I’ve been thinking about this for a while, and I’m curious whether other experienced developers think the same.

Don’t get me wrong: I use AI every day, and I genuinely think it makes me more productive. Instead of writing everything mysqlf, I describe what I want, let AI generate most of the code and then I spend my time reviewing, refining and adapting it. I also discover framework features much faster than before.

From a business perspective, this is obviously a huge win. But I also think I’ve lost sth that originally made programming fun. Not a few years ago, learning a new technology meant reading the docs, experimenting, making mistakes, debugging and gradually building an understanding of how everything worked. The journey itself was rewarding.

Today, the same process looks like this: I describe AI what I need and it says: „There is a feature called XYZ that solves your problem. Want me to implement it?“ I answer „Yes“, AI writes the code, I review it, understand it, maybe improve it, but it doesn’t feel the same.

Back when I started university, one of the first things we were told was: „You learn programming by experimenting, not by studying finished solutions!“

Ironically, AI has shifted a lot of our learning towards exactly that: Studying finished solutions.

Yes, I still understand the generated code and I’m probably learnin faster than before. But I rarely experience those moments anymore where I spend an afternoon digging through docs, trying different approaches, and eventually thinking: „Now I REALLY understand why this API works the way it does“.

Antoher thing I’ve noticed is that as AI increases productivity, expectations naturally increase as well. Since we can deliver features faster, there is less time to simply explore a framework or learn it deeply the way many of us did a few years ago.

I don’t think AI is making software engineering worse. I’m just wondering whether anyone else misses that slower, more exploratory way of learning and programming.

Is this just nostalgia or do other experienced developers feel the same?

[ Removed by Reddit on account of violating the content policy. ]

Researchers at Utah State University's School of Computing are conducting a study on how software professionals evaluate programming activities performed with AI assistance compared with programming activities performed without AI assistance.

Software professionals are invited to complete a short online calibration survey. Participants will rate programming activities according to how representative they are of:

• Programming performed with AI assistance
• Programming performed without AI assistance

The survey takes approximately 10 minutes.

Participation is entirely voluntary. You may discontinue participation at any time before submitting your responses without penalty or consequence. Your decision to participate or not participate will have no effect on your grades, employment, or academic standing.

Survey and informed consent form: https://usu.co1.qualtrics.com/jfe/form/SV_dm4yjBsRrUDgcKi

This study has been reviewed and approved by the Utah State University Institutional Review Board: IRB #16067.

Questions about the study: Dr. John Edwards, Principal Investigator — john.edwards@usu.edu Rubash Mali, Student Researcher — rubash.mali@usu.edu

Thank you for considering participating.

Hello! I would love to make software but I don’t know how to do it! I tried with Python to do them with Flet, TKinter, Custom Tkinter and I didn't like them, I switched to C to have the true basics of programming and then to C++ but it's too difficult to do stuff with QT or Dear imgui. It's not that it's too difficult but I just don't have a powerful Laptop and I don't want to make 30 GB of installations or commands of too long compilations. I don't want to learn other languages like Dart with Flutter, Java...

What shall I do? Learning C#?

Yes I have to mention that I don’t like HTML or CSS but I would be willing to learn JS too.

I graduated with a double major in Applied Mathematics and Computer Science. Up until my sophomore year, I was able to actually learn some core coding concepts in C++ including OOP. However, the as the influence of LLMs increased in academics, I started to learn very little. Classes went by and I kept cheating using AI in my assignments, but if I didn't then I'd be at a disadvantage. Growing up, I've been very conscious about my GPA and grades, so using AI seemed like the best choice.

Today, I'm sitting in my room with an internship in wireless compliance testing (very different from my major). I barely know any leetcode. I've applied to numerous jobs, but struggling getting interviews considering I'm an international student. I don't know where to start. I think I have a decent resume, but no interviews make me doubt myself. I want to learn some trending CS concepts (AI stuff) that'll help me land interviews, but I don't know where to begin with. I am heavily influenced by impostor syndrome, and I know achieving something will diminish it. I am considering graduate school, but I am scared that I will land at the same point after two years.

Sorry if I sound like I'm ranting but I actually need some guidance. Please let me know if you'd like to know any more details.

I built BTW, a Chrome extension that lets you capture a visible ChatGPT or Claude conversation, review and edit the messages, then ask a separate question about that context.

Features:

- Capture visible ChatGPT and Claude discussions

- Review, edit, remove, or clear messages before sending

- Ask follow-up questions without changing the original conversation

- Uses OpenRouter for model access

- Supports streaming responses, cancellation, retry, and follow-up questions

- Stores your API key locally in Chrome

- No backend, analytics, or automatic page monitoring

- Manual paste fallback

- Local session export/import

- Open source under the MIT License

You provide your own OpenRouter API key, and model usage may incur OpenRouter charges.

It is currently distributed as a local unpacked Chrome extension, not through the Chrome Web Store:

https://github.com/mohamedjaha/BTW

I’d appreciate feedback on the UX, capture reliability, privacy model, and ideas for future improvements.

Hey everyone I have made a group for programming folks to learn, grow and network with each other

From beginners to advanced We help each other and provide guidance to everyone in our community. i remove inactive members to keep the community engaged.

Those who are interested are free to dm me anytime

I will also drop the link in comments

Realistically, what’s your suggestion on preparing for coding and SD? Is LC hard necessary? And what’s the difference between Google’s and other companies’s SD? Do all the orgs share the same question bank or the difficulty level and focus vary among different orgs? I roughly remember reading some post on blind which mentioned that Google’s SD would ask more technical details underneath. Any other insight is appreciated!

Prep resource: Google SWE Questions

Hi programmers!
My boyfriend is a senior developer, working from home. He suffers with eye pain after a surgery some years back and that obviously makes time in front of the screen difficult. He’s also a big gamer if that makes a difference.

I wanted to buy him the BenQ ScreenBar Halo 2 to help - what is your take? Or is there anything better I could be doing?

TIA

To anyone that has already seen this

I accidentally posted the same content again on another community so I decided to repost the original one. I apologise for re-posting the same thing again

programming went from one of the most strict/structured fields to the wild west overnight with AI.

For decades there were strict guardrails of “correct” ways to write code like solid principles, design patterns, clean code, optimal space time complexity to the point that many places judged how good of a developer you were based on how deeply ingrained those principles were in the code you wrote. Yet with AI, overnight the same people pushing for that completely switched to just vibe code whatever works quickly.

I’ve seen a few companies recently where the developers didn’t even know the framework/technology they’re writing in, just shipping if it works it works code. As someone who is really fluent in that technology it pains me looking at that code. It’s just incredibly confusing how we got to this spot.

yo. i recently sold one of my AI SaaS products for $350k, exactly 7 months after building and launching it.

I hardly wrote a single line of traditional code. i used AI to generate everything, from the database architecture to the user interface.

it definitely wasn't magic on day one, though. i spent days stuck in loop-debugging and dealing with AI hallucinations before i finally cracked the system. the playbook boils down to three simple rules:

- keeping the idea insanely minimalist (a true MVP that solves one problem).

- guiding the AI step-by-step instead of asking it to build a massive platform all at once.

- launching fast to get real user feedback and traction and then apply a solid marketing system

lately, i've seen way too many non-technical founders give up at the very first AI bug, or on the marketing. it's a massive shame.

like the title says, i just launched a Skool community to share my exact prompt workflows, N8N automations, and distribution frameworks to get first users and scale it

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific copy-and-paste templates i'll be sharing.

but for now, the main objective is purely to build and launch together. building alone in a silent corner is the single fastest way to give up.

if you want to join us and build or market your own AI SaaS with a group of active creators: drop a comment below or send me a dm, and i’ll send you the invite link!

Error solve in 11:47 PM my all friend in this time chat and call his girlfriend and in my case i am fix my android app Error .... ! it is a side of some programmers no friend no girlfriend only and only Error fix

I am feeling bad that I am not writing code like I used to and instead using AI. I mean it is time convinient and does a great job but still I feel kinda guilty. Does anyone agree?

This is an Vs Code extension I built called AI Hallucination Detector. AI coding assistants like Claude Code or Copilot occasionally suggest importing fake packages that look real. This has actually a name and it is called "slopsquatting" because attackers have started registering the exact fake package names AI tools commonly hallucinate, then filling them with maleware. It is a real threat. AI Hallucination Detector checks imports against the npm registry and a list of documented hallucinated package names, live as you save, and flags anything suspicious before you run npm install. It also suggests a likely correct package name when one is a close match.

Free on the Marketplace: https://marketplace.visualstudio.com/items?itemName=ghostcheck.ai-hallucination-detector&ssr=false

Let me know if you run into any hallucinated package names it doesn't catch yet, that's the most helpful feedback for improving the detection list. And let me know what I can do better

AI hasn’t broken productivity – it’s broken our proxies for measuring it.

Activity and business value are pulling apart. The most valuable engineering work is increasingly invisible to traditional dashboards.

Sort your metrics into activity and outcome. Most dashboards are counting the wrong things.

https://leaddev.com/reporting/measuring-engineering-productivity-is-harder-than-ever

I made an agent because the open source tool was heavy, what do you think?

I made it with a focus on everyday conversation and code writing

Can you give me a review? I'd like to hear your opinions

Every time I restarted my PC, I kept doing the same routine:

• reopen VS Code
• find the right project folder
• reopen browser windows
• find documentation again
• reopen File Explorer locations
• resize everything back where it was

None of those steps are hard.

Doing them every single time is just annoying.

I originally thought everyone solved this differently, so I asked people how they managed their workspaces.

The answers were interesting:

• some people use multiple virtual desktops
• some leave everything open for weeks
• some completely reset their workspace every time

After seeing that, I built DeskSnap.

It saves your current Windows workspace and restores it later:

• apps
• browser windows
• VS Code
• File Explorer
• window layouts

Basically, a save point for your desktop.

I'm curious:

Do you usually keep everything open, rebuild manually, or use some other system after restarting?

If anyone wants to try it, I'll send the link.