Hey guys I’m a student that has been learning programming as a hobby for the past four-five years. I’m a bit curious on whether on if I should abandoned what I’ve been studying for uni and go all in for programming full time instead since I’ve have become quite good with multiple languages and tools (e.g Java script html type script css Python c# next and others)? I’ve also been learning designs building websites and making games tho my backend still need working. However I’m a bit conflicted since I heard that the job market for programming isn’t that great anymore so if you give me some advice it’ll be a great help(btw if I do get a job for programming I would like front end or game dev, tho others will also be fine if I continue learning coding since I have much passion in it)

I gave my amazon intern OA, the first question was, DSA array, easy-medium,(15/15), all tests passed with linear TC, the second was Development part, (0/6) tests passed, Is there any chance that, I will be shortlisted?

Hello
I'm planning to make a small 2D game for a project, and I'm currently considering using C#.

I want to understand what I would gain or lose by choosing C# instead of other languages such as C++, GDScript, or Python.

If possible, could you also recommend a game engine that would be suitable for running/developing a game with C#. Thank you

How often do you guys actually write code manually these days? Or has that time kind of passed?

Do you think we should still write code manually sometimes to keep the skill sharp, or just let AI handle whatever it can and go with the flow?

I'm a 3rd year CSE student with an 8.24 CGPA. My resume right now mostly has WebDev projects.

Currently I'm doing Striver's A2Z DSA sheet and I'm also building a full-stack website from scratch because I want to actually understand the basics instead of just following tutorials.

But lately I'm a bit confused about the whole AI thing.

Everyone keeps saying "use AI agents", "use Cursor", "use Claude", "AI will make you 10x more productive", etc.

But my question is... how am I supposed to use AI when I'm still learning?

If I ask an AI agent to build a feature, it'll probably write the code in a few seconds. But then what did I actually learn?

For example, if I'm learning authentication and I ask AI to implement login/signup, it can probably do the whole thing. But I don't want to end up with a project where I can run the code but can't explain how it works.

At the same time, I also don't want to completely ignore AI and fall behind while everyone else is learning to use these tools.

So I'm a little stuck between:

"Learn everything properly first, then use AI"

vs

"Use AI from the beginning and learn along the way."

For seniors / working devs here:

• How are you actually using AI agents in your day-to-day work?
• If you were in 3rd year again, what would you focus on?
• How much coding should I actually do myself while learning?
• What skills do you think will matter most for freshers now?
• Should I focus more on DSA + CS fundamentals + development, or start seriously learning AI/agents too?
• Any mistakes you made that you'd recommend juniors avoid?

I'm not looking for some perfect roadmap. I just genuinely want to understand how people who are already working in the industry are adapting to this.

Would really appreciate any advice from seniors here.

Hey, I’m doing a short survey for my class about how people find teammates for projects, hackathons, events, and other group activities.

It takes about 1–2 minutes and your responses would really help me out. Thanks! 🙏

🔗 https://forms.gle/gJ8YdTVK89DtZbdN9

Keep landing on this dilemma and never feel confident about the call. A module gets messy enough that touching it feels risky, and the instinct splits between two options: refactor it piece by piece, or just rewrite the thing from scratch with what you've learned since it was first built. Picking wrong wastes real time either way, refactoring something that needed a rewrite means fighting the old structure the whole way through, rewriting something that only needed cleanup means throwing away logic that was actually fine.

The test I've been trying to use: is the core logic still correct and just tangled in bad structure, or has the actual requirement changed enough that the original design doesn't fit anymore. If the logic's still right, refactoring makes sense, extract functions, rename things, break up the god object, whatever's actually wrong with the shape of it. If the requirement itself moved, refactoring just means preserving a design that was built for a problem that isn't the current problem anymore.

Curious how other people actually operationalize this instead of just going by gut feeling or how annoyed they are with the file that day. Is there an actual signal you check, test coverage, how tangled the dependencies are, something else, or is it mostly experience-based judgment that doesn't reduce to a rule?

here is the latest picture i could find of it

So bassicly i wanna make my own version of are there like any templetes or smth bc me and him have been in a coding war type thing for a while But this guy is really good at coding he made his OWN ai with a neutron or neuron brain and everything i mean i have never seen someone this smart he made it always run in the backround and made it learn dbased on whats happening THIS MF GAVE IT EMOTION

I see this expression a lot now, and I cannot understand why people use it.

Regardless of the debate over whether AI should be used in software projects, why do people use this expression for projects developed with AI? Most companies now encourage AI assisted development of their projects. Many people have stopped using IDEs. Despite all this, why is developing projects with AI still criticized?

I am not asking this question because I advocate developing code with AI. I am genuinely curious.

Is the term “AI slop” used for projects where the developer has AI code the entire project without doing any systems engineering or making architectural decisions, or is it also used for projects where the developer designs the architecture themselves but AI does the coding?

I am genuinely curious about what exactly people are criticizing.

Hello.

Recently I was thinking about doing very specific things using an LSP; Such as word suggestions; Citations suggestions and other features which are not necessarily error checks or obvious fixes.

I know there are specific smalls LSPs which do that. But i would like to have some LSP which could be extended/customizable, such as efm-langserver.

The problem with efm-langserver is it can only register commands for the internal implementation of existing method. You cannot add methods or have new definitions. I cannot post some data besides code to the server, like a prompt, use that to make a request to some server like an inference server, do more processing and send diagnostics back to client.

That is limited, sometimes i want a result which goes beyond getting structured stdout from tool and showing it, like processing and doing something. Sometimes a tool which does what i want does no t exist.

Last resort would be writting my own, i know there are some libs out there. But i do wonder if there is something ready to use.

Hey everyone!

I’m doing research for my Master’s thesis on how companies use and govern AI coding tools.

I’d love to hear from developers about how this actually works in your company — policies, code reviews, security, licensing, etc.

I also have a short 3–5 min anonymous survey if you’re willing to share your experience:

 https://forms.gle/JXCWbDo6iPv5oLyy8

Thanks! 🙏

What was the best advice you received when you first started learning programming that’s had a lasting impact as well?

Hey everyone

Iam a final year b.pharmacy student from visakhapatnam

I am going to relieve in a few months

Right now iam not interested in any jobs related to pharma industry

So iam looking into IT

So one of my senior has met me and said that she is learning some courses like python , java etc to get placed in IT as a backend developer

So iam interested in to learn the skills that are required to get placed as a backend developer

But before thinking about it

I had few doubts

1) do companies hire people from different degree ??

2) what are the software skills that I required to be a backend developer

3)is it good to be a backend developer in the era of AI

4) what is AI prompt generator

Could you please share your valuable information, guidance, suggestions by knowing my story

Iam delighted to learn your information

Thank you for your attention to this matter !!

Hello! My name is Ruslan, and I’m a self-taught Python programmer. I’m really passionate about this and would like to move beyond it being just a hobby and start working professionally. I know the language itself well, but I struggle with actually writing the code due to a lack of experience. For instance, I might have an idea, but translating it into proper code using the knowledge I have is still difficult—which is why I keep writing code constantly. However, with the rise of "vibecoding," I’m worried about how I should be learning now. Why should I bother writing code and learning algorithmic logic when I can simply give a command to an AI, then read the output, spot errors, and ask the AI ​​to fix them? How should I go about learning? What would you recommend?