How To Think Like The Top 1%

Mental models are powerful. Some of the most successful people in the world swear by mental models. Mental models are basically simplified representations of how the world works. You take something really complicated, you simplify it into a framework that you can then use for decision-m and problem solving. For example, a mental model that I really love around decision-m is the expected value model. This model Says that instead of thinking about decisions as being either good or bad decisions, you think about each decision as having a set of positive and negative consequences. That we should make decisions

that give us a repeated high probability of winning on average over the long term rather than just oneoff. I think this is a great mental model. I use it all the time. I teach the professionals that I work with. It's such a useful model that it's become Standard in a lot of fields revolving around decision-making and probability like trading and finance and professional poker even. So, in this video, I'm going to share with you six of my favorite mental models. But these aren't just regular models. These six are very special mental models. In fact, one

of my favorite books of all time is probably this one. It's 50 models for strategic thinking. But here's the thing that I've observed after teaching mental Models to so many people. What I've realized is that mental models are not enough. Regardless of the actual model that you use, the way that you apply your context and knowledge and situation to the model can make or break how effective it is. For example, I previously worked with this data scientist for this large e-commerce business and they were trying to make a decision about which email campaign to use.

And so by looking at the past data, He estimated the probability of making a certain amount of money for each campaign and decided that campaign A is the one that has the higher probability of delivering higher profit than campaign B. So they went with campaign A. They lost a lot of money. The issue wasn't just luck. The issue was that the past data that he was looking at was in the holiday season and the way that that campaign performs in the holiday season was very different to how it performs in The off season. So even

though he was applying this expected value model, he just missed an entire factor, an entire variable that would have changed his equation completely. This is actually the reason why he reached out to me in the first place because it seemed like an impossible problem. How do you know what you don't know? Yes, you've got a model. Yes, you have your knowledge. How do you know you're applying the model in the right way and you don't have gaps And blind spots? And so, this aspect is what I want to focus on in today's video. The six

mental models I'm going to give you are not just regular models because they're what I call meta models. They are the mental models that you should apply whenever you use any other form of mental model. And the first meta model is called nonlinearity. In the example I gave before with that data scientist, the mistake he Fundamentally made was that he believed that a certain campaign, so let's say this campaign is called A leads to a certain level of profit or a certain level of result whereas campaign B led to a different kind of result. And

so this is an example of linear logic or linear thinking where we say A leads to result number one and B leads to result number two. But in real life relationships and logic is rarely linear. In real life it's not like this. It's more like A and B uh influence each other in the presence of C under the condition of D which also relates to E. And all of these things combined when going through F leads to a certain type of result. And so there is this uh incentive for our brain for the human brain

to try to find simplicity to find the the easiest way to understand something. And it's very tempting to see relationships and logic as linear. But if this is the true nature of a Relationship or a logic or how things actually work, then any attempt to turn this into something that's linear is actually going to be incorrect. And so the meta model of nonlinearity means that by default you should assume that relationships are not onetoone and linear. You should assume that anything that is complex and multiffactorial is nonlinear. And what that means is that when you're

thinking about the decision or the problem, you actually want to Catch yourself on linear thinking. So this is your your takeaway. First of all, detect and be wary of linear thinking patterns. As you're thinking through a problem or a decision to make, if you notice that you're thinking in a very linear way where there's a onetoone relationship, if I do this, it will lead to this. Whereas, if I do this, it will lead to this. If I want to achieve a certain Result, I need to make sure I do this and then I do this

and then I do this and then I do this. That kind of pattern of thinking is very fixed, rigid, and most likely inaccurate. So, catch yourself when you're thinking in this way and challenge yourself to think more nonlinearly. A great exercise for this is to actually try to map out the relationships between the different factors or the different Variables as part of your problem or your decision. So a complicated decision or complicated problem is not complicated because the universe deems it so. It's because in order to achieve a certain result, there are so many different

factors and these factors all relate to each other. It's this complicated web of interactions that makes something complicated or difficult in the first place. And so what some people will try to do is they'll say, Well, it's so difficult to think about this. If I still want to achieve this result, the easier way is to just not think about this at all and instead oversimplify it with linear thinking. That is not going to be effective for guaranteeing your result, obviously. And if you fall into this trap, then of all the hundreds of different mental models

that you could be using to solve a problem, you're not going to know which one is the most appropriate for this. You're going to think, "Hey, because I've simplified this issue, I can use this mental model and that gives me a nice clean result that I can feel good about." But maybe if you thought deeper about the problem, you'd realize that that mental model doesn't actually make sense in this context or it's it's being applied too forcibly. Maybe there's another model that you can use instead. Again, the mental model is there as a tool to

help you to make this decision And to simplify something that's really complicated. But in order for that model to give us a useful output, it depends on the input we think is relevant to give it. So the activity of actually deliberately sitting there and mapping out all the different variables that we think create this complexity is an excellent exercise. So when you try to map out these relationships, the first step is just to list out every variable that you think just literally dump them. Dump them out. list out every factor and variable that you think

could be useful and relevant in thinking about this problem. And then you just go through this list and try to see how these things influence each other, how they're connected. So in that marketing campaign example, maybe we've got some words like uh the type of audience, the timing or the seasonality of the campaign, the different channels of distribution, the actual content of the Campaign itself, the offer and the perceived value of the campaign, the size of the audience. Okay, whereas this is like audience like demographics, maybe even like data attribution in terms of how good

your data tracking is and how reliable your data is. So this might be a bunch of different words to represent the factors that make a decision about which campaign is going to be more profitable. And so as we look at this, there are Lots of possible relationships like okay, well we know that the audience demographic resonates with a particular type of offer. But then also we know that the the timing and the seasonality also influences the perceived value of that offer. And also we know that the the the content of the campaign itself is going

to frame that offer in a certain way. And the content obviously is depends on the timing and the seasonality. And this audience also Exists within a certain type of channel. Like some people might be on emails whereas some people might be on Tik Tok versus some people might be on Facebook in terms of how profitable this entire thing actually is, which is the the point of this campaign. Well, that's also going to depend on the audience total size as well as well as the you know the quality of that audience and how much money that

they have to spend. So this is just a very simple example Just to show you you know this you can see that there's lots of different other ways that you could have arranged this. This is just one example. But then as you go through this uh just by going through this process of thinking about what's important and how it all relates together and uh what are the factors that influence the profitability you know we might realize hey we've actually completely forgotten about an entire variable which is you know the cost to Run the campaign you

know and then as soon as we add this additional word of cost in we might think okay well now that that also makes a difference because different channels have different costs and different audience demographics are more costly. to market to. And so we're now seeing the complexity of this decision. And when we get to so many arrows going everywhere, what happens is that we look at all of this and we say, okay, this is The result that we want. And this is all the stuff that makes it complicated. So the solution here is not to

say, well, let's just ignore all of this because it's too hard to think about. It's to go through the process of trying to think about it so that we can gain more clarity and organization about this complex thing. Because as we think more about the complicated part, it helps us unwrap this and over time it becomes easier and more Intuitive for us to understand and that is what contributes to the problem being actually solved and getting the result that we want. And the reason I recommend doing this mapping activity as a key takeaway to actually

try to challenge yourself to do this and to feel that complexity and feel that mental burden is because if you're trying to make a complex decision or solving a complex problem and you don't see how the pieces fit together, you are going to have to Pay the consequence of that through the quality of your decision-making. And again, this is basically an expected value thing. You may get lucky. You may be able to ignore that and make a certain decision and you get lucky with that decision one or two times. But if you continuously make decisions

and solve problems in that way, ignoring the complexity and oversimplifying things, your luck will eventually run out. And especially if the decisions you're Making are important and costly, it only takes two or three times of getting a negative result to undo all the positives that you've stacked up previously. It is much faster and cheaper to get feedback on how good your decision is likely to be by doing this activity and seeing how much you struggle. If you struggle with mapping things out and seeing how it all fits together, it means it's not organized in your

brain. It means you don't really Understand how it all connects. If you did really understand it, you would find this easy to do. And when someone is feeling overwhelmed with a decision, overwhelmed with a problem, they're not sure where to start. There are all these different moving pieces. They all relate to each other in complicated ways. They don't know what to prioritize. They don't know how to make that decision. I can guarantee in every single one of those instances, that person is going to Struggle to map things out. And when you sit down and force

yourself to address that weakness head on, that is when you start creating clarity of your decision-making process, that is what allows this complicated problem to be broken down into simpler components. So just remember, linear thinking is an illusion. That's your brain looking for a shortcut, probably not accurate. Nonlinear relationships, that's the truth. That's reality. If you struggle Thinking in terms of the reality, the question that's left for you is are you willing to either take the risk of being wrong, which might be okay in some situations, or would you rather do the hard work of

trying to organize it and gain clarity. So that's the first meta model, nonlinearity. And so you can see what I mean is that any framework you use, any mental model you use, when you think about how am I going to apply my context and my knowledge and my Situation to this mental model, you need to be starting from a position where you recognize the nonlinearity of what's going on. Otherwise, the way you use that mental model is going to be wrong. And the next mental model is very similar to this idea of nonlinearity. It is

the idea of gray thinking. When I work with software engineers, especially tech leads, one of the biggest problems that they face is uh whether to move fast or to maintain quality. So when you Move fast and you're pushing out new features all the time, it increases the error rate and there's lots of other things and technical debt that builds up. Whereas if you're trying to maintain quality, it reduces your agility and it means that you can't, you know, develop new features as quickly and that could impact the the overall business. And so to resolve this,

some mental models that a senior software engineer might use could be around the decision of should We move fast or should we maintain quality? And there are lots of frameworks and mental models that they might use to balance that decision. But in actual fact, those models would be incorrect. It would be wrong to use those models because that's an example of falling into the trap of black and white thinking as opposed to gray thinking. Black and white thinking is saying that it's either A or B. That these two things are polar opposites and Mutually exclusive

of each other. And just like how it's very rare for things to have a onetoone linear relationship like over here, it's very rare in real life for things to be so black and white. Most things are on a continuous scale. And most of the best solutions are in the gray area in between. By the way, I know someone's going to comment this. It's spelled G R A Y versus G R E Y depending on which country you live in. So going back to that software Example, you can move fast with good deployment pipelines and QA

processes while maintaining quality. You can strike a balance of both of those things. And so you can see when you start thinking in terms of the gray, it means that other types of mental models may be more suitable. The problem is not should we maintain quality versus should we go fast. It is understanding what parts of going fast lead to the reductions in quality. How can we Maintain quality in a lean agile way without sacrificing speed? What are some models of thinking that allow us to increase speed and increase quality? And the reason we are

biased towards black and white thinking by default is very similar reason to why we're biased towards linear thinking by default as well is that it's a cognitive shortcut. In fact, not just a cognitive shortcut, a cognitive emotional shortcut. It is much simpler. It's much easier. It's Much less overwhelming to assume and say, "Hey, this really complicated thing with all these different factors that come together, it's a onetoone linear relationship." Likewise, it's the same thing to say, "Hey, this really complicated decision, it's easier to say it's either A or it's either B." It simplifies our decision.

It creates an illusion of simplicity, but it does so using what's in in in logic and reasoning studying uh is called a false Dichotomy. A dichotomy is when we see things as as two different things. And a false dichotomy is saying we've basically split aside uh two different factors as being mutually exclusive from each other when actually they don't have to be. And so the takeaway for this is in a similar way, catch yourself on black and white thinking. And the best part about this is that you don't actually have to understand the Gray first.

It's enough to recognize the red flag of something being very black and white. And the best example that I can think of off the top of my head is actually uh a conversation pretty recently that I had with our very own YouTube strategist Anv uh who's actually going to be reviewing this video. So, hey, Anv. And I remember a conversation where we're talking about uh different things in terms of uh creating content and and there's lots of different Nuances in terms of creating content and educating at scale. And we were talking about this problem of

how do you create content that really resonates with people that they can relate to when people are so diverse, they come from so many different backgrounds. Do we create content that is broadly resonant with many people but is pretty superficial or do we create content that is deep and nuanced but it only resonates with a a small percentage of the population and What he said at the time was I don't know the right way to think about this but I recognize that the way that I'm seeing this is very black and white which is usually

not true for anything I really understand properly. So it probably means that I need to think about this more. And I think that is a perfect example of catching yourself on black and white thinking and going towards the gray. And you can probably feel this yourself is that when you Think about stuff that you really know a lot about, there are not that many black and white statements that you would be able to make about it. And so if there are things that you're tackling, problems and decisions that you have to make at work that

the way you're thinking about it, you may feel very confident. But if the way you're thinking about it is also quite black and white, then for me that is always uh a warning sign. That's always a red Flag. It doesn't mean you're wrong, but you should explore it. And when you're in that situation and when you realize, hey, I might be doing some black and white thinking. The second takeaway is actually just to do more of this. Engaging in nonlinearity helps you to identify different factors and variables that you might have been missing before and

show you where a gray solution might exist. Now, at this point, if you've been listening Attentively, the question that's probably in your head right now is this is all really useful so far, and I'm finding this really insightful. I wish I'd known this sooner. Why didn't I know this sooner? And in my experience, nine out of 10 times, the reason that you didn't know this is because you're not signed up to my newsletter. For those of you that don't know, I have a free weekly newsletter that I send out. I write them myself Where I

think about all the different models, the meta models, the insights, the principles that I think would really help you learn more efficiently and also manage yourself more efficiently. All the things that you need to be a well-rounded, effective professional. These are things that I've distilled from my years of working with so many people. And each of these newsletters could probably be its own YouTube video. So, if you found this video useful so Far, then I'm sure you're also going to love my newsletter. Again, it's totally free. It takes a few minutes to read. If you're

interested in signing up, I'll leave a link to that in the description below. Now, the third meta model is what I call AAM's bias. Now, there's this thing which you may have heard of called AAM's razor. I first learned about this in medicine. Okam's razor says that the simplest explanation is probably the right one. So, if someone Comes in and they've got all these different types of symptoms, like they've got a headache and they've got a fever and they've got a cough and they were sick before and they've got this rash all over their body

and they're finding it hard to breathe. It's more likely that there's one disease with all of these symptoms rather than like five different diseases occurring simultaneously. It's named after William of Okam who was this 14th century Philosopher and it's called Okam's razor uh because the term razor apart from meaning like a blade in logic refers to a tool which cuts away unnecessary possibilities to make decisions easier. So another razor is called Alder's razor uh which is also called Newton's flaming laser sword which states that if something cannot be settled through experimentation and observation then it's

not worth debating. It basically means that this is going to be a a Futile endless debate that no one can really prove. And so AAM's razor is really good because it forces you to be consilient in the way that you look at evidence. It means that if there's lots of different factors that are popping up, don't just say, "Hey, there's lots of individual things." It kind of forces a level of nonlinearity, which is a good thing. And it says, "Find the underlying cause that ties all of it together." You're sort of like a Detective doing

like a murder mystery with all the like the crazy photos and the string corkboard thing going on the wall. But I'm not talking about AAM's razor. I'm talking about AAM's bias. I call it Okam's bias because this is what I see happening when people use Okam's razor too aggressively. And the issue I see is people doing over attribution where they see all these different symptoms and then they force it to fit a single cause because that's the simplest Explanation. And so this can actually be really dangerous because it may not be all caused by the

same thing. For example, when I was working in the emergency department, people come in for heartburn, stomach pain all the time, like every single day, dozens of people. And when you're assessing someone that's coming in for like heartburn or stomach pain or something like that, you always have to be careful of diagnosing all of that as gastritis or reflux because what It could also be is a heart attack. Pain occurring here is not so far from pain occurring here. And every doctor has heard horror stories of having a patient assessing them as having just like

a pretty benign, you know, acid reflux or heartburn issue, but then it turned out to be an underlying, you know, heart problem. But the thing is that there is a temptation to just say, "Yes, this is just heartburn. It's just acid in your stomach. Nothing to worry about." Because working someone up and and investigating them and treating them for a heart problem is much more complicated. It requires a lot more work. And when you're a busy doctor working in emergency, you've already got endless amounts of work. You want to make life easier for yourself. And

it's the same thing outside of the emergency department. In any profession, you don't want to give yourself more work by turning something that could be simple Into something that is unnecessarily complicated. But we have to understand the risk that oversimplifying could lead to error in medicine. Actually, this is such a big problem that not only is this issue like drilled into us constantly during medical school and in our training to make sure we don't make this mistake and we still make this mistake, it's actually got its own term which is called Hickham's dictim which basically

came around in medicine to counter AAM's Razor. While Okam's razor says that the simplest explanation for all these symptoms is probably the most accurate, Hickham's dictim says verbatim, patients can have as many diseases as they damn well please. It states that reality doesn't owe it to you to be simple. How easy or difficult it is for you to understand doesn't matter. And so here's the takeaway for you to avoid AAM's bias is first of all be aware of the cost of simplification. Whenever you're simplifying an issue and there's lots of different components and you're trying

to find, you know, one way to attribute all of those things to progress on your problem or your decision, remember that any step of simplification increases the risk of some kind of error. you're losing some level of detail every time you simplify. Sometimes those details don't matter. It's just noise that's preventing you from making a good decision. But Sometimes those details are crucial. What's important is not to just say don't simplify ever because that's going to slow down your your pace of execution too much. Simplification is a cognitive shortcut and cognitive shortcuts are not always

a bad thing. What's important is to recognize the cost of that shortcut. What risk are you now exposing yourself to by having simplified it in a certain way? Which factors are you choosing to remove? And again, if you haven't done This nonlinearity piece, it becomes really hard to do this because you're not even aware of what you're losing. All you're doing is you're taking what is a vague sense of overwhelm and you're turning that into something that feels simple. You have no concept of the risk you're exposing yourself to. And this ties into the the

second part, which is when you are simplifying something, be mindful. Are you simplifying it because you just you're lazy or you just Can't be bothered? Or are you simplifying things to reduce the amount of noise? Simplifying things to reduce the amount of noise and make a better decision is a good thing. Simplifying because you just can't be bothered or it takes too long or it's just too hard to think about how it all connects together is not useful. You can get to a point where you see how everything comes together and you know what's important

and how these different factors Influence each other and make the educated decision to remove some of those variables because you don't think it's going to be important and now you create a simplified representation of the problem that you can now put into the appropriate mental model so that you can work through that framework and come to a decision or solve that problem. Now that's very different to again that feeling of overwhelm. This is very vague concept that there are lots of things Going on and because I want to make it simpler, I'm just going to

only focus on the parts that I immediately am aware of and find intuitive which again reality does not owe it to you to fit what you think is intuitive. Now, when you do it the first way and you see generally how it connects together, you've done like sort of this nonlinear map, you may still be wrong. You may decide to cut away factors that you don't think are important and then you run your Experiment. you you get your data and you find hey actually that was important you it doesn't mean that you are guaranteed to

be in the the most optimal place every single time but again it's about the expected value there is a higher probability that you're going to mitigate huge risks there is a higher probability that you're going to get the result that you want when you make decisions in this way and you approach problems in this way consistently over Time you're more likely to win whereas If every time you're faced with something that feels overwhelming, your response is to oversimplify it by just cutting away everything else and not thinking about it over time, you're likely to lose.

And I'll give you a little pro tip for this one. And this this can be your third takeaway is learn to be okay with black boxes. Black boxes are basically areas of uncertainty, things that you don't really know how it All works, how it all fits together. you know that there's this sort of clump of of concepts that relate to each other and it's pretty complicated and you don't really want to dive into it. Even if you can't explore that, you might not have enough time. It might be too complicated. There is a big difference

between seeing the black box, appreciating and recognizing that it's there and then making a decision versus ignoring the black box, not even knowing Which variables or factors you might be missing. The difference is that when you make your decision, when you solve the problem and you get real world data and feedback on how effective it was, whether you got the actual result at the end of the day, when you get this feedback coming back to you, if you knew that there is this black box part of the process that you didn't quite figure out, you

can turn to that black box and say, "Okay, maybe I need to dive into That a little bit more. Maybe this part that I thought wasn't important actually is more important than I thought. So now it's worth my time to explore that because I need the result. Whereas if you didn't even do that level of thinking, you're not even aware of that black box. You get this result that you didn't expect that is not desirable and then you don't know what to do with that. You're not learning from that experience. It prevents you from being

Able to think and process failures and data points in a productive way, which significantly slows down how fast you're able to iterate and learn from that experience. So that's AAM's bias. See reality for what it is. Don't simplify things just to make it easier for yourself and then expose yourself to to tons of risk. Now, one of the most common reasons that I see people oversimplifying things in a way that is inaccurate and not catching themselves On the fact that this is an oversimplification is this fourth meta model, which is framing bias. I'm just noticing

that my S's just look like backwards C's. But if you zoom in enough, you can see that there's a little squiggle there. So that's an S. Anyway, I want you to remember this statement. Just because it's logical doesn't mean it's right. Information can be organized. Problems and situations can be categorized in any number of Different ways. And sometimes that way that you categorize it is not only logical, it's also practical and effective. The issue, and this is what framing bias is about, is that the way you think about a problem or a situation or a

decision you need to make shouldn't be restricted to the way that it was presented to you, the way someone else organizes something, the way someone else categorizes something. If someone presents something to you in a way That's like here's A, then B, then C. When you first consume that, it may feel very logical to think about it in that way, but you have to have the cognitive flexibility to recognize that that may not be the best way to think about it. And in many situations when there is an existing problem and lots of people are

thinking about it in a certain way and finding it difficult, the way to break through that problem is to frame that problem differently. the ability to Break free of existing structures and ways that people tend to think about something and having that flexibility to see things laid out and organized differently creates immense value in the professional world. This is what I was saying at the very beginning is that the difference between a great worker uh and a great thinker versus someone who's just average is not really about what they know. At a certain point, everyone

knows enough. The difference is the Person that knows how to think about a problem in a different way. So simply put, framing bias is when the way information is presented to us changes the way so changes how we think about that information. So if I say here's a problem, here's a situation. It's basically A and B and we need to get to C. And so you say, okay, there's A, there's B and we need to get to C. Cool. And if that's the only way you think about this problem, you are likely to run into

framing bias because perhaps actually the true solution is to say, well, hold on. You've said that it's A and B. But to me, A and B actually sound like the same thing. And it feels like there's something else that leads to C, which is this other thing, D. So, isn't it perhaps A plus B being one thing with D leading to C? Isn't this the right way to think about it? And the situation I See this all the time, the most common by far are technical disciplines where there's usually lots of different information and there

are existing frameworks and models on how to think about things. And these frameworks and models tend to be very utilitarian. They're very practical. They allow you to have these cognitive shortcuts that you need to use every single day. So these existing frameworks exist exist to speed things up. So in medicine a really Common framework that people think about all diseases through is what's the history? What do people say when they come in as a patient? What are the signs and the symptoms? What are the investigations like the blood tests and the the x-rays and the

CTS that you can do? What would you find there? And then what is your treatment? Sometimes you divide that treatment into what do you do acutely right now versus what do you do chronically. 90% of every single Disease can be categorized through that framework and 90% of the time when you're learning these diseases you're learning it through that flow. The same thing is is common with uh software engineering where there's an existing software development life cycle. There are existing frameworks. So when people think about problems with software, they think about it through this framework of

the software development life cycle. But the thing we have to recognize is that If there's a specific problem you're solving or decision that you need to make that's particularly complicated, it's not likely that that framework that exists and you're familiar with is created with this type of problem solving or decision-m in mind. This was created for an entirely different purpose. And so if the way you're thinking about this problem is using this method of thinking, there's going to be misalignment and it's going to be Really hard for you to do the nonlinearity and seeing the

reality for what it is when you're locked into seeing it through a different pattern. It's going to feel very forced like it doesn't quite all connect together. And again, reality is your benchmark. Reality tells you the truth. If you're thinking about a problem in a certain way and it doesn't fit, the issue is the way that you're thinking about it. That's the part that needs to change. You can't manipulate reality in order to make it fit the way that you need it to. And so this is crucial because the way that you think about a

problem or a situation is 90% of the battle. A lot of time is wasted and lost on just trying to figure out the right way to break down a complicated situation. And a lot of mistakes come from not having thought about it in the right way to begin with. applying the wrong mental model or applying a mental model and missing some Of those factors. Again, it's not the lack of a mental model. It's the lack of the meta model that teaches you how to use the right model in the right way. And a really famous

example of uh people overcoming the framing bias, allowing them to switch mental models and create enormous value is actually in Toyota. So if you weren't aware in the ' 50s and60s Toyota started really making a name for themselves in really highquality efficient production line like Manufacturing. There are a lot of quality control and efficiency practices used in all sorts of industries around the world today that originated from Toyota in the ' 50s60s and 70s. And one famous example is the Toyota Anden cord system. Back in the 50s, the prevailing assumption, the frame that people were

taught about manufacturing is that efficiency is keeping that production line moving as much as possible. Anything that stops the production line Creates inefficiency. And so a lot of the models around increasing efficiency were how do you log and document failures and inconsistencies in your production line so you can go back and fix it? How do you make the logging faster for the workers? How do you make it more accurate? How do you uh you know bring people in to diagnose what the issues are and then when do you take time to improve those processes and

repair them? And so what Toyota did Differently is that they broke out of that framing bias and they said well what if efficiency doesn't come from never stopping the production line. What if efficiency comes from constantly learning? And they did the exact opposite. They gave workers the ability at any point for any worker to pull the and cord which stops the entire production line. As soon as a worker on the ground level saw an issue, they would pull the cord. The supervisors Would come in, the technicians would come in, they diagnose the issue. They they

had improved the process immediately. And as a result, their production process was able to increase in efficiency much more quickly and iteratively than than the traditional manufacturing model. In fact, this principle ended up becoming one of the core pillars of the lean manufacturing revolution of the 80s that a lot of manufacturers in the western worlds Would start studying to improve their own processes. And so that all comes from being able to escape this framing bias. So here's a takeaway for you for this, which is to actively reframe. There's always more than one way to see

a situation. If you can only think of one way where it makes sense and it intuitively fits in, you're definitely missing a perspective. There's always a different way to see it. So your job is To find that way. Now it doesn't mean that the other way of looking at it is better. But it is faster and cheaper to go through the thought process, figure out those other ways of thinking about it and evaluate which perspective, which frame of thinking about this problem is the most productive for me, rather than taking the easy way out and

saying, "Well, it makes sense the way that it was presented to me. It feels logical, so I'm just going to stick with this." And then potentially missing the real game-changing perspective. And I'm saying actively reframe because it is an active process. You when when someone presents something to you in a way unless it already is like really disorganized and you have no idea where to start. If it's presented to you in a way that's like here's how you should think about this problem A, B, and C and it feels logical and it feels intuitive. You're

not going to feel the need to Reframe that problem. You're not going to feel the need to challenge yourself. It feels like unnecessary extra work that you're giving. But when you get into the habit of constantly trying to reframe the information and seeing different ways that it comes together, this process not only is valuable and deepening your thought and helping you arrive at innovative really highquality solutions and decisions, but also that process starts getting easier for you. So it's not all this extra work. It might be at the beginning, but once you get used to

it, it's as easy as just thinking about anything else. And in short, what that means is that by getting used to these meta models of thinking, you are getting used to being excellent, which is kind of the point of the next meta model, which is the anti-comfort model. There's this other great book called anti-fragile By the legendary Nim Nicholas Taleb. And what he talks about is this idea of systems and processes that are fragile. So that means that when things change, they get worse. And then he talks about systems that are resilient. Supposedly the opposite

of fragile. So when something is resilient, when things change, it doesn't get worse. It's able to withstand that change. But then he talks about the idea of something that's anti-fragile, Which is something that when things change, it gets better. The thing that creates instability and concern for fragile systems and the thing that puts pressure on resilient systems, an anti-fragile system thrives from it. And this is the same idea with anti-comfort. When something is comfortable, it means that we're used to it. We're familiar with it. It's easy for us to think in a way that's comfortable.

If there's a problem that we have at work, if there's A complex situation or a decision that we need to make and we're thinking about it in a way that feels comfortable for us, what it means at a cognitive level is that we're using patterns of thinking that we're used to. We're relying on existing habits and patterns of problem solving and organizing information that we have experience with. Now, if someone is uncomfortable with a problem or a situation, they're feeling overwhelmed. They're seeing all of these different Factors and then they're feeling there's too much. I

I don't know what to do with all of this information. They want to retreat away. An anti-comfort mindset. This meta model is talking about actively looking for ways to make yourself feel less comfortable. It's going from feeling familiar with the patterns of thinking, having a way of approaching a problem or a decision that you feel pretty comfortable with, and then actively looking for reasons why You're wrong. The idea is that you are wary, you're cautious of that feeling of comfort because it means that there could be a blind spot that you're unaware of. I guess

that's what a blind spot is. And so in short, we can say that an anti-comfort approach means that you are looking for your gaps. You're asking yourself, "What have I missed? What could make me Wrong?" You want to feel a little uncomfortable when you're too comfortable. And this is hard to do because it there's there's emotion tied into it. You don't want to give yourself more work like we talked about. But an anti-comfort mentality means that you are more committed to getting the result that you want than how you feel about the process of getting

to this result. You're willing to accept discomfort in exchange for a Better result. And so the takeaway to this is is is really simple because the takeaway to this one is just do all this stuff. Do all of this. Use these other models. Trying to use these meta models whenever you're working through a framework and thinking about a problem is uncomfortable and it's going to make you look at that feeling of overwhelm and say, "Hey, what are you why am I overwhelmed? What is it that I do not know that is making me feel like

The pieces don't fit together?" And so merely the commitment to apply these meta models means that you are taking an anti-comfort approach. And to anchor this in in terms of why it's so worth it to do this is actually the final meta model which is the model of delayed discomfort. There's this concept I talk about a lot called desirable discomfort. It's saying that just because something is uncomfortable doesn't mean that that is A bad thing. Whether something is bad or not is your interpretation of that feeling. But discomfort is just a sensation like the the

breeze against your skin or you know smelling some kind of food. It's just a sensation that you're noticing. When we tell ourselves this is a bad thing, that can sometimes be a barrier to growth and improvement. When we're engaging in a hobby or a fun activity that is that's mentally or physically challenging that is creating Discomfort, but we we interpret that as being fun and worthwhile. And sometimes there are things that are worthwhile that create discomfort that we interpret as being bad. Learning is a great one where there's lots of studies that have been done

around how people self-regulate their learning strategies which has found that when learning and using a certain strategy feels difficult and feels like it involves more mental work and thinking, people think that That means that this strategy is not effective and so they stop using it. But actually what's clear is that the most effective learning strategies force you to think more deeply. And so in that case that is desirable difficulty. You actually want your brain to be thinking more deeply because that produces a better result. Now an issue with the way that I've seen a lot

of people interpret this idea of desirable difficulty is that they will have a certain task that They need to do and this this task uh may have a way of doing this. Like for example, if it is learning about something, there is a a strategy that you can use and a method and a way to go about learning uh which I teach in all my other videos that could be difficult. It could induce a level of difficulty or I could do it in the way that I'm used to doing which is potentially comfortable. It's much

easier. I know how to do that. And so this is not Difficult. And so the the the issue here is that they're making this decision about saying, "Okay, this one is actually the one that I feel like doing because it's easier and this one is the one that is harder for me to do." But I'm telling myself, this is the one that is actually desirable. This is the one that I should do. And so now you're torn between what you know you should do versus what you kind of feel more drawn towards, which Is the

easier option. And if on a bad day when you just don't have enough time, when you don't have the willpower, you just resort to the easier option. But this is not the full picture. And this is the part that I want to communicate really clearly here is that this is only the first part of that decision. Because often if it's desirable difficulty, when you pick the path that involves lower levels of difficulty, it's also going to lead to a Lower level of result as opposed to if you pick the path with the desirable difficulty, which

leads more closely to the result that you actually wanted in the first place. And when you have the lower level of result, this result also has consequences. And now you need to manage these consequences. So that's extra work you need to do. That's extra effort. That is extra time that you need to spend. And all of this this is also difficult. And Sometimes the consequences of not getting the result that you want adds an extra layer which is that it is emotionally difficult. And so the decision that you're making at this point when you're deciding

how should I go about this task is not desirable difficulty versus ease. The true decision we're making is do I pick the path of desirable discomfort which is this one or do I pick the path of Delayed discomfort which is this one. So the discomfort is there regardless. It's just do you pay that upfront or do you pay that later? And most of the time it's better to pay that upfront because the level of discomfort is easier to plan for upfront. Whereas if you have delayed discomfort, you don't know what the consequences of that is

going to be. You don't know how much discomfort there's going to be. It's harder to assess what The cost you're paying in those consequences and getting the bad result actually means. And the future version of you has other things to do than pay off this discomfort, debt, and the consequences of getting the poor result. In learning, I see this all the time where people pick the easiest, most passive way to learn something. They're covering 100 pages of content in half an hour. They write up a beautiful set of notes that 90% AI generated. And then

The future version of them is now stuck with 3 4 hours a day where they need to go through the stuff to keep on top of it or they'll come back to it 2 weeks later and they've forgotten everything. you've now created a problem for the future version of yourself. And that's where people get stuck on this overwhelming just hamster wheel of constantly working and constantly trying to catch up. The thing you're trying to catch up to is not your present Challenges. The things that you're trying to catch up to is the challenges that the

past version of you made for you today. And so the takeaway for you is this. Sometimes delayed discomfort is okay. Sometimes delayed discomfort is actually just strategic. You can make that decision. Just make that decision intentionally. Intentionally decide whether you want the discomfort Now or later. If you need to make a decision about something, if you need to solve a problem and you need to do it by the end of today, you maybe don't have time to go through all of this stuff. And so you may be willing to accept the risk that you're going

to pay for that discomfort later if the result you get isn't good enough. And you can hope that it is good enough. You can use the mental model that you think is the best one for you Based on your limited understanding of the issue and just hope you get the result right now while understanding that that's probably not the best way to go about solving problems and making decisions long term. But just make that decision consciously. And when you decide that you are going to take this difficulty up front, hold yourself to a high standard.

If you're going to take on a level of discomfort, do it right. At least don't Shortcut yourself. When I'm doing a coaching consultation with someone and I'm sitting there watching how they apply a certain learning strategy or a learning technique and they've been struggling with it for for weeks or even months, one of the most effective things that I do that allows a transformation to occur in that person in one hour that they previously weren't able to do in 6 months before that is simply being clear about the standard they need to hold Themselves to

and not letting them get away with it. when they see a problem and they say, "Okay, well, I'm seeing this problem in this kind of way." And I say, "Well, what's another way that you could think about this? What's another way you could perceive the situation? What's another way you could group and categorize and connect it into a big picture?" And they say, "I'm not really sure. I don't let them get away with I don't know." I encourage them to just Try their best. Just try to find another way. when they're looking at all these

different parts that connect together and they're getting overwhelmed and they say, "I don't know how it connects together." All I say is, "Well, just try to connect it. Just see where you get to. Yes, it's overwhelming. Yes, it's complicated. That's the reason it's a problem in the first place. That's the reason it is your job to solve this. So, just try." And honestly, 70% of the time When someone has an issue, that is the difference that allows them to make the light bulb click. That's the point where they realize, oh, this is what it feels

like to think at this level. That's when they realize, oh, it's actually not as scary as I thought, not as bad as I thought to hold myself to this standard. And then from that point, it gets easier and easier. And I know that when someone's able to experience what it's like to think at that level, just even Once, then we're winning. From that point, everything is easier because they know that they can do it, they can hold themselves to a certain standard, and they can hit that standard. And as they repeatedly hit that standard again

and again, it gets easier and easier and easier to do it. So these are the six meta models that you should apply anytime that you're using any other type of framework or mental model. If you found this video useful, please share it With a colleague or a friend. And if you're interested in leveling up the way that you think and improving your skills, you're going to need to make sure that you're spending your time effectively. And one of the biggest time waste that I see is how people spend their evenings coming home after work. So,

if you're interested in some strategies on how you can reclaim your evenings, then check out this video here where I talk about that very topic. Thank you so much for watching and I'll see you in the next one.