Most AI videos tell you to use more tools. I've made a few myself. This one This one says the opposite. If you're new here, I'm Dylan. I run an AI consultancy. I coach people on AI workflows every single week. And almost every week in coaching, someone's juggling probably four AI tools at once. The people getting real work done are the ones using fewer AI tools, not more. I'll show you the three-step rule I use to pick an AI fast, then I'll show you the only times it's worth switching. So, let's get into it. Now, these are just four of the tools that I often see people trying to balance at any given time. And it's not just the tools themselves, but it's also the bills that come with it, the projects associated with each tool, the memories inside of each tool that have been remembered on your behalf, different configurations you've set up, all types of things. So, the complexity compounds, especially when you're uncertain as to which tool is suitable for which task. So, instead of being overwhelmed by all different tools and features you can choose from, especially if you're a beginner and/or you're susceptible to AI FOMO, the fear of missing out associated to all the new models and features and things like that, you need to take a step back and realize that it's okay just to choose one model, choose the one that's closest to you right now. And you can choose one of three. I would say these are the three big players that you can choose from. And I've specifically listed these because they tend to be the ones that have most of the features that are necessary for many tasks that people are trying to use inside of their work, as well as have a bright future ahead of them because of all the funding they have and the ability to build out new models and new features. And when I say closest, either it's the model that's open in your tab right now, or it's the model you've been using most frequently in the last like 2 weeks. Just choose choose that model and focus on that tool going forward, at least for the next 3 to 6 months. And the reason I'm so adamant about this is when beginners or people that have AI FOMO, when they start out with a specific problem, they ask themselves this question, the wrong question, which is which AI is best for this task. That's the wrong question, especially for beginners. The right question is what problem I'm trying to solve today? That's all that matters, the problem itself, not the tool. Because most of these tools, especially the big three that I just shared, can solve many of the problems that you care about. So, let's focus on the right question not the wrong one. Quick pause and a regular programming. This video is brought to you by me, as always. Two quick things. First off, below is a 30-day AI Insight series, completely free. You'll get 30 insights in your inbox of how you can apply AI to your business and your work. The second thing is if you'd like to work with me, below are a series of offerings to see if there's a good fit for the two of us. Now, let's get back to the video. And when you get started, there's three steps you're going to take. So, the first step today is grabbing the closest model to you, like I mentioned previously. So, either it's the model that's open in your tab right now, or the one that you've been actively using in the last 2 weeks. Don't get caught up in trying to figure out which model is best, just choose the closest one to you. After you've done this, you're then going to go to the next step, which is giving your full effort to the given problem that you've chosen with that AI. And when I say full effort, I'm specifically talking about the importance of ensuring that you give high-quality context to the AI for that problem, as well as high-quality instructions/prompts to increase the likelihood of the AI achieving that task. So, this step really comes down to making sure you're using the tools effectively and correctly in a high-quality way. So, once you've tried hard, you likely would have solved the problem. If you solve the problem, ship it and move on. And this is where people get hung up. Sometimes they solve a problem partially or fully with an AI, and they ask themselves, "Well, I wonder if there's another AI that can solve this even more effectively." Again, this is a trap. So, instead of falling into that trap, if the AI has solved the problem that meets your criteria, which ideally are binary, so it's yes, no, pass, fail, one, zero, if it passed that cleanly, then you move on to the next problem, because you want to be productive, not distracted by all these AI tools and features. And with that said, there are some caveats here. So, I do recommend exploring new features, new tools, and models, but doing it a very small percentage of your time. So, there's exploring and shipping. The exploring phase should be like 2%. So, that's going to be maybe 30 to 45 minutes on a Sunday, where you'll explore new models, new features, new tools. Bu