The 10-Hour Plan to Get Ahead of AI

If you are in your 20s and you're working right now, or you're about to start work, you're in school, you're thinking about a job, the elephant in the room is AI. And I think I kind of walk both lines of that world. On one hand, I'm 20 years old, I go to school, everyone I know is in their 20s and just starting out in their career. And so I very materially feel the real costs of that. And I think if you are in your 20s, whether you're 28, whether you just got out of college, whether you have three more years until you're out of college, AI at some point will either materially help you or materially hurt you. That is a very, very real thing if you have not felt that already. And I don't think that's a good thing for society, the economy, because we're just not setting people up for success. But on the flip side, I have this channel where I talk about all these different AI tools and platforms and upgrades. And AI has been the single biggest enhancer to my finances, my income, my productivity, my creativity by a mile. And so having been on both sides of that, I have a few thoughts about how you, if you're in your 20s or just starting out in your career, can best set yourself up to not get annihilated, steamrolled by AI. And my goal here is not to just spiel generally about very obvious things like get better at AI. Instead, I want to give you basically a three-step process so that you can go after watching this video, do these three things, and you will walk away probably not getting crushed by AI in your career. It's never a promise. That's just the world we live in, unfortunately. But I think there is a very low-effort, high-yield path here that will benefit you regardless of the domain in which you work and or study currently. That, my friends, is going to be the video. It'll be a straightforward one. No editing. Just plug in some headphones, go for a walk, and learn how to not get steamrolled by chatjpt18. I'm just kidding. There is no chatjpt18.6. Anyway, let's go. And a quick thing before we keep going, because everyone who's tried to build a presentation on a genuinely complex subject knows this feeling. You have research notes, scattered data, ideas pulled from five different places, and you just sit there trying to figure out how to even structure the deck. And AI can gather information, but a great presentation needs your own ideas and story. What you really need is not a one-click PowerPoint tool. It's a workflow that helps you think and edit freely. So this one is sponsored by AIPPT.com. And the reason I wanted to show it is their flow mode. Presentation tools give you a generic deck. And even with powerful models, you'll still need to tailor it for your actual presentation. And every company has different priorities. Every manager wants something different. And you'll probably need to add your own insights. And so that is what makes AIPPT.com different. It starts with a solid outline so that you can easily rearrange sections, add your own ideas, and shape the story before the slides are built. So it gets you from zero to about 90% completion while leaving you to the freedom of actually making it something that fits your audience. And that's what we talk about on this channel all the time, combining the human with the AI, not letting the AI overwhelm what you as the human talent. So let me just show you. Pull up AIPPT.com on the screen and follow along. While I do this, it takes about a minute. So here's what that process could look like with those scattered research docs and unstructured notes. Instead, let's open AIPPT.com. We'll create a new project and then select flow and then choose nano banana mode. And then here's the prompt we're going to paste. So create a quarterly board update for an early stage AI startup. I'll let you pause on the screen and read the rest of that. And you can see the outline that's being created, the visual effects, and there's tons of different themes, layouts, diagrams, and charts, kind of that whole suite of editing again to make you that much more productive. And we can see that deck render in real time. And then finally, upon completion, we can see how this messy multi-topic prompt gets turned into that clean, logical sectioning of the deck. And we can also add a new section if we want with, for example, company specific data. So this is our before, this is our after, when it's clearly more efficient for you. And that's the part that I keep coming back to. AIPPT.com handles the heavy lifting by building the framework so that you stay in control of the final content. And once your ideas are ready and structured, everything from layouts, charts, and themes can be refined in the same workspace. And that is much closer to how presentations are actually made. And when you're done, you can export the deck as HTML, not just as the PowerPoint file format. So if you want to share, it's a live link instead of a file or to embed it on a site that is built in. And you will still, using this, tweak a slide here and there. That's normal. But on a complex topic, this fast forwards you through the structuring problem, which is the part that usually stalls everything. That's your pitch deck, market analysis, research presentation, board update, and handles all of the heavy stuff. So if you want to try it, the link is in the description or on the screen here, and you can use the code in the description for 20% off. That is AIPPT.com. So go build something with it and tell me what complex topic you are building with it first. And that said, back to the video. So first, there are two obvious things I want to say about the relationship of young people with AI, which are not going to be very helpful, but are necessary requisites before we can kind of move past that into these material ways to actually benefit from AI diffusion. The first of those is AI fundamentally increases economic uncertainty. I made a different video about this. We'll put it in the cards. Long story short, AI makes the economic future more uncertain for us, and that induces back to right now by basically making us all more risk averse. As in, if you are a completely logical person, what you would do to hedge against the future uncertainty or fear caused by AI is simply to work more, right? Try to make more money. Try to move up in your career faster to accumulate the resources such that those things of the future won't hurt you. Now, again, that's not super useful, right? Just work more. Just try and make more money. Just try and get into a position of influence faster where you're not going to get laid off. But that is also, I think, just step one. We are going to get into a world where some people due to AI are going to try and move much faster and put more effort into their career versus other areas of their life. And maybe you can start there. Again, you don't have to. We're going to look at the very low effort path in a second here. But at the same time, if you are existentially concerned that your field is going to get eliminated by AI, you should probably be working more or thinking more about this or just putting more effort into what you're doing. That's number one. The kind of obvious thing to say, number two, is, hey, just work in a field that AI is going to impact less in the short run. For example, if you are an electrician, you'll be completely fine, at least until Optimus takes over the world. But if you compare a legal assistant to a electrician, right, the electrician is going to have much more of a lead time to kind of adjust to that new world. And they'll be better set up long run to function in an economy, whereas robotics are kind of the mainstay of labor, such as electrical work. But again, that's not going to be super helpful for you if you already have a set career path, if you've been working for a while. But you know what? Maybe that is helpful. Maybe you're considering what career path to take. And I'll just say it. If you are existentially concerned about your field of choice, you can just change it. So with those things in mind, what I want to transition to a little bit then is what I see as the lowest effort. So not that hard way to benefit from AI across whatever field you work in or you want to work in without suffering as much of the consequences of doing so. And what that will look like for most people is basically just either be much better at your job, which goes back to just working more or putting more effort into it. Or what we're going to look at is just better utilize AI. Let AI do the heavy lifting for you. Have AI be a component of your resume and your job. Because if you are the master of AI and that is really easy to do, as we're about to see, then you are going to be that much more resistant to people, for example, getting laid off because their jobs are replaced by AI. So those three steps we're going to look at is a system that gets you fully equipped with minimum effort to deal in an AI dominant world, to put it on your resume as a line item, and to genuinely just basically speed run the whole arc of being comfortable with these different tools professionally. So step one of that three steps to mastering AI, if we want to clickbait it, is you need to be fluent in knowledge of the space. And what that specifically breaks down to, as step one, is you researching and understanding at a basic level, at least the following things, labs, models, capabilities, hardware, and terms. So if you at a basic level understand those five things, you can put that on a resume, you can deal in a conversation with anyone, you can sound technical, and those are what support your understanding of the actual tools that later on you will actually use. And so labs are just the different companies that are developing AI, right? Then the models are, okay, what different models are those companies developing? And also a little bit about model architecture itself, right? What are the different kinds of models? You have image, you have video, what else do you have? And then what's inference versus pre-training, and how do AI models work? And then just the different set of models at a high level, what the industry looks like, and then again, who exactly is making them? And also that's a very short list. There's maximum 10 companies in the world that are seriously making models. You have the big labs, right? You have Google, you have OpenAI, you have Anthropic, and then XAI in the US, you have Alibaba, ByteDance, a few others in China, you have a few others scattered around the world, but that's pretty much the list. Do a little bit of research, listen to some founder interviews, and you're good to go on those two things. On the capabilities side, that's just understanding a little bit of the context of where were these models a year ago? What are they doing now? Where are they going? What's the general direction of the technology? That's also just sign up for a few newsletters, listen to a few talks, and then also just if you start to use this tech, you will get more of an intuitive feel for that over time as well. Then on the hardware and term side, terms, generally speaking, ties into all of that. It's just, again, you want to know what some of those words mean, so if they're brought up in an interview, you're not like caught completely flat-footed. And on the hardware side, that's just, okay, you know GPUs. You've probably heard the term, I would hope, GPU. Why are GPUs so important in AI? How does that relate to the compute landscape, to data centers? How does that play into TPUs versus CPUs? There's also resources out there for that. My honest take, though, is just chat to AI about this if you want to learn about how that whole hardware stack plays into AI. Just talk to Claude. Talk to OpenAI, the app on voice mode for an hour. Just learn a little bit about that. And I think that's that last component in understanding the full soup-to-nuts AI ecosystem from the hardware that builds it to the companies that then develop the models on top of the architecture and then deploy those models via these different features that change and evolve and improve over time. So that is step one. Learn and research those five categories. You do not need to be an expert, but if you put in 10 hours to do that over the next month, you will be in a better spot than 85 at least, if not 95 percent of people. And then you can confidently talk about that. Again, you can put it on your resume, but that's just step one. And then we're going to heat up here with step number two, which is pretty simple, and that is vibe code three new things. I literally want you to open up Claude. Claude's the best for this. If you want to do codecs from OpenAI, you can do that as well. And then just take three ideas you've thought of at some point or come up with ideas by talking to AI or build something that already exists. I don't care. Sit down, vibe code three things. Now, this should be fun. This should not feel like work because you are honestly just creating things and you don't actually have to do the work. You just kind of translate what the AI is doing into the real world. But just do that. Because what is that unlock, right? It unlocks to an employer, hey, this person can go and create things that are useful. You can actually put those three things as line items on your resume. I created these tools that helped me in this career. They actually are relevant to your career. That's even better. And the total effort to do this is like sitting down for 90 minutes, having some fun and basically birthing these three epic new things. And when I say vibe code, I mean, I want you to go through that full process of actually think of the idea, develop it with AI, figure out how it's going to get built, take all the code that the AI builds and actually deploy it, deploy it with Purcell, with GitHub. Locally is, you know, step one there. And if you don't know what any of that means, you're completely fine. AI will teach you. It is really easy. And I promise for like nearly all of you watching this, if you clicked on this video, you're going to enjoy doing that. So that is two steps of three. Step number one was research those five things. Step number two is vibe code, three things right now, not literally right now. You still have to finish this video, but after finishing this video, now step number three is to set up a few projects or workflows that are actually relevant to your life or work or studies, whatever it is right now. This is what I've been saying on this channel for years. It's kind of the highest yield, lowest effort way to measurably improve your life or work right now with AI. And what that is, is just take something you already do often for school or for work, and then try and automate it with AI. And so for this third step, I want you to just go through the motions of setting up that kind of workflow or automation in some of these real world tools. I'll give you three. Clawed is going to be the easiest. So that's Clawed, Desktop or Cowork. And then you can set up some projects in Clawed and go watch another video on that. But basically a project is just a self-contained thing where you can give it knowledge, you can give it context, and then you can set it up so it's kind of this specialized AI that can do something for you. Open Claw, I think would be the second platform to play around with for that. It's a little bit more complex. You have to work in the terminal, you have to install it, but it can do some really cool things as well. And then also we just reviewed the Axio Work Platform Launch. That one I think is really good in terms of just the UI UX ease for playing around with workflows and automations. So take one or multiple of those three platforms, figure out three things in your life that you can automate or that you can train an AI on, and then just go and set those up. And I'll give you one material example there. Let's say you work in a white collar position and you have to draft a end of week report that's sent out to your team. Do this, go to Clawed, set up a project, call it End of Week Report Agent. Then you're going to take the prior 52 reports that you've done. Let's say you've been at this job for a year. You're going to feed them as context into the AI. And then in the little instructions panel, you're going to say, what I'm going to do is feed you the inputs every week or the data to put on this report. You have an example of all the previous reports that I've done. When I feed you that data, I want you to create that report following the same format, the same style. Just pick up the legwork, do the manual stuff, make it easy for me. And then now, every week in the future, you just plug the raw data in and Clawed does the rest. And then every week in the future, you just save three hours because you don't have to build that report anymore. And once you build that muscle or just play around with that for a few times, then you can start to look at everything through that lens of, can this be done more efficiently in this way with these tools? Maybe it can, maybe it can't. And that's a skill that you can put on a resume that you can share with an employer that your boss will like if you can now work three more hours per week on more important things. And I'm not making some statement that everything can or should be done with AI. But for most people, there are very material ways where you can be more productive, save time, save effort by going through those very simple setup of workflows. So those are the three steps. Step one, research those five things. Step two, vibe code three things. Step three, set up three workflows or projects inside one of those tools. And beyond that, go deeper if you want, go crazy. But as far as just get the basics out of the way, and if you do those three things, you will be in a better spot than 96% of people. That is my take on how to do that. And I wish you luck in the changing world, but I have faith that if you are diligent, if you try and learn these tools, I think it'll work out. And if it doesn't work out for you and you did all those things, then that means it won't work out for anyone. And then we'll probably be in a UBI type spot, but who knows? Regardless, I appreciate your time being here. I hope you found this one useful and I will see you in the next one. Cheers.