The only way to discover your strengths is through feedback analysis. Whenever you make a key decision or take a key action, write down what you expect will happen. Nine or 12 months later, compare the actual results with your expectations.
In any control system that is functioning properly, the methods used to control a signal won’t be correlated with the signal they’re controlling.
Worse, there will be several variables that DO show relationships, and may give the wrong impression. You’re looking at variables A, B, C, and D. You see that when A goes up, so does B. When A goes down, C goes up. D never changes and isn’t related to anything else — must not be important, certainly not related to the rest of the system. But of course, A is the angle of the road, B is the gas pedal, C is the brake pedal, and D is the speed of the car.
Suppose you have a problem to solve. What do you do?
Well, you sit down and think real hard, and after extensive and careful planning you try the well thought out and rigorous solution that you have thought up. Right?
No, wrong! Bad.
The correct thing to do when you have a problem is:
Think for a short amount of time.
Make sure it is safe to try things.
Try something you think will work.
Observe the result. If you succeeded, yay you solved the problem! If it didn't work, think about what that means for the nature of the problem and try again.
Conventional tech industry product practice will not produce deep enough subject matter insights to create transformative tools for thought.
...The aspiration is for any team serious about making transformative tools for thought. It’s to create a culture that combines the best parts of modern product practice with the best parts of the (very different) modern research culture. You need the insight-through-making loop to operate, whereby deep, original insights about the subject feed back to change and improve the system, and changes to the system result in deep, original insights about the subject.
Thinking [in terms of loops and arcs] allows us to let go of a specific journey or sequence, and imagine dozens of scenarios and possible sequences in which these skills can be learned. This doesn’t mean there aren’t more fundamental skills that other skills build upon, but we can let go the tyranny of how, precisely, a person will move through a system. We’re free to zoom in and obsess on these loops, which does two things for us:
Approach the design of a system as the design of these as small but significant moments of learning.
Consider the many ways these loops might be sequenced, with the exact order being less important.
Getting feedback can be thought of as a form of design research. In the same way that we wouldn’t do any research without the right questions to get the insights that we need, the best way to ask for feedback is also to craft sharp questions.
Something strange is happening in the world of software: It’s slowly getting worse. Not all software, but a lot of it. It’s becoming more sluggish, less responsive, and subtly less reliable than it was a few years ago.
In some ways this is hyperbole. Objectively, we’ve never been able to do so much, so easily with our smartphones and laptops and tablets. We’ve never pushed more data between more places more readily. But while the insidious “worseness” I mention falls only in part on the engineering side of things, it falls harder on the more subjective, craft side of things, making it all the more worrisome.
Why should we care about this? Because the majority of our waking hours take place within the confines of applications. A truth recently amplified by the covid pandemic.
And I believe software used by millions (if not billions) has a moral duty to elevate the emotional and intellectual qualities of its users. That elevation begins with craft.