Detailed Notes
AI project failure is more common than most teams realize—and it’s usually not because of the technology.
In this episode of Building Better Developers, we break down why AI projects fail, what companies get wrong about adoption, and how to actually use AI in a way that delivers real value.
Most organizations jump straight to tools like AI or CRMs without defining their goals, processes, or requirements. That leads to wasted time, frustrated teams, and expensive failures.
We cover: - Why starting with tools leads to failure - What AI readiness really means - How AI exposes broken processes - Why small implementations work better - How to use requirements-driven development
If you're a developer, tech leader, or founder trying to figure out how AI fits into your workflow—this episode is for you.
Chapters 00:00 Introduction 02:00 The Problem with AI Adoption 05:00 Using AI as a Team Member 08:30 Why AI Projects Fail 12:00 AI Readiness Explained 16:00 Adoption Challenges 20:00 Large Project Risks 24:00 Start Small Approach 28:00 AI and Developer Skills 32:00 Requirements Matter 36:00 30-Day Challenge 40:00 Wrap Up
Call to Action
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Transcript Text
Understand? Good morning. >> Set up. >> How is that? How's that audio level? >> Now I can hear you. You see that was good. >> Yeah. >> Okay. Good. See, grab that. Grab that. That the right one. There's the right one. It's here. Bait. All right. We're hitting record. Should I go here? Um, I'm going to move my So, hello everybody. We are doing the standard studio arrangement here. Just a second while I get off camera and hopefully get in on camera where it's a little better lighting. Oh, that was looks much better now. So, I'm not looking down at everybody. >> Yeah, now you're better. There we go. Okay. So, >> yeah, that's a good point. Let me fix that. Get these straightened out a little bit. Bam. There. Yep. Pardon us while we just sort of like do our basic setup for you guys. There we go. How's that? >> Looks good. So, excellent. So, I don't feel like I'm getting I'm bright but not being blinded. Um, >> I still have to work on that. I don't have good lighting in this room, but this is what I got to work with today. >> Yeah, I get different. It's different based on my uh what time of the day obviously is I get a little bit different light depending on whether because I got a window right here. So, it very much can change what I end up with. Um, all right. Well, welcome everybody. Welcome back to our weekly challenge. Uh this week we're going to talk about Dustin do uh doice. I forget how to pronounce his last name, but that's okay. Dusty. Um this is really good conversation that we had. We're talking about really like right sizing how much you bite off uh when you're actually building out a project. So this is great. Um welcome to our weekly challenge for developer, building better developers. I am Rob Broadhead, one of the founders of developure. If you don't know already, check all of our back catalog. Um, also the founder of RB Consulting where we help you straighten out your uh we help you prepare for big projects and make sure that you are ready that you are properly going in with the eyes wide open uh as you jump into one of these big investments of an IT project. Uh good thing and bad thing. I'll talk a little bit about more of this after our introductions, but good thing is I've had some really fun uh AI chats this week. Uh numerous of them with actually with real people and uh a couple with AI itself. uh made some adjustments and things like that that were uh fun, but also I'm going to talk about them a little bit because in the conversations with chat uh with the chat group, the chat bots of varying sorts, I got some interesting feedback and thought it just some stuff that'd be cool to share. Uh bad thing is my sun just like moved. I just had clouds go over. So now my lighting is going to change a little bit as we go through this. But better yet, let's just pass this over to Michael while I try to find my glass of water. Hey everyone, my name is Michael Malash. I'm one of the co-founders of Building Better Developers, also known as Developer. I'm also the founder of Envision QA, where we create reliable, tailored software that helps you work smarter, scale faster, and stay in control. Good thing, bad thing. Uh good thing, uh like Rob, uh we've had some interesting conversations with some different people lately. Uh been getting out, networking a little bit. Um kind of meeting some new people and learning some cool new things about what's going on in the world. uh bad thing uh what's going on in the world. I'm trying to I'm on a news fast and uh basically social media fast trying to stay away from all the negativity going on in the world right now. Wow, that's quite the fast because the negativity is uh pretty much everywhere except for here. We are positivity all over the place. Let me tell you about my AI thing. This was actually really uh fun, amusing and and educational. uh one of the things that we have done at RB consulting and we have we have embraced AI substantially. So we are as an AI consultant I'm also using it uh drinking your own you know drinking from your own Kool-Aid as it were something like that scratching your own inch it uh built our old LM LLM we have the RB operating system which is basically our uh and our document library and things of that nature several other things. Uh so we we've actually nicknamed as we've mentioned before AI uh typically chat GPT we call him chip uh which him is I know misgendering possibly uh which is where this story goes uh but we also utilize uh we use Grock we use perplexity we use Gemini we use Microsofts a little bit uh and mostly just because that's just not in our primary tool set uh but we do have it available because these things are becoming sort of uh you know just you're going to see them everywhere. So in doing so actually we've had a lot of conversations uh we being primarily myself and Natalie our operations manager and talked about the team and development and how do we what are some ways that we may want to integrate or uh advertise essentially or tell people that like hey we use AI and it came to me at some point um that I was like well maybe because we've got a our team page maybe we should add AI as a team member. And so I thought about it as more it's it's a little bit of a gimmicky thing and stuff like that. But then I actually went down that rabbit hole with AI itself and said, well, how would this how should we do this? What would this look like? There's a lot of interesting stuff that came out of this. Uh the short answer is that we will have it's not out there as I speak, but probably by the time well by the time this shows up by the time you guys are watching this, we will have uh Chip will be one of our member of our staff. And I had ship build its own uh page and everything else. Uh because we have a staff page. We have and it it really was there's a conversation that went with that to make sure that we are clear that chip is a tool that we use. Chip is something that we're using. Uh we're not letting it run. I'm I'm not a fan of letting it just run wild and do a bunch of bots and do a bunch of stuff. It's it's really a virtual assistant for lack of a better term. It really is u just something that we use to be like hey I need you to create this report blah blah blah. It does help with coding and other things. As we got into this uh it did a really good job. Surprising to me it did a really good job of we'll call it humanizing uh the chip personality on that page. Now granted I gave it really good um templates. I said like here's what our others look like and it did a really good job about talking about like here's what chip does and here's some of the tasks it does because that it knows very well. Uh but then it also said like what chip does when chip is you know when chip's not working which was sort of funny because it's like well basically chip doesn't it addressed it in a serious way. It says well chip isn't but if chip isn't working then it's probably hiding behind a spreadsheet or something like that. So it gave it like a little bit of a human touch which I thought was uh was very interesting. More interesting was when I said give me an image because we have two images. We have a business and a casual image for all of our our team. And I said I need a business and a casual image. Now initially it didn't give me anything. And I said well okay I need a business and a casual image. And it gave me initially um I'm not going to show it here but I may throw that somewhere in the links at some point. It gave me this uh cartoonized very young female. Think of like manga type you know those kinds of of uh cartoons very much the big eyes and wide eyes all that kind of stuff. So it felt it was cartoonish but not overly cartoonish. Uh but the interesting thing was like and we actually had the conversation why did you choose female and because it was just a it was just one of those it's like we had never gendered it and so the whole thing was to put it to to AI to say like how do you see yourself and it addressed it and said well I really don't have a gender however when we asked why did you pick female it said that um AI is generally considered female because it's an assistant, because it helps you out, because it's it is trying to be helpful and a lot like it gave a nice list of these traits that essentially it said these are female traits. These are typically attributed to females. We also asked a question like how is that look if we have a female with a mostly male staff? Uh would it be better to be uh male or not? And it definitely addressed that and talked about balance and things like that. And so it's really interesting that we we went through this and it actually sees itself and it actually gave the example of Alexa, Siri, all of these and I hadn't thought about it, but all of those are are female voices. They're all, you know, you can change it to whatever you want, but essentially it's treated out of the box as a as a female. So, it's a really interesting thing about how we'll say AI sees itself. uh having watched Tron Aries just weeks ago, it actually is like an interesting little like, you know, that stuff's all in your head as well. But it's uh it's it's one of these things that I think it'll be I'm really interested as we go into this is how we recognize what AI can do for us and what it assumes because there's a lot of those things that goes back to what we're going to talk about today. what we talked about this week is that there are assumptions that go into some of these things and if those assumptions are wrong then the whole project's going to fail. Um wrapping that story up is we did go back and we said we would like to have something. It actually suggested what it called human adjacent uh picture and it turned out that actually the human adjacent is just a a generic looking mid probably 30 40ish probably more 40 to 50 year old female more or less. I mean it had a short haircut some stuff like that but you would think this would be like a woman of some sort or someone who identifies as a woman. Uh initially it was very young. uh looked a little more like 20some, early 30some. Um somebody I will not mention her name uh mentioned that like maybe we can make them a little older. And so we asked to make could you be a little older and it jumped probably 20 years in I would think in the image that it used. Uh we also asked could you be a little more robotic and it just slapped metal all over like a really bad setting of mine. So um it was a really fun This is one of those things. It's a it's a really fun um exercise, but it's also I think very educational as to what >> what we give AI and and how it thinks and what it saves and and what it doesn't. And I think if you haven't done if you haven't gone down this road a little bit and actually pursued AI beyond like beyond just like a stateful AI of some sort, not just like I ask it a question or I do a search and then I'm done, but actually utilizing the we'll call it the memory of it. Um you will find I think that there's a lot to a lot to learn there and there's a lot of apps you can build related to this. Um this is something that we will Michael and actually will be talking about that we may have something down the road that we we offer some of these kinds of things. Uh because it is it's something that's like it's here. There are practical uses to it today. You just have to be very careful as you as you get into it. That was a very long story. I know. So and you it looks like you may have even had some thoughts on that, Michael. So I'm going to throw that out to you so I can take a breath. So, it's funny because we talked to Dustin about, you know, software systems and software as a service, things that talking about like the business problem and it's like almost everything you went through through this process kind of touched on different points in the conversation we had with Dustin, you know, talking about adoption, you know, adopting is adoption is a real problem. you know, buying tools too early, using them, and you just walk through like, okay, we're kind of past the adoption phase of AI. It's like, we need to start embracing it. We need to start using it, you know, but the problem is companies don't know how to use it, right? They don't understand what this tool really can do for them. So, it's just funny and I love how you went through the process of, you know, starting with Chip. you know, you've been talking about chip for weeks and now you've like tried to humanize it, trying to incorporate into your business that I find that extremely funny. Uh, unfortunately, when when uh you did the whole manga thing, all I could think of was Twitch. Um, so for those of you that may not know what Twitch TV is, it's the video gaming streaming service where you can go watch people play video games. And a lot of people have funky uh animated uh icons that kind of simulate them. Uh, which I think we can even do in Zoom, like we can put on like little cow faces or whatever, and they'll kind of emulate us um our speech and our hands. It it's just I really find it interesting how you took an idea and kind of this problem you had and it's like well how do you embrace this? How do you how do you adopt it? How do you apply it? And it's just really cool because I've been dabbling with AI but from a different perspective. Uh I'm working on getting it more into the business side of things, but I've been working more on the automation side. Similarly, trying to take that code uh that test generator tool of mine and make it even more automated using AI to get AI to basically real time uh test software uh instead of just doing it uh you know build all this test. I kind of want a rules engine that would basically test my uh test for me. And basically, you don't have to keep the test sort anymore. You basically have these rules and then it just goes through and tests the site for you. So, it can kind of be um it can work with your system. It can grow with your system instead of being stagnant. So, if your code changes, it would be like, "Oh, hey, you've got new code changes. Let me look at our test and see if there's anything new that you haven't covered yet." and it looks to grow the the test that way. So, these are just kind of things that I've been working on similar to what you're doing. But I love the idea though of the virtual assistant. That's really cool. It's just funny though. It I keep going back to the conversation with us. It It's like a lot of the things he talked about for adoption, for growing your business, for you know, getting things uh going, this is where we need to begin. But the problem is a lot of businesses don't follow that. They go buy these tools. They go buy like earpiece, CRM or some AI package, hand it to their employees and say here go with no real guidance, no real instructions and they want to see return on the investment immediately. It's like, well, what are you doing with this? How are you doing it? Well, I don't know. you know, you've I've got like this pile of work to do with these do deadlines and now you're giving me something else to do on top of this and expect immediate return on investment. You're expecting me to immediately becoming more productive, more focused. And that's the opposite effect because when you introduce something new in an already stacked work space, you're going to see an increase in work and uh and a decrease in performance in the short term because you've now overwhelmed your staff. You've overwhelmed your employees and now you have to get to that point where they have to have time to play with the tools. They have to have time to figure out what how it works. But the problem is if you don't give them that time and you don't give them that direction, it's not going to work. You're going to fail or you're going to break things that are already broken. Like it this could extremely highlight bad processes, uh, procedures, and I'm going way off on a soap box here, so I'm going to pause and head this back to you for a minute. >> Um, it is easy to go there. And this is it actually does circles back to a lot of what we talked about with with Dusty this week is that uh and it's actually interesting. I had a a conversation on another podcast. Um and one of the things we talked I was actually asked what is because this is what RB consulting does. It's like what is AI readiness? If you're providing an AI readiness assessments, what is AI readiness? And it's interesting because I said well you know the funny thing is is like we're taking everything and just slapping the name AI on top of like what are you an architect? No. now I'm an AI architect, but it's like no, you're not. You're just an architect. What's an AI project manager? It's a project manager. Is we're all putting this cart before the horse. And I said, really, like AI readiness is actually just business readiness. It's the exact same stuff really that you would need to do that we talked about with Dustin. If you're going to do whether it's like a CRM or if you're going to go all the way to a full-blown ERP or something like that, you need your proverbial ducks in a row in order to do that and be successful. If you're just going to take a big honking tool and say we're going to use this and we're going to shove our business into it, and you don't know what your business is, if you don't have enough awareness of how your business works, it's going to fail. You're going to spend a lot of time on that. And that's what we're seeing now is Gartner's got stats out there that it's going to like I think there it changes a little bit each time I see it, but it's roughly about 75% or 70% of the AI projects this year will fail. And the average cost is going to be I think $7 million per failed project for you know mid to largeiz businesses. That is not a small amount of of change. And it goes back to and they even mentioned that companies aren't ready. they're diving into this. And so to sort of add a little caveat to my earlier story there is like we as technologists should be playing around with AI. We should be finding ways that it's and picking at it a little bit and saying like does it do this does it solve this problem or this really it's this style of problem. For example, um emails like how does it really help you write an email? How does it really write help you write a status report? How does it really help you track KPIs? Because part of it is going to be understanding where its limitations are, which you know, jumping to the end, it's it is a pattern recognizing engine. So, it has to have the patterns first. If you don't have the data, it's not going to it honestly, it will magically create data sometimes, but it's not going to create the right data. it's just going to fill in the blanks just like a, you know, a a very junior staff member that's like, "Oh, I've got to just put data here, so I'm just going to put whatever. It doesn't matter." AI will do that kind of stuff. Even if you tell it not to. So, we need to be, if you're on the cutting edge of this, uh, if your business wants to be, you need to actually be there and be able to say, "Well, these are some things it does and these are some things it doesn't." And in most of cases, the whole like jump to AI is no. If you aren't in a point where you can solidly automate your processes, which means if you can't solidly define and document your processes, AI is going to be a failure. And this goes back to what we talked about with Dusty is there's all these big projects and these big budgets and all this stuff comes in and sometimes it's a it's a rush to get something done. And it's like, okay, we've got 6 months to put Netswuite into all of our business because our current whatever the product is, our license is about to run out. And so, we want to make sure that we can get off of this license in time before we get whacked with whatever our our bills are. That is all well and good and very good reasons. You know, those are solid reasons to get this done. However, if you go off halfcocked, you're not gonna you're going to end up spending more time fixing stuff and chasing stuff down because now you've already started the process and now you're having to rewrite uh documentation and migrations and integrations and all of those shuns that we talk about in the many times. Then you have to rebuild those. You have to redo those. So you need to really sit down and and plot out more I think more importantly than it has been in the past. You really need to be specific on requirements and specific on your design because if you're going to utilize AI or utilizing a resource, a person if you want to call it that, that needs requires very detailed instructions. You can give a human something and say go do this. Um, I had something from the editorial thing. Why? This says, "My son doesn't like AI." How should I mention that? Should talk that story. >> I just also add in that some people don't like it. >> Ah, okay. >> And Tim went into details with you about why he does it. >> So, okay, good. Um, I had something my my editor just like threw some ideas at me to talk about here. So, uh, I will talk about this in just a second. Um, because I wanted to close in. Oh, the key is small. If we jump into something that's really big, then you have to have all of your ducks. You have to know all of the pieces of your business in order to do it. It is going to be much better. It is much easier for us to take this in a peacemeal approach. take something that is a small well-defined process and then let's make sure that we can detail it out, we can automate it and then we can maybe use AI to get there. And honestly, I think you're going to find that by the time you get to the using AI portion of it. A lot of times AI actually doesn't add anything to it or if it does, it's just very minute pieces because all it's doing is pattern recognition, which guess what? We've been writing code to do pattern recognition for decades. And so sometimes we can build a better, tighter solution because we can very tightly define what the pattern is, what we're looking for, and how to do it as opposed to having AI do it and its costs. Simple example of that would be if you have a CSV file that is just first name, last name, address, city, state, zip, you know what that pattern is. you know like if it's uh you know pipe separated or or comma delimited or whatever it is you know what that pattern is it is very easy to do that yes you could tell AI to do it and it could bring it all back but what was the cost for AI to do it and even the time to process for AI to do it versus if you just had a script that did it as well and I would be aiss if I didn't address my editor and say while I have very strong opinions towards this and we are obviously diving right into AI Um there's nothing wrong if you're waiting if you're sitting there and my son for example uh who is in it and has been doing it for several years now uh is not a fan of AI and he's brought up some really good places where it is not he is in a I don't want to name his product uh that he works on regularly but it is one of many products that is out there that is just saying we are going to add AI and that's really this goes to Michael's conversation what he said is like they're just trying to add AI. Well, it's one of these that I don't think anybody ever asked the people that used the tool where whether they needed AI, whether they wanted AI, or where it would even work. Because my son actually spent a a decent amount of time laying out a solid list of all the reasons AI is not needed. It's not going to help. And it really is going to probably cause more harm than good when all is said and done. We had a conversation that you guys will hear about as well with it's like this also poisons the the employment pool to some extent because now you're seeing junior developers their jobs are disappearing because people are saying well I can just use AI for that but that means then the m the mid-level developers don't have junior de developers to train so that they don't grow up to become mid-level developers and then eventually your whole you know your whole ecosystem is is poisoned and you end up in trouble. So, I will now get off of that side. Apologize to all you guys, but I'm sorry, but not sorry. But I think this is something it's worth uh spending a little time on a Friday talking about because it is a a very common theme. And obviously, Michael and I both have, you know, strong opinions and experiences with it. So, I will step down so you can step back up onto the the soap box. >> Yeah. So, it's interesting. Um Ian's point is actually very interesting because I've seen some applications just like he said that have introduced AI and I see no useful purpose for it at this time. It's just hey here's AI in your tool. It's like why is it just so we can uh say we're using AI? It it was interesting because I read an article or we were in a conversation with someone the other day, but one of the automation comp or auto uh companies, their chatbot is literally an API in the chat GPT. So, if you can figure out which one that is, you don't have to waste your tokens or your money. You literally just go to their chatbot and you have a full access to the professional level of chat GPT. It's like these are examples of why adapting too early, not understanding why you're you why you're getting this tool. Just hey, we're getting it can be a problem really. And Dustin kind of laid this out. It's like start with the goal. You know, we we mention this all the time. Understanding your why. Define your outcome. Start with the outcome. So one of the examples he gave was company needs a CRM. He's like that no what the company needs we want to increase customer retention. Two different things. One is the process one is a tool. Figure out your processes figure out your procedures. Write those down. AI might be able to help you with that. But you need to really think through what it is that you need. What your business needs. What are you trying to accomplish? Then walk backwards. It It's funny in software we call this test-driven development. We start with the end and work our way back to building the code. So you start from the solution and then um or you start with the end product and then you work your way back and write the code. So for instance, if you need a JSON parser, so you're going to end up with JSON. So you start with a little method that just spits out JSON and the test just reads the output. Okay, yes, I got JSON. And then you work your way back and you build the parser. You build all the pieces. But at the end, the test never changes. The test should always get this response. No matter what you do upstream, you should always end with this uh JSON. You should end with this process. Same thing. So you start with the goal. What is the end product? So your end product is never going to change. What you do upstream should fall in line to get that end product. If it doesn't, you're doing something wrong. So that's one of the things to figure out. Interestingly enough though, just going out and buying tools, throwing AI at doesn't mean you're going to get there. Those tools and things you buy may highlight that whoops, we don't have the policies and procedures or the process in place to get to this end product. So just throwing this tool in just highlights that we're way up here when we need to be down here. So take the time and revisit. This is not something that you do once and walk away. You need to constantly be reviewing your policies and procedures, your processes, and making sure that you're on track to hit your goal, that you're always focused on your goal. you're focused on what it is that your company wants to produce, what your solutions are, and that you're hitting that, that you're not going off on all these tangents or rabbit holes. Now, adoption can still be a problem. You know, time matters. Like Ian, he's waiting, so he is not one of those early adapters. Me and Rob, we're jumping in. You know, it to us it's a new toy, but we're taking this toy and we are figuring out how to turn this toy into a BMW. We're trying to take this toy car and turn it into a real car, making it productive, making it sleek, making it useful. However, if Ian waits too long and AI becomes too embedded in companies and companies really only want developers with AI skills, then he might miss the boat. He might lose jobs or be unable to get contracts because he is not versed enough in AI to keep up with the current status quo. Now is that right now? Probably not. But it could be coming. So these are just things just in any tech stack any development. Over the years we've seen this you know back in the 80s it was Cobalt for train 90s it became C uh C or uh C C++ Java and then over time we've seen Python and you know Groovy, Ruby, all these other Rust uh languages come up. Those that jumped on those early were kind of the forerunners, but they had a hard time finding jobs. They had a hard time figuring out what to do with these. That's kind of where we're at with AI right now. It's like it's everywhere. It's there. People can jump in. They can play with it. We're still figuring out what to do with it. But the problem is once people start really figuring out what to do with this, that is the time to start jumping on, start learning it. Get in there, figure it out. Because if you're not, you'll be on that late side and then you're going to be playing catch-up and it's going to take you a little bit longer to get there. And if AI goes the way everyone thinks it's going to go, if you're too late in adapting to AI, you may be too late to stay on this trajectory. You might be playing catch-up for a long time. A lot to unpack there. I've got a couple things to show out. First one, it's not Ian, so I don't I want to protect the innocent. Ian is not the son. is anti-AI. Um Ian has got a different approach. Uh Ian happens to work for me for those of you guys that don't know. And and our approach for the we'll call the the junior developers I guess uh which are actually all mid-level developers at this point is to figure out where to best utilize AI. They have found that is useful as a tool. Um they don't use it in the same way I do because they're using it as developers. I'm using it as running a business operating system as well. like I'm using using it fully as a a virtual assistant. Um, if you're just starting out, if you're a if you are a junior developer, I would just say you need to understand how to talk to AI to utilize it, but do not make it your primary way of getting your work done because you need to understand the underpinnings of what you're building. And if you're not doing that on a regular basis, then you're going to end up using AI is going to be your crutch instead of being a tool. and then you end up in a a very bad situation. And I think that's what we're running into with businesses is they're just like, "Okay, I'm gonna I've got something bad. I don't have a process that I I understand, so I'm going to slap AI on it and I'm going to fix it." Um, I would say, uh, Michael referred to it as being a new toy and stuff. It is, yes, you can see it that way, but I would say it is a toy like a double barrel shotgun is a toy is that you can actually do a lot of damage and you need to be very intentional with what you're doing. There are already patterns that are out there for uh AI use, for AI architecture. There are definitely patterns of solutions that AI work very well with that that are proven that are documented that have um background behind it. Uh if you want some fun research is look into uh Albania's AI cabinet member u called Dileia and what they've done uh with that. there are a lot of there's a lot of places to go to realize find out where AI uh mistakes have been made but also where it can be very valuable and where power very powerful. So um I would which sort of gets us into the challenge for the week. Um Michael also mentioned you know this is all test driven development sort of follows this but it's actually bottom line it's like at the end of the day it's requirements driven development. It's like you have requirements and this is why I'm I'm going to harp on that just a bit is you have requirements and then that leads to your solution. Now if you do it one of the ways you can do it is you do requirements and then you have tests that actually validate those requirements and so now you say what I build after that my test should all should always succeed because they have to output essentially what the requirements are expecting. This is what you should do is actually let's practice requirements. I think I want to go to a 30-day challenge instead of a 7-day challenge. And I'll see what your your thoughts are on this, Michael, because we have not talked about this before because we almost never do. Um, I think is take a 30-day challenge, build a tool, build an app, and start with scratching your own itch. So, maybe your problem is um like as a developer, maybe your problem is I want a I need to have a better way to find my old code. is find code that is like, you know, find that JavaScript function I wrote two years ago that I know is out there and I just don't want to rewrite it again. Basically, building your own, you know, AI code repository that you can go refer to. That could be an example. But the key to this is write out first before you write any code or before you have AI write any code or anything like that is write out your requirements. Get yourself and it doesn't have to be word and all that kind of stuff. use like markdown or something just very specific. It has to do this and this and this and this and this and go into all of those and ask yourself questions about all of that is like how can I provide more information about each of those requirements and then start having a conversation with I pick your tool and basically walk through it and say maybe give it from the start say I want to build this. Give it all your requirements and start with what do you need to know? What have I missed? What can I, you know, what am I needing to add that I have not? Where are the gaps? Uh, is this is this valuable? Maybe you ask, is this something that already exists somewhere? What would it look like in the real world? What would the market look like for this? How would I talk about it? What would I call it? You can have these conversations, but the goal is to move you from requirements in that day one to a working application by day 30. Now, doing so that means that you're going to like give yourself this sprint. You're going to have to put some milestones in there. So, maybe by the end of the first week, you need to have something that is a solid uh data model and flow diagram or something of those n of that nature. Since you can use AI to generate code, you may have like maybe it's a clickable demo of some sort by week two. Then maybe it's uh I need to know what I have to have all of the functions fleshed out. So, I need to know essentially this is the feature set that I'm going to be generating. By the end of week three, maybe you need to be like, "All right, I need to have something that I can now play with, that I can work on, that I can test. I need to have the uh the test, the unit test generated for it. I need to have documentation generated for it." Those kinds of thing, and then get yourself to day 30. What are your thoughts on that as a a bigger than normal challenge? I think that works because it kind of flows with the conversation we had with Dustin and it gets us back to focusing on the requirements, focusing on what it is that we're trying to accomplish. What is our goal? Because a lot of times that's where we fail. We think we have the requirements, but they're so loosey goosey that you don't have the requirements. What you have is you have an idea that it's not fully fleshed out. And when you just try to implement that idea, you end up with a whole bunch of if then, what ifs. And if you have what, well, what if this, what if this, then you're not there. You don't have the requirements. Requirements should be able to be read as a statement. If you read the statement and there is no if then or well, what about this? Then you have a good requirement. If you have a statement that prompts, well, okay, well, what about this? What about this? What then you don't have a requirement. you have a just an idea. So get your statements, get your requirements flushed out so that they are as definitive as possible and then work through build the software. I love it. Um, one little tidbit I kind of want to throw in, uh, when we were talking about, you know, train, you know, the mid-level developers training the, uh, lower level developers to be and the mid-level developers to become senior. I'm already seeing this trend in a negative way. I'm seeing mid-level developers or team leads say, "I'm too busy. Go talk to AI. Go have AI solve your problem. I don't have time to deal with you. I'm too busy working this problem." That is very dangerous. If you are not helping your team problem solve your problems and you're pushing them off on AI, one of two things is going to happen. they're going to leave. Or two, your software is going to become a dumpster fire if it's not already. Or three, you're never going to move up. You're going to be stuck putting out fires. You're going to be stuck in that busy mode. You're not going to learn the management skills necessary to become that senior, to continue analyzing, and continue to grow. >> I think it's a good parting thought there. uh a good way to grow, a good way to uh help your career is like yeah you can use uh and you can use AI to get used to like ordering something around and and sending commands and see how that works. But then you definitely are going to have a you need to have that personal uh experience because that is what's going to help you grow as a developer and uh not only the soft skills but also the technical skills because it is always better to help you uh solidify something in your head if you have to explain it to somebody else. And the more you have to explain it, the more that becomes just something that now it's just embedded in your psyche essentially. Hopefully our ugly faces are not embedded in your psyche or the back of your uh eyeballs. And we thank you so much for hanging out with us. Uh thank you for spending your time and uh just enjoy your challenge, enjoy your weekend. And as always, go out there and have yourself a great day, a great week, and we will talk to you next week.
Transcript Segments
Understand?
Good morning.
>> Set up.
>> How is that? How's that audio level?
>> Now I can hear you.
You see that was good.
>> Yeah.
>> Okay. Good.
See, grab that.
Grab that.
That the right one. There's the right
one. It's here.
Bait.
All right. We're hitting record. Should
I go here? Um, I'm going to move my So,
hello everybody. We are doing the
standard
studio arrangement here. Just a second
while I get off camera and hopefully get
in on camera where it's a little better
lighting.
Oh, that was looks much better now. So,
I'm not looking down at everybody.
>> Yeah, now you're better.
There we go.
Okay. So,
>> yeah, that's a good point. Let me fix
that.
Get these straightened out a little bit.
Bam.
There. Yep.
Pardon us while we just sort of like do
our basic setup for you guys.
There we go. How's that?
>> Looks good. So, excellent. So, I don't
feel like I'm getting I'm bright but not
being blinded. Um,
>> I still have to work on that. I don't
have good lighting in this room, but
this is what I got to work with today.
>> Yeah, I get different. It's different
based on my uh what time of the day
obviously is I get a little bit
different light depending on whether
because I got a window right here. So,
it very much can change what I end up
with. Um, all right. Well, welcome
everybody. Welcome back to our weekly
challenge. Uh this week we're going to
talk about Dustin do uh doice.
I forget how to pronounce his last name,
but that's okay. Dusty. Um this is
really good conversation that we had.
We're talking about really like right
sizing how much you bite off uh when
you're actually building out a project.
So this is great. Um welcome to our
weekly challenge for developer, building
better developers. I am Rob Broadhead,
one of the founders of developure. If
you don't know already, check all of our
back catalog. Um, also the founder of RB
Consulting where we help you straighten
out your uh we help you prepare for big
projects and make sure that you are
ready that you are properly going in
with the eyes wide open uh as you jump
into one of these big investments of an
IT project. Uh good thing and bad thing.
I'll talk a little bit about more of
this after our introductions, but good
thing is I've had some really fun uh AI
chats this week. Uh numerous of them
with actually with real people and uh a
couple with AI itself. uh made some
adjustments and things like that that
were uh fun, but also I'm going to talk
about them a little bit because in the
conversations with chat uh with the chat
group, the chat bots of varying sorts, I
got some interesting feedback and
thought it just some stuff that'd be
cool to share. Uh bad thing is
my sun just like moved. I just had
clouds go over. So now my lighting is
going to change a little bit as we go
through this. But better yet, let's just
pass this over to Michael while I try to
find my glass of water. Hey everyone, my
name is Michael Malash. I'm one of the
co-founders of Building Better
Developers, also known as Developer. I'm
also the founder of Envision QA, where
we create reliable, tailored software
that helps you work smarter, scale
faster, and stay in control. Good thing,
bad thing. Uh good thing, uh like Rob,
uh we've had some interesting
conversations with some different people
lately. Uh been getting out, networking
a little bit. Um kind of meeting some
new people and learning some cool new
things about what's going on in the
world. uh bad thing uh what's going on
in the world. I'm trying to I'm on a
news fast and uh basically social media
fast trying to stay away from all the
negativity going on in the world right
now.
Wow, that's quite the fast because the
negativity is uh pretty much everywhere
except for here. We are positivity all
over the place. Let me tell you about my
AI thing. This was actually really uh
fun, amusing and and educational. uh one
of the things that we have done at RB
consulting and we have we have embraced
AI substantially. So we are
as an AI consultant I'm also using it uh
drinking your own you know drinking from
your own Kool-Aid as it were something
like that scratching your own inch it uh
built our old LM LLM we have the RB
operating system which is basically our
uh and our document library and things
of that nature several other things. Uh
so we we've actually nicknamed as we've
mentioned before AI uh typically chat
GPT we call him chip uh which him is I
know misgendering possibly uh which is
where this story goes uh but we also
utilize uh we use Grock we use
perplexity we use Gemini
we use Microsofts a little bit uh and
mostly just because that's just not in
our primary tool set uh but we do have
it available because these things are
becoming sort of uh you know just you're
going to see them everywhere.
So in doing so actually we've had a lot
of conversations uh we being primarily
myself and Natalie our operations
manager and talked about the team and
development and how do we what are some
ways that we may want to integrate or
uh advertise essentially or tell people
that like hey we use AI and it came to
me at some point um that I was like well
maybe because we've got a our team page
maybe we should add AI as a team member.
And so I thought about it as more it's
it's a little bit of a gimmicky thing
and stuff like that. But then I actually
went down that rabbit hole with AI
itself and said, well, how would this
how should we do this? What would this
look like? There's a lot of interesting
stuff that came out of this. Uh the
short answer is that we will have it's
not out there as I speak, but probably
by the time well by the time this shows
up by the time you guys are watching
this, we will have uh Chip will be one
of our member of our staff. And I had
ship build its own uh page and
everything else. Uh because we have a
staff page. We have and it it really was
there's a conversation that went with
that to make sure that we are clear that
chip is a tool that we use. Chip is
something that we're using. Uh we're not
letting it run. I'm I'm not a fan of
letting it just run wild and do a bunch
of bots and do a bunch of stuff. It's
it's really a virtual assistant for lack
of a better term. It really is u just
something that we use to be like hey I
need you to create this report blah blah
blah. It does help with coding and other
things. As we got into this uh it did a
really good job. Surprising to me it did
a really good job of we'll call it
humanizing
uh the chip personality on that page.
Now granted I gave it really good um
templates. I said like here's what our
others look like and it did a really
good job about talking about like here's
what chip does and here's some of the
tasks it does because that it knows very
well. Uh but then it also said like what
chip does when chip is you know when
chip's not working which was sort of
funny because it's like well basically
chip doesn't it addressed it in a
serious way. It says well chip isn't but
if chip isn't working then it's probably
hiding behind a spreadsheet or something
like that. So it gave it like a little
bit of a human touch which I thought was
uh was very interesting. More
interesting was when I said give me an
image because
we have two images. We have a business
and a casual image for all of our our
team. And I said I need a business and a
casual image. Now initially it didn't
give me anything. And I said well okay I
need a business and a casual image. And
it gave me initially um I'm not going to
show it here but I may throw that
somewhere in the links at some point. It
gave me this uh cartoonized very young
female.
Think of like manga type you know those
kinds of of uh cartoons very much the
big eyes and wide eyes all that kind of
stuff. So it felt it was cartoonish but
not overly cartoonish.
Uh but the interesting thing was like
and we actually had the conversation why
did you choose female
and because it was just a it was just
one of those it's like we had never
gendered it and so the whole thing was
to put it to to AI to say like how do
you see yourself and it addressed it and
said well I really don't have a gender
however when we asked why did you pick
female it said that um AI is generally
considered female because it's an
assistant, because it helps you out,
because it's it is trying to be helpful
and a lot like it gave a nice list of
these traits that essentially it said
these are female traits. These are
typically attributed to females. We also
asked a question like how is that look
if we have a female with a mostly male
staff? Uh would it be better to be uh
male or not? And it definitely addressed
that and talked about balance and things
like that. And so it's really
interesting that we we went through this
and it actually sees itself and it
actually gave the example of Alexa,
Siri, all of these and I hadn't thought
about it, but all of those are are
female voices. They're all, you know,
you can change it to whatever you want,
but essentially it's treated out of the
box as a as a female. So, it's a really
interesting thing about how we'll say AI
sees itself. uh having watched Tron
Aries just weeks ago, it actually is
like an interesting little like, you
know, that stuff's all in your head as
well.
But it's uh it's it's one of these
things that I think
it'll be I'm really interested as we go
into this is how we recognize
what AI can do for us and what it
assumes because there's a lot of those
things that goes back to what we're
going to talk about today. what we
talked about this week is that there are
assumptions that go into some of these
things and if those assumptions are
wrong then the whole project's going to
fail. Um wrapping that story up is we
did go back and we said we would like to
have something. It actually suggested
what it called human adjacent uh picture
and it turned out that actually the
human adjacent is just a a generic
looking mid probably 30 40ish probably
more 40 to 50 year old female more or
less. I mean it had a short haircut some
stuff like that but you would think this
would be like a woman of some sort or
someone who identifies as a woman. Uh
initially it was very young. uh looked a
little more like 20some, early 30some.
Um somebody I will not mention her name
uh mentioned that like maybe we can make
them a little older. And so we asked to
make could you be a little older and it
jumped probably 20 years in I would
think in the image that it used. Uh we
also asked could you be a little more
robotic and it just slapped metal all
over like a really bad setting of mine.
So
um it was a really fun This is one of
those things. It's a it's a really fun
um exercise, but it's also I think very
educational as to what
>> what we give AI and and how it thinks
and what it saves and and what it
doesn't. And I think if you haven't done
if you haven't gone down this road a
little bit and actually pursued AI
beyond like beyond just like a stateful
AI of some sort, not just like I ask it
a question or I do a search and then I'm
done, but actually utilizing the we'll
call it the memory of it. Um you will
find I think that there's a lot to a lot
to learn there and there's a lot of apps
you can build related to this. Um this
is something that we will Michael and
actually will be talking about that we
may have something down the road that we
we offer some of these kinds of things.
Uh because it is it's something that's
like it's here. There are practical uses
to it today. You just have to be very
careful as you as you get into it. That
was a very long story. I know. So and
you it looks like you may have even had
some thoughts on that, Michael. So I'm
going to throw that out to you so I can
take a breath. So, it's funny because we
talked to Dustin about, you know,
software systems and software as a
service, things that talking about like
the business problem and it's like
almost everything you went through
through this process kind of touched on
different points in the conversation we
had with Dustin, you know, talking about
adoption, you know, adopting is adoption
is a real problem. you know, buying
tools too early, using them, and you
just walk through like, okay, we're kind
of past the adoption phase of AI. It's
like, we need to start embracing it. We
need to start using it, you know, but
the problem is companies don't know how
to use it, right? They don't understand
what this tool really can do for them.
So, it's just funny and I love how you
went through the process of, you know,
starting with Chip. you know, you've
been talking about chip for weeks and
now you've like tried to humanize it,
trying to incorporate into your business
that I find that extremely funny. Uh,
unfortunately,
when when uh you did the whole manga
thing, all I could think of was Twitch.
Um, so for those of you that may not
know what Twitch TV is, it's the video
gaming streaming service where you can
go watch people play video games. And a
lot of people have funky uh animated uh
icons that kind of simulate them. Uh,
which I think we can even do in Zoom,
like we can put on like little cow faces
or whatever, and they'll kind of emulate
us um our speech and our hands. It it's
just
I really find it interesting how you
took an idea and kind of this problem
you had and it's like well how do you
embrace this? How do you how do you
adopt it? How do you apply it? And
it's just really cool because I've been
dabbling with AI but from a different
perspective. Uh I'm working on getting
it more into the business side of
things, but I've been working more on
the automation side.
Similarly, trying to take that code uh
that test generator tool of mine and
make it even more automated using AI to
get AI to
basically real time uh test software uh
instead of just doing it uh you know
build all this test. I kind of want a
rules engine that would basically test
my uh test for me. And basically, you
don't have to keep the test sort
anymore. You basically have these rules
and then it just goes through and tests
the site for you. So, it can kind of be
um it can work with your system. It can
grow with your system instead of being
stagnant. So, if your code changes, it
would be like, "Oh, hey, you've got new
code changes. Let me look at our test
and see if there's anything new that you
haven't covered yet." and it looks to
grow the the test that way. So, these
are just kind of things that
I've been working on similar to what
you're doing. But I love the idea though
of the virtual assistant. That's really
cool. It's just funny though. It I keep
going back to the conversation with us.
It It's like a lot of the things
he talked about for adoption, for
growing your business, for you know,
getting things uh going,
this is where we need to begin. But the
problem is a lot of businesses don't
follow that. They go buy these tools.
They go buy like earpiece, CRM or some
AI package, hand it to their employees
and say here go with no real guidance,
no real instructions and
they want to see return on the
investment immediately. It's like, well,
what are you doing with this? How are
you doing it? Well, I don't know. you
know, you've I've got like this pile of
work to do with these do deadlines and
now you're giving me something else to
do on top of this and expect immediate
return on investment. You're expecting
me to immediately becoming more
productive, more focused. And that's the
opposite effect because when you
introduce something new in an already
stacked work space, you're going to see
an increase in work and uh and a
decrease in performance in the short
term because you've now overwhelmed your
staff. You've overwhelmed your employees
and now you have to get to that point
where they have to have time to play
with the tools. They have to have time
to figure out what how it works. But the
problem is if you don't give them that
time and you don't give them that
direction,
it's not going to work. You're going to
fail or you're going to break things
that are already broken. Like it this
could extremely highlight bad processes,
uh, procedures, and I'm going way off on
a soap box here, so I'm going to pause
and head this back to you for a minute.
>> Um, it is easy to go there. And this is
it actually does
circles back to a lot of what we talked
about with with Dusty this week is that
uh and it's actually interesting. I had
a a conversation on another podcast. Um
and one of the things we talked I was
actually asked what is because this is
what RB consulting does. It's like what
is AI readiness? If you're providing an
AI readiness assessments, what is AI
readiness? And it's interesting because
I said well you know the funny thing is
is like we're taking everything and just
slapping the name AI on top of like what
are you an architect? No. now I'm an AI
architect, but it's like no, you're not.
You're just an architect. What's an AI
project manager? It's a project manager.
Is we're all putting this cart before
the horse. And I said, really, like AI
readiness is actually just business
readiness. It's the exact same stuff
really that you would need to do that we
talked about with Dustin. If you're
going to do whether it's like a CRM or
if you're going to go all the way to a
full-blown ERP or something like that,
you need your proverbial ducks in a row
in order to do that and be successful.
If you're just going to take a big
honking tool and say we're going to use
this and we're going to shove our
business into it, and you don't know
what your business is, if you don't have
enough awareness of how your business
works, it's going to fail. You're going
to spend a lot of time on that. And
that's what we're seeing now is
Gartner's got stats out there that it's
going to like I think there it changes a
little bit each time I see it, but it's
roughly about 75% or 70% of the AI
projects this year will fail. And the
average cost is going to be I think $7
million per failed project for you know
mid to largeiz businesses. That is not a
small amount of of change. And it goes
back to and they even mentioned that
companies aren't ready. they're diving
into this. And so to sort of add a
little caveat to my earlier story there
is like we as technologists should be
playing around with AI. We should be
finding ways that it's and picking at it
a little bit and saying like does it do
this does it solve this problem or this
really it's this style of problem. For
example, um emails like how does it
really help you write an email? How does
it really write help you write a status
report? How does it really help you
track KPIs?
Because part of it is going to be
understanding where its limitations are,
which you know, jumping to the end, it's
it is a pattern recognizing engine. So,
it has to have the patterns first. If
you don't have the data, it's not going
to it honestly, it will magically create
data sometimes, but it's not going to
create the right data. it's just going
to fill in the blanks just like a, you
know, a a very junior staff member
that's like, "Oh, I've got to just put
data here, so I'm just going to put
whatever. It doesn't matter." AI will do
that kind of stuff. Even if you tell it
not to. So, we need to be, if you're on
the cutting edge of this, uh, if your
business wants to be, you need to
actually be there and be able to say,
"Well, these are some things it does and
these are some things it doesn't." And
in most of cases, the whole like jump to
AI is no. If you aren't in a point where
you can solidly automate your processes,
which means if you can't solidly define
and document your processes, AI is going
to be a failure. And this goes back to
what we talked about with Dusty is
there's all these big projects and these
big budgets and all this stuff comes in
and sometimes it's a it's a rush to get
something done. And it's like, okay,
we've got 6 months to put Netswuite into
all of our business because our current
whatever the product is, our license is
about to run out. And so, we want to
make sure that we can get off of this
license in time before we get whacked
with whatever our our bills are. That is
all well and good and very good reasons.
You know, those are solid reasons to get
this done. However, if you go off
halfcocked, you're not gonna you're
going to end up spending more time
fixing stuff and chasing stuff down
because now you've already started the
process and now you're having to rewrite
uh documentation and migrations and
integrations and all of those shuns that
we talk about in the many times. Then
you have to rebuild those. You have to
redo those. So you need to really sit
down and and plot out more I think more
importantly than it has been in the
past. You really need to be specific on
requirements and specific on your design
because if you're going to utilize AI or
utilizing a resource, a person if you
want to call it that, that needs
requires very detailed instructions. You
can give a human something and say go do
this. Um,
I had something from the editorial
thing. Why? This says, "My son doesn't
like AI." How should I mention that?
Should talk that story.
>> I just also add in that some people
don't like it.
>> Ah, okay.
>> And Tim went into details with you about
why he does it.
>> So,
okay, good. Um, I had something my my
editor just like threw some ideas at me
to talk about here. So, uh, I will talk
about this in just a second. Um, because
I wanted to close in. Oh,
the key is small. If we jump into
something that's really big, then you
have to have all of your ducks. You have
to know all of the pieces of your
business in order to do it. It is going
to be much better. It is much easier for
us to take this in a peacemeal approach.
take something that is a small
well-defined process
and then let's make sure that we can
detail it out, we can automate it and
then we can maybe use AI to get there.
And honestly, I think you're going to
find that by the time you get to the
using AI portion of it. A lot of times
AI actually doesn't add anything to it
or if it does, it's just very minute
pieces because all it's doing is pattern
recognition, which guess what? We've
been writing code to do pattern
recognition for decades. And so
sometimes we can build a better, tighter
solution because we can very tightly
define what the pattern is, what we're
looking for, and how to do it as opposed
to having AI do it and its costs. Simple
example of that would be if you have a
CSV file that is just first name, last
name, address, city, state, zip,
you know what that pattern is. you know
like if it's uh you know pipe separated
or or comma delimited or whatever it is
you know what that pattern is it is very
easy to do that yes you could tell AI to
do it and it could bring it all back but
what was the cost for AI to do it and
even the time to process for AI to do it
versus if you just had a script that did
it as well and I would be aiss if I
didn't address my editor and say while I
have very strong opinions towards this
and we are obviously diving right into
AI
Um there's nothing wrong if you're
waiting if you're sitting there and my
son for example uh who is in it and has
been doing it for several years now uh
is not a fan of AI and he's brought up
some really good places where it is not
he is in a I don't want to name his
product uh that he works on regularly
but it is one of many products that is
out there that is just saying we are
going to add AI and that's really this
goes to Michael's conversation what he
said is like they're just trying to add
AI. Well, it's one of these that I don't
think anybody ever asked the people that
used the tool where whether they needed
AI, whether they wanted AI, or where it
would even work. Because my son actually
spent a a decent amount of time laying
out a solid list of all the reasons AI
is not needed. It's not going to help.
And it really is going to probably cause
more harm than good when all is said and
done. We had a conversation that you
guys will hear about as well with it's
like this also poisons the the
employment pool to some extent because
now you're seeing junior developers
their jobs are disappearing because
people are saying well I can just use AI
for that but that means then the m the
mid-level developers don't have junior
de developers to train so that they
don't grow up to become mid-level
developers and then eventually your
whole you know your whole ecosystem is
is poisoned and you end up in trouble.
So, I will now get off of that side.
Apologize to all you guys, but I'm
sorry, but not sorry. But I think this
is something it's worth uh spending a
little time on a Friday talking about
because it is a a very common theme. And
obviously, Michael and I both have, you
know, strong opinions and experiences
with it. So, I will step down so you can
step back up onto the the soap box.
>> Yeah. So, it's interesting. Um Ian's
point is actually very interesting
because I've seen some
applications
just like he said that have introduced
AI and I see no useful purpose for it at
this time. It's just hey here's AI in
your tool. It's like why is it just so
we can uh say we're using AI?
It it was interesting because
I read an article or we were in a
conversation with someone the other day,
but one of the automation comp or auto
uh companies, their chatbot is literally
an API in the chat GPT. So, if you can
figure out which one that is, you don't
have to waste your tokens or your money.
You literally just go to their chatbot
and you have a full access to the
professional level of chat GPT. It's
like these are
examples of why
adapting too early, not understanding
why you're you why you're getting this
tool. Just hey, we're getting it can be
a problem
really. And Dustin kind of laid this
out. It's like start with the goal. You
know, we we mention this all the time.
Understanding your why. Define your
outcome. Start with the outcome. So one
of the examples he gave was company
needs a CRM. He's like that no what the
company needs we want to increase
customer retention. Two different
things. One is the process one is a
tool.
Figure out your processes figure out
your procedures.
Write those down. AI might be able to
help you with that. But you need to
really think through what it is that you
need. What your business needs. What are
you trying to accomplish? Then walk
backwards. It It's funny in software we
call this test-driven development. We
start with the end and work our way back
to building the code. So you start from
the solution and then um or you start
with the end product and then you work
your way back and write the code. So for
instance, if you need a JSON parser, so
you're going to end up with JSON. So you
start with a little method that just
spits out JSON and the test just reads
the output. Okay, yes, I got JSON. And
then you work your way back and you
build the parser. You build all the
pieces. But at the end, the test never
changes. The test should always get this
response. No matter what you do
upstream, you should always end with
this uh
JSON. You should end with this process.
Same thing. So you start with the goal.
What is the end product? So your end
product is never going to change. What
you do upstream should fall in line to
get that end product. If it doesn't,
you're doing something wrong. So that's
one of the things to figure out.
Interestingly enough though, just going
out and buying tools, throwing AI at
doesn't mean you're going to get there.
Those tools and things you buy may
highlight that whoops, we don't have the
policies and procedures or the process
in place to get to this end product. So
just throwing this tool in just
highlights that we're way up here when
we need to be down here. So
take the time and revisit. This is not
something that you do once and walk
away. You need to constantly be
reviewing your policies and procedures,
your processes, and making sure that
you're on track to hit your goal, that
you're always focused on your goal.
you're focused on what it is that your
company wants to produce, what your
solutions are, and that you're hitting
that, that you're not going off on all
these tangents or rabbit holes. Now,
adoption can still be a problem. You
know, time matters. Like Ian, he's
waiting, so he is not one of those early
adapters. Me and Rob,
we're jumping in. You know, it to us
it's a new toy, but we're taking this
toy and we are figuring out how to turn
this toy into a BMW. We're trying to
take this toy car and turn it into a
real car, making it productive, making
it sleek, making it useful.
However,
if Ian waits too long
and AI becomes too embedded in companies
and companies really only want
developers with AI skills,
then he might miss the boat. He might
lose jobs or be unable to get contracts
because he is not versed enough in AI to
keep up with the current status quo. Now
is that right now? Probably not. But it
could be coming. So these are just
things just in any tech stack any
development. Over the years we've seen
this you know back in the 80s it was
Cobalt for train 90s it became C uh C or
uh C C++ Java and then over time we've
seen Python and you know Groovy, Ruby,
all these other Rust uh languages come
up. Those that jumped on those early
were kind of the forerunners, but they
had a hard time finding jobs. They had a
hard time figuring out what to do with
these. That's kind of where we're at
with AI right now. It's like it's
everywhere. It's there. People can jump
in. They can play with it. We're still
figuring out what to do with it. But the
problem is once people start really
figuring out what to do with this, that
is the time to start jumping on, start
learning it. Get in there, figure it
out. Because if you're not, you'll be on
that late side and then you're going to
be playing catch-up and it's going to
take you a little bit longer to get
there. And if AI goes the way everyone
thinks it's going to go, if you're too
late in adapting to AI, you may be too
late to stay on this trajectory. You
might be playing catch-up for a long
time.
A lot to unpack there. I've got a couple
things to show out. First one, it's not
Ian, so I don't I want to protect the
innocent. Ian is not the son. is
anti-AI. Um Ian has got a different
approach. Uh Ian happens to work for me
for those of you guys that don't know.
And and our approach for the we'll call
the the junior developers I guess uh
which are actually all mid-level
developers at this point is to figure
out where to best utilize AI. They have
found that is useful as a tool. Um they
don't use it in the same way I do
because they're using it as developers.
I'm using it as running a business
operating system as well. like I'm using
using it fully as a a virtual assistant.
Um, if you're just starting out, if
you're a if you are a junior developer,
I would just say you need to understand
how to talk to AI to utilize it, but do
not make it your primary way of getting
your work done because you need to
understand the underpinnings of what
you're building. And if you're not doing
that on a regular basis, then you're
going to end up using AI is going to be
your crutch instead of being a tool. and
then you end up in a a very bad
situation. And I think that's what we're
running into with businesses is they're
just like, "Okay, I'm gonna I've got
something bad. I don't have a process
that I I understand, so I'm going to
slap AI on it and I'm going to fix it."
Um, I would say, uh, Michael referred to
it as being a new toy and stuff. It is,
yes, you can see it that way, but I
would say it is a toy like a double
barrel shotgun is a toy is that you can
actually do a lot of damage and you need
to be very intentional with what you're
doing. There are already patterns that
are out there for uh AI use, for AI
architecture. There are definitely
patterns of solutions that AI work very
well with that that are proven that are
documented that have um background
behind it. Uh if you want some fun
research is look into uh Albania's AI
cabinet member u called Dileia and what
they've done uh with that. there are a
lot of there's a lot of places to go to
realize find out where AI uh mistakes
have been made but also where it can be
very valuable and where power very
powerful. So um I would which sort of
gets us into the challenge for the week.
Um Michael also mentioned you know this
is all test driven development sort of
follows this but it's actually bottom
line it's like at the end of the day
it's requirements driven development.
It's like you have requirements and this
is why I'm I'm going to harp on that
just a bit is you have requirements
and then that leads to your solution.
Now if you do it one of the ways you can
do it is you do requirements and then
you have tests that actually validate
those requirements and so now you say
what I build after that my test should
all should always succeed because they
have to output essentially what the
requirements are expecting.
This is what you should do is actually
let's practice requirements. I think I
want to go to a 30-day challenge instead
of a 7-day challenge. And I'll see what
your your thoughts are on this, Michael,
because we have not talked about this
before because we almost never do. Um,
I think is take a 30-day challenge,
build a tool, build an app, and start
with scratching your own itch. So, maybe
your problem is um like as a developer,
maybe your problem is I want a I need to
have a better way to find my old code.
is find code that is like, you know,
find that JavaScript function I wrote
two years ago that I know is out there
and I just don't want to rewrite it
again. Basically, building your own, you
know, AI code repository that you can go
refer to. That could be an example. But
the key to this is write out first
before you write any code or before you
have AI write any code or anything like
that is write out your requirements. Get
yourself and it doesn't have to be word
and all that kind of stuff. use like
markdown or something just very
specific. It has to do this and this and
this and this and this and go into all
of those and ask yourself questions
about all of that is like how can I
provide more information about each of
those requirements and then
start having a conversation with I pick
your tool and basically walk through it
and say maybe give it from the start say
I want to build this. Give it all your
requirements and start with what do you
need to know? What have I missed? What
can I, you know, what am I
needing to add that I have not? Where
are the gaps? Uh, is this is this
valuable? Maybe you ask, is this
something that already exists somewhere?
What would it look like in the real
world? What would the market look like
for this? How would I talk about it?
What would I call it? You can have these
conversations, but the goal is to move
you from requirements in that day one to
a working application by day 30. Now,
doing so that means that you're going to
like give yourself this sprint. You're
going to have to put some milestones in
there. So, maybe by the end of the first
week, you need to have something that is
a solid uh data model and flow diagram
or something of those n of that nature.
Since you can use AI to generate code,
you may have like maybe it's a clickable
demo of some sort by week two. Then
maybe it's uh I need to know what I have
to have all of the functions fleshed
out. So, I need to know essentially this
is the feature set that I'm going to be
generating. By the end of week three,
maybe you need to be like, "All right, I
need to have something that I can now
play with, that I can work on, that I
can test. I need to have the uh the
test, the unit test generated for it. I
need to have documentation generated for
it." Those kinds of thing, and then get
yourself to day 30. What are your
thoughts on that as a a bigger than
normal challenge?
I think that works because it kind of
flows with the conversation we had with
Dustin and it gets us back to focusing
on the requirements, focusing on what it
is that we're trying to accomplish. What
is our goal? Because a lot of times
that's where we fail. We think we have
the requirements, but they're so loosey
goosey that you don't have the
requirements. What you have is you have
an idea that it's not fully fleshed out.
And when you just try to implement that
idea, you end up with a whole bunch of
if then, what ifs. And if you have what,
well, what if this, what if this, then
you're not there. You don't have the
requirements. Requirements should be
able to be read as a statement. If you
read the statement and there is no if
then or well, what about this? Then you
have a good requirement. If you have a
statement that prompts, well, okay,
well, what about this? What about this?
What then you don't have a requirement.
you have a just an idea. So get your
statements, get your requirements
flushed out so that they are as
definitive as possible and then work
through build the software. I love it.
Um,
one little tidbit I kind of want to
throw in, uh, when we were talking
about, you know, train, you know, the
mid-level developers training the, uh,
lower level developers to be and the
mid-level developers to become senior.
I'm already seeing this trend in a
negative way. I'm seeing mid-level
developers or team leads say, "I'm too
busy. Go talk to AI. Go have AI solve
your problem. I don't have time to deal
with you. I'm too busy working this
problem." That is very dangerous. If you
are not helping your team problem solve
your problems and you're pushing them
off on AI,
one of two things is going to happen.
they're going to leave.
Or two, your software is going to become
a dumpster fire if it's not already. Or
three, you're never going to move up.
You're going to be stuck putting out
fires. You're going to be stuck in that
busy mode. You're not going to learn the
management skills necessary to become
that senior, to continue analyzing, and
continue to grow.
>> I think it's a good parting thought
there. uh a good way to grow, a good way
to uh help your career is like yeah you
can use uh and you can use AI to get
used to like ordering something around
and and sending commands and see how
that works. But then you definitely are
going to have a you need to have that
personal uh experience because that is
what's going to help you grow as a
developer and uh not only the soft
skills but also the technical skills
because it is always better to help you
uh solidify something in your head if
you have to explain it to somebody else.
And the more you have to explain it, the
more that becomes just something that
now it's just embedded in your psyche
essentially.
Hopefully our ugly faces are not
embedded in your psyche or the back of
your uh eyeballs. And we thank you so
much for hanging out with us. Uh thank
you for spending your time and uh just
enjoy your challenge, enjoy your
weekend. And as always, go out there and
have yourself a great day, a great week,
and we will talk to you next week.