What I'd Learn Instead of Automation in 2026

So, I made 400 grand last month building automation systems, and I'm going to tell you why learning automation in 2026 is probably one of the worst career moves that I think you can make. Uh, before you click off this video, hear me out. I run an automation agency called Leftclick. We have worked with everything from local businesses that make 10 grand a month to 8 figureure investment firms and recently a multi-billion dollar portfolio company. I've also spoken alongside some of the biggest people in business today like Alex Ramosi and Sam Ovens. And to top it off, I run the largest AI community on school by revenue, which just means I get a ton of visibility into how automation systems are being sold today and the way things are going. So, you probably heard some rumblings about this, so let me make it clear. The skill that has made all of us a lot of money over the course of the last couple years is well on the verge of becoming worthless. I think that there are a select few that are positioning themselves for what is coming next. My goal with this video is just to add to that select few and then educate people on where we go from here. So, some

uncomfortable truths for you. AI is advancing very quickly and technical skills are becoming obsolete. But there are a few things that you can learn today that will make you more money than any automation skill ever could due to leverage. And today I'm going to show you them as well as the exact moment that I personally realized that my big $400,000 a month business was disappearing. And then more importantly what I and all of you guys could do about it. Okay? Hopefully by the end of the video you'll understand why some of the smartest people I know are pivoting away from automation and then towards something a lot more valuable. Let's do

it. So the big lie that everybody in the automation space is telling you is some variant of hey you should learn these tools and you'll be set for life. You should learn make. com. You should master naden. You should understand how APIs work. And if you do this magical set of things, you will have job security forever. Uh while there are no free lunches in life, I think anybody with a good head on their shoulders can probably sniff the already. The reality is that AI is advancing so fast that the technical skills that you're trying to learn today will probably be automated away before you have the time to fully master them and they get paid for that mastery. And I want to show you exactly why using a framework that's played out in most major industries over the course of the last 200 years. Just before I do, to be clear, it's not that automation is worthless today. It's not like if you spent time learning it, you'd be totally screwed or anything. Uh it has a lot of value. I automate stuff all the time across multi-million dollar businesses routinely. And I get a lot of value out of that. It's just that the implementation of automation is growing less valuable. It is the doing of the thing. Uh because tools are getting better and better every week and they're getting to the point where now they can do a lot of the old technical heavy lifting for you. So, if you followed me until now, you know that this is basically my main business thesis. I baked it into all of my content. my community. I've baked it into Maker School. I spent the last 6 months or so teaching people business skills and not, you know, how to make some weird API call to some deprecated service that barely exists. All I'm saying is that as a whole, eventually we're going to very quickly reach that tipping point where automation as a skill to learn is no longer anywhere near as valuable as just knowing how to interface business with technology. So

skills in the margins get invalidated quickly. And to explain, I want to tell you about a hypothetical example. A woman that I have just come up with called Sarah the Seamstress. By 1795, Sarah the Seamstress knew 47 different handstitching techniques. She could do French seams and blind hems and decorative embroidery. And all of these took her many years to master. She made very good money because at the time these skills were very rare and valuable. and she had quite the reputation as well until the industrial revolution happened and her skills that were previously rare and valuable were no longer rare and valuable. Okay, fast forward a couple generations. Sarah had a granddaughter. Maybe her granddaughter didn't need to know those 47 different hand stitching techniques. Instead, what she needed to do was learn how to operate a loom, right? Which is like an automated uh stitching machine essentially. So instead of learning all of the hand stitching techniques, she learned how to maintain and then clean and then lubricate a bunch of machines that did what her grandmother did by hand. But now she can do a 100 times faster until the computer revolution happened and then the skills that she spent all the time learning that were previously rare and valuable were no longer rare and valuable. Okay. Anyway, so Sarah's great great granddaughter, I don't know how many greats we're at now, no longer needs to know how to operate a loom. Instead, she needs to learn CAD design, which lets her create clothing patterns on a computer and then send them to some automated manufacturing system that's set up perfectly. Well, what do you think is happening to Sarah's great great granddaughter right now? We're in the AI revolution. So Sarah's great great great granddaughter doesn't even need to know that cat anymore. All she needs to know is how to prompt AI to generate clothing designs from a simple text description. She literally just needs to know how to say, "Create a summer dress with floral patterns that is suitable for professional settings. " And if she's good at that, if she knows how to communicate that to a model, it's done. So the pattern here is that every major technical revolution invalidates the skills at the margins of the previous. These are the surface level technical execution skills. These are the stuff that your hands do at the bottom. And at every level, the value in systems moves up. I made this example for you because the same thing has happened to me and I'm seeing it all over the internet. Uh in 2020 when I was running 1 second copy, you know, I had to know every make. com module, every API endpoint. All this knowledge was valuable because it was rare and very difficult to achieve. And so it let me do cool things like scale my own business to over $90,000 in a month in 2025. I don't need to know any of that. every nan node or make. com module. I don't even need to know most API endpoints nowadays. All I need to know are the business requirements of the person that I am looking to help. I then just copy the documentation of these various use cases then paste them into chat GBT and for the most part it'll find me you know what is relevant. It's not perfect yet but it will be very shortly. So basically what I'm trying to say is in 2026 and 2027 AI will very clearly be able to build entire automation systems just from the business requirements itself. It'll describe what you want in plain English and it'll create the entire thing which means the value that you bring to an organization. The thing like Sarah that you'll be paid for will not be your understanding of the tools. It'll not be the stuff that your fingers are doing. It'll also not be your ability to copy and paste documentation which we are currently doing today in 2025. Instead, future skill will be your knowledge of what that business is suffering from and how to communicate that knowledge to a model so that it can build you that solution. Basically, the interface between a business and artificial intelligence. Okay. So, here's what you need to stop doing and start doing. memorizing tool features and API documentation. And you need to start understanding business systems and the patterns in value creation, which we'll touch on later in this video. You need to stop learning how to drag and drop modules and start learning how to identify problems worth more than $50,000 or so to solve. The people that are making the most money in 2026 are not going to be the best at automation tools. In fact, I would go as far as to say that the people that have made money over the even the last couple of years haven't been the best at automation tools, myself included. Uh they will be the best business problem identifiers and they will just happen to use AI as a tool. My second major point

is that communicating with models is that new high lever skill. So, here's what over $100,000 in consulting taught me about the future of work. Very soon, we will become capable of instantiating complete workflows entirely in natural language. These will not just be simple automations. They will be entire business systems. And businesses will pay premium rates for your ability to do this in a clean, straightforward, and logical way. So, my personal timeline on

this is that in about 12 months, natural language will create more than 50% of workflows. You describe what you want. The AI will either build it or it will instantiate one of those agents to take care of it for you. And in general, these workflows will still have some issues and highly technical knowledge will be valuable, but it will be valuable in so far that it will allow you to solve AI generated bugs and that's about it. In 24 months, AI will be able to build complete systems from business requirements. That means customer relationship management systems that currently take you a ton of time to build. Uh inventory tracking systems, sales pipelines, and all of that literally just from your natural language prompt. Now, I think it's natural and easy to be scared of this. A lot of my own business is built on my knowledge of technical skills and the idea that knowledge will be invalidated or significantly reduced in value is pretty scary considering my income. But it also creates a massive opportunity for people who can prompt AI. Right? If you think about it, by moving up a level of abstraction, what we're also doing is we're moving up a level of leverage. And so, you know, it's like an order of magnitude. If right now we're capable of driving X, if you learn the skill up one level of magnitude, you'll be able to drive 10x. The main upside to AI is that it's very flexible. The main downside to AI is that it is very flexible. So in order to corral all that flexibility into some sort of workable business, you need a framework and that is really the skill to learn. So what I'm going to do next just while I have you is to give you a simple framework you can use for prompting. This is developed a couple years ago in a research paper. Uh not a lot of people know about it, but it's the underlying framework that a lot of high quality prompts and businesses applications are using now, particularly in enterprise. So I'm going to give this to you. You guys can do whatever the heck you want with it. Hopefully make some money. It's called the clear

framework. C L E A R. The C stands for clarity. The L stands for logic. The E stands for examples. The A stands for adaptation. Then the R stands for results. And I'm going to guide you through what all of that looks like right now. So for clarity, what you want is a precise problem definition with measurable outcomes. You don't want, hey, build me a lead genen system. You want something that's like, create a one-page qualification SOP that identifies companies with 50 plus employees in manufacturing that have also expressed interest in automation within the last 90 days. You want to be extraordinarily clear with what you want. L stands for logic which is structured thinking that the AI can follow and execute. Basically where you break down a bunch of complex problems into sequential steps with clear decision points. Then you want examples which is providing specific scenarios and edge cases. You know like if there are three or four outcomes you want to delineate and then talk about each. If you're doing your lead qualification system when a lead scores above 80 points you should route to a senior sales route. Um if it's below 50 points and send to a nurture sequence if it's between 50 and 80 schedule a demo call right like make it really clear what the outcomes are. The A for adaptation stands for iterative refinement based on AI feedback. So most people just prompt once. They'll expect perfect results and then they'll fail. The real skill is actually in the conversation going back and forth refining and improving the output based on some sort of eval. And then finally results which are where you validate that the output matches the business requirements. So can you measure success? Can you prove return on investment? If so, you're doing pretty reasonable. In a year or two, when AI models will be able to generate entire workflows from scratch with very high reliability, your ability to use frameworks like Clear will basically correlate one to one with the amount of money you make. Here's an example of a bad prompt that does not follow Clear. Build me a lead generation system. Now, here's an example of a good prompt that does follow Clear. Create an outline for an automated lead qualification system. It is for a B2B manufacturing consultancy. Incoming leads will come from LinkedIn ads and cold email. The lead qualification system should score them based on company size. If there are 50 plus employees, it is 30 points. If the industry is manufacturing, add 25 points. If the engagement level, it's a downloaded white paper, is 20 points. They booked a demo, it's 40 points. Leads scoring 80 plus should automatically route to a senior sales rep with a Slack notification. Leads scoring 50 to 79 should get scheduled for an automated demo booking. And leads below 50 should enter a sixweek nurturing sequence with industry specific case studies. The system should integrate with HubSpot and track conversion rates at each stage. Right. If you send the first prompt, you'll get a generic template. Since AI is inherently flexible, it'll come up with all sorts of different tools that it could use to solve the solution. Uh the output will not be reliable. It won't be consistent. And business pays for consistency. The second constrains that flexibility into the direction that you want. So it is very specific, but basically what it's doing is it's almost like a bowling lane. It's giving AI the guard rails to act within certain

constraints. My major third point is that systems thinking transcends specific skills. So here's why Michael Jordan could have dominated tennis if he'd wanted to. It's not because he was naturally gifted at tennis. He'd never played professionally. It's because elite athletes understand one level up. They understand movement patterns. They don't just understand the specific techniques. They know the shape of athletic performance. They know training systems and mental preparation and competitive strategy and recovery and so on and so forth. I want you to know the same principle applies to business. A marketing agency and an AI automation agency actually look almost the exact same except for the deliverable. They have the exact same plan acquisition system. project management. They have almost the exact same team structure. and odds are they have very similar pricing models. If you understand the shape of a service business, you can make any service business work. Now, this is systems thinking and it's the most valuable skill you can develop because it transcends whatever specific technology or tool happens to be popular in a given moment. And instead, you focus on wider themes that are shared between them. The specific tactic may change, but the wider strategy never does because the wider strategy of our economy is rooted in human psychology. Anyway, let me show you what I mean with one of my own businesses. I started with a content agency called 1 second copy, right? We hit 92,000 bucks a month using some very specific systems. We had some content creation workflows. Uh we had a few client management processes. We had a team structure. I had some management skills and so on and so forth. Now when my business partner and I launched Leftclick, which is our automation agency, I want you to know that the shape of our business was basically the same. Despite the fact that we were selling something totally different, which is automation, it turns out that an agency is an agency. Most of the processes in any agency like your lead generation, your sales, your marketing, your onboarding, and your reactivation are going to be the same regardless of whatever thing you're selling. So in our case, you know, we spent all this time consolidating high-quality agency knowledge. What we did is we just took that higher level strategy, the shape of this container called an agency, and we just poured a bunch of leads into it. And I scaled this to $72,000 in a month. I mean, you can do this, and you can find pretty good success with it so long as you understand the shape of a business. So all you need to learn is the shape of business and you'll be able to thrive. You don't actually need to learn like a specific uh instantiation or technical implementation of a business. Okay. So in general what is a shape of a business? Well here it is. Uh marketing leads to sales which leads to onboarding which leads to delivery which leads to reactivation and hopefully some sort of retention. Every business will follow this pattern whether you are selling websites or automations or legal advice or information products or physical products literally whatever. So

yeah, the main takeaways of this video are our prior skill automation is at the margins and so because it's at the margins, it's getting invalidated pretty quickly. The new higher level skill is communicating business requirements to models. And the even higher level skill is understanding the flow of value and seeing businesses as a general container, each with their own shapes and then learning how to fill that shape. The unfortunate truth is that automation skills kind of have an expiration date, right? The tools that we're all learning today will eventually be automated away by AI. And I think a lot of people here probably see that as a very bad thing. Logically, I would push back against that. Technology is eventually added massively to the quality of life of every single generation, and our generation is one of them. It's just hard to see it when you're looking, I guess, from inside of the well. You know what I mean? If you guys want to position yourself to win in this new economy, what I talked about in this video is how you do it. And don't be afraid to change. I'd encourage you to embrace it. Okay. Obligatory pitch. If this is what you guys want to do, check out Maker School. We focus overwhelmingly on learning the business behind AI, the shape of this container, not just the technical skills. I'm biased obviously, but I can't think of any place that is better positioned for this transition than ours. So, there's a link in the bio below if you want that. And if you guys would like help implementing AI and systems into your business, if you guys want to see the sorts of things I'm talking about here, the business shape and so on and so forth applied to your company, then I encourage you to work with my team, Leftclick. It'd be great to have you. Just book a call below and we'll set you up. Thanks for watching. Have a lovely rest of the day. I'll catch all y'all in the next video. Bye.