277: Why You Shouldn't Use AI to Build Your Product

Every founder is looking for ways to save time and money.

And right now, AI promises both.

But here’s the catch: while AI can write code, it can’t think through your product’s logic, security, or scalability. The result? A shiny prototype that collapses under real-world use.

In this episode of Tech for Non-Techies, Sophia Matveeva interviews Natalie Kaminski, CEO of JetRockets, with a knack for bridging the gap between non-tech founders and the digital world. With experience spanning multiple countries and roles she brings a hands-on approach to turning ideas into real, successful products.

At JetRockets, she leads a global team focused on building high-quality Ruby on Rails platforms that align perfectly with business goals.

Sophia and Natalie unpack the limits of AI in product development, why “AI-native” platforms often fail at the fundamentals, and what happens when shortcuts lead to security nightmares.

In this episode, you will hear:

• When to use AI for fast prototyping and when to bring in engineers
• The “toilet in the living room” test for spotting bad product architecture
• Why great developers are more valuable than ever in the AI era
• The red flags that signal a product quote is too cheap to trust

Free AI Mini-Workshop for Non-Technical Founders

Learn how to go from idea to a tested product using AI — in under 30 minutes.

Get free access here: techfornontechies.co/aiclass

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TRANSCRIPT 

Natalie Kaminski  00:00

I've seen a case where a law firm actually, like a small a small legal firm, they decided to build a new onboarding flow for their clients, and they spent like three days, it was told over a weekend, you know, and vibe coded an onboarding application for their clients where they would allow their clients to upload sensitive information. The idea was to, yeah, the idea

Sophia Matveeva  00:24

where this is going, Oh, my God. The idea

Natalie Kaminski  00:28

was to, you know, make the onboarding process a little bit more efficient. And so they built something out that was full of holes, security holes, particularly all of the client data was widely exposed.

Sophia Matveeva  00:47

Hello and welcome to the tech front and techie podcast. I'm your host. Sophia Matvei, if you're a non technical founder, building a tech product or adding AI to your business, you're in the right place. Each week, you'll get practical strategies, step by step, playbooks and real world case studies to help you launch and scale a tech business without learning to code. And this is not another startup show full of jargon venture capital theater or tech row bravado. Here, we focus on building useful products that make money without height and without code. I've written for the Harvard Business Review and lectured at Oxford, London Business School and Chicago Booth, so you are in safe hands. I've also helped hundreds of founders go from concept to scalable product, and now it's your turn. So let's dive in. Hello, smart people. How are you today? I'm recording this for you from Abu Dhabi in the United Arab Emirates, and it is a lovely place to be in late October. I highly recommend it. And in today's lesson, we are going to discuss whether, in the age of AI, non technical founders still need developers. And today's guest says, Absolutely you do. You're about to hear from Natalie Kaminsky, the CEO of jet rockets. For 16 years, her team has built products for non technical founders and for business leaders. So she has seen AI hype. She has seen the wins from AI and she has also seen the very expensive mistakes which you're about to hear about. And in this conversation, Natalie explains why AI can generate code but can't create a product that scales. You'll also hear her brilliant toilet in the living room analogy for what architecturally wrong looks like. We get into where AI is fantastic, why serious products still need professional engineering and how to spot those too good to be true quotes before they burn your budget. So if you have a tech idea but no tech skills, this episode shows you exactly when to use AI and when to bring in the pros so you don't end up shipping something that's fragile, insecure or impossible to scale. So let's learn from Natalie. In this age of AI, do non technical founders still need developers

Natalie Kaminski  03:09

absolutely 100% and I would even argue that now, even more so than ever, there's a lot of talk going on about how, you know, engineers are becoming obsolete because of all these amazing AI technologies. But anyone who actually has ever used this technology, so who knows how these tools work underneath, can quickly realize that developers are needed more than ever, and here's why, AI does not equal understanding. Basically, AI can generate code just like it can generate an article for LinkedIn, or, you know, any other media, if you give it some information and you prompt it properly. However, it does not mean that AI, the tool that you're using, is actually going to understand what is it that you're building. So on the one hand, yes, you could probably prompt AI to build you a decently looking login page. It's not going to go on its own unless you tell it to, to make sure that it's secure, for instance, or to make sure to request certain you know password parameters, or to make sure to know what to do with that login once you log in. And again, I'm using just very basic examples of features that you know any platform has, but you can extrapolate and imagine that if you're building a somewhat complex platform that has some sort of logic about it, then you can't simply rely on AI, because at the end of the day, building a platform is more so about the context, Understanding consequences, edge cases, logic, than than simply producing code. So AI is excellent at producing code. Some of that code can even be synthetically correct, but most of the time it would be architecturally wrong. And so you need to have an engineer, someone who actually understands the code and how platforms are being built. World in order to, you know, oversee, correct, control, maintain and guide the AI tool

Sophia Matveeva  05:07

that you're using. So without any tech jargon, do you think you'll be able to explain to our listeners what does it mean to be architecturally wrong? Or, even better, could you give us an example of when maybe somebody came to you who is a non technical founder, who built something with AI and it was architecturally wrong. So we can tell what architecturally wrong means, you know, in terms of, you know, users or maybe wasted budgets,

Natalie Kaminski  05:36

absolutely, I can even take it, you know, further away from tech jargon, and use an analogy of building a house if you feel that would be useful, right? So imagine you're building a house, and you want a house to have electricity, and maybe even, you know plumbing, and you know, have a toilet on your first floor. And imagine that you're building that house, or some builders, let's say robots, right? The future, builders of houses are building the house for you, and you're coming to see the house, and you're seeing electricity. You're seeing plumbing, but your toilet is placed in the middle of your

Sophia Matveeva  06:13

living room, okay, yeah, architectural issue, right?

Natalie Kaminski  06:18

So on the surface, you've got electricity, you've got plumbing, but your toilet is in the middle of your living room. Is that going to be an acceptable solution? You know? Is that an acceptable build of your house? Probably not. So. Again, it's probably a little bit over simplifying. But when it comes to web technology, it could be anything, anything from not accounting for future growth of the system, because when you build a system, you know you can build it in such a way that it solves the immediate goal. But it's not that it will not allow you to expand the functionality in a easy, simple, maintainable manner, right? So for example, if, let's say you're starting out building a platform for, let's say dating. Keep it simple. It's a dating app, and one of the features is for user to be able to upload their photo. And you can build it in such a way that the system will allow you to upload a single photo versus multiple photos, and now we're getting a little bit into sort of database relationship and how things underneath work. So if you're going to build your platform to allow to upload a single photo for user profile, it would be very inconvenient and unnecessary, difficult to expand the platform in the future to allow for multiple photos, as opposed to building that future scalability into the platform from the get go and

Sophia Matveeva  07:49

so what? So? How long has jet rockets been around now? You guys have been around for quite a while, right? 16 years. Yeah, okay, wow, 16 years so, and you're working with a lot of non technical founders and business leaders, so you know, really people who are probably listening to our show. And so I'm wondering, What changes have you seen in what people are coming to you with since the AI boom? Because I'm wondering, are people coming to you saying, oh, you know, we've created this thing with AI, and now we need you to help us scale. Or are they saying we built this thing with AI, but we don't really understand what it is like. How has the age of AI changed demand for your services? I'd say

Natalie Kaminski  08:37

all of the above, right? So I'm seeing positive changes, as well as some sort of, you know, regression, so to speak, in my in my found or in my target audience. So on the positive side is because of the tools that are now available, you know, and I'm particularly referring to stuff like lovable for instance, founders have a very affordable, easy to use way to ideate and build proof of concept, you know, something that in the past, sometimes they would have to even come to me very early on in the process and be like, Hey, can you build us a proof of concept? And, you know, inevitably, they would have to spend significant amounts of money on a product that may or may not see the, you know, light of day. Now, with the advancements in these particular technologies, that they don't need to come to me, as a matter of fact, when they do, I advise them against it. I say, Listen, you're at the stage that you should go and use lovable build your own prototype. It doesn't have to be pretty, doesn't have to, you know, be fully functional, but it gives you enough of a functionality to be able to play around with your vision. Because, you know, picture is worth 1000 1000 words, right? You may think you want something, but in reality, when you put it together, you realize that, no, this is not quite what I'm looking for, etc. So it gives you a quick, easy. Easy, relatively cheap, just sometimes even free, way of ideating and really honing in on what is that you're building. So on the positive note, when these people come to me, they typically now come to me at a stage where they have proven their idea they found the product market fit, even if sort of the beginning stages of that, and we haven't wasted their budgets on that process. Now we can invest we can take their money and spend it on actually building out a scalable, proper solution that will allow them to conquer, you know, their user base, on the flip of that is many people who fall victim to a lot of these falsehoods. You can read on LinkedIn or, you know, other media. Hey, you no longer need to need engineers. You can whip something out in two days. I guess the new term now is building AI native platforms. Well, that's just, just just just another hype word, in my opinion, right? And so they say, Yeah, I don't need engineers. I can just go and vibe, code something on my own. And the most dangerous are the types who have a little bit of technical skill, you know, just enough to fool themselves into thinking that they now can be, you know, full sort of engineer using these technologies. And what happens is, I've seen a case where a law firm actually, like a small a small legal firm, they decided to build a new onboarding flow for their clients, and they spent three days it was sold over a weekend, you know, and vibe coded an onboarding application for their clients where they would allow their clients to upload sensitive information. The idea was to, yeah, the idea

Sophia Matveeva  11:47

where this is going. The idea

Natalie Kaminski  11:51

was to, you know, make the onboarding process a little bit more efficient. And so they built something out that was full of holes, security holes, particularly, all of the client data was widely exposed anyone who wanted to and luckily, they they kind of stopped themselves before going too far. But they did. They were on the verge of releasing it to their client base. And most people, you know, they get the link from a reputable firm, they tend to just say, Okay, I'm going to follow the link, upload my documents, etc. They kind of assume that the firm takes their job responsibly and is not going to send them anything that's not well secured. Well, unfortunately, that's not the case. So I see those cases as well. Yeah, gosh,

Sophia Matveeva  12:37

that's absolutely terrifying, and it's also making me think that as a customer for something serious. Am I now going to start saying, hang on a second. How was this product made? Was this made by Vibe coding, or was this made by actual professionals? Because, you know, if it's like a recipe app, I don't care if it's vibe coding, but if it's something where, you know, I'm going to exchange money or I'm going to exchange sensitive data, then no, I want the pros to be looking at it. You actually the number one person you described. So the version one is the ideal tech for non techie student, because essentially, our business and what we teach has changed as a result of AI. And when it first came I was thinking, I wonder, I wonder, how we can use this. I can see applications. I'm kind of skeptical about this whole you don't need developers, but I'm not a developer myself. So let me speak to developers and see what's happening in the market. And essentially the conclusion that we came to is exactly what you're saying, is that we help people either with ideas for a whole new thing, or ideas for, you know, a new direction, like a new set of features to use AI to create a test version. We teach them how to test it with their target market based on that, to see, okay, what do we need to iterate? I will ready to go forward and actually invest more time and money in it, or do we need more experimentation and so and then we always say, Okay, now you've got this. You now need to know how to work with the professionals. You need to work with the professionals. And you need to, you know, know how to get the best ROI on your investment of working with developers, professional designers and so on. And so the first person that you described is literally like, if, if that's what they do, and they've gone through our program, they've passed with flying colors. And what I'm actually seeing is that there are some students who went exactly through this journey less than a year ago. And you know, I caught up with one of our alumni who went through our program, literally last November, so literally a year ago, and her brother. Her product is now live. She's making money. She's hiring people, and it's because she didn't waste a huge amount of time. No, I don't want to say waste. She didn't have to spend a huge. Amount of time before she validated her vision, and so by the time she came to speak to the professionals, her stuff was really validated. It was just more like make this we know exactly who we're going to send it to. We know what they're going to pay. And also for ROI, for her, it was much easier to pay developers because she knew she was going to get the money back from her customers very, very quickly. But I'm wondering, there is so much AI hype, and you know, there's Natalie and you and me, we are, frankly, small business owners, and we're taking on messaging that's coming out of really, really well funded Silicon Valley companies with, you know, Sam ultimate saying that, okay, soon you're going to have companies that only have one person, because AI is going to do everything. The thing is, people are falling for this. And what I am wondering is, essentially, how do we tell people to be skeptical, but also hopeful and experiment, because I don't want people to think that, okay, this is a scary thing. I never want to use AI, or I'm only going to use it for design because Sophia Natalie told me so. But you know, maybe in three months time, there will be some other application, and they're listening to this later. So how do we encourage people to stay in the zone between experimental but also not completely falling for everything that like Sam Altman and Elon Musk say,

Natalie Kaminski  16:33

Well, I mean, here's my and you know my view? I'm a, what I like to say I'm a healthy skeptic, right? So I definitely embrace AI, and I use AI on a daily basis in my personal life as well as my professional life. And maybe because I use it so much, I can see the you know, sort of faults with it, right? I can see that it's not all knowing, all capable new technology, right? I think it's important to stay up to date about the news, but also, but also, kind of not forget about what was said a year ago, right? Or what was said like six months ago, if I recall correctly, and forgive me if I'm paraphrasing, but I believe it was the CEO of complexity that maybe six months ago. So he said that, oh, we will not need engineers in six months.

Sophia Matveeva  17:27

I'm hearing things like this. And what's so interesting is that the senior engineers I know, like the really senior, like really well paid people, even if they're not working in AI, they're not even remotely worried,

Sophia Matveeva  17:42

not even remotely worried about, you know, their massive salaries being less massive,

Natalie Kaminski  17:48

but, but the thing is, so my point was, is that, you know, these grandiose, big statements are being made to create publicity, and that's okay, that's always been the case, right? Like big companies have to create hype, because that's the only way for them. Well, not the only way, but one of the ways for them to increase their valuations. And that's how our, you know, capitalistic system works, and that's, that's okay. It is what it is like. We all know it. I mean, I mean, think back about the no code revolution, right? When bubble and such first came to market, everyone said, Oh, that said we're going to replace developers where what happened in reality? In reality, demand for software skyrocketed. Developers became even more valuable, complexity increase and so on and so forth, right? I mean, and

Sophia Matveeva  18:35

we have bubble developers, because bubble is actually really hard to master if you're a non technical person. And we've taught glasses on bubble, and we've actually stopped doing that because, you know, we say, okay, we can give you the basic architecture, but to be honest, it will like the best. The people who I know, who build really useful things with bubble have some sort of technical expertise, whereas if you take a lawyer, like from your earlier example, and you give them bubble, I mean, they will build something, it's not gonna be great. I mean,

Natalie Kaminski  19:09

I'll give you another example. You know, forget technology. I mean people, you know, law firms, right? Like, I sometimes use chat GPT for legal advice, right?

Sophia Matveeva  19:18

Me too, absolutely. But

Natalie Kaminski  19:21

I also know where the boundary is right, like I know that certain things, you know, maybe I'll ask chat GPT to review a contract that been I've been sent because I don't, you know, want to pay $400 an hour for that and kind of identify red flags for me. And then if there are red flags at that point I may decide to go to professional right? It's sort of like, I use it as a first sort of line of defense, so to speak, at the same time, at the same time, you know, a lot of our agreements, or a lot of business dealings, they very strictly prohibit people from Share. In the details or the information about the deal with the wider audience, you could argue that uploading this document into chat GPT could on its own, you know, violation of the contract. So my point is that a lot of people, I don't think people who are good at what they do, people who know their profession very well. Can be easily replaced by technology, right? So my advice to your point. My advice is to people who kind of like, oh, what's happening? How do I follow be the best you can be in your particular field. Know your field well. Keep an eye with the new technology you know, stay impressed about what's happening. How to like, figure out the way to effectively integrate technology into your daily life, but without jeopardizing your own skill set.

Sophia Matveeva  20:56

Right? Don't give up your own judgment Exactly. What about your costs? Because obviously you have developers working for you, and are some of them using AI, and as a result, how has their work changed and have your costs gone down? Have they become more productive? I'd love to understand what's happening, you know, for the engineering side. Yes.

Natalie Kaminski  21:25

So this is a huge misconception, I think, right now in the industry, that says that, oh, if a developer has mastered how to use AI, they should be paid less well. I would argue on the contrary. And I would say that if a developer has mastered to use a new tool to become more productive and more efficient, they should be paid more because you get the same stuff done at a faster rate, supposedly, right. So why would it cost less? Right? I mean, imagine if you hire and going back to the analogy of building a house, if you're hiring somebody to lay your bricks manually, versus maybe, you know, there is a combination of some machinery and manual labor, right? You want the machinery to be used, and you and people who know how to use machinery are probably more valuable in the market. You know, in the workplace, the same goes for engineers, right? And so where we can see. So first of all, yes, we absolutely embrace AI and we absolutely use it in our work day, right? My engineers, and by the way, at Jet dragons, my engineers, can decide which tools they prefer to use, because every tools are slightly different, and people have different opinions depending upon their skill level, as well as their you know, preferences, like some people just just basic, like human, you know, personal preferences, but where we see AI being amazing assistant is with scaffolding, testing, refactoring, naming, like, stuff that engineers don't want to do, as it

Sophia Matveeva  22:57

is, like, like, kind of like the admin of engineering, like every job, has its own documentation and admin.

Natalie Kaminski  23:08

Tedious take a lot of men, quote, unquote, manual labor, and just like you know, where engineers were forced to do it by hand because there were no such tools, now they can automate these processes. And then that is excellent. That saves, you know, a good engineer, like a high a well skilled engineer, jet rockets, if they embrace AI and they integrate the AI in the daily operation, they can be 30, sometimes even 40% more effective. That's awesome, right?

Sophia Matveeva  23:37

That's a huge time saving and a huge productivity saving, which means that, you know, they can work on more projects and take some time off,

Natalie Kaminski  23:46

absolutely right? They can work on more projects. But also, should the clients pay less? The clients don't pay us. You know, when you hire a professional, you don't hire them for time. You hire them for value. Yeah, you high, or at least, that's how, yeah, so if I can deliver value faster, I could even argue that I should be charging more.

Sophia Matveeva  24:08

Well, it's like, I think the example that everybody can relate to is, if you're good, if you were to go to a dentist and you you had to have a root canal, you know, God help you if that's the case. And one person said, Okay, I'll do it in half an hour, and the other person said, I'll do it in five hours. I mean, I would, and the half an hour, I would just be like, just take, take my money, and the shorter, the better.

Natalie Kaminski  24:38

So, absolutely, absolutely, yeah. What

Sophia Matveeva  24:42

are you finding in terms of kind of client expectations? Are they are people now expecting the impossible because of AI? Are they now saying, Okay, well, you know, if I'm going to hire developers in the first place, I. Expect that, you know, I'm going to pay you, I don't know, $20,000 and essentially, I'm going to have, like, the equivalent of Facebook tomorrow.

Natalie Kaminski  25:08

Yes, yes, I see that. And you know, I always say that not every client is a good client for us, and that's okay. I'm not trying to win every piece of business. And I did have several leads that came to me with, you know, expectations that were completely unreasonable. You know, I had a person present to me, a 35 page PRD product requirement document that included a lot of complexity. The product had to do with financial services, like basically, a lot of complexity, a lot of processing, a lot of data calculations, manipulations and whatnot. And when I kind of gave them a ballpark estimate, which was pretty reasonable and based on my experience, and you know, everything we've built in 16 years, the response was, Oh, my God, this is way too much. I was told that this can be done in like two weeks for like $10,000 and I my only response, response to them was, that's awesome. Go with that firm if that's how you're inclined to do. You know I'm not gonna see. My position is that I'm not going to are like, when we're so far away from each other, right? There is no point in having that argument if a person thinks, what I find extremely puzzling is when a person comes with an idea and they say, I'm going to make 10s of millions of dollars, but I'm only willing to spend few 1000 on it. I'm like, that's that's not how the world works. You cannot expect to spend a few $1,000 and as a result, have yourself a business that's going to make you millions and millions and millions. It's just simply impossible. If it were possible, I guess we'd all be millionaires right by now, but, but it's not possible to make money. You have to spend money, be that on development, on marketing and user acquisition and other you know things. You have to spend money and and until you realize it as as a founder, you will not be able

Sophia Matveeva  27:16

to succeed. And you know, also, I think what you're saying that, you know that $10,000 example versus whatever you're saying, let's say six figures. I don't know 100,000 I think it's useful for founders and for business leaders to just keep that in mind, that when you're going around and you're getting cost, that's a good thing to do that. So take the normal thing to do. You should survey the market and understand what's going on. But if you have somebody who's such an outlier with a really low price, and you're thinking, oh my god, this is amazing. It's just that thing of, if it's too good to be true, it probably is. And I'm not saying I haven't fallen for it myself. I mean, for long time, listeners with the podcast, you'll know that when I first got into tech entrepreneurship, we tried to create our first version of an app using a tool called reaction native. And that tool was basically too early, too young, and it didn't work. I won't go into the whole thing now, but essentially, we tried to, kind of, we tried to cheat the system, basically by using this cool new tool, which promised us releasing on Apple and on Android simultaneously. And what ended up happening is that we spent 2000 $10,000 and, you know, a couple of months, creating something that was completely unusable, having to scrap it and then go to the expensive version anyway. Just, you know, 2002 months later, and 10,000 $10,000 later. And you know, when I look back at that, I think, well, I was a baby founder. I didn't know what I was doing. And given the information, and also tech want to take us, didn't exist. Nobody. Exist. Nobody was telling me not to do it, and so given the information I had at the time, that decision made sense. But if you are listening to this show, you don't have the excuse to do this sort of thing. You have to see that okay, if there's one really cheap outlier that's promising to solve it all over the AI and then other firms who have built products that are actually being used. Maybe those firms have been around for a while. They're saying something wildly different than okay, you have to, you have to be really skeptical. So my last question as we wrap up, what would be your advice, Natalie, to a business owner who has an idea for how to add tech to their business, or, you know, your typical non technical founder who has an idea for an app, for example. So when they are thinking, Okay, I've got this idea. I know. I I've. Learnt that I need to use AI for testing. I know that then I need to go to developers. You know, that person is also going to have a lot of pressure on them saying, Oh, you shouldn't, you know, your cost should be much lower, like you should use AI for everything. Where are you integrating AI in your product? To that person who is inevitably in this market going to have that pressure. What would you say to them? What was your advice?

Natalie Kaminski  30:25

Well, first, I suggest that they found a reliable partner who is, on the one hand, definitely you know up to date about latest technologies, right? So yes, embraces AI, uses AI as a tool, and knows where to apply AI, but having that partner in their corner to be able to together, you know, especially as a non tech founder, you have to have someone who would act as your quote, unquote, fractional CTO, right? And you do not need to hire that fractional CTO as a standalone person, right? You could find a partner, a development partner, who is going to build your product, but also advise you on a strategic level. And you know, help them explain to you and explain to your potential investors, advisors, partners, users, whatever, how does what role does AI play in your product, and what role should it play in your product? I recently had an example where my, one of my long standing clients, was, you know, approached by such an advisor and was told, and she was told that, oh, your product, which, by the way, has been on the market for five years, super successful, making money, everything is great for the product. But this quote, unquote, self proclaimed advisor, said that unless she converted her app to be an AI native app, that's again, same term being used, then a couple of college students will replicate her business over a weekend. And I mean, people have to be held responsible for statements like this, because it's irresponsible, it's it's immature, it's irresponsible. It has nothing to do with reality businesses.

Sophia Matveeva  32:07

Yeah, business is not like that. I mean, even let's say the product could be replicated like I mean, it can't be let, but let's imagine, at least would. Let's just take that variable out of the equation. That's not the only thing that makes the business successful.

Natalie Kaminski  32:22

I mean, anyone can go and vibe code an app nowadays, right? But it doesn't mean that everyone will have wild success in the marketplace. So I think I'm gonna wrap this up with one advice, focus on the business, focus on the product that you're building, which means focus on the solution that you're providing to your users, why you doing what you're doing, and how you can do it best, and partner with a reliable partner who will take care of your tech for you, because you're not tech founder, and who will be able to have honest and open conversations about, you Know, where and why to use. Ai, yeah, awesome.

Sophia Matveeva  33:02

That is a really, really useful note to end on. So thank you very much. Natalie, it's been a pleasure having you back on the tech from the techies podcast.

Natalie Kaminski  33:10

Thank you, Sophia.

Sophia Matveeva  33:16

Wasn't that interesting? My two insights from this conversation are, number one, use AI to prototype and to test quickly. And number two, bring in engineers to design for security scale and the future that you actually want. And if this sparked an idea and you want to bring your product to life using AI So to test your product and have something visual that you can show people using AI. Then what you need, here's my free class, how to make a first product using AI. You will learn how to turn your idea into something you can actually show and test with real users so you can get feedback and then work with developers. The smart way go to tech for non techies.co, forward slash AI class to get it on demand or tap the link in the Jenner. And on that note, have a wonderful day, and I shall be back in your delightful smart days next week. Ciao.