That programming as a career means you're going to spend writing nice, clean code 80% of the time.
It's rather debugging code or tooling problems 50% of the time, talking to other people (whether necessary or not) about 35% of the time and the rest may be spent on actually spending time doing the thing you actually enjoy.
I may be exaggerating, but only a little.
That a "working" prototype with no tests is just as good as a carefully-designed and well-tested feature. I see this happen so often that a coder puts a prototype in front of a product manager or exec and they are like, "this is exactly what we need, now! Ship that!" And then misery ensues for all of the engineers that need to maintain this piece of garbage. As managers pressure the engineers to build new features on top, they inevitably break fundamental parts of it, and without a confident leader to demand that tech debt is paid off, that product will consume the souls of many desperate coders.
In contrast, if you do it right the first time, there will be significant parts of code that never need to change, and the parts that do need to change will be much easier, because it will be obvious if it breaks the tests.
This one's a hot take, but: That Python is easy.
I've had to work with it in three projects in the past five years and I consider it one of the hardest programming languages, for anything but very short scripts.
You don't get proper compiler assistance, unless you have 100% test coverage. You don't get a helpful text editor. You don't usually get helpful type hints in libraries you use, so you have to genuinely just study the documentation and/or code. You get tons of quirky behavior in the stdlib, build tools, async stack, imports. You get breaking changes in minor versions of the language.
I find writing code in Python extremely mentally taxing, because you just get so little assistance, that you have to think of everything yourself.
I've got a lot of these.
Programming is not doing leetcode problems all day long. Those problems can be a good brain exercise or a good prep for a [misguided] technical interview but in a real programming job you have next to no chance of running into problems like those. Even if you do, you're an idiot if you spend hours toiling away at a problem that somebody else already solved much more efficiently than you will. Your boss doesn't give a crap if you pulled all of the code straight from your brain.
Programmers are not hackers. The reverse might be true but hacking is about finding problems (and exploiting them) while programming is about fixing problems.
A programmer can do anything that involves code. Maybe not quite this succinct but I think most will assume you can write a mobile app or a website just because you say you can code. Websites, games, apps, and so on are written in code but they all involve different technologies, toolsets, and standards. I'm sure I could fumble my way through any kind of software but don't expect it done quickly if it's not my area of expertise.
Requiring a candidate to know a specific programming language is stupid. Nearly all of the commonly used languages in industry are similar.
It's maybe more valuable to require knowledge in a specific framework, where knowledge is less transferrable between popular frameworks. Nonetheless, I personally rather hire an engineer that solves problems and learns flexibly rather than one that happens to know the right tech.
Technical Leads are not rational beings and lots of software is developed from an emotional stand point.
Engineering is trade offs, every technical decision you make has a pro/con.
What you should do is write out the core requirements/constraints.Then you weigh the choices to select the option that best meets it.
What actually happens is someone really likes X framework, Y programming language or Z methodology and so decides the solution and then looks for reasons to justify it.
Currently the obvious tell is if they pitch Rust. I am not saying Rust is bad, but you'll notice they will extoll the memory safety or performance and forget about the actual requirements of the project.
No programming language, development philosophy, or technology can save you from projects and business lacking clarity. Your ability to communicate and be understood is as/perhaps more important than the quality of your ideas. Consistency is better than perfection.
Some programmers are software engineers. They solve problems, sometimes problems with great ambiguity or non-straightforward solutions.
And some programmers are... code technicians? They understand and write code, but their job seldom involves problem solving. Often times, they're asked to code an already solved problem, or mostly solved.
This is not a diss. I was in the second camp for a while. But it hurts your career to stay in that. So be careful.
This one might be a bit controversial, but has rung true in my general experience. Probably a lot of exceptions to these rules, but here goes:
You don't really know a programming language until you understand a fair amount of the standard library and how packages/modules/dependencies work. Syntax is pretty easy, and any mainstream language will work just fine for solving basic leet-code style problems. But when you really spend a lot of time working with a language, you're going to spend more time learning about common libraries and how to manage dependencies. If you're working with a language like C++ or Java, this could also include build systems and how to use them.
Another precursor to being able to say that you know a language is that you should also be familiar with best practices (ie. how to name modules, how to write documentation, etc.) and common pitfalls (undefined behavior, etc.). This is one of the hardest parts about learning a new language in my opinion, because the language may not necessarily enforce these things, but doing them the wrong way can make your life very difficult.
The misconception that we’re the person to go to to fix your printer…
..I mean we probably can fix it, but it’s a waste of our time…
Myth: code can be ugly as long as it works, don't spend company time on making it look good or on minor optimizations.
The truth is that you can tell when effort has been put into a job. Even if it just works, the lack of discipline means that in the end it will be difficult to maintain and probably will fail in unexpected situations.
Every language has its conventions, but if I spot more than a line of separation between blocks of code, that is a common telltale sign of noob. Run from that shit.
That coding interviews are even by the tiniest measure good indicators of how capable a candidate is for a software engineering job.
I saw a great thread on Mastodon about this: link
When you release something, your work is not done. You have to maintain it, fix bugs, release patches, and probably the worst part, keeping it up to date.
For example, Apple decides to deprecate some API, or decides to switch cpu architecture, or for the millionth time change how app signing works, or add some new security feature that breaks your app. Now you need to make your app work properly on the new platform, switch APIs, all the fun. Or, there's some critical vulnerability in library you used and customers are deleting your app from their computers (a lot of companies use automated scanners that check against published CVEs). It's most fun when you learn that the new version that fixes the vulnerability completely breaks compatibility with the old one and now you have to rewrite all the code that used that library.
Also, maintaining open source projects is not fun. It's a lot of work, in most cases unpaid, thankless, and building a community around a project is really hard.
Myth: You are lazy.
Truth: It's highly probable you are neurodivergent.
While, accurate numbers are not available, I have seen people estimating that 20% of people working in FAANG are neurodivergent. If coding comes naturally to you but the laundry is your mortal enemy, it's worth learning about ADHD/ASD and other common disorders. Being a coder can be a sign, the immediate feedback helps a bunch of us, or as Russel Barkely says "when you solve a problem on a paper, NOTHING HAPPENS".
Edit: Rephrase.
That “just changing a word” is easy and quick. A codebase is an iceberg. Management only really typically understands the surface, but there is a disproportionate amount of ice under the water.
I had to change all instances of a label from a word to an abbreviation. Because we don’t have i18n set up in the app, it ended up affecting 55 different files. I did my best to consolidate into everything calling a common function, but it’s far from perfect. 55 files changed because management said “oh this word here should be shorter”.
It's not magic
It is cool
That Python is the most readable language. Merely forcing an indentation style is only part of the issue. Python programmers have a tendency to write a bunch of named parameters all on one line, and it's a mess.
Even the automated documentation can't make it right. What the hell is this shit?
class werkzeug.test.EnvironBuilder(path='/', base_url=None, query_string=None, method='GET', input_stream=None, content_type=None, content_length=None, errors_stream=None, multithread=False, multiprocess=False, run_once=False, headers=None, data=None, environ_base=None, environ_overrides=None, mimetype=None, json=None, auth=None)This is not enlightening. It might as well go on the shelf next to the worst regex you've ever seen. The automated doc generator needs to break these up to put one arg on each line, or just omit it altogether and let the detailed docs handle it.
It's not just the doc generator, either. I see this kind of style all the time in Python code. It's unreadable and it also makes it harder to figure out diffs when a parameter in the middle is changed (though it's helped by color coding for pull requests on GitHub and the like).
It's almost like the language attracted a bunch of people who thought indentation was the only thing you needed to make readable code. No further thought put into it.
There are no absolutes, and most of these “myths” are at least true to some extent. Much like any paradigm (worse is better, whitebox testing, lbyl vs eafp, etc), none are universally best. And all are helpful to know about.
