A week ago, when I was commuting back to home, I had a brilliant idea for an essay. I thought of an introductory narration and as I can recall, it sounded good. I didn’t write anything that day but attempted to in the next. Unsurprisingly, the clarity had vanished. I couldn’t even finish a few lines—and even they weren’t delightful to read.

Why was something that was effortless a day before became a laborious struggle?

It wasn’t obvious why that happened. I attributed it to the unaccounted difficulty in ideating vs. trying to do it. But, a few days back I found the actual reason. I was blocked because I was overanalyzing everything. Here’s how I wrote:

I would write a sentence, rethink it, and write it in another way. Then, I would read it aloud to make sure it sounds good; if unsatisfied, I would repeat the whole process. I would, then, reiterate it for the paragraph. When the rewording, rethinking, and reading got exhausting, I would give up because a simple paragraph took ten minutes to construct.

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Young people, indirectly or otherwise, are sold on the idea of “following your passion”; that you can’t go wrong pursuing your interests. A person should become a musician if he likes practising music; a writer, if he likes writing.

It might be an India-specific thing but high school graduates are prone to think that modern society wrecked their only chance of pursuing their dream when they weren’t allowed to take a college course in that direction, in their “field of interest”. Safe careers are believed to be the antithesis of a purposeful life that their “passion” could’ve given them. I believe the popularity of the sentiment was heightened when “3 Idiots”, a Bollywood movie, portrayed in a fairy-tale way, that everyone should do what they’re made to do. It’s easy to see the movie and shout: “Yep! That’s me.”

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Most software ventures fail and they fail because they never solved a problem, to begin with. The Internet has made it easier than ever to start a software business but, at the same time, made it too enticing to create a product that no one needs. For that reason, it’s only rational to first test the waters with a Minimal Viable Product—a reduced subset of a full-blown software. As the well-reasoned logic goes, if people are ready to pay for your rough-and-ready product, there’s decent chance you’re heading in the right direction.

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I have always delayed buying furniture. The act of buying sizeable things induces a feeling of acquiring a burden that will affect my relocation freedom. For a considerable time, I didn’t have a table in my room. I worked on the bed with my Macbook during this time. It wasn’t awful but mentally, I made it be.

Source: Mac Desks

Browsing stunning photos of professional desks, I was often awed by neatly kept books, stationary, and a high-resolution monitor. I fancied the delight of having the same environment, believing it’d bring a kind of a productivity boost. To an extent, I held my working conditions culpable for my procrastination problem. The reason I didn’t feel like working on my side-project, I thought, is because my environment needs to be fixed.

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There isn’t any established science that categorically nails the process of creating a startup (I have used “startup” to refer an Internet business of any scale). However, there are pointers from founders who did it successfully and cautious lessons from those who failed. Be it marketing, sales, hiring, or making business decisions, every area pertaining to startups has been meticulously covered in books, podcasts, courses, and articles.

One would think that the vastly accessible material has helped the likelihood of startup success. Maybe it has but there is hardly any evidence to corroborate that claim. Most Internet ventures still fail; most before getting any significant traction. What do we make of that? Why following the footsteps of successful founders remains failure-prone?

Maybe because building a startup is not as straightforward. It’s an antithesis of Anna Karenina Principle which suggests that the reasons behind unhappy families are numerous, whereas happy families have predictable things working for them. Obversely, successful startups succeed in their own way, while failed ventures are almost alike. It would be a glaring oversimplification but we can reduce startup failures to two reasons —

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Last week, I created a small script to aid my workflow which left me wondering why I didn’t make it earlier. It adds an option in Finder’s context menu to start a static web server in any folder which makes it easier to preview static websites. Technically, it’s equivalent to firing up the terminal, cding to the directory, and using one of the many options to create a static server. The convenience of doing in one step which took three is minor, but automating the process is also advantageous in secondary ways. The crucial benefit is removing the tedious chunk—even if a small one—of my work. I can take pride in how my real work won’t include time to get a static server running.

Everyone’s daily work is filled with similar tedious chunks insomuch that it’s hard to distinguish the real work. Time spent in checking reports buried down a web of links; in collating data from several sources; in syncing files via email. In programming? In creating a build with five manual steps; in setting up workflow that requires several applications to be up and running. Time spent in these trivial tasks eats into the real work; worse, creates an impression that real work is getting done.

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Quantity over Quality. Jeff Atwood wrote about this contentious maxim back in 2008. The crux of the argument being, unrelenting creation always leads to improvement. Jeff backed it with an allegorical tale of a ceramic teacher from the book Art & Fear —

The ceramics teacher announced on opening day that he was dividing the class into two groups. All those on the left side of the studio, he said, would be graded solely on the quantity of work they produced, all those on the right solely on its quality. His procedure was simple: on the final day of class he would bring in his bathroom scales and weigh the work of the “quantity” group: fifty pound of pots rated an “A”, forty pounds a “B”, and so on. Those being graded on “quality”, however, needed to produce only one pot - albeit a perfect one - to get an “A”.

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There are things in science that are awfully hard to explain despite not entirely being hard. We are wired to reason in a certain way, which might be detrimental when it comes to understanding an intricate system.

Richard Feynman, the celebrated physicist, had an interesting anecdote regarding it. In one of the interviews, he narrates how his father asked where the photons come from when the electrons transit from higher quantum state to a lower one. “Photons don’t lie inside the electron, they are just released during state transition. It’s like speech; spoken words don’t come out of bag in the throat.”, he explained. Understandably, his father wasn’t satisfied with the analogy, but there wasn’t much Mr Feynman could have done better.

In the past few months, I got an answer to the basic question I had about money: where does it come from? If I got money from James, who got it from Tim, who got it from Ken, then, who sits at the top of the chain?

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There are a few ways programmers can score big money — high-value consulting, entrepreneurship, early-stage stock options coming to fruition in a liquidity event but the simplest of them all is a Big Fat Paycheck. In general, programming is a well-compensated skill, but when it comes to certain industries, or certain skills, or a combination of both, compensation gets an order of magnitude more than the decent salaries.

These outliers in compensation are more apparent in the United States where the fight to find and retain talent has protractedly been intense, especially, when it comes to technology giants and aggressive finance sector companies.

In most cases, engineers who get paid prodigiously happen to be more than an engineer. Their role entails leading other engineers and working alongside higher management but despite that, complex engineering is the essence of the work. That could be heading a team to build a massive cloud infrastructure, for instance.

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Code Gets Better Some codebases are crappy — actually, quite a lot of them are — but it’s distinguishably common to hear sharp criticism of code written even by decent engineering teams. Often this takes the form of complaining how the existing codebase is riddled with things-not-done-the-right-way. It’s typical when a small team of hackers grows to a bigger company and hires more programmers. From an idealistic viewpoint, it’s warranted one.

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