There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [1, 2]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas.
Walking intrigues the deskbound. We romanticize it, but do we do it justice? Do we walk properly? Can one walk improperly and, if so, what happens when the walk is corrected?
This talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?"
"Feature complexity is like surface area and quality of execution is like height. I want a base level of quality execution across all features. Whenever I commit to building or expanding a feature, I'm committing to a baseline of effort on the user experience."
There’s a distinction to make: The set of features you choose to build is one thing. The level you choose to execute at is another. You can decide whether or not to include a feature like ‘reset password’. But if you decide to do it, you should live up to a basic standard of execution on the experience side.
Features can be different sizes with more or less complexity, but quality of experience should be constant across all features. That constant quality of experience is what gives your customers trust. It demonstrates to them that whatever you build, you build well.