a very high rate because people do see that it is worth the $99 that we're charging on a monthly basis, uh, for, for our platform, you know, for utilizing our platform.

It's a great— yeah, it's a— by the way, I, I know, like, I tried it, so I, you know, I'm not like— I'm not even challenging the notion. The time saving is just insane. And, you know, you, you just get a creative where you can just go, you know, get going. But in my mind, it's like, like, yeah, if I want to just do it myself, you know, it's like, is that even like possible? Like, if you load up, you know, some open source like, um you know, will you be able even to get like a creative, a decent creative?

I mean, I think the question is, is it possible for me to build my own computer and build my own server and, you know, do all these things and source the materials? And like, yes, it is possible for me to do all these things, but like, is it worth my time? And it's not my differentiated edge in a competitive business market is to spend my time reinventing the wheel or to find, you know, or to play into my strengths and my unique advantage. In my unique perspective to, uh, you know, to deliver a great product for the market. And so, um, um, I think our product was worth it. $99 is definitely worth the value we provide. Uh, and I think founders, you know, instead of spending that time creating ads, you know, manually creating ads on these design tools, which, you know, by the way, you know, most, most fontpreneurs are not designers, they're not graphic designers. That's not their skill. Their skill is building great products or, um, product, you know, or services. And so, like, I would say, you know, focus on, you know, focus on building the best product and service that you can, and then, you know, let AI generate graphic designs for you. Because the alternative usually is just you hiring a graphic designer, and I can assure you that our product is cheaper than hiring a full-time graphic designer or marketer to go and run these ads for you.

Or a freelancer for a campaign or something like that.

Exactly. It's much cheaper than a freelancer. Answer. And so, um, um, and so yeah, instead of like spending the time learning how to run ads or learning how to, you know, become a great designer, let AI do that for you and focus, you know, and, and then, you know, and then you can have, you can have more time to focus on all the myriad of other things entrepreneurs need to focus on to build this viable and successful business.

Excellent. Well, uh, thanks for sharing all the, uh, golden nuggets, uh, in this episode, Hikari. So if people want to keep learning from you, How do they get in touch?

Well, you can definitely email me at hi@omneky.com. Hi@omneky.com.

You can follow me. Hi, right?

Hi.

Hi.

Yeah.

Yeah.

Hi. Hello. Yeah. And then you can also follow us on X. You can follow us on Instagram. You can follow us on LinkedIn, Omneky. Search for Omneky on any of these platforms. You can follow our YouTube channel. We have a lot of great content there. And most importantly, you can sign up for a free trial and try out the technology yourself and try out the tool for yourself and see the value for yourself.

Excellent. For people not tuning in live, just check the show notes. You'll have all the links to connect with Hikari. Click on the trial, give it a go. 100%. If you run ads or you plan to run ads and you are a small, you know, or a founder or entrepreneur and you just want to try it out, pay for a month, right? Like pay $99 for a month. That's going to be cheaper than hiring any freelancer. And in that month, you're probably going to see the value and continue using the service. Um, as well, um, drop your growth questions in the comments, um, and visit masteringtechgrowth.com to check our community out. And as always, guys, until the next time, stay safe.

It's a young lad.