John Carmack: Career Advice

Granted in any sane company this should just be done by the devs themselves. But as the OP said, in most teams knowledge about versioning, branching and version control is very very limited. Even if all you know is how to do a rebase of a longer lived feature branch easily in git (skipping the commits from the other branch) you will be the wizard that everyone goes to. Many many devs will not even attempt a regular rebase. It's black magic for them.

If all you desire is a cozy job in a large company with braindead processes and policies this sort of thing is probably enough to be tipping the scales towards: well we shouldn't lay off that guy coz he's the only one that can work the version control magic AND he codes like mad.

If you wanna stick out in a company filled with John Carmacks you will have to do better, sure.

The level of understanding of git you need to stand out is very very limited in my experience. Most devs in "regular" companies struggle to understand even the basic rebase. Even on a logical, abstracted level. Never mind how and why it actually works as well as it does.

The types predicaments I see people get themselves into even with git vs say subversion is mind boggling. I have never gotten myself into a situation that wasn't resolvable by simply making sure that everything I try is done after committing my changes. You can just always go back and retry. And just slapping a label (branch in git speak, sure) on a commit before force pushing after that rebase with lots of conflicts so that I have a backup. And even that is not strictly necessary. I've fucked up conflict resolution only to notice when the build server tells me and I had to go find a commit hash in my terminal output somewhere to resurrect it (I guess I was lucky I didn't hit an auto cleanup of dangling commits in between ;))

It's clearly just an example, but whether it's a bad one or not is debatable. Git is used by most shops, and most people have challenges with it at one time or another. Further, it is IMO an excellent example of how choosing the right data structure for a problem can have a profound impact on the resulting application. You could do worse for broadening your knowledge of ComSci than by a deep study of Git.

It sounds from your post like you may do front-end work. I work primarily on distributed systems for machine learning, so I can't speak to front-end work, but in my experience understanding basic data structures and algorithms is quite useful in day-to-day work. It is great you have gotten to where you are without doing technical interviews. On the other hand, every job interview I have had has had multiple rounds of technical interviews.

And I should also make clear that I am not saying become a competitive programmer or a Leetcode expert. For example, there isn't much value in looking at dynamic programming style problems unless you are interviewing at a top company. But spending 30min to an hour a day on easy to medium level questions will definitely sharpen your reasoning about algorithms and data structures. And like I said, in my experience those are used very often in day to day work (at least on the backend side of things). Also, to clarify, I am not saying you should do this forever.

As an anecdotal example, I recently reviewed a PR that had a lot of complex if-else statements that was dramatically simplified through the use of a set. The updated code was easier to read as well as understand. When I pointed this out, the engineer agreed and understood what was going on. But their initial instinct was to use the one tool they knew: arrays and chains of if-else statements. This is the kind of skill I am getting at - knowing enough about your language, data structures, and algorithms to know when to use the tools in your toolbox.

I don't think it is unreasonable to expect a software engineer to understand the difference between tree-based and hash-based data structures, when you should use arrays, and pros/cons of linked lists, etc. Practicing this kind of stuff, which is very easy to do in Leetcode, is the fastest way to build this intuition (at least in my experience with distributed systems).

Edit: just wanted to add that understanding these things makes it extremely easy to reason about systems like Redis, memcached, Cassandra, Kafka, etc. If you understanding the basic, then you start having these moments of clairty thinking "oh this is just a big hash table!" etc.

Also, meant to add that thee repetition of Leetcode style questions is super valuable in learning the APIs of your language. Things like "how do I create a hash table? how do I populate it? How do I check if it contains a key?" This is all simple stuff but a lot of new grads aren't as familiar with the APIs. It's not a big deal, sure, but it is also an _incredibly_ easy way to stand out.