> It's been a huge learning curve.
I have been doing this professionally for over twenty years, and I still learn something every day. Over the past couple years, with AI augmentation, I learn even more, move faster and go deeper into the systems that I work on.
A CS degree was never going to provide you with all of the tools that you need for a successful career. It provided you with the basics to get your foot in the door.
AI is not replacing you or an education. AI is raising the bar of what you can comprehend and retain. From someone who is technically minded (and self-taught), all I have ever wanted is to keep learning.
I’m hearing this more and more from both students and teachers. It seems like everyone in education is frustrated and can’t figure out how to use AI for education productively yet.
TBH I’m also thinking about how to use AI at work for learning. (My work environment is 100% all-in on AI.) Everyone can see and admit that AI coding is making us lazier and that it produces too much code to do old-style line by line reviews. Some people are using agent teams to churn out millions of lines of code where there’s zero hope of reviewing it. We don’t yet know how to keep quality high and complexity low while doing agent coding, we’re just having them write lots of tests and hoping that when things break they’re easy to fix. Agents should get better at broad architecture in the future, but they’re definitely not there yet.
> The amount of work involved has also tripled
This has to be one of the big ironies of using AI. I’ve heard this from other students too. The problem is that old-style assignments where the level of difficulty was hand-crafted is way way too easy for an LLM, therefore teachers need to crank the level of difficulty so the student has to actually spend some time on the assignment. But LLMs are getting better every month and the difficulty is so high that no students can possibly do the assignment by hand and now small errors in assignment design can lead to large errors in effort and time required.
I think it's worth asking what a CS degree is for. Is it
to teach you how to code and make you obviously hire-able
by industry? Maybe it's to teach you how to think about
data and code? If you think it's the former, then AI is
probably going to be a problem for you. If the latter,
it's neutral to somewhat good.
I've been hiring CS grads for 4 decades (yikes!) and
there's definitely been a shift. Not all existing
programs are bad. Not all young software devs are bad.
But... the percentage of recent grads that seem to
understand what data processing systems are about has
definitely fallen.
Us old farts in industry must share some of the blame
here. Our industry seems to be pretty boom or bust.
Someone comes in with a stack of money and tells people to
build { the web | blockchain | AI | virtual worlds | etc }
and suddenly there's a rush. At the start of the gold
rush, we're not sure how to build everything that's going
to be the next google [[1]] so we fill the room with young
kids who have seen some recent tooling and will work
cheap. We don't develop them. We want them to be
compliant drones dancing to a tune played by a CTO and
VP/Eng who got their jobs because they're the children of
the fund investors who gave the startup a bunch of money.
And then we go back to Universities and tell them "OMG!
Your not bar-raising your grads by teaching them __fill in
the blank__!" [[2]]
So... I don't doubt it looks like AI is destroying the
degree. But maybe it's just making it hard to ignore
previous problems with the uni to industry pipeline.
And I didn't mention the Mythical Man Month once in this
comment. I'm getting better.
1. I'm not sure too many people want to be Google at the
moment, but over the last 25 years, they've certainly
done well.
2. I'm intentionally misspelling "you're" because in my
time in industry, I've found only about 15% of people
would pass a 7th grade spelling test.This sounds awful, but the culprit is the terrible faculty at this institution:
> Whereas before, assignments were designed by a person who thought them through at least once, then approved by other people in the department, now I doubt they're getting read more than once (if that). Errors abound, often with corrections coming a week or two before the deadline.
This is entirely unacceptable. Professors who are using AI to generate assignments and course loads need to be discipline and removed if they can’t start doing their job.
From the title I thought I was going to be reading an article wondering how AI would devalue a CS degree, but this is actually a story about a CS program falling apart because the instructors are flailing about without AI.
While AI is writing much much more of my code these days, I still need to be able to speak intelligently about what I am building, why I chose a given design and the tradeoffs between alternatives. When fixing things, it's still important to understand what broke and why. I don't think that will ever change in any organization that operates in high compliance environments or cares about delivering high quality products.
I don't think programming becoming 'easier' has make understanding programs any easier or less important. Even if all of the above goes away, I think computer science has taught me a lot about how to think about problems.
Answers so far are assuming that this is complaining that their traditional CS course is not that useful for getting a job anymore.
That’s not what it’s about. It’s actually from someone who genuinely wants to learn for the sake of learning who’s talking about how AI is creating havoc in her studies.
Being able to write a coherent critique that stays practical and doesn't stray into bombastic moralisation or interpersonal frustration is a rare skill that speaks well to your communication skill and taste. I think you will do just fine in a world of AI in engineering.
I used to have a lot of anxiety about Ai wiping out all the Software specific jobs, software development/testing/project management, etc. I actually do think that's still likely to be the case going forward. Pick an industry and try and become an expert in it. Someone will still have to prompt and dream up new features. There are still things that you can't prompt your way to, but they're on the relationship side, not the technical side. I'm not sure what I would say to someone currently doing a CS degree, Math degree, Physics degree, or wanting to do one. Most likely I would say if you want to have a stable income, get good at sales.
Hey.
First off, congrats on spending time doing side projects in OpenProcessing. Keep working on projects that keep you motivated and keep you learning.
We've been there, lost in our learning paths. Even before AI there were times when we were overwhelmed with our CS journey. You'll overcome, don't you worry about that.
The CS degree was never the end of the learning journey. It was always _what you put into it_. You'll learn what you practice, and uni just happens to be a good place to practice things. Whether that's optimizing AI harnesses, understanding how CPU caches work, crunching pixels on a GPU or the principles of distributed computing... it will all make you a better thinker and good at what you do one day.
Stay curious.
Why are more people (bots?) using bearblog. The landing page claims it's fast and privacy focused, but it offers so little... I could recreate it myself in a day so why aren't people running their own blogs, especially in CS where you could learn something doing it.
I'm also now reminded that this is ran by that same guy who complained about the MIT license allowing people to do whatever they wish.
I decided to finally get a CS degree at juuuust the right time (well, for my personal reasons of "love of the game" at least - individual interests may vary), having wrapped up ~2 years ago.
It was interesting to see things change towards the end. Some was the chaos from the lack of consistency the article highlights just starting to emerge. Mostly though, it was just the rampant surge in cheating and the classes not being prepared for it.
The double standard of "YES WE'RE USING AI BUT THAT DOESN'T MEAN YOU SHOULD!" needs to be called out much more. It isn't some forbidden fruit.
It's not a double standard. It's the same standard applied to different things.
The best way we know of to learn something with AI is to do the work yourself, then watch AI blow you out of the water on the same task, learn its tricks and do the work again (better, even, since AI isn't that great at it yet)
Which means the teacher can use AI, and you can't.
This is also an entirely different subject to whether you should be learning that specific task in the first place or delegate it to AI.
Since you are (likely) young - here's a tip when writing such articles:
Provide examples.
It's hard for readers to gauge whether you're complaints are legitimate or overreactions.
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I never fully grasped when others would say that religion is meant to bring structure to peoples lives. As a world with AI starts to unfold I finally understand what they meant. Humans are incapable of functioning normally let alone progressing in theirs lives without rigid structure.
I do agree with this perspective ... But I do understand the anxiety tho.
The advice I give you is the same I'm trying to believe in myself: just chill dude... AI isn't human and while can't be one, you are "safe"... We are still figuring it out while it happen to find another way to "feel valuable" after code-writing is no longer the source of our self-value.
Ok, you definitely didn't read the post.
Did you even open the article? It’s not what you think it is.
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Basically true for all degrees. I studied non-cs engineering before getting into coding and feel it often. At times have felt “should have stuck more with mech e where jobs are more stable and the tech moves slower” but know it’s kind of a fallacy.
Other than keeping up to date with how to best use AI/harnesses what else would be most important to stay on top of for retaining a software engineering job these days? Also AI seems generic to me. Could I bother you for a more detailed breakdown on the most important topics/skills you would consider necessary for a software engineer to be knowledgeable of?
I don't think they're complaining about the learning curve.
Didn't say that to refute it. I chose that to make the point that the degree is not the destination.
Iff your goal is using a degree as a stepping stone, which seems less and less popular these days.
For some, the degree is the destination and that's more than fine as well. It's a marker that says "others agree I learned x to a certain level, and I had fun doing it". This tends to overlap well with those who just liked it as an extra method of learning.