Ep 271 Ghazenfer Mansoor - Building the Right Product in the AI Era

Transcript of Ep 271 Ghazenfer Mansoor - Building the Right Product in the AI Era
Host Eric Wright, guest Ghazenfer Mansoor
Timestamps match the published episode. This transcript and its speaker labels were generated automatically and may include small errors.

[00:00:14] Eric Wright: Alright, we're back again and this is one of the fun ones because I rarely get a chance to talk to seasoned pros in broadcast podcasts, but also in the industry. So I'm really, really honored to be able to share a microphone today today with Ghazenfer Mansoor and we're going to talk about everything that's going on live with AI and growth and technology, and particularly I love the area that you're working in around compliance. And I come from a lot of very compliance-bound industries in the past working in both healthcare and financials. So this is close to my heart but before we get too far, Ghazenfer, for folks that are brand new to you, if you don't mind, let's just give an introduction to you and then we'll jump in.

[00:01:13] Ghazenfer Mansoor: Yeah, thanks, Eric, for having me. My name is Ghazenfer Mansoor. I run a healthcare software development company, Technology Rivers. We do two things. We build healthcare products, HIPAA compliant product for health tech companies. Majority of our customers are health tech companies, physician entrepreneurs. People have ideas to want to build a compliant products, web, mobile. The second part is working with healthcare services companies, helping them improve operations through AI and technology. This is where building internal tools, process automation,

[00:01:50] Eric Wright: clinical workflows, AI agents, that kind of stuff. Excellent. And there's the little leak that we're going to talk about your book as well as part of this, which I am. So congratulations on that. That'd be great to jump into, but let's first start by, how did you get here? You know, what brought your worlds into what now is Technology Rivers?

[00:02:12] Ghazenfer Mansoor: So I have a tech background, I grew up in Pakistan, I did a master's degree and then moved to United States, working with different projects and and early in 2000, started working on a mobile, which is way early, it was a web-based, those smaller phone creating wireless communities, and that's where we saw the opportunity. And then from that opportunity spun off a different startup. I was one of the only member of that startup. it was creating a mobile platform. So that's how my journey on the mobile started. And then obviously fast forward, that helped me write the book that I'll talk in a bit, but working with different companies as a consultant, as a startup engineers, different roles performed. Then I started a recruitment software startup. There's a SaaS company. And then 2015, I started this business, which is helping businesses in a product development. We started with a model that building the right product the first time, because we have seen that people build the products and keep building and making mistakes and startups do not have a whole lot of funding to test their ideas. So we wanted to build the right. So, and then that we have done successfully for many different startups. Along the way, as we started narrowing our focus, the software development is pretty broad. There's so much competition. So one of our only customers are the health tech companies. And that's how we started getting more and more into health tech. Then we did a couple of projects where startups came out of the Hopkins Innovation Center, and that's when we learned HIPAA. So now, as of today, we built over 50 healthcare applications. Half of them are HIPAA compliant. some web, some mobile, some combination. So now our focus is purely 100% building healthcare products.

[00:04:18] Eric Wright: Well, that is a niche where we need you and we need much of what you're doing because seeing more and more and more every day, we're just bombarded with software supply chain, risks, and people are sort of speed-running their journey into agentic AI development. And unfortunately, they're using the rear-view mirror to go back and check the architecture. I love that you want to really begin building with what is the right product before we begin. Really understanding that, spend the better time on architecture, particularly when it comes to compliance, rather than kinda let's just start carving code. I'm all about agile, but there is certain things that do need to be architected up front that I think we're, as a software industry, we are unfortunately starting to lose track of. So I'm curious actually, Ghazenfer, on your view of the world, now granted, keeping up with the world, whatever we say today, by. The time this publishes isn't two days. Who knows what could happen? But as of as of today, you know, what do you feel is the state of software, especially in this agentic AI era?

[00:05:40] Ghazenfer Mansoor: Yeah, and you're pretty right on this one. Like the foundation is the key and that's what we talk about like building the product right way, meaning you have to have the right foundation. So without the right architecture, right foundation, you cannot make the product successful. And more importantly, it's many products are not always failed because of that, but also because of building the wrong product. So the requirement is having the right requirement, understanding what needs to be build is key. Again, this is a broader topic. We can talk a lot more deeper into that, but I'll go over a couple of things while we're talking on this one. One is one of the things we noticed that in our business, majority of the work that was coming to us was fixing the broken projects, where people, I mean, and this story is repeated again and again, people have bad experiences with like, somebody's just building it, building it just, but it's not working. Sometimes it's a core issue, sometimes it's the requirement issue, sometimes it's user experience issues there are like, there are many different reasons. So this is what we have one of the eBooks on that top eight reason why software will win projects and how to fix them. And that's one of the top downloaded eBooks that we have, because this is, I mean, that tells us where the problems are. And now we see the same pattern on AI. Many of the AI products are failing because people are just taking it easy. Oh, we think, oh, just like another app, It's like another ChatGPT. So the state of the software is evolving, it's keep changing, especially with the AI. On one side, we are saying it's adding productivity. You have people that are producing 10 times, 20 times faster but at the same time, it's also confusing for many people, including for many tech people. And that's also causing it to create mistakes. So we're at a state where industry is still learning, people are experimenting, they're trying different things, some are working, some are not working, and many of the time it's not about working, it's about not doing it the right way. So I think that what we notice is that AI just changes how you work and every person is different. So for example, you know, like as you're whether it's whatever the to whether it's a writing whether it's technical like articulating the problem is one of the most important thing so you have to know how to articulate the problem and the people who do it well are gonna be really good people doing the AI work how do you are you able to write the context and it's not like people are still using AI just like chat or search just asking question that's not because if you're not giving the right context right data it's not providing you the right data so that thing is changing for development as well so if the developers are just following the instruction and getting thing build those developers will have a hard time the people who are product people people who know how to solve the problem people who know how to ask the right question providing the right context, articulating things right are going to be the most successful people in the AI world because they are going to be able to convey this message to the AI and get the answers right and then when it's not done right you you go deeper in that and get the right answer and I always say that it's like your assistant. You give instruction and it will do the work then he says well can you improve this one, can you do that? So some people are able to take the work from assistant and some not. Some are assistant. then you have to be learning how to get the work from your assistant and that will help you change your mind and going in that direction to get the

[00:09:57] Eric Wright: results right. Yeah it's interesting when you talk about you know I always call it slow down to speed up and part of it is really thinking through what are the right questions that you need to be asked. One of my, I actually just had a podcast recorded recently with a fellow named Alex Bunardzic who we worked together for a few years. And I remember his, what he would always have is whenever the problem inside an app he had this little feedback widget that would be. And all it was meant for was really asking a simple set of questions. You know, what went wrong? What were you trying to do? What did you expect to happen and what did happen? And as soon as you kind of follow that track and then doing one-on-ones and really even before the problems occur, thinking in that way of not just racing past the outcome, like the meme of the guy stepping over seven steps, you know, it's like we have to understand what the outcome is, but we have to also understand other intricacies and dependencies that are architecture related along the way. And that could be also security and cost optimum. There's a ton of different factors that can drive changes in architecture. And it's very difficult sometimes to get junior folks, folks that are brand new to it, to really see that systems thinking approach and thinking about the whole, the totality of the system and how things operate within it, you know, applying the right constraints. So that is a very senior funny that when you talk about using an AI as an assistant is really, that's what we built them as, is to be an assistant. And then we suddenly made them the software architect and made them autonomous. And it's, that would be like handing your junior developers, deity bless them, you know, but they're not going to be thinking in that systems thinking approach necessarily. And they will like a lot of these AI tools be trying to get a good answer, not the right result. And it's kind of like being a good person versus being a nice person. AI is nice in the way that it replies, but it means that it will bypass checks and balances and previous instructions to get to the answer that it thinks you want. We've built it that way, and we don't want that in our teams, but yet we've sort of software defined this in the way that we've made AI assistants behave. Now, looking at your experience in early building, because that clearly, your sort of, you know, hands-on keyboard experience started very early, and obviously, you stay active in participating in development. So what was your move as you went from, like, just initial builder to really thinking in that full systems thinking type of approach for building products products and platforms?

[00:13:11] Ghazenfer Mansoor: So I think my key moment was during the time when I started my SaaS product, which was a recruitment software. So we built the first product, which was a really strong foundation focused on the technical part. And we looked at the competitor software, build something that's rock solid. We spend more than a year onto the development of it. And we went in front of the customer and we realized it's so complicated. It has so many features we went after the feature, like typical problems that most technical people, I would say typical approaches that most technical people will take like going after, oh, we need this thing, we need this thing, we need this thing. So it was a great product, but nobody was using it. And then I had a friend who suggested like, okay, you need to go back to the whiteboard, go by use case by use case and see what each user. That's when I engage a user experience person. Did some whiteboarding session, we did the design. Like obviously we still had the core product, but then change how we approach. And then we started getting the customers. So that was a big change in terms of how you think about it. At the same time, I also feel like, I think these discussions come into, as you approach the thing, like being a good developer, and this is one of the talks that I always have with my team as well. You want to be a good developer versus being a programmer. So your mindset is how do you actually build the application. It's some things are natural. Some are your habits. know how some people are thorough detail-oriented some are naturally very few people are trained so in some ways some of those things i do have that came as part of my nature as well like thinking like i always tell my team that i was doing the test driven development when there was no concept of that we never heard of that like but i would write my first function but i would write the test first and then well in that case the test may be just writing a main method in java and then we'll just run then with one maybe the system that out and then moving forward and then gradually expanding write a function test it move keep expanding that was the mindset i had like taking a lot like thinking about am i building something that just me using or as i build something that could be used for a year from now as the system is expanding some people will think about today some people will think of for their sprint two weeks only and some people will think for a month a year five years how i mean that's how we are all wired like as you growing up in the business like the businesses think of so we create strategies for years we're not creating for a month strategy but yes your marketing and your other pieces of your business could be planning for the next few months, next few weeks, depending on what role you are doing, you have those different people and different work. So that mindset gradually, and as you start working on these, you start thinking about all of these, and then gradually you train yourself as well. So I don't know if I answer you your question the way you were expecting, but I think that's how I look at it. Certain things are you're wired that way, and in certain you have to train yourself, but along the way there was extensive learning in terms of how other people are doing, whether we talk about the productivity part, whether we talk about communication and all of those. there's a help available, there's a guidance, the coaching, and all of those those are the learning that helped me go towards the right path. So I think the most important lesson I would say in that said like if you are willing to learn, if you have this mindset that I'm not perfect and I can be better, that means you keep that room of improvement

[00:17:36] Eric Wright: all the time. Humility is a skill and unfortunately not one that is baked into everybody. Some learn it, some don't, some are a little early to it. But yeah, and in fact I'll say you, how you explain that really showed me even more of my what I hoped you know out of your approach. Like it really is that foundation. That's kind of why I worry sometimes about there's a bit of a push away, like people don't need any formal schooling. Now, I don't have a CS background. I don't have all these things. I came to it differently through the operations side. So I didn't have to have the sort of pragmatic programmer type . But what I approached the problems in the sort of doomsday scenario and preloading what all these things are that could go wrong the great thing about being an overthinker makes me particularly good at disaster recovery and that was my system that i was able to navigate beautifully through and and i can launch into it right away and i imagine if i were to say okay Ghazenfer we've got to do this thing you aren't going to race to features you immediately are going to say okay what are the goals how do we think of this in the long term like your immediate questions will be so fundamentally different than someone who is just used to opening up AI IDE of choice and type, okay, we're starting a new project. It's going to do this. It's the pause to think It's the pause to think deeply about what are the goals of the system and also, you know, what are the constraints in which we want it to survive in? And I think constraints are beautiful. Constraints are rules in which we can freely work within. And I feel better knowing what those, you know, whether they're soft or hard constraints. So that's, now on the software side, you've come through a lot of generations of how software has been built. And how do you look at like kinda the availability and architecture, you know, resilience today versus how you maybe would have when you when you started that first software company?

[00:20:07] Ghazenfer Mansoor: Things have changed significantly. I think with time, technology, technology is becoming easier and easier, cheaper. Now storage is cheaper, the tools are cheaper, you can achieve a lot more than before. I think the important part is how do we take advantage of this one? It's not about just building the same thing again, but now getting it faster. But sometimes those approaches are also different. The architectures are different. The people are building more, you can say, non- word slip of my mind, but less tightly coupled or loosely coupled applications. Because if you are creating an application that are fully dependent on different things. And the world is moving toward that and we already have all of those things when we talk like we have APIs has always been there you have this API and those kind of integrations and then now you have MCPs for the AI work so so all of these things and then all the system that we're building whether it's on cloud any of those you can make it in a way so that these are all the the independent pieces that could easily be plugged in together. So now you can do much faster development, and much cheaper, be more productive and many time it could be 10 different pieces of your code maybe in a 10 different languages and they still all work together, could be a different lambda services or whatever the different microservices. So so These improvements help a lot. At the same time, for some people it may be too much confusing as well because there are too many options available, but majority of those will do the solutions the way you want but I think at the same time now with AI with all these lights even the Claude Code, Cursor and all of those different tools available you can do a lot more faster and I'm the way I look at it it's not about just doing it faster but it's actually doing it better than before because previously you didn't have enough time to do everything Let's say if you pick up anybody's card, you may not have people, people may not have done, for example, the unit cases and all the time, maybe 50% of the projects will have it. Now it's much easier to do them, much easier to audit the card to, I would say, to look at the core coverage and all of those things. Enforcing those rules, governance is easy. Again, it brings its own challenges as well, but at the same time, now you have a lot more oversight and much better way to oversight. So bottom line you're getting a lot more productivity in the same time or even in the lesser time.

[00:23:06] Eric Wright: It is strangely wonderful how fast we can move but also frightening in many ways. Like this is what I worry is that people are seeing speed as the new feature and forgetting about the outcome that they were trying to get to which was I said the difference between speed and velocity speed is just going fast but velocity means that you have an awareness of your start point and your end point and you have a greater speed on that path people are forgetting about the path and they're just aiming for the speed I feel like and that's it's also tough because folks like you and I we're probably connected to a lot of what's going on in the industry and we're reading news and we're keeping up with the situation as they say. So we become sort of overexposed to the noise that's in the environments and then we walk into a real active enterprise production environment and it really feels like ah like you got off the highway and now you're at the you're in the cult off the highway you can hear the highway but this is where reality is actually occurring so how do you how do you find the the sort of split is there really still a dichotomy between how things are really being done today versus how the industry pundits and the the folks on twitter and blue sky think it

[00:24:36] Ghazenfer Mansoor: going? So it is the fact it is the reality that AI has changed the world and things are moving faster. Always give example of Blockbuster and Babies R Us, Toys R Us. You have a choice are you gonna be competing because the new change is coming versus oh it can't change or it's not easy and we do hear that comment from developers from big corporations many times oh AI has these restrictions or we cannot use in our environment so it's like closing an eye and waiting for some miracle to happen Eventually what will happen, one CIO will come, one CEO will come and he says, well, we're going to move towards this one. And then suddenly all those people who are not willing to make that change will be crushed. So I think the stories of Babies R Us, Blockbuster, all those are well known to everybody. So this is our opportunity to go up and say, well, we're going to compete. We're going to learn the AI. We will get on the bus. We will get on this ride. Worse is we just let it crush us. So I think the decision is ours.

[00:26:05] Eric Wright: I do feel like this is why there's such an impactful importance to the human side of AI as an industry, particularly in software developments that we, You have a chance to participate in it or to complain about it. And it's or to a complaint known in any way but like if that's if all I'm going to do is just throw complaints into the world and like you know turn a blind eye to what's really going on I'm I'm giving up my position and that's it's such a tough thing for people to see past you know it's very easy to get focused on the negative side and and just sort of hoping it won't arrive but you're seeing it, but you are building a very human approach to it while embracing AI for its best of capabilities, but leveraging humans for the best of capabilities. So from the Technology Rivers standpoint, what do you look for when you're bringing new folks on board? What is the ethos that drives the human side of Technology Rivers?

[00:27:25] Ghazenfer Mansoor: So, the hiring part also changes, because now we also have to have the right people. I was talking earlier in terms of how do you articulate the things, how do you solve the problems? In the past, it was just a technical. Technical skills are still important for the kind of work we do. at the same time, if you're not able to articulate those problems, right, if you're not able to solve those problems, and you just have a technical skill, probably it it's not going to work in the long run. So, our hiring approach change how we hire people how we interview how we work them. Everything is changing. bridging AI also as part of it. Along the way, obviously, AI bring all of those challenges. So what we started doing in our company, we made a mandate and this was not just started, started like to go where we started defining those goals like for AI and for other things so that the whole company's on board. We allocated a specific amount of money, can use towards buying the AI tools, experiment it so that they have the capacity to do those experiments, because once they have it, then they can try a different thing. And once they start seeing the opportunity, then it's much easier for those people to adapt versus just listening to others and, oh, this is coming.

[00:29:06] Eric Wright: Now, that is, I like to call it sort of the culture of experimentation, And this is what has always jumped out from successful teams and it's so funny that that you just described it exactly as other folks I have seen that have been in really good. Tightly, you know, bound to ethos, but loosely coupled to solutions that I think is the right way to go. And in doing that and supporting that again, like we talked about constraints as being enablers, you say, hey, here's sort of the outer bounds, but move within these bounds. And that controlled freedom gives a lot more culture of experimentation, I find, with the right people, of course, as you said. So how have you seen where some of the sort of the traditional software houses have never found that? Like I see all these sort of big, big, big orgs and they're getting these giant RFPs and they're doing these big things, I don't want to name them, but we hear unfortunate stories all the time. about

[00:30:30] Ghazenfer Mansoor: I don't know that's honestly the answer to this one. I think those things are still happening. Those, I think, the big RFPs, the big projects, it goes back to the problem solving. What are we trying to solve and how? So, I think it's a complicated challenge at the same time. Now, what we see is a lot more people. The feel is that, oh, it's much easier. It's AI, we can get things done much faster. But at the same time, it comes with its own challenges as well, because people have these misconceptions that, oh, AI would would solve my problem if I just search AI and it will give me everything. No, AI, there's a lot of hallucinations, a lot of mistakes. So AI will always tell you the truth. Like they'll always tell you, say, it knows the answer. Like even if there is no data available, so it really says, oh, I don't know the answer. I mean, every time I say it would, if it doesn't know, it will guess. That's not the real answer. You can't have your real business problem solved based on the guesses. So having the right context, the right data, all of those things, like in your business, like you have to have the right data mapped. And because AI is giving you results based on the data that you have, you have given the right governance, this ethical part. There's a whole lot of things that comes with it. I think the traditional mindset in many places is still there. As we were talking, the change is difficult. People are, still doing all of those RFPs. Now, there's a twist coming into it. Well, a lot of those proposals or RFPs are being created by AI. now unfortunately a lot of that stuff is also creating a lot more confusion that now if they're humans are reading and is generated by AI versus if it's created by humans and then AI is generating the result they both have so there's a human loop that does come in place it's a combination of things so I think Yeah, so the change is big, and it's not easy, even at a small organization. So I think it's a gradual progress that people will have to make and go towards adapting AI and the faster work, I would say. And the way we look at it, I think anything when you create as a big project it's always going to be a challenge. We look at it as can we pick one small thing and solve it and then it doesn't look like that you're going to make that as a big project. Once you make that small change and make people excited about it then do another one. So once you have those drops of those small small changes and gradually it will become into a big water bucket bucket for you. So the same is the case case with AI or any change. If you solve one problem at a time, you don't realize that after something, oh, this is huge. Now we're in the last one, one year or two years, we solve these 50 problems using AI. And we didn't even realize that we are moving towards AI.

[00:34:09] Eric Wright: Right yeah, and that's if you if you defocus from the larger picture, almost like sort of a. A depth of field like bring it to like what is this specific thing? What is the outcome I need to achieve? And then you sort of laser focus on that thing. It allows you to concentrate with the rest in the background, obviously, but yeah, that is such a good way to describe it. And I never wish ill on these big companies or people that have struggled with these changes. And I want them all to learn, adapt, survive, and continue to employ many, many people and build things that are positive for our world. It's never that we want to look and say like, Ah, you know, that giant, you know, tech firm, you know, didn't deserve to survive. You're like, no, no, no, like, it's tough. It's tough to run an organization of that scale, especially public companies where they have fiduciary responsibilities and they, that can lead them into difficult decisions and tough directions. So it's, I have a deep respect and understanding for it and a hope that we all come out of it together with the same goals. And that's why I love, like, what you've done is to be able to be a beautiful disruptive force, whether intentionally or not, in how you've approached the problem and you've proven it time and again, you know? So this is not a like, oh, this is, Ghazenfer's first shot at it, he's just a kid at a school and he thinks he can take over the world. Like, no, no, we've been at this for a while and you've proven it in practice more and more, which is what we need. I like to see great builders with the right ethos putting more people to work and solving problems, particularly in healthcare. Like, wow, if you can be impactful, I tell people all the time, like the code isn't the outcome. Like it's great that we build these things, we build these tools, but then think a little further. And there's somebody who, you know, I'll show this famous video of this girl who she gets a cochlear and they turn it on and she hears her mother's voice for the first time. And when you see that, even just describing it, is like, it's emotional. Like, that's what you do. Like that, when you can inspire people building code towards that thing, I think that's so important. Maybe on that, how, like how do you involve engineers with the end outcome and like understanding what it's gonna look like in the real world? Do you find, do you let, do engineers participate more with kind of product management and with the customer side? How do you structure, how you communicate with your clients through that development process?

[00:37:17] Ghazenfer Mansoor: Yeah, so we involve everybody from day one. So, like we use Slack for all of our communication, we use Zoom calls, we use Jira. So even for all the client calls, everybody's on a video call. So it's a collaborative effort. So, because even if different people are working for a different part if they don't know the business part, is gonna impact the overall solution. So knowing what are we building, understanding the end goal, knowing the business part of it, that does make a difference. So it's not about the responsibility of a one requirement person or one product person. It's a combination. So everybody's involved in some way because any change that happened on one side could have an impact. So it could impact the foundation part. The tech people needs to be your testers. So yeah

[00:38:28] Eric Wright: in like planning. I remember meeting with somebody who's an engineer for working on on large like cruise ships and he says they they do so much planning obviously you can't just you can't YOLO code a cruise ship but he said like their their project plans are two years long long and they're in 15 minute increments and they know because there's so much that is a very fixed timeline that you can't escape there's physical engineering and to know that a slippage they can sort of predict how that's going to affect the final delivery because when they deliver, it's a million dollar a day fine. So they've got a very hard line boundary that they have to hit without sacrificing quality, safety, et cetera, et cetera. So they've had to be super, super rigorous and that's a very distinct problem that has a very distinct challenge. Challenge in architecting towards. I don't want to get that rigorous, but I do like that, we We need to continuously sort of check where we are against the overall. And that's another thing that I find that a lot of developers forget is that they'll put away the overall, they'll get that depth of field singular focus, but then they defocus too much, and they get locked in on maybe the wrong deliverable or the wrong outcome. they're aiming for. So how do you, how do you maintain both the long view and the short view as a leader and also

[00:40:05] Ghazenfer Mansoor: within your team? So this is one of the ongoing challenges. So we have to continue to work and improve. Part of that is training reminders and different strategies that that we, that we adapt. So, I think a combination of things we're trying to do, soause we have to build this clarity framework internally in our organization where we have this rule that every time you're doing something, you have to ask multiple questions. And then you have to share share at the end of the meeting like hey this is what I understood and then there's a communication like you acknowledge you respond you follow like so whatever are the things we're trying to do those things so that um we're not missing the things i think the bigger part is when you miss certain things in a discovery and that could pile up into something else in the long long run, right? And the most important part is, whatever are we doing today, is that impacting the overall goal? What is the end goal of the product that you are building? What is the end goal for whether it's an an internal project. It could be a marketing team end, goal it could be the sales goal or the development team specific goal. Are we moving towards the end goal? So how is the task that I'm doing today is impacting my goal towards my my task towards my end goal of this product so knowing the goal knowing the direction the project is going knowing the right outcome does negative so this is where it's important that you bring those people earlier in the conversation so that they are also also

[00:42:29] Eric Wright: And it, I mean, I hear what you're saying, you know, that's the beauty of, you can tell us it's inborn or at least so deeply learned that even your approach to answering questions is always thoughtful and so appreciated because it's very easy for people to just want to race like an AI to an answer and call it the right answer with hope that they can maybe pick it up later if they need to. but it is good to pause, pre-reflect, you know. And then as you answer, you're already thinking of, as I'm describing the answer, what is the goal of of what I'm trying to answer? It's surprisingly hard to find people that can even do this conversationally. So that's it stands out in everything you do, which is which is amazing to see. We're

[00:43:26] Ghazenfer Mansoor: learning every day, so it's not something we came up with a long time ago. It's just the learning process that gradually improving And some lessons And some lessons I've learned the hard way.

[00:43:39] Eric Wright: That's, well, that's the good thing. And I like the best thing about humility is admitting that we've been on the wrong path a few times, right? Like that. The reason we know the right way is because we found the wrong way during during some paths, you know, exploration. And every journey is likely to take you towards a thing. And even the client may have changes to their goals for the project and the tool, especially as we see, you know, rapidly changing, you know, regulations and, and ways that we're handling that, that those things can't adjust quickly. But I find that we are having to be very adaptive in in that, you know, rigorous, you know, when people say HIPAA, you can't just say like, we're HIPAA ish, like, this is, you You have to be legitimate in saying that you can provably deliver within the boundaries of the regulation and the requirements. And it's very easy for people to just think like, you know, there's no close enough when it comes to HIPAA or, you know, these type of regulations, especially this because our health information is I'm Canadian by origin. don't have the level of sort of identity and health challenges that we have in the States now that I've been in the States for many years it opened my eyes to how different it is with a vast population and so many different ways from state to state and then you get global like it's I'm scared I'm already overwhelmed just thinking about it and you you somehow keep this you have the outcome, you know what you're aiming for. How do you keep that ability to navigate within those tight bounds and also just keep moving fast and keep up with different technologies and ways to deliver solutions?

[00:45:44] Ghazenfer Mansoor: It's also one of the difficult ones. I'm a big process person. So I think anything we look at it, I like to, my approach is that this is not something to fix, but how do we build the process so that it doesn't happen again? It still happens multiple time. You just have to, again, that goes back to the training the process because the people are still people you still have to train them as well so it's an ongoing process but the big another big part is the productivity part how do you get things done in a way so that you can achieve more by doing it faster. So that means there are different ways. Could be a focused time, could be blocking a time, could be just delegating and finding the right people who may be doing. There are certain things that do need more iterative time or multiple time involvement and there are some where you have the right team member and those things get done you don't have to worry about it once it's once you hand over so depending on how those problems are solved which team member gradually those things are again they're improving and in some cases we struggle but yeah so i think overall i think this is also a necessity it was talking earlier, if you have to be competing on an AI part, so we have to be staying on top. So this is where like whether I'm doing this podcast or other like I have to keep improving my knowledge as well, knowing how all these different things work as well as working with those clients, learning from their experiences and from my team's experiences because all of those things are the ones that is becoming the input to all of the stuff that I'm

[00:47:47] Eric Wright: doing. It's you have to be a continuous learner and a continuous explorer and in your podcast is fantastic and you've obviously you've been on a bunch as well as the as a guests and so I was lucky enough to take in some of your your previous contents and you're you've you work so well with with people. And And ultimately, it's probably pervasive again through Technology Rivers in that in that you run a mentoring organization and you don't hide the business from the developers. You involve them in the business, like involving them with the the clients versus trying to like segment them out and keep them isolated so that they're only focused on what they're supposed to. That it's very rare to find people that can do that as a leader and do it successfully because it's hard to keep that focus and keep that strict method of freedom and but tighten down the constraints when needed to do complete the task and get it done. So it's so mad respect to how you've you've brought this to the world. And we always like to say, I don't want to burn off our time. I could talk for you for hours, especially because I like to say that you're, you know, I like to talk to people who literally wrote the book on it and you did. So let's about your book, which was just released. So congratulations on that, and I'll make sure to put links and point people towards it. Let's talk about the book and what went into it. And I have no doubt I will put my endorsement that people need to get it.

[00:49:53] Ghazenfer Mansoor: Absolutely. Yeah, thank you. So the book is called beyond the download, how to build mobile apps that people love, use and share every day. So we all have hundreds of apps on our phone and we know the meaning of beyond the download those apps are downloaded how many times do we actually use there are very few apps that we use on a daily basis so how to build the apps that people actually use it's not about downloading you can get a download through many different ways but it's about bringing the users back to the app so that getting that retention keeping users engaged how do you do that and how do you make it exciting for them to be on that and that's when this these things happen then there are I think those numbers are known to Apple Google as well so obviously that means they will also promote if the app is good it will get its name out so I think so the book talks about different strategies we have 32 plus chapters that talk about there's one on AI as well how to leverage AI for that so it talks about different strategies how to build those apps so that you get more users more engagement so and it is different like this every app has a specific user base so it's not gonna be the same Same thing won't work for everybody, different strategies would work differently for different people. And some are free, some are paid, some will have effort. But Book is for all the people who are building the app, who own the app, or who have the idea so that you build it in such a way so that you can have the most

[00:51:49] Eric Wright: engagement. I love about the the thesis and the whole premise of the book is that it again teaches you to ask the right questions based on where like these are the fundamentals that a lot of builders don't have you know like they can be great software builders but not understand that how like distribution ultimately is what gets you to the world and it's very difficult. The greatest code can be beside another piece of software with the similarly great code. One has a great marketing and distribution, another one does not. It's not the code quality necessarily that makes this a successful application or successful problem solver. There is so many more elements to how do you describe the problem that you solve? And just like every startup, the most successful startups that I found are always bound in this vision of being so deeply in love with the problem that it just drips when you look and they describe the problem and you go, okay, I've been listening to you guys and for a talk about this problem and this is it, I've hired five agencies, They can't I always end up in the same And now because the way you talk about the problem People would think, oh,. You're giving it all away like well, Mr. Beast gives the secrets away all the time on podcast after podcast. Yet there's no second Mr. Beast. You know, there's a there's a thing that's very you about what you and your team deliver. And what's even more cool about it is how open you are about describing it. Even like your resources on the blog and your downloadables are spot on, great. Everybody should just go get it and say, okay, how do I take this and put it into my practice? So thank you for putting more great content into the world that isn't just a, hey, buy my tool at the end of the last chapter.

[00:54:04] Ghazenfer Mansoor: Yeah, thank you. Thank you. And I do want to add one other thing about my podcast, which is called Lessons from the Leap. And you can find it on on my website, ghazenfer.com. So the podcast, the book about about everything, you can find it from my personal website.

[00:54:26] Eric Wright: Have you ever had somebody say, like, hey, you should keep some of this inside? is every once in a while I bump into somebody and they're like, don't you worry that you're giving away all your secrets? And like, what I'm giving away is that my secrets aren't the secret. Like I want to be the secret to what I deliver, you know, or like the ethos is the secret. How have you, what have you done despite advice instead of because of it over your career?

[00:54:57] Ghazenfer Mansoor: Yeah yeah so this is yeah I mean I do get that a lot and it's interesting because honestly at the end I feel like nothing is secret that data is out there it's about many times you just didn't know it so now you have it but even if you share it how many people are going to implement that. So every time somebody tells me, I share one story with them, and again this is one of the books I was reading, I didn't read that personally, so that there was a talk by somebody, so you know the Geek Squad acquired by Best Buy, so the Geek Squad founder was giving a talk and one of the guys in the audience asked the question, he said it does not make sense that you put the tutorial on how computer even though . you're in the business of fixing the computer like how do why do you give all the secret on the YouTube and then you know the history how geek squad was acquired for whatever that big amount so the way we look at it like when you are sharing these things there is always going to be a small percentage of people who will take those and do it themselves because they, they can technically can or they just don't want to spend money but there will be a big amount of people who can do it but don't have a time to do it and then you are the one who's trusting who's building that trust and oh we know how to do it so I think hiding the secret doesn't make anybody. I mean yes you know it but then it stays with you but how do I know you know it unless you share it. So for us it's about building the trust. I think people trust us more. Whether and we were built putting together the HIPAA checklist, I looked, at so many competitors, I probably look at 50 plus different sites, and I downloaded many of those HIPAA checklist. Not a single one had the real checklist that was needed to build HIPAA compliant app. Because those were done by marketing people and marketing people will do search and they'll find, because we have this term in computer called garbage in garbage out. you got something from other sources and this is what you got and you put it but when you put these things in practicality that's different so we wrote something that is actually used in development and you need to have that check so when people come to us and well you don't hire us that's fine here's a checklist look at it just make sure whoever is building it follow these steps. Even then, that's fine, but do they have to follow that? Because if the other developer is doing it and they are not the one bringing those things, versus do I have to validate my work? If I work with a vendor, I want to see their process rather than them saying, hey, this is what you want to follow. So if the checklist is not there, I have less stress on that vendor. If it's my checklist, then it's my process.

[00:58:22] Eric Wright: Yeah, and interestingly, And interestingly, it is a beautiful qualifier for who's the right client and customer to work with. And you look into sort of the geek squad method. Like if they publish a how-to and even give a video and do all this, if somebody consumes that and decides to go it alone, they probably should have done that. And they just needed the nudge. Even if they were a customer, they probably would have been a complaining customer because they would have been going. at it, thinking, I probably could have done this myself. Their approach to the buyer experience is already sort of jaded because they're just like, they're only doing it out of frustration, not necessarily out of actually just wanting to embrace a solution. They just, they're stuck and it's, it's a tough lesson. So there are certain kind of buyers where, you know, I've had many, many people tell me, especially in consulting, sometimes you have have to fire your clients. When the relationship is not working well and you're not working within their org style and they can't work with your org style. style and sometimes it's just the right thing to step away and that it's tough as a founder because we think well I should be able to solve everybody's problem it's like no, no that's not what you need to do that's not why you're a founder that's not why you're successful you're successful in solving the right problem for the right customer at the right point in their journey the right way, not be everything for everybody because if you try to be everything for everybody, as they say, you become nothing for nobody. You've done it. You've continued to narrow and find niche and then accelerate within it. And to most people, if they looked at it, they would say that looks upside down. You should have started it with just healthcare and then expanded out to everything. You're like, no, no, no, no. That's not how we build a successful organization. Now some try to do that and that's how we get the big four consultancies because then they become everything for everybody and we struggle with getting good outcomes in most of those environments unfortunately. So I applaud your approach and for putting it out there. There's a beautiful confidence in being able to do that and with that, that makes me want to work with you. That is what ends up happening is that the more people give way, they think like, he's so confident in telling us how he does it, I wanna see it in action. Like that's what it creates is a beautiful relationship before you even write the first line of code, which is what's needed. So what has got you the most excited about the sort of pace of news in AI and like the pace of opportunity? I know we've only got a couple of minutes left,' but, you know, sudden people would be frightened. I'm frightened of what could happen if we don't do the right thing, but I'm excited about what we can do. So what are you excited about here in the start of 2026, Ghazenfer?

[01:01:44] Ghazenfer Mansoor: So I'm excited about the opportunities that AI is bringing. Yes, in some ways for some people it's scary as well because they're looking at the jobs only. It's in business but at the same time it's opening up opportunities as well. So one of the things I always say, if you look at it, most of these people usually have more stuff to do than they can handle. So how many times you have people in your company where you can say, oh, I am done with everything and I don't have a work. In your personal life, in your business life professional life, everywhere, you always have most stuff to do, right? Now AI is giving you that opportunity so that you can achieve a lot more than what you used to do. With AI, with agents, with automation, now things are getting faster. So you started seeing these people who were obviously not able to do certain things because of whatever the limitation, they had no time. Now they're starting achieving, and they're starting to get more excited. So as people start getting excited, they say, oh, I could do five of these things more. Now, so that's really more of a, you're seeing like rather than people powered, now you're doing the system powered. It's not impacting anybody's job. It's just that now those people even achieving a lot more. So that means you have a lot more happier employees because they have seen what they achieved in the past versus now what they're doing. I'll give you a small example and one time I had this list of close to 50,000 people from a different list and I had one of my team members clean it up to do certain things and the amount of work she was based on this was about a month long she said okay it's gonna take end of September to then I said okay how about we do this together we opened up we did a screen share we opened up ChatGPT we loaded with few prompts we were done in less than two hour that whole thing that was supposed to be done in a month now that opened up the eyes so then she started doing a lot of those so now suddenly a lot of those things are getting done much faster but yes there are other things that start coming into the plate that means you have you can do no different types of things that means you are learning new stuff you have more opportunity more time to train yourself so I think AI is opening a lot of opportunities and that's um it's exciting time and it's exciting time to avail that opportunity but yes you can sit aside and wait for others to crush so going back to the same thing we're talking but I would say that it's like a storm right are you just gonna wait for storm to come and hopefully it won't crush you versus are you gonna prepare yourself so that it

[01:05:06] Eric Wright: does not impact you. Well it couldn't, I couldn't close it any better than that. Ghazenfer, thank you so much. This has been a fantastic conversation, one I could continue on. For folks that want to get connected with you, what's the

[01:05:22] Ghazenfer Mansoor: best way to do so? My personal website is ghazenfer.com and my business website is technologyrivers.com, r-i-v-e-r-s.com. So anything about the business, feel feel free to reach out. And then I'm also accessible through LinkedIn. Feel free to reach out, but do mention the podcast that way. I know how you learned

[01:05:49] Eric Wright: about me. Indeed. Yeah. So I definitely tell people to do that. And so thank you so much. And yeah, I'll make sure I've got links to the book so that people can preorder because we're coming up on availability. And this is going to be exciting. I'm looking forward to getting my copy so that I can go from tip to tip on that one and it is so great to have these conversations and know that there's more of us out there that are trying to solve problems and creating human opportunities in a very AI driven world. So thank you Ghazenfer, thank you again.

[01:06:26] Ghazenfer Mansoor: Thank you very much and thanks for the book download and appreciate the feedback as well on Amazon. So thanks for having me on the show.