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IIIMPACT is a Product UX Design and Development Strategy Consulting Agency.
We emphasize strategic planning, intuitive UX design, and better collaboration between business, design to development. By integrating best practices with our clients, we not only speed up market entry but also enhance the overall quality of software products. We help our clients launch better products, faster.
We explore topics about product, strategy, design and development. Hear stories and learnings on how our experienced team has helped launch 100s of software products in almost every industry vertical.
When you start to look underneath the covers, it's not a sentient thing that's getting smarter and smarter. As you dive deeper into these different AI tools, which is the one that's gonna come out ahead? Is it what it's doing on the back end or how easy it is to use for people on the front
Brynley Evans:What is it that you want? What is it that AI can do? Until you understand exactly what it's capable of and how it could benefit you, how can you really be in a good position to say this tool is right for us?
Makoto Kern:Hey, everybody. Welcome back to another episode of Make an Impact podcast. I'm your host, Makoto Kern. I've got my cohost, Brinley Evans.
Brynley Evans:Hey, everyone. Good to be back.
Makoto Kern:Yes. This is gonna be a very, interesting podcast. But, before we jump into it, you know, we at Impact, we've been we've been in business for the last twenty years. We've launched hundreds of digital software products across every industry, and we've seen similar problems that that we always help try to fix with companies. They always try to jump straight into wireframes.
Makoto Kern:They are misaligned, and they don't know their users. So we've been helping companies really try to accelerate and make their software better. So before we jump into this podcast, I think, Brinley, we we wanna thank everybody for reaching a huge milestone with Impact. Hit 10,000 subscribers.
Brynley Evans:Thanks for watching.
Makoto Kern:Which is amazing. I think it's a testament to, like, all the posting we've been doing. We've been doing this for almost, like, a a year, I think, by now. So I think that's that's great. So just wanna recognize that all the viewers out there and all the subscribers, thanks for supporting us.
Makoto Kern:Yeah. Big thanks. Yes. I think let's just jump right into it. So today, we've been seeing some really, things that are are that could be worrisome, but are we in a AI bubble?
Makoto Kern:Is this similar to not com crash and boom?
Brynley Evans:Exactly. Yep. That's what's really, you know, could be scary. I would say we've been around the block a few times, but we've, we've lived through that .com crash and, you know, seen its direct impact on companies and businesses. And now seeing these parallels, I think it's something we had to explore and look at what was that for maybe those that weren't involved in the internet around late 90s.
Brynley Evans:What did that involve? And what are the parallels now with this potential AI bubble? And as a business owner or a product owner, what do you need to look out for? I think those are some of the things we wanted to cover today.
Makoto Kern:Yeah. From what I've seen in a lot of the comments in some of our recent podcasts about AI replacing your jobs and AI is gonna take this or that. There's been some new research that we've been seeing. But before I jump into even that, you know, we started Impact during that .com boom and bust. I remember everybody wanting to have a website that was a Craigslist slash MySpace slash whatever.
Makoto Kern:Give me a clone of this or that. And I remember just like the the hype around that. And now it's really understanding, are you going to be the AOL or the Netscape? Or are you gonna be the Google or the Apple that comes out ahead of all this? And this is probably what we're seeing right now.
Makoto Kern:If you added a .com to your name, all a sudden your valuation just jumps 25, 50%, whatever, just because you did that. Feels like similar here where if you add any type of dot a I or you add AI into your system, all of sudden, it's worth millions. And your salaries and all these expectations, it just seems very frothy right now because of that.
Brynley Evans:And it's it's the hype. I mean, if we dive into a bit of the history for those that kind of weren't aware of the the .com crash, you rewind back to the the late nineties, and, you know, the Internet was was crazy. It was new. It was exciting. It was seen as the next industrial revolution.
Brynley Evans:You know, Makoto, you you followed it closely in terms of investment and, you know, I think everyone was scrambling to invest in in an Internet company. That sort of assumption of, you know, even the investors as well, you know, most people, including the investors, didn't necessarily even have a clue about what the internet was or how it worked. And it was really just, they wanted to be a part of this. They knew it was exploding and there were going to be winners and losers. I don't think anyone saw that it was gonna burst and there were going to be losses that would be felt as much as that.
Brynley Evans:So there was this weird sort of irrational investor enthusiasm that was very much built on the hype and the momentum of that. I think sort of companies going public with no revenue or business models, but just the promise riding on the promise of the Internet alone. And I think it was it was February. Right? We got it.
Brynley Evans:I think it
Makoto Kern:really Yeah, basically jumped from 1,000 to 5,000, the NASDAQ, within like 1995 to 2000 or like 1998 to 2000 is how long it lasted. Then it dropped off a cliff. Like, it fell over 75%, the Nasdaq, and it was a bear mark for the next two years.
Brynley Evans:And there was billions of dollars just disappeared, just evaporated in that crash, which is, pretty scary, especially that many, you know, businesses are pretty good.
Makoto Kern:They're heavily invested into it.
Brynley Evans:Exactly. And whether it's, again, I think you're mentioning, you either came, like with the AI, you come out of it stronger or you fail altogether, but it's not just that it's the impact on businesses that may not even be fully integrated in tech. Like we saw in that.com crash, you had things like fashion retailers or just retailers in general using storefronts like the Yahoo storefront that fell flat or the boo.com company, which so many retailers integrated into their platforms and spent a lot of money on technology and that all fell flat as well. What we did see coming out of it was sort of rising from the ashes with these big companies like Amazon and Google, because they sort of paired that long term vision with real value and execution. They understood the value that the internet could offer, not in 2000 necessarily, but, you know, as we moved into 02/2010, 02/2020, and the growth of this new sort of frontier, I guess.
Makoto Kern:That's a great point because it's almost while there are similarities with the with the bubble side of things, there's similarities with the the creation of the user experience moat where, yeah, you can have a browser, but the browser experience became that's the one that separated. Who had a better browser experience? AOL or or Google? Who had a better, you know, product? Blackberry or Apple?
Makoto Kern:I mean, these are things that are showing that your user experience is your moat. And we'll get into that, I think, little bit later in this podcast. But I think right now, let's, there's some really interesting points that we are seeing as far as the bubble from the AI washing to the AI absolutely like getting faked to some of the things that we've been seeing as well when there's some recent research papers that have been released about Claude and some of the things that are happening at the back end. There's whistleblowers coming out about OpenAI, about how they're just you know, there's basically stealing creators' copyright and material and then using that to train its own AI. I mean, there's a lot of things that could cause us to be in this bubble.
Brynley Evans:So maybe we quick fire and we go through Yeah. All the reasons why we could be in an AI bubble. And then we're going to and flip So look at the first one I'll go with is we look at valuations and how they're just outpacing value. So there are so many AI startups at the moment, and a lot of them are securing massive amounts of funding despite again parallels lacking a clear business model or potentially meaningful revenue. They're riding this AI wave and people are hungry to invest.
Brynley Evans:So, you know, they're they're sort of pushing up the valuations. That's a big one of the big warning signs. You wanna go with the next one?
Makoto Kern:Yeah. I think yeah. So yeah. The next one. The hype cycle dominates.
Makoto Kern:Much like the .com boom, anything, anytime you add just AI into your system or you're adding it, all of a sudden you just your your value inflates without changing anything else fundamentally.
Brynley Evans:And that's so funny. I mean, how many times have we seen that just with the products we're working with? Well, we've got this new feature of something AI and I don't know, feels so overused. I think being in the industry and looking at all the tools and seeing a lot of what are just sort of white labeled services and rushed out services as well. Again, another one, just riding that hype cycle, just like the .com bubble.
Brynley Evans:And then the thing like we were chatting about it the other day, five coding, being able to have development tools now that you don't need a lot of experience to develop, but it allows you to deploy solutions, but not necessarily ones that are particularly good quality. So anyone has access to now output their own sort of product or their AI product, but it's really fostering a culture of rushed development practices. People don't have that sort of knowledge about the architecture. It's kind of that mentality of, well, if it works, ship it and we'll deal with it later. I think a lot of the things we saw in that sort of .com crash time as well of you know, these these new services or integrate this plugin or do this and, you know, it's not really tried and tested.
Makoto Kern:Yeah. Look. I mean, there's definitely aspects of being able to vibe code things, to do certain modularity of the code where it's, like, really easy to to produce and you just don't need to spend that time. There's force multipliers within the the coding space that AI can help with. Even design space, it's still far far even farther away, but it's ways in which you can just quickly conceptualize things from a design standpoint.
Makoto Kern:But if you get somebody who's inexperienced using a tool that accelerates their output and the output is horrible or bad or has the same problem, like, all the developers or designers, they all talk. And if they're, hey. Use this for this. And there's a problem with that. There's a hole.
Makoto Kern:That hole is now carried along the entire organization because there's nobody experienced enough to realize, hey. That's wrong. Don't do it that
Brynley Evans:way. Absolutely.
Makoto Kern:And so you're compounding the problem when you accelerate quality. So
Brynley Evans:And and you're missing out on that. I I think we look at any seasoned engineer and they've worked with so many different teams, worked with different tools, they've probably joined the industry in a time where you felt you were burned by those products that disappeared or you built up a way of approaching technology and implementing it that would catch these things. But now you've got people that don't have that experience. They're coming in, a lot of it's done for them and they're not necessarily spotting any of these major issues. There's a point with this that I wanted to make.
Brynley Evans:Everyone is very driven. It's always your time to value. Focus on your time to value. And if it's anything we learned from the sort of .com bubble bursting, it's like, no, it's time to real lasting value. That's the key.
Brynley Evans:You can get a product out, but you need to focus on real value. If there's not that there, it's not gonna last. It's not gonna survive.
Makoto Kern:Yeah. And I think that's the next point is a market saturation. You know, the barrier to entry is much lower now. You're gonna see so many copies of a specific, almost the same tools, chatbots, whatever. The differentiator is not the the back end at this point because everything looks in the same on the front end.
Makoto Kern:So you really have to understand, you're gonna create something, you're gonna have competitors coming out and looking exactly the same thing. So your market share and profits are gonna drop pretty dramatically.
Brynley Evans:Absolutely, and who do you partner with or invest in when there are all these different solutions that seem the same at a surface level, but often it's when you start using that tool, which we'll dive into in a bit, you really start seeing that difference. I think another one is again the parallel with the .com kind of crash is these investors that don't really understand AI either and it's just whether it's sort of venture capital pouring into these AI ventures or people just making investments in AI companies. It's again, based on the momentum rather than the fundamentals and looking for that real value. What are they delivering that is actually valuable and different to everyone else?
Makoto Kern:The technical debt is another one. And I think this is where it's building in a sense of where people are blindly using these these products. So, like, Claude, for example, what they released was where, you know, you've got a few things that are problematic. It's the it's the copyright violations. They're actually suppressing about quoting any type of source.
Makoto Kern:They're trying to cover something like that up, which is unethical as we know. But it's not thinking on its own. It's actually taking things from people who are creative and who are coming up with these things. There's also other things that they looked into where it's like a when they do a web search, it's thousands of lines of code. It's it's almost being held by digital duct tape.
Makoto Kern:It's alarming. And that's something where, you know, it's not Skynet. It's not really thinking about what it's doing. It's it's really all these if then statements. You know, that's something that when you start to look underneath the covers, it's not a sentient thing that's getting smarter and smarter.
Makoto Kern:Yes. It's getting more efficient. But I think that's something where as you dive deeper into these different AI tools, which is the one that's gonna come out ahead? Is it what it's doing on the back end or how easy it is to use for people on the front end?
Brynley Evans:Yeah, that's it. I think those are some of the main reasons we could sort of list about why we're in an AI bubble now. But if you're, again, a business owner or you are managing a product, you're in sort of software services at all, what do you need to be worried about? What are those things that you need to look out for? And I think the number one thing that comes to mind is wasted investment.
Brynley Evans:It's like you're risking spending your own money or your business' money on tools or vendors that may not even be around a year from now. If this bubble bursts, it could be a lot of infrastructure that you've invested in that, you know, is throwaway, and you you're starting again. So very important to to carefully look at that.
Makoto Kern:I'm curious. In video games, cheat codes let you skip months of grinding to unlock special abilities instantly. Have you ever wished for something similar for your software challenges? What if there's a way to instantly access twenty plus years of specialized expertise instead of developing it all internally? What if you could solve in weeks what might otherwise take months or years?
Makoto Kern:Would you agree that most organizations faced a steep learning curve when implementing new software solutions? At my company, Impact, we serve as that cheat code for companies looking to transform complex software into intuitive experiences that users love and that drive real business results. Would it be valuable to explore, and how might this work for your specific situation? Visit impact.i0 for a free strategy session focused on your unique challenges. I think also with the stability of platforms and the poor user experience, I think these two, again, if it's not easy to use, if there's problems with it, you know, we're seeing people where there are clients that are integrating into their products.
Makoto Kern:And then we track the actual metrics of what prompts and things are happening. And as we are looking at this, we see a massive drop off. They've may prompt it a couple of times and then they just go back to doing what they're doing. This is more around like enterprise software and this is a problem where people don't see like, hey, AI is just another feature and the way you use it within your software product or whatever, is that solving a user problem? Is it really helping them out or is it just faster for them to figure it out a different way versus trying to sit there and type and prompt it to try to get its answer.
Makoto Kern:It's poor experience and it's really not driving home what the business should be doing.
Brynley Evans:Exactly. And I mean, as well as sort of the poor user experience, think it's also Think about core business problems. There's so much hype that you may be thinking, right, we're not implementing AI, we're going to get left behind. Our competitors are already doing it. Oh, no, we just have to go.
Brynley Evans:That company was saying they got saying AI. Yeah, let's take it. Let's do that. I would really say you need to stop and take a good check about what is it that you want? What is it that AI can do?
Brynley Evans:Because until you understand exactly what it's capable of and how it could benefit you, how can you really be in a good position to say, This tool is right for us? It's something that you want to sit down and understand and then say, All right, again, where is that real value? How are we gonna realize value from the AI investment? And when you've aligned that way, you're gonna be in a really good position. But again, you need to think of things like don't go necessarily with proprietary options, go with open source.
Brynley Evans:How are you structuring internal knowledge in your company? What are the right tasks that people are doing in your company or that your team is doing? And how can those be taken on? How can they really be supplemented by AI? I think as long as you're addressing those things, it's good.
Brynley Evans:And not just going for AI for the sake of AI. That's, I think, a point for concern if you are just riding that hype wave.
Makoto Kern:So maybe we take a flip on that script and say reasons why we're maybe not in a bubble. Absolutely. I think there's different points here that we could bring up. And the first one is the infrastructure is there. Know, unlike the nineties, we have the cloud, we have these amazing GPUs, robust kind of data pipelines.
Makoto Kern:The only other thing that I think is the infrastructure might be a little bit weak at and they're trying to solve that is the energy, requirements. And that's taken a lot of energy. And I know there's talk about using going back to nuclear. There's such a scare around Chernobyl. Oh my god.
Makoto Kern:We're gonna have one of those. But it's actually really safe from what a lot of people have said, and that's actually can help power a lot of these these GPU facilities that take an absorbent amount of power to run.
Brynley Evans:Absolutely. There are quite a few, I think, why we may not be in an AI bubble. I think building on your point is really, you think of the different phases, like we were in a sort of starting phase when the internet came around, there weren't all those things that you're mentioning. And we still had to figure out so many processes as well. Think how our UX processes have been defined before UX was even a sort of buzzword, how they've refined and the tools have refined.
Brynley Evans:And everything from just running automated testing to deployment pipelines. There's so many things that we've perfected over the last twenty something years that didn't exist when the dot com crash happened. So, you know, thinking we've got all of those, we've also got the foundational tools like, your GPT-four models, or Gemini or Claude. You can physically test those and you could see the value that they can offer. So it's not like they would necessarily be something like the tools that we're mentioning where, oh, we've got this great flash based tool that's going to allow you to see a Garmin in three dimensions.
Brynley Evans:And no one's gonna have the infrastructure because a lot of people are still in dial up and this would be something that needs broadband. There's so many sort of technological limitations I've experienced for that .com crash. We're not identical now and some would almost say we're more in the sort of adolescence phase where a lot of these have, these processes have been refined, the technology has been refined. We're now just working through how we're integrating these new technologies that we're coming up with on the existing infrastructure.
Makoto Kern:We definitely use it within our workflows, just everyday lives and the productivity gains, you see that. Anything that has to take a lot of time, you're compressing a lot of data or information and you need to summarize it, You know, these kind of things are really, really helpful. I've seen huge improvements in efficiency and I go to one story and I know I told you about this before, but you know, my son, he was working with actually a Smithsonian, some kind of it's like a volunteer thing where you actually translate these 1,800 cursive documents. And we actually put it through AI just to test it out and see. And a lot of the AIs didn't work properly.
Makoto Kern:And, you know, one of them actually did, you know, you got from maybe 1% of it, maybe not really reading this cursive. But when we started training a different one, we were able to get about a 60 to 70% accuracy rate to read these like documents that were made in eighteen hundreds with this crazy cursor. And so it was pretty amazing to see that do that. And, you know, if you train the AI right, you could definitely see, I mean, we were able to translate documents so much faster versus trying to figure it out, trying to teach them how to you know, what cursive is and and all that. It was, pretty fascinating to see that that jump.
Makoto Kern:Mhmm. And, you know, again, we trained it in like seven different AIs and one of them only hit. All the big ones didn't work, so it was pretty amazing.
Brynley Evans:That is cool. So I guess the next thing is, again, coming back to, if you're thinking about implementing AI, what should you really be doing to select the products and understand what you touched on, Lakota, of the UX moat?
Makoto Kern:I think this is yeah. Going back to that UX moat, what is your moat? Is it the technology in the background? To be honest, no one cares what is happening in the background, what background are you using. It's the front end.
Makoto Kern:And the front end is really just like AOL to Netscape to to Google. What wins out back in the .com boom and bust are the ones that really focused in on UX. I think Apple was really the first like big company that focused on the user experience. Steve Job was just he was adamant about making that frictionless, easy to use. And he's the one that actually, I think, helped pushed our industry to really have companies focus on not feature focused, like, hey, if we build it, it'll come.
Makoto Kern:You know, company leaders are still going through with that kind of thinking where like, hey, just build AI, our customers will come. It's not the case. You have to have that user experience that's frictionless, enjoyable, and you have to do it consistently because people are going to be or competitors are gonna be on you. As soon as they see how you do something, immediately they're gonna start to copy you. So you have to continuously improve, continuously check those things as you're building product.
Brynley Evans:And I think understand what is market centric as well. As you said, like a big issue being sort of feature centric or even project centric focus, instead of saying, well, this is what the market needs at the moment, this is where it's going, and identifying that and aligning with that and then making that your UX moat. Can you create a new experience that is going to make your product stand out? Yeah. It's coming back to those things like focusing, we say it again and again, but focusing on that real value, not just the technical flair.
Brynley Evans:You want the tool that's easy to use, it's going to solve real problems that you've identified that the market needs and is going to beat a much more potentially sophisticated product that is clunky or confusing to use.
Makoto Kern:This jumps us into kind of like a good kind of summary between the two sides of the AI debate. And I think we've got strong signals that shows that we could be in an AI bubble.
Brynley Evans:But then
Makoto Kern:And we've got this Yeah. We don't other side that shows that we might not.
Brynley Evans:Yeah. So it's a tricky one. I mean, what are we looking at? For the AI bubble, we've got things like the valuations are inflated. We've got a lot of products we're seeing it rushed, and you've got market sentiment that's really driven more by that buzz than by business outcomes.
Brynley Evans:And then, I don't know, Makoto, on the other side, what what are we looking at?
Makoto Kern:You know, we're seeing foundational models that are super powerful.
Brynley Evans:Exactly. We've
Makoto Kern:got pretty much the infrastructure that can support them. When applied, you know, carefully, AI is transforming how business operate.
Brynley Evans:That's right. I mean, we've seen it ourselves. When we look at the AI projects we're involved with, there is a tangible benefit to it. And it's something that given you take the time, like I was saying earlier, to identify how it's going to benefit you, you can't go wrong. Those are the things that, coming back to things you can do is pilot things before you commit to them.
Brynley Evans:Ask those right questions about what the learning curve for a tool is. Is your team going to use it? Is it going to actually deliver that value? And avoid tools that are going to require a constant sort of handholding from the vendor, or if something needs ongoing explanation or support, it's not going to scale well internally. So I think we sort of look at those two sides and go like, okay, well, we could be, we couldn't be.
Brynley Evans:And we sort of go from there in terms of, you know, make the right decisions and you gotta come out stronger and separate that substance from the hype.
Makoto Kern:There's a bold prediction that we can make by 2027. I I think there'll be two types of technology companies. Those that use AI as a tool to enhance human capabilities or those that have tried to replace human capabilities with AI. You can kind of guess which one will still exist. And our listeners, what you should kind of think about is what is your competitive advantage?
Makoto Kern:If it can be replicated by AI, you really don't have a competitive advantage.
Brynley Evans:Absolutely. Also say, be careful where, again, where you invest everything. It may be more trying to set up, you know, strong foundations, in your company. Get your data in a good way to interact with AI. Get your knowledge in a good way.
Brynley Evans:Yeah. I think that's where it's really going to, it's going to be beneficial. Don't follow the crowd, jump into the first thing that you see.
Makoto Kern:Yeah, and I think if you're building products and you're trying to launch software and you've got competitors, you know, really look at your current your product strategy. You know, how much of it depends on having better technology versus having a better user understanding? Because, know, the technology side is getting commoditized, But, I say the user's love and enjoyment doesn't. So, you know, this is a kind of a good good way to end our segment today. And
Brynley Evans:Let us know what you think in the the comments. Drop your opinion in there. Do you think we're in an AI bubble? Do you think it's, it's smooth sailing from here? AI is doing the rest.
Brynley Evans:We wanna hear it.
Makoto Kern:Yeah. We love it. I I love to hear the different comments that we've got people from one side of the fence that just wanna move out of the out into the country, forget technology, forget, you know, forget all that and just, you know, work on a farm. But you got the other ones that are trying to embrace it or they're scared of it, but they wanna try to figure how to do that.
Brynley Evans:Coming to the farm too. You can't get away.
Makoto Kern:Oh, yeah. For sure. But, yeah, thanks for tuning in. Like and subscribe. We love, the audience and how much support we've gotten.
Makoto Kern:And, yeah. Tune in next time. I think we've got a really awesome, podcast coming up in the next couple weeks as well. So stay tuned. Bye, everybody.
Brynley Evans:Take care. Catch you soon.
Makoto Kern:Bye. Have you ever played a video game and discovered a cheat code that instantly unlocks abilities that would have taken months to develop? I'm curious. What would it mean for your business if you could access a similar cheat code for your software challenges? What if you could bypass months of trial and error and immediately tap into proven expertise?
Makoto Kern:You know, I've noticed that many organizations spend years developing specialized software expertise internally, often through costly mistakes and setbacks. Would you agree? That's a common challenge in your industry as well. At my company, Impact, we function as that cheat code for companies looking to transform complex software into intuitive experiences. Our clients gain immediate access to twenty plus years of specialized knowledge and an experience of launching hundreds of software digital products in many different industries without having to develop it all internally.
Makoto Kern:You might be wondering how does this actually translate to business results? Well, companies we work with typically see go to market times reduced by up to 50%, their overall NPS scores rocket up, and their product to development team's efficiency significantly improved. Instead of struggling through costly mistakes, they accelerate directly to solutions that work. This is why organizations from startups to Fortune 500 partners with us for years. We consistently help them solve problems in weeks that might otherwise take months or years.
Makoto Kern:If you're responsible for digital transformation or product development, wouldn't it make sense to at least explore whether this cheat code could work for your specific challenges? From boardroom ideas to code, this is what we do best. Visit our website at iiiimpact.io. You can see the link below to schedule a free strategy session. It's just a conversation about your unique situation, not a sales pitch, and you'll walk away with valuable insights regardless of whether we end up working together.
Makoto Kern:Thank you.