Conventional tech industry product practice will not produce deep enough subject matter insights to create transformative tools for thought.
...The aspiration is for any team serious about making transformative tools for thought. It’s to create a culture that combines the best parts of modern product practice with the best parts of the (very different) modern research culture. You need the insight-through-making loop to operate, whereby deep, original insights about the subject feed back to change and improve the system, and changes to the system result in deep, original insights about the subject.
Evergreen notes are written and organized to evolve, contribute, and accumulate over time, across projects. This is an unusual way to think about writing notes: Most people take only transient notes.
Evergreen notes should be atomic
Evergreen notes should be concept-oriented
Evergreen notes should be densely linked
Prefer associative ontologies to hierarchical taxonomies
I once read a good definition of aptitude. Aptitude is how long it takes you to learn something. The idea is that everybody can learn anything, but if it takes you 200 years, you essentially have no aptitude for it. Useful aptitudes are in the <10 years range.
Your first short story takes 10 days to write. The next one 5 days, the next one 2.5 days, the next one 1.25 days. Then 0.625 days, at which point you’re probably hitting raw typing speed limits. In practice, improvement curves have more of a staircase quality to them. Rather than fix the obvious next bottleneck of typing speed (who cares if it took you 3 hours instead of 6 to write a story; the marginal value of more speed is low at that point), you might level up and decide to (say) write stories with better developed characters. Or illustrations. So you’re back at 10 days, but on a new level.
This kind of improvement replaces quantitative improvement (optimization) with qualitative leveling up, or dimensionality increase. Each time you hit diminishing returns, you open up a new front. You’re never on the slow endzone of a learning curve. You self-disrupt before you get stuck.
The interesting thing is, this is not purely a function not of raw prowess or innate talent, but of imagination and taste.