How to Use AI Like a Pro: The 5 Phases That Will Save Your Business Hours

Where do people go wrong with AI is that they don't know the five phases they're used to. Using AI to write something or to answer a question. In many ways, having a chat with ChatGPT, that's like 90% of the society's interaction with what AI is. But to really get AI to work for you, you have to go through five phases. The first one is ideation. Ideation is where you get an idea and you can use AI in all five stages. But it's important that we know that they are five discernible stages. Stages, because the first one is ideation. You're coming up with an idea how to ideate, how to think of what your idea might be, to kind of really get clear on what that idea is. Then you're going to do research, research around that idea. So you then say, I want to figure out how to do something like that. Then you get into composition. This is the part that everybody is very familiar with ChatGPT. Write me a this, you know, edit my this, look at my this and edit that. Then there's the refining and editing portion, which is where you get massive. It's so easy to get AI to create massive amount of information. It's like, well, how do we trim that down? And then distribution. And AI can help with distribution now more than ever. But when talking to AI, whether you're doing in chat or if you're just talking to AI, like I want to kind of say, you can assign artificial intelligence a role, but you can give it a personality, you can give it a job to do, you can give it a style, you can assign it a profession, you can give it a perspective. And then you can also ask it to format the output. So another piece that is important to recognize is the why OpenAI kind of was the one that gave all of humanity kind of the understanding what AI could be. But it's actually been around since like the 50s started just by identifying pictures of cats and dogs. Then you get this like massive explosion about three years ago now when OpenAI went from GPT to GPT2, then GPT3. And GPT3 is where they added chat to it, made it so you could talk to it. And that was like the big breakthrough that made AI kind of accessible to everybody. And by accessible, it was free and people were blown away. Then they charged $20 a month for GPT plus, which is where you, the smarter models or larger context windows and kind of multimodal things. You could send it pictures or you could get it to output Graphs or you can make it generate videos. In doing that, they charge $20 a month. So most people are not using ChatGPT Pro. It's a $200 a month AI. A lot of people don't see why they would pay $200 a month for AI. You might be right that there's not really much of a need Chat GPT Pro. And it's a sign that the world is changing. There will eventually be a two thousand dollar a month chat GPT or something and then there will be a $20,000 a month thing. So when it went from $20 to $200, it's a decision, do I want to pay 200amonth for AI? Like am I really willing to spend 200amonth for ChatGPT Pro? Like do I need it enough to justify it? There is 50% of the world that's just like, there's just no way that's what I make in a week. I can't sacrifice a of my money to buy ChatGPT Pro. I don't care how good it is. I just can't afford it. When it's $2,000 a month. Are they going to choose to buy it at $2,000 a month? The only reason that he might say yes is because he found a way to use Pro to be so to make it so that there's enough value there that almost pays for the use of the $2,000 a month model. And that's why I want everybody to be at least be considering, if not for you, for your team to be considering, how do we put AI in our hands or our people's hands in such a way that it will justify paying for the next level. Because there's a lot of really smart people that think that this will be the determiner of success. Johnny Harris did a really good video on talking about AI in the military. And it talks about how decisions that would take weeks take minutes. So curating a list of targets, establishing the priorities, the list of assets in the region, potential collateral damage, the resupply routes, everything that's needed, United States government, government can process that decision in a matter of minutes. It shows that the technological innovation in the military has made a difference. If you don't think it's going to make a difference in capitalism, in roofing, there's a problem, artificial intelligence causing massive change all over the world. You know, in geopolitics, you don't think it can have a difference in your business. I want to show you an example of a project that I'm working on. We're changing up our product at RBP and AI has the ability to do something called deep research. This is too big to even begin to discuss all this. I went in and asked it to work through a problem and I'm going to kind of show you where my prompt was and what I got back. This is how long it takes, by the way, because you're going to be blown away here in a minute. Research completed in 7 minutes, 13 sources. What this basically means is I asked it a question instead of the usual like quick instantaneous response. What it did is it said, okay, I'm working through this, searching for relevant sales compensation for recurring services. It went and looked at this. Then it went and found a source in Reddit. Then it went and looked at something else and read more of Reddit. Then it said, hey, I'm analyzing this. I'm looking through fair splits and listing like this for setters and closers. Then it says, oh, I found this on quotapath. So that says, okay, I'm piecing together some information. Oh, I found another website. I'm going to read this. Okay, I'm evaluating base salaries and blah blah blah. Then I'm going to search for this. And then it says, okay, shifting my approach to look at something else. Then it says, okay, I looked at this. So then it found this website. Okay, let me see. Scrolling through to capture next. Then it went, read this. Then I said, okay, I'm going to work through this. Went to this website, read that. And if it sounds like I'm talking for a long time, that's because it literally did all of this over the course of seven minutes. And it combined all this and then now. So that says research completed in seven minutes. Gave me 13 sources. I'll show you where it stops. So this whole chat was about three prompts, by the way. So it thinks through. That's everything that I got from one prompt. It's absolutely massive. What this deep research can do this. The prompt right before this One was this one. Research completed 8 minutes, 27 sources. And you can see the activity that went through this is a whole bunch of data. Like that's a lot to read, right? Like if I said okay, like I did this, now I have to read all this. What you'll kind of see here is a different compensation plan for rbp. That's what I'm working through is a different compensation plan for the kind of the three levels of sales that happens at rbp. So find. Go to Notebook lm. Okay, so this is A Google tool, Notebook lm. So what I did was I took my questions, so I copy pasted my questions into a Google Doc and added that as a source. I took a 2 1/2 hour long video of Alex Ramosi sales and put that in as a source. I pasted in the responses from ChatGPT and I copied over all the sources and the PDFs that it used as resources and I spit that all into this thing called Notebook lm. Now, what that allows us to do is if I push this button, what it's going to do is it's going to generate a podcast discussion about the plan that this thing spit out like this.

Welcome back everyone, to another deep dive. Today we're going to be tackling a question that I'm sure you've all thought about. If you're an entrepreneur or really anyone in business, and that is how do you actually scale a business?

It's the dream, right? To take your business to the next level.

Exactly. You know, how do you make it bigger, how do you make it better? And, you know, most importantly, how do you make it more profitable?

Profitable.

So they're building a team that's not only bigger, but also more specialized and capable of handling the confidence to keep pushing forward.

Exactly by month 12. So I don't want to tell you the whole, like you listen to the whole thing, but if you're talking about refining and editing and distributing, if I wanted to give the company a way to digest this massive amount of information, I would maybe use something like that to distribute it.