The Boring $15k AI Offer That's Killing SaaS (And Making Millionaires)

The $5 trillion AI SAS industry is about to crumble. And it's going to create one of the biggest opportunities to create wealth with AI that we have ever seen. And this is because businesses right now are wasting on average $100,000 per year on a mess of software tools that don't talk to each other, creating a data nightmare that makes AI completely useless. And today, we're breaking down the exact $15,000 service that replaces a business's entire clunky SAS tech stack with a custom AI powered system. and I'm going to show you how as a beginner you can start building and selling this kind of system using just vibe coding tools like lovable. So let's get into it. Thanks for coming on.

Excited to hear what you got to share with us today. — Ken as mate. Yeah, really appreciate the opportunity. I'm looking forward to jumping in showing you through the whole thing from start to finish. All right, so quickly what I'm going to just take you over is who I am. So this is my Upwork profile. This is where everything started. Uh I'm in their expert vetted program or the top 1% program and also the top rated program. So I've done a hell of a lot of work through here. You'll see AI transformation partner was actually coined term from Ulim. Uh but we've done a lot of work in the AI space and this is where I learned all of the groundwork skills that allowed me to understand the business proposition that I'm about to tell you about. So from there I built uh similar channels. So I've got a YouTube channel where I talk about freelancing and AI. Um, I've got a community and then I've also got this agency called APG Software which has done in conjunction with my brother and business partner over 250 projects. Uh, we've done work for one of Australia's biggest TV shows, Pittsburgh's [ __ ] Grown Company, Australia's biggest solar company and one of the world's biggest fast food chains. And it's built off the back of a generic software company. So we initially started building software for everybody. So process automation and apps of every kind, SAS apps, internal systems, everything. But we found a new opportunity that we're kind of going all in on. Um, similar to what you talk about in the productized services and niching your agency, we're trying to niche down into one offer that we genuinely think is addressing an extinction event with AI and where AI is going to be in 5 years. Um, and the solution is based around internal systems for businesses. It's a 10 to 20k USD offer in 2 to four week sprints and I think that is generally going to address an issue that is going it's do or die for businesses in the next 5 years and they don't even really realize it yet. So massive opportunity there. — I've been thinking about the same thing as well and I definitely think even at Morning I this opportunity up. It's like where is the where's it going to break first? How is it? Who are the people that are going to be implementing it? And I think it's been really exciting to see you guys pop up um because that's obviously the start of the bottom end of things and coming for the small businesses. So yeah, excited to get into it. — Yeah. So the reality in 2025 is we have this massive SAS landscape and every business is in most cases we can see here even businesses with 0 to 10 employees are spending you know close 50 close to $100,000 on this on their software subscriptions to operate their business. And as we get higher up, we get into the multiple hundreds of thousands of dollars. So some of the key things to take out of here is that companies are wasting or spending on

average $89,000 on SAS waste. That average spend is about 5. 5 grand per employee and almost half of those SAS licenses are going unused or underutilized. So there isn't there is an issue here and companies are investing a lot of money in these tools to operate their businesses. And I've actually got some live sales calls with me selling this offer on YouTube where you'll see business owners, they all know it. They can feel this pain. They're talking about it and it's this SAS sprawl. It's this mess of tools, like 10, 15 tools. It's it really looks like this. It's a mess. And people like a lot of these business owners, they don't even know what's happening in most of these tools. Um it's a mess. They're spending a lot of money on it. And the data is disconnected. They're duct taping these things together to try and get something to work. — I mean, anyone who's doing AI automation will know recognize all those things very clearly and the jumble if you are trying to build a system for them, how much harder it is to build on top of those when you're having to connect between all these different places at once. So, there's like particular looking ahead into the AI automation future those rails for them to add on AI on top of um it's not necessarily the best foundation to be building on top of. Right. — 100%. And I'm going to that's what I'm going to build up to here. Um yeah, we come from a process automation background using make. com, Zapia, NAN to like duct tape these things together, but it's a duct tape job. It ideally it would should all be in the same spot. And so the reality check here is that the reason SAS is great for smaller companies. They on board, they pay a little bit of money and they get this like state-of-the-art software that looks amazing that they can jump straight onto. But what happens as they scale is these per user per month subscriptions that the vast majority of these tools charge start to add up and a lot of these tools end up getting underutilized and budgets, you know, companies quickly start spending tens of thousands of dollars on these subscriptions. And so why SAS even exists in the first place, long story short, behind the scenes, tech is confusing. There's APIs, frontends, backends, servers, clients, clouds, all these technical terms. And if that doesn't make sense, it's not supposed to make sense because. 3% of the world actually knows how to code. And a fraction of them are experienced enough to be able to handle all this infrastructure. So traditionally, especially when we're talking like '9s, 2000s, 2010s, even to this day, to be honest, proper software development, production grade enterprise software takes years and millions of dollars. So naturally, what happened is SAS entered the scene. Now, the same way that we go to the grocery store to buy meat, if you want to have beef hamburgers for dinner, you're buying from a grocery store, you don't have to go and kill a cow and worry about how that gets into your source bin. The grocery store handles all the messy business. You go and buy the ready-made product from the grocery store and it's ready to go. SAS did the same thing with tech. So, they take care of all the messy business. They build you a nice interface. You basically pick whatever you need off the shelves and you can use it pretty much instantly. So what happened was we had this honeymoon phase where companies typically only enterprise companies could afford to build their own software. So we had this honeymoon phase where the small business medium businesses, the real estate owners, the landscapers, the small guys could come in and they could use tools that and compete in this market and get on board in these tools in like weeks and for a couple of thousand. But as they scale, things start to add up and couple of issues. Same way with the grocery store, there's a couple of issues with these SAS platforms. One is that there's no customization. So, you can pick from a couple of different types of beef or a couple of different, you know, rice brands, whatever, but you can't customize the quantities. There's a limit to the customization you can do. And the other thing is vendor lockin. So, as we're all familiar, we all remember co what happened when the grocery stores started running out of toilet paper. Uh it was absolute chaos. So we become reliant on these vendors to they handle all the messy business, we forget how to even do the messy business. And so what happens is it's all good 95% of the time, but if something happens and those vendors that we rely on start to buckle, we don't know what to do with ourselves. And so the same thing happens with tech. But up until this day and age, those cons are well worth it. I mean, we're weighing like millions of dollars in years of development against a couple of risks, but in the grand scheme of things, that made a lot of sense

until the age of AI. So, this has completely changed the game. Well, what's happened over the past couple years? So, we've had the introduction of AI coding tools and AI in general that has dropped the speed and cost of software development and it's also promised to increase productivity. But I've seen you talking about this, Liam. This is the promise. The actual reality is starting to look a little bit different. So, we've seen big consulting companies and stats come out of a lot of companies investing heavy in this AI and spending thousands of dollars, but the ROI on that investment is actually underwhelming in a lot of scenarios. And so, the answer is why? Like it, you know, we all can all go on chat GPT. We can see it can do crazy things. It's obviously very intelligent. So why are businesses struggling to actually make this AI productive in their businesses? And the reason is because is of what we call the context problem. AI is extremely intelligent and in the next year or two people are talking about super intelligence and all sorts of crazy stuff. It's basically currently operating like a Harvard MBA with a blindfold on. So what's happening is a lot of businesses are bolting on what you'll see as like NAND workflows and AI automations, but it doesn't have access. The data is all over the shop. They've got meeting recordings in places, tasks in places, documents in Google Docs, invoices in QuickBooks. All this data is all over the shop and it's not talking to each other. So, the AI brain doesn't have the actually have access to the information that it needs to generate quality output that is as good or better than a human. I still think this isn't like talked about enough like it just the complete difference performance of your own I mean I use AI writing assistants a lot like I build my own I've been going on claw code and creating my own like a writing assistance and the context is just the essential ingredient it when it knows everything about me my businesses my strategy um sort of recent things I've done and if you have good data feeds to add into that and make sure that it's always up to date with the latest information about you and your business. It's just completely game-changing. So, I think this is really there's a huge opportunity for a software or a company to come in. I don't know who would do it, whether it's like a small guys like us could get a go in there. Um, but essentially being the all-in-one context hub that can sort of be agnostic across platforms and whether you're hooking into it's kind of like how you had the like you can have MCP servers and you could have a platform that connects all your MCPS into one and that's what you use across you know like one integration point uh rather than having to integrate into all of the different ones uh manually and I think there's a there's an opportunity for like your context brain that can shift across different uh different platforms and different providers um similar to what you talking right here. — Yeah, 100%. Context is really the diff and nobody's nobody talks about that, I think, because there's so much hype around like the automations and people just trying to take a screenshot of an NN automation, but don't really show the output. So, it looks cool, but the reality is a lot different. So — and I think I think one of the issues as well is that context is kind of like the thing that Claude or Chat GBT and these kind of companies when it comes to their projects uh that they are intentionally like vectorizing and chopping up that data to retrieve it in smaller chunks right but the re real way for it to work I mean there's context engineering but in most cases it's like I here is the context I need to be it to be aware of in every situation and they just go chop it up and give you little chunks back. So, um I think it maybe they don't want to talk about it as much cuz it's going to push their costs up massively, especially on their subscription plans, but yeah. — Yeah. And well, and the other thing is like you're you don't really have access to your data. These big companies do. So, you can't really make a move unless these big companies like, okay, we're going to give ChatGpt or whatever access to your data. So, yeah, that that's kind of the issue. And the inevitable solution is what we're going to talk about now, which is an entire CRM or one unique software that's going to do two things. So there's two real problems that we solve with this tool. I think there's the problem that these business owners feel. So when you look at the sales calls on my YouTube and basically when I talk to business owners, especially nontechnical business owners that they hear all the hype, they don't really know what it's about. The problem that they feel and they can relate to is the monthly bleed of these SAS tools. So they're spending $3,000 plus, sometimes like $10, $20,000 a month. They feel that they it hurts them. They see the money go out every single month. They see people staff members not using these tools properly, not really using them. That's the angle that we've had the most resonation from business owners on what we solve. But I actually think there's a bigger problem here that is under the hood that most people are not aware of, which is this AI extinction event. And like I've seen some of the biggest podcasts out there. I was looking at the Steven Bartlett on the diary of the CEO. He's interviewed a bunch of people on like is AI and some of the statements that these people are making and working every day in AI like it doesn't some people are saying that you know massive things about UBIS and 80% of the workforce getting uh replaced and all these crazy things. Doesn't really matter what your take is, but I think everyone's on agreement that this is going to shake businesses up in a way that we've never seen before. And so in my opinion, the time frame is up for debate, but in the next 5 years or so, companies without AI unified data will not will cease to exist and not be able to compete because the competitors that have integrated AI properly are going to be operating at 10 times productivity and for a fraction of the cost. You can see this as the rails just like how we were talking before unless they have with all of these automations and I think particularly once you have these huge like AI agent workforces where or you've got multiple different specialized ones created or you have things like the chatb agent where you have these generalized computer use ones the that layer of context that can just spread across all of these different uh systems that they build is going to be essential. — Yeah 100%. And so that gives birth to

the solution. So we've been running software company for the last four years. So, we've built a ton of internal systems previously, but the solution that we've built is, and I'll talk about some of the issues with this a little bit later, but the solution that we've built here is it's basically a 10 to 20,000 USD offer. And what we do is we replace a large portion of your SAS stack with a custom internal tool that we build in two to four weeks that strips you of those per user per month fees, but at the same time gives you a proper system to protect yourself against this AI extinction event and be able to properly enable AI into your business. — So just some quick stats on this. So we've been doing 40 to 60K per month on these builds in the last 3 months. So we've really focused we we've moved away from being a generic service agency to try and just focus on doing this one thing and doing it correctly. So that's been the main focus um of what we've done — and on the I don't want to like steal man the push back you might get from some of these business owners like okay so I'm going to give up the reliability well flaky I suppose reliability is questionable in some of these uh these bigger systems they do break as well but okay I'm going to put myself on the hook for a custom software now that I have to rely on you guys for as people who can be the so it's essentially like handing the keys over to being reliant on a on an agency which is — always the push back you're going to get. Oh, so what? So this means if I want any change I have to come back to you you've attached me and I'm reliant on you now. Um and what's this realistically if you were to add up all those maintenance fees and costs for the year um what is what would they be paying an equivalent to their SAS thing? — Yeah 100%. So those are two common objections. So the first one is we completely open source this. So I personally think that the SAS model is going to have problems in the next 5 or 10 years. So we with this things this whole thing is completely open source. They can they own the code. Uh we aim to manage the entire thing for less than a thousand USD per month. So they own the code. They could go and work with another developer if they want to. But because we know this system so well, we think that's unlikely. But this is not it's not we're not selling a SAS here. We're building them the same way that we've been building apps for companies for 5 years. And every app that we've built, we've like 98% of them will stay on with us for maintenance. I can't even remember one that hasn't. So that same approach, we're using that same approach here, but we're just building one specific kind of app that we know thrown through. — Mhm. — Okay. — So, — cool. Um, and I'll take you over the rejections as well in a sec of of this, but essentially what happens is these are like 80% of service based businesses under the hood operate very similarly. So these basic functions we've got like CRM functions, client and company management, projects and workspaces, task boards, messaging, etc. Uh lead genen and quoting estimates, proposals, stuff like that, dashboards and reporting, social media calendars and marketing and what I think is completely essential in the next 5 years, which is AI ready infrastructure. That's what we're aiming to build into this tool and template. So a screenshot of one of the screenshots or examples products that we've built. Now this product we're constantly a form in we're constantly improving the way we build this. AI is genuinely like even in the last year the way software development works at agencies that are actually up to date with what's going on has flipped on its head massively. Like we've changed our business processes in the last one year alone more than we have in our entire existence. So this is constantly updating. But some of the functions that you're going to see in these are like dashboards, custom dashboards. So this would replace SAS tools like PowerBI. We've got lead qualification um and yeah lead qualification. So lead genen comes through gets displayed in this board. Bunch of like AI sentiment checkers that kind of stuff. Quoting, estimating, proposal generation, invoicing, payroll, projects, some project management, more project management. So AI sentiment trackers on meetings channels so communications things that Slack Trello would typically be used for is these are some of the features that we build similar to what we talked about before and that kind of conjugates itself into this AI brain AI agent UI here where we can build these interface. Now this is just a surface level like a service level is a rag chatbot that's able to essentially extract all this data. So, we're talking every message sent in your company, every invoice sent, every proposal, every task action, everything that happens is all happening in one place. The data is all in one place. We can use it. We can access it and use it really, really quickly. We're not duct taping all these tools together, worrying about API access, all that technical stuff. It's dead simple to build. In this use case here, we're talking about how many hours we logged against a project, but you could ask it anything. — Okay. Interesting. This is a my best shot at trying to explain what is pretty complex especially to nontechnical people on how this entire system works. So ideally you have a CRM. This contains absolutely everything in your business. Everything from leads, proposals, messages, invoices, transactions, everything. That data is synced into what we refer to as the AI brain which in technical terms is usually a vector database in along with some sort of knowledge graph technology. Then you have your AI agents. So what everyone's really familiar with is these n automations agents that do things like generate UGC social media posts, build proposals, etc. These source all their contextual information from this knowledge graph or sorry this knowledge base and then use that within your business's processes to reduce the time spent on boring admin stuff. Uh and essentially yeah reduce the time spent and increase your business's efficiency. So in as basic terms or in as basic way as we can put it this is what this entire system aims to do. — So yeah makes sense. Yeah, really difficult to like explain this to your average small to medium business owner who does not care about technology at all. So, we've done our best shot there. — So, so those agents are the ones that you're running sort of programmatically in the background. They're not necessarily like co-pilots or thing that are built into the uh into the software you built. Yeah, — exactly. Yeah. So, the initial product that we build is just the CRM system. We every business is different. They need different agents. So, this is what we build on top with the data that we've got here. So yeah, these are in most cases just NAN agents that post the data back into this original system. Cool. So who's this for? We obviously there's only a very niche buyer that is interested in this and it's usually small to medium business founders, but they tick these boxes. So typically service based businesses spending at least $3,000 per month on SAS. They've heard about AI, which is pretty much every business owner on this planet, but they don't really know what to do about it. And they just want a system, smart, simple system that works. So, how do we do it? — Yeah, this is the source that everyone wants to know, bro. So, dig it in here. — I could talk about this all day, but there's two ways that we do this. So, we use AI coding and we also use a templated based approach. So, we have a template that does in our case 60 to 80% of what most of these businesses need. So, we build all of this functionality in a template software that works, that's stable, and then when a new business owner comes in, we're using advertising to try and target the correct buyer in an industry that we know we've already got 60 to 80% of this templated approach and we obviously tweak it to their individual business's use case. That way we can ensure that it's stable. We can build it quickly, which are the two most important things we're selling to businesses. And it's also cheaper and more efficient for us to build it. So we start with a template and then we use clawed code in conjunction with something that's called the BMAD method. Now before I like jump into more detail on what the BMAD method is, I want to shout out the guy that built this because the whole thing's open source. It's completely free. You can watch a full master class on it on YouTube um and fork the entire repo yourself. And if you're someone that's like in this vibe coding space, you're playing around in Lovable, VZ, you're trying to build apps, I cannot preach this system anymore, I'm not going to jump deep into the weeds. I've got full videos that I'm releasing that will jump into the weeds on exactly how this works, but essentially this is a framework of how to build actual stable production grade apps. We're hearing with a lot of this like AI vibe coding that it gets you 80% of the way quite well. And I've been doing a lot of playing around in Lovable and those tools, but a lot of people start to have hiccups, especially towards getting something actually production grade. This will solve a lot of those problems for you. And genuinely, no one's really even talking about it. Uh, but promise me like, go download this, try it on a project idea that you've got, spend an hour or two in here, and come back to this video and let everyone know how helpful it was, cuz I cannot preach this enough. — I'm going to have to give it a go. — Yeah, it's cracker. Um, and so the key thing here is that AI coding or really coding in general is 80% planning and 20% execution. And so that that's what this BMA method will do is it will plan things out extremely best practice. It takes you through the proper process for how to build apps and breaks everything down really moduly. So when we scope out these projects, we use claude code along with this BMAD method to have a really stable way along with knowing technical skills as well. — Mhm. — But that's how we bolt on the extra 20 to 40% on these initial templates. And so the general AI friendly tech stack that everyone's talking about things like resend for email, we use Nex. js and superbase to build these apps. N for the workflow automations for self for hosting pine cone for your vector database and that yeah that's the general stat — my question always is even when I'm doing building my own vibe coded apps is just like how if you've like one shoted this you've done a really good plan then it executes on it like how are all the little connecting bits that are necessary cuz there's a lot of little buttons that are going to be on a on a full dashboard and software like that like — do they come out of the box working or is there a ton of debugging that you need to do go test every feature. Of course, you got to test it, but like what's the realistic failure rate on things like that? — Yeah. So, we before we even get to prompting anything, we build there's an entire playing process before we even get to prompting these tools. In terms of fail, the way this BMAD method works, so like it's different to lovable cuz the way lovable works is you build this giant prompt. It tells it what to do. You try and like there's this is not really about oneshotting. It's a little bit slower than like those vibe coding tools that you will that you'll that the common ones out there. Um, so it's not really a oneshotting process. It actually breaks everything down into like individual tasks and you work through each task uh methodically. But what that does is it actually helps you understand what you're doing cuz when you work with lovable looks great but you don't really know what's going on under the hood. It will explain everything that's happening and it is a hell of a lot more stable. So yeah, there's way less hallucinations. It injects the correct context into your code. It's it is slower. Uh by slower, I mean we're not oneshotting things and walking out the room in 10 minutes. Um so it's not slow by any means. It's rapid, but it's not it's we're not oneshotting anything and building a full internal 10K system in 10 minutes, but we are doing it in two to four weeks with the combination of these processes. And yeah, can't hop on about this enough, but it will actually help you understand what you're doing cuz I don't think you can constantly sell tech with at least you or someone that you trust having an understanding of what's happening. And this will help you solve that problem. — I suppose the key thing is that we're about to jump into here is once you've got that base built out as the sort of the central software for them, then that gives you the platform to build the all the agents and automations on top a lot more easily. Right. — Exactly. And it's really just n bolting on n automations or like sometimes it's adding extra features into the software as well. But yeah, how

so how do we charge for it is going to solve that answer. So it's like a three-step process to selling these. So there's the scoping. Now what happens in the scoping is we essentially the scoping is critical. It's really important. It takes longer than the build in most scenarios. The we do two things. So we wireframe the business life cycle. Now what I mean by business life cycle is every process in the business from client acquisition all the way through to product or service delivery. So usually that typically looks like some sort of funnel lead gen system comes through lead qualification process followed by often like an estimate a quote or proposal followed by invoice for project kickoff. Then there's the whatever ops are involved in delivering that project and then we've got the project delivery. We need to understand how that works in detail before we can really do anything. So we need to understand that how it works and we need to understand how you currently do that. From there we can do two things. We can use lovable and or v 0 or any of these tools to prototype what a new system could look like for you and we can identify areas of opportunity for and basically justify the business use case of this new solution. So there's two ways you can do that. One is you can demonstrate that you can replace a number of their SAS tools which cost X amount per month and so you can display that saving. The other way you can display savings is by reducing manual hours or manual work from their team. So for example, if their admin team spends 20 hours a week doing payroll and you can demonstrate a system that takes two, there's 18 hours times the admin's hourly rate of weekly savings that you can justify. So this scoping phase, we charge a fixed price amount for this. uh is essentially the blueprint for what you need to build, but it also extremely logically explains the business use case for the project in detail. — And how do you minimize I mean anyone who runs an agency will probably know um the amount of like proposals that never got a word back kind of thing that you get, right? So, how are you putting that as a as like a paid expiration? It's like, hey, okay, for us to scope this out, it's going to be 1,500 or like 2 grand for us to do this. um this is just going to give you a full plan for it or you I doubt you're going all the way through all of that and then just go like yeah no I'm all right cuz that's — yeah 100%. So we like I do the we do the discovery call for free. — Um from the discovery call we then say look we've got a we try and show them the value through a really nicely decorated funnel and PowerPoint display on this call. We're actually working towards giving them a clickable product like access into a demo of the tool because that's going to be super powerful. We're pretty close to getting that ready. Um, but what we'll do is yeah, we actually so we charge 3,000 USD for we build them a prototype as well. So it's the scoping document plus a prototype on lovable or a tool like that. — So that's like it's good because you get the financial investment. It's not a massive amount of money, but if you're dealing with small to medium businesses that have this pain point and are willing to work in this system, they will have — Yeah. — And financially qualifying them. — So important to get that financial qualification before you let them go too long. — Yeah. Exactly. It's not, you know, like we're not looking to make massive profits on that or anything, but we're not really losing money on that either. That's there then we can justify whether it's a 14 or a 28 day sprint and we do three times per week check-ins. I'm going to talk about why this particular approach is needed for business internal tools specifically. But then after we built on the tool, we work in sprints. We have a we have three pricing models that we work off post launch or post MVP. Um, and those extra sprints are like building AI agents and automations, feature upgrades, etc. And the way you justify these like the good thing about this tool is it's literally most of the selling process is what's your existing process? how long is it taking your staff to do it or how much are you paying for a software tool to currently do it? If we can do you this and it's and it costs this much amount, you're going to save this much amount and we can deliver it in two weeks. — We've got like two different vectors to attack on that where you've like I'll either save you the software cost and or I'll also save you the like inefficiency that are costing you a lot of time wasted for these different staff members. So — yeah, it's honestly like selling it is is really not that difficult. Um it's delivery that w was definitely harder and has slowed us down up until this point. — Are you just wanting to I mean the obvious solution is just to start doing it only for one type of company which is you kind of alluded to before. Um but then if you're doing content for your lead generation you are sort of stitched up there because you like in my case I get leads from all different angles. So, we've tried to niche down previously and then a gigantic lead comes in that we can't really say no to. And so, it's tricky unless you're going to be doing outbound running ads or doing um doing cold outreach and stuff. So, what's your strategy there? — Yeah. So, we've got an ads funnel. You're literally speaking about my exact problem cuz that is like one of the issues that we've had is like I get all these leads, they're great, they're great projects. I'm like, I would love to do that, but then I also want to I want to build a repeatable process that's going to allow this to scale. So, but yeah. Well, so targeted advertising and a and a proper VSSL with a funnel, a qualification funnel to that. That's like the other part of the puzzle to get this to work is how do we target a specific business like to the niche like landscapers, consulting companies, whatever the case is. We want to target get really good at them. Then, you know, landscapers are very similar to plumbers or whatever. Like, then you just hop to the next level. the three things to be wary of with building specifically internal systems for businesses because so we've done this a number of time before not in this offer just as a generic software agency as well and we learned a lot of lessons there which have helped us deliver this better but I think there's three things you need to be wary of jumping down this internal tool space for businesses one is businesses hate change the solution needs to be stable and simple so instead of going above and beyond trying to do all these complex things solve complex problems especially in this 14 28 is we're going for dead simple. We want monkeys to be able to use it. And so we're trying to make where we're actually working into a new uh UI system and framework, but we're trying to make this as simple as possible. No bells and whistles at all. So that's number one. Two, implementation needs a rip the band-aid off approach with a lot of these businesses, especially established businesses that have been operating for 20, 30 years. They've been doing the same thing year on year. If you come in and be like, "Hey, look, we got this whole system. We're going to basically throw a good 50 to 90% of what you used to run in the bin. Come use this. " There's a lot of push back and a lot of people get pissed off and you've got one or two strikes. Like if there's issues with the software and it interrupts operations just one or two times, — they basically just going to be pissed off and just be like, "No, we're not doing it. Throw it in the bin. " — So — that's a big one. Imagine having you're not available for like maybe 24 hours or 12 hours or something might be over a weekend something breaks and like everyone is just screaming about what the [ __ ] is this new stuff we've got. So that's a big risk to take on I guess. — Yeah 100%. So um that also ties in I haven't got this in here but that's that is also why we stay away from certain sectors. So finance, we stay away from healthcare. There's certain sectors where too much red tape, too much hassle. — Yeah. — Rather wouldn't deal with that. People always ask me, "Oh, how do I deal with this compliance or this industry or what's the, you know, how do I deal with these risks? " There's so many opportunities out there that there's low hanging fruit everywhere. You're going like, if you're scared about it and if you're starting out, I wouldn't recommend going for these nalia just like — 100%. So, yeah, the rip the band-aid off is like, so the other thing is these businesses, as I said before, hate change. So often you have to have something stable, something that works, but also the reason why we check in with them three times per week and we try and do this in 14 to 28 days is two reason. One, we obviously make more money in a quicker period of time. So that's a win for us, but also if you don't get it done in that time frame, businesses, it tends to get put on the back burner. Like you're typically dealing with people that are high up at these businesses. They've got 20 other things that they're worrying about. And then this, if it screws up one or two times, they've got a million other things on their plate. it goes on the back burner and then it starts to drag out for months. So, we really want to get it right. We stable. simple and then we want to rip the band-aid off and be like, "Hey, look, let's plan to get your entire team on board on this next week. We know there's going to be a couple of hiccups. We're going to be on deck to worry about this, you know, 2our turnout time, whatever the case is. Um, let's get on board this cuz we know it's going to be uncomfortable for a week or two, but it has to happen. " So, that's that. And then scoping is critical as well. So like with building any software and that that's another spot where this BMAD framework is really going to help you out but you need to clearly scope out the project clearly explain what's going to be happening and that's why half the reason why we work the prototype's amazing so good news is on lovable on these tools you can basically design in large part the majority of what how this is these apps are going to work look feel in conjunction with a bunch of good documentation it's a pretty rock solid scope but yeah you need to make sure that scope is critical One thing I guess

after you get over that hump of all the like the initial scoping, the planning out using that BMAD method, building it and then pulling the band-aid off and getting it plugged in is the stickiness and kind of the lifetime value of one of those clients. I've been sort of half not about this about what we're doing at Morningside, but when you do have these big clients that can even just a smaller business client and they're going to work with you for you are their go-to AI partner now. Um you have so much context in their business, you've built the system that their business runs on. As long as you're able to deliver well and you're not going to sort of give them some crappy system sometimes or give them reasons to break off that relationship with you and go elsewhere, then you have their business for basically the next 5 years if you wanted it, you know, um with all the new updates that come out and adding on new AI agents and systems on top of it. — Yeah, 100%. And I think the thing with when you whenever you're selling a quality product that you genuinely believe in is like a lot of these business owners, they're all talking to other people in the space. Listen, if you've built a genuine quality product, I mean, what we're building here is pretty revolutionary. No one's even really doing anything close to this at the moment and getting it to work properly. But I think yeah, as you said, if you can get it to work nice and stably, these business owners will look at the other businesses in their space, see how inefficient certain things are there and in general at if you're doing a proper if you're selling a quality product, you're doing a proper job, you know, people are willing to pay high ticket and generally pretty happy with your service and will stay on

with you. And so if we're talking to the beginner now, maybe the agency owner who's been selling automations or agents here and there and they're looking to shift. Okay, maybe this is the offer I want to dial in on for maybe 2026. What would you give them as like the quick start plan? — You don't need to build an internal system. Like there's a lot of businesses that just want one little system like one nice B like leads board where all their sales agents can go in and view the leads and do cool things there. So it's really if you're already in the NNN like the AI automation space, all we're really doing here is like you lovable is a perfect entry spot. I would say start with lovable cuz you can do like you can do most of this in lovable but this BMAD method and claude code is like it's level two. Lovable is level one. Level two is to go through once you're done with lovable. There's certain hiccups there. Level two is to understand this BMAD method. Start building things with clawed code and this BMAD method and that's going to unlock like the next level of complexity which is going to allow you to do this. So my tips would be yeah learn those two things. Find someone that is an expert in this nextjs super stack who can c you can do 90% of this yourself. Find someone that actually understands the tech. If you're nontechnical or you don't you know you don't code hire someone on Upwork. Find someone to just QA that tech at the end. Make sure that there's no security risks. all those kind of things. And then yeah, that that's that would be it. Step one, learn lovable. Step two, learn Claude code and BMAD. Step three, build your own product practice. Build a templated approach to solving a particular problem for a niche. Step four, build a demo for that so that people can go through it and see the value. Step five, build a lead funnel. Step six, pump money into the leads. — Adam, that's freaking awesome, man. Thank you so much for coming on and sharing. I've been looking forward to this uh for a few days now. So I think you guys have all got some really good stuff to sink your teeth into there now. Uh this is definitely where things are going. Um you've even got guys like Chimath probably up to 8090 what he's doing over there is similar but going for enterprise and they've signed 40 million in contracts for this year. I think they're going to do 40 million in revenue this year uh in their first year doing the same kind of stuff but for the enterprise which is custom software replacing all of their clunky tech stack with something exactly like this. So, it's very interesting to see this happening at the top and at the bottom from where you're coming from, Adam, and going to small businesses. So, this is our entry point for anyone who's looking to maybe pivot their AI automation agency into something like this or clear offer. I think this is a really really good horse to bet on for the coming years. So, Adam, I really appreciate you coming on sharing the source. You guys know how to contact him. I'll leave his uh links in the description. Um yeah, mate, it's been a pleasure and looking forward to hearing about where you go with this in the future. — Cool. Appreciate it, mate. Yeah, all my links are down here if you want to connect with me. appreciate the opportunity as always, Liam. A lot of this is obviously inspired by the continual good work that you guys are pumping out um on this channel. So, yeah, appreciate it big time, mate. So, I hope you can see why I'm so excited for this particular opportunity. If you are running an AI business or want to start one, this is an extremely interesting place to look into, especially looking forward to 2026 as AI coding tools make it even easier for beginners to come in and make these kinds of custom softwares for businesses and that really unique advantage of centralizing everything so that the AI systems that you build for your clients have access to all of that data within one software. And I think this is really where those rails become important for them to get the edge on the competitors long term. If you're someone who wants to get the jump on this early and learn how to build these kinds of softwares, you can follow my full guide, full course, like two hours long, breaking down how as a beginner you can start to build these kind of applications using vibe coding tools like Bolt. But aside from that, guys, that's all for the video. Thank you so much for watching and I will see you in the next