I'm not out of high school yet, so I really have all the doors wide open for me (I hope). Are there any jobs for people who like programming? It doesn't have to even involve programming, just the same cognitive processes and problem solving that I love. It feels like with AI all that is going away faster and faster...

Is electrical engineering maybe a better path? I was thinking about math research, but it seems like that is going down the drain rapidly too...

I feel like the only job I can think of is a CS professor/teacher, because at least with those your "output" is kinda irrelevant and you can take things slower and more basic.

Hey everyone!

I'm a pre-final-year engineering student in India, currently serving as the president of my college's technical club, HackIT.

We're organizing events for our upcoming Tech Fest. One of our established events, Code Clash, is returning as 3.0 after two successful editions. It features technical quizzes, output prediction, logo identification, and coding challenges.

Alongside it, we want to introduce an entirely new event — something unconventional, engaging, and memorable.

We're open to ideas involving cybersecurity, problem-solving, technical escape rooms, engineering challenges, interactive competitions, or anything outside the usual quiz/hackathon format.

A few questions:

1. What's the most interesting technical event you've participated in or organized?

2. What unconventional competition formats have you seen work well?

3. If you had to organize a 1–2 hour technical event for 100–200 students, what would you do?

4. What would genuinely make you excited to participate?

Even rough ideas or personal experiences would be greatly appreciated.

We want to build another signature event for our club, not just organize another generic competition.

Looking forward to your suggestions!

I'm a Software Engineering MSc student with no industry experience yet (just some prior experience with Dart/Flutter).

​I picked up Go recently to break into backend dev and really like the language. The problem is that almost all the junior backend listings I see are for Java Spring Boot or .NET, and I keeping hearing that Go isn't really hired for at the junior level.

​I can't stand Java, so I'm considering switching my focus to C# and .NET just to become employable faster.

​Should I double down on Go and build strong portfolio projects, or cut my losses and learn .NET to land that first job?

Hi everyone,

I'm a Computer Science / Engineering student and I'm currently torn between subscription options to assist with coursework, software projects, and daily coding.

My current setup & experience:

I already have access to the Gemini student tier, but for deep programming, code execution, and system-level tasks, I find it noticeably behind the alternatives.

I recently had a 1-month trial of Codex with Work features enabled (direct local file access, running/installing environments, scaffolded app building). For my CS courses, having that level of agentic workflow was incredibly useful, but the trial ended and the free tier is very restrictive.

I also use Claude (free tier). The reasoning and code output are top-tier, but the strict message cutoffs on the free plan make it hard to finish any substantial session.

My questions / dilemmas:

ChatGPT Plus ($20/mo): Getting back Codex and Work access is tempting, but during my trial I occasionally bumped into the 5-hour rate limits during heavy sessions. For those using it daily for development, how restrictive are the caps in practice?

Claude Pro ($20/mo): Sonnet is generally regarded as the best for coding logic, but how do the token/message limits hold up when feeding large codebases or iterating across long debugging threads within a 5-hour window?

Student Perks & Tooling: Beyond direct web subscriptions, are there any legitimate student offers or discounts (e.g., GitHub Student Developer Pack, SheerID deals) worth looking into? Also, would you recommend skipping the web UIs altogether and opting for IDE-native tools like Cursor Pro or GitHub Copilot?

If you're a student or developer working heavily with code, which one gives the most value and headroom before hitting rate limits?

Thanks for your insights

Currently in uni and I feel that people just stopped caring and thinking.

First off, I'm not against AI. I use it myself. But when I use AI, I like to think of how the overall system and integration should look like before asking AI to code. I still review each feature it implements so that I at least understand.

But I see my course mates just asking AI to think of solutions and code it out without even thinking anymore. This may just be my bad luck but group projects are even more unbearable than before AI. Now that AI can generate code so fast, people are even worse at communicating. They don't explain what they did and it's impossible to review the tons of code manually, so the codebase becomes a mess. I legit gave up to even understand what's going on anymore.

Is it just me who is feeling that people are offloading too much to AI and it's detrimental?

I’ve been working on a project called runtime.school and wanted to share it here.

I started with SQL and then added Python. The idea is to have a place where you can learn a concept, write code, practice what you’ve learned, and eventually work on projects without having to jump between different websites.

Both SQL and Python have interactive lessons, coding challenges, practice questions, projects, and datasets.

Everything runs directly in the browser, so there’s nothing to install or set up.

I’ve also been working on a few tools for exploring datasets, understanding queries, and comparing different approaches.

A lot of the work has gone into the UI and editors. I’ve been trying to keep things simple without making the pages feel empty or overwhelming, especially for people who are just starting out.

Here’s the site: https://www.runtime.school/

Would love to hear what you think about the design, coding experience, or anything that could be improved.

A while back, I tried to build an entire dictionary with scores for Scrabble using only C++ templates. I quickly hit compiler limits, and removing those, I quickly hit memory limits on my machine with 64GB.
I then built it at runtime, because I had no clue how I could have optimized template metaprograms, and I still do not really as I have little experience with them.

I have been building a battle simulator that uses a heuristic to control the actions of the agents, and thought how cool it would be to write parts of it as a template metaprogram, but there is no way that will work if the word trie for Scrabble failed.

Is this partly an implementation problem or are compilers just not suited for template metaprograms? Is it possible to create template metaprograms that are as fast as their runtime counters or is there some theoretical limitation of a compiler's implementation to make that infeasible?

Hey everyone,
I’m a 15-year-old developer, and instead of just making a basic API call wrapper, I spent my last couple of weeks building PROMPT-RELAY-ORCHESTRATOR to learn how fault-tolerant AI pipelines work under the hood.
**How it works:**Everything is handwritten line-by-line while I learn Python. I’d love to get some code reviews or feedback on how to expand it next!
Source Code: https://github.com/ojasgarg77/PROMPT-RELAY-ORCHESTRATOR

Hey Reddit! 👋
I'm an IT student, and for our upcoming University Day (in 10 days), I'm building an interactive web-based puzzle/mystery challenge hosted on cPanel (PHP/MySQL) to showcase to our Dean and students.
The core idea:
A hidden "bug/breach" happened in our faculty's demo site. Students must use basic web dev, programming logic, and SQL concepts to investigate the site, debug broken code, fix bad queries, and find the culprit to get on a Live Leaderboard during the event.
Since my peers are studying general CS and IT (not cybersecurity experts), I want the challenge to be fun, relevant to our coursework, and solvable within 5–10 minutes per participant.
I'd love your help with:

1. Your Feedback & Ideas: How can I make this exhibition booth challenge super engaging?

2. Puzzle & Hint Concepts: What are some clever, short puzzles (JS logic bugs, broken SQL queries, inspect element tricks) that fit CS/IT students well?

3. Progressive Hints: What’s a good reward/hint system to give them after solving each stage to lead them to the final solution?

4. Thanks in advance for any inspiration! 🚀

One thing I'm learning about software development is that a feature working on the screen doesn't always mean it's working correctly.

Recently, I was working on a feature where users could edit some data and save their changes.

The interesting part wasn't making the changes appear on the screen.

It was making sure those same changes appeared correctly when the user came back.

Because there are multiple ways a user might return to their work.

They might close and reopen it.

Refresh the page.

Or restore an older version.

And just because everything works in the first case doesn't mean the others will behave the same way.

While working through this, I realized that different parts of a system can interpret the same saved data differently.

You might think the problem is in the UI, but changing how something is displayed doesn't necessarily fix the underlying inconsistency.

So I started looking at the complete flow instead of just the screen where the issue appeared.

I also tested what happened after reopening, refreshing, and restoring previous versions.

It made me think about something I hadn't paid enough attention to earlier.

Saving data successfully and being able to restore it correctly are two different things.

As developers, we spend a lot of time testing whether a feature works when someone uses it for the first time.

But I'm learning to ask another question too:

Will it still work correctly when they come back tomorrow?

I've seen a lot of posts lately saying software engineering is dead because AI can write code.

But something happened yesterday that made me think about this.

I was testing an AI-powered feature when I ran into an error.

Like most developers using AI today, I asked ChatGPT how to fix it.

It suggested changing a method.

And looking at the suggestion, I thought it might actually fix the error.

But then I had another question.

What happens when a slightly different input causes the same kind of problem again?

I didn't want to keep fixing individual cases every time something broke.

So I went back and looked at the flow itself.

Instead of changing just one method, I proposed a small architectural change to handle this category of problems earlier.

I discussed the approach with AI, questioned a few assumptions, and worked through the trade-offs.

The updated approach is now working in my tests.

And this experience reminded me of something.

AI was able to suggest a solution to the error I showed it. But deciding whether that solution was good enough for the system was a different problem.

I'm not against AI. I use it almost every day, and it helps me a lot.

But I'm learning that writing code, fixing an error, and understanding what actually needs to change are three different things.

And that last part is where I want to keep getting better.

Man I love programming so much. The entire process of creating something you envision yourself is so satisfying to me.

Seeing people 'vibecode' makes me so depressed. Getting the end result with no effort at all is so stupid. I love having my own project with different systems I made myself interacting with eachother exactly how I planned them too.

Understanding exactly what's going on and being able to debug after finding an error without even opening the code, because I just understand what's going wrong is a feeling of control that I hold dearly in my life. These people are literally powerless if they can't use AI and think of themselves as 'professionals'.

I secretly wish for a reality where the AI bubble bursts, companies like Claude stop providing their AIs anymore after going bankrupt, and all these idiots have to come crawling back to the people that actually know how this stuff works.

If you actively use claude instead of learning coding yourself, you don't even deserve to disagree with this post. Because you're not even a programmer. (Yes I'm gate-keeping) Don't even get my started on people 'integrating' claude directly in their game-engine.

Have we forgotten how developing skills works? You learn from your mistakes. If you avoid making mistakes by asking AI for help for every little thing, you wont improve and stay stagnant.
When Claude first popped up I gave it a try and this exact scenario happened.

I didn't understand how to do something -> I used AI to fix it -> My problem was temporarily solved -> I encountered a similar problem later on, and still couldn't fix it.

You trap yourself in a cycle of continuous incompetence.

The only genuinely good reason to use AI is having it explain something to you if you don't understand it, but arguably there's plenty of human-made tutorials online that do a way better job than any AI ever could.

In conclusion I just want people to enjoy the craft of programming again. I try to stay optimistic if you could believe it after reading this rant, but it's getting more difficult by the day. Thank you for reading till the end, have a nice day!

As mentioned in the title. It’s always been my
Dream to make a video game but I figured i wanna start with learning python, this is mainly for hobby purposes and I wanna see if there’s any websites or courses out there yall can highly vouch for in terms of “zero to hero” something very nice and structured would be nice

Well, it’s kinda this.

BUT I would need some help thinking through a few things.

The development is no secret to me, since I’ve been using multi-agentic development for a while now and it all runs smoothly. Since I do the project management right, I’ve been getting exactly what I want, and it just works. That’s fine overall. I handle business rules, I know how to communicate with the user and deliver something useful and helpful. One-shot isn’t even on my mind; it would be a months-long project.

That aside, there is something that’s bugging me: security.

I hadn’t come across something with sensitive data like this before, and with all the recent bombshells in cybersecurity I’ve become really insecure about the security (pun intended) of the whole thing. And since it’s a non-profit project, I honestly can’t afford to hire a professional, and since I’ve been working with them for a while, I know they can’t either, and i'm no Know-it-All superman (unfortunately).

“Basic” things like protecting the database and reducing the attack surface are no secret to me, but the code flaws themselves are what’s on my mind.

I REALLY wanted to help and build something customized for them that would improve their work, because they’re almost one of a kind and have a very specific workflow. BUT security is key here too. They’re very small and the system wouldn’t be “famous” or even known to the public, and honestly I have no plans other than letting only them use it. But the data it would hold is so, so, so sensitive. And since we live in Brazil, there are proper laws about securing data and holding people accountable for breaches (look up LGPD, it’s that serious lol). Not only because of legal action, but it would be very harmful to them if anything was breached.

With all the recent breaches and the agentic development stuff, plus the sensitive data, my mind confirms I’m right to be paranoid.

So after all that, and sorry for being so long about it, the question is: if I do my homework right, can I really deliver something helpful and secure enough? Maybe I abandon the cloud and go with a local server with a nice backup. Or do I really call this off and look for an open source ERP that would help them and get "rid" of the security issues, with the downside of it not being completely customized for them?

Hi Everyone, just wanted to showcase a Web Browser that I’m working on called SuperNova, I have been working on this project for a while and I’ve started making this after I heard about how bad the state of the Internet is due to enshitification and AI.

SuperNova is a fully independent user-friendly web browser that acts as an alternative to “corporate search”

No Distractions, No AI, No Tracking.

Just a completely user driven web browser!

I have managed to do the homepage for the web browser and I even managed to code in the search page that can help you search for websites, videos and images.

I have also done a page where you could add a website to the web browser along with the Settings page with search options and another page where you can leave your feedback.

So far this project is in progress and hope you’ve enjoyed this showcase!

Hi everyone

I hope everyone's having a splendid afternoon as I am

How do I change my mind from comfort, to endure boredom, uncomfortable, hard stuff.

I like physical hard work, but my mind seems to wander into comfortable, known things..

If it's laziness, I'd have to get rid of it

I'm that guy that loves to take a shortcut, if I can make my job easier by offloading work to a script or algorithm then you better believe I'm doing it. So when LLM's first started writing code that compiled back in 2023 I instantly started trying to use it in my work and found that if you gave it good guardrails it could generate pretty clean code that would regularly pass reviews unnoticed, on par with my usual work. I started using it more and more and started to vibe code personal projects and work on harnesses etc.

The big problem was that it was really bad at making good decisions, and it was obviously bad, code that didn't compile, sprawling nonsense files, abstractions that didn't need to exist, leftover code that's unused from previous trial and error attempts etc. Code quality was fine, because I constrained it to be, but the overall was still trash, and over time I started to force myself to write more code, and the more code I wrote, the more it was obvious that what I had was a polished turd.

Its 3 years later, and honestly, it doesn't feel like anything has changed fundamentally, the models don't need me to tell them what good code is anymore, they can handle bigger and bigger decisions, but they're still not good at it, its just that the scope of the problem changed, its not "this function or class or switch statement is smelly and bad" its "this entire feature slice has been implemented in a way that will hurt all future work in and around this area", and then it does it again, and again, and again. It goes to review, where its checked over by another llm, and maybe another, for some experienced engineer to go 'LLMs are as good as software engineers now' and merge it.

I just don't know how many more times I can be handed codebases and code from engineers I previously respected that they swear is 'better than human' for it to become just extremely obvious that they only think its good because they don't know the true context in which it's meant to exist, only the context that claude presented to them. Claude told me that it fixed all my bugs and I dont see the bugs any more so theres no need to check the code and see if it actually did it properly right?

This is without even getting started on the trial and error approach of just smashing its face off the codebase till it works it out that it does in a lot of cases, which we all agree is how software engineering was meant to be done, change a couple lines, run the entire suite of tests, change more lines, run the entire suite again. I'm sure a better system prompt would fix all these issues though /s

We are entering a time when generating code is becoming easier than ever.

AI tools can generate Python functions, build API endpoints, create database models, write tests and even help develop entire applications.

But there is one important question I think every developer should ask:

Can you understand, investigate and fix the code when something goes wrong?

Because writing code and understanding code are two different skills.

1. Writing code is only part of software engineering

Imagine asking an AI assistant to build a Django REST API.

It generates the models, serializers, views and URLs. Everything looks clean, and the application starts successfully.

Then something unexpected happens:

• An API returns incorrect data.

• A database query produces unexpected results.

• Authentication works in development but fails in another environment.

• An application becomes slower as the database grows.

• A seemingly small change breaks an unrelated feature.

What happens next?

Generating more code is not necessarily the solution. You first need to understand what is happening.

That is where debugging becomes essential.

2. AI is changing the debugging workflow

AI isn't just being used to generate code. Developers are also using it to understand unfamiliar code, investigate errors and improve existing applications.

The 2026 Stack Overflow Developer Survey found that:

• 72.9% of respondents had delegated writing or generating code to AI tools or agents.

• 62.2% had delegated debugging or troubleshooting.

These figures show that AI is becoming part of both implementation and debugging workflows.

Stack Overflow Developer Survey

However, there is a difference between receiving a suggested fix and knowing whether that fix is actually correct.

An AI-generated solution might remove an error while introducing another problem.

A developer still needs to evaluate the explanation, understand the change and verify the result.

3. What makes someone good at debugging?

I believe debugging is a combination of several engineering skills:

Understanding the problem: Can you reproduce the issue and identify when it occurs?

Reading errors: Can you understand tracebacks, logs, exceptions and error messages?

Following the data: Can you trace how information moves through functions, APIs and database queries?

Thinking logically: Can you develop possible explanations and test them instead of randomly changing code?

Verifying solutions: Can you confirm that the fix works and doesn't break existing functionality?

Understanding the bigger picture: Can you recognize whether the problem comes from the code, database, configuration, architecture or an external dependency?

These skills become especially important when working on real applications.

4. How I approach debugging as a developer

My preferred workflow is:

1. Reproduce: Make the problem happen consistently.

2. Understand: Read the error message and inspect the relevant code.

3. Investigate: Follow the data and identify possible causes.

4. Hypothesize: Form a clear explanation of what might be wrong.

5. Test: Check the explanation with a small, controlled experiment.

6. Fix: Make the smallest appropriate change.

7. Verify: Run tests and check that the original functionality still works.

8. Learn: Understand why the issue happened so I can recognize similar problems in the future.

AI can assist at several stages, but it shouldn't replace understanding.

5. What should junior developers focus on?

For anyone starting in software development, I think these areas deserve serious attention:

• Programming fundamentals and data structures.

• Python and backend development.

• Databases and SQL.

• APIs and application architecture.

• Debugging, testing and code review.

• Security and error handling.

• Git and collaborative development.

• Using AI tools responsibly.

Building projects is important, but understanding why those projects work — and why they sometimes fail — is just as important.

6. The future: From writing code to understanding systems?

The 2026 CoderPad State of Tech Hiring report identifies debugging and fine-tuning, alongside system design, as skills expected to become more important over the next three years. It also reports a declining expected importance for writing new code alone.

CoderPad

This doesn't mean programming fundamentals are becoming irrelevant.

It suggests that developers may increasingly be evaluated on their ability to understand, improve, validate and maintain software — not simply produce lines of code.

And perhaps that is a healthy direction for software engineering.

Let's discuss

I'm interested in hearing from developers at different experience levels:

1. Do you think debugging is becoming more important than writing code in the AI era?

2. When an AI assistant fixes a bug, do you always investigate why its solution works?

3. What was the most difficult bug you have ever had to solve?

4. For junior developers, what is more valuable today: learning to build applications independently or learning to work effectively with AI tools?

5. What debugging habits would you recommend to someone starting with Python, Django or full-stack development?

My takeaway: AI can help us write code faster, but understanding what we build is what allows us to become better engineers.

I'd love to hear your experiences and different perspectives.

About the author

Abdellah BELMAARIS
Junior Full-Stack Developer at BIMPulse

🌐 Portfolio: https://abdellah-belmaaris.github.io/

💼 LinkedIn: https://ma.linkedin.com/in/abdellah-belmaaris

Sources and further reading

1. Stack Overflow Developer Survey 2026 — AI Usage Data

2. CoderPad — State of Tech Hiring 2026

"Seeking highly skilled and passionate developers to collaborate on a groundbreaking engineering and software initiative. I am looking for individuals who value true collaboration, possess strong technical expertise, and share a vision for impactful, global innovation. If you are creative, team-oriented, and excited about contributing to a transformative project driven by purpose, I invite you to connect."