kill ai distraction.. to get back to work

You need to kill the AI distraction so you can get back to work. So at the moment, every single day there's some new AI news, a new AI tool, something going on, and the promise that it's going to disrupt everything. And the truth is chasing all of these demos and every new product launch is absolutely not going to make you rich. We live in a world where the YouTube algorithm is currently strapped to this model. If you're following people like this, No offense, Alex, but it's, it's game over. Um, every day it's something that's going to kill something else. And then the new king in town, this is, this is all just clickbait nonsense. Okay. AI is a tool, right? And you're picking the tools that you want to have in your toolkit. If you hired a builder and every single week he was coming up saying, oh, forget the hammer, we've got a new tool that's going to totally revolutionize it. You may as well be watching like infomercials. If you remember those late night infomercials from the '90s, it would be like a ladder that has 72 different combinations. That's, that's what this AI is. This is SMOB. Okay. But AI is a, is a valuable tool. You have to use it, but you need to be this. Okay. You need to pick your AI tools wisely. Um, you need to still have your skill and master your craft. You don't want to be the person that's all the gear, no idea type. Okay. This is about, you know, removing the distraction, getting back to clarity, getting grounded, right? Not ignoring AI. This is going to be a filter that will absolutely let you evaluate all of the new AI tools. So you actually stay on top of it more than other people. But in this video, I'm going to be talking about and giving you a way to think about how to assess new AI tools, right? So this is a challenge. Half of these, more than half, like 99% of these demos are lying to you. So forget half, like 99% are total bullshit. Okay. Think about the Boston Dynamics dog. Look at this. My entire life, I was born in '94, right? I've had these videos shown to us of this dog, this thing is going to totally change everything in the next 5 to 10 years, right? This Petsman thing was going to be the police force in 3, 4 years' time, right? The Wildcat is going to change the battlefield. Spot Mini, all of this stuff is junk. Okay. So if you look into the, if you look into the company Boston Dynamics, it's been bought and sold like a dozen times. It's, it's basically a glorified tech demo where you can see these things climb a set of stairs. Um, but it doesn't actually serve any practical purpose in the real world. So they get them out into the real world, put it in a forest, and it can make it like 2 steps. Okay. The reason I'm talking about this is because you should be having the same level of skepticism when it comes to AI tools, right? Don't just take it at face value. Don't take it based on the, the 2-minute video or the person saying like, this made me $100,000. This will go on for 20 years. You know, if you think about AI growth or Boston Dynamics growth, we might actually be at the top. There may not be another run-up from here. Right. It may just flatline and all of the technology advancement has happened. Okay. And if that's the case, you should still absolutely use it because it's, it's advanced a lot and it's incredibly useful, but don't, don't just bank on the fact that it's going to go like this again, because we don't know that yet. The Boston Dynamics, if this was 2009, this is 2026. And even that might be an exaggeration of how much it's developed, right? The demos from 2009 look just as good as the 2026 ones, basically the same thing. So you need a filter, not more tools. Okay. And I highly recommend everyone check this video out. Just type in Elon algorithm on YouTube. Um, he has a filter for work, right? And We've got a filter for evaluating, evaluating AI tools that I'm going to show you in a second. But his, his method that he follows is he questions the requirement. So why is he doing something altogether? Um, let's say someone comes to him and says, we need to increase the size of the battery 2 times. He might say, why do we need to increase the size of the battery? Could we not just make the car more efficient? Right? So question why we actually need that thing. Delete it. Delete the requirement entirely, right? So potentially the, the reason for the battery is, or increasing the battery 2 times is so that it can charge faster. Obviously that's not a very good example, but if you imagine that's the end result, he might say, well, why do we need it to charge faster, for instance? So think of a way that you can just delete the entire chunk of the process. And you have to do this in order. You can't skip through steps. So question, why do we even need this? Question, can we delete it altogether? If you can't delete it, then you need to simplify it. So remove the number of moving parts. So if you think of simplicity as, let's say there's two points, that's the line of communication. If we add a third part, there's more communication, right? If we add another bit, Look how much more complex it becomes, right? Right? Because you've gone from having one way or two way back and forth. Now you've got double each side and it goes further and further. The more pieces we add. Now you're going to have something like this going on. You get the point, right? So simplicity is removing some of these parts if you can, or making it just straight line communication where it goes back and forth. Okay. So then after you've simplified it, you need to accelerate the timeline. So basically, how, if it's going to take us 12 weeks to implement this, how can we do it in 2 weeks? Speed is incredibly important. And then only finally does he automate it. And this part's really key because you don't want to spend time and investment automating something that you should have deleted or not even had in the first place. Right? So we want to apply the same thought process to the tools. So this is the AI filter. Okay. Let me walk you through this. 5 steps, super simple. The first thing that is really key is you want to glance at the tool. Okay, because you don't want to lose a competitive advantage that could genuinely help you. And so what glance means is you might watch a 2-minute video, 5-minute video. You need to understand what the tool does conceptually. So a good way to think about this is the same way you understand the difference between YouTube, Facebook, Instagram, Twitter, right? Those 4 platforms. You're not an expert in how the Twitter algorithm runs. Okay. You don't, you don't, you haven't tried to become an Instagram influencer, but you know the difference between the 4, right? That's what you need to apply to AI. You should know Fireflies is for transcription. You should know that's possible. You should know a elevator pitch style summary of what these tools can actually do. That way you're not missing out on things that could be truly impactful. The next step is the pain. So once you've figured out what it does, you need to ask, where in my business or my life does this specifically help? So if you can't articulate what exact problem it fixes, don't, don't bother with it. Like move on to the next thing. Forget about it. Just keep doing what you're doing. This is the only way to learn. Everything that you, you're picking up in AI should have an immediate solve or solution for a bottleneck within your business, right? So once you've determined it has got a use case for solving a pain point, then you want to look at the forecast and basically ask yourself, is another tool going to come along and replace this one in a few months? Will this feature get absorbed into something I already use? Will it get faster and cheaper soon? So kind of like Elon questioning the requirement. Does this actually have legs, right? If you determine that it's not likely to get replaced and it, you know, it is a serious pain point, the next step is going to be auditing. And that's basically asking, how long is this going to take to implement this AI tool? And how much time will it buy back? Because if you're implementing something that takes 10 hours and it only solves a 2-minute task, don't bother. Like, you're adding complexity because nothing is truly ever automated. Everyone, like, Zapier workflows break and stop all the time, Make.com's a nightmare. Like, nothing is truly ever automated. An account disconnects, something times out, right? So you're adding overhead. And then finally, once you've gone through all of these steps, at that point you solve the pain point or the bottleneck. That's what you learn the tool for. So you're not just watching AI news to stay in the loop, right? You are attacking that problem with the specific AI tool and solution that you've decided on. I never just sit randomly watching YouTube videos on AI, right? The only way I've ever learned anything is I have something that I want to build or a problem I want to solve, and then I'm spamming different YouTube videos that have the solution. I just see YouTube as a library or resource of answers. Same thing if you're in a private community, you should only be asking questions about the specific pain point or bottleneck that you're dealing with now, not stuff in the future. Don't theorize, don't have hypotheticals, waste of time. Cool. So this is the filter. This is the cheat sheet. Lance, can you understand it? Name the exact problem you're going to solve. Ask, will it still exist in 6 months' time? Does the math work? The time invested to set it up versus the time replaced. Or saved, and then solve, solve the problem, like jump in and actually solve your problem. Okay. This is the filter. Grab a screenshot of this and start running every new tool through this assessment.