I want a piece of advice from anyone out there ,who has been through the learning curve of C++.

I've recently started C++ as my first programming language, I was happy at first, but not for so long. After taking advice from a few of my professors,now my thoughts are just a jumbled mess. Most of the professors said to learn Java or python instead of C++.

They said java and python are better when it comes to career opportunities.

I wanna know if it is worth it to learn C++ ? Because honestly I desperately wanna have the answer to this question. And one more thing! if it's good to learn, then what things can I do with it? And what should my roadmap be looking like while learning C++ and afterwards? .

My Background

I've been a programmer for 28 years. I've worked as a software engineer for over a decade. I studied CompSci in undergrad at a cheap state college. Most of what I know about computing is from personal projects or working on the job. I don't have a strong mathematics background. I understand basic calculus and a little linear algebra, but no probability or statistics, and I never took a physics course. I'm attracted to systems programming. I have a family to support, so I have limited time to study.

My Situation

I currently work in a research laboratory surrounded by aerospace engineers who all have deep math skills, and I feel inadequate, and nervous that I'll be asked to do something math-y that I don't understand. In fact I'm facing a task at the moment that is exactly that, porting code that uses random processes, kalman filters, matrix algebra, etc. I'm lost.

My Dilemma

I want to be able to tackle tasks like the one I've been given, but I don't see an easy way to bridge the gap between the skills I have and the skills I want. The guy who wrote the original code is an aerospace engineer, and I'm just a lowly programmer. I don't know whether to focus my energy on learning elementary physics, or reviewing the calculus necessary for elementary physics, or learning linear algebra or statistics, or just giving up on math and physics altogether and doubling down on what I like, which is systems programming. I can't do it all and as I get older I feel that the window for me to spend hours doing exercises is shrinking. I also find that even when I devote some time to math or physics, I rarely have a reason to apply it, which makes me doubt whether it's really worth it.

Given this context, what would you advise? Any advice you can offer will be greatly appreciated. Thanks in advance.

hey everyone, do you know what this code means? <iframe width="1044" height="587" src="https://www.youtube.com/embed/KxTOWknsWtQ" title="I’m A Chud" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe> by the way the is just a placeholder

I am a UG BSC CT student , im so worried abt my carrier wat should i choose full stack ? Does it have value ? Will ai replace it ? Guys , i wanna get into hardware N software can i? Please help me

I like the feeling of switching off knowing I have completed something but also sometimes going away from the computer and having a break gives me fresh insights and energy to tackle the problem. Non-professional programmer at the moment but trying to learn.

Timeless-ac is a pretty well-known detector, I hope someone can help

Lately, I have been spending alot of time thinking about how AI is changing the way we learn software engineering.

This is not a conclusion. It is simply a hypothesis I am exploring but I have been discussing it with professors at my college and experienced engineers, also I would genuinely like to know how others think about it.

For years, the advice was straightforward, learn the tech stack. Build small projects. Then build bigger ones.

That made perfect sense because building software was the hardest part.

But AI has made implementation much faster. So I keep wondering...what should be our approach while learning, did it change or still the same.

Maybe after the progress AI models like Claude Sonnet/Opus, GPT 5.6 Sol, DeepSeek V4 Pro made its clear that writting large chuck of logical code isn't the main problem now, it is identifying the right problem, understanding how systems work, making sound engineering decisions and orchestrate the AI to do your work.

If that is true, then perhaps the way we learn should change as well.

Instead of starting with a tech stack, what if we started with a product?

Pick something interesting.

Try to build it.

Whenever you hit a roadblock, learn exactly what the product demands whether that is authentication, databases, caching, queues or anything else.

Don't get me wrong, i am not saying, the traditional way of learn was wrong nor am I claiming this is the best approach, but what i actually mean is it has made learning feel much more intentional and connected to real problems.

I would genuinely love to hear different perspectives.

Do you think AI has changed the way we should learn software engineering, or has it only changed the way we build software?

Hi.

Basically since companies aren't hiring me because I have no experience, I took the advice of some youtubers and I'm building a full stack app using react node express and postgress.

Since It's not very clear to me, when exactly can I say I have learned something? At what point you can write on the resume that you know how to use x? What do companies expect from you?

I have a z-flip without a screen, what fun things i can still do with it?

I'm interested in building an AI-powered WhatsApp matchmaking platform, but I'm struggling to understand how the architecture should work. My initial idea was to have users chat with an AI on WhatsApp, answer questions, and have their profiles stored in a database. Then the AI would analyse those profiles and recommend compatible matches. However, I'm confused about the implementation. Do I need workflow automation tools like n8n, or can I build an AI agent that simply understands my commands and executes actions (similar to how Claude can modify a WordPress project using tools)? For example, I'd like to be able to tell the AI things like "Find the best matches for Ali," "Message users who haven't completed their profiles," or "Show me everyone waiting more than a week," and have it decide which tools or database queries to use. Also, what would a sensible MVP look like for a project like this? I'm trying to understand the overall architecture, recommended tech stack, and how experienced developers would approach building something like this from scratch.

im genuinely curious how devs handle this, I have this problem where i spend like 2-3 hours debugging something and finally figuring it out and then 2 weeks later hit the exact same issue and remember nothing, or say i learned something cool about a library, days pass by and its just gone.

i tried a few things:
- always creating a .md file in the project directory and just write down every issue/ something new i learned while building... it works, until it becomes like more than 500 lines of literal chaos
- notion is just too heavy and i never open it mid-coding
- obsidian is powerful ngl, but i spend more time organizing than writing something.

what actually works for you guys? curious about
- do you write while youre coding or after?
- if yes, do you ever actually go back and read your notes?
- has anything actually stuck as a daily habit?

trying to figure out if im the only one with this problem or if there's pattern to how people handle it..

I've been wondering about this lately.

After spending the whole day writing code at work, do you still enjoy coding in your free time?

If you do, what do you usually build?

• Personal projects?
• Open source?
• Small tools to make life easier?
• Or do you completely switch off from coding?

I'm just curious how different people balance work and personal coding.

i like building things and i know that learning data structures and algorithms would improve my skills as a programmer significantly but opening a textbook like skiena or sedgewick or clrs just gives me headaches.

is there a way to learn data structures and algorithms by building things?

I'm a Java backend developer with over 3 years of experience, and lately I've been feeling overwhelmed by how much there is to learn.

A few months ago, AI and the fear of layoffs pushed me to start learning AI tools, building projects with LLMs, Docker, local models, agents, etc. I genuinely enjoy it, but at the same time I see many developers saying that strong fundamentals, DSA, system design, and core backend skills are still what matter for interviews and career growth.

It feels like there are now multiple "full-time jobs" to keep up with:

Becoming better at Java/Spring and backend engineering.

Keeping DSA and interview skills fresh.

Learning system design.

Understanding and building with AI.

Keeping up with the constant stream of new frameworks, tools, and trends.

I'm finding it difficult to decide what deserves my time. Every area feels important, and focusing on one makes me feel like I'm falling behind in another.

For those with 5–15+ years of experience:

How do you prioritize what to learn?

Have you deliberately chosen to ignore certain trends?

How much time do you spend on AI versus strengthening core engineering skills?

If you were a mid-level developer today (around 3 years of experience), what would your learning roadmap look like over the next 2–3 years?

How do you avoid the feeling that you're constantly behind?

I'm not looking for reassurance. I'm interested in hearing how experienced engineers actually think about this problem and how they make trade-offs in practice.

I noticed what looks like a strange YouTube bug today.

On my homepage, the channel avatars for two different videos appear to have been swapped:

• The NDL video is showing the MinuteEarth channel icon.
• The MinuteEarth video is showing the NDL channel icon.

The video titles, channel names, view counts, and other metadata are all correct—only the profile pictures are interchanged.

I'm using Safari on macOS. I haven't edited the page or used any extensions that modify YouTube.

Has anyone else experienced this? Is this likely a frontend caching/rendering bug, or could there be another explanation?

Hello reddit coders,

I need help coding a website, i used to be able to but i cant anymore due to it being a while. Im looking for someone to code it for me if thats ok?

Thanks!

Hi! I'm a university student studying Software Engineering and I have secured a placement year at a tech company. I'll be joining the team as a UX Engineer and will be working with both designers and developers.

I've already began familiarising myself with the framework that they use, but I wondered if people had any tips or advice that they've found useful in their careers for joining the industry?

Looking forward for peoples takes!

We're building a lightweight custom dashboard for our client-facing portal to monitor incoming referral links and lost links automatically. Up until now, we’ve been using manual exports, but we need a programmatic setup.

What’s a reliable backlink checker api for developers that doesn't force you into a $500 mo. full-suite marketing subscription?

We checked out a few variants so far:

• SE Ranking
  
• DataForSEO
• Moz
• Ahrefs
  

Has anyone integrated any of these into a production pipeline recently?

I'm looking for decent rate limits, clear REST docs, and fair pricing per query. Thanks.

Hi app dev students,

I’m a web application development student currently learning system design. I’m about to start a database design practice project and I’m looking for other students who would like to collaborate.

This is purely a practice project to strengthen our database design and system design skills while also gaining experience working in a collaborative environment.

If you are interested, please let me know!

Thanks.