Goodbye, Google An Article by Douglas Bowman stopdesign.com Without a person at (or near) the helm who thoroughly understands the principles and elements of Design, a company eventually runs out of reasons for design decisions. With every new design decision, critics cry foul. Without conviction, doubt creeps in. Instincts fail. “Is this the right move?” When a company is filled with engineers, it turns to engineering to solve problems. Reduce each decision to a simple logic problem. Remove all subjectivity and just look at the data. Data in your favor? Ok, launch it. Data shows negative effects? Back to the drawing board. And that data eventually becomes a crutch for every decision, paralyzing the company and preventing it from making any daring design decisions. Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such minuscule design decisions. There are more exciting design problems in this world to tackle. designdecisionsdata
Mediocratopia An Article by Venkatesh Rao www.ribbonfarm.com 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. Leveling up aptitude You need to make the step forward skill
Leveling up aptitude 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. learningcreativitytastepractice