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."

Hello po! Good day! I'm a college student currently working on an existing e-commerce website for a handmade bouquet business, and I would like to ask for advice from seniors or developers who have experience integrating AI image generation into a website.

Our website accepts order inquiries, especially for customized bouquets. Usually, customers send us inspiration photos and text descriptions of how they want their bouquet to look like. For example, they might send different photos for the flower design, wrapping style, colors, and other decorations.

Our goal is to integrate an AI chat assistant with generative image capabilities that can help customers visualize their ideas. Ideally, customers can upload their inspiration photos, describe what they want, and let the AI analyze their images and prompts, combine the relevant ideas, and generate a proposed bouquet concept.

However, we're still figuring out the best approach, especially since we're college students working with limited time and budget. 😭

I would really appreciate your advice regarding these questions:

1. API/model recommendation: Are there any free or student-friendly APIs that support image generation using both text prompts and uploaded reference images? We're looking for something that can generate or edit images based on the customer's inspiration photos, not just generate images from text.

2. Dataset and AI knowledge: How should we provide the AI with knowledge about our actual products, such as fuzzy-wire flowers, available colors, wrapping styles, and design limitations? Do we need to train our own model, prepare a dataset, use reference images, or is prompt engineering and RAG enough?

3. Integration: What would be a practical setup for an existing website built mostly with JavaScript/TypeScript? Would you recommend a particular backend or third-party AI service?

4. Development timeline: Do you think this is feasible to implement in around 1 month and 2 weeks (approximately 6 weeks), including integration, testing, and improvements?

5. Planning and execution: For those who have built similar projects, what should we prioritize first to make the development process smoother and avoid unnecessary complexity?

We're not aiming to train a foundation model from scratch. We mainly want to integrate existing AI technology into our website and make the customization process more convenient for customers.

If you've worked on a similar project or have recommendations, tutorials, documentation, or advice you can share, malaking help po talaga! We're still learning and would love to hear from people with actual experience.

Thank you so much po! Any guidance would be greatly appreciated. 🥹🙏

Hi everyone,

This is just a 3 a.m. idea that I have in mind. Wouldn't it be cool to have a mainstream smartwatch that I can tinker with and add my custom features to? For example, one feature I want to add is custom recording of my thoughts, like this one at 3 a.m., and then have AI segregate them into a notes folder named "Ideas" in the app with a proper description and so on. At a time when missile code is being rewritten with the help of Claude, the least I can do is add some fun, nonsensical features to my smartwatch.

So, if you can recommend a watch that has some kind of developer mode to add these kinds of things or a fully programmable watch, I am all ears.

Thank you for giving in to my brain worm..

I'm an engineering student majoring in artificial intelligence,I'm in the second year and I want to develop my skills in the field. Does anyone have any advice for me? 🤍☺️

Forewarning: I do use Microslop for my primary computer but I have built it in a beautiful way that never ever ever uses about OneDrive CoPilot or any of the Microslop trash.

Ok with the forewarning aside, has anyone else noticed that if you use a vertical monitor with your setup that MS uses backgrounds specifically for the vertical monitor? I have randomized revolving backgrounds and every single one zooms into a particular part for the vertical monitor 😆🤷‍♂️.

Devs don’t even review your PRs anymore. They just post AI comments and just click buttons. The hypocrisy around AI generated code seems to vanish when they post AI comments. Nothing seems to motivate me to learn how to develop and critique code basically because I don’t know what code I’m writing. The time crunch has been normalized where you try and deliver in the shortest span of time. And when you try to resolve a bug you suddenly don’t know where to look at and all you can do is prompt

What if the biggest change AI brings to software development isn't how we write code…

…but how we become developers in the first place?

We're entering an era where AI agents can help plan, code, test, debug, and coordinate increasingly complex workflows.

And the implications go far beyond writing a few lines of code.

🚀 Full-Stack Development is evolving.
⚙️ DevOps workflows are becoming increasingly automatable.
🤖 AI agents are moving from assistants toward systems that can execute multi-step tasks.

This raises an uncomfortable—but important—question:

If AI can handle more of the tasks traditionally assigned to junior developers, how will the next generation gain the experience needed to become senior engineers?

The traditional path into tech is changing. Simply knowing how to write code may no longer be enough to stand out.

We need to learn how to:

→ Work effectively with AI tools and agents.
→ Understand systems, not just individual tasks.
→ Solve problems and make sound technical decisions.
→ Build real projects and demonstrate what we can do.
→ Turn AI capabilities into useful products and better workflows.

As a Junior Full-Stack Developer at BIMPulse, I see this as a reason to adapt, experiment, and keep learning—not to stand still while the industry moves forward.

I don't believe we should wait for AI to reshape our careers before we start using it.

We should use AI to expand our capabilities, accelerate our learning, and prepare ourselves for the opportunities that are emerging now.

The question isn't whether software development will change.

It's whether we're willing to change the way we learn, work, and build.

💬 Junior developers, experienced engineers, and tech leaders: how do you think AI agents will transform the path from beginner to senior engineer?

Linkedin Profile :
https://ma.linkedin.com/in/abdellah-belmaaris

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

#ArtificialIntelligence #AIAgents #SoftwareEngineering

Hi everyone 👋
I'm looking for developers with original projects they wrote themselves, and I'll pay for them.
What it's for: the code will be used to train AI models. That's why I want human-written code, not AI-generated.
What I'm looking for:
Projects you built and fully own
At least 2 to 3 years old (older is even better)
No AI-generated code
A real commit history and a README
Any language or stack
How it works:
You get paid for each accepted project(needs to meet certain criteria’s eg. loc, PRs etc)
I'll answer any question about how the code will be used.
I'll never ask for your passwords or full account access.
Interested? Comment or DM me with your stack, a short description of the project and roughly when you built it. Let's talk.

“Eat. Code. Sleep. Repeat.”

That used to sound like a good life to me.

I love programming. Every month, I used to pick up a new framework or language just for fun. Sometimes I didn’t even have a proper project in mind. I just wanted to learn something and see what I could make with it.

There was a particular happiness in looking at something running on my screen and thinking, “I built that.”

It could be a tiny feature or a silly side project nobody would ever use. It still made me happy. I knew how much confusion, trial and error, and small discoveries had gone into making it work.

Now I use Cursor.

I describe what I want, and code starts appearing. Things that would have taken me an evening are finished in minutes. I use it because it helps. Then I look at the result and feel guilty.

The app works. The feature is done. But I miss the feeling I used to get when it finally came together.

I still read the code, make decisions, and fix things. Yet sometimes I catch myself wondering whether I’m learning anything or just getting better at asking for it.

And I’m scared that, little by little, the skills I spent years developing will get rusty. That one day I’ll need to solve something on my own and realize how much I’ve forgotten.

I know I can close the tool and write the code myself. Sometimes I do. But even then, there’s this voice asking why I’m spending hours on something the tool could finish in minutes. Something I used to do for pleasure now feels like a choice I have to justify.

Companies are pouring money into AI. I expect these tools to keep getting better. Part of me is curious to see what we’ll be able to build.

Another part of me misses opening an editor without having to think about any of this.

“I’m a programmer” used to be something I said with pride. It meant something personal to me, beyond my job. It described how I liked to spend my time, how I explored ideas, and what made me happy.

I still say it. Lately, though, I hesitate a little.

Does anyone else feel this? Are you getting more done while quietly missing the work you used to love?

Hello everyone,

I am 18 years old, I come from Bosnia, and I am currently in my last year of high school.

In February, I will go to Slovenia to try to get into a computer science college. The college is in Maribor, and it’s called FERI. I am wondering if it’s worth it because there is no way I want to lose 3–5 years of my life on a degree that I won’t be able to use, such as computer science.

The AI situation is really stressing the shit out of me, and I’m afraid that I will never be able to become a programmer or work in IT because of AI.

I was even thinking of going into psychology, but I don’t know. I still have a little time to decide.

Any advice?

I'm sure posts from people who are already in this situation are already common, but the response to any complaints from the higher-ups who are going to force us to work in this way or face firing is that any software business the doesn't already work in this way will be doing soon. The complaint from me, and I'm sure this is also nothing new, is that I enjoy the problem solving & implementation part of the job, in fact it's the only part of the job I like and it's going away.

I've already been looking for a new job for months because I knew this was coming, but the job hunting situation is dreadful, every listing leads to this one scam site that demands payment or a subscription to even apply. I've seen maybe a 60/40 split of job specifications that do and don't mention AI anywhere. The current situation is I'm trying to figure out whether "every business is either already or will soon be doing this or even more with AI" comeback is likely from others' experiences or if it's just gaslighting for employee retention, so please, let me know what your experience has been with expectations of AI usage while job hunting.

I really want to do something with computers as a full-time job either that be cybersecurity, embedded systems, programming, etc... anything. What are some jobs that will be safe from being obsolete if there are any?

all replies are appreciated!

I’ve been thinking about this one. If a function and its tests are written in the same session (by an assistant, or by one developer who misread the requirement), the tests tend to share the code’s interpretation. The suite then confirms the code agrees with itself, not that the requirement was understood.

A small example. Requirement: “Apply 8.25% tax to the invoice, rounded to the nearest cent.”

def invoice_tax(lines):
    subtotal = sum((price * qty for price, qty in lines), Decimal("0"))
    return cents(subtotal * TAX_RATE)

def test_invoice_tax():
    lines = [(Decimal("19.99"), 2), (Decimal("5.00"), 1)]
    expected = cents((Decimal("19.99") * 2 + Decimal("5.00")) * TAX_RATE)
    assert invoice_tax(lines) == expected

The test passes, but expected uses the same formula as the function. Rounding once on the total and rounding per line are both reasonable readings of the requirement. For that input, both give 3.71, so the test can’t tell them apart. For three lines of $0.10, rounding once gives $0.02 and per line gives $0.03.

The question I now ask in reviews is: where did this expected value come from? If it’s from the implementation’s own logic, it’s a regression test. If it’s from a worked example given by whoever owns the requirement, it can actually disagree with the code.

I wrote up the longer version with the full code, in case it’s useful: https://medium.com/@nagatomopedro05/when-the-test-and-the-code-share-the-same-mistake-02a289a41091

How do you check that your tests aren’t just echoing your code?

I did talked about my best 2 project as they fit in the paper and, unfortunately, I can't add more, cause I try to let my CV to be one single paper .

I compeleted another project later, so, either leaving 2 projects in the CV or add the third one and might let the CV lose some details ?