a brain dressed as a heart will never beat the same way, no matter how hard it thinks about it. Your brain might be able to whip up a five-page single-spaced essay outlining exactly what you want and need in extensive detail, but your heart will always have the last word (and trust me, they will fit on a post-it). Certainty means you’re moving at the speed of trust — a personal pace that ultimately has no record to beat or even road to follow.
People, in general, are terrible at valuing their time, perhaps because for most people monetary compensation for one's time is so detached from the event of spending one's time. Most time we spend isn't like deliberate practice, with immediate feedback. We focus so much on product-market fit, but once companies have achieved some semblance of it, most should spend much more time on the problem of product-market unfit. Twitter the product/app has hit its invisible asymptote. Twitter the protocol still has untapped potential. The most obvious path to this is Groups, which can subdivide large graphs into ones more unified in purpose or ideology. Google+ was onto something with Circles, but since they hadn't actually achieved any scale they were solving a problem they didn't have yet. In addition, perhaps there is a general limit to how far a single feed of random content arranged algorithmically can go before we suffer pure consumption exhaustion. Perhaps seeing curated snapshots from everyone will finally push us all to the breaking point of jealousy and FOMO and, across a large enough number of users, an asymptote will emerge. Seduction is a gift, and most people in technology vastly overestimate how much of customer happiness is solvable by data-driven algorithms while underestimating the ROI of seduction. just because a given person's product intuition might hit on the right moment at the right point in history to create a smash hit, it's rare that a single person's frame will move in lock step with that of the world. How many creatives are relevant for a lifetime? Pattern recognition is the default operation mode of much of Silicon Valley and other fields, but it is almost always, by its very nature, backwards-looking. One can hardly blame most people for resorting to it because it's a way of minimizing blame In my experience, the most successful people I know are much more conscious of their own personal asymptotes at a much earlier age than others. They ruthlessly and expediently flush them out. One successful person I know determined in grade school that she'd never be a world-class tennis player or pianist. Another mentioned to me how, in their freshman year of college, they realized they'd never be the best mathematician in their own dorm, let alone in the world. Another knew a year into a job that he wouldn't be the best programmer at his company and so he switched over into management; he rose to become CEO. By discovering their own limitations early, they are also quicker to discover vectors on which they're personally unbounded.
Using spaced repetition systems to see through a piece of mathematics
You might suppose a great mathematician such as Kolmogorov would be writing about some very complicated piece of mathematics, but his subject was the humble equals sign: what made it a good piece of notation, and what its deficiencies were. even great mathematicians – perhaps, especially, great mathematicians – thought it worth their time to engage in such deepening. I’m still developing the heuristic, and my articulation will therefore be somewhat stumbling. Every piece should become a comfortable part of your mental furniture, ideally something you start to really feel. That means understanding every idea in multiple ways, People inexperienced at mathematics sometimes memorize proofs as linear lists of statements. A more useful way is to think of proofs is as interconnected networks of simple observations. For someone who has done a lot of linear algebra these are very natural observations to make, and questions to ask. But I’m not sure they would be so natural for everyone. The ability to ask the “right” questions – insight-generating questions – is a limiting part of this whole process, and requires some experience. Conventional words or other signs have to be sought for laboriously only in a secondary stage, when the mentioned associative play is sufficiently established and can be reproduced at will. So, my informal pop-psychology explanation is that when I’m doing mathematics really well, in the deeply internalized state I described earlier, I’m mostly using such higher-level chunks, and that’s why it no longer seems symbolic or verbal or even visual. I’m not entirely conscious of what’s going on – it’s more a sense of just playing around a lot with the various objects, trying things out, trying to find unexpected connections. But, presumably, what’s underlying the process is these chunked patterns.
Designing with Intuition — Vicki Tan from Headspace
The secrets data won't tell you
It’s become standard to lean on quantitative, experiment-driven design, especially when decisions must be made quickly and with very little time and resources. But this method often only reveals surface-level themes and not much about your users’ true intentions. In this onboarding case study, Vicki will walk you through how we learned to design using intuition, blending science and design research to create a solution that met our users’ needs.
About Vicki
Vicki is a Product Designer at Headspace, creating experiences to guide new users towards a healthy meditation practice. Previously, she was at Lyft, optimizing the passenger ride experience, and at Google, designing tools for reducing bias and predicting outcomes. Prior to Google, Vicki was at Stanford School of Medicine coordinating research studies in Pediatric Oncology. She holds a degree in Behavioral Psychology from the University of California, San Diego.