About Of Relevance

What is this place?

Of Relevance is a collection of ideas and concepts that I find worth researching and remembering. It’s my version of a personal digital note taking system.


I (like most people) learn best by taking a three-step approach to knowledge: first I acquire it (reading or listening), then practise it (by doing or discussing) and then (ideally) teach it (explain it to others). The first step is easy for me, and I happily consume plenty of content daily. It’s the second step – the practice and consideration of this consumed content – that presents the challenge, and I find that “acquired” concepts that at first greatly excite me are too soon forgotten in the chaos of daily life. Not only is this increasingly frustrating (am I missing out on the secret to life?) but it also seems like consuming the content is a waste of time and effort (even if it probably isn’t). My solution is to therefore jump into the third step and “teach” what I read.

“Teach” is a bit of a misnomer, since I am actually teaching myself, not you, the reader. So it’s more learning than teaching. But by making this endeavour public I hope it may benefit someone else, and possibly facilitate further discussion (and thus more teaching). It also forces me to be deliberate about what I consume, how I think about it, what I write and thus what I retain.


When I come across content that I think is worth thinking about further, or sharing, I make detailed notes on the parts that interest me (I use Logseq as my note taking app). I then formulate those notes into content that I share here or on Twitter/X.

All the content I produce is meant to be fluid, and possibly temporary. As I go deeper down rabbit holes, and come across complementing or contrasting points of view, notes are adjusted, interlinked or amalgamated. It takes about a week to go through a full podcast (some of them are over 3 hours long), make notes, go away to think about stuff, go down rabbit holes, synchronise with previous notes. At this point (Dec 2023), I have no plans to use AI in any of this process (that might change?) and I estimate it will take about a year before I may have something of significant value here.

Side note: It’s important to repeat that I am teaching myself, not you. So when I write a “summary” of a book or a podcast, I focus on ideas that resonate with me. Almost guaranteed, those ideas are different than those that would resonate with you (and they are also different from ideas that will resonate with me in the future, when/if I ever re-read or re-listen to the content). Don’t treat my writings as a comprehensive summary, but more like a gentle prod to the original content.

Done is better than perfect. I assume that I will to get much better at this the more I do it. I will allow for that improvement to happen naturally and gradually, and will not sweat an overwhelming amount of time trying to get a piece just right. By definition therefore, this is a work in progress.


I apologise in advance. I am very bad at attribution. My notes can be transcribed word-for-word, or paraphrased, or written down once they have percolated in my head for days. In my haste to jot ideas as I listen/watch/read I rarely record perfect attribution. In addition, as my notes expand, I reference and amalgamate other view points. By that point, once everything has been mushed and edited over and over, it is impossible for me to keep track of what is a concept that I read or heard somewhere else, and what is an original thought that was inspired by someone else. I will try my best to give credit where credit is due, but honestly if in doubt assume someone else said it first, even if I don’t include the source. I understand this approach rarely flies in the world of academia, but also… this isn’t a thesis.

What will you find here?

Ideas and explanations inspired by podcasts, books, articles/ other written content, interviews and my own thoughts. These are brief snippets, meant to start a rabbit hole exploration, or just some reflection or deep thought.

Topics that currently (Dec 2023) interest me: AI (specifcally how it will affects our next 5 years with respect to health, education, work, income), productivity, self-help, health, digital strategy, the chasm between digital mavens and noobs, scientific spirituality (eg manifestation as a neuroscience), meaning and self-discovery.

I enjoy the works of: Andrew Huberman, Ali Abdal, Arthur Brooks, Esther Perel, Lex Friedman, All-in Podcast, Paul Graham, Steven Barlett, The Atlantic, The Cut, Bloomberg Business Week, Wired, Fast Company, Tara Swart, Ryan Holliday, Tim Ferris, First Million Podcast.

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