Strategic Foundations for Business Growth – Interview with Charly Leetham (Part 1)

Welcome to Building Better Developers, the Developer podcast, where we work on getting better step by step professionally and personally. Let's get started. Well, hello and welcome back. We are continuing our season. We're building better foundations. We are building better developers, the developer podcast. I am Rob Rudd, founder of Set Developing our podcast site and all that great stuff. Also the founder of RB Consulting, where we help you leverage technology to build a technology roadmap for success. Good thing, bad thing. Let's see a good thing. This is one of those fun kind of things. Good thing is, is that where I'm at, I've got a little townhouse and they've got a little HOA. And one of the things they do is they come by and do pressure washing regularly, which I guess like twice a year or something like that, which is awesome because it means I don't have to do it. The bad thing is, is that they were like, when I was trying to park, all the trucks happened to be right in front of my driveway. And so I had to like, you know, finagle my, I had to like Tetris my way into the driveway, making it a little bit more anxious of a parking job than I normally would have needed in the garage. But who's never anxious or at least I'm not anxious when he's introducing himself. Michael, go ahead and take over. Hey everyone. My name is Mike Mulash. I'm the co-founder of the development. I'm also the founder of Envision QA, where we help companies with custom built software and basically any type of software issues. We come in and we help you through testing and kind of walk through the process with you and make sure that everything's working great. Good thing, bad thing. Good. It's kind of mixed. It's that time of year again, where in Tennessee, the seasons can be anything from winter to summer in a given day. So when the weather is warm and nice, we're good. When it's not, it's really miserable. It's like, man, I wish I had my coat. And now like the sometimes bad host that I am, I have to make sure because I've just realized like I needed to know beforehand how to pronounce her name. So she may be correcting me. So she may be doing more than just a general introduction. We have with us, Charlie today. I'm hoping that's right. If not, correct me and go ahead and introduce yourself. Hey, guys, it's actually Charlie, but Charlie is the one that I get most. That's cool. But it is Charlie. It's short for Charlene. And it sort of comes back to the tomboy aspect of my youth. So there you go. So, hey, look, thanks so much for having me on today. I am really looking forward to this a little bit about myself and I'll try to keep it short. I have got nearly 40 odd years experience in the IT industry. It wasn't IT when I started. It became IT. And I have basically done anything from field service through to sales management, contract management, client management. And now I run my own business, which is why we're talking today, I think. Now, I don't know if there's anything else you guys want me to share about myself, whether that's just going to come out as we talk, because I think that's probably a good place to go. Well, I think let's start about what your business does, because as we all know, IT is a huge area. So if you can talk a little bit about your business and what your focus is, what your service or your products. So we help small businesses operate online, basically. I've changed my tagline so many times, I'm not quite sure what I'm using at the moment. But basically, it's tech when you just need it to work. I'm your tech, I'm your IT team. I can be your CTO. I like to sit basically between businesses and their tech providers, do that translation and give honest and sometimes brutal assessments as to where things need to be, need to go, what needs to be done. I find a lot of businesses, a lot of small business owners, particularly, they don't have the budget. To have their own IT person often and nothing against the brother-in-laws or the cousins or the aunts or the uncles who try to help out. But they get someone in from the family who says, yes, I've got a bit of knowledge and they really they have a bit of knowledge. It's just not the depth and it's not the generalities that they need to be able to help a small business. And small businesses go, I just can't get it to work and it's costing me so much money and it just hasn't worked for six months. And I can walk into that and go, OK, let's go through it. Let's talk about what you're doing. Let's talk about what you're trying to do. Forget what you're actually doing. Let's talk about what you're trying to do. Who are your providers and how can we make that work better for you? Or sometimes it's just the tech people aren't giving me answers. I can't make this work and I can step in between them, do that conversation and then talk back to them and say, hey, this is where we're at. This is what you need to do. Here's how we can fix this for you. I'm that person. I'm the tech wrangler. That's I have I've heard that tech wrangler wrangler term before, and that was one of them I really like. Also, it was in combination with handling technology sprawl, which is another one that I run into. Huge. Yeah, huge. I want to dive into this a bit because just now it's really like it's a little bit of a personal thing is, have you seen in as your career has gone on? Because I have I have and I love to hear somebody else. They're your thoughts on this is like what used to be the big ticket items and what IT used to look like. I feel like and to me it has gotten less so in recent years, particularly, especially go back maybe the last five or ten years that it has become definitely much more accessible. And more often than not, especially with small businesses, I'm finding I'm sort of having the education slash conversation with them about, you know, this thing that you think is is too much that you can't do. It's too expensive. It's too big actually is completely within your reach, especially with the rise of software as a service and and some of those kinds of things. And even the even the big, big boys like your your Salesforce, your NetSuite, your Oracle's and stuff like that, they have entry level stuff that is actually not only useful, but is also viable for even some of the smallest budgets. I totally am. And as you said that, I was just sort of thinking of the term commoditization has come into it well and truly. And I think that's actually part of the growth of any industry or in anything that we see. You start off with things that are really high end, they're expensive, that you don't know how to use them. I'm going to use the term that difficult to use. And then as the technology matures and as the industry matures, everything becomes more accessible, everything. The pricing comes down. More and more people can take it on. That is the evolution of an industry, of a business, of anything. If you look at it and things become more commoditized. Absolutely. I'm seeing it. Who would have thought just going to that, who would have thought that you could run your mail in a cloud and have it give you your word processing, your spreadsheeting, your databases, the analysis of all of that. And have that all at your fingertips. If you know how to use the system. 10 years ago, yeah, I was still setting up Outlook on people's computers and going, oh, you want to log in on your phone and on your computer and have your mail on both and be able to manage that and know that your VA has responded to it. Like 10 years ago, that, that was a major thing. We had a whole heap of processes around it. Now it's not. You delegate the account. It's all in one place. People can log in. They can see if a message has been read. It can have tags put on it. It can be moved into folders. Just that in itself is a major step forward. So yeah, I'm seeing it. Absolutely. Now, cool. I'm glad that I'm not the only one that's just like, feels like this has really gotten there. And so I think a good followup to that is so as these things become commoditized and like you said, there's like the, the work that you did 10 years ago, same thing. Like when you're doing desktop support and stuff like that, it's different. It is. There's a lot like, especially if you talk about like the data centers and installing servers and all the stuff that used to exist that really has sort of gone away because it's now just out there in the cloud and you just connect and you're ready to go. How do you see that and how you've had to evolve? And especially now, I think for the audience, a great one is like AI is now, you know, it's quote eliminating jobs. People say, and it is, it's going to, there's certain things that are going to be become commoditized as we've always seen. And so how do you, how do you make sure that you differentiate yourself? And while you're, while leveraging the technology changes and the advances also are able to put food on the table and do all the things you need to do to make yourself, you know, still valuable to your customers. Fascinating to me how many conversations end up going back to AI at the moment. It has really taken off. And if we were to look at it, I am certain we didn't see AI until the beginning of last year. I think that was when it actually hit the market and we saw, you know, chat GPT come out and people saying all of this stuff and people were becoming prompt engineers. And we're not seeing many of those anymore, but how do you, how do you leverage it and how do you keep yourself relevant? Learn how to use it. Don't, don't be afraid of it. Learn how to use it. Understand what its limitations are. I look, I've got a couple of episodes on my podcast about AI is not as good as you think it is. AI lies. Overly confident in the information it gives you. And when you start to dig into it, it actually makes up links. It actually makes up information and hands it to you and says, yes, this was the answer. And when you go and dig into it, when you sort of say, well, give me the references so I can go and check that. You know, that's, that's not what that's it. That link doesn't even exist. And I had a conversation with AI at one point, cause I was digging into some legislation about something here in Australia. And I'm like, well, can you give me the links that you've, you've given me this analysis on it gave me the links. I went to them. I said that that legislation doesn't exist or that link to that legislation is incorrect. Oh no, but if that legislation did exist, it would exist at that link. So that was a bit of a, that was a bit of a long way around to say, understand its limitations, understand what it can do and learn how to use it. Learn how to learn how to make yourself more productive using it. Bring it into what you're doing. And again, I'm going to go back to, you know, email around 10 years ago, we were using email, but email wasn't something that we used a lot of. And when email first started coming in, there's only a few of us using it. A few of us had understood that it was really cool to be able to send electronic messages and people were still relying on the postal service. Now the postal services are dying. Yes, we still have to use them, but the postal services are dying for your general domestic mail because everyone's moved to email. That is now just part of the life that we live. That's just part of how we operate. And AI, I think is going to fill that. Another probably unpopular view on this is I don't think AI is going to get a lot better than it already is for a very long time. It still works on large language models. It still requires a whole heap of data to pull into it, to be able to give you the information, to be able to do what you want it to do. Sure. Look, we're seeing generative AI take off. And I think that might be a little bit of a problem. The niche stuff we're going to see do really well. But the general stuff about we're just going to be able to take over your job, we're just going to be able to work out how your job works and come and do it for you. There's a lot that goes on in that wetware. There's an awful lot that goes on in that wetware. There's a lot of point decisions that we make at any particular point in the time, at any particular segment of time that we can't even do. We can't even define. We don't even know we're doing it. We just do it. Our assessment of the risk that we're at, the consequences of what we're going to do. Oh, if I do this now and this is this and this is... I don't think AI can do that. It might be able to in the long run, maybe. But that's going to require a lot of computing power, which is going to require a lot of energy. Let's not get into energy too much, but we don't have that amount of energy in the world to be able to power data centers to do that. There's all the things that sort of come to mind when you ask me about AI. If you want to know how I think you should be using it, make yourself more productive. Learn how you can use it to be more productive. Some examples I can give of that. I do my monthly reporting for my clients. I normally pull it down into a CSV, pull it up into Excel spreadsheet, run pivot tables and then generate the reports from those. The other day I said to AI, can you read CSVs? Yes, I can. So I dropped all my CSVs in. I said, I want reports that look like this. Here's my brand book. Here's the way I talk. I want these formatted reports. I said, here it is. Here is a doc X. You can just download that, put it out and send it as a PDF. That halved the time I spent. Now it took me a little while to get it to that because I had to do all of the work around. Here's the criteria. Here's how I want you to do it. I don't want it to look like that. I want you to look like this. But I've done that once. I don't have to do that again because now I've got the set of instructions that next time I come in to do it, I just paste those instructions in and say, go ahead and do it. Or I'm using Claude AI to do that. I've set up a project. Just pull that project in. Off I go. There's all my CSVs. Do your job. Give me what I need. Does that answer your question at least? Oh, yeah. Because I think it is. And that's it also sort of added to it is the you know, I think there's people I agree that there's I don't think it's where we're at right now. I think it's going to need a lot because it needs energy. It needs processing and it needs data. And I think it's one of those that now I think we've sort of you know, you've been here long enough as well. You probably remember the day where you'd like buy a laptop or back in the day when it was a desktop. And then 30 days later, it was already you know, out of it was like, oh, that's old hat. It was it was stuff was progressing very quickly and it sort of slowed down. And now I'm wondering if this is I think this may be the cusp of another one of those, you know, geometric growths where it's like, oh, now we need we need to be able to store huge amounts of data. And have bigger processors and all that kind of stuff. And then now it's going to, I think, push because that's what we are as humans is we're always finding new ways to solve some of those problems. So I think people are going to find ways to do the process with less power behind it and things like that. Or everybody's going to have a little portable nuclear thing like they did in the Back to the Future movies or something like that. But there's some way there's going to be somebody there's going to be some brilliant people and they're going to figure out a way to take us that next step. I do want to like just for the I think for our audience, I think it's a very important thing is it's like, don't be afraid of it. Go learn it. We all had to learn back in the day for some people don't even realize this. We had to learn how to Google stuff like what is a what is a search? I remember people like, how do you search for stuff? And then A.I. is really just to me, it's just a progression of the search engines. It's, you know, that just have that conversation. I really wasn't that far. That's why it sort of has been I feel it's been very natural for it to be incorporated into the search engines that are there because that's sort of where they were going. And at the end of the day, it's you know, A.I. is really not much different than expert systems. If you can give them like you do the steps, then it'll follow the steps. But watch out, because if you skip a step or if you're too vague in a step, you'll get some interesting stuff and you will get I will just add because I'm I know I'm on my soapbox a little bit. But I had an argument with Chachi BT one time about that where I said, I'm grabbing information and it sent me fake LinkedIn stuff. I'm like, I need to contact information for those people. And it sent me fake LinkedIn stuff. And I said, OK, well, don't unless it is a verified LinkedIn address, don't give it to me. Just make something up. And then it said, well, no, I gave you the right. And no, you gave me a fake. I looked at it. It's fake. So I finally was like, just don't give it to me. I'm going to go use another system and then connect into it. And I'll go figure it out. It's like, you know, it's like you're not good enough. So I'm just going to go back and do it myself. So you're and we're going to find that it's just like anything else is it's like it has its its limitations. And some of that is also the issue because how these languages were trained. There's a lot of archival sites that are out there that have old information and old pages. And that's what they're scraping. Because I found a couple where because I've had to go recover websites that people lose. And it's like because they got hacked. And you go to these sites to find that information is public without a lot of companies knowing that their information is stored in these archival sites. And so I scraping it and it's using that. Interestingly enough, though, you both kind of touched on it. But the way I look at AI is it's more of a rules engine. It's like the old dragon that we speaking. You have to train it or you have to basically give it the steps and the processes in order for it to really work or essentially give you your feedback. So you're essentially giving the inputs to the application, a rules engine, for when you prompt it to give you the feedback that you need. And that is the extent of what I see AI is today. Besides it just being glorified Google search, it essentially is good, especially with code, though, is good at finding because it scraped all the Microsoft, you know, get hubs and things where all the public repositories are. It is smart enough because they've had developers already go through and train AI for certain tasks that most general people use. But it's already been trained. It's already been given these rules to give you that feedback. And that's really all the modern AI is. It's a rules engine that can regurgitate what it has been told within its guidelines. If you go outside of those guidelines, you're going to get weird stuff and it's going to get all funky. I actually want to just sort of touch on that. And you it was a perfect segue. Actually, you've got to understand where the data that you're getting the information that it's regurgitating to you is coming from. And now I use it a lot to check code to say, OK, look, I'm getting this error message. We had to learn how to use Google. I love that. I actually love that because I used to just get that really long Microsoft 0x code that you get on the blue screens of death. And I would type like I'd write it out and then I'd type it in and say, what does this error message mean? That was Google. Well, now you can do that on AI, right? That's the sort of thing that you do. And when you're looking at code and you're looking at errors you're getting, you're like, OK, what does this error actually mean? Give me the guidelines as to where I should be looking for this problem. Where am I looking at this system over here? Am I looking at this system over here or is it something completely different? That information comes from the large language models. Now, when chat GPT and all of those or open AI came out, it was the Wild West. People didn't actually realize that open AI was using their data to train itself. And then when they started working out that their data was going into open AI and this was now being disseminated to just about everyone, people said, no, you can't use our data. And they started. Yeah. Now we've got silos of data. So the information that we're getting those answers from for me, it's things like Stack Overflow and GitHub and all of that. And I know that when I go to Stack Overflow and look at I fixed it this way, it's like, no, you didn't. No, you didn't. No, you didn't. And you like you find five or six threads with the one answer all the way through. And it's the wrong answer all the way through because one person has picked it up and copied it and someone else has picked it up and copied it and someone and chat GPT goes, well, that must be the right answer. But it's not. Yeah, Copilot is notorious for that since Microsoft owns Stack Overflow. They dump that entire code stack into Copilot. So if you want to, and they basically say that if you need to search for something on Stack Overflow, Microsoft even suggests go to Copilot. It's faster to go to Copilot to find information on Stack Overflow to go to Stack Overflow. And that right there tells you that there is two definitive problems. One, Stack Overflow has a lot of information, but apparently it's not easy to find. And two, search engines are very limited on how they can parse through that information. So AI is unfortunately the best way because it is again more that rules engine where it can quickly parse through a lot of data very quickly. But that's also like once you understand that that's actually a really good way of understanding how you can use AI to make yourself more productive. Because I use it to say, as I just said, give me the potentials on this and then I can use what's between my ears to go through and say, logically, that doesn't make sense. Well, let me just go and check that. No, that doesn't exist. OK, that one's wrong. Let me check this. No, those rules don't exist. That command that you're giving me is actually incorrect for whatever reason. It's actually incorrect. So you can start to then it's that process of elimination, isn't it? Yeah. Like where am I getting to? What? I'm probably closer to an answer here than I am here. So I'm going to go down this track for a little bit. That's how you use the AI that we have today. That's how I think you should be using the AI we have today. That's it. That says developers. I have seen authors who have gone to writing what they call AI books. Now, they're not getting the AI to write the book and just publish it. What they're doing is they're giving the AI a whole heap of instructions around what their setting is or what they want their setting to be. Now, tell me what my setting should be. Tell me what my world should look like. And they have this conversation with the AI that that flesh is that all out. Then they get a set of instructions. Great. Well, that's what my world looks like. Put that aside. This is the character I want to build. Tell me about this character. Oh, there's the rules for that. And then they get all these sets of rules and they plug it in and they say, now write the story that follows these notes. These are the notes I want to hear. They get that story and then they go through and edit it. So they're becoming editors as much as they're becoming writers. And I think that's we're seeing that in a lot of areas. And I know we've gone a little bit off on the in the. But I think that's what it is. And I think that's I think one of the skills that you need to develop if you haven't in using it is how to be a good editor as to how to do reviewing code or reviewing answers. And it is great for having conversations and getting you thinking outside the box a little bit because it'll get some weird stuff in there or something that's picked up somewhere. It's like, oh, some people do this. You're like, I've never thought of that. And then next thing you know, you can go down those rabbit holes and explore it yourself. But it always comes back to like, you've got to realize it's like if you don't put the guardrails on, then you're going to get some interesting stuff. If you can do the good job as a as a delegator, as a as an editor, is to really say, OK, I need you specifically like, OK, focus, say I this is what I need you to do. Give me this back. And then, like you said, you know, I think like the story is like you build on that so you can do it in these bite sized chunks and then get there. But you're going to have to you're still as a human being is going to have to drive that process. Yep. Yep. And look, again, you know, I have clients come to me and say, oh, we want to put a chat bot on our site so that people can ask it questions. OK. What information are you going to feed it? What do you mean information? Well, how is it going to be? The question the answers to the questions that people are going to ask you have a list of questions that people ask to begin with, because that's going to give us some idea of what data we need to pull into it to make this quick. We can do a quick and quick and dirty implementation, get it up and running, and then we can start feeding more and more into it. Or do you want to just to go out and get answers from your competitors and give your competitors answers to your clients and then have them when they come to you, you know, you know, you're going to have to have a chat bot on your site. To your clients and then have them when they come to you and say, but your product is as old. No, that's our competitor. We'll go and buy that from your competitor because that's what we want it to do. So that's the other way is think about what information you want to be feeding to your people or do you want to not feeding. But, yeah, you want to put into a system so that you can help your clients better. I think as a follow up to that, what's really good is sort of swinging back to the focus of when you sit down with your customers. One of the things when you're first talking about like, OK, you know, you you need somebody to help you with technology. And so now they're saying, yeah, we definitely need somebody to help us with technology. We need something that we can afford and things like that. I like start with the simplest stuff is like, what are some of the things that you run into when you're when they're setting it up? Where they're like, because this probably is stuff that I think is not as common now because people have done it more. But especially looking back the last five, ten years, I'm sure we're a lot of the companies are like, OK, I'm new. I need to set up a website. I need to be on the Web. What are some of the things that are that you know, I guess we'll start with the common mistakes, maybe some that people are like, oh, yeah, this is what you do. Well, what are some of the things you've run into where you're like, well, no, you need to either like the chat, but you need to think about it more or no. Here's a better way to approach that. That's such a broad, such a broad topic. I'm just going to come back to have a clear idea of what they want to actually achieve when people come to me and say, I want a website. The first thing I ask is, OK, what do you want it to do? Are we selling something? Are you training people? Is it a brochure where site? What is it you want it to do? Be really specific, because if you want an e-commerce site, you could be looking anywhere between five and ten years. Five and forty, fifty, sixty thousand dollars. It depends on what you want it to do. If you want a brochure where site, sure, you can go out and pay two hundred dollars for a brochure where site or you can pay two thousand dollars for a brochure where site. They're going to give you different things. They're going to do different things for you. So understand what that scope is. And that's a big that's that's still a mistake that I see people making is I want a website. My business coach told me I needed a website. I want a website. OK, so what is it you want it to do? Ask yourself that question. Be really, really specific. Think about the budget that you've got with that, too. Don't just go out to people and say, how much will it cost me to do this? Because there is such a range, such a such a differential differential there. And as I said, that two hundred to two thousand to four thousand dollars for a basic website that exists. That's just the way it is. The other thing I'm going to say is don't get tied down on a technology stack. Don't get tied down on a particular solution that that's yeah, that's a big one for me. I'll have someone come to me and say, I want to use X, Y, Z. Why? Well, I saw the ad and it looks really cool. And I actually had this conversation with someone one day. I want to put this thing in place. OK, so what is it? What is it you want this thing to do for you? What do you think it's going to do for you that you don't currently have in place or that you aren't currently doing? What's just going to make me money? That's what the ads telling me. OK, I now I know where we're at. So now we have to go back and do I always go back to let's do a needs analysis. I don't want to I don't want to come to you and say the answer is X. Now, what was the question? I want to know what it is you're trying to what is your objective? Let's take technology out of it. Let's take the way you might do things out of it and just say this is your input. This is your output. What is this output? What is it you want to do here? Because that will frame so much of what we put in the middle of it. Sometimes it's a really simple fix. Sometimes we've got to get a little bit more complex security. Security people still don't understand security people. Why do I need to factor authentication? Why do I have to change my passwords? Why can't I just write my passwords down and share them via email with my VA? That that one that one actually kind of terrifies me. The amount of times I've seen that done is like, oh dear, let's go change all our passwords now. It's not done just because you get the deliverable. It's not finished. It never finishes. Once you've got a deliverable, you will always have maintenance that you need to consider. So if I go back to websites, for example, it's not just that you put a website up and it will sit there and run. Yes, it will sit there and run, but it will require updates. You've got to make sure your software stays updated. You've got to make sure that your hosting provider is doing the right thing. Review who's got access to your admin consoles on a regular basis. Those sorts of things. It's all those basic things that we were dealing with them 40 years ago. We're still dealing with them today because human nature doesn't change. It's just the way we can do it. Years ago, my dad said to me, you know, to err as human, to really mess things up requires a computer. And if you want to look at how bad things can get, we've got so many computers now. One thing goes wrong and everything just sort of goes, oh. So there's some of the things that I can think I can talk about. I don't know if that's the answer you wanted, but it's those sorts of things that I still deal with. I was dealing with it 40 years ago. I still deal with it today or 20 years ago. I still deal with it today. And that is where we're going to pause this episode of our interview with Charlie. Yes, it's Charlie. I did not get it right the first time. Charlie Leatham, L-E-E-T-H-A-M. Got all the links in the show note. And as we come back in the next episode, she will share a little bit more of us. This funny enough was just one of those episodes that we mentioned AI too early. And we did go a little bit off the rails of our original conversation. But I really appreciate how she just dove in with us. I think there's some great content there. So definitely I hope you're taking notes and you're ready to go for the next one around. We will return with part two of our episodes of our interview with her. And we are not done with the season as well. We've got plenty more coming. So just hang out and take a deep breath before you dive into the next episode because it's time to take some notes again. As always, go out there and have yourself a great day, a great week. And we will talk to you next time. Thank you.