Sometimes I think AI has removed the joy from programming. Time was when making a TODO application felt like real work (as beginners). Now there's no feeling of achievement after completing projects. For example I'm working on a PID controller for my custom drone firmware. I programmed like 13 C files and I used AI to review it & it started over engineering & hallucinating only to result in an over engineered unreliable non working product. So I tried my own code & it worked without modifications. Has anyone experienced this as well?

I’ve been working as a developer for over 10 years, and one thing I’ve realised is that the average person isn’t nearly as competent as we like to believe. The number of genuinely bad developers I’ve worked with over the years is honestly astounding. People with years of experience who can barely solve a problem without following a tutorial or copying what someone else did.

And I don’t think this is limited to software development.
Humans are pretty good at learning repetitive tasks, getting comfortable with them and doing the same thing for years. That’s basically how a huge part of our workforce operates. Unfortunately, that’s also exactly the kind of work AI is getting ridiculously good at replacing.

Now add declining birth rates to the equation. Fewer young people entering the workforce, an ageing population and companies potentially struggling even more to find skilled workers. Why would businesses keep relying on humans when AI and robotics could eventually do the same jobs faster, cheaper and without most of the headaches?

And I think software development itself is going to change far more radically than people expect.
We have programming languages, frameworks, design patterns, architectural principles and all these abstractions because humans need them. We need structure to understand what we’re building, maintain it and collaborate with other developers.

But does an AI really need all of that?
If AI eventually becomes capable of building, testing, debugging and maintaining entire systems on its own, why would it need to follow the same conventions we’ve created for ourselves?

Look at the recent PHP memory-related vulnerabilities that needed patching, with AI reportedly playing a role in uncovering them. Think about how many vulnerabilities might still be sitting in codebases that have been maintained and reviewed by humans for decades.
Now imagine AI becoming significantly better at analysing entire systems, understanding memory management and finding security flaws that thousands of developers have overlooked.

I wouldn’t be surprised if we eventually reach a point where AI starts questioning the foundations of how we build software in the first place.
Why keep relying on layers of frameworks, abstractions and human-friendly programming languages if AI can eventually generate, optimise and validate machine-level instructions directly?

Maybe assembly or even binary-level generation will make more sense someday. Not because lower-level code is automatically safer, but because the limitations that made high-level languages necessary for humans might not apply in the same way to AI.
Sounds ridiculous today, but so did the idea of AI writing entire applications a few years ago.
We’re already moving towards a world where developers increasingly rely on AI-generated code, sometimes without even properly reviewing what it produces. And I’m seeing this happen more and more. Imagine what happens when AI becomes significantly better than the people who are supposed to review its work.

I genuinely believe the average worker is far more replaceable than most people are willing to admit.
And here’s the uncomfortable part: companies don’t need AI to be perfect. They just need it to be good enough, reliable enough and cheaper than hiring someone.
We’re constantly talking about how AI needs human supervision, how it makes mistakes and how it can’t replace real expertise. Fair enough. But we’re comparing today’s AI with today’s workforce. What happens when AI keeps improving while the average human doesn’t?
I think we’re much closer to that reality than people realise.

Curious what others think, especially developers who’ve been in the industry for a while. Are we overestimating AI, or are we massively overestimating ourselves?

as a person who worked in this industry for 5 years, I can say that all the AI hype is just a hot garbage so the investors will funnel money even more.

compared to 2020, LLMs just became dumber. look at Claude for example. it was the most capable AI I've used for coding. what we have now?

"Sorry I can't help with that". and then sudden bans with no reason provided or prior warning. or chatGPT. being the best general purpose from my perspective and now, it can't even write a simple JavaScript code.

I found myself spending more time trying to correct the stupid AI than actually doing something. fck that.

going through the web and asking in stackoverflow, and waiting for answer is much more efficient than doing such thing.

I don't understand.

why AI instead of learning and improving is just became worst of itself. missing context. cutting conversation in the half of it and not wanting to continue, giving not working code, hallucinating.

it is just a mess.

I just enjoyed how i would think of new solution and see it work but now I have to use AI to be fast and this is depressing me as I see people did not spend time and work to actually learn coding to make things work when they dont know how while I am taking time debuging and working on my code and then i appear not productive will AI take my work and think instead of me and then I be stupid not able to solve problems ?!!!

I'm a backend developer working in Azerbaijan, and honestly, I'm starting to feel quite anxious about the future of software engineering.

I genuinely believe that the industry is going through a massive transformation, and things will never be the same again.

I've been using Claude Max for over five months. At this point, I spend most of my working day writing prompts, reviewing AI-generated code, and directing AI agents rather than writing code myself.

Around 75% of the people in my company use Claude or Codex. Interestingly, even our company director, who used to be an SQL developer, now builds software using Codex and spends time attending meetings and presenting products to potential clients.

This has made me think a lot about the future of our profession.

Here is my current situation:

• I work as a backend developer in Azerbaijan.

• AI has become a major part of my daily workflow.

• I have my own AI-based side project, but it isn't generating revenue yet.

• There are periods when I don't have much assigned work because AI has made certain tasks significantly faster. Sometimes I genuinely don't know how to use that extra time productively.

• Asking for a salary increase feels increasingly uncomfortable because I keep questioning how much value I actually bring compared to what AI can do.

What's interesting is that the situation in Azerbaijan still seems relatively calm. Companies aren't making widespread layoffs, at least from what I can see. However, the number of available developer positions seems to be decreasing.

I'm curious about what's happening in other countries.

I'd really appreciate hearing about your personal experiences:

1. Are tech companies in your country laying off software developers because of AI, or are they mainly reducing new hiring?

2. Have you noticed fewer junior or mid-level developer positions being advertised?

3. Has your company changed its expectations of developers since adopting AI coding tools?

4. If AI allows you to complete your work in half the time, does your company expect you to produce twice as much?

5. How are you making yourself more valuable in this changing environment? Are you focusing on system design, AI engineering, architecture, business knowledge, or something else?

6. Are you considering moving away from traditional software development into product management, entrepreneurship, consulting, or another field?

7. Have you started building your own AI-powered products or businesses? If so, are you actually making money from them?

8. Do you still think becoming a software developer is a good career choice for someone starting today?

9. If you had 6–12 months to prepare for the next wave of AI disruption, what would you focus on learning?

I'm not looking for generic advice like "just learn AI" or "adapt or die."

I'd love to hear from people who are actually working in the industry and experiencing these changes firsthand.

Are we going through a temporary productivity shift, or are we witnessing a fundamental change in the economics of software engineering?

Thanks for sharing your experiences.

Hello guys! I am Lewis and like coding. Today my aunt said that I might not become a developer because AI is so powerful. Being a Developer is my dream and I want to achieve it. But now I am scared that I never will become a developer because of it.

My question is:

Will AI really take over all developer jobs? Or can I work as developer until the day I am old? I currently go to school but want to start to work in this direction in the next few years.

Would it be disrespectful to get help from AI while coding? Not too muc or always, tho. My friend does his coding super messy and I got curious about this. Im aware of what AI does.

Just a few years ago, the meme in traditional human coding was "If it works, it works" or "Don't fix it if it's not broken." So everybody was 'on board' that human code sucked but worked. Now AI does the same thing, but gets called bad code/AI slop etc.

I'm a cybersecurity student so I used to study coding, but haven't got deep enough to distinguish good code from bad code, and then started vibecoding.

Also, the "secure-coding should never be vibecoded" is the current norm in the cyber security side of CS, so I guess that's also one of the major reasons I'm raising this question.

So is the code really that bad? Or is it actually acceptable, but people just had higher hopes for AI code?

I'm new to programming and im only 17 so im a lot confused.

IS PROGRAMMING WORTH IT IN 2025?

I mean right now if you want a decent amount , you need to work for 2-3 years and have atleast 2 years of experience to earn 100k amount . Whereas actors , youtubers , influencers earn 30k a month and some earn 100k per month . And the competition in cse is very much increasing a lot. And most of the 9-5 software engineer don't have a social life.

id like to give more details but unfortunately every single post has been moderated, i will pay and i will provide more details abt both projects

The real reason why 16 gigs of RAM is not sufficient is AI — but not in the way everyone thinks.

My point is: engineers use AI to develop apps that turn out sloppy (bad UI, poor UX). But the fault here is not about using AI — the app can still be optimized, developers just choose not to. The reason is that the big companies they work for give them high-end, high-performance computers for development, so they don’t care about lower-end devices. Of course the app may work on potato PCs, but the thing is it will have way more issues than the developer expected.

Luckily I have a solution — ban AI. lol just kidding.

Give developers low-end machines so they are forced to optimize their apps to the absolute max.

Let me involve an example to support my case — WhatsApp. WhatsApp was good, working, no issues. But now WhatsApp is basically a web wrapper, requiring internet to even open, and it lost lots of other features too like the popout chat where tf is it !?

So the developers are tricked into thinking they are doing a good job, but in reality tech is evolving backwards.

I used to dive straight into coding new features. Write tests, build functionality, refactor, rinse, repeat. After 3 months of switching my workflow to plan with AI first, my productivity has completely transformed.

The difference? I now spend 2-3 hours with AI planning my feature implementation BEFORE writing a single line of code. This upfront investment saves me 10-20 hours of development time per feature.

My workflow:

1. Take the product spec to an AI and have it generate a comprehensive technical design doc

2. Ask the AI to critique its own design and identify edge cases

3. Have it draft API specifications based on the design

4. Generate UML diagrams and ERDs for more complex features

5. Have it craft the implementation context, including potential interactions with existing systems

6. Review and refine the designs, architecture diagrams, and specs

The magic happens when you use all this planning material as context for your coding. My team lead has started implementing this approach across our department

Has anyone else tried an AI-first planning approach? What workflows have you developed that maximize AI's architectural planning capabilities?

I'm Looking for skilled Europen or Russians Developers with good English proficiency and speaking skills, who are interested in the US Job market and want to get a job in US companies.

Upvote and dm with your resume please.

I apologize if this sounds insulting, just understand that I'm being really honest and trying to understand.

How do you get work done in GUI IDEs?

If I see a developer share their screen from Windows, I already assume they are a slow developer sometimes incompetent. I started writing code on Windows with Visual Studio then Eclipse. Once I discovered EMACs, ssh, tmux, my ability to knock out problems quickly and accurately grew dramatically. My standard setup is OS X and all code is done via emacs on a linux server.

On to my question, how do you get work done efficiently with a mouse? Just to preface, I have serious mouse shoulder problems. I can't imagine spending an entire day clicking through folders in VS Code or any GUI IDE to get work done. I can find a file, edit it, test it, push it to `git` without ever touching a mouse. Now it's 2023, M$ has bought up all the AI R&D and put those features only in VSCode with Github Copilot. Without that, I wouldn't even consider installing a GUI IDE onto my computer. I do wish there was a way i could do development on Windows without it feeling like it slows me down 90% compared to my OS X + Linux setup.

Looking for developers who can build or assist on white-label AI products.

I run an AI studio focused on launching multiple SaaS and agentic tools. I need sharp engineers who can:

• Build or customize white-label platforms

• Ship fast without micromanagement

• Work across AI, LLM, and data stacks

If you’re interested or know someone who fits, message me.

We've entered an era where AI does pretty much all the coding now. How are you developers preparing for this? There are already so many ideas out there, so I honestly don't know what or how to prepare.

Personally, I feel like building services with AI tools is getting easier, but architecting scalable systems or coming up with truly defensible product moats still seems tough. Are you guys focusing more on system architecture, domain knowledge, or something else entirely?

Our company has started capping our AI limits, start at 400$, and manager approval around 800$ and then post 800, skip level approval is required.

We've basically moved down to haiku 5.5 after mostly using opus & gpt, seems to be more value for money with haiku suprisingly. Wondering if this is the situation everywhere now?

For context, I'm a hobbyist programmer who has no intention of pursuing a career in software development. I have no experience when it comes to actually working for a company with deadlines and management pressure, etc. Because of that I'm very interested in how AI gets used in commercial development.

I'm having trouble understanding the appeal of AI in code development, because to me it seems just like a quantity over quality solution to efficiency.

In order to have a good codebase, you need to understand exactly what your AI generated code does. If you don't the code is effectively unmaintainable, because AI can't be trusted to just solve every problem that comes up. If you use AI to solve a problem or bug, you need to understand how it solves that problem. If you can understand how it solves the problem, it doesn't seem far fetched to me that you could've come up with that on your own, and you're losing out on maintaining your own problem-solving skills, which could come back to bite you later. Of course, sometimes you get lost in the sauce and need a second pair of eyes, but why not get a second pair of actual eyes from a co-worker or a more senior developer, with whom there's much less chance of a hallucination, or incorrect response?

My point is mostly that, even with AI, you have to think a lot and understand everything that's going on in your codebase, and at that point, what benefit does AI have in building and maintaining a quality codebase? To me, it just seems like it reduces typing time, which in my experience as a hobbyist, the thing I spend the least amount of time on is typing. I spend most of my time thinking, and looking at the code.

The only thing I've found it to be really good at is searching through stack overflow quicker than I can lol. It's good at browsing forums and finding solutions that other people have wrote, not at coming up with solutions on it's own.

I have my own moral opinions on AI, like everyone does, but I wanna leave that out of this discussion and just hear what people have to about it's usefulness.

This is something I started doing around year ten of my programmer career. I encourage everyone to do the same.

write a script to clone a fresh copy of your codebase instantly on your system. Great for reviews and health checks. If you are using git, this should be some git commands and a few cp's

bonus points: add a parameter to the script that checks out a specific branch.

branch=$1 git checkout $branch

iddqd: extend the script so that it instantly builds and launches the code after checkout. React Native devs should be able to do this fairly easy with the cli tools available

I use this technique to speedup reviews and to avoid interrupting my own work.

it's okay to have multiple copies of the same codes guys 😀

Dear junior developers who just passed out or have 1 to 3 years of experience:

Do you think you write better code than Claude Opus 4.6?

Do you still think you should stop writing code manually and instead become a system architect just telling Claude what code to write and defining the system while believing your job will still be safe?

Do you think Claude might one day decide for itself what code to write and how to design system architecture, and do it better than you?

And if that happens, do you think you can just move into management to save yourself?

Cursor was fine, could make mistakes and generate stupid mistakes!

but Antigravity..! bruh, it's definitely taking jobs, I'm certain!

recently created complete App with Antigravity and it's working in production, in most cases useing AI at work, wrote very less code since 1 year, just reviewing and defining architecture, even architecture i discuss with LLM first and then do some Google for latest stuff.

researching on how to produce more vegetables in less time, valid resources are welcome.

Hi,

I've turned my personal website into an AI that can be queried by recruiters, what's your opinion about this? Good or bad idea?

Lately I've seen a lot of people very happy about AI since it has boosted their productivity a lot. It has happened to me too, just not at the same extent as them. For example, one guy said he created a full CRM that could have taken him 3 or 6 months, in just 3 weeks. I mean, I've learned at a very high pace since I'm using AI, but I haven't been able to multiply my productivity by a factor of 8. I usually find AI the most valuable when I have to create things from scratch, but the moment I have to tweek or convert a design into code, especially on mobile, suddenly it becomes less than ideal. Can you guys share some tricks or your workflow or any resource AI related that could help to really improve my productivity? Thanks

Reach out to me plz.

My day has shifted from writing code to reading it. Tests pass, the feature works in the demo, and then something odd shows up two weeks later.

These are the things I now look for on every review that tests usually don’t cover:

• Duplicate logic. The model happily re-implements a helper that already exists three folders away.

• Quiet error handling. Broad try/catch blocks that swallow failures and return something that looks fine.

• Race conditions and double submits. It writes the happy path very well, and the edge cases less so.

• Over-engineering. Abstractions and config options nobody asked for.

• Dependencies. A new library pulled in for something five lines of code would do.

What I haven’t figured out is how to review fast without getting lazy. After the tenth clean-looking diff in a row, I notice I’m skimming.

What’s on your checklist? And has anyone found a review habit that actually keeps you honest?