The [Lake Erie] ecosystem underwent a series of changes, each of which were related. There was an increase in the human population; which led to higher phosophorus levels in the water; which led, at last, to an increased level of algae in the lake. In effect, Lake Erie’s ecosystem was rewritten. Changed by human activities into…something else.
But Franklin cites the study because it’s doing something slightly novel: applying Selye’s principle of stress to ecological systems, suggesting that they are, much like humans, just as susceptible to external stressors. And I’ve been thinking about that a lot lately, especially this week. Because Franklin’s suggesting that the work begins not by “fixing the system.” Rather, she suggests it’s about shifting the priority a little: to removing whatever stress you can.
In the early days, design systems promised us more consistent interfaces, more collaborative teams, and improved shipping times. While they’ve certainly delivered on some of those fronts, they’ve introduced new challenges too. Let’s talk through what’s working well—and what could be working better—as we take a closer look at the systems between us and our work.
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.