Private Lecture: How to Remember EVERYTHING You Read

As a learning coach for the past 13 years, I've worked with over 30,000 students and professionals. And everyone I work with pretty much has the same problem. There's too much to learn and not enough time. Recently, Dan, a software engineer and actually one of my employees came to me with this very problem. Especially in software, there's constantly new developments to keep up with. And for a professional, learning is earning. The faster he can learn, the better he can perform. But he was struggling to learn everything and then actually retain it. He'll say that he'd be going back and rereading notes that he had written months ago, realizing that he's forgotten half of it. And also just spending more time on learning wasn't an option because he was already trying to balance full-time work and family responsibilities. So, I had a meeting with Dan to coach him on improving his retention and improving his learning efficiency. And I think these are all things that can help many of you as well, which is why I am sharing this with Dan's permission. So, here it is. Everyone that I work with in every setting has the same problem, right? They have too much to learn. Okay. And then not enough time. — Y — like that's the quintessential problem of every person that I work with. And so the too much to learn, not enough time issue. The way that you solve that is through snowballing, right? You have to be able to snowball your learning. Like that's going to be the golden key here. Snowball. A snowball occurs when it's kind of like a bunch of little magnets. So, you know, if you just imagine having a bunch of magnets on a desk, it's all scattered around, but you just touch one of them and it forms that connection. It hooks onto one and then it spins around. It starts hooking onto all the other ones and then before you know it, the entire table is just like all latching together into this, you know, enormous magnetic ball because all of those things have started clicking together. That's basically what we want to achieve is that we want to be able to create those initial connections at a level of quality and a level of depth fast enough that new information has a place to stick and it has that place to stick very quickly. When it takes a long time for information to stick, one of two things is going to happen. One, the most common thing is that you're going to consume that information. You will understand the information because understanding something just requires like a level of logical ability. like it's nothing special to be able to understand something. Everyone can understand something if they, you know, read it enough times. Once you understand it, it it'll be understood, but it hasn't connected to anything. And so, as a result, it's very temporary. Yeah, it's in that isolated state. And so, isolation in learning is obviously, you know, that's the dangerous game. You never want anything to be isolated. That piece of information and the time that was invested in trying to gain that information is not turning into a learning asset, right? that is just like you've just created learning debt for yourself. Anything that's isolated is becoming learning debt because now it becomes a thing that you spent time on that you're not able to use to connect to other things. You can't apply it in the way you need to and the future version of you needs to pay off that debt by going through and learning it again and also feeling bad about it. Either it's going to become learning debt because it's just too shallow and you've understood it and then you forget it eventually. That's the first case. Well, the second thing is that you're going to enter into the illusion of learning. And this happens when you feel that you've got it down somewhere. You've written in your notes, you've put it on your notion, you've used a second brain, uh you've, you know, like understood it even better because you've, you know, used AI to kind of bounce back and forth. And so, you feel like your understanding is like even deeper than it was before. And so, again, it's like building on that understanding, but at the end of the day, it's still isolated. And even if it's, you know, technically connected in your notes or even on a mind map, it's connected technically. There's lines connecting it or it's, you know, you can find it in your notion database somewhere and it, you know, if you click on the link, there's all these other different tags and things connected to it. At the end of the day, like if it's not connected and organized in a way that you can recall in your memory, that's not functional expertise anyway. And so this is even worse than learning debt because now you're not even aware of the fact that it's become dead. And that becomes blind debt. That's the worst because then you estimate your expertise to be higher than it actually is — and the only way that you realize that you don't know stuff is that when you go to try to use it, you are just wrong. And then that creates like essentially either like incompetence or bad decisions or just like inability to solve problems or just the wrong solutions to problems which in the professional world can obviously be very costly. And then figuring out that is actually a blind spot for you is very difficult and very complicated because again there's that kind of veneer of confidence because you know that knowledge is stored there. It's only when you really challenge yourself to try to recall and use that knowledge or when you try to apply it in a way where unless you have the truth it definitely won't work in your situation. Sometimes that's easier because like literally something may fail to compile. — Um but you know when it comes to like making a decision it's really blurry. like you might not know for months that it was a bad decision. — And so then again going back to trace

back why was that the wrong decision? Why was I unable to make the right decision with the information available becomes very opaque because you're not aware of which knowledge deficits they are. We have to understand that when we feel that we're learning something it should feel in the first phase fairly overwhelming. That's the first landmark we look for because it we're basically saying there are a bunch of pieces here. I'm going to use this jigsaw analogy where if you imagine just taking a big like a thousand piece jigsaw puzzle tipping out all the pieces on a table, it's just like everywhere. If you if your goal here is to create that big picture and bring it all together, it should be overwhelming cuz there are so many different pieces. You know they all fit somewhere very purposefully, but you have no idea where to start. You don't know which piece is what. You don't know you know what goes anywhere. You do not want to be avoiding that overwhelm because when it comes to learning, avoiding that overwhelm means that you're avoiding sifting through those pieces to see where they fit. Usually what avoidance manifests as is just putting things down in a notion database, just writing things down, writing some notes just to at least get some thoughts down on paper. But at the end of the day, it's like, okay, you're bypassing that feeling of overwhelm, but you're also bypassing the exact process you need to undergo to organize it and make it your expertise. When you're faced with that overwhelm, the first thing to do is just acknowledge that there's an overwhelming amount of information and therefore recognize, okay, I'm in the right place. This is the correct starting position. It's like when you play games, if there's no enemies around you, you're in the wrong place. You know, you go in the direction where it is getting harder. The second thing to do is then use strategies that progressively allow the organization of knowledge to increase while maintaining the level of uh cognitive effort. If I draw this graph here uh and this is your cognitive load or cognitive effort. There are different strategies uh that produce different types of results. There are strategies that can take you from high level of cognitive load and cognitive effort and it can reduce that down very low. These are usually strategies that involve passive learning. We're now just trying to rote learn, wrote, memorize, do things by repeat. We're removing the overwhelm and reducing that cognitive load by not even thinking about how everything is connected to the big picture. This is the equivalent of saying, "Wow, it's so difficult to see how all these pieces fit together. I'm just going to take up a single puzzle piece and I'm just going to try to understand the single piece really well. " It's like, great, you can do that. That's very easy for you to do, but it's also kind of meaningless because you cannot translate that knowledge effectively. If you just think about how impossible it is to try to memorize every single piece to an extent where after you have memorized each piece, you can just close your eyes and see how it all comes together. Yeah, I don't think that's humanly possible. That's basically what people are doing for learning. Like there are literally like a thousand different things that you need to learn. So that's a method where your cognitive load is going down very quickly. And so it feels very productive. This is the illusion of learning here. It feels very productive because it feels the overwhelm is becoming much easier. And so this is bad. There are strategies that take our cognitive load and then it makes it go up even higher than it is. This is also bad because this is now saying, "Hey, there are thousand pieces that are all connected together. Let me see how every single piece is connected all at once. " — Yeah. Okay. So it's the complexity. It's too many interconnected problems at the same time. So now this is also biologically impossible because the human brain can you know deal with maybe depending on you know like your intellectual capacity is like between like you know seven to maybe 15 different things at the same time. Me personally like honestly beyond like four or five I'm just like this is a bad place to be in. You don't want to be trying to juggle so many different thoughts. There are some people who are so exceptionally gifted that they can legitimately be reading through, you know, pages and pages of content, not writing down anything, and they're just simply mentally connecting absolutely all of it in a single go on the first pass through. If you're one of those people, good for you. For the mere mortals, you know, the rest of us, that's not a viable strategy. And those people don't need learning methods. They're just overpowered to begin with. So where we want to end up is inside this like goldil lock zone where we are using a strategy that allows that load to go down and then we are allowing that load to raise up again and then we're using a strategy that brings it down and then it goes up again and it continues in this way. So what's happening if we zoom in onto this process is we are at this point in this phase we are choosing to take a segment and then in this phase we are organizing that segment and here we are now loading up a new segment and then here we are again organizing that and then reintegrating it. So, this is the equivalent of saying, "All right, I'm going to start with the edges of the

puzzle first. Let me find the borders, the colors that seem obviously really, you know, related together. Hey, I've got this huge big uh blue sky on this picture, but there's this like red plane. There's only one red thing in this entire picture. Okay, all the red pieces. Clearly, they're going to be together in some way. " So, we're choosing some place to start where we feel like we're going to have a pretty good shot at bringing that picture together. And then we're going to go through and bring it together in our best possible capacity. And then once we've done that, we're going to look at it and it's going to be slightly less overwhelming. Still pretty overwhelming, but at least the segment that we've been looking at, that part is now easier. That's not overwhelming anymore. Like that makes sense. The frame is now there. Like we can see it for a big picture. So then we pick the next segment. And this is just whatever area we think we're going to have the next best shot at. Then we look at that and we, you know, put it together. If we can fit it into the existing big picture that we're building, fit it onto the frame, that's good. If we can't, we might leave it there for a while and see if we can connect it back later. And we just continue this process until eventually these pieces start connecting together. And it's this cycle of constantly going like the zooming in and out. This is what effective zooming in and out looks like. You're zooming in to find the right segments. You're zooming out to bring it into the big picture. You're zooming in to find a new segment. You're zooming out to reintegrated into that the big picture. And so over time, it becomes less and less overwhelming as opposed to more overwhelming, which is what happens with uh normal learning. When people usually learn using either of these strategies where they are just passively learning, then they're going to eventually get to a point where they've realized, "Holy crap, I've spent 6 hours learning this, but 3 weeks later I remember barely none of it, and I also can't use it for my work in a way that's actually meaningful. Now they feel overwhelmed, and it's even worse cuz they wasted 6 weeks. " Or they're going to feel here where as they continue to learn more, there are so many things going on their brain is, you know, just like exploding. If that's happening, that's a bad sign, right? It should be progressively becoming less and less overwhelming because your brain finds it easier to understand a big picture. Even if it's made up of 500 different parts, a big picture is still one big picture. — Whereas a thousand isolated separate parts is extremely overwhelming. And so over time it gets easier and easier. And once you have a big picture that's relatively formed, 50 60% formed, new pieces are much faster to add in because you have so much more referential data in your brain. And that's what snowballing means. Once you get to a certain point where you can actually see what the picture is going to look like, each new piece of information that comes in, you know where it's going to fit because instead of 600 different places it could fit, there's only four. So now it's very fast for you to be like, is it here, here, or here? That's basically the abstracted version of how you get to a point of being like really fast with your learning. And when you do it this way, naturally your memory should be very good and naturally your depth should be really good as well because it's impossible to organize it accurately without exploring the detail and the depth otherwise the way you organize it is going to be incorrect. Now at this point Dan understands the main learning principles around snowballing but he doesn't know how to implement this in his daily learning session. So in the next section I'm going to introduce some specific tactics that he can actually apply on a practical day-to-day basis. I'll just pause there and you know for if you've got like questions or any remarks or comments about that. So it makes first and foremost it makes sense because fundamentally to me I relate it to things like I do with development experience at the moment where you do kind of have to zoom out establish so the layer lands the problem you're addressing and then you have to zoom in target a small part you have to organize and plan it so that it's manageable there's not too much cognitive overload you can draw a line and say this stuff's not important just focus in here build it to a certain state that you're happy with and then say cool zoom back out what's the next piece that grows off that and kind of like you talking about your snowball so valid analogy that part makes sense to Okay. What I struggle probably more with is defining what the right way to do that is, what the right sort of framework and structure is around that because that's the part I probably um haven't done. I'll dive into that area. I'll read some videos, look at some blogs. For me, that's surface level information. Generally, most time if I'm not careful, you talk to me half an hour later, I won't remember enough of it to be useful. Sometimes I'll dive deeper and take into more like having a chat with um chat jibity or Claude and explore the topic and actually start to, you know, prompt and say, "Cool, I understand that. " But when it's in relation to this, I think it would work like XY Z. Let's explore that more. Right? So that for me works cuz I'm going deeper. — The deepest level I generally get, this is why I like dev so much is my ability to be able to actually apply it and use it. And then when it's brought into the context of trying to build something, it's much more tangible. There's other problems that start to arise and come out of that which then surfaces, oh cool, I need to go and learn more about that. I've got experiences going through that where I've seen it. What I just don't ever feel like I have is a consistency really. It's just that sort of holistic. I know at a high level what I want to do, but I don't have a

framework or structure that I can keep referring back to and go, "Yep, cool. " Don't even think about looking for some random video. The next thing I need to do is here because I've pre-organized it and planned it and that's what it is. I don't often run across things where I'm like cognitively it's too much all at once that I'm recognizing. It's not like I'm going to go and be a doctor tomorrow. There's not so like big sort of topics. There's always been a gradual progression for me. So, it's not often where I'm like this whole area is way too much overwhelming. even AI space I think I roughly know at a high level but how do I tackle it and more importantly how do I decide what to tackle first and how deep — I I'll comment on that second part first because that's actually there's a really interesting angle to this there's two different ways that type of um phenomenon can arise so learning is earning right at the end of the day the faster you learn the more effective your decisions are the less opportunity cost that you're burning if it takes you six months to learn something that affects the way that you work today, then between now and 6 months from now, — you're underperforming essentially from where you could be. In my view, the faster you can learn something, the better it is always, — right? Like unless you just really enjoy taking your time learning something, which is fine for like a hobby or a language where you're just cruising, like it's all good. But when there's something at stake, you just want to you don't want learning. You just want knowledge. You just want to go from not knowing stuff to knowing stuff. — I'm almost to the point where if I don't have a stake in it, then I don't actually want to learn it. — Yeah. And that and that's really common because there's so many things to learn and you have to prioritize it. Right? If you're getting to a point where you're feeling you're not really feeling like that cognitive overload, there's two different scenarios here. Number one, you have a very high level of expertise already in that field. — So when I'm learning new stuff about learning science in the field of learning science that I'm more well-versed in, — yeah, — you know, there's new articles popping up all the time. I might have like 20 different tabs open of 20 new research articles. it's very easy for me to go through that information because it's just adding on like one little detail on a body of knowledge I already know. Like there's not really much um cognitive transformation. My existing schemas aren't really being challenged at all. Or if it is being challenged, it's a very small easy tweak and adjustment to kind of reframe the way that I think about something. So that's situation number one. And so you'll know you're in that situation because you've spent the last decade becoming an expert at that thing. If that's not the situation, probably what it is that you're actually underloading your potential for learning. And the reason that this happens a lot of the time is because there isn't a strategy to manage that overload. So we actually prevent ourselves from overloading preventatively. So if we say, "Hey, I already know that I'm not going to be able to learn like this entire textbook on AI. " So you're not even going to so you wouldn't even try to because it's just not a concept that you feel like is a viable strategy to begin with. For you, it's you know, there's likely going to be some elements where you are pretty well verssed in it. So therefore, it is naturally easier. But there's some areas where probably either due to a lack of time or because you just don't feel like you'll be able to consolidate it effectively. You're actually holding yourself back from just jumping straight into that ultra deep end. And so it's about creating the tactics to learn how to swim in that deep end so you do feel confident to just really hit yourself in the face with that overwhelm but still navigate through it effectively. If I was to take that then right when it comes to the topics I discussed around what I'm learning Italian for sure feels like that sort of domain 100% like that's like there's so much to learn there to learn a whole new language I've never learned another language so for me it's like oh I'm using Dualingo once a day and I'm starting right I've made that start that's my first step but I haven't at all spent time to reflect and understand how I can actually deep dive into it and to be honest like you kind of alluded to there is a level of like there's too much like I don't want to yet deep dive into it when it comes AI, aentic systems, the systems thinking, even the tech strategy was one of the other ones I have here for the reforge course. I guess for me it's I don't have a good this is probably self-reflecting on the spot, but I probably don't have a good enough foundational understanding of what I do know and what is already there. So when new information and topics come along, I can learn them in a little bit isolation. I can see how they relate, but I'm not doing it intentionally. I'm doing it probably more reactively or not even excitedly is a word, but in a way I'm like that sounds interesting. That could be useful. — It's opportunistic. — Yes, it's opportunistic for sure. — What I'll start with is saying like these are not the hardest problems to solve, — right? Like you're in a good starting position. Uh and the reason is because if you already understand this concept that I talked about here, the idea of like trying to maintain that engaging challenge and understanding that that's what it should feel like. If you have that as a goalpost and you understand what that feeling is, that's 70% of it right there. There's so many different techniques and strategies that can allow you to do this. The tactics part is actually the easy thing. The difficulty is that if someone doesn't understand this, I can teach the tactic. strategy and the method and they learn doing this step one, step two, step three. But then when they do that, they don't know where their own cognitive load is going. And so they might be, you know, they can't adjust their technique to make it work for them because they just have absolutely no idea where the goalpost is. — They don't have a feedback loop. Yeah.

— You know, the most like stuck cases where people are really struggling for a long time. This is what I I'll do. I'll say, "We'll block out two hours. You're just going to study in front of me and you're just going to narrate your thoughts and I'm just going to watch every single thing you write down. Every time I see you write something that I feel like is going into like a lower order of thinking, I'm going to challenge you and ask you like why you thought that? Why did you draw that line there? Why are you connecting it this way? Why are you reading this instead of reading this? Like and I'll go through at that level and that's what creates that calibration for how they should be thinking versus the way they are thinking. Obviously, I'm not going to do that right for everyone. So, so that's not a viable solution. You know, the viable solution is you have to be able to like monitor yourself over your own shoulder to be able to do that. So, if you have a general understanding of this, all the other problems that you talked about, they're actually like in the easier basket to solve. Uh, let's talk a little bit about the tactics because I think when we talk about the tactics, a lot of the other things are going to make more sense. Any method that you use that allows you to create a meaningful organization is an effective method. And the good thing is that it doesn't matter if your background knowledge is like implicit or explicit. you know what you sort of talked about for most people most of their knowledge is not going to be explicitly laid out and like a clear mental model and a clear schema especially for people like you know if they go through our program and stuff they're going from like not really understanding how all of this works and not building explicit schemas to like suddenly now realizing they need to build an explicit schema and all these tools to do that. So there's like this clear transformation from like not being able to suddenly feeling like they need to. So there feels like there could be this clear divide between high quality learning versus like random learning that's been happening for the years before that. But it's not the case. Like expertise is expertise. If there's stuff that you feel confident on, like that schema is there. You may not know like you may not have formed that explicitly. as quickly as you could have if you were to rewind like 5 10 years and do it all over again with better methods. But the expertise is still there. So when you go to use that expertise and you test yourself and you challenge yourself on that expertise, you will be able to form that schema and the schema evolves. So it's not like you don't have to have it in a mind map. You can be learning something new, seeing how it relates to how what you already know and then building a schema as you go and then that just becomes your schema. Like real expertise is very fluid. So I wouldn't worry too much about not knowing where your previous gaps are. Like those things will just appear naturally. You like you you'll figure that out. What we need to start with is actually having like a clear tactic, a clear method for us to basically do this process. — Yeah. — So, I'm going to start with um kind of the basic template. This is sort of the basic starter like one two combo that most people should start with and then from here you can adapt and evolve it to different context. So, the first thing is we need to get a lay of the land. If you are in a dense forest, the first thing you need to do is just get to a high point to see like where you even are. It is very difficult to form connections uh or to solve a jigsaw puzzle and form a big picture if you're only given like five pieces of the puzzle at a time. And so the first thing we need to do is get ourselves to the point of being like, "Wow, this is a lot. " And we do that by collecting as comprehensively about the topic as possible. The basic technique that I recommend for this, the starter technique is basically just a keyword collection. you go through and you just collect all the major keywords that you think are relevant about this topic. This is where your own sense of comfort comes into it. If this is a field that you feel like you already know a decent amount about, then you might and you're sort of comfortable staying in that area of like high cognitive load and really thinking through things and you know you're not going to be so overwhelmed that you instinctively back off. Some people have that emotional response, you know, like whoa, this is too overwhelming. They get really anxious about it and they it's hard to tolerate. you get a sense for that yourself. Uh, but you start off with a list of key words. If you're sort of on the conservative end, you feel like you're going to be a bit more anxious with being overwhelmed. You might start with like 15 keywords. But these are now 15 of the biggest, most important concepts across the entire topic. For myself, where I'm, you know, very used to it. I'm just going to go ballistic. Like I'm going to go as many possible keywords as I can across the entire spectrum of the topic. So, if it's a brand new topic that I'm learning about, I might start with like 50 to 100 keywords. You should look at those sets of keywords and just feel like enormously confused. You don't know where to start. It should feel the same as if you're just looking at all the pieces of the puzzle laid out in front of you at once. — So, when it comes to those keywords though, what are the sources of those keywords? Are they keywords that based off your current knowledge and understanding? Is it you doing rapid exploring and researching to find those? — Six years ago, you asked me that, I'd say scan through your textbook, go through videos, look at articles, you know, take it from your own set of, you know, knowledge. Now if you ask me that just tell chatbt this is what I want to learn and generate 50 of the most important keywords around that topic and even if it's not exactly like onetoone exactly what you need to know based on the resource it is it's like going to be close enough of a match for you to start with it honestly doesn't matter like that knowledge is going to evolve this is just a springboard and then you can look at that list and if there's stuff that's missing you can either add them in manually yourself or you can say hey I noticed that like you're missing

these types of keywords like what about keywords like this and this and this you're missing this kind of angle all together, I'd be like, "Okay, cool. Yeah, you're right. Let me regenerate that list for you with like these other ones and then you'll get, you know, more and more. " So, this keyword collection part used to take like 30 minutes sometimes. Uh, and now it takes like three. — Yeah. — Um, and that's like not this is not productive effort. This is one of those things where spending cognitive effort on just doing this part is not going to help you. This is like the preparation for the learning. It's just giving you a good starting point. like you don't want to like if you if you're starting with that blank canvas, you don't want to have to like hike 10 km across a mountain to buy your canvas. Like you want that delivered to your doorstep. You get that list of keywords and then from here there are multiple different approaches that you can take and uh for in a professional context you have a lot of flexibility and freedom in terms of how you want to do this. Your goal remember is to find your segment and organize it but you want to do it in sort of like layers of importance. Think about your cognitive load like a cup of water. That's your cognitive capacity. That's a volume of water that you have. Let's just say to make it easier, you know, we've got like a liter of water. — You can either pour that liter of water on a flat surface and fill it very very wide but very shallow or you can fill it into like a narrow test tube that's very deep but you know like very narrow, right? Depending on what you're trying to learn and like you know why it, you're going to choose to spread your cognitive load either very widely across the entire topic. This is the approach that you would take if you're learning something that's relatively new and you have to gain a lot of expertise across a very broad topic. You'll try to cover it very shallow and superficial but as broad as you can. Kind of like looking at a landscape. You're kind of squinting, you know, with one eye. You just basically see where the mountain is and like the forest and the lake, but you can't really make out any of the other features, but it gives you your major landmarks in the topic. These are the biggest things that things are going to hang off of. — So, in those keywords, you'd pick where you think are going to be the biggest like the biggest most important keywords. — Uh or you might notice that like these 10 different keywords are all actually very similar to each other. And you might hypothesize that actually even though it's not given to you this you can group it and give it its own keyword like you can generate your own keywords. That again takes a you know a level of skill. Like for some people they're not comfortable with generating their own keywords and that's fine. They can get to that point eventually but if you can look through those and if you feel like there's no keyword that's suitable generate your own. You want to start with roughly six four to six keywords which is not a lot. We're operating again within that tight cognitive band. Like I said before, you like anywhere anytime you're getting beyond sort of six different elements floating around at the same time. You're probably not in a cognitively optimal state anymore. The quality of your thinking is going to be just too confused and your attention is too split on basically juggling rather than processing. — So, uh you want to go through get to the four to six. That's the wide shallow approach. Exactly the same thing if you're going for a narrower approach. The only difference is that your first thing is filtering. So, you're just going to go through those keywords and make a decision. Is this likely to be relevant for that deep trench I'm trying to build for myself or not? And then you'd filter through until you get to a short list of keywords that you feel are likely to be more relevant for that narrow piece of expertise that you want to develop. And then you do the same thing. You figure out the four to six keywords within that narrow trench that you think is going to be important for you. It's really the same process. The only difference is that in one step, you're going to filter and screen it down. In the other, you're just starting with everything and then getting a lay of the land. — The whole generalist versus the specialist sort of — Yeah. In a way. — But yeah. And then once you have those basic pillars uh that have been formed, there are two main things that you want to make sure that you're doing here. The first thing is that you want to start hypothesizing a flow and a it's not really a sequence. The most accurate way to describe it is actually a schema, but people don't really know what a schema. — I do, but yeah, — it's an interconnected set of ideas, but the connection between the ideas has to be meaningful. That's the really important part with a lot of beginners. and actually even like pretty inter intermediate level learners that have like a strong basis of deep processing and actually I suspect that you know you're doing this partially as well because of the fact that you said that you are zooming in and out and you are finding these connections but you're finding that memory and that depth is not quite there. So I suspect that there's an element of this that's going to be happening for you which is that not all relationships are built equal. The worst place to stop, well, stop is before you even find any relationships to begin with. The worst place to stop is in isolation, but the worst place to stop after you've uh found a relationship is after that first relationship. Um, this usually happens because again, we're not used to being in that overwhelming high cognitive load state. And so, we're sort of desperately trying to bring that load down. You know, it's easy to say, "Oh, hey, these two things are related to each other. I see, oh, this is before and then this is after. Cool. Before, after. Done. " Well

it could be before and after, but it could also be like um you know, positive or negative. Or it could be not like grouped like that at all. It could be a completely different type of grouping like maybe you know the thing that's before and the thing that's after maybe they're actually within the same group. There are multiple ways that different things are connected to each other. And so it's not about finding a relationship. It's about trying to find the most meaningful relationship for how number one it makes sense for you and number two how you're going to need to use that knowledge. The way that you need to use the information is not always actually is usually not the way you need to learn it initially cuz the way it makes sense for you is very heavily influenced by what you already know. Your prior knowledge, your experience, your tendencies, the analogies that you can form. If you are a competitive skier and you've been skiing for, you know, 20 years and there are so many, you know, skiing so well and so deeply that when you learn about Python, you're like, "Hey, this logic and structure really reminds me of the way that I train my students when, you know, they're skiing, right? That's an analogy that could you could completely viably form that someone else wouldn't form. " And so the way you structure that information is going to be uniquely well suited for you and your memory. — But it's not really related to how you're going to then use that information. And this is the distinction is that if you develop expertise, you can use that information however you want. The first step is develop expertise. If you don't have expertise and you don't have long-term memory, you don't have anything later. Like that's the prerequisite that has to be met first. So you prioritize that. This is really common in like medicine and healthcare. And there might be a similarity in software and let me know if there is because in like medicine and healthcare things are usually presented in a way that's very structured like there's this very clear sort of template of how things are often taught. It's like hey first someone comes in with this symptom and then you do this investigation and this examination blood test and then you do this management like and so when people learn about diseases it's always taught in that way and so people in healthcare they tend to feel like hey that's the way I need to use that knowledge that's the way it's taught to me it makes sense it's logical therefore that's the structure that I'm going to use but it's also very not memorable because that structure doesn't help you to remember it because it's the same structure for everything it's like going into a warehouse and someone telling you, "Hey, it's easy to find. It's the one on the shelf. " And like, if there's a million shelves, that doesn't help at all, — right? Whereas, if something is like in a in a tin, another thing is on a shelf, trolley, then it's easier to distinguish. And so, the structure of the knowledge and how you organize it should actually reflect the nature of the topic itself. And a lot of the time when it's taught, it's not taught that way. It's taught in a way that is logical and makes sense to teach, but it doesn't necessarily mean that it is easy to remember because that exact same structure may be so similar to the way that you learn everything else. So I'm not sure if there's a there's an equivalent for — most things when you learn in it have that sort of equivalent sort of structure which is that the material or the particular library or particular piece of software whatever you want to use is generally presented in a way that a is idealistic towards the product itself being self advocating. So like it makes it look like it's simple makes look straightforward but also quite often the way it's presented is generally in isolation. It's presented in a way that's relevant to itself and how you would use it on its own. But the interconnected relationships of how it fits within the domain that you're trying to apply it to is not often done. Which I think is the same struggle I've had throughout schooling and stuff. Whereas if I can't personally see and understand the importance and the relationship to other parts of — my knowledge life and whatnot, — it automatically has a whole of a lot less value. It's like cool, I'm learning in isolation, but if this isn't something that I can applicably use elsewhere and I know why it's useful there, — I struggle straight away. I'm like, yeah, cool. If there's no link, why am I learning this? Why is it important? And that's where I often go, I'll learn enough to understand at a high level and I'll deep dive when I need to use it. — Yeah, that's actually perfectly fine in professional context because like there's a lot of stuff that you don't need to dive deep into straight away. You can just, — you know, learn it. You can go back to it later. It's those things that where it wouldn't be convenient to need to go back to it later or actually you do need to know it deeply enough to be able to use that very specific knowledge to frame how you know you think about other things. Especially when it comes to decision-m and strategy, high level planning, things like that. you often do need to have like pretty concrete very specific knowledge about you know like detailed things to understand the implications of different decisions. I think the key flip is really understanding that the feeling of relevance is a symptom that the information is connected and the ability to connect information is a skill. And so even though we may initially feel that something is relevant or not relevant, that is almost a way ironically irrelevant to how well you should be able to learn it because if it starts from a point of irrelevance, well the first thing you need to do is find the path of relevance to be able to

create the necessary connections. And if you're starting from a point of relevance, well, you need to do that anyway because you need to find other ways to connect it as well to find the most meaningful structure. Okay, so the part we just covered were around strategies and tactics around creating mental schemas and these things will improve your retention and overall increase your learning efficiency. It's one of the most high yield techniques that you can learn. If you're interested in learning a little bit more about these types of strategies or other types of strategies to boost your learning efficiency, then I would also recommend checking out my free weekly newsletter where I distill some of these types of techniques. I'm not going through, you know, an hour of coaching, but I'm taking what I think are the key principles and insights that can help you on a day-to-day basis and then putting them into 3 to 5 minute emails. I write them all myself. I think very carefully about what I should put in these newsletters and it is again totally free. So, if you're interested in signing up, I'll leave a link to that in the description. Now, in the next section of the coaching call, I'm going to summarize everything that we've talked about so far and then bring them down into a final set of action steps for Dan to take after the call ends. — In the last like 5 n 10 minutes, it'd be good to kind of establish what I should do next. I think for you the best starting point right now is we I want to get a general calibration. Uh and I want you to explore that feeling of just trying to challenge your hypotheses and frames and also trying to make your frames a little bit more explicit and just feeling what types of new discoveries and new learnings you gain from doing that and then seeing how your thinking about that topic evolves. So if we're learning about something to do with uh you know agentic AI or something you might uh just start by dumping down you know everything that you know about that uh you if you feel like you want to start with the whole keywords thing to begin with like you can start with that but then challenge yourself look at those and then ask yourself what's the other way of representing this like what's the other structure you know is there someone out there who is a deep expert on this that's going to look at this and say actually there's an even simpler more intuitive even better more meaningful way of representing this topic the things that you think are the most important, they're actually not. This is really the simplest way that you should think about it and then just push yourself to see if you can figure out those different angles and then observe how that changes the way that you think about some of those more detailed components as well. You might do this and you might feel like, okay, that was a useful activity, but still fairly like easy to do. Then that would tell me two things. one either you're not pushing yourself hard enough or uh you actually are very comfortable with that. Um the difference would be the type of cognitive load it's inducing. No matter how much you know about a topic, this process of actually challenging your schema and trying to find an alternative schema, it's cognitively engaging. If I'm doing something on learning science like self-regulated higher order learning which is just the very center of my domain of expertise if I'm trying to reorganize that it's engaging for me and I've done I've tried to reorganize it like hundreds of times every time I do it it's always engaging. So if you don't feel that it's cognitively engaging that's a red flag. That for sure means that you're not actually pushing yourself and critiquing and challenging yourself enough. You really need to like interrogate that. — Yeah. uh or if you feel like yep it's engaging and therefore you should feel it's useful. You should feel that your knowledge is actually deepening. Even if you're not learning anything new, you should feel like you're starting to see this topic in a way that felt that feels different to how you saw it before. It is more comfortable. You should feel that your memory is actually getting stronger just from doing that process. Like these are all symptoms that you are engaging in that process correctly. — So as part of that when you're drawing essentially like that the keywords, the mind map, you're creating the relationships and understanding it. What are some of the angles or ways you can approach it to kind of I guess push that challenge? So for me, I'm thinking like if I draw a bunch of relationships and I draw lines and say, "Yeah, they're related. " My first instinct is go, "Well, if I want to challenge that, then I look at that relationship and say if I had to teach someone, explain to someone how I think this relationship exists, how would I do that? Go through and explain it. " — So you can do that. There are a few different techniques. I'll give you like a menu of them. So at so to test yourself on a high level, you can do the you know teach it to a 10-year-old type of drill and just be really careful with yourself and just think is this actually easy to understand for a 10-year-old or is it not you know and that can help you to understand whether your overall flow is quite intuitive um and whether you've grouped it enough and it's simple enough. So that's like a very good initial litmus test. Most of the time if you're not able to do that it means that the the depth is not quite there yet. There's relationships that you generally understand but you're not able to really articulate very clearly and that means that there's a knowledge gap there. One thing there's a drill sometimes that I do in workshops which is you take those keywords that you've connected together and you take two keywords that you feel are not connected together and then you find the way that you would be able to group them like you actually deliberately try to create a schema in a way that is does not seem plausible and that can be an activity just to explore different patterns of thinking — different angles sort of approach thinking right it's like how do you look at it differently — another extension of this which is

practically maybe a little bit more useful if you find the first drill easy to do is you create your initial groups and then you predict what the other groups should be without looking at the rest of the knowledge. So an example of that is like I want you to fill in the blank here. I've got three different groups left, middle, and right. Right? Like it's it's intuitive. It's instinctive, right? Whereas so when you look at the groups and the way that you've arranged information, try to think is there a way like if I've categorized one thing as a method, the other one feels like it should be like a result, you know, something like that, you know, that feels like logical and intuitive. Whereas, if I grouped one thing as a method and then the other thing that I've grouped it as like necessary coefficients or something, it's like, yeah, I don't feel like that, you know, you would come to that instinctually. Like the only reason you'd know that group is if you memorize that group and that's high risk. — That's a similar sort of pattern, right? So, when you're talking individual nodes and linking the relationships by grouping those nodes themselves and then finding the relationships between those groups is another sort of level on top, right? — Yeah. Exactly. So you're always it's you you're always creating the layers upon layers like groups within groups and then as you form groups it gives you an idea about how the other things should be grouped as well because of that it gives you a new idea in terms of another way to you know like to reform the groups and so that process is very common where as you learn more in depth you realize that the group that you've created isn't really comprehensive for actually the concepts that you're talking about or you might have labeled as a method but then after you go through it you realize hey this is actually not a method at all I thought it was a method but this is actually like an entire architectural al principle that it's talking about, you know, so then you're like, "Okay, well now I this I can't have this label as method. I need to reabel this as principles. " But now that I've reabeled it as a principle, it doesn't fit with this other group here. So now you're like, "Okay, well, if this is a principle, then what is this group really talking about? " And then you investigate that thing. And then you say, "Oh, well then I have to split this thing off. " So that's the that process is constant. — Yeah. — Like that that's really productive learning. And in fact, if you're not doing that, there's definitely lost opportunity. And it also means that you're probably going to notice that impact in terms of the memory and your application as well. — Okay. And I guess one last thing then is what's the general method you have seen or encourage students in terms of actually capturing this physically and then how do you use that sort of material when it comes back to for future conversations. — I always recommend starting off with free form handdrawn infinite canvas mind mapping. The reason I recommend that is because it is viable to do like mirror boards uh and use like digital mind mapping and things like that. But f there's three things. First of all, you want to be able to use the free form nature of it to be like very free in the way you express the idea. Like there's a difference between me doing like this versus me doing like this. — Click the box, click the tool, drag this, the circle's not big enough, got to change the bowl. — Yeah. Yeah. There's a difference between this as well. like it's very hard to have that level of granularity without being like distracted basically by like navigating an interface and things like that. You know, you want to stay in that flow where the connection between your brain and what's happening on the pen is as close as it can be. And the benefit of that, which is the second thing, is that it gives you a visual insight into the way that you're organizing and thinking about information. It slows down that thinking process and forces you to really understand like okay you know it's you know like if I'm rearranging these ideas that are here like am I going to arrange it like this or because I understand that in between here there's likely to end up being way more information so I need to leave that space and the third thing is that it makes it much easier for diagnosis it means that when I look at the way that you've written the notes it gives me a better insight into how organized and clean your own thought process processes so that when I look at it again, I can visually spot where there might be gaps in the process. And then when you're really comfortable with doing this and your consistency and quality of learning through free form handwritten mind mapping is like 100 out of 100, then when you use digital tools, you know, you can make all the same things without breaking out of that flow. But just being able to do this fluently is like a there's a big learning curve. And so I just say be just take it safe with this. Yeah. — And when it comes to infinite sort of mind map that you're working on, how does it work when it comes to if you're writing by hand versus when you're doing it digitally, digitally you can take sections and rub them out and rewrite them and redraw them. Is that an encouraged practice as part of this or is it more just establish it and then put it to the side and then redo it from scratch? You can definitely move stuff around like you know take stuff you move it you know reconnect it differently you know like move this stuff like reconnect it like totally fine you know that's the reason why digital is better than on actual physical paper which is how I learned to do it you know in the old days because actually like the iPad wasn't I think even invented — yes we are sharing our age um no cool okay that makes sense thank you very much it's been very helpful — cool no worries um yeah and just book in your next one with me when uh you feel like you've got some stuff to show that

was my coaching call was Dan. Uh, if you enjoyed this format, please let me know. It's something new that we're trying and I genuinely want to know if it's helpful for you guys. Uh, and if you want to see how all the stuff that we've talked about comes together into a cohesive learning system, then I'd recommend checking out this video over here. Thanks so much for watching and I'll see you in the next one.