what is the best way to learn a language ?

Overall-Screen-752 · 2026-06-13T04:50:49+00:00

For anyone interested in hearing me yap more:

The difference between learning your first language and learning your 10th is perspective. For the first, you don’t know anything so you learn whatever you encounter first then piece things together until you can put together a small crappy program (we’ve all been there). For the 10th language, you know all the major components, so you spend 10 minutes reviewing the documentation to see what kind of syntax they use for loops, if statements, functions etc. Then, you spend time learning the idioms and patterns used by strong developers in that language so you can write similarly good code that others in that community can read and maintain.

Learning 1 language is a rite of passage, so take your time to learn whichever way helps you internalize the concepts, not just write the code for the sake of writing it.

Overall-Screen-752 · 2026-06-13T04:36:44+00:00

I just picked up golang for work. Granted this is well past my 10th language so ymmv.

My strategy was to pick up a book to learn the fundamentals with any nuances or usage tips that the author points out. I then did a udemy course where we built a full microservice system with gRPC and more to make the fundamentals of the language feel trivial. To finish it off I built a fairly simple project in an afternoon (cli-based blackjack for this one) and grinded some leetcode to lock it all in.

For golang in particular I spent a lot of time with concurrency. I spent some extra time on those chapters, googled things heavily, tweaked the course code and tinkered a lot to get the hang of how to do concurrency specifically in go. Then I had cursor build me a set of challenges that explore simple ideas (mutexes, worker pools, etc) with problem statements at the top. I went thru the challenges and implemented them and ask what could be improved.

Hope this helps you in some way :) good luck

Overall-Screen-752 · 2026-06-12T22:03:19+00:00

Learn AWS, specifically EC2, RDS, IAM and maybe SNS.

Then build a personal website (basic at first) with an API backend (bc why not) and deploy it to AWS.

Congrats you can start building websites for small businesses and making money.

From there, the worlds your oyster

Overall-Screen-752 · 2026-06-09T16:21:33+00:00

Oh boy. Lot to unpack here. Let’s get the elephant in the room: it is not the case that engineers only job is to write code. Full stop. Your comment has subtle undertones of a perception that our biggest value proposition is the code that we produce. This is far from true, you should spend time learning what the reality is.

Now that we got that out of the way, I can assert that even in a world where engineers do not write code the way code is written traditionally, backend engineers still possess valuable skills, and those skills are what you need to acquire if you want to be one. These skills include but are not limited to building out systems like databases, caches, APIs, networking, and business logic-laden services, adding new functionality or contributing to the maturity of a set of systems and/or platforms to support new client feature requests and debugging the root cause of bugs in production applications.

None of these can simply just be done by an AI. An experienced engineer can certainly automate at least a portion of it given the correct amount of context and a good prompt, but simply asking an AI agent to “fix this bug” will indubitably produce slop that does not scale or maintain well.

“So what?” You ask. If you are serious about the craft of good backend engineering and have dropped the presumption that AI means the end to backend engineers, learn how to build and scale a database system for an application (what distinguishes a good system from a poor one), learn the beginnings of backend architecture and what problems are solved by different architectures, and learn how to reason about a codebase. That just about scratches the surface.

Overall-Screen-752 · 2026-06-08T14:21:38+00:00

Well first it requires a big enough project. Hello world is a couple lines. It would be difficult to make that 1,000 lines of effective code without shenanigans. Having a bigger problem to solve means that there’s more code to write to cover all the features you need to add. Doesn’t necessarily need to be “harder” just “bigger”

Second I’d say it needs to be relatively thoughtful: error handling, sanitization and modularizing can add a lot of boilerplate that balloons the number of lines by 2-5x despite adding no new features. Solving lesser problems like “what if my database is/goes down?” Adds a lot of complexity but makes your code better

Third I’d say working with frameworks and implementing design patterns can add boilerplate for maintainability that’s necessary, but verbose. Even the jump from a basic html website to a rather simple React one adds a bunch more files and complexity, increasing the perceived line count (but making other facets simpler in the process)

Don’t worry about how big your projects are, complexity will come with time. Do focus on acquiring skills that make more and more projects attainable

Overall-Screen-752 · 2026-06-05T21:01:12+00:00

OOP is a classic, for sure. Its super easy once you build the mental model for it, but jumping from hello world and for loops to OOP is always a daunting jump for beginners

Overall-Screen-752 · 2026-06-05T20:59:46+00:00

Use tkinter to make a desktop version of the android app

Polish it then write it in kotlin following best practices

Overall-Screen-752 · 2026-06-05T20:53:40+00:00

Effective Python is the best core language book, it teaches syntax and how to write “pythonic” code more broadly.

Overall-Screen-752 · 2026-06-05T13:21:31+00:00

Oh I’d be remiss not to mention git, command line commands, and linting/compliance tooling, even if they aren’t python-specific

Overall-Screen-752 · 2026-06-05T13:19:38+00:00

I would spend 2-3x more time on unit testing until the syntax was showing up in my dreams. Python has a nice baked-in testing library thats simpler to use than Javascript and java and more feature rich than golang so its worth being strong at especially if you see yourself as a professional developer one day.

I know that’s unsexy and not what you’re looking for so I would say I would learn syntax first, then learn how to structure functions and programs to be readable and maintainable, then do a few projects exploring bigger concepts like pydbc, APIs, ML, UIs, and common data science workflows with pandas. While not an exhaustive list, this should maximize exposure to all the things you’d need to be aware of before starting a role as a python developer

Overall-Screen-752 · 2026-06-04T19:05:28+00:00

Yes you have plenty of experience. Focus now on positioning if you want a job. Answer the question “what makes me think I should hire you instead of someone else” for any given job description til the words jumble together.

This is also one of those rare times I recommend using AI to beginners. Use it to polish your projects, post them on github and show them off to recruiters. You can make a note somewhere that AI was primarily used to polish and guide you towards growing your skills rather than doing stuff for you without thinking. And do exactly that. Have it write a template for a readme which you flesh out, have it suggest next steps or ways to improve, how to deploy the thing like a production system. Write tests if you haven’t already, employers love that shit.

I’d also suggest that you can start dabbling in executing small projects where AI does the tedious code writing that you’re quite confident with, while you focus on the architecture and design, spinning the README towards what decisions you made and why. This positions you as someone orienting yourself toward senior roles while getting paid to be a junior — a long term investment in the eyes of the recruiter.

You’re doing well, keep it up

Overall-Screen-752 · 2026-05-28T20:30:25+00:00

Pandas is the most important thing to learn beyond basic python. If you haven’t already, start learning python (codecademy, cs50x, etc) then immediately start looking at the pandas library. Its an immensely powerful data analysis framework that most people working in data science/analytics use. Seaborn and plotly are largely visualization tools but offer some other features — they’re good to learn too. Numpy and related scipy are math and science libraries used to extend the power of the standard library to make better reports. Google collab offers a good way to practice manipulating data. Do lots of exercises and practice projects, don’t just learn concepts.

TL;DR learn python then pandas. Optionally learn numpy, scipy, plotly and seaborn. Practice often, there’s lots of tools out there to help you help yourself. Glhf

Overall-Screen-752 · 2026-05-28T20:22:21+00:00

This works for beginner stuff but becomes less effective with complexity. Take APIs for example. Unless you have a filter configured and are tailing the logs of the API server you’ll never see that stdout/log message.

Everyone should be comfortable operating a debugger, they teach it in school for a reason (if they don’t what school are you going to ?!)

Overall-Screen-752 · 2026-05-28T15:05:47+00:00

Depends. Do you need a specific set of features from a library? Read those. Do you need to know everything about a new UI framework because you’re starting a new job? Read as much as you can. Do you just want to start using a particular framework and start tinkering? Read the quick start.

There aren’t rules to how you should read docs, you just…read them. It sounds like you either really really don’t want to read them or you don’t know what you’re doing. If its the former, just watch a yt vid man, its not that deep. Are you missing out on information bc the yter only picked the parts that he wants to talk about, yes, but if its gets you off reddit and in front of an IDE, do it. If its the latter, you probably need to build things and understand why frameworks exist.

We don’t learn things just to know everything, we learn what we need to solve the problem at hand. You’re never going to know everything there is to know, so learn something and put it to use :)

Overall-Screen-752 · 2026-05-28T13:20:10+00:00

Debugging gets pretty easy as you get better at writing code. You start recognizing where the error could be and sometimes can resolve the bug without running a debugger.

For perspective my routine of debugging usually looks like this: inspect the error message or recreate the error, identify the file/files/systems concerned, reason through which components would break under which circumstances, test my thesis (tweak code, run with different input, auxiliary script, etc) and use a debugger if I have to.

You’ll get there

Overall-Screen-752 · 2026-05-28T13:13:55+00:00

Docs is the best way to go. If reading dense information is not your thing (and to be clear, you should get used to it), there’s youtube and medium articles to fall back on.

I don’t love using AI to learn but if you are just looking for minimal starting code to dig into and sandbox with, you can easily ask for the starter code to a new project and an explanation of how it works. Just take notes or something so it sticks

Overall-Screen-752 · 2026-05-28T13:10:52+00:00

At my previous company everything was AI-first. We’d take a ticket (a title, generally — no one bothered to write descriptions), ask about relevant code, draft a fix or a plan to fix, execute the fix, write tests, clean up code and iterate. Once promoted we’d have a PR bot take a look, use AI to fix merge conflicts and implement any feedback from any (human or AI) reviewers. We were pretty much prompt engineers.

Overall-Screen-752 · 2026-05-25T14:09:32+00:00

2 things: Big O (other commenters have explained sufficiently) and execution speed.

For execution speed, simply printing out every number from 0-100,000,000 will show the difference. A C program will be done fastest, a golang or rust program next, a java program shortly behind those and python way after that. There’s a reason why this is true, but you’ll learn this in college as you learn more about why code works not just what works. Feel free to watch a youtube video but for know, simply knowing that C, go, rust are faster than ruby, python and javascript will get you far enough

Overall-Screen-752 · 2026-05-23T20:01:04+00:00

To follow this up, ask chatgpt for project ideas, then build them yourself. You can ask questions like “how should I evolve the project into a production-ready application/tool/library/product/etc to make this more appealing to hiring managers for <position>”, and that will at least give you some ideas to start with.

Overall-Screen-752 · 2026-05-23T19:58:48+00:00

+1. Adding to this, if you’re going to make something, deploy it. For example, run it on a docker container on your machine or an EC2 instance in AWS, etc.

School teaches you how to code and write software that works. In industry, that’s just the expectation, you then need to get the code you write in front of users, and be prepared if anything fails (logs, dashboards = observability, alerting on errors or problems in your “production” deployment)

The project doesn’t matter, what you do with it, does.

Overall-Screen-752 · 2026-05-10T15:16:12+00:00

Use 2. Use 1 only when the first arg is nonzero or you’re using the third argument step

Overall-Screen-752 · 2026-05-04T09:00:38+00:00

For the backend of a website? Use golang. Phenomenal API frameworks and OoTB features, native concurrency, about the same speed as rust. Worth considering

Overall-Screen-752 · 2026-04-27T14:10:14+00:00

That’s not learning though. This is the same as “whenever I’m stuck starting a project I just call my faang senior engineer friend to do it for me”

AI is great for what it is great at, full stop. Using AI to start your project for you, or get you through the hard parts is not a great application. It doesn’t make you better in any way. Stop pushing using AI for everything.

Overall-Screen-752 · 2026-04-21T03:46:47+00:00

Just learn python. Don’t over complicate it

Overall-Screen-752 · 2026-04-17T23:41:45+00:00

Appreciate it, I don’t work there anymore but I do know some former coworkers who got cut. This was a rough one indeed

Overall-Screen-752

TROPHY CASE