How to Memorize Large Amounts of Information Quickly (Encoding Guide)
You only need these 3 questions to master encoding (including a step-by-step real time studying walkthrough of encoding itself)
I spent my first airplane flight of 2026 studying a Wikipedia page.
Yes. I am a loser…
…but it was the most fun I’ve ever had on an airplane flight to date!
And I’ve also learned so much about encoding.
Encoding is how you store information in your long-term memory.
If you have ever met someone who seems to just remember lots of information instantly, it’s because they have excellent encoding skills.
Before we begin, it’s important for you to know that this is a continuation of this post.
Read that post on priming before you read this. It’s important that you do so. It also goes through how I currently conceptualize my own learning system:
You’re back, yes? You’ve read it?
Excellent!
Now let’s learn about encoding.
To remember more, you must edit what you already know
Encoding is not about simply cramming more information into your brain.
I once spent 2-3 months last year writing over 70,000 words worth of linear notes in Obsidian from just 3 books, and how much of those notes do you think I remember?
Absolutely fuck-all :)
Why?
Highlighting words in a book doesn’t mean you’re encoding the ideas into your long-term memory (I’m looking at you, 6th-year me, who highlighted 95% of the Irish history section of my history book cause it bored the shit out of me).
Writing and adding notes to your second-brain software doesn’t mean you’re adding new knowledge to your long-term memory either. You only think that writing leads to learning because you’re engaging in the encoding process without realizing it. Correlation does not equal causation here.
And encoding has less to do with adding information to your memory but rather transforming what you already know.
It’s like pulling weeds from your own garden of knowledge so you can grow new flowers in their place. Letting nicer flowers connect and become integrated within the ecosystem you’ve already built. Your own beautiful walled garden of knowledge.
Profound Idea: Isolated information will always get deleted by the brain, but connected, integrated, and deeply rooted information won’t move a damn muscle.
Now, return back to my 70,000 words worth of linear notes example:
I was just hoarding information without actually integrating it into my garden of knowledge inside my own brain.
Hermann Ebbinghaus, the guy who theorized the forgetting curve, said that the brain forgets 50-70% of what you learn within 24 hours if you do not encode it.
Meaning that when you sit down to read Crime and Punishment for an hour one Thursday evening, and realize you have gained nothing of practical value from doing so, this is why.
If you’re not connecting information to prior knowledge (through what’s called elaborative rehearsal) it will get binned with your morning coffee sachets when you go to sit at your desk and “read.”
Profound Idea: Your mind is a spider’s web and not a storage box. And…
… the act of encoding information is how you weave new threads into that web, and you also need to be willing to cut the dead ones if you want to learn anything new.
So.
How do you engage in the encoding process with the most simple system possible? That can be used immediately by any learner, for any purpose?
Use these 3 questions and that’s it
I don’t see a point in doing a deep-dive into all the principles and neuroscience of encoding for two reasons.
Because (1) most people would get very overwhelmed trying to take it all in in one sitting - myself included - and (2) I want you to take something from this guide to use immediately, to start improving your encoding skills by at least 20-50% right away (that’s a rough but achievable estimate, especially if you’re new to all this).
It’s also the reason why this newsletter is less about explaining the learning science itself and more about offering my own perspective on the learning science. In all honesty there’s nothing stopping you from asking Chatgpt or Claude to explain encoding to you in simple terms in whatever way you’d like.
But this guide is about offering my own understanding of encoding, and I hope to offer a perspective on learning how to learn that you can’t get anywhere else.
So.
There are two ways of looking at encoding in terms of the processes involved.
In terms of the AQAL model, that would be from the Q1 and Q2 perspectives; the physical processes inside the brain and the mental questioning inside the mind.
Put simply, how encoding happens through the neurons firing inside your brain, and how you encode information through thinking about the right questions with your mind.
Hence, I have condensed everything I know about effective encoding into just 3 questions for you to ask yourself while learning anything.
I repeat.
You only need these 3 questions to engage in the encoding process.
I will support each of these questions with the theory behind them soon.
But for now I want you to drill these questions into your mind and to always keep asking yourself them relentlessly:
How does this relate to what I already know, and what I’ve been reading?
How does this change the mental model I’m building?
How do I plan to retrieve this knowledge, or in other words, use this knowledge for a desired outcome in the future?
That’s it.
These questions cover at least most, if not all the techniques that require high quality encoding.
I want you to think about these questions before you read on through the rest of this newsletter, and to look for reasons as to why you think they work.
These questions will also force your mind to think upwards towards the higher levels of thinking based on Bloom’s taxonomy (evaluation and creation).
Now that we have our simple encoding system covered, I will now show you why these questions work for encoding, and how I used these questions to learn about encoding from the Wikipedia page itself - real time encoding while learning about encoding!
Your brain is a web and not a box
Before we get to the walkthrough of how I went about doing some encoding in real time, you need to understand the mechanism behind why we are encoding.
Profound Idea: Real knowledge doesn’t look like a page of linear notes. It looks like a spider’s web.
I’ve said this profound idea enough as you might know by now and it’s always worth restating. But I’ve finally learned the underlying principle behind why this is the case.
Finally, a name to the face… or the theory.
It’s called semantic network theory.
New information doesn’t get “stored” into your long-term memory in isolation. It gets integrated into existing connections that are already there.
Think of your long-term memory as a spider’s web. Every concept is a node. Every connection is a thread. When you learn something new you’re not adding a new box to a shelf. You’re actively weaving a new thread into the web, which means the stronger your connections the less you forget.
Isolated information gets forgotten and connected information grows roots and becomes immovable.
This is why I hate linear notes, and I don’t know why we just aren’t told that knowledge is non-linear in this way.
We have over a century of research proving that linear learning is a disease, supporting why I think taking linear notes and learning through rote memorization with linear notes will always be a fucking disease to teach anyone.
Sorry if you disagree.
But that’s my contrarian perspective I’m offering on the learning science.
Here’s the history:
In 1885, Hermann Ebbinghaus proved we forget information rapidly without encoding. He used a metronome while repeating nonsense syllables to test his memory and discovered that repetition alone isn’t enough to remember something. When he repeated syllables that did have a meaning to his brain, he remembered those syllables better. This is due to semantics. You need meaningful encoding to beat the forgetting curve.
In 1949, Ivan Pavlov and Donald Hebb gave us the concept of schemas. Knowledge inside the brain looking like a spider’s web. Hence the phrase “neurons that fire together wire together.” Your prior knowledge creates the neural pathways that new information travels on. If you don’t have a schema (spider’s web) to catch the new information, it falls straight into the bin outside your own brain.
In 1956, George Miller discovered that our working memory is tiny. We can only hold 7±2 units of information at once (not items, but units - I will talk about how to organize items of information into units through a technique called chunking later on). Again, note that I said units and not items. A phone number isn’t 10 digits. It’s 3 chunks. This is why we must group concepts (chunking) to fit them into our brains, especially to reduce cognitive overload while reading.
In 1972, Fergus Craik and Robert Lockhart proved that depth of learning matters. A lot. Deep processing (focusing on relevance and integration) creates stronger memories than shallow processing (focusing on what the words look or sound like in isolation).
All of these discovery points throughout history point to the same profound idea:
Profound Idea: Encoding is about integrating new information into your existing web of knowledge.
That’s it. That’s encoding.
And integration requires transformation. You can’t just weave new threads into a blanket without changing the overall pattern. Like how the philosopher cannot sculpt his own mind while expecting change to feel effortless and pain-free.
Thinking must be done with a hammer and that’s why it hurts. This is why encoding feels like destruction as much as construction.
A metaphor for understanding encoding
I’m going to steer away from using my “mind is a garden” or “knowledge is a web” metaphors for a second to explain the mechanics of how encoding works.
Here’s the big picture of how encoding works with all its parts and steps.
I want you to imagine encoding like building with Lego bricks.
