How To Use AI Better Than 99% Of People (3 mental models)

No said it's not about junior or senior. It's about good with AI or not good with AI. But what does it mean whether you're good with AI or not? How do you judge that? I think there are two things we have to look at and shift our thinking around. Number one is fundamentally now what can you do with AI? And number two is how are you going to do that thing with AI? The second you're using AI, you can now promote yourself to be the boss. And I'd argue that you want to promote yourself to the big boss with a B. What I mean by that is I see lots of people online who were saying, "Oh, you know, you can use AI agents as your assistant now. " Or, "Hey, when you use LLM, it's like a smart intern. " And this way is yes, thinking about I'm no longer the last person in the rank. I have an intern that I can use. I have an assistant I can use. So yes, you've promoted yourself. But think about the difference of what you can do if instead of building an assistant, you decided, I'm going to build a chief of staff for me. Yes, an assistant helps you protect your time, your attention, right? This is 1,000% the limitation of knowledge workers is that a thousand people and a thousand things are pulling us in different directions. And we need to be able to manage that energy and manage that time, manage our calendars and our todos to get those things done. And yes, an executive assistant can to a certain extent understand what should be prioritized, what are the things that are important and kind of fit pieces together. So we do get leverage from an assistant. But if you bring your big boss energy instead of an assistant, you're thinking about my AI agent is going to be my chief of staff. Then you'll realize, okay, this agent is not just helping me manage my time, protect my energy, they are my thought partner. They are going to turn the visions that I have into something that's executable. The chief of staff also manages a team of people, a team whether it's real or whether it's other AI agents who can then do more things. So your leverage just jumped from yes, the assistant can help me manage my calendar to yes, my chief of staff can then manage more people to get more meaningful things done. And the type of conversation you're going to have with this chief of staff is going to be fundamentally different than the ones you're going to have with your assistant. With the chief of staff, you're mapping out priorities, mapping out opportunities, possibilities of which direction you should go, all of the things that you can explore and the type of work, the type of thinking is going to be higher order. Right? So, we're moving up the bloom taxonomy. A lot of people ask me, "Oh, so what do you think about uh AI making you more stupid? " Like, yes, if you decide to use it at a lower order thinking capacity, if you tell the AI, hey, you are going to help me think through how to organize my calendar. Yes, you're that is the type of work that you're going to be doing. And if you say, okay, yeah, whatever you say is right, I'm just going to use it. then yes, you're not actually elevating your capacity of what you can think about. But the AI is also a mirror. If you say, I want to do higher order thinking, so I need a thought partner that has that kind of capacity, then you're not going to become more stupid. you are going to think about, okay, for my chief of staff, they're going to need all of this context, plus they're really smart and they have access to all of these other research that I can never read through with my entire life on Earth. Then you're naturally going to get smarter and think about problems in a deeper way. Use that leverage in a different way. So, I'd argue bring that big boss energy into what you can do. You can just say from today on I'm the boss with a big B. I'm Bowser in Mario rather than one of the mini bosses. Having that flexibility in who you see you can become is such an empowering part of this technology. And I'm not saying that, you know, just by telling AI, hey, now you're my chief of staff, it can do all of these chief of staff things and help make everything happen. No. But how you think about what you're going to provide it and how you think about what kind of ideas you're allowed to work on fundamentally changes. That's not a small feat. You are being empowered by the technology. And it doesn't limit you from having an assistant and a chief of staff, right? Yes. AI is not quite there yet in order to perform all of the things that a human like experienced chief of staff can do. Fine, but we also have to think a little bit further into the distance of the day when it is able to. You've already shifted your thinking to match that capability. And there is no one saying you cannot have an assistant that is perfectly functional through an agent as well as a chief of staff. It's just that we have to change what we think we can do and that is the main thing. So this is why seniority doesn't matter anymore. Right? Previously we can have people who are managers or you know execs and we look at them and we think oh I don't think you actually can do all of these amazing things. I don't think your thinking is really that clear. So yes the role that you know people are given doesn't matter anymore. If you have the brains, experience of that exec that you think, you know, is not performing. Well, now with AI, you can just give yourself more capacity so you can function and do the work that person does. And in the workplace, the number one prerequisite for promoting someone is they're already doing the work of that role. So, you can literally just go do that. But this also means that if you are a leader, you are someone who already manage teams. You're someone who knows how to delegate, how to think at that more strategic level, higher order thinking. You know what are the things that you want to be working on. Well, now you can just maximize that and scale that ability to not just the physical team that you have access to, but also a team that doesn't stop 24/7. And that again exponentially expands what it is that you can actually do. So if you're searching for that meritocracy of hey I have ideas I think clearly I can get stuff done then there is a clear progression forward and you have a lot more resources than you had just a year ago.

ago. All right now that you're bringing the big boss energy how are you going to do the work? How is it going to change from what it is that you do before you got promoted to boss? There are three things and for sake of simplicity I think you should spend 33% of your time on each.

The first one is learning because uncertainty now is the only thing that we know is certain for the next 10 years. Every single second there seems to be news about something is fundamentally changed again. Oh my gosh, now we can do this. And we don't want to fall into this frantic AI guilt and AI overwhelm and just chase and to keep up because that only creates more distraction for ourselves. Instead, I suggest you learn to change your behavior. So what I mean by that is when I say learning most people will think yeah you know I already learn I consume a lot of information but that is only the first part of the process right getting input to understand something new okay that is part one learning is a process and at the end what you want to do is change your behavior because if your behavior stays the same then there was no point in learning and because we're thinking about that behavior we're thinking about internally what is that change I want to make so it's not about chasing the news of oh AI can now do this, that. What do I want uh to make sure I keep up on it's rather what is the behavior that I want to change now to get a different result and let me focus on that. Having that internal clarity then give you a better map of how you're going to learn. Okay. So basically remember you're looking for that behavioral change. Input is consuming. Everyone knows how to consume. All right. But you have to take it further. It's a process. Right? Then you map it to your current situation. Then you find what is that behavior I'm going to change. You're going to make that change at least once. And you're going to let feedback to tell you, oh, now that I made that change, is that the one that I want? don't want? And use that feedback to continuously learn and be your input. So now you have a learning cycle and you're spiraling upwards. It's not okay, I watch Vidi's video on why you have to take notes during AI. it is I watch that video, okay, that I said I'm going to start taking at least three notes today. You took the three notes and then you looked at them and said, "Okay, did this help me? Did I take the right notes? How do I want to move on from this tomorrow? take three more notes or do I want to focus on something different? " You are actively engaged in this process of learning. Take that feedback, make that into your input. Then maybe it is you go back to the video and say, "Okay, I actually don't know, you know, what kind of notes I should be taking. " You look at the video again. Now something else pops out. Okay, I'm going to try it again, right? I change that behavior and I watch the feedback and that way you actually get something out of the learning. If you have not made a change, whether it's a behavior, whether is you made a decision about something that you were undecided on, then you have not learned anything. You have to change some sort of pattern in your brain in order for that to actually sink in and be helpful to you. The whole process, the whole loop of learning has to happen over time. And this brings us to the

second thing you want to shift how you think about it, which is create. And again, I don't mean the single act of creating something new or something original. rather again it's a process from identifying a problem understanding that problem coming up with a solution create that solution and then get feedback of does it actually solve the problem is this the problem I actually want to be solving for and you continuously spiral upward again creativity is a proxy for intelligence right this is why everyone's going crazy when all of the LLMs can generate things they can generate gen you images, they can generate you onepager documents, they can do powerpoints, they can do all of these things. That's why we think it's intelligent. And so at a fundamental level, you need to be able to create outputs. But the difference is you don't want to be creating in the pre-ai age, right? Pre- Big Boss age of someone told me to do this and this is why I'm creating this output. No creation is this whole thought process starting from identifying a problem. You are the one who should own that problem. It's not that oh you know the company's strategy team came up with this problem and now I'm just a cog in the system trying to fix it. No, you are the one looking for that problem. Okay. [snorts] Then you shape it, you understand it, you start to create the solution for it. Let's bring it back to what we did in the first um thing which was learning as you were learning you know how to use obsidian to take notes in the age of AI and you realize okay wait a second I find it really difficult because there are notes that are about ideas and there are notes about practical todos perfect right now you have a problem that you've noticed and then you start to understand this okay actually I realize that as I'm looking at a very practical to-do versus my ideas, I notice that at the core of it, I'm thinking in very different ways. When it's about an idea, I need to focus. I need to diverge. I need to think about all of the related ideas to go deeper. But when it's something more practical like a to-do, I'm very much converging onto what is the next step and I'm pushing it forward and I need to use other tools like you know the internet or some LLM and I'm moving all over the place. So now we understand the problem. There's a different thought process happening between the two. Okay. So the solution I'm going to do is to start two vaults. Yeah. One vault is about ideas. Another vault is about the practical to-dos. And I'm going to try it out. So then you go on your Obsidian, you create a new vault for all of the things that are practical. And then you test it, right? You say, "Okay, now I'm going to take notes for the next 3 days. " And then you might say, "Yay, it worked. Awesome. " Right? You've created something that is your own. or it's oh gosh it's not working I still need to refer to some of the stuff in the other vault all right so then you identify the next problem of there still needs to be some integration then you go through the loop again and by the end you have something that is uniquely yours right from my video of hey you should take notes um when you're using AI to now hey here's a specific thing that I can apply the knowledge to learn from and then create something that's my own. And now, you know, if you want to you create your own video telling people, hey, if you also have this problem of not being able to separate idea space and the practical space, here's what I tried and it worked. You are now reclaiming your thought process for yourself, right? It's not about Vickiy's going to tell me what to do. Yes, she got you started, but because your situation is uniquely yours and you want to achieve things that are uniquely yours, you have now we have now merged our ideas to create something that works for you, right? You are in control of that higher order thinking process, which is awesome.

awesome. All right, the third thing that you want to focus on based on these two steps is now systematizing. Remember, you're the big boss. So, how do you get other people to achieve outcomes that you want at a standard that you like is to systematize workflows so they don't have to start from scratch so they can leverage your experience and what you like and what you found over the years and be able to do that instead of always waiting for you to do it. So again, a higher order cognitive ability is to take all the knowledge in your brain and make it explicit. Take that test of knowledge, make it explicit and create workflows for others that can follow it. And good news is of course AI is awesome at doing that. If you already have experience running teams, creating standard operating procedures, SOPs or any other workflows that you create into a little tool, a little SAS, then you know what I'm talking about. This is how you get scale. And this is why you see in every single agent harness, whatever it is, claude code, you know, codeex, manis, they all have something called skills. a way of doing something for the agent to understand so that whenever it does that thing, it goes and checks, oh, this is how I'm supposed to do this thing as opposed to make it up, right? Because you can leverage what you already know with your agent. This requires you to do two things. One is take something vague

and break it down into steps. If it's taking notes, it might be, oh, you have to have some metadata and then you want to write the core idea. tag it and you want to link it to other nodes and so whether it's you or whether it's a human teammate AI agent can follow how you think through this process. Now the second

thing you want to do and most people stop at the first thing so focus on the second thing and it's bringing out emphasis and identify leverage points. What I mean by that is the problem with SOPs is, you know, if you got on boarded and people just gave you a document with, you know, steps one to 100 and you look at it, you're just like, "Okay, I I'm not really getting any of this. Sure, I I'll try it and see what happens. " But when you actually use a process, what happens is the person explaining it to you usually tells you, "Oh, and this step is really important because you know if you don't do this, it'll mess up something later or it's, you know, 8020 in this process. The most important thing is the research that goes in because garbage in garbage out. If this process, this part is not done correctly that everything else is not going to give you the right answers. So you need to be able to clearly articulate where is the emphasis, where are the leverage points that matter more than all of the other documents, right? Which words have more idea density to them. Let me give you an example, right? One of the things that people always make is some sort of document, right? And you say, okay, to make this document, you follow steps 1 to 10. And then where do you put the emphasis? One great one is quality. What are the things that you want to check in order to ensure quality? So you call out, always double check numbers, always double check dates, always double check the fonts that we use whether they are consistent or not. Just by placing emphasis for this SOP of just, you know, 10 steps. Now both you and your human teammate and your AI teammates can all understand, oh, I need to doublech check the quality parts of this because people usually mess up with numbers. this. People usually mess up uh the font and the font sizes. Same idea. We can also apply something like 8020 to the document, right? Okay. Steps one to 10, but focus on step number one, getting the right data and the research in and spend most of your time there because if we don't have good data, research, then the results are just going to be garbage in garbage out. And

now the third thing you want to be able to do while everyone stayed on the first thing is you want to see how you can connect this workflow and improve it over time. And you might have noticed this pattern right before Big Boss U. It was very much okay do this thing and then you say okay I've done it. It's a completion logic that most of us have of just okay here's a task let me finish it. But as the big boss you understand it's not about just finishing things. We want to be better at doing something because you understand that there's multiple ways of doing something and getting to a result. And AI is really great here, right? that you know most of the agents not only can write their own skills based on just going through uh once doing a workflow with you but as you're saying no change this change that you can prompt it to say hey now update that skill to make sure that we capture all of these uh nuances that we didn't capture before. This is how you make your work compound. Thinking in loops is really important. And coincidentally, and probably not so coincidentally, the difference between an LLM that works with chat versus the LLM that becomes an agent is that the agent takes time to go through a loop. And we want to go from a completion logic, which takes, oh, you want a let me give you a to, oh, okay, you want a let me think through what is the plan for getting you to A. What are all of the things I need to take into consideration? what are all the tools and skills I have? Let me create it and then let me double check. Does that actually get you to A. And you know this is the same with any human teammates that you have, right? When you have an intern, they come in and yes, they give you I you want a I give you a I don't think about, oh, how is a going to be used later? How can I make a better? I just create it and throw it back to you. You tell me if this is good or not. Right? And that's the frustrating part. Whereas having someone who think in loops, whether it's you, whether it's your AI agent, whether it's your human teammate, by learning how to think in loops, they think for themselves and they recognize, oh, actually these things can be improved better. Actually, I need to think about, oh, how can I improve it? And I can make suggestions. Hey, you said steps 1 to 10, but I think we should add and tweak some of these steps in order to make it better. And the Japan Airlines CEO Totoisa had a really good analogy for this, which is they think about passing on the baton the best way that they can between teams. Japan Airlines is known for their great quality in customer service in an industry that have so many moving parts. So how do they think about it is in loops. They think okay I am the ground staff. When I pass the passengers to the flight attendants on the plane, I don't just say hey here you go, right? I think about, oh, what are the customers going to need on the flight? What are the flight attendants going to need to know when people are boarding? And let me pass that information in a way that helps them so that once they're on board, they get the best service and they're notified of the things that they should know. And the crew on board then thinks about when the plane lands, what are the things that we need to communicate in order to make sure the next team has some emphasis to oh, what should they be focusing on as they're doing their part of the job? And the cycle continues. So if you apply it to a work place situation, it could be it's the marketing team thinking about okay, how are we going to talk about this product? Thinking that eventually all of the prospects get passed to the sales team. And the sales teams need to know one to three about each of the customers in order to close the sale. Sales team then think about the fulfillment team. Okay, we've closed a sale but the fulfillment team needs to know customer A is really focused on this one part of the product. So they need to know that to give that better experience to the prospect uh to the buyer. And the fulfillment team then thinks about the next thing customer service. Okay, these are the questions we always get. So let me make sure we pass it on to the customer service so that they can better help uh clients whatever it is. By just thinking about the next part of the loop, you help create this loop thinking inside your organization, whether it's human run or AI run or a hybrid of the two. The fundamental change we're making is to go from get things done to actually having your point of view on what should be done and how to do them. You can use AI just as the supercharging engine for getting things done. Right now, you know, everyone's expecting more of you to do more with less time. So, you just say, "Okay, AI, do this. I'm not going to bother, you know, really checking how things are going. I just need to send these along. " Yes, that's one way of doing it. But a better way of thinking about this technology is to now exercise your point of view on what it is that's worth doing and how you're actually going to do it. Right? By what we talked about earlier, whether you choose AI to be your assistant versus your chief of staff, what are you going to talk to it about is your point of view on what it is you want to spend your time and energy on doing. Then it's about how to do it. We talked about being able to learn, being able to create, being able to turn them into workflows. You notice that the workflows are not standardized unless you let AI tell you how to do these things. Every single step of the way, we talked about how do you adapt it to your own situation using the loop. So, what you're doing is exercising your point of view, building your point of view. Your skills on how to create a document might be different from my skills of how to create a document. We have different goals. We have different experience. We have different of what we decide is right or wrong, good or bad. And so that is a very empowering and freeing idea, a very human one, right? Is that you are at the center unless you give that power away. You have that choice. When output becomes cheap, then we get a lot of quantity, which can be good and bad. What we usually do is, "Hey ChBT, give me 10 ways of saying this difficult thing I've been thinking about telling my boss. " Or it's, "Hey Claude, give me 10 ways to get from LA to New York. " Okay, fine. This helps us decide which one is better, which is a good thing. But also, it's the same thing that leads to AI slob, right? Is, hey, just create this output. But you notice what we're not thinking about. The next step is quantity begets quality. Yes, currently AI swap is a problem, right? Because people are still stuck in that getting things done mentality, that completion logic of I just need to create output and put it out there. But you don't have to stay there. But you have to think about the next step, at least for yourself, of how I'm going to use that quantity to get me to better quality. And for me, quality comes from three things. If you're going from zero to one, it's about better exploration. Previously, we were limited by our time, by our energy, by how much we can find, by who we have access to help us do these things of finding good research, finding good data, finding talking to people, right? But with AI, we can think about exploration in a whole new way, right? We can do so much more research that's targeted that's wasn't possible before. Quality comes from better loops. So like what we talked about, if you have something that you're optimizing towards, you can use feedback. Andre Kaparthy, one of the founding members of OpenAI, he created this tool called Auto Research, which continuously loop as an agent until it gets you better results. And it learns how to do all of those and build that feedback into its own skill. Right? That's now possible. And quality comes from better criteria of your point of view of what's good and what's bad. This is not an absolute. There is your taste, your curation, your judgment that comes into okay, I like this red one versus this blue one or I like writing that sounds like no versus nim tallet. It doesn't really matter but it's for you to be actively involved in the whole process of thinking and creating developing your point of view is crucial. So coming back to it's not about whether you're a senior or junior. It's about how good you are with AI and by good it means how are you thinking about this partner? Where are you positioning yourself? How much of your yourself are you bringing into this collaboration with this tool? I hope you will bring that big boss energy. Let me know what you think in the comments below and I'll see you in the next video. Bye.