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Everywhere you turn, someone’s either hyping up AI or panicking about it.
But if you’re a lifelong learner, you can’t afford to miss one simple fact:
The real danger isn’t the technology itself.
No, the major problem we all face is how other people’s thoughts about AI quietly and constantly reshape our thinking.
Pretty much on a daily basis, we undergo a whiplash of influence as one person plays prophet of doom and another froths with unhinged praise.
If you don’t study memory and its relationship to thinking as much as I do, you might not notice this shift happening.
But I do, and am concerned that many people can’t see why the disconnected dialog about artificial intelligence is so corrosive.
Perhaps most alarmingly of all is how many people adopt new tools unthinkingly and try to move faster, consume more and mistake speed for substance.
Little by little, they come to rely on the dopamine hits created by endless summaries instead of doing the critical thinking work that leads to synthesis and understanding.
The solution for you so that you don’t burn out and wind up forgetting everything you try to learn?
Slow down.
Continue using notebooks, sketches, mind maps and time with physical books.
As I’ll show you in a moment, the best AI innovators are doing just that.
And it’s smart because these simple activities will help build your memory, preserve your thinking and ensure you get the most out the new tools. While continuing to enjoy the benefits of ancient memory techniques.
To help you find the balance, in the video below and various resources I’ve shared on this page, I’ll help you explore AI technologies while creating a brain that no technology can imitate.
Let’s get started.
How to Use AI as a Lifelong Learner (Without Harming Your Memory)
The first strategy is to keep using physical notebooks.
You might think that sounds old fashioned, but it’s not.
For example, David Perell recently had Sam Altman on his podcast to discuss his method for clear thinking.
It’s very similar to the journaling method I’ve been teaching myself for years. It involves pen, paper and the mind. Nothing more.
If the CEO of OpenAI operates this way, why wouldn’t you?
I think this example, amongst the journaling habits of other top performers is great. It helps us completely sidestep yet another paranoid conspiracy that suggests the moment you stop writing by hand, you start letting machines dictate how you think.
It’s the other way around:
The humans shaping the way artificial intelligence platforms operate regularly journal.
Why Analog Tools and Slow Reading Matter More Than Ever
Their example is also useful because it highlights the relationship between the medium you use to assist your thinking, what you think about, and how you think.
And I believe it’s beyond obvious that many people mistake how fast they consume information as an accomplishment, when far too often it’s really just busy work. Little more than activity.
This confusion of activity as accomplishment isn’t a new problem. Speed reading gurus have duped people for years with the fantasy that speed is a kind of substance.
And the few good ideas you might find in speed reading books and courses? They tend to be borrowed from somewhere else.
Skimming and scanning books, for example?
Many, much better tactics existed decades before mass market speed reading books started teaching such tactics. Many ultimately wound up watering the strategy down.
These days, the entire speed reading industry is obsolete. And the reading approaches I’ve advocated since my university teaching days has never been more important.
I’m talking about my realistic approaches to reading faster, finding the main points and memorizing what matters in textbooks.
It’s more important than ever before because now, the real skill is knowing when to use shortcuts and when to apply reflective thinking so that books have time to settle in.
Sometimes it makes sense to take a second pass through courses and books. This is one reason I developed a personal re-reading strategy.
Even though I use zettelkasten and the Memory Palace technique, reviewing both your notes and the source material often gives you additional insight that you cannot get any other way.
Yet, we live in an “efficiency” focused culture where the speed of AI summaries create an illusion of depth, when in fact they are actually prompts to get back to traditional reading tactics and techniques.
The Real Meaning of Artificial Intelligence
As you can tell by now, I’m not at all saying to avoid using AI.
Rather, I believe that the best way to protect your lifelong learning goals must involve learning to use it through experimentation.
But not without acknowledging the strange paradox we all face. Various AIs can now summarize any book you feed them. In all kinds of flavors depending on their training.
In other words, if you want to know how a celebrity would criticize a book, there’s an AI that can approximate their response for you.
Yet, despite this wealth of textual production, very few people can remember what they read last week. Some people can’t even remember what they read an hour ago.
Adding to the confusion is the fact that many people are using chatbots and calling them artificial intelligence, when they are anything but.
Unless we actively approach the learning process differently, we will continue living in a world where increased volumes of content decrease retention.
So how do we reverse the trend?
One of the best critical thinking exercises you can conduct is to think much more deeply about what this term “artificial intelligence” means.
In my view, many people use “artificial intelligence” far too loosely, almost the way we use terms like “automobile” or “vehicle.”
Rather than do that, try and stop yourself and drill down into specifics.
To that end, let’s look at some interesting authors and creative people who can help you form better definitions for the various aspects of what AI is (and is not).
Four Books That Show What Real Thinking About Artificial Intelligence Looks Like
If you want to see what real thinking about AI and its relation to learning looks like in practice, you won’t find it summaries.
You’ll find it in the work of people who engage the physical world, wrestle with complexity, and use tools, both analog and digital.
The following authors show, each in their own way, what disciplined perception and deep understanding actually produce.
Andrew Mayne
Andrew Mayne is a polymathic inventor, author, magician and multi-media talent.
I recently heard him talking on a podcast he co-hosts called Weird Things about how important memory training and using physical notebooks is to him.
The episode is called Robots, AI, and the Future of Work: A Deep Dive.
In this dynamic discussion, Andrew also talks about various angles on robotics and how important human connections still remain to him… even though he is deep into multiple areas of artificial intelligence and generative chatbots.
He’s also the host of the Open AI podcast, a role that started not long after he appeared on this episode of the Magnetic Memory Method Podcast.
One thing you might notice in that episode is that Mayne is surrounded by interesting physical objects. He loves new technologies and the world they can potentially help us create, but not at the expense of the immediate, physical world.
He’s a huge fan of memory techniques too, but at this moment, I’d like to highlight one of his most interesting novels: The Naturalist.
On top of being excellent genre fiction, it’s also a very interesting meditation on the nature of the physical world, new technologies and the role of expertise.
The tactile world is everywhere in the novel and Mayne expertly conveys the raw sensory foundation true expertise requires.
Although technology is involved, the role of observation as a mental discipline shines through. Essentially, you’re reading about the human training of perception itself based on the mind’s ability to track multiple data points in both the physical and technological worlds.
In order to think about them and solve problems in both the immediate world and the digital, Mayne’s hero needs to rely on critical thinking muscles AI can never replace.
That’s why it’s ultimately a book about the kinds of computational thinking humans have done for a long time in collaboration with our technologies.
Here’s a key example, probably my favorite part of the book:
“Our war on cancer has been filled with countless maybes. Billions of dollars and millions of human hours have been spent chasing after a pattern we can’t even begin to guess at.
Even still, we’ve made some progress. Many of these maybe have panned out. People live longer than before because not all that effort was wasted. And for every maybe that turns out to be a no, we still move forward.”
Don’t mistake this for romanticism. It’s more like cognitive realism.
Our brains evolved to think through contact with the world. Digital tools can extend that process, but when we allow our fears about technology to replace our common sense, comprehension collapses.
Michael Connelly
The second book I suggest you check out is The Proving Ground by Michael Connelly.
In this legal thrillers Connelly delivers a courtroom narrative where truth itself is on trial. Following the death of a young student prompted by a young man’s exchange with an inappropriately trained chatbot, you as the reader explore how quickly a legal team has to learn to use multiple technologies.
In the story, data gets forged, evidence gets erased, and reality itself gets imitated, messing with the procedural mechanics that both the legal thriller and crime novel rely upon. It’s like the nature of proof becomes entirely psychological as the characters feel the need to train themselves faster than the latest LLM.
But another reason I think of Connelly is interesting for those of us interested in learning memory is that he’s built an entire paracosm around a character named after Hieronymous Bosch. This is an allusion to the painter of astonishing works like The Garden of Earthly Delights and The Last Judgment.
These are fairly highbrow references in so-called popular fiction, but my point is that Connelly’s productivity is hardly the antithesis of algorithmic creativity.
It’s referential.
Plus, Connelly was a crime reporter before succeeding with fiction. And it was observing real life detectives while reading other writers in the crime genre that led him to finding the missing ingredient that brought his own stories to life.
It was literally seeing a detective put the arm of his glasses into his mouth while crouching over a victim’s body that he found what he needed to make his fiction seem real.
How is that not training in a way that reflects how AIs work to produce their outputs?
How I Trained On Connelly to Produce My Memory Detective Series
One reason I’m excited by some of the generative text AIs is that I’ve written many books. Some of them are memory training guides in the style of Tony Buzan’s The Memory Book.
Others are more personal, like The Victorious Mind. I was influenced (or trained and prompted) by the stories shared in Moonwalking with Einstein and Ultralearning.
Yet other works are translations from the ancient memory tradition by people like Peter of Ravenna and Jacobus Publicius.
But Connelly holds a special place in my personal writing within the memory improvement niche because his books helped spawn my Memory Detective series.
There’s a long story behind how exactly Connelly arrived in my one, one I shared with Guru Viking on this episode of his podcast.
But the key point is this:
When Connelly originally inspired me to produce “Magnetic Fiction” that uses the detective genre to teach memory techniques, I originally considered reworking Sherlock Holmes stories that were in the public domain.
Early Training Meets New Goals in a Brave New World
But that didn’t seem quite right, especially since I had written many novels before and worked in the film industry.
As I shared in How to Remember a Story, I spent years as a Film Studies professor and wound up working on a few movies as a story consultant. I even have a screen credit as a writer.
So although I could have used ChatGPT to write Flyboy, the first novel in the series, I decided to study Connelly novels even further and write the book on my own.
But it was also my memory of how stories work that I drew upon to produce the text, almost like an AI draws upon training. In fact, I would go so far as to say that everything I produced could only come from the training of what I’d previously read.
The point I’m trying to make might sound abstract, but what I’m trying to suggest is that my works are compressions of what I’ve studied. As are Connelly’s.
Speaking of “compression,” the next book I’d like to recommend takes the idea of learning and memory through training to an astonishing level.
The Radical Compression of Poetry Into Living Matter:
Christian Bök & The Xenotext Project
Christian Bök’s Xenotext project is the most literal act of intellectual preservation imaginable. It is a decades-long attempt to encode a poem into the DNA of a radiation-resistant bacterium called Deinococcus radiodurans so that two poems can endure for thousands, even millions of years.
As another genuinely polymathic thinker, Bök spent years shaping The Xenotext through a combination of computational tools and deeply human expertise. His work exemplifies the point I’m trying to make about learning and memory because Bök successfully managed to:
- Commemorate meaning in our brave new world of big data and new interactions between biology and technology
- Encode human thought in a way that resists much of the ephemeral thinking of our times
- Counterbalance computational art with the AI-generated noise and “slop” we are now regularly navigating online
- Approach learning through research, endurance, patience and the materialization of conceptual ideas that anyone can enjoy
To accomplish all of this, Bök studied molecular biology, worked alongside geneticists, and carved a poem out of thousands of biochemical possibilities until it could survive as both literature and living organism. It is a fusion of the ancient ambition to become immortal with the rigor of modern science.
So when people claim that creativity ends the moment machines can mimic art, I point them to The Xenotext as an image of what books will be like in the future and in some ways have already become thanks to AI.
As quoted in a Stanford University article, we are facing the possibility of working regularly with books that “no longer take on the form of codices, scrolls, or tablets, but instead [….] become integrated into the very life of their readers.”
When you can carry not only entire libraries in your smartphone, but actually talk to them and get a response, it’s my view that we’re already living in this world.
But equally interesting to me is how Bök’s project reveals what true interdisciplinarity looks like. It’s not chasing new tools for their novelty, but extending a lineage that runs from Homer to the present on a quest to create beautiful works that endure.
Bök’s success isn’t a story of speed. It’s a story of patience, constraint, and the willingness to make thought incarnate even at a microscopic scale. The smaller the medium, the more pressure it places on the idea. Which is why the central vision of The Xenotext feels cosmically large.
The Ancient Connection Between Compressing Ideas Into Matter and Human Memory
Fans of memory techniques will recognize the name instantly, but they might not have heard some of the lesser known tales of Simonides of Ceos.
I’m referring to the ancient poet credited with inventing the Memory Palace technique, or method of loci as it’s also known.
Simonides was also known to carve epitaphs in stone.
Once, on the way to catch a ship for a long, oceanic journey where he would work on writing epic poems in praise of the finest achievers of his time, he came across a dead body. So Simonides gave the abandoned man a proper burial and carved into the stone epitaph:
οἱ μὲν ἐμὲ κτείναντες ὁμοίων ἀντιτύχοιεν, Ζεῦ ξένι᾿, οί δ᾿ ὑπὸ γᾶν θέντες ὄναιντο βίου.
I pray those who killed me get the same themselves, O Zeus of guest and host, I pray those who put me in the ground enjoy the profit of life.
“Enjoy the profit of life.”
Before we continue with the story, think about what just happened.
Simonides encoded his wish for a reward by programming it into stone.
Is this act really that different than Bök encoding a poem into a deathless bacterium in the hopes that a few of our words might enjoy the profit of life beyond the death of our sun?
Later that night, the ghost of the dead man appeared to Simonides in a dream.
“Don’t get on that ship,” the ghost said.
Simonides warned his fellow travelers the next morning about the ghost’s message, but they would not listen. Everyone but Simonides got on board and the ship sank.
In response, Simonides returned to the epitaph and wrote,
οὗτος ὁ τοῦ Κείοιο Σιμωνίδου ἐστὶ σαωτήρ, ὃς καὶ τεθνηὼς ζῶντι παρέσχε χάριν
This is Simonides’ savior who even though dead, has bestowed on the living a grace.
Whether it’s Simonides chiseling an epitaph or Christian Bök encoding poetry into biological matter, the impulse is the same:
To ensure that meaning endures beyond the noise of the moment. Thought becomes durable when it is fused with matter.
This is where your learning habits matter.
Because in an age where AI can generate interpretations, summaries, and opinions at scale, it is dangerously easy to adopt other people’s conceptions of AI without realizing it.
Those impressions don’t just stay on the surface. They settle into implicit memory, the form of memory that shapes your assumptions and decisions beneath conscious awareness.
The only antidote to the harm that passive acceptance creates is deliberate, embodied thought and regular acts of memory-based learning.
This means:
Reading widely.
Thinking slowly.
Taking physical notes that force your mind to engage with the material rather than passively absorb someone else’s framing.
That’s how you prevent your implicit memory from being silently steered by the loudest or fastest voice in the room. Human or machine.
And if you want to build a system that protects your ability to learn in this way, especially now, then I strongly encourage you to go through my Self-Education Blueprint:
It’s designed to help you construct a learning philosophy grounded in clarity, embodiment, and intellectual autonomy.
If you’ve already completed it, revisit it now with the lenses we’ve explored today.
You’ll see new pathways you missed before.
And you’ll be ready for whatever comes next.
Because whatever it is, it’s coming.
And where preparation meets opportunity, there is no ceiling.
