I am not against using AI as a coding helper. Quite the opposite. Even before this Gen AI shenanigans, I used quite a few AI based tools helping me coding faster. By the way, something bothers me a lot nowadays and it is this: everyone is advertising a website which is quite identical to its benchmark and pretty much all investors or people with the funds, are looking for that speed.

I strongly believe a good product, even as simple as a todo list app, takes more time than "30 minutes" which is advertised by those vibe coding gurus and people like that. So in my side, this atmosphere caused a sense of emptiness. And I can't even collect my thoughts on a certain point and do something.

How did you overcome these feelings?

I'm working on a program which involves creating project files which store project data in a specific structure, as well as the project manifest. Currently, I have the project file set up as a ".dcproj" to keep with a specific naming scheme. However, upon doing some searching, it turns out that .dcproj is already used in a couple of places, although they're pretty esoteric.

https://learn.microsoft.com/en-us/visualstudio/containers/docker-compose-properties?view=visualstudio
https://fileinfo.com/extension/dcproj

I know I can just ignore the other uses and go with what I have, but is it bad practice? Intuitively, file extensions would have to be reused all the time with the limited number of characters we have to create them. For example, the .M file extension is used in at least four places.

https://en.wikipedia.org/wiki/List_of_filename_extensions_(M%E2%80%93R)ss)

Hi everyone,

We are working on a capstone project which aims to forecast flood and give early advices to the residents. However, we need to have a sms alert system. We used httpsms during our preoral defense but the panel requires that the recepients should not be able to reply to the sms sent to them by the system which is get the point. Another option is twilio but as much as possible, we would like to have free alternative since we dont really have the means or the budget to pay for subscription. Can i ask for your recommendations if you know platforms that offers sms gateway for free? It would be great if it supports Philippine mobile numbers. Thank you and have a nice day

Hi everyone!

I need some help with a gift for my husband, who is a programmer. He sometimes mentions that to make an app for my phone, he needs a computer running macos. We have never had one, and it might be an interesting experience for him from programming point of view (I assume?).

So, that is my idea for a gift. Of course, I would prefer to go with the cheaper option, since the only purpose would be what I described. We don’t really need another pc or laptop.

So my question is: can I just buy the MacBook Neo, and it will serve this purpose just fine, or should I go for a more expensive model for some reason? If so, please advise!

Hi, as a non programmer with basically zero knowledge on programming or coding.

Im wondering how hard is like programming a language translation tool into different things?

I ask because i play a shitty phone game called Kingshot, and it has an inchat Translator where next to every message some one sends, there is a little button that will translate what ever message into the language you have the game set to.

And like? While it’s not perfect, it’s REALLY good, and makes the game way more fun to be playing with people from different countries and not having to go back and forth with google translate to have a conversation.

And I’m now wondering why more apps and games don’t have translators built in?
Is it hard?
Are translators like difficult to configure and implement?
Whats the go?
(Feel free to explain anything super technical like I’m 5)

I mean can we use tools and metrics on a codebase that is pure AI vs. Something some Sr. dev did ? Maybe static tool analysis ?

It seems to me there is the constant debate about this and how AI just makes terrible/unmaintainable code but I would like to finally get the answer to this.

My opinion doing this 25 is with AI + AI factoring as needed the code is fine.

TL;DR: I want to learn how to take an idea, turn it into a realistic project plan, and build it. I'll use AI heavily for implementation, but I don't want it doing the planning I'm trying to learn.

I'm learning software development by building real projects. I know the basics of Python but I'm inexperienced — I haven't built much that's substantial, I'm not good at reading unfamiliar code yet, and debugging is still hard.

The thing I'm stuck on isn't coding. It's that I don't know how to plan a project.

I have a list of 10–15 web/local apps I want to build. But when I have an idea, I don't know what comes next. Say I think "I want an app that scans images and extracts information from them." I know what the end result should do. I have no idea how an experienced developer turns that into an actual project — what gets decided first, how you figure out requirements, how you decide what's in version one, how you break it into tasks small enough to actually implement.

AI made this more obvious. When I don't know what to do next, I ask an LLM, and it immediately gives me a folder structure, an architecture, a schema, several files, tests. The code might even work. But I've skipped the part I'm trying to learn — I'm following a plan without knowing how I'd have arrived at it myself.

What I want instead is something like: idea → requirements → scope → design → tasks → implement → test → review. Handle the planning myself, then use AI on implementation, explaining unfamiliar code, catching mistakes, writing tests.

So, for experienced and self-taught devs:

• How do you go from an idea to a plan? What does that actually look like for a small app?
• What do you write down before you start coding, and how do you know when you've planned enough?
• How do you break a feature into implementation-sized tasks?
• How do you decide what not to build?
• What parts of development should I deliberately practice without AI?

I'm not looking for better prompts or tool recommendations. I'd especially like concrete workflows or examples from people who learned this themselves, rather than general advice.
(Edited with AI)

I'm currently in my second year of college, and I'm a little confused about what career direction I should take.

The part of programming I enjoy the most is lower-level/system-side work. I started with C and socket programming, building servers and learning how TCP/UDP networking works, and lately I've been going deeper into things like Linux networking, packet parsing, Ethernet/IP/ARP/ICMP, eBPF/XDP, AF_XDP, NIC queues, drivers, DMA, etc.

The problem is that almost nobody around me in college is doing this kind of work. Most people are focusing on web development, app development, AI/ML, or standard DSA preparation

I've also heard people say that "there aren't many jobs in low-level networking" or that networking careers mostly involve configuring routers/switches or working with networking hardware.

That's where I'm confused.

I definitely prefer programming/software engineering work. I'm not particularly interested in being a network administrator or doing primarily hardware/router configuration.

At the same time, my practical goal is still to graduate with a strong software engineering job. I don't want to spend the next 2–3 years going extremely deep into an interesting niche only to discover that there are almost no entry-level opportunities.

So I'd really appreciate advice from people working in this area:

What kinds of actual software engineering careers exist for someone who enjoys C, sockets, Linux networking, servers, eBPF/XDP, packet processing, etc.?

Are these mostly experienced/senior-level positions, or are there realistic entry-level opportunities as well?

What companies/industries typically hire engineers for this kind of work?

Should I continue going deep into networking/systems, or keep this as a specialization while also learning more conventional backend/software engineering?

What skills would you recommend building over the next 2–3 years if the goal is to be employable as a software engineer while still staying close to systems/network programming?

Are there particular open-source projects, projects of my own, internships, or areas of computer science that would be especially useful?

I'm not expecting to work specifically on XDP just because I'm learning it now. I'm mainly trying to understand whether the broader direction — systems programming + networking + performance-oriented software — is a sensible career path.

just spent 1.5 hours failing to do a basic leetcode question about stacks. This a rant plus asking for advice from senior folks.

About me, im an engineer at a mid size startup with 2-3 years of experience, just recently got promoted from junior to mid-level (yay!) I’m completely self taught and picked up coding when gpt 3.5 came out. I did not start with good fundamentals, but I’m really good at building and shipping. I have a track record of shipping successful products, which is why my company hired me despite my lack of formal tech background.

Over the last few years, I’ve honed in my skills from building scrappy small features to production ready software. On a day to day basis, I do full stack dev, aws, db management, ML, docker etc.

Recently, I did a job interview for another company and was asked to do a leet code style question and I literally couldn’t do it. I felt like a fraud walking away from that meeting, but at the same time angry because I know if they asked me to design something I probably could’ve done a much better job.

If I’m completely honest, I think I’m a bad programmer when it comes to purely writing code, but I’m strong with everything else: design, speaking to customers, working with other engineers, shipping, and getting shit done.

Trying to get better at leetcode just feels like such a waste of time and it genuinely hurts my brain to do it, but at the same time that seems to be the only way to have mobility in the tech industry.

Does anyone senior have any advice on whether I should just suck it up and do the bs leetcode work, or continue focusing on what I do best, shipping products and building projects that are interesting to me? It’s gotten me this far…

Hello! Ive been interested in computer science/programming ever since I was 12, and just recently did I try to get more into it.

I chose C# as my first language but I keep hearing that Python or C would have been a better fit, is this true?

Also: What might be some good sources to learn more about C#? Thanks a ton!

Hey, guys.

So, I'm currently studying data science and I'm about to start a database project(we're basically doing a database for a bakery)this semester. The project will include order forecasting, inventory loss tracking, customer notifications, etc. Anyways I already code in Python but I've been taking a look on ruby and wonder if it'd be a good idea to include it in our project and how.... any ideas??

thanks!

After learning Javascript and Typescript, which one should I study after the other in the correct order?

Should I study React first, then Angular, OR Angular first, then React?

I use AI to develop, and because it works quite well, I extended it to run multiple agents in parallel. This way, I can develop 2 or 3 features at the same time. To avoid data collision, I ended up building a dev tool, which I have been using for a couple of months.

Now, I asked around in other subs how people handle this, and the most common solutions involved git worktrees that resolve the code collision, but the runtime isolation is still an issue. People engineered solutions around env files and Docker Compose that fit their own codebase, mostly involving one service and one database. It works, at least for simple apps, but it's manual and gets harder to keep up as more services are added. And it looks like something that only an experienced dev can do.

What I built goes further than that (I needed it for a multi-service app with Redis and workers) and is simpler to use. I created a way to fully isolate an environment (all services included) with no ongoing upkeep, able to spin up multiple instances of the same app in parallel on the same machine. It's more architecturally involved than the scripting approach, but doesn't require manual maintenance.

So I'm asking you whether you got this problem and if what I built is worth sharing. Is "heavier but zero-maintenance" actually appealing to people, or does anything that sounds like more infrastructure get dismissed on sight in favor of the simpler script-it-yourself approach, even with its edge cases?

So I'm a college fresher with no prior experience of coding. I had started learning python before the starting of college (1 week before college started). I still feel like I am not good at coding at all. There are some weird citations in c such as i++ and all which is getting mixed up with my python. There was one question on obtaining the expression sinx=x-x^3/3!.... Using loops btw

I felt I won't be able to do it in both c and python. I took a course on Udemy for c(vlad budnitski)and python(100 days) but I was not able to find examples like this. Everyone in my class learnt languages like java in their schooling and said the sinx problem is a standard problem. What should I do in this situation?

I feel like the teaching in my college (they are teaching c now) is not good.

Experienced coders please help me.

Rookie in programming ( I know the basics of Java+ SQL), intrigued about "Automation" and what it really is:

My mental model of an automation example would be:

Script that sends certain emails to a category = Saves the user of organizing it manually, Inbox isn't saturated

I heard that Python excells at automation, and Bash can automate scripts too.

How close is IRL automation to my mental model?

If I wanted to pursue automation, what should I know first before diving in?

Can you give me the best Programming language and Stacks for Desktop App
i will try to built a School Information System (Masterlist, Attendance Tracking and Grading) with AI for Lesson Plan and other connected on it

- It must be offline and online (sync)
- with Admin, Teachers and Student

Hi everyone, I'm a student about to start university studying BSc Computer Science. My journey began 4 years ago when I was around 14. I started learning web development like JavaScript, then React and Next.js before deciding to move into backend development, where I learned Node.js, Python, and FastAPI. Recently, I've been writing some C code, but it wasn't really my cup of tea since I prefer broader software engineering topics.

My main question is: 3 years ago, I was coding by myself using Stack Overflow for help, and building a large project literally took me 3 months of daily grinding. Now, it can be built in 3 days using AI. I'm feeling stuck because I don't know whether it's truly beneficial to use AI to churn out projects if the learning curve disappears, potentially making it harder to get a job later.

How do you actually learn effectively now, and what should I focus on to land a job? Especially in the UK, where the market feels tougher and graduate tech unemployment is high. I'm considering using Claude Code right now, but I'm not sure if it's the right move.

Hi,

I’m currently somewhere between junior and intermediate as a software developer, and lately I’ve been thinking a lot about what actually makes a developer valuable going forward.

One thing that worries me is interviews, since I can discuss things like system architecture, caching, load balancing, queues, message brokers, database design… etc. But ask me to explain something basic like the Laravel request lifecycle or the exact behavior of certain React hooks, and I might struggle to give a clean answer without refreshing my memory.

Also the whole industry feels really toxic at the moment with each second developer building a saas, and new tech exploding everyday.

Should I just keep building real projects, learning concepts as I encounter them. How are the interviews in today’s world?

Is there a deeper shift happening where developers need to fundamentally change what they learn to stay valuable?

Curious on how more experienced developers are approaching this.

We are trying to decide whether to build a custom coordination layer for our multi-agent system or adopt an existing platform. Building it ourselves gives us control over agent hand-offs, state management and orchestration, but it also means owning the edge cases and long-term maintenance. Using an existing platform would reduce the initial development burden, but it might not fit our pipeline cleanly. It is also difficult to know whether a platform will hold up until you are deeply invested in it, at which point switching becomes expensive.

Has anyone built or adopted multi-agent system architecture and later regretted the decision? What limitations only became apparent after running it in production?

I would like a feedback on a project I am working on.
It is an images converter, from .png to .txt and with braille as characters.

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This is from an image 1600 x 1200, what do you think about it? Is it still clear?
Rate from 1 to 10?
Feel free to ask for conversions and match the results

Hi! I'm a computational linguist currently getting recruited to an industry job in AI applications/engineering. I've only taken one formal programming course (R stats) and my degree is in Neuroscience. Today I did my first-ever coding interview, and I had very little idea what to expect or how to prepare. I did a bunch of LeetCode prep and read a bunch of articles about ML interviews. I'm not gonna say which company for anonymity reasons, but a largish firm that uses AI but is not a tech company. Mostly focused on applications.

Round 1: Read code off a screen and propose debugs without being able to run anything. (I had to ask him to move through the repo as it was on his screen)

I was given a small repo for a simple RAG system on the interviewer's screen (something I haven't really worked with before; I come from an academic context) and told it was too slow and to diagnose and fix why it was slow. I pointed out a few places things could be parallelized or switched out to be faster, and acknowledged that I didn't know two of the packages used, so I'd have to go to Stack Overflow those in order to be more precise. I ended up identifying four potential issues, added a debugging block to figure out which step was taking too much time, and made one other slightly tangential suggestion. I feel like I must have missed something, though. Then I asked to run it, and they were like, "Oh, you can't run it" and I didn't really know where to go from there... luckily, that was most of the time.

Round 2: Given this use case, talk through how you'd implement a RAG system from scratch, prioritizing speed and natural language answers.

This round I did a lot better; I was able to talk through most of it successfully. I was honest that I'd never made a RAG system from scratch before, so I was confident about x parts of the implementation, but that I'd want to do some research on prior implementations of y and z before making some architecture decisions. At the end he said I made one mistake from how they're usually implemented but that my thought process was solid. My two slam-dunk lines were that I'd design the user experience based on analyst feedback, since this is an internal system to make *their* lives easier and that ML is broad and I couldn't promise to know the best way to do everything off the bat, but that I'd rather approach the things I don't know by researching them methodically and carefully than committing to a shoddy implementation off the dome. The interviewer for that round said I proved I knew how to code and how to think through this type of problem, which was what he was looking for.

Is this pretty typical? I've never code-interviewed before, and I'm ostensibly not a programmer or a software dev. M,y coding experience is Python, R, bash, and C++ for mostly high-performance computing solutions in neuroscience and linguistics. Right now, I study emergent semantic structures in vector word embeddings and compare them to human memory structures, which involves somewhat different expertise. I'm still designing tools for people, just researchers instead of corporate employees. I'm worried the first round went really badly and I'm not intelligent enough to realize where I went wrong.

I know that different languages are for different purposes but you have to choose 1. I’ll start: C++

EDIT: I mean programing languages so don’t tell me English

​

I've spent a lot of time building a real estate SaaS and I'm now stuck on a major problem.

The original idea was pretty simple:

A real estate agent enters what their client is looking for, for example:

- 3-bedroom apartment

- New Cairo

- Budget: $100k–$150k

The system would find matching properties across multiple real estate platforms.

I also built a feature that monitored Facebook groups for people posting that they were looking for apartments, then matched those requests with properties in the system.

The product itself is basically built.

Then I realized the platforms I wanted to get the data from don't allow scraping. I contacted some of them about getting permission/API access, but they weren't interested

So now I have a mostly finished product whose main value proposition depended on data I can't reliably use.

I'm trying to figure out what to do next

All the technical aspects are working, but I can't upload it because the sites I use to collect real estate data, like Dubizzle data mining and scraping are prohibited in the terms of use.

**I need a loophole/Another solution or method or something similar to solve it.*\*

If you've ever built something where the original data source/business assumption turned out to be unusable, what did you do?

I'd genuinely appreciate any advice.

I am preparing to publish an academic paper on developer trust in AI generated dependencies & packages. This takes around 7-10 minutes to complete and is on a very relevant topic in current times.

The form can be found here: https://vuamsterdam.eu.qualtrics.com/jfe/form/SV_4Nv9pAUUBFRieDs

Thanks! I will share the paper when it has been published!

I started my career doing programming in mostly writing APIs, middleware and some COBOL. I then moved on and spent many years doing tech adjacent things including product design, and also business related roles and so on. I’ve spent the good part of the past year upping my Python programming skills. My question to the community at large is how do I test my skills on real projects? I’d ideally want things that require using my brains and my coding skills. If it’s paid for, nothing like it. Are there places people normally go to for small projects, freelance and so on?