On Talent I observed something fairly early on at Apple, which I didn’t know how to explain then, but I’ve thought a lot about it since. Most things in life have a dynamic range in which [the ratio of] “average” to “best” is at most 2:1. For example, if you go to New York City and get an average taxi cab driver, versus the best taxi cab driver, you’ll probably get to your destination with the best taxi driver 30% faster. And an automobile; what’s the difference between the average car and the best? Maybe 20%? The best CD player versus the average CD player? Maybe 20%? So 2:1 is a big dynamic range for most things in life. Now, in software, and it used to be the case in hardware, the difference between the average software developer and the best is 50:1; maybe even 100:1. Very few things in life are like this, but what I was lucky enough to spend my life doing, which is software, is like this. So I’ve built a lot of my success on finding these truly gifted people, and not settling for “B” and “C” players, but really going for the “A” players. And I found something… I found that when you get enough “A” players together, when you go through the incredible work to find these “A” players, they really like working with each other. Because most have never had the chance to do that before. And they don’t work with “B” and “C” players, so it’s self-policing. They only want to hire “A” players. So you build these pockets of “A” players and it just propagates. Steve Jobs, Steve Jobs: The Lost Interview Waste as little effort as possible on low competenceA small team of committed coworkersBuild projects around motivated individualsIndividuals matter talent
Waste as little effort as possible on low competence One should waste as little effort as possible on improving areas of low competence. It takes far more energy and work to improve from incompetence to mediocrity than it takes to improve from first-rate performance to excellence. Peter F. Drucker, Managing Oneself 95%-ile isn't that goodOn Talent talent
95%-ile isn't that good An Article by Dan Luu danluu.com Reaching 95Mistakes at the top Waste as little effort as possible on low competence talent
What Do Metrics Want? How Quantification Prescribes Social Interaction on Facebook A Research Paper by Benjamin Grosser computationalculture.net What are the effects of this enumeration, of these metrics that count our social interactions? In other words, how are the designs of Facebook leading us to act, and to interact in certain ways and not in others? For example, would we add as many friends if we weren’t constantly confronted with how many we have? Would we “like” as many ads if we weren’t told how many others liked them before us? Would we comment on others’ statuses as often if we weren’t told how many friends responded to each comment? In this paper, I question the effects of metrics from three angles. First I examine how our need for personal worth, within the confines of capitalism, transforms into an insatiable “desire for more.” Second, with this desire in mind, I analyze the metric components of Facebook’s interface using a software studies methodology, exploring how these numbers function and how they act upon the site’s users. Finally, I discuss my software, born from my research-based artistic practice, called Facebook Demetricator (2012-present). Facebook Demetricator removes all metrics from the Facebook interface, inviting the site’s users to try the system without the numbers and to see how that removal changes their experience. With this free web browser extension, I aim to disrupt the prescribed sociality produced through metrics, enabling a social media culture less dependent on quantification. metricstechnology