Grok 4.2 Agents For Beginners - Grok 4.2 Full Guide With Usecases

So Grock 420 beta is here and we absolutely need to talk about it. So since Grock is here, if you want to know firstly how to access the model, make sure that you do have a premium subscription because it isn't available on the free tier of Grock. It is available on the $30 a month tier. There's just the first tier. Now Grock 4. 20 before you start going crazy using the model, please understand that this model is by far the most computer intensive. What that means is that you will likely hit your limits very quickly if you aren't careful about when you choose to use this model in your day-to-day for its reasoning capabilities. And so if you take a look at this user here, he sent less than 10 messages to Grock 4. 20 and he already hit the limit. So you have to understand that the limits are there. So please understand that you don't want to just completely overuse the model in its initial stages. So, I actually spent a lot of time with this model and because of that, I know how to prompt this model and get the most out of it. Grock 4. 20 is a really different model because it's not a model. It's actually a set of different agents that are doing work on your behalf. So, when you hit the drop-own menu, you can see the GO 4. 20 actually is four different agents. But most people don't realize what those agents are or what they're actually meant to do. So when you actually take a look at the agents here, you can see that each agent has a different role and a different purpose. So the number one agent that we do have here is Captain Grock. Now this is essentially the coordinator who will essentially tell the agents what to do. This is of course one of the most important things and you'll see how that impacts us later in prompting. Harper is usually the research and fact expert. Lucas is the creativity and balance. Benjamin is the one with the math, code, and logic. And so that makes up all of the four AI agents. Now, it's important to know how to structure your prompt so that you can actually get the best out of all of these agents when they tend to collaborate. And I'll show you guys some clear examples after testing for hours on end how you can actually do that. And so, if you actually want to know how the Grock 420 beta works, this is essentially how the framework is. And I know this might seem a little bit confusing. The only reason I'm adding this into the video is so that if you're a more technical user, you can quickly screenshot this and then of course you can reason with your own prompt. But of course, if you're a complete beginner, don't worry about all of this. I'm going to make all of this basically make complete sense. So let's dive into it. So let's say for example, you have a question you want to ask the model. You basically get the most advantage from Grock 4. 2 two, when there are conflicting opinions and you would benefit from a different set of opinions and there's no clear answer. So essentially what I'm saying here is that oftent times crop 420 can be best for open-ended questions. So let's say for example a question is when should I buy Bitcoin? Okay, because this is something that is very controversial and it's super simple that everyone knows. Okay, so let's say for example you're saying when should I buy Bitcoin? We don't want to put our prompt in just when should I buy Bitcoin. We actually want to structure the agent on what we want them to do. So what we can say is Harper please research information on the best time. Then what you could say is you could say then Lucas consider opposing views via research too. And then you could say Benjamin factch check their results. Okay. And then what we're now going to do is for the last and fourth final thing is we're essentially going to say, "Captain Grock, please summarize and give me a final output. " And so essentially what we have here is a prompt structure that I've developed where I realize that the best way you can get out of this model is essentially to have first find views that support your argument, then find views against it, third you have someone fact check it, then fourth you have someone give you a final answer summarizing everything. So once you put that in, you're going to see now the agents are now thinking. And so you can see here that Captain Grock is basically telling the agents what to do. He says, "Harper, please research this. Lucas, please research this. Benjamin, then you do this. " And remember, this is all happening in parallel. And that is why this is so effective. And most people don't realize that when you have multiple agents working on something, it reduces the rate of hallucinations, I think, by 10 to 11%. So if you're working on something that does require a degree of accuracy, then this could certainly be something that helps you out if you realize that the markets tend to hallucinate. And so here we actually do get our final prompt. So it's going to come up with a, you know, final solution here. And then it gives us a little bit of context. It gives us Harper's research signals for the best entry points. Then of course you can see Lucas's opposing views. Then of course at the end it's going to give us a practical takeaway. And of course it does have the Benjamin fact check here. And the reason I've included this step in the prompt is because anytime you have an LLM do something, it often goes off and doesn't fact check it itself. It doesn't reason with another agent. So when you have, you know, Harper doing the research, Lucas then having the opposing views and then you have Benjamin factecking, I think this is

arguably probably the strongest prompt because you essentially have two opposing views. And the reason I want appealing views here is because LLMs tend to be too psych too agreeable. And when LLMs are too agreeable, they essentially don't give you a nuance point of view. Meaning that if you say, "Isn't today a good time to buy Bitcoin? " It's probably going to agree and tell you that your idea is great. When you have a different idea and then someone can then fact check that idea, that just makes the result that you're going to get back a lot better. And so you can see here it says, "If you believe in it long-term, start to decay it now or maybe do a lump sum risk management. " Of course, this was just a basic example, but I wanted to show you guys how you can actually get the most out of Grock 4. 2. Now, let's take another example that has a bit more information where we can actually fact check what they've said and what would actually be useful for the everyday person. And so, I've written a second prompt here, and it says, I believe that universal basic income will lead to a 20% decrease in GDP. Benjamin, find the strongest data supporting my claim. Harper, refuting it using certain economic reports. and Lucas create a synthesis that explains the middle ground theory. In fact, that prompt I will change and I'll ask it to fact check, ensuring it's all correct. And then I will ask Captain Grock to essentially act as a judge and tell me which agent presented the more logically sound argument based on evidence provided and reach a logical conclusion. And so the reason you actually want to do this is I've already said different reviewing arguments, have someone fact check it, and then have them present the final solution. Now, of course, even in cases like this, there is never going to be a set direct answer that you can follow because decisions are nuanced. Maybe for someone who's 90 years old, maybe it's not the best time for them to buy Bitcoin. Maybe for someone who's, you know, 12 years old, maybe it's probably better for them. So, of course, don't forget to add as much context as you would normally with your prompts because that is of course going to help you out tremendously. And I know most people often times do prompt in a vacuum. And considering that Grock doesn't have memory at this moment in time, it is probably worthwhile to ensure that if you're prompting anything, you have whatever context you can add to that situation. So, it is context aware and it's going to use that when it does the reasoning for you. So, once again, we had Benjamin finding the supporting evidence. It says he highlighted certain macroeconomic models. Then, of course, you've got Harper's refuting evidence. Luca's fact check. And so, you can see the judgment there. And it gives you an opinion. And it says Harper's refuting argument is more logically sound. And here is why step by step. It says the logical conclusion that basic income will lead to a 20% decrease in GDP is simply not supported by the evidence. The strongest available data actively refutes catastrophic declines and effects depend heavily on design/ financing yada yada. So this is why I'm saying that this is a tremendously powerful tool that most people are missing. I'm seeing people on Twitter that are coding and doing all that good stuff. Grock 4. 20 isn't a model that is really designed for that. It's more designed for reasoning. And even Elon Musk when he said he was designing these future models, he essentially designed them to actually be useful on the day-to-day basis. And considering that if you prompt it in this structure, you get the most out of the model. There's no doubt why. Let's actually compare this to a simple base prompt. So, you can see how much more powerful this is. So, I'm just going to take the first statement here. Then, what I'm going to do is I'm going to paste this in and I'm going to say, is this right? And then you're going to see the type of prompt that you do get. Remember, this is using agents as well. And another quick tip I did forget about and this is a bit weird but it is something that I do. If you actually want the AI to reason in a certain way sometimes you can say search this website first go on to this you know source prioritize this source. Those are things that you can do if you know a lot about the you know super interesting source. I'm not sure what the specifics are but maybe some sources are more reputable than others. Of course if you have that in domain knowledge don't forget to use that. And so once again you can see that we have the information here and interestingly it does actually give us a very interesting train of thought. It tells us that the evidence is highly mixed and it does say that no this is not you know quite likely and it does say that the bottom line is that it could reduce GDP but it talks about that figure is from one specific simulation. But I do think that if we go back to the other prompt you can see that it says Captain Grock and it basically walks you through everything. It walks you through the arguments for the arguments against. Of course, it does fact check it and it does give you a decent logical conclusion. When you're using these models, it's important to understand what you're using because I think this is a little different from standard chat agents. And another thing that you can do as well that is super useful. If you want, you can actually see the reasoning trace. So, you know how I told the model to do this and to do that. I told essentially Benjamin to find the data. You can see that the task was actually sent to Benjamin to find the strongest status to support the claim. You can then see that Harper was of course, you know, sent to find the data and refute the reports. And then of course Lucas was to fact check it. Okay. So Lucas was sent to fact check all of this all the methodologies check the impacting studies and then of course you can see overall as you get the end prompts here you get a much more robust answer. So for me this is how I plan on using Grock 420. I don't actually have Grock heavy the team of experts since it's $300 a month but I do think that Grock 420 is most certainly a powerful tool. You could argue that this is quite like a

model council which is most certainly completely powerful. But if you have any use cases or this video helped you, don't forget to leave a like on the video. And of course, if you do want the prompts and other things like that, don't forget to check out the community. It's only $10 a month to stay up to date with AI if you're there for just 10 minutes a