From beginner to AI native

0:00 So, this whole course is basically assuming that you know nothing and that you don't have a technical background, which if you guys don't know who I am, my name is Nate and I do not have a technical background. But, I've been able to do some pretty incredible things with AI in the past couple years. I've got multiple different businesses that are based on content, education, certifications, events, consulting, and all of that is powered by a small team who is really, really good at using AI.

0:22 The whole idea is that one person can do the work that it used to take teams. And I felt that ROI myself. And if you guys haven't, by the end of this video, you will have a very clear path to feeling that ROI and having AI systems that help you do more and that will eventually become the baseline. So, it's great to be getting ahead of this stuff. Okay, so first things first, what is Claude Code?

0:45 Because I know the word code probably intimidates a lot of people. If you've never coded before, you don't have to code. So, Anthropic, that's the company that is behind this ecosystem, right? Um, the cloud models, Claude Chat, that is probably what a lot of you guys are used to. So, there's basically these three products. The first one is Claude chat and that is where you can talk to Claude in the web or wherever you want to do it on your phone and you just talk to that large language model the AI model and you get an answer.

1:08 So kind of like a a chatbot. Then we've got Cloud Co-work which is kind of like the next step up. Fun fact, Cloud Co-work the entire product was built using cloud code by a few engineers. It would have taken the team weeks and weeks and much larger team but they were able to ship this in like a week with a few engineers. So very very cool. And cloud co-work is much more for kind of like your knowledge workers, your managers.

1:31 It's much more of a simple interface to do simple automations and stuff, but cloud code is just the most powerful. And the cool thing about cloud code is like I said, you don't need to know how to code at all. And so I really don't ever use cloud co-work even though you could argue a lot of the stuff that I do in cloud code could be used in co-work. code is just way more powerful and it's where I see the future as far as thinking about building your own agents and just having things that are a lot more agentic for you.

1:54 So those are kind of the three products, but what's cool about it is they're not that different to actually use. So if you learn one really well, you're going to be able to transfer those skills wherever you go. So don't feel like you're locking in by choosing one of these products. That's why I choose the most powerful product. So if I open the Claude desktop app, what do we see right here? This is Claude chat. You know, I can come in here and I can say, "Hi, Claude." and it can kind of understand a little bit about me.

2:38 It can see my preferences. Obviously, it knows my name, but this isn't where you're going to get real work done. This is where people are kind of treating this as like a Google search engine or they're connecting their Gmail and helping it, you know, having it help them write email drafts and stuff like that, but it's not true agentic power. And this is Claude Code. What do you see? It's a very similar interface. You just talk to it in chat, but now what happens is it's able to access your local files.

3:01 As you can see here, I can choose a folder to actually work within, whether that's my desktop or my downloads or my Herk 2, which is kind of my AI operating system, which is a term I might throw out a little bit today. Don't worry about it too much. At the end of this video, I'm going to show you a full course around how to actually build your own AI operating system, but this comes first. The whole point here is that Claude Code is able to work inside of local files as well as touch anything out there online.

3:24 It can touch your Gmail, your Slack, your CRM. It can touch anything online, but it can also touch your local files, which is really, really important. And the other cool thing to note is that when you're in cloud chat, you know how you guys probably are aware of models like Opus or Sonnet regardless of the model or even Fable. Now, Claude Code is powered by all of those same models. So inside of cloud code, you still use sonnet or haiku or opus or fable, but the code aspect is basically just enthropic saying, "Hey, because you're working with local files, here are some other things you can do like web searches and web fetches and searching through local files that make you a little bit more powerful than cloud chat." So fundamentally, it's not that different from cloud chat.

3:46 I don't ever use cloud chat anymore. Everything that I would typically do in Cloud Chat, I'm doing in Cloud Code because Claude Code knows everything about me, my business. It can see all my YouTube videos. It can see all of my Slack threads. It can see everything that I'm doing, which makes this feel way more like an employee rather than just like Claude chat, which kind of feels like a virtual assistant, right? I'm not reexplaining myself to Claude Code because it knows everything about me.

4:09 So, you're probably going to hear the term harness, magenta harness, AI harness. That's what Claude code is. And this is kind of the way that I think about how you build with AI. This three sort of layer circle. At the core, we have the AI model. So, Opus 4.8 or Fable or GPT, whatever model you're using, that's at the core. Then around that, we have the AI harness. So, cloud code is a harness that uses AI opus or other cloud models to power it.

4:55 And then on top of that harness, you have you. So, your brain, your prompts, your context, your data, your business. That's how it works. So if we make this a little bit more practical with analogy here, we've got the model here. We've got a car and then we've got you. So opus is a model, right? But without this is basically the engine. So we put this inside. If I can make the layering right, we put this basically inside of the car.

5:18 Wherever you think the engine in this car might be, let's just say it's here. Then this is still not going to really be that useful. It's not going to be able to drive or go anywhere without the human. So the human has to come in here and drive the car. So the human is steering the harness and the harness is powered by the AM model. That might make no sense to you at this point. That's okay.

5:40 I just wanted to sort of lay out these terms because you will hear these terms the more you get into AI. So just a simple way to think about it because as you continue to evolve and as the tools continue to evolve, you might switch out the model. So maybe you'll be using cloud code, but eventually you might switch this out for a different model or maybe you'll be using the model, but you'll switch out a different harness.

5:40 Maybe you want to get in a different car and just drive it in a bit of a different way. So they're interchangeable but at the core this is what we're looking at AI harness and you and really the most important thing in this whole picture is you. If you are not giving it the right context then it's not going to be able to do the right stuff for you. So that's what it looks like. Okay. So that is what cloud code is.

6:02 Now before we start getting into some of the technical stuff of getting set up and you know building stuff I wanted to talk about the mindset because the mindset around this stuff is so important for many reasons. I think the first one is that you know the space changes so fast. new models, new tools, new headlines. The space changes fast. So, how do you learn things in a way where it's not outdated next week? And that's what I want to teach you guys today.

6:23 That's so important, in fact, that I actually wrote a book about this. It's called Becoming AI Native. And in this book, I go over kind of like throughout the chapters, these 12 big mindset shifts. And so, throughout this course, I'll probably relate back to some of these mindset shifts a little bit. But, I wanted to talk a little bit about mindset before we jump into the weeds of everything today. But before we hop into those mindset shifts, I want to talk about real quick with you guys.

6:46 Six AI skills that I think every single person needs to master just to basically future proof their careers. AI is real and it's not going away. Just like social media replace newspapers and billboards and Netflix replace cable, AI will change and replace millions of jobs, including yours, unless you learn six important skills. These six AI skills will futureproof your career so that you don't have to try and start a business if you don't want to or switch careers if [music] you don't want to.

7:09 So, these six skills are going to apply no matter what job title you hold or whatever career you're pursuing. And I can guarantee you the last skill in this video will surprise you because it's the most unique skill, but it does work. So, let's just get started with skill number one, the AI person. So, becoming the AI person. I know that that sounds like super obvious because this is an AI video, but I think that a lot of people misunderstand what that actually means.

7:31 If you're watching this, you probably feel like you're on the beginning side of AI. And honestly, you probably are because there's so much happening right now. There's always new models. There's always new tools. There's always new agents and workflows, new benchmarks, all of this kind of stuff coming out every single week. But I bet if you went and you talked to [music] your friends or your family or just a lot of the people that you work with, they probably already think of you as an AI person.

7:52 Or if they don't, you want them to. And that's the point. Being the AI person is relative. It doesn't mean that you're the best AI engineer in the world or that you understand [music] every single AI model and the architecture behind it. You guys probably think of me as an AI person, but in reality, I feel overwhelmed every single day by how much I still don't know. But just remind yourself it's all relative. It just means that inside of your circle you know more than the other people and that matters way more than you might think.

8:15 I've seen this happen over and over in my communities. People start picking up AI almost like a hobby. So they're playing with Claude, maybe they're testing out codecs, maybe they're messing around with Google V3, building little tools or little AI side projects, automating parts of their job, just running a bunch of experiments. And then what happens is they start showing people and that's usually all it takes. They show someone at work, hey, look at this thing I built this weekend.

8:38 Or hey, I used Claw to clean up this process. or hey, I figured out a way to make this task, which normally takes me three hours, only take me 20 minutes because of AI. And all of a sudden, that person becomes known as the AI person. And the reason this is so powerful is because companies are about to have a ton of like AI moments. They're going to get access to a new model or they're going to spin up a new internal product or maybe they're going to want to build a little AI task force internally.

9:01 [music] And when that happens, someone's going to say, "We need someone to lead this." You want someone in the meeting to say, "Actually, I know someone who's really into this stuff." Or something like, "We should ask Nate. you know, he's told me that he's been playing around with all these AI tools. That's how these opportunities open up before there's a formal job title. And that's how people get pulled into better projects. That's how people become more valuable without quitting their job and starting from [music] zero.

9:22 And the data backs this up. So IBM's 2026 CEO study found that 85% of CEOs said that all functional leaders have to become technology experts in their own domain. Not just the CTO, not just the engineers, not just the IT team, everybody. So whether you're in marketing, sales, finance, ops, legal, customer success, whatever you're in, this applies to you. And the thing to remember here is that it's not just in one department. It's not like cyber security where you kind of have like a new team and then you're done.

9:45 It's going to seep into every single role and every vertical whether you like it or not. And I know some of you are probably thinking, "Okay, but my role doesn't really need AI and that's your mistake. Your role will need AI because every single role will." So instead of trying to switch careers or learn a completely new job, just take a look at your role. Take a look at what you already do and ask yourself, how do I become faster and better and more useful at this specific task and this specific role with AI?

10:07 So, I mean, think about it. If you were an accountant when Excel came out and you basically just said, you know what? I'm good. I like the way I do this. I'm going to keep doing all of this on paper and with a calculator, you were done. Like, that was probably your last day at that company, if you said something like that, if you made kind of like that stubborn statement. The people who learned Excel first were just faster.

10:30 They got through spreadsheets in a fraction of the time that it used to take them. Let's just say from two spreadsheets a week to 10. That's just random numbers, right? But that new level of output became the baseline. And AI is like that, but it's a lot bigger. Cuz right now, being the AI person feels like an edge, but in a few years, it's just going to be the new normal. So, the advantage isn't waiting until someone's forced to learn it.

10:30 The advantage is becoming the new normal. While most people still think it's optional. So, practically, how do you actually do this? Well, I would say you pick one main AI tool and actually get pretty good with it. So, as of May 2026, recording this video, for me, that's Claude. And I use Claude for my general knowledge work and to build automations. But the exact tool isn't the point. The point is, you need one tool that you're not just messing around with.

10:51 You're using a tool to actually deliver some sort of ROI. And then you can pick one workflow in your current job. You can take something that you already do every week. And then figure [music] out how you can use AI to make it better or faster. Document what changed, how long did it take before, how long after, what got better, what still needed human judgment. Now, obviously, be smart. Like, don't expose company data or break any regulations.

11:14 Don't try to automate something at work without getting like permission about it. And if your company has guidelines and you can't use Claude, then that's actually another opportunity for you to [music] look at because you can go dig into what those regulations are and you can figure out which tools you actually could use. And that alone shows that you care. But I just want you guys to remember that you don't need to [music] change careers. You can just find the AI native version of the career that you already have.

11:37 So that's skill number one, become the AI person. But skill number two is where a lot of people are going to mess this whole thing up because the more you use AI, the more tempting it gets to just trust the output and say like that's good enough. And that's where skill number two comes in, which is taste and judgment. As AI gets better, it gets easier and easier to just trust the first thing that it gives you.

12:00 And I saw this joke the other day that was on one side, we had a person with a bullet point and they were using AI to turn that bullet point into like a super professional structured email to send to the team. And then on the other side, we had that team and they were using AI to turn that structured email into just one bullet point. Now, it's funny, but it does also kind of create the perfect image of where work is going if we're not careful.

12:22 You know, everyone's transforming things, but is everyone reading it? And that's dangerous because when you first start using AI, you review everything, right? Like you read every word, you double check the claims, you make sure it sounds like you, but the outputs start getting pretty good and then you get more comfortable with it and you just kind of let your guard down and that's the trap. And sometimes the giveaway is really small like [music] m dashes.

12:22 You know, AI is notorious for putting m dashes in everything because it's been, you know, trained on so many white papers and formal documents. And so like for me, I've basically never manually written or typed an M dash in my entire [music] life. So if something goes out for me with five m dashes in it, people who know me are going to look at that and be like, "Okay, Nate obviously didn't write this. This is AI." And the problem is the second they think that it changes the way that they interpret that entire message.

12:44 They start wondering, "Did this person actually read this? Is any of this true? How much of this is actually them?" And that's where taste comes in. And just to be clear, I'm not saying that I don't use AI to write or that you shouldn't. I think everyone should. It's just about taste. But anyways, this issue comes up for me all the time with video. So AI helps me make motion graphics that are honestly way better than what I could do by hand.

13:06 They're way faster. They're cleaner, they're more polished, but it doesn't always get right where the motion graphics should come in or how long they should stay on screen or the visuals and like what's explaining and if it's distracting or if it's helpful. And that is still my job to watch the whole video back and give feedback. And that's going to be true in every field. AI can write the sales email. You still need to know if it'll annoy the prospect.

13:29 AI can draft you the HR memo, but you still need to know if it'll make the employees feel weird. So, how do you actually build this skill? First, you should study the best work in your field. If you're in sales, study great sales emails. If you're in marketing, study great landing pages. Next, start saving examples. So, build a library of stuff that you actually like and stuff that sounds like you. And when something's good, don't just say, "Cool, that's good." And just copy and paste it somewhere else.

13:52 Ask it why. Ask what made it good and ask what makes it clear and ask what makes it trustworthy and tell it why you think it's good and tell it what you like about it. Third, every time you correct AI, you feed that correction back into the system. So, the feedback loop is for good things, but also for bad things. If AI writes something and you change five things, say, "Hey, here are five things that I changed.

14:14 Here's why. Update your instructions so that next time it's closer." And that's how you actually train the system to better understand your [music] taste. Because at the end of the day, AI can generate the work. Taste is deciding what deserves your name. Because remember, if you produce something with AI, your name is signed to it. Whether that is something that's really, really good and the whole team loves it, you [music] will get credit for it. Or if it's something that's bad, you will take the blame.

14:14 It doesn't matter if AI wrote it, doesn't matter if you wrote it for that piece of [music] work because your name is assigned to it. So now the question is, how do you actually get AI to produce better work in the first place? Because if you're just typing prompts and just [music] crossing your fingers, then you're leaving a lot on the table. So that's skill number three and it's something that you can apply the second you close out of this video.

14:36 And that skill is becoming a context engineer. So you might have heard the term prompt engineering. This was a huge thing a couple of years ago. The whole idea of prompt engineering was that if you