Start With the Problem, Not the Tool with Navin Mirania

AI automation is everywhere right now, but most of what people see online is the easy part: a slick demo, a chatbot, a promise that one person can suddenly do the work of five. We get real about what happens after the hype, when you try to put agentic AI into production and it has to run every day on real data, real customers, and real consequences.

Grant McGaugh sits down with Navin, a longtime IT and workflow automation builder who helps small business owners design reliable AI agents, configure tools, and connect messy systems into clean business process automation. We unpack why the biggest challenge is not “which AI tool should I buy” but “what problem am I solving.” From financial reporting workflows to e-commerce operations, we show how to map the steps, define the inputs and outputs, and build an AI roadmap that actually improves speed, communication, scale, memory, and pattern recognition inside your company.

We also dig into AI governance and validation, because probabilistic AI outputs still need domain expertise, especially when accuracy matters. Then we shift into what is changing in marketing and discovery: SEO is no longer the only game in town. With Artificial Engine Optimization (AEO), people ask AI for answers, and businesses need to understand how they show up and how to audit what these systems return. If you want AI to save time without creating new chaos, this is the playbook to start with. Subscribe, share this with a founder who is overwhelmed by AI tools, and leave a review with the workflow you want to automate next.

Thanks for tuning in to this episode of Follow The Brand! We hope you enjoyed learning about the latest trends and strategies in Personal Branding, Business and Career Development, Financial Empowerment, Technology Innovation, and Executive Presence. To keep up with the latest insights and updates, visit 5starbdm.com
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And don’t miss Grant McGaugh’s new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/

See you next time on Follow The Brand!

Transcript

Why AI Automation Is Everywhere

SPEAKER_01 0:01

Welcome everybody to the Follow Brand Podcast. This is your host, Grant McGall, and I get an opportunity to talk about a subject that has been top of mind this entire 2026 season as we go now in uh July 2026. And this, what has been on top, meaning right in front of my funnel, like every day when I'm talking and I'm looking out, is AI automation. People now have uh really got a taste of what AI is from a chatbot, a large language model, but they're starting to say, How do how can I automate business processes? You know, that's what we call business process automation. It's been going on for a long time, but not with an AI layered algorithm on top of that. I want to introduce you to my good friend Naveen. He does this for a living about developing agents, building out workflows, configuring tools, and guided execution around, especially for small business owners. What this really looks like beyond the hype, because they make it seem so easy if you're following a lot of certain people, but it is not an easy thing in production. Easy thing maybe for beta, but not in production. Production is a whole different animal. So, Naveen, would you like to introduce yourself?

SPEAKER_00 1:19

Yeah, sure. Uh yeah, nice to meet everyone here. And nice to be on the show. So I'm Naveen and I'm based out of India. And I have around 25 years experience in the IT sector. Mostly I've been working with clients in the US, UK, Canada, and the Western countries. So prior to the AI era, I've been doing a lot of data analytics, a lot of uh market studies and things like that, a lot of building up sales funnels. It used to be a lot manual process back then. But in this AI era, it's more like automation using systems such as Goha Levels. And there are so many other systems in the marketplace. Like, and I'm adapted to everything, I've used all the systems. Different clients prefer different technologies, different methodologies. Sometimes they take a subscription to a particular past platform because someone told them to, but they don't know exactly how to use it or how to derive value from it for the business. So that's where I help them and apply my knowledge because a good understanding of data structures and how these systems are layered in the back end. So if they are if they are providing certain outcome, I exactly know how it's configured in the back end and how to properly optimize it. So that's my expertise area where I understand, you know, a business from a founder's point of view, understand what the problems are, understand where the bottlenecks could be, and then use technology and these modern systems to bring about efficiency in those workflows and make life easier for whoever is running the business.

SPEAKER_01 3:18

You know? So this is what I want to ask you, because I think what you just said there, because now we people say, oh, okay, we have an expert in the room. Like, yes, we have Naveen, he's an expert in the room, especially when we're talking about agentic AI. He's lived this world for a long time, even before they were calling it AI, you know, business process automation has been around, but it is taking on a different uh look. You just mentioned some of this stuff was done manually, now it's done automatically. But taking that AI knowledge and turning into a practical revenue generating solution, that is where you sit and live. Help us first understand the problem that you normally see with small business owners when they see this signing object and say, oh wow, I can take one person and make them five by utilizing the AI agents or genetic AI agents. What's the common problem that most people don't see before they kind of jump in to this new technology?

SPEAKER_00 4:19

Right. So uh let's take an example. Let's say uh there's a financial advisory firm, right? There are a lot of financial advisors in that firm. And when they're dealing with their clients after their meeting with the clients, they have to prepare proposal reports. You know, they get a certain set of input data, then they have to do some number crunching on that data and provide a financial report to the clients, right? So it becomes a very manual process where you know you're crunching the numbers manually using Excel or whatever. So this is a perfect example where an AI

Turning Business Pain Into Workflows

SPEAKER_00 5:00

system would be very helpful. You know, it takes inputs from a set of data. It could be a PDF, it could be a, you know, some sort of uh Excel sheet or anything. And then it applies the software takes over, does all the number crunching, and you know what could have taken four to five hours to prepare a report and present it to the client now just takes about 30 minutes or maybe even lesser, because it's all optimized and processed through a system, you know. And but as a as a business owner, you as a financial advisor, let's say, you just know the numbers, you know how it should be working, but you don't know how to put it into a technical language, you know. Yeah, how how to present it to a technical person so that he can design a system which automatically does that number crunching. So my my expertise lies in that area because I understand both the business and also the technology. So I'm the sort of the bridge between the business problem and the technology that's going to solve it.

SPEAKER_01 6:21

This is important. I want to already really lean in what you just said, because we are so used to, especially when you're dealing with um large language models that we're all enabled by AI chatbots and things like that. We're speaking human language to a machine language for the most part. But it is a certain way that you have to present that data, what you're saying, in order for that machine language to truly understand what it is that you want to get you that type of uh output. And going back to what we I've been talking about all year about deterministic systems and then probabilistic systems, when you're dealing with probabilities, especially in numbers, you want exact, precise numbers. If you're putting everything into an AI engine, you might not always get the exact right answer. Is that correct?

SPEAKER_00 7:20

Yeah, you know, governance is a big part of AI. You know, people think, okay, we have an AI system and it's going to do everything for us, right? That's true to an extent, but then there's also a concept of AI governance where the output that AI gives has to be validated by a domain expert, you know. So someone running a medical report on certain data and you know, generating some sort of a report, but then that has to be validated by a medical expert to verify that the data that has actually been presented is correct. So a lot of people say that, okay, AI is going to replace human labor, humans, right? But that's not 100% true. It's going to do a lot of the work that humans have been doing, but the domain expertise is still going to be there. So someone still has to validate what AI is present in. So that's called AI governance. It has to be a big part of the, you know, the workflow when businesses are implementing AI in the organization.

SPEAKER_01 8:42

I love what you see. I and I want our people to really understand that. Domain authority, your particular expertise, what you understand right from wrong, you know what needs to be done is still necessary. Because even when, like even myself, I'll put in, I ask for an output, let's say in an AI chatbot, they'll give me some output. I'm like, no, I need to revise that. I might go three to four reiterations. The machine is not going to just do that on its own. Because far as it's concerned, it's done its job, right? It's it's it's gotten the right output. It doesn't understand that it's right or wrong. It's just as far as it's concerned, it's giving you what you asked for. So when you get into agentic AI modeling, now you're starting to get to multi-step applications. Now I'm going to go still in the problem world, not the solution world, because if you're taking bad data and now you're scaling it and you're manipulating it, it is continuously being uh worked through an agentic type system. And agentic again means multi-step. It has different tasks that it's doing. That's how you're building out the automations. So in order for it, be in order for it to be reliable, you've got to have somebody that understands what that output needs to be looked like at every step of that interaction. Help us understand that a little bit deeper.

SPEAKER_00 10:09

Yeah, you know, uh, for example, uh, let's say let's say someone is trying to implement uh AI system and the organization, right? So uh the team that is developing that AI system needs to have the input from the domain expert. Like, you know, uh traditionally, we have been using these inputs, you know, and then we have been given we have been getting this output, right? So how do you that's like arriving from step A to step, let's say F, right? A, B, C, D, E, F, right? So that domain expert knows the data is going through several steps to get a final outcome. Now, when AI system is being implemented, that domain expert really has to explain it to the tech team, you know, and then they uh understand the workflow and implement it, right? Okay, let's take an example where uh uh let's say a business, an e-commerce business, they have the problem that their cost of operations is high and revenue is low. Right? So how how does AI solve that problem, you know? So probably the company, the e-commerce company, they have data segmented into different channels or platforms. Like they may have a Slack channel, they may have a you know uh customer support system, they may have the CRM, they may have the meeting recordings, right? Where different team members are discussing the challenges that they're facing with customers. So all of that data, when it accumulates over a period of time, it becomes very fragmented. And you cannot actually derive the essence out of that data. You know, like what is the essence that is lying within that data that can help the founders, the management take some actions and improve like what needs to be improved to reduce the cost of operations, to increase the revenue, you know, because within that data, there may be certain complaints by the customers who may be saying, okay, the competitor product has this feature or this attribute which your product doesn't have. Could we implement that in your product? You know, if you could implement that, your product would be so much more better than the competitor's product, right? But that sentence may get lost in the entire, you know, the entire volume of information that is out there. Right? So a system, an AI system, hence it's programmed to capture every data point, it won't miss it.

unknown 13:15

Right?

SPEAKER_00 13:16

And it'll incorporate every everything said by every customer and give a summarized, synthesized output, which helps the management take better decisions, improve their product, improve their customer service. And this overall improves the you know how the customers feel about the company, about the product, the overall customer experience.

SPEAKER_01 13:42

I truly believe that I want people to understand that in my world, I used to say technology does three things very, very well. But I'm gonna say it does five things very, very well now, meaning speed. It does things very fast. So if you need to

Governance And Agentic Reliability

SPEAKER_01 14:00

speed something up in your uh manual work processes, you might start looking at an AI type system. Communication, especially anything that's a repetitive routine or has to be communicated in different modalities, whether it's uh video, it's audio, it's text, communication is very, very good from a technical standpoint. The other thing is scale. How can you scale it in many different ways, right? So that's very good when it comes to execution if you've got bottlenecks and things of that nature. Well, there's other, there's two other things that are very important memory. So memorizing and having a memory of context uh within the project that you're working with, right? So you don't have, especially when you got these disconnected software systems, whatnot, does it remember uh all these different uh uh uh inputs and what's there? So memory is another big deal when it comes to technology if you need something memorized. And then the last one is patterns. And I love that patterns, it really understands patterns or it can be maybe able to discern patterns a lot quicker than the human eye. So if you put all those five things together of what it can do, then you start looking at your workflows that you're talking about. You know your workflows a lot better, and then you can say if this is a quiver, do I need more speed here? Do I need better communication right here? Can I scale at this point? Do I need things to be memorized? You know, a little bit, you know, everybody has their uh storage, really what we're talking about, right? And then can I recognize the patterns and the trends that are very you know important for decision support? So I can now, to your point, solve a business problem. I've got too much overhead and I don't have enough revenue. But if I have some of these five things operating in the system, maybe I can get to what I want to do. Does that summarize a little bit of what you're talking about?

SPEAKER_00 16:01

Yeah, definitely, definitely. So, for example, uh, like you know, there may be a certain process in a company where five people are doing the same repetitive process. They're doing something manually and it's a repetitive process. So that's a perfect candidate for automation. Like you said, AI is useful where because it remembers things, you know, it does things fast, and you know, it does where repetition is a problem, it really speeds up things. So definitely what you said aligns well with an agentic AI system.

unknown 16:40

Yes.

SPEAKER_01 16:41

So what let me ask you this. And you're so now you've been in technology a long time, and now you've seen AI really kind of change the platform, I call it enterprise uh um process applications that are now done a lot quicker, a lot better, where before it would have taken you probably a long time to get to that result. What's some of the biggest things that are kind of an aha moment for you now? Like, wow, I couldn't do this six months ago, but now I can do it now.

SPEAKER_00 17:10

You know, a lot of things in terms of marketing as well, you know, like earlier preparing content, right? Social media was a big thing back days and still is. So preparing content for social media used to be, you know, uh such a big problem. You you writing content or getting ideas, you know, different and researching different business trends and finding out ideas to talk about from there. So all of this has become so much easier, you know, and then following up with customers, like for example, with a system such as Go High Level or any any other competitive system for that matter, it's become so much easier to stay in touch with clients. You put in the details of the clients into the system, and it sends out automated newsletters to them, it sends out automatic updates to them. It's become so much easier to nurture clients, so much easier, and as a result, so much easier for them to you know understand your product, understand your services, and feel more connected to you. So all of that has become so much easier, which used to be difficult.

SPEAKER_01 18:36

You said it was expensive. Only the most uh most wealthiest companies could do something like that. Like it was so so far advanced uh that you couldn't afford to maintain a system like that. But now the common person with very low uh investment could have a system of agentic AI systems that can do all these things, can automate these tasks, can get you better productivity, can get you better decision making, can scale your workflows very efficiently, but your cost hasn't gone up, you know, but your productivity has gone up, and I would hope your revenues and profits would go up. Um is it that hard to implement these days? What are some of the things that people need to understand about that?

SPEAKER_00 19:27

You know, the most important thing to understand is, you know, not tools. It's not like using a certain set of tools, but rather identifying the problems that is that are holding you back. Some problems AI may be able to help, some AI may not be able to help, right? But understanding the problems and then having a clear vision, like what is the AI roadmap to solve it. That's the most important thing. It's not like, okay, I purchased this tool, I purchased that tool, and now I'm going to adapt those tools to my business. Yeah. It should not be that way. It should be the reverse. It should be first identifying the problems and then finding out what tools are appropriate to solve those problems. You know?

SPEAKER_01 20:20

No, 100%. That's why I said you have to first understand what the tools do and then look at your business process. Like, all right, where am I having the most friction at? You know, or what is where is the real bottleneck? Because if you've got great customer service, you don't necessarily have to put an AI automated voice system in. You might be, that might be fine. But then you might find out, man, processing these orders is becoming very tedious. And I got to take a lot of my most valuable resources, should be your human resource, and then put them back there to do all these repetitive, redundant, you know, uh uh manual tasks. Then you're like, wow, is that something I can automate? Right. I think that's very, very important. So I think do you help businesses to think through that? Because they may like, I've never really thought through that. I don't have my operating procedures like in front of me. I don't really know where all the bones are buried, let's say, in my business operations, do you help talk them through that?

SPEAKER_00 21:26

Yes, definitely. That's that's my key strength, you know. Like I said I mentioned earlier, too. I've been in business for so long and having tracted with so many founders, so many business owners, you know, I've I've worked through the challenges. And I can really, you know, once I speak to a founder, once I speak to a few people in an organization, I can understand where the challenges are and what could be solved there to make things and life easier for them. So I definitely work through the challenges.

SPEAKER_01 22:00

With the people I work with, I would definitely bring you back because that that's the big you before you now want the artist to understand it. Before you start spending tools or or I should say buying tools and spending monthly amount, um talk to an expert like Naveen who's gonna help you because if your whole goal is to like where can I automate? Because I'm hearing the hype, I understand where, hey, if I'm a small business, I might be a business of one person, a business of five, ten people, but I can 10x that

Build An AI Roadmap Before Tools

SPEAKER_01 22:30

utilizing AI agents and the JITEC AI. What does that look like? How can I do that to make my team more efficient? It's not about replacing human beings, but it's like, hey, if I don't need to hire another person, I can just AI enable the people I have to do things better to achieve the objective of the business. I think that's very, very important. So that's why you need an expert like Naveen. Like you said, you understand the language of the business and you understand the language of the technology. So then you can begin to help them through that journey. Now, help us understand the difference between a custom AI solution, that something that's built, built for that, specifically for that organization, and then an off-the-shelf type SaaSARFWA as a service type AI application.

SPEAKER_00 23:25

You know, for example, uh let's say uh I've been working with a client, you know, where they they receive certain medical reports and then they enter it into a platform, right, for certain uh monitoring and things. So a couple of years back, we were we were getting those reports, you know, and those reports, the data was being fed into the system manually, right? One at a time, you know. It had uh errors, it had chances of errors because it was manually. You had to look at the report and then enter it into the system. But now recently, what has happened is you just take that report, upload it to the system, and the system automatically detects the data and puts it at the right places where the step, the exact step that was being done manually a couple of months or years back, you know? So that's that's a custom solution, right? That's a custom solution because it's it's a very unique problem where you need to pick up certain data points from a PDF and populate a online platform. So that's a custom solution. Uh automated solution could be like an off-the-shell program, like let's say go high level. I'm talking about go high level again, right? Supposing you're running a campaign, you know, and uh let's say you're running a real estate campaign where you're a realtor and you have certain properties, and you know you want to generate more leads for that property, right? You put up a you put up a post on, let's say, Instagram and say, okay, people who are interested in this property, uh drop me a high. Right? The people they drop a message and automatically the go high level system takes over and it sends them a form, you know, form to fill up, right? No manual intervention here. The go high level system is automatically doing that. The person fills up the form, what type of uh what's his budget, whatever property he's looking for, and everything. And that form again populates the data into go high level, and then the go high level sends in more reports, more more about the property, more about the area in general, like you know, what's the crime rate there, how many schools are there, and different uh basically the entire whatever the uh profit person who's trying to buy the property needs to know about that plate. You know, it's a sort of nurturing system that so this is an off-the-shelf system. The entire thing is already built in, but you just need to configure it, you know.

SPEAKER_01 26:14

So yeah, it's important to understand. And then the difference between the two of owning something, maybe you want to make it into intellectual property, so it's your proprietized system as to something that uh you utilize, you know, like a Microsoft prop firm or something like that. And then um, a lot of people you'll find out that they might label some of these systems as as their as their own intellectual property as well. Talk to me more about your particular company. I know I think you're the CEO and owner of the company. Talk to me about the company and what it does.

SPEAKER_00 26:52

You know, uh, like I um yeah, so basically mine is an IT company. So we've been in business for almost 25 plus years now. Okay, and we've been dealing mainly with CRM systems, you know, a lot of market studies, data analytics, a lot of hand holding with clients to achieve their goals, right? For example, I work with a lot of coaches, and the coaches what they need to do is they run different programs, different training programs, right? So setting up the webinar systems for them, setting up the you know, the entire workflow for them, where you know, linking up the payment gateways, configuring different training products, so all of that kind of thing. Basically, and I have a team. Besides me, I have a team. So each of my team members, they are experts in their own areas, own systems, you know. And together as a team, we can we are able to provide any kind of uh IT solution that a company is facing challenges with. You know.

SPEAKER_01 28:12

I know you demonstrated a lot of you understand the implementation of what it takes to get there. You are uh affordable, uh, which I I I like. Uh you're one of the partners that we're working with now, uh, and I really appreciate that. And I know what another thing that you do, but I don't think a lot of people uh are aware of that, you review and audit AI solutions. Help us understand what that means when you're auditing an AI solution.

SPEAKER_00 28:44

Well, let's say uh these days, you know, back in the old days, uh SEO search engine optimization was a was a big thing, right? And now these days, with the advent of AI, with the advent of AI, it's more like uh, you know, uh AEO, that's artificial engine optimization. So yeah. So what happens is you need to train all these AI modules like Claude and Chat GPT. So people these days, they are not searching for uh they are not actually looking searching for uh information, they're looking for answers. They they ask, they ask like Chat GPT, okay? They ask, like, who are the top dealers in this product in my area? You know, they're they're looking for answers. So people, let's say a particular company, they need to be found on AI. They need to be found on AI. People need to find them on AI. So someone asks, like, okay, who's the best insurance advisor in my area? Okay, so a person who is AEO optimized, whose company is AU optimized, they'll appear in the chat results. You know, so those, yeah, but the results that that AI is giving out, you know, we need to audit whether they are the right. If someone says, okay, those are the top results, whether they are actually the top results or not, you know, so those kind of things, those kind of audits we do. And like earlier I mentioned like reports being uploaded

Custom Builds Versus Off The Shelf

SPEAKER_00 30:30

into a platform, and then the platform, whether it's picked up the data correctly and populated the right fields. So that's again AI auditing. AI has done its output, but then we need to audit whether it's correct or not.

SPEAKER_01 30:46

Excuse me and I want everybody to understand what he's saying. There's there's a big shift going on in the digital world, where before a lot of people they would optimize their websites and things like that for search engine optimization. Well, the behavior of people has changed. So you're not just going to Google typing in information and getting those 10 blue links that we no one would really go into the other pages if you weren't in the top 10, you're not going to probably be fine. Well, now people are going to their AI model and it's just asking a question and getting an answer. Well, how is now the uh the AI chat by getting that information? Where is it pulling it from? And where is it going to then display it, you know, in front of the user? That is gold right now, because you want that, you want to be known as the expert in the field, in the mind, let's say, of the AI engine. And that goes back to what you were saying earlier, understanding the difference between human language and then machine language. You have to be able to speak to the machine in a certain way that it says, yes, I want to get Grant Maga and five-star BDM into that answer for the AI chatbot to present to the user. Is that about right?

SPEAKER_00 32:07

Yeah, that's right. That's right. So that's called artificial engine optimization. And that's something all businesses have to look to in the coming days because everyone is now searching for answers. You know, they want answers, ready answers, rather than them looking for something and then deciding on an answer for themselves.

SPEAKER_01 32:31

Yeah, you're getting more precise information. These uh these AI chatbots are talking to you in a very authoritative voice, so it sounds very, very confident with the information that's that's coming back to you, but you have to have a certain influence uh there uh to get the right result that you're looking for. So understanding AI is only the beginning, the implementation creates real business impact. And I'm saying that because those are Naveen's words to me. Understanding AI is only the beginning, implementation creates real business impact, and this is why we need to work with organization that Naveen runs, and then why this is so important. So, as I leave you with this last question, and I want this to the uh, I want you to think about this. Why do you do this kind of work?

SPEAKER_00 33:32

Actually, it's uh it's been a passion for me because I love solving problems, I love you know, understanding challenges and solving problems. So that's why uh I did my computer science engineering in the first place. So since the time I graduated, that's been my passion, and that's what kept me going for these 25 years, you know. So I'm still as excited as I was on day one.

SPEAKER_01 34:04

I like that. I want to ask you this other because this is I've been in technology, what, 30 some odd years now? And you know, with AI, you know, coming on the scene in the last two to three years, I noticed, and maybe it's just a marketing thing or what, but all of a sudden, all these other companies are all AI experts. And I'm like, well, what were you doing before 2022 or 2023? Like, what was your expertise before that? Because if you didn't understand business process automation, or you didn't understand software code, you didn't understand all these other things that preceded what you would call AI algorithms, the way it's utilized today, do you think there's a lot of confusion in the marketplace when people are starting to look like, oh, well, this person must they they they say they know AI automations, but you gotta peel that back a little bit, don't you think?

SPEAKER_00 35:06

Yeah, that's true. So just to understand your question, what you're trying to say is what was happening prior to 2022, right?

SPEAKER_01 35:15

Yeah, yeah, man, like there's just so many companies out there, all of a sudden, you just they all are saying that they're all AI experts. Let's say it like that. And you're saying, well, but you you know, what were you doing before? You're you had 20 years' experience. You've seen this whole industry just in digital transformation taking place, and they had all kinds of names for it the digital front door,

AI Audits And The Rise Of AEO

SPEAKER_01 35:40

the the transformation project, you know, software-enabled applications. I mean, just and but is it more of a marketing or is it an expertise now that uh people are adopting, or maybe they've always said, I don't I don't know how you discern that.

SPEAKER_00 35:59

You know, uh, like what I've seen, and I was thinking about it a couple of days back as well. So what people really called AI these days has always been there in some form or the other, not as pronounced, but still there, you know. For example, uh, what is AI? It's intelligence, artificial intelligence, right? So, you know, running some sort of a workflow or thing, like earlier there used to be MailChamp and things. So some sort of, you know, uh intelligent data, you know, deciding on some intelligent data on those systems was already there, but it has evolved over a period of time, and that's what we are calling AI these days, you know. But portions of it were still there prior to 2022 as well.

SPEAKER_01 37:00

I hear you, and that that's what I wanted to understand that portion, because there's always been logic, you know, software is logic. So the if has always been there, that's what we call deterministic, but now you're giving it the flair of probabilistic. So probability plus C right.

SPEAKER_00 37:22

Yes. So earlier it used to be only that technical people used to understand, you know, the logic. Computer science, as you say, is all logic. Okay, if this happens, what happens next? Or if that happens, what happens next, right? It used to be in code form. Only technical people, people who know coding, they used to understand that. But these days, all this has been presented into a package such that even a layman who doesn't know coding or who doesn't know technology can understand it. So it's a matter of presentation.

SPEAKER_01 38:00

I like that. So it's commoditized or got down to a point where the uh, like you said, the common man can utilize as that's why I see the world now in this giant IT experiment that everybody's involved in. If you're using clawed and then you get clogged code, all of a sudden not everybody can create code at speed, and you're creating software applications at speed, but there's a lot more into it. And I guess that's where we're gonna help people understand this. It's not just now you have a coding platform, you might have a beta, you might have an application that could possibly produce a certain output. But there's a lot of other things that go in into that whole process that I don't think a lot of people, especially if they're not used to what the uh IT world actually looks like from a business standpoint, haven't even contemplated that. And this is one of the reasons why you need a person like yourself to guide them along that path.

SPEAKER_00 39:00

Yeah, definitely. You know, it's some things you understand in theory, right? You read through a thing and you understand, okay, and you feel, okay, that's a good thing. I need to implement it for my business, right? But it it gets overwhelming at times, where you know, you understand, need to understand a lot of technical jargon, and it gets overwhelming at times. So, and you'd rather spend that time on your business, you know. And so that's where people like me, consultants like me, can be useful, that we implement those processes and at the same time explain it to you like what's happening. So you just need to know the parts that are useful to you to run that application or to run it for your business. But you don't really have to go into the technicalities because you know that defeats the purpose of AI. AI is meant to save you time. But if you get into too much technicalities, that's going to take up a lot of your time.

SPEAKER_01 40:05

No, you said it right, exactly. You need to concentrate on the things that your business expertise, your domain expertise is in the business that you know, uh or the product or service that you you you um produce, right? So then you want just to AI enable it. Remember going back to those five things I talked about, the the speed, the communication, the um uh the actual scalability, the memory of processes, and then also the uh patterns there. So I believe that especially a five-star BDM, that you can

AI As An Enabler And Next Steps

SPEAKER_01 40:40

succeed with AI when you beyond get beyond the theory and you become part of the everyday operations. I think Naveen will help you understand that. So you can begin to see your operations grow. He's explaining it to you, but you don't have to get into the weeds of it. So again, taking away your time. One of the big things that people like about AI that saves them time, and it should also help them to grow, you know, monetarily and actually improve their intelligence along the way. Would you like to leave us with any last thoughts before we conclude?

SPEAKER_00 41:14

Yeah, the last thoughts would be, you know, you have to consider AI as an enabler, right? You know, enabler. So to it it is meant to save you time and improve your life, and you know, so that's how you should look at it. Not as a competitor that's you know, that's taking away people's jobs or anything like, but but rather as an enabler that's helping you become more efficient.

SPEAKER_01 41:44

I love that. I love that. And if people want to contact you, what's the best possible way?

SPEAKER_00 41:50

Uh, a best possible way is my email. Once we get connected on email, then I can just uh drop in my WhatsApp number or my SAT channel or whatever is convenient for them to communicate with me.

SPEAKER_01 42:06

Awesome. I can't wait to work with you, especially a lot of businesses that I work with, because they understand they have to identify what the opportunity will look like. We have to work with you on that. We can design the workflows, we can build the automations, we can create the assistance, implement the AI, optimize the solution that you will need and get the answers you want, and then remove those roadblocks. There's some of the things that that when working with Naveen and myself that we're able to do. So I want to thank you again for being on the show on the five starbdm.com platform. We call it Follow the Brand. So thank you so much for being a guest, Naveen. Appreciate you.

SPEAKER_00 42:45

Thank you so much. My pleasure to be on the show. You're welcome.