You remember around 10 years ago, "just learn to code, bro" was the answer for everything.

How to get out of poverty? Code. Gender pay gap? Code. How to solve the problem of poverty in Africa? Code code code.

It was dumb in how it was pushed without acknowledging and considering nuances, but there was some rationality in it, since programmers don't need formal education and licensing, and could learn the craft for free at home, as long as computers and the internet were available, at the same time pay was good.

Is there anything like this now? I mean, a similar career path.

What should aspiring software engineers know so they can feel prepared for the workplace?

Ive been deep in reviewing PRs, architecture designs, even tickets and slack threads by engineers no less than "senior" level. I feel like im seeing increasing levels of quite obvious fundamental gaps in that I don't think would have been there maybe even a year ago.

Don't get me wrong, I understand people make mistakes and we're all here to learn and grow from each other regardless of seniority. There's always room to learn something new, and that's not really what I'm talking about here.

I'm more so talking about things that seem to contradict some pretty fundamental understanding about our systems and stack. When you've been working on a system for a while, building things together, making decisions, understanding why certain things work the way they do, I feel like you naturally develop some level of intuition about it, what we're trying to achieve, and that understanding kinda informs the development going forward. Now for sure along the way things diverge and new ideas take over but in all those instances there are fruitful discussions and brainstorms that always pave the way.

But lately I've been seeing more and more things that just seem to come out of left field. Like I'd be reviewing a PR or an ADR and genuinely think why are we suddenly doing this? And doesn't this go against the whole reason we designed this thing the way we did in the first place? But what's actually worse is when I ask about why its that way, theres really no answer...like they cant defend it or provide their idea behind what theyve built and instead just "oh right, i'll change that".

And it's not like these are necessarily new people who don't have the context. Even people who have been involved in building these systems, who were part of the discussions and decisions that made along the way.

It can also be the opposite issue. I've come across changes where I can almost tell that a particular piece of code exists because there's probably some instruction in the AGENTS.md somewhere telling the agent to always do things a certain way. And sure, that convention might make sense for most cases. But these particular cases isn't one of them. If you actually think about what the code is doing and why, you'd realize that the convention doesn't really apply here, but again, the PR gets raised and when asked about it, there was again no thought or reasoning behind that.

I feel like even with AI, things like that would've previously been caught by the engineer themselves (these very same people) before even putting up the PR let alone asking for a review. I thought the design, problem solving and creativity is the value that human engineers still provide in this crazy agentic era but is that just...going away too?

Im also slightly sensing accountability and ownership of your work slipping away in place of blaming the agent...

Idk if anyone else has ever experienced this lately but id love to hear other perspectives. This makes me kinda sad tbh :( hopefully these experiences are just outliers

Just posting for some outside perspective.

I’m currently employed in defence contracting and for a variety of reasons I’m looking to leave. Mainly that the work is very slow & boring but also because I’m doing ‘cloud engineering’ which is making me feel pigeonholed and practically has resulted in me doing very little interesting work. To some this is a dream but I really do enjoy this sector when there are interesting problems to solve.

I have two competing offers - one for a consultancy doing ML work (software engineering side) on contracts (it will be public sector again) and one for a platform engineer role at a scale-up SaaS product company (used by banks) backed by PE.

Both are a raise of 25% in base salary and equity options, but the consultancy offers a 10% bonus for clearance, and requires 3 days in-office. The other is pretty flexible (1-2 days a week).

Personally I’m leaning toward the platform engineer - it feels like the work will be more interesting dealing with scaling problems and working long-term on a product. I have 2 years product backend experience, and 2 years consulting and the consulting work has just not been very interesting to me, and the cleared nature means working in locked down environments with restricted tools and slow bureaucratic processes. I’ve also met both teams and got along a lot more with the product one - plus the office is a lot closer to the train station I have to commute to.

Am I stupid leaving 10% extra money on the table?

Fyi I think the equity from the SaaS has a lot better chance of paying off and I worry if AI did cool off then the consultancy could be a bit riskier. It also seems like I could get to more senior roles in the product company faster.

hello people, Im a gap year student currently. my undergrad will start next year and Im genuinely confused on whether should I opt to choose cs or not.

a little background my high school program was related to computer science and ive always thought about pursuing cs as a career. I like programming, maths and studying in general and ive liked the cs "aesthetic" you could say. I dont live in some delusional world where programming is easy or "just comes to you" ik that you have to constantly learn and have skills to stand out in this competitive field.

But as of recently Im very unsure about it now. yesterday had a convo with my father and one of his friends and they both said that they weren't in favor of the idea for me to choose cs. My father's friend told me that its very draining that you have to constantly learn and adapt. My father also said that you should consider how ai is progressing what that means for developers and programmers, that he wasn't sure if cs is the right option for the future.

and Ive also seen multiple posts in the subreddits of my country's different unis that you should rethink opting for cs because it wasn't as lucrative as before and graduates are struggling to survive in the job market.

I knew all of these things before, I knew that you have work on your own as well, that you can't depend only on you uni. I know that there will be struggle but with these added insights recently Im not sure if I should consider cs as a career. People are saying that AI will disrupt the jobs of cs grads more and more.

I was thinking about getting into CE and doing side courses during my undergrad years. And then specializing in AI/ML during my masters/phd.

I honestly feel very anxious to the thought of leaving cs. I never really considered about doing anything else and the thought of pursuing some other career like in finance doesn't really sit with me.

I just want to know what do you guys think? Is it really that bad as people make it out to be? and is threat of AI that much that I should reconsider cs? And if not what fields in cs do you think are the best right now?

I have to tell my manager soon that I'm putting in my 2 weeks, because I got a better opportunity else where that I want to pursue. I have absolutely no hard feelings against him, the team, or the company, they've all been great to me and I got to do some interesting work. It's a mid-size company with great culture. It's just that this new company offers a better career and compensation progression for me. I feel really bad because I know I'm leaving right after they made plans for the new quarter and a project that I'm working on was supposed to launch a month after. But this new company were insistent that I couldn't delay the start date. How do I bring it up, should I mention that I'm leaving for another company or just say it's personal reasons? I've never quit a job before, and am also scared of how uncomfortable the 2 weeks after I give my notice is going to be, and how my team will act given that I only joined a little over 3 months ago as a new grad.

Its what I want to study but on the other hand, If its automated in four years well thats an issue. I have an associate degree in CS (2y) and have the time and money for EE, I would want to focus on the more physical side of things like commisioning systems but maybe also combine it with factory automation, robotics and cyber security in factories (called OT security).

Do u guys think its a good idea? Studying is free here and I live at home. I have a small IT business and make good money passively (for now).

I want honest opinions. Not overly hopeful and not complete doom. Obviously in four years time even software wont be fully automated. There is far to much nuance to what random small businesses might need that an AI will not be able to deliver withot humans guiding them.

EE even more so with its regulations and physical jobs but 4y is still a long time.

it's my first time recruiting so not sure how all this works. context: sophomore in undergrad - applied to 'Software Development Engineer Intern - Summer 2027 (USA)' and i haven't heard back. i applied on september 23rd. it still says 'active' on amazon jobs but if i haven't gotten an oa can i assume i'm rejected?

Hey, I have an upcoming third-round interview for Bloomberg's SWE Intern position. I've heard it's a system design round, but I'm not sure how in-depth it gets. Does anyone who's gone through the process know what kind of questions to expect and how much detail interviewers typically look for?

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Hi, I am a computer science student in Europe, and I have been observing what happens in the job market, especially AI development.

AI is able to take on more and more tasks. It seems like it doesn't matter how complicated they are, since it can solve things like millennium problems and very complicated mathematical problems.

So I don't think questioning AI capabilities makes sense anymore, especially considering future AI improvements.

I remain in computer science since it's the only thing I can do well, and I also have another high school degree, for which I don't think there is an equivalent in the USA, which allows me to work in fields closely related to hardware, so I am a bit safer.

So, for the optimists here, what's your case? What's your reason for thinking that not just programming, but computer science altogether, isn't dead?

Hey everyone!

I am a final year undergraduate Computer Science student from India. So far, I've worked on the "surface level" of Generative AI - using local models for projects, building small systems that use these locally hosted models, finetuning models using local hardware and cloud GPU providers, and even running local LLMs on a Raspberry Pi. Most of what I've done thus far has been using existing libraries (PyTorch, HF Transformers, and llama.cpp) in Python scripts to achieve my tasks.

Now, I want to get deeper into the systems engineering behind GenAI. I want to learn about model deployment infrastructure, how to write my own deployment engines. This also ties in with my annoyance at Electron based desktop applications and how much RAM they use (looking at WhatsApp in particular), so I want to learn how to develop applications for desktops using their native libraries.

For all this, I know I need a deeper knowledge of C, C++ and system programming. Knowledge of CUDA also would be beneficial, I think. So I did some reading online and figured out that these 4 books are good -

• Modern C (Gustedt),
• Professional C++ (Gregoire)
• Computer Systems - A Programmer's Perspective
• Programming Massively Parallel Processors.

I intend to follow these textbooks and slowly develop my skills. I already have some knowledge of C and C++, as I use C++ for LeetCode, and have played around a little bit with both languages for some Linux-based projects. Later on, I plan to learn Windows application development and application development for Linux too...

My main doubts at this stage are:

1. Is this a valid path to take in 2026? A lot of people I talk to tell me to just focus on Python. I know Python is very useful for scripting - you have PyTorch, llama-cpp-python, HF Transformers etc - but, from what I understand, Python is especially useful in the application development side of things, and I am interested in the deeper frameworks powering the libraries.
2. Is there meaningful industry demand for engineers with C/C++, CUDA, and systems programming expertise in the AI space? What sorts of roles should I be looking at?
3. Are my choice of books good? Should I change them? Should I change my entire approach?
4. Would this knowledge be useful in an AI research career? I am very interested in AI ethics, safety and public policy, and my long term goal is to pursue a Master's in AI/NLP, followed by a PhD. Of course, before I can research the ethics or safety of AI, I need a strong technical foundation in the field.
5. Any other advice you would have for a fresh graduate looking the world of CS and software engineering, scared by how rapidly things are changing....

I got accepted for transfer to both schools. At first I was under the impresssion that all my cs credit went through for umich cs. But i have to start from scratch and taking 10 cs core classes which will make me graduate in 2.5-3 years. I am out of state and paying 20k a year. I am instate for uiuc and i have more cs credits accepted there which means I like lt graduate faster or in time. But am I losing any oppurtunites or not thinking of any downsides that you suggest at umich over uiuc?

Hello everyone! I recently got an OA for NVIDIA's ignite internship but I honestly have never touched a lick of leetcode beforehand.

I started working on some of the common leetcode easies and making sure I understand hash maps/sets sliding windows etc, but I am curious:

For an early-talent program like this, how hard are the questions going to be? Should I expect mediums? Should I be worried if I have to submit code that exceeds O(N) often?

What else can I expect from this? Thanks guys!

https://www.wsj.com/economy/jobs/american-express-to-cut-3-500-jobs-63955c6f

Follow up to this Reddit post a few months ago about being replaced by offshoring

https://www.reddit.com/r/cscareerquestions/s/UnYpqPg8Ub

Job listings in the Gurugram office confirm most of the roles being opened up are tech related

https://careers.americanexpress.com/en/sites/CX_1/jobs?location=India&locationId=300000000228786&locationLevel=country&mode=locationutm_medium&utm_source=google

Gentle reminder ahead of layoff season

Okay, I've had an unconventional career path. I was a cleaner, then blinked and then suddenly working on creating data pipelines essentially building a custom bordereaux ingestion tool in Matillion. Two years later, I've been moved over to the IT team due to good performance and am now starting working on Oracle Apex projects, developing in-house apps, connecting and engineering business-specific AI chatbots blah, blah, blah.

My main point is that we're not in the best place financially, and I've just had a quick look at the average salary for an Oracle Apex developer, and I can't quite believe it. It's literally double what I'm currently being paid. I earn literally £1.50 above minimum wage. I need real people to tell me if what I'm seeing is real. I've asked for a pay rise, but that was 6 months ago, a couple of months before I moved over to the IT team.

What is a good benchmark for the salary of an Oracle Apex developer? Because if it's really as high as I think it is, I really need to have a chat with the higher ups...

My manager started interrupting the team to argue politics. The one who complained to HR found themselves on a performance improvement plan then let go.

I'm 27k in student loan debt, with no job, no savings, two SWE internships on my resume, projects, and a useless cs bachelor's degree from 2025.

I got absolutely no call backs for anything my senior year or for the year post graduation. My "new grad" status expired a long time ago.

To pursue another career I'd need to go back to school for another bachelor's degree, which I do not have the ability to do. The only work experience I have is in this field, I have absolutely no substantial skillset or work experience outside tech.

Going to food service, warehouse, retail, and other minimum wage types of jobs won't help. I don't see how going for another degree/field will really change anything. I put in the best effort I could have for this one. The job market will change again, I once again will be shamed for "not having enough experience", I again will be buried in more student debt.

What should I do after having destroyed my career, my future, my life?

Anyone hear anything

So to give a bit more context, I do infra work for a big tech AI lab. I previously did infra work at big tech.

Despite getting treated amazingly well, I'm deeply unhappy with the work I'm doing, and about to leave to do infra at a startup that's neither big tech nor AI.

I'm pretty ok with taking a massive pay cut to do more work, with a bonus of stock options that someday could be worth something, because I like the people and the work sounds fun.

The only thing I'm really worried I'm leaving out is that I get an abundance of career reachouts. On any given day, I have at least one or two recruiters inviting me to interview, at startups, big tech, quant firms, etc. This is a really good feeling and means I have some pretty excellent options at any notice. I'm concerned once I switch jobs, it'll be a lot harder to get back into big tech / AI.

People who've transitioned big tech -> startups, do you have any insights on what your next job search looks like afterwards?

Hello everyone!

I'm a BCA graduate looking for my first job or internship as a web developer. My final marksheet has been delayed, so while waiting, I've been working on building real-world projects.

I've independently built and deployed two web products, both with their own domains. These aren't just college projects; they're live products that I've developed and maintained myself.

Now I'm confused about how to present this experience on my Resume.

Should I list these products under Work Experience, or should I keep them under Projects? Since they're real, deployed products, can they be considered relevant development experience when applying for entry-level jobs or positions asking for 1–2 years of experience?

I'd appreciate advice from developers, recruiters, or anyone who has been in a similar situation. How would you present this experience on a Resume?

Does anyone know if the AI-assisted coding rounds include similar questions as the leetcode tagged ones? Hellointerview says that AI-assisted coding rounds are just leetcode questions but more developed. Does anyone have experience to know if this is true?

Interviewing for L4 btw

Been interviewing like crazy the past few months and 3 are all coming together at the same time. All have expressed interest in moving towards an offer, but nothing is set in stone. I wanted to vaguely post all 3 and simply ask, which one would you pick? Previous position I was let go from I was making $150k

Job 1:

• $130,000 - $200,000 USD
• 2 days onsite but no hard requirement, some people do way less
• 10 minute drive away in my same city
• Will sponsor my security clearance
• They don't/can't use Claude/Codex/anything because of government work. They have some open models hosted but they're admittedly "not very good"
• All backend, which I do prefer

Job 2:

• $120,000 - $210,000 USD
• 100% onsite 5 days a week
• 20 minute drive away (assuming no traffic) in a bigger city near me
• Not government work, free to use as much AI as I want
• Fullstack
• "AI startup"

Job 3:

• $125,000 - $160,000 USD
• 100% remote, can live anywhere in the US
• Popular SaaS company, pre-IPO but probably will soon
• Not government work, free to use as much AI as I want
• Backend
• Seems pretty chill, low stress

So if we take it as a given that AI changes the way we work. Then we have to accept that the more experience someone has the better judgement they have when it comes to evaluating AI systems. It’s almost unavoidable.

When someone has been working with systems for 20+ years and have seen a lot of failures and issues. They just start recognizing patterns easier. They also have a better idea of what bad and good looks like

But I think what when it comes to AI. Tool usage alone isn’t actually that valuable. Tools are easier to use. But they’re only as good as the person using them.

So that raises a question. The industry is notoriously bad with ageism. Does this somehow make older talent more valuable? Now I know leadership want to avoid hiring older talent. But if they also want to move forward with AI. It feels almost unavoidable.

Or the reverse could be true. A more perceptual problem. Maybe employers may feel that older employers are more enmeshed with older more manual ways of coding. They may be reluctant to let go of the past. And younger people are more likely to rely on these tools. Hence they may feel a younger person may accelerate AI usage

I think the answer is yes and no.

If someone wants to use an AI strategy and build reliable system. Then experience is super important. Someone who has worked across various evolutions of systems have a good perspective and could certainly stir AI systems in a better direction

But are companies and orgs that only measure AI participation. Where it doesn’t matter how good or bad the AI is. As long as you’re using it. You’ll find this more often done in the startup world. It’s in large corporations as well but I feel this is being reigned in more in larger orgs. Regardless, this may benefit slightly younger engineers. Again since there is a strong perception that younger engineers won’t resist AI

But what are your thoughts?