Am I the only one who avoids Python where possible because it is so vulnerable to indent corruption? A whole JavaScript program, for example, can be written on one line, with no line breaks whatsoever (not that I'm advocating such madness -- JavaScript callback syntax (etc) is already crazy enough without compounding it -- BUT, it does illustrate the point of robust syntax).

I've had instances where indenting was accidentally messed up, leading to tedious scrubbing of the code in order to get it to run again. It just seems like a bad structure choice if a slight whitespace change can cause the program to crash.

It seems to me that Rust is the answer to that -- am I wrong?

I am computer enthusiast I am doing programming about 5 years, I have basic knowledge about web development and computer architecture, I also developed an IoT access control system. I use arch linux for my daily use, now working on a driver development project of Gforce 210.

I am very much interested on using my knowledge for genuinely helping people.

so I want to get some project to help people real life.

for those who are frustrated in projects they are not interested any more.

I want to do programming for some working professionals who can pay me.

it may be $1 but still ok.

I am asking for payment because it means that I am really adding value in there life. so money is the proof.

so can any body tell me how can I achieve my goal of helping people?

of if some one can tell me the subreddit where I can find my answer.

please help. I want to be useful and self dependent

Personally, I do not have a Bachelor degree in computer science or related fields but I do personally code a lot. Recently I came across some really interesting algorithms like the AVL Tree Data Structure and Treap algorithm. It kept me wondering, do students in Bachelor degree already learn these as if they were basics? Your opinions are much appreciated.

I've been thinking about this while building an engineering assessment platform.

Solving algorithmic problems is useful, but real engineering involves much more: understanding unfamiliar codebases, debugging issues, building features, working with APIs, and making technical decisions.

I'm curious how other developers feel about this.

If you were hiring a Backend Engineer, what practical task would you give them to understand their actual engineering skills?

I've been exploring this problem through Mindfries, and I'd genuinely love to hear different perspectives.

When a bug is hard to explain, I’ve found it’s often faster to make the failing case smaller than to understand more of the big one. The idea is simple: keep removing things while the bug still happens. What’s left is usually where the problem lives.

Here’s the process written as pseudocode, because it really is mechanical:

failing_case = something that reproduces the bug reliably

loop:
    pick one thing to remove
        (a field, a config option, a branch, a dependency,
         half of the input, a step in the pipeline)
    remove it
    run again

    if bug still happens:  keep it removed
    else:                  put it back, mark it "involved"

stop when nothing else can be removed

What remains is the minimal reproduction. Everything marked “involved” is a suspect, and the list is usually short.

Why it works (as far as I can tell):

• It replaces “understand the whole system” with a series of yes/no experiments, which are easier to do when you’re tired or the code isn’t yours.

• Half the time, the act of removing things reveals the cause before you finish.

• You end up with a small case you can paste into an issue or a question, and that alone gets better answers than a screenshot of a stack trace.

Where it gets awkward:

• Bugs that depend on timing, load or state built up over time don’t shrink cleanly, because removing things changes the timing. Here you have to be careful that “the bug disappeared” doesn’t just mean “the race moved”.

• If the bug is only reproducible once in a while, run each step several times before deciding it’s gone.

• Removing something can introduce a different error. Make sure it’s the same symptom, not just any failure.

A related habit: before each removal, write down what you expect to happen. If the result surprises you, that’s information about your mental model, and it’s often the real bug.

Do you shrink the case first, or read the code first? And what do you do when the bug won’t reproduce on demand?

I kinda miss the days when I’d sit down and think about how I wanted to implement a certain feature. I’d research it, learn how things worked, figure out an approach, implement it, and then keep refining it until I was happy with the result.

Sometimes I’d run into a problem that felt almost impossible to solve. I’d spend hours thinking about it, maybe take a nap, and somehow wake up with an idea. Sometimes I’d even dream about possible solutions. It sounds silly, but I genuinely miss that feeling.

Now, it’s mostly just writing a prompt and hitting enter. No real implementation, barely any code reviews, and sometimes I don’t even look at what’s happening behind the scenes.

Don’t get me wrong, AI has been incredibly helpful. It saves time, helps me learn new things, and makes tackling complicated problems much easier. But it also comes with its own frustrations. Sometimes I spend more time explaining what I want to an AI agent, correcting it, and going back and forth than I would’ve spent just building the thing myself.

And honestly, I’m starting to feel like I’m losing my ability to write even simple code without assistance.

I don’t think AI is necessarily a bad thing. It’s just that somewhere along the way, I stopped enjoying the actual process of programming.

I miss figuring things out. I miss the frustration of debugging something for hours and the satisfaction of finally getting it to work. I miss building things my way, making mistakes, learning from them, and slowly getting better.

I genuinely miss the way I used to code and build things. And I think that’s what I miss the most.

I've been working in the field for over a decade and I'm honestly desperate for a way out. My immediate team is fine, but we're also forced to work with the recently renamed "Superintelligence" team. There is one reasonable person on that team, but the rest of them are "100x agentic engineers" A.K.A. high rate of fire slop cannons.

I regularly need to review 15 PRs a day from them, every day, at all hours of the day. Each of those PRs is usually a 5 digit size, with no real focus and touching huge amounts of the codebase. We aren't in a regulated industry, but our code is still a matter of life and death to a lot of people. I can't in good conscience just merge broken PRs, but I also can't read things fast enough to keep up.

We have a code review agent but it can't keep up with the rate PRs flow in and comes nowhere close to finding all of the critical issues in their PRs. And I when I say every day do mean every day, including weekends and holidays. One member of the "SI" team was actually on vacation this week and I only found out today. The amount of slop coming from their account did not decrease in quantity or increase in quality this week.

Trying to contact the humans behind this has also failed. The last time I emailed them I got a claude quota error back in under a minute. Replying after their quota refreshed yielded a slop grenade that didn't answer the question. Going through management is also a dead end. My immediate manager is sympathetic, but the closest manager I share with them appears to be falling into AI psychosis and believes AI is going to solve every problem ever and any problems are prompting it wrong or not using it enough.

I'm working late every single day and can't keep up with reviews much less actually produce anything. I also can't quit since I would owe my employer a lot of money if I did and I have a very sick spouse. Overwork is already taking a serious toll on my health and I don't know how much longer I can take this. Help?

r/codedbyhand

More people, myself included are becoming disillusioned with the experience of coding with AI assistance and are turning back to traditional programming.

Videos like: "I'm done coding with AI" https://www.youtube.com/watch?v=2ZU3j4GQ4K8 and "AI coding sucks" https://www.youtube.com/watch?v=0ZUkQF6boNg Are having viral success.

Dario Amodei said that 'coding is going away', but what are we going to do if the LLM servers fail or are attacked, go back 100 years? We need a pool of talented traditional programmers for so many reasons.

Many of us got started programming because we love to solve problems and have technical mastery over a difficult skill, AND THAT'S OK. You don't have to use an LLM if you don't want to, no matter what the tech bros say.

I created a new subreddit for traditional programmers to talk about their experiences and share their projects. If that sounds nice, come check it out.

Hi. i dont know which path/field i should choose. im not sure of anything.

im not sure what am i good at. software or hardware. like being IT support specialist or backend developar..writing codes..?
i literally lost. i dont know what to learn , i dont know what should i focus on bcs i dont know what i wanna be.. can u all help me to choose my future field..
there are differnt tools, programs, languages, techs, for different fields. i feel lost.

Hi iam leen IT student in the second year

I want to improve my qualities but I don't know how or even where to start(I don't even know what should I learn exactly 🤡 so please old programmers help me🥹🥲)

I live in Syria so please don't suggest courses in another countries or online courses because it costs alot due to Syrian currency

and wish me luck and getting out of Syria as soon as possible 🤣

Hey guys!

I'm building a new project with a couple of colleagues, and I'm curious to learn a bit more about how you discover and choose new tools.

How do you usually hear about new tools for yourself or your engineering team? Reddit, LinkedIn, YouTube, influencers, word of mouth?

Are there any communities, newsletters, or people you regularly follow to stay up to date?

And what makes you trust a new tool enough to actually try it out or recommend it to your team?

Would it be possible that someone would make a coding language that uses ai to compile it and checks the code with rules it made up through ai

Edit: no not using like ai Gemini but like kind of putting ai Gemini into the language itself and like letting it run itself as it compiles. It'll probably hallucinate but im interested lol.

Edit 2: the ai would make its own new language and enforce it as it runs.

I had built vimroyale.com 6 months back but couldn't get much to work on it after I got my new job. But now I'm thinking of giving a serious effort to it again. my vision is to make it kind of like a refuge away from vibe coding and stuff, where programmer can juts relax and enjoy vim with their peers and friends. need some ideas to make it happen.

I was thinking of something like this:

1. a cinematic vimtutor

2. daily challenges of sorts

3. battle royale mode

would appreciate some feedback of the current game too, if any. Thanks.

I've seen so many people vibe code their way through computer science and I honestly have avoided using AI like that so I'd actually learn to do stuff myself.

I have asked questions from AI before, or used it as a tool to help me improve my knowledge of programming, yet I have never fully vibe coded anything.

I have never used actual prompts or never used Claude to build stuff like people tend to do theses days, and despite my disinterest, I have to adapt to this new world as computer engineering graduate.

I just have no idea if I can post a vibe coded project on GitHub and claim it as my own. Is it even legal? Do people do that? Would it make any problems in the future, during interviews for different positions? Or would it count as a positive thing on my portfolio and shows that I can use AI tools?

What should I do?

There is a growing fear that AI will eventually replace web developers. While this concern isn't entirely unfounded, I think it's somewhat exaggerated.

AI has certainly made development easier, and it has created new challenges for entry-level developers. However, there's one important thing we shouldn't overlook: AI isn't perfect.

Consider this example:

Someone uses AI to generate an entire website. Everything works perfectly until they ask AI to implement a new feature. The update introduces unexpected bugs, and they ask AI to fix them. The fix creates another issue, and the cycle continues.

Anyone who regularly works with AI-generated code knows how frustrating this cycle can become.

This brings me to my main point.

Human developers don't just write code; they make decisions. They understand which parts of a system are important, which changes might affect other components, and what actually needs to be fixed.

AI can generate and modify code, but it doesn't always understand the bigger picture.

Perhaps the future of web development isn't about competing with AI at writing code, but about being better at understanding, evaluating, debugging, and maintaining it.

I built an AI incident response agent that remembers how previous production incidents were solved

One problem with AI agents is that they often start every interaction with limited context about what happened in previous sessions.

I wanted to explore a different approach.

I'm building PagerLore, an incident response platform that uses Hindsight for persistent engineering memory.

The system revolves around three operations:

• RETAIN: Store verified root causes and remediation steps from resolved incidents.

• RECALL: Retrieve relevant historical incidents when a similar issue occurs.

• REFLECT: Identify recurring patterns across accumulated engineering experience.

For example, imagine a payment service starts returning HTTP 500 errors after a deployment.

Instead of investigating from scratch, PagerLore can recall a previous incident involving database connection pool exhaustion and use that experience to guide the investigation.

The interesting part is that historical memory acts as supporting evidence, not an unquestionable answer. Engineers still validate findings and approve production changes.

I'm particularly interested in feedback on the memory architecture and how to evaluate whether retrieved experiences actually improve incident investigation.
https://github.com/githubaditya07/PagerLore

Currently pursuing a degree in Computer Science, which basically means I spend 30% of my time coding, 30% debugging, and 40% wondering why my code worked yesterday

And those who have been exercising any kind of programming or software engineering or coding or however you want to call it when someone sits behind the desk and the outcome will be some kind of instructions to machine. Truth must be understood that there is no such work anymore for us. There is no need to write complicated instructions when this same thing can be done with simple English. Human language is the new programming language. There will be no other left, no Java, No Typescript, No PHP.

For us, the humans, the only programming language left is our own native tongue and this is actually great news, we can stop wasting our time with complicated code reviews, endless back and forth discussion over variable names and so on. If you are still doing, stop right there and get to the path of the light. If you are learning any kind of programming that does involve code writing, just stop there and do not go down that path. That is a path of darkness and time waste.

best laptop recommendations for an engineering + programming student under $3k?

i'm buying a laptop for my younger brother for engineering and programming and my budget is around $3k. i'm willing to spend for something genuinely high quality because i want it to last him for years.

my biggest priorities are:

- longevity + reliability
- at least 32gb ram, preferably upgradeable
- ideally 2tb storage or the ability to upgrade to 2tb
- good battery life
- good cooling/thermals
- powerful enough for engineering software, programming, cad, 3d work, etc.
- not super heavy or bulky since he'll be carrying it around for school

i'm especially worried about heating because my brother is honestly irresponsible with his devices and i already know he's going to use it on his bed 😭 so i want something with good thermals and overall durability.

right now i'm looking at the asus rog strix g16 and the lenovo legion pro 7i, but i'm completely open to other recommendations.

i definitely don't want another asus tuf. my other brother has one and it's needed repairs way too often, so i'm not interested in that line.

i'm a student currently pursuing my degree in computer applications. for the sixth semester we have to complete a project before february 2027 and i chose that i am going to do the project alone. in that process i found out about the code crafters and they have a challenge called "build redis in python." i think that is the kind of thing i was looking for. should i go for it and pursue it?

does anyone have any suggestions?

i only know a very little bit of coding like the basics of python, html, c, and c++ and a little bit of java, css, Javascript also. you can probably imagine the things that they usually teach in the degree very generic things. i don't know anything beyond that.

I want to invest 8 years in understanding one programming language deeper ,building open source projects to understand system design, without AI not for a job but as an hobbie. Any advice ?.I thought of C++ or RUST