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?"
My own time in a Silicon Valley startup has proved this much to be true; planning doesn’t make for better software. In fact today our design systems team doesn’t have sprints, we don’t have tickets or a daily standup. Each day we come to work, figure out what’s the most important thing that we could be doing, and then we—gasp!—actually do it.
Watching so many other teams slowly flail about whilst they plan for quarter 3.2 of subplan A, whilst our team produces more work in a week than they all do combined in a quarter has been shocking to me.
After four years of working in a large startup, I know what I always assumed was true: you don’t need a plan to make a beautiful thing. You really don’t. In fact, there’s a point where overplanning can be a signal of inexperience and fear and bullshit. The scrum board and the sprints and the inane meetings each and every day are not how you build another Super Mario 64.
Instead all you have to do is hire smart people, trust them to do their best work, and then get the hell out of their way.