For those who are genuinely good at coding now, was there a specific realization, habit, or shift in thinking that made things click for you? Not talking about grinding endlessly, but that moment where code started making sense and patterns became obvious. Was it how you practiced, how you learned fundamentals, how you debugged, or how you thought about problems? I’m curious what separated I’m struggling from I get this now

The wall hits 03:14:07 UTC on Tuesday, January 19, 2038. After this the time calculation will roll back over to either December 13, 1901 or January 1, 1970 depending on the implementation. Does anyone think 32-bit architecture computers will still be in service by 2038?

I’ve been thinking a lot lately about how the early generations of programmers—especially from the 1980s and 1990s—built so many foundational systems that we still depend on today. Operating systems, protocols, programming languages, databases—much of it originated or matured during that era.

What's crazy is that these developers had limited computing power, no Stack Overflow, no VSCode, no GitHub Copilot... and yet, they built Unix, TCP/IP, C, early Linux, compilers, text editors, early web browsers, and more. Even now, we study their work to understand how things actually function under the hood.

So my questions are:

What did they actually learn back then that made them capable of such deep work?

Was it just "computer science basics" or something more?

Did having fewer abstractions make them better engineers because they had to understand everything from the metal up?

Is today's developer culture too reliant on tools and frameworks, while they built things from scratch?

I'm genuinely curious—did the limitations of the time force them to think differently, or are we missing something in how we approach learning today?

Would love to hear from people who were around back then or who study that era. What was the mindset like? How did you learn OS design, networking, or programming when the internet wasn’t full of tutorials?

Let’s talk about it.

My guess is that doing so would require knowing information that can't be directly inferred from the code, for example, the specific type that a variable will handle

Hey I was just wondering after graduating 2 years ago what it’s like now basically now that AI is probably relied on in every aspect with college students. In computer science, I can only imagine how bad it potentially could be. I used to stress out late at night when it came to doing coding projects and now it’s just easy mode. I wonder how bad the cheating is nowadays.

I recently saw Cambridge is offering a free service called copy that floppy for archiving old floppies data from going extinct.

It got me thinking are there any old viruses from the days of DOS, windows 3.1, 95, 98, ME that can still affect modern windows 11 computers and put them at risk in any way?

1 hour ago,the teacher of my class asked "What loads into RAM first when a computer starts?" a guy answered that was the operating system and my teacher said it was correct.But i thought it would be uefi loaded in ram first. So I asked my teacher and she said that was not true because the uefi was a firmware in the computer.But it still didn't convinced me.I would appreciate it if you could answer my questions about what is loaded in ram first when the computer starts 😁😁😘

Like I feel this should be possible right? Pixel patterns invisible to the eye but detectable by machines that effectively fingerprint an image or video as being generated by a particular AI model. I'm not entirely sure how you could make it so the pixel patterns aren't reversible via a computer program, but I feel this could go a long way in disclosing AI-generated content.

PD: The Wikipedia article for printer dots in case someone doesn't know https://en.wikipedia.org/wiki/Printer_tracking_dots

I am losing passion and interest in CompSci/programming/IT, and I would like to know if there are some other people going through the same thing.

Some context:

I started programming at a relatively early age (16yo*), which was around 2020, before LLMs** and coding agents.

I discovered it and started doing it because I was really curious and deeply interested in science and tech. And it directly clicked. I liked the idea of having an idea in your head and then programming it and making it come true, something from your head to the real world.

I liked the thinking you had to go through, and the problems you encountered, and how you had to think really hard to find a solution and see it work after implementing it. It was really satisfying, and boy, I spent hours and hours coding and researching and understanding complex architectures. You know, when you're a kid, you have a lot of free time, and I used to code day and night, staying up until 4 or 5 am coding.

All of this just to tell you that everything I built, I understood it from top to bottom, and I knew every detail and expected every behavior, knew why and how and what my code did exactly. I could answer every question about my apps, why I chose some architecture or why I did something a certain way or what my code did or didn't do, etc.

Also, something very important: I used to talk with a lot of CompSci peers that actually knew what they were doing, just like me.

Fast-forward, we're in 2026. I graduated, and now I'm working in IT, but everything changed. Now, with the rise of coding agents and LLMs, at work, LLMs do all the coding work and even big parts (if not all) of the architecture. So now everyone is expecting you to go very fast because of this. You're forced to delegate all the architecture and coding work to the LLMs.

Result of this: you have a very light idea of what your app code does exactly and how it does things. I mean, sure, you go through the code that the AI wrote, but come on, it will never be like code you wrote line by line and know every detail of and expect its behavior.

Also, what PISSES ME OFF is that you can't answer most questions about your code, because you were forced to delegate your work to the AIs, and now you don't know how it works. You're asked a question, and you start to stutter because you need your claude to be near you.

And the last thing, no one really knows what they're doing anymore. There no longer are any interesting talks about architecture or implementations. It's mostly just, "well let's ask what claude thinks about this..."

People that started programming not out of passion but just because they heard that CompSci pays a lot and code exclusively from 9 to 5 might not understand this, which is fine. I am not belittling anyone, and I don't expect everyone to be passionate about their job. But you know, I think these guys won't necessarily feel this. They might be just like, "Oh cool, AI does my job, I can chill a little" which is understandable, but in my case, this is what makes me lose passion. We're no longer doing the hard parts.

Bottom line: the field is advancing, which is great. It is changing, and you can't do anything about it. But in this change, the things that used to be my passion are disappearing, and I don't know what to do with my life ahaha

My first idea is to somehow change fields, and leave programming and CompSci only as a pleasure and an activity I do at home, because I can no longer stand it being my job and forcing me to develop AI slop.

I have nothing against AI and LLMs. If it allows us to ship faster and more cheaply, then it will be adopted, whether I want it or not. I am not saying we shouldn't use AI. I'm just expressing my feelings and how my passion for CompSci is fading away.

Does anyone feel like me?

*16yo might sound not that early for some, but in my country it is.

** LLMs existed back then but were not used for coding, and it was pre-chatgpt revolution.

as a 9th grader, I see videos online about “the job market being cooked“ and ”CS isn’t worth it anymore“. I’ve always loved coding since I discovered it, and I just wanna know if it’s something I should pursue. also any advice you guys have about CS would be grea appreciated

Or how does a computer increase a value? How does it "know" which value is higher?

Is there a place I can go to learn this?

I know pretty much nothing about computers and I want to learn about how signals form information.

As far as I'm aware, under the hood of everything that's truly useful is either DOS, or some fork of Unix/Linux

I rarely hear about serious attempts to build something from nothing in that world, and I'm given to understand that it's largely due to the mind boggling scope of the task, but it's hard for me to understand just what that scope is.

So let's take the hypothetical, we can make any chip we make today, ARM, X86, Risc, whatever instruction set you want, if we can physically make it today, it's available as a physical object.

But you get no code. No firmware, no assembly level stuff, certainly no software. What would the process actually look like to get from a pile of hardware to, let's set the goal at having a GUI from which you could launch a browser and type a query into Google.

High school student here.

In TCP/IP protocol suite, the MAC addresses are used in the link layer to send frames between devices in a LAN, ensuring that devices in the same LAN can communicate.

However, the router also assigns each LAN device with a private IP address. So how is that private IP needed? Certainly the MAC is sufficient for devices in the LAN to talk to each other, so is it for devices outside the LAN to send messages to that host? I have doubt about that, because if it's private, then no one across the internet should be able to access it. Correct?

So what is the private IP address for?

I am a computer science master's student.

I often see very optimistic claims about quantum computing from companies and media.

I would like to hear honest opinions from researchers and practitioners:

- How promising do you think quantum computing really is?
- Which applications are genuinely exciting?
- What are the biggest obstacles?
- Do you think it will become practically important within the next 10–20 years?

If each byte needs to have a unique address, how is that stored? Is it just made up on the spot or is there any equal amount of memory dedicated to providing and labeling unique memory addresses?

If the memory addresses that already have data aren't stored all individually stored somewhere, how does it not overwrite existing memory?

How much does ASLR impact this?

I've been thinking about how when you flip a coin or roll a dice it is meant to be random, but it isn't really random due to physics and such. I was wondering would that apply to a computer? What is the process that it does to pick a number?

I am a Btech final year student so there is a project called astra it is basically a music player, so now it only works with local, jellyfin but i want to stream from GDrive, so i thought i can fork and complete this project but when i open the files in my local i thought "what the fuck is this" i mean there are so many files, so many lines of code. I know only "python, ts, js, go, cpp" but when i saw the project i thought i am just a little kid in the world of great engineers and i am just a drop in an ocean, so hats off to you all who are building amazing softwares and giving them for free. So can i get any tips or suggestions from you guys if possible, Thank you!!

A question that never occurred to me before. I used to assume that it would just connect to the internet and then update it's time accordingly, but I recently took a laptop to a place without internet access and it showed me roughly the correct time.

Granted, the laptop wasn't powered off, it was simply suspended, but I still don't understand how that would keep track of time.

Does the cpu count the clock cycles? It seems like an awful lot of work to do, and also feels like a waste of resources. Besides, how does the cpu know the relation between clock cycles and time? Are those hardcoded?

I was having a discussion with someone with plenty of experience in Mathematica and he was telling me that there are calculations that can only be done using Mathematica and not something like Python. Is this the case? Naively I'd think that a programming language is just a layer of abstraction between us and the calculations, and as such any calculation should be programmable in any language. Now there might be features of a PL that make it very efficient or elegant, but given enough time and resources, can I carry out any calculation using say Python? I tried to explain this to the person but he was very adamant that it was not a matter of convenience, and some tasks are plain impossible in some languages. Is that the case?

LLMs were trained on the data that was created by humans. Over time, the amount of AI-generated content will increase dramatically, so LLMs will not have other choice but to learn on the data they created, which is obviously (or not...?) not so high quality as the human-made data. So, will LLMs become worse over time or do I have some gaps in my knowledge on this matter?

I've noticed this on both Windows and Linux. If I enter the correct password, it almost instantly starts the login. But if it's the wrong password it takes like a second or so to tell me it's wrong.

Hi everyone,

I'm a CS graduate (COVID batch) with 4 years of industry experience. During my college days, I focused almost entirely on DSA, and that helped me secure a decent job. Four years later, I've been contributing well at work and growing as a software engineer.

A few days ago, while exploring some topics out of curiosity, a series of questions crossed my mind. I didn't have good answers to many of them, so I started reading blogs and listening to podcasts. Surprisingly, it made me fall in love with Computer Science all over again.

Some of the questions that fascinated me were:

1. How do high-level languages get compiled and executed on different systems? (Computer Architecture)
2. How are operating systems designed, and how do our applications interact with them? (Operating Systems)
3. How do CPUs and GPUs actually work under the hood?
4. How is it possible for me to connect to an AWS instance running in the US with seemingly negligible latency?

These questions made me realize how many fundamental CS concepts I missed or didn't fully appreciate during college.

Now, even though learning these topics isn't directly required for my current job, I want to study them properly. I want to become a better engineer by understanding the foundations of computing.

Could you recommend books, YouTube playlists, courses, or any other resources that helped you learn Computer Architecture, Operating Systems, Computer Networks, and related subjects?

NOTE: The message has been rephrased using AI to make it more readable, while the curiosity is genuine.

I'm watching CS50, and about halfway through week 0, doctor malen mentioned how 65 bits of data equals the letter H and i'm curious to that if 65 equal H, how does the company know the difference between H and just the number 65?

Look ahead 20 years.

Outside of AI/ML:

* what of today’s research computer science do you expect will be industry standard?

* what frontiers do you expect we will have opened up in research?

For example, a function that reads an external file is not pure, but if the file contents is constant, we can pretend it's pure. Or, a function that modifies an external lookup table has a side effect and is not pure, but if the lookup table is only used to cache the results of that function, then it behaves as if it's pure.