Most people are bad at programming. Most people that are good at programming are very busy. They are not usually the people who advise you on how to program.

I'm primarily self-taught. I always enjoyed understanding how things work and getting skills in those areas. I would spend a lot of time finding various articles and explanations for the problems I wanted to solve and trying to find the best way. It was a slow, arduous, and, most of the time, unfulfilling process - at least, this was my perception then. The results of following this process included grit, humility, and a repertoire of analogies that I could introduce in conversations. At that time, I wasn't reflecting as much as I do now, and although I was aware of multiple ways of doing things, I couldn't determine which was the "correct" way.

Being the youngest in the room.

I was lucky to have had many doors open since I was young. Most frequently, I showed potential, and many people considered hiring me to work together on a problem. It was a bet each time hiring me since I couldn't showcase real-world high-impact issues, but somehow, I could maintain conversations on that level. A common feedback I receive is that I'm too mature for my age. So, I'm often the youngest in the room and, at the same time, not the least experienced (yay!).

In this position, I tried to learn as much as possible from the more experienced folk. Learning to think better, execute better, and communicate better. Since a few years back, much of my progress has been unlearning around half of the things I thought were good and correct. I'm not saying that half my peers are wrong or that half the knowledge they know is terrible, but it's how I understood it and accepted it as facts. I believe we are always trying our best with the available resources (tools, knowledge, skills).

Context is part of the conversation.

A choice can be stressful since it can have repercussions. If a choice is easy, then it's not a choice anymore; its outcome would be a default value we accept. An example where analogies are not always great is that I sometimes hear the "paradox of choice" principle in conversations around choices. A team once tested if putting more kinds of jam on a supermarket display would convert into more or fewer people buying jam. The conclusion usually shared is that adding more possibilities makes the decision process harder, sometimes too hard.

So, if you remove products, sales will increase, right? Why are supermarkets still selling so many brands and alternatives? A few paragraphs from Uncontrolled by Jim Manzi:

First, note that all of the inference is built on the purchase of a grand total of thirty-five jars of jam. Second, note that if the results of the jam experiment were valid and applicable with the kind of generality required to be relevant as the basis for economic or social policy, it would imply that many stores could eliminate 75 percent of their products and cause sales to increase by 900 percent. That would be a fairly astounding result and indicates that there may be a problem with the measurement.

[...] the researchers in the original experiment themselves were careful about their explicit claims of generalizability, and significant effort has been devoted to the exact question of finding conditions under which choice overload occurs consistently, but popularizers telescoped the conclusions derived from one coupon-plus-display promotion in one store on two Saturdays, up through assertions about the impact of product selection for jam for this store, to the impact of product selection for jam for all grocery stores in America, to claims about the impact of product selection for all retail products of any kind in every store, ultimately to fairly grandiose claims about the benefits of choice to society. But as we saw, testing this kind of claim in fifty experiments in different situations throws a lot of cold water on the assertion.

Further, these causal relationships themselves can frequently change. For example, we discover that a specific sales promotion drives a net gain in profit versus no promotion in a test, but next year when a huge number of changes occurs - our competitors have innovated with new promotions, the overall economy has deteriorated, consumer traffic has shifted somewhat from malls to strip centers, and so on - this rule no longer holds true. To extend the prior metaphor, we are finding our way through our dark room by bumping our shins into furniture, while unobserved gremlins keep moving the furniture around on us. For these reasons, it is not enough to run an experiment, find a causal relationship, and assume that it is widely applicable. We must run tests and then measure the actual predictiveness of the rules developed from these tests in actual implementation.

So, every time I read a blog post with succinct wisdom drawn from a single experiment in a single domain, I remember this. We should expect real challenges to be tough to understand and overcome. So, if no context is attached to the wisdom, the wisdom should be checked more before acceptance.