I've Tested 4 AI Platforms in 8 Months. Here's What I Learned.

Before we get into this episode, I just want to let you know the book Fix This Next for Real Estate Investors is out. It's available anywhere books are sold. I hope that you all grab a copy because it is the book that will help you identify the next thing that you and your team need to focus on in your real estate investing business to scale it to where you want to be. Pick it up anywhere. Fix This Next for Real Estate Investors. In my world, 2026 is the year of AI agents. Think about it. We started off January, or at least I did. I started off January implementing OpenClaw. It was this AI agent that ran on its own machine and it transformed the way that I worked. Months later, we started talking about this next AI agent called Hermes Agent. And Hermes is really, really, really good. In fact, in my opinion, it was better than OpenClaw. So I began moving all my files over to Hermes. And then just in the last month, we've had two big developments with AI agents. One is Buzz. And the thing about Buzz is that it allows you to bring in your humans. And the humans get to work with AI agents that have access to all of the files that we've been working on all year long. And then just in the last two weeks, we now have GrokBot, which, by the way, GrokBot is really, really, really good. So throughout the first, what, eight months of the year, I've already tested four of these platforms and you probably have two. Or maybe you're just still on OpenClaw and that's OK. But the thing about this particular development is that what we're seeing is we're seeing the AI agents come faster and faster and faster. All these new platforms are bringing new challenges. And at the end of the day, it can create friction within your business. Because if you're trying to build your business processes around these AI agents and then tomorrow a new framework appears, GrokBot 3 appears or whatever it is, the challenge becomes is that we keep feeling like we are going to have to reset everything up. And this, to me, is the risk with GrokBot because, see, GrokBot is really, really easy. It's really, really good. And if you haven't done anything with AI agents, GrokBot might be the place to start because it's essentially you just download some software and you're off and going. But beyond that, what we really need to do, though, is we really need to begin to think about our documentation. I have a book that's coming out next year. It's going to the editing process right now. And it's called Think First, Then Automate. Because what happens is when we get these tools, we want to go out there and we want to just jump in and start automating stuff. We want to just jump in and start feeding all of this stuff in. And what I want everybody to do, the world, what I want the world to do is I want them to slow down, slow down a little bit and think about the thinking behind it. And really document the thinking and think about the files in which your AI agents are using. Because at the end of the day, what made it super simple for me to move from basically agent framework to the next framework was the fact that I had all of these Markdown files, my company systems and processes and the stuff that we had worked on in the past, all within Markdown files sitting in Dropbox. So all I had to do was give the new framework, whether it was Hermes or Buzz, all I had to do was give them access to the Dropbox folder where all of this history was. And they were off to the races again. They were not starting new. And this becomes kind of the challenge that I see with GrokBot. And it's something that if you're going to use GrokBot, you have to be aware of is that GrokBot, while it can write to those files and still have access to the same Dropbox folder, it's GrokBot is more contained within the Grok environment. Whereas everything else allows you to bring in your own AI models, whether it's, you know, open our chat GPT or Claude or whether you're running a local model. We've talked about local models on this channel before is that we really need to think about how are we setting this thing up and think about where our files are. When I was a young, a young adult, let's say 18 to 20 years old, I had this boss. His name was Lewis. And the whole thing that Lewis continued to like womp into my brain was this concept of documentation. And it was so bad that, you know, it was a running joke because I hated doing the documentation. And Lewis would say, Mr. Todd, where's the documentation? I'll say, oh, you'll have it by September 1st. Well, September 1st came. And he's like, where's the documentation? And I said, I told you it'd be there by September 1st. He's like, but it's September 3rd. I said, I didn't say what year. I hated the documentation. I hated sitting down and thinking about how do we do things and building the processes around it. I really didn't like it. But the more that we move into AI and the more that we start to use on agents, the deeper that documentation is going to run, not only for you, but also for your employees and the team members that you're working with. Because when you can have all of these files that are there, what we've done in the past and the way that we're thinking and the way that we're making decisions, and we can just take that folder and put it into the AI framework. It just makes what we're doing so much simpler. So that's the whole part here is that we want to make sure that we don't have files everywhere, putting them in databases over here. We want to think about how we're going to structure this, how we're going to structure this data. And then how do we move that from framework to framework as things evolve? Because at the end of the day, if we understand how all of the work flows through our company and it's documented, then that's easy to move to another particular agent. Because as it is today, where these agent frameworks are coming faster and faster, it's going to create whiplash and it's going to make you feel overwhelmed in your business if you're trying to keep up with the next thing. Think about it. Like I felt like that this whole weekend is, you know, for the last two weeks I've been using GrokBot. And then over the weekend, I'm feeling overwhelmed. Like, oh my gosh, which one do I want to choose? Do I want to choose GrokBot for my business? Do I want to choose Buzz? And I have these agents inside of Buzz. You see, all of this can feel overwhelming. And it can be easy to feel like you're being left behind. But at the end of the day, you're not being left behind if you're experimenting with this stuff today. Now, if you have your head in the sand and you're like, I'm not going to do anything with AI agents, you might have a problem, especially in the world of business. Because the AI agents are going to drive some of the efficiencies that we're going to see and some of the challenges. And, you know, that's the thing is I want you to really slow down and think about, hey, what are we trying to do here? How are we going to store our documentation so that when the next AI agent framework comes out, if we choose to go that route, we're not starting over from zero again. So that's the message is slow down, think first, and then we'll talk about automating business processes later. But we have to build processes first that are automatable. And I'm curious, what AI agents are you using? How are you thinking through this and what challenges do you feel? And I'd like to know. So if you have feedback on that, head over to scotttodd.net forward slash ask. And I'll see you in our next episode.