80% of AI Automation Basics in Just 29 Minutes

80% of AI automation basics in less than 30 minutes. That's what we're going to be talking about today. I'm going to be giving you guys the core foundational concepts you need to start and then scale an AI automation business in a fraction of the time of your competitors. I scaled my own a automation agency to $72,000 per month. So, I've learned a fair amount along the way. I also now coach almost 2,000 people on how to do the same. Naturally, I pick up on a lot of patterns. So, that's what we're going to be covering. This is you unfortunate person faced with a decision. Do you want to spend 100 hours learning a bunch of BS or do you want to spend less than an hour? Let's do half an hour actually to acquire 80% of the basics. I believe you've chosen right. Why don't we jump right into the very first point and it is the most boring point ever. And you're probably like, Nick, why did you start with this point? Well, it's because I think a lot of people see AI automation as this hype train and this big bubble. And I want to push back against that. AI automation is not really all of that. It is just like any

other business. Don't get caught up in the hype. shiny objects. The skills that make you a successful AI automation business owner are the exact same skills that make you a successful plumber. They're recruitment agency owner. e-commerce business owner. I'm going to draw a business model on the right hand side here. And I just want you guys to kind of like see what which business models this matches. Okay, we start with our lead genen. And there's a variety of things that we do for Legion. We could do cold email. Okay? Maybe we do PPC. That's paperclick ads. Maybe we do referrals. These are all ways of getting people interested in your business. And what do you do with all these lead genen mechanisms? Well, you then shuttle them to some sort of conversion. So, usually this is a sales call. Okay. What happens on the sales call? Usually you'll send a proposal of some kind also known as a quote or an estimate. After that point the person becomes a client. When they become a client you then fulfill and ideally at the very end of this there would be some sort of retention mechanism that you know gets them back in through some other call and then you just repeat and this is really what makes you money. Okay. So, I just drew that and that is how all AI automation businesses work. Um, but kind of just like zoom out a little bit. If you squint, what you'll notice is this doesn't just apply to AI automation businesses. That exact funnel that I drew literally applies to like 90% of B2B businesses all over the world. And so, I say this to mean the only difference between an AI automation business and the vast majority of other businesses that you may or may not have experience with, the only difference is this section right here. It's that little fulfillment section. Okay. So, you know, in a plumbing business or whatever, that might be, I don't know, repairs. That might be, you know, new pipes. In a recruitment business, that might be a candidate being placed. In a PPC agency, that might be, you know, some ad creatives being developed or something. The point is the fulfillment is the different part. Okay? That's the AI automation part. But everything else, your ability to drive leads, your ability to close those impress the hell out of those leads, whatever, all of this stuff is foundational and is shared with literally every other major digital business model today. So, the reason why I say all this is because don't focus 90% of your energy on that tiny little bit at the end that just happens to be AI automation. If you guys really want to crush it at this business model, focus the vast majority of your energy on the same foundational concepts that you'd have to learn in any business.

Focus on your ability to drive leads. sell to those retain customers after they've made it through your pipeline. If you guys are incredible at that, and even if you happen to be second rate at AI automation, you guys will make way more money than if it was the other way around. Okay? So the fundamentals are always what make your automation agency or business successful. It's never fancy tech. It's never your implementation. Um don't overthink the technical aspects like I see a lot of people coming from, you know, programming or development or engineering backgrounds do. Um and certainly don't underthink the business side of things because the number one thing that I see when people enter uh my communities and my groups and my products, they're always like, "Hey Nick, you know, I'm an engineer and I'm great at building products, but I'm not very good at marketing. " And I'm like, "All right, well then you're not very good at being a business owner. So, we need to fix that first, right? Your development and engineering skills, those things can wait. We need to make sure that you're a good marketer. you're a good salesperson. And ultimately, we need to make sure that you're good at business development if we are to develop a business. " Cool. So, I mean, you know, understated hopefully, but uh yeah, I think that's probably one of the most important parts. Now that I've covered that, we can actually start getting into some technicals. Okay. So, I think a lot of people that are watching this are probably at the start line of their AN automation business. I mean, if you weren't, likelihood of you watching content like this is probably lower. So, um I know real Sherlock Holmes over here, but one of the core foundational parts of AI automation agency fulfillment uh is your ability to use an

API. So, an API just stands for application programming interface and um all that really means, did I actually get that right? API stands for application programming interface. All right, cool. Good god. I don't think I've actually spelled this out in a very long time. Got to love acronyms. Um, all that really means is it's just a essentially for our purposes, it is a server URL somewhere on the internet that we can send a request to and then we can get things back. And the cool part about APIs for us is you know those AI automation tools that we tend to really know and love. Stuff like make. com, stuff like nadn, stuff like zapier, stuff like lindy, all these drag and drop no code platforms which are really what most people think about when they think AI automation. Well, these don't have built-in integrations with every platform that you might want to connect them to for business purposes. Okay, in those situations, we need to use an API or an application programming interface to build our own connection to those services to allow us to get a job done. I want to say that if you only use built-in integrations, not only is your ability to do anything actually really cool for the client severely limited. A lot of the time the client scales just do that stuff themselves by dragging and dropping modules across the screen, but not only is it super limited, you can't really drive as much value as you realistically could out of any platform because a lot of the time the simple endpoints that are exposed by make. com or zapier or nan or whatever um you know they're just a lot more parameters there a lot more options uh in the API versus just the drag and drop. So, what I'm going to do here is I'm actually going to run through how to connect to an API. And I'm going to do it using two tools that are really popular right now, make. com and naden. And hopefully this is just going to give you guys a walkthrough what I look for when I connect to an API. Um, as we see, the number one thing that I always do immediately is I look for O. Then I look for a way to copy and paste a simple example. And then from there, I basically build a minimum viable API call that just works. The second I have something that works, which usually involves some method endpoint and header shenanigans. The second I have something that works, everything else is so much easier. So, um, yeah, let me show you one example in make. com and then I'll show you another example in, uh, n as well. What's the API we're going to be connecting to? It's this really cool one called firewall. I've been using firewall a lot more recently. Essentially, what firecall is, it's just a way to scrape like any website and then return the results in what's called markdown. So, this is my website right over here. Okay, leftclick. ai, growth systems for B2B companies. Got a handsome photo of myself in the top right hand corner. Then a bunch of other BS. I'll save you guys the time. Essentially what we do is um you know they have this little playground here so you guys can visually see what's going on. But let's say I want to run a scraper for a leftclick. ai. Essentially what's happening is on the back end it's spinning up uh its own server and then it's calling my website and then it's extracting all the data for me. And then what I end up getting in return is this markdown here. And markdown is just a compressed version of the HTML on the website. So I have like access to formatting with these headers. I have access to the links. basically everything I'd need. What's the value in scraping websites and stuff like this? Well, I talk about scraping a lot. Most of the examples in this video are going to be all scraping based. Um, just because I think there's like tremendous um kind of strategic sales value. Uh, but you know, the vast majority of the time, anytime you're whipping up an email campaign for somebody or you're sending any sort of outreach or you're doing any sort of marketing that really matters, you're going to be doing some sort of scraping in Aon Automation. So, I just wanted to make sure this is hyper relevant. Okay, cool. So, um, that's more or less the playground. So, what I want to do now is I want to run this through API. I'm going to open up my make. com scenario over here. I just have it called API call example. The first thing I'm going to do is I'm just going to open up an HTTP request. And then what I always start with is the make a request module right over here. Okay. So, now I'm going to head over to Firecrawl. And what do I want to do? I want to use their API, right? So, I'm going to go firecrawl API. I always just Google the API that I'm looking for. And I see there's an API reference here. Awesome. Looks good. Now, I'm confronted with kind of an intimidating page. I have SDKs, APIs, like what are all these threeletter acronyms? Well, the good news is this specific API is actually pretty up toate and it's pretty clean. Um, not all APIs are like this, but essentially the very first and most important thing that I'm looking for is always the authentication. I think I might have called it authorization back here, but really what I meant was authentication. Okay, so we need to authenticate. Now, the way that authentication typically works is there are two or three primary methods nowadays. Um, the simplest one is what we see over here, which is why I picked this API, and it's called authorization bearer. Now, authorization bearer is super simple and it's super straightforward. And essentially, all this means is we need to add a header in our HTTP request that includes the term authorization and then the value of that needs to say bearer and then a space and then we need to have our API key. Okay, I think this nuance is lost on a lot of people. At least certainly was for me when I got start started with all this stuff. So, I'm just going to show you guys what this actually looks like step by step with this real API. And then I'm just going to um change my API key afterwards so you guys don't all run up my fire crawl dev. Uh okay, cool. So, let me just see here. Um what endpoint do we really want to call? I guess let's find an endpoint. So, I'm going to find the simplest possible endpoint. I'm just going to try recreating the playground request. So, I think it's a scrape, right? I'm just going to click scrape. And what do we see here? Post scrape. Okay, cool. The very um important thing is on the right hand side. You see how there's this curl request and usually most APIs nowadays will have a big snippet of code. Well, this is where I basically go to copy and paste a code block with everything I need as quickly as humanly possible. Now, what we see is if I go back to my um Excal here, we start with the authorization and we figured out how to do that. That's fine. Now, we're going to look for a copy pasteed example and then we're going to put together a minimum viable API call. So, we've done this. Okay, we've done this and now we just need to put together this minimum viable API call inside of make. So, I'm just going to drag these docs all the way over to the left side so I could just very quickly and easily access make. com. And then what I'm going to do is I'm just going to copy all the fields that are relevant. Now, always relevant are always going to be the URL. So, I just grabbed the URL directly from here. I'm going to copy and I'm going to paste it inside of my URL bar. The method, which if you guys remember said post over here, it's usually going to be get or post. And then the headers, so authorization bearer token. And this is where we put our API key. Okay, so in make I'm going to go down to headers, go authorization, then I need to type bearer. And now I need my API key. So where am I going to get that? Top right hand corner. I'm going to go to my um fire crawl. Then I'm going to go down to API keys. Obviously every platform that you're using is going to have a different UX for API keys and stuff. But this is what fire calls looks like. Okay. And then I'm going to go to API key. And I'm just going to copy this API key. I'll go back to make and I'm just going to paste that in. Okay. So now we have the authorization taken care of which is really cool. The next thing we need is if we go back to this doc, you see how um there's a uh content type application JSON header. Well, in make it's really easy to do. You just go body type and then you go raw and then content type you just set to JSON application/json and then uh under request content. That's where this data flag is going to come in. And it's always a data flag in a post request. So, what I'm going to do is I'm actually just going to copy this entire thing. Okay. I'm going to go back into my make and then I'm going to paste it in. And all I want is I want my URL, which in this case is being covered with a string. So I'm just going to paste in leftclick. ai. Now you see there are a ton of options here. Include tags, exclude tags. Usually in APIs like this, anytime you see these strings with this, it's kind of like this code. This is just like a standin or like a template or like a placeholder. So I'm just going to get rid of all of these. And to be honest, do I even need any of these? I don't really think so. It looks like the only thing I actually need is just the body, right? I'm just going to remove all other options but this URL. Maybe I'll leave the markdown, too. Okay, get that out. Going to make sure that everything is still formatted in JavaScript object notation. That's definitely a good skill to learn if you guys are using APIs. And then I'm going to rightclick this and press run this module only. I see it's taken some time. It's a pretty good sign. Usually when things take time and on make. com side, that means you're not getting an instant error. And what do I see if I go down to the bottom of the screen? Metadata markdown. I have all my markdown in this variable over here. If I scroll even further down, I have my entire website. And then I also have a bunch of other fields like source URL, scrape ID, description, title for my meta, all that stuff. So what have I done here, guys? I've successfully built an API request, inmate. com. As you see, it only took maybe 2 or 3 minutes as long as you know where to look and where to start. I'm going to do the exact same thing now in

NAND. And you'll see it's actually even simpler because, you know, the solutions usually do a fair job of giving you what's called a curl request. And you can actually just copy and paste a curl request directly into NAD. Does most of the work for you. So now I'm going to open up an NAN um uh workflow over here and then I'm just going to type in HTTP request. Same thing as before. Then you see in the top rightand corner it says import curl. What you can do is you can actually just grab this curl, copy all of it. Okay, curl is just a way that you send a request using your terminal. Then I'm going to click import curl. Paste it all over here. Import. And then now we've actually automatically filled out all of that data. Okay. By just copying and pasting a curl request. This is why a lot of people like NAND. NAN is a little bit more developer friendly and geared towards people doing API integrations and stuff like that. I need an API token. So, I'm just going to copy this over. Go back over here. Paste this in. Super easy. Then, what else did we have? We just had a URL, right? So, I'm just going to go https leftclick. ai. And then I'll leave the formats part and just delete everything else. This to me looks like pretty good JSON. If you're ever unsure whether something's good JSON, just go to jsonformmatterater. com, paste in your JSON, then click format or beautify. If it works, you're going to get something like that. If it doesn't work, let's say we have an extra comma, it's going to tell you where the error is. And usually, you'll be able to look at the fifth line and then be like, "Oh, okay. I have an extra comma there. " Anyway, now that we know that that's good, I'm just going to go back over here and I'm going to click test step. Same as before, we do not get an instant error. What we do get is we get the data on the website scraped ready for us basically instantly. Okay, so yeah, API calls are not magic. They're actually pretty easy and pretty simple and pretty straightforward. You just have to be smart about how you use them. So, next up, let's talk a little bit about the other side of the equation. We just talked about sending data. Well, let's now talk about receiving data. And the best way to receive data is using

something called a web hook. A web hook, to make a long story short, is just like an API call is a way to connect something that doesn't have a connector built into your note platform. Uh, it's a way to create your own connection um sending data out. A web hook is just a way to do that for sending data in. So web hook is just a custom URL basically that you are creating that enables you to point other services to you and then when you do something like maybe you change a record or you update a status or uh some new email comes in or whatever you can actually trigger a web hook on the make. com or the nadn or whatever your note code tool is end to start some flow. Okay, so highly encourage you guys to figure this out because if you do figure it will make you unstoppable. Learning web hooks and learning APIs are probably like the two I don't know I'd say they're probably like the two highest leverage things to learn in the actual AI automation fulfillment side of things aside from you know this business skills we talked about earlier. So how exactly would you do that? Well in make it's pretty easy. All you do so you just go to this web hook node or module. What you want is custom web hook. Okay. Then you create a custom web hook and I'll just say my example web hook. And now what you have is you have a server essentially that is willing to receive a request. All you need to do is send a request to this server and then you are going to trigger your make. com flow. So if I click run once, you'll see it's waiting. Okay, the simplest request you could send with a web hook is actually just you trying to access a website. So if I just take the URL, which was this one up here, and then I paste it in, what do you think is going to happen if I press enter? Well, my browser is going to send a request over to this web hook URL, which is going to trigger my flow. So I just press the button. As you see, it says accepted. And then if I go back here, this make. com operation, it actually got triggered, which is pretty crazy. Now, there's some built-in logic with web hooks that they don't really teach you about, but because web hooks are just a server request, you can also do things like past query parameter uh query parameters over. So, um, if I were to put a question mark and then say query parameters equal example, then press enter, what you see is I now have access to a variable called query_parameters. Now, I'm doing this with a browser, but you can actually do this with any service you want. And you can do this with u monday. com. ClickUp. There are a variety of different ways to do this. If I go over to app. clickup. com, which is just a simple project management tool that I really like, then I click on their automations uh feature. You'll see here that if I click manage all automations, I have the ability to set up an automation where when I do something, basically I can fire off a web hook request. Now, if I request, if I paste this URL in here, then I just say, I don't know, task created. So, every time I create a task, I'm going to call a web hook. If I do this, okay, then I go back to my make scenario, run this, ClickUp, and again, ClickUp can be whatever the hell you want. It doesn't have to be ClickUp. It could be monday. com, it could be pandoc. Basically, every one of these tools has a web hook feature. Then, if I say this is an example record, I press enter. Then, I go back here. What you'll see is ClickUp just triggered that web hook and then sent it over to the address that I listed which has now enabled me to start a flow in my no code tool. So it's as simple as that. Does not have to get more complicated. So I'm sure you guys can imagine NAND is basically the exact same thing. There is a web hook node. The only difference between um make. com web hooks and then NAND web hooks are there's a test URL and production URL. Um, and generally when you are testing something, you need to have this web hook- test in the URL. When it is live and it's ready for production and your workflow is on, it needs to just say web hook. You also need to specify the method. It needs to be either a get or a post, but I'll leave all that to specific programming videos. Um, it's more or less the exact same flow here. So, if you know how web hooks work, you're already 90% of the way to being what I would call a good automator. Um, you know, web hooks, API requests, these are basically like the tools of the trade. And to be honest, anytime you're using a built-in automation or, you know, a drag and drop node anyway, all you're doing is you're you're using web hooks, they're just not telling you that you're using web hooks or you're using API calls. They're just not telling you that you're using API calls. All right. Okay, cool. Next up, I want to talk how to prompt AI

models effectively. As the AI and AI automation probably implies, most of our work involves weaving in artificial intelligence into some sort of business process. So, I have the simplest possible way to think of this, and I'm going to give it to you right now. There

are basically three types of prompts and these are present across more or less all of the current at large language model tools. There is a system prompt. Okay, there is a user prompt and then there is a assistant prompt. These are the three types. Now, the way to prompt an AI and to consistently achieve pretty good results, you know, you got to go a lot deeper if you want to get amazing results, but if you want pretty good results, results that are enough for you to whip up a flow in a few seconds and then impress a business owner, what you need to know is that the system prompt is how the model identifies. So this is where you say you are a data entry professional or something or you say you are a skilled recruiter. You are the president of the United States. I don't know whatever the heck you want it to roleplay as. This is the identity that you're giving the model. Okay. The user is where you give it a task where you say your task is to do a thing. Then the assistant prompt, okay, is what the AI gives you back. And usually the way that I like to do things is I like to have the assistant give me back my stuff as a JavaScript object notation um JSON uh string. So, it's going to look like this with curly braces with a key and a value. The reason why I do that is because when you get in the habit of doing this, you can then very easily integrate this with any tool on planet Earth. You're using what's called structured data. And once you have structure to your data, you can obviously um you know, forward that over to some software platform, parse out the keys, add the values to other variables and stuff. It's pretty cool. Okay, so that's more or less what this looks like. just to run you guys through it very quickly with an NAND flow that I built to personalize um real client or real lead data. I've since sold this system many times. I've also put this up on Maker School and make moneywithmake. com, my two automation communities. We've had many, many people sell this. This is exactly what a real functional system that you guys can charge money for looks like. Um the AI model for this system essentially has a system prompt where you say you're a helpful intelligent writing assistant. That's its identity. And then we have a user prompt where we give it the task. Your task is to personalize an email. You'll do this by taking a prospect LinkedIn profile and then editing five templates for different sections of the email. Subject line, icebreaker, elevator pitch, call to action, and a PS field. Your templates are below. Then I give it some templates. guidelines. Then finally, to make a long story short, I say respond in JSON using this format. Okay. Then what do I have? Well, this is where things get a little bit more complicated and where most people kind of lose me, but essentially after um the system prompt, you put a user prompt. After the user second user prompt where you actually give it the data that you want it to operate off of. And then finally, when you're done, the AI will return essentially an assistant prompt. So, this is sort of the behind the scenes sort of, you know, the best way to think about using this sort of stuff um live. And it's what I follow every single time that I build a system that prints money. I mean, I follow this card blanch. I'm going to have this Excala draw in the uh description, so you guys can just click the link, look at this exact structure, and use it in your own platform. Um, I'm using uh just Nad for that example. But keep in mind, you can do the exact same thing in Make. com, Zapier. That's why I drew this out just so you guys had something that's platform agnostic. Okay. Number five is to use what's called testdriven development. Now, I don't think a lot of people fully understand what this means, but usually the way that people will build out workflows is they will try and in their head map out what the whole thing looks like and then they'll drag and drop like 50 modules together and then click run or test. Then obviously there'll be an error at some point during the flow and then when the error occurs, they're not entirely sure where they need to go to fix it or why it happened in the first

place. Don't do that. Instead, do what's called testdriven development. When you start building stuff, okay, start by dropping the first module in. Okay, then test to make sure the first module works. that with the inputs that you provide that module, everything the outputs are as expected. Once you're done with that, then and only then do you drop module 2 down. Then you test module 2. Then and only then do you move on to module 3. And so on and so forth. The reason why is because if something in your flow breaks, okay, and you know that everything up until here was perfect and then all of a sudden there started being a break right over here, where do you think your error is? Obviously, the error is right over here. So, this is where you're going to look. The reason why this is valuable is because when you're building systems, debugging, the process of going through and trying to figure out what the problem is a massive time sync. It's like a binary search tree in technical terms. It's super freaking expensive time-wise. But then if you test driven develop like I'm doing here, every time you test a module after you put it in, it actually just it's a fixed time cost. It takes like 30 seconds every time you do that. Your flow has 10 modules. What are you doing? You're testing for 5 minutes total and you know the whole thing works and you know exactly where the debug um is, right? So instead of your uh debugging kind of looking like this, if this is time and this is um I don't know let's say debug time and this is like your step in process basically your debug time looks like this which is a lot more consistent uh like this a lot more measurable and a lot more reliable. Okay, so just a much simpler and easier way to think about it. When you guys create something, okay, just like I tested the web hook, test the web hook first before putting down uh the next module. Okay, when you're done with uh whatever you're testing, actually test the whole flow again. Okay, right click on it, click run this module only and say, hm, you know, did the uh value y come out like I expected? Yes, it did. Okay, great. Now I can move on. The second you get in the habit of this, your builds are going to be a lot faster. Okay. And then the last thing I wanted to cover is anytime you're building something, start at the end. Don't start at the beginning. So, you know how earlier I was talking test-driven development, start with module one, start with module 2. Well, actually, I was kind of being tongue and cheek. What you should really do is, let's say you have 10 modules in your desired flow. What you want to do is you actually want to start with module 10. You want to test to make sure module 10 works, and then you want to work backwards to module 9. You want to test to make sure module 9 works, then you want to work backwards to module 8. Now, I know you're probably thinking this is silly, but let me give you a quick example flow. Let's say you have a very simple proposal generator. Okay, this is a proposal generator flow that I've built and shown on my channel many times. The way that this works is usually you will have some form. You will have the salesperson full information about the prospect in this form during a sales call. You'll then have AI to generate content whether that's a copy for a proposal, maybe you're customizing an email to send out or something. Then you will customize an asset, so either a Google Slides or a Panda doc. Then finally, you'll send an email with the Google Slides proposal. How would I actually build this thing? I actually wouldn't build it left to right. What I would do is I would start with the last module. Okay, this is where I'd start. I'd actually put down a module that sends the email that I want that contains a link to the Google Slides proposal. You know, if my flow starting left to right is supposed to start with a type form or something, I wouldn't actually start with the type form. What I would do is I'd go all the way on the right here and I start with the email. Okay? I would have send an email all the way on the right. I would then add an example of the data that I want along with the attachment type that I want. I would do all of this and then I would test it. I would make sure it lands. And only when I make sure that it lands. the end does what I want to do would I then work backwards, which in this case might be a Google Slides module or something. Okay. So maybe now um I would do Google Slides and then I would go create presentation from a template. Now this is a little bit backwards. So I'd stick it right over here. Then you know after that what would I do? I would go and I would add an open AI node. Okay. I would test to make sure that open AI node works. And then I would uh we're doing create a completion and make sure that's all good to go. Okay. Then maybe before that I have some other data processing stuff. But the point that I'm making is I would actually this entire time work this way, not this way. And there are a couple reasons for this, but to make a long story short, when you work backwards, what you're doing is you're eliminating wasted time on all of those paths that lead nowhere. So if this is the flow at the end of it, okay, it's four modules or nodes. In order to create it, what you actually had to do is you had to make this and then you had to try this and then that didn't work and then you had to go back here and you had to try this and maybe that worked. But then you tried this and that didn't work. You tried that and then you got back here. Okay. And then finally you got over here. So like this is the the actual flow. And I think I drew an extra one here, didn't I? Yeah, I did. That's all right. But during the building process, you experimented with all these weird ass paths. It didn't actually lead anywhere. These are all wasted time. Okay. It's kind of like how you have like a million in one ways, okay, to make it to X over here. So, these are all the ways that you could go. If you just started at X and then picked one of these, let's say, let's make this blue. Let's say this one here, you'd actually only ever spend that time building it backwards and traversing that one path. You don't actually have to try all the candidate paths it's called. So, yeah, start at the end, not at the beginning. easily the simplest and most

straightforward way to getting this done. If your goal is to send an AI written email, have the AI write the email first and then send it. Don't actually like start with the trigger. Don't start with all the introductory logic. Don't do any of that. All right. Hopefully that makes sense. Awesome guys. Had a blast putting this video together for you. Hopefully you've earned the 8020 of the 8020 at this point. If anybody has any questions about up and getting up and running with AI automation as a business model or web hooks APIs or any of the more technical things that I talked about today, just drop a comment down below and more than happy to help. And if you guys like this sort of stuff, definitely check out Maker School. We're just under 1500 members as of the time of this recording. Prices are increasing the second we hit that 1500 member cap. If you guys wanted to start an automation business, now is definitely the time. Things are booming and uh it's easier and better now than it ever has been before. Otherwise, like, subscribe, do all that fun YouTube stuff, and I'll catch you on the next video. by