Gen Z has a very doomeristic view towards CS careers now due to social media influencers prematurely dismissing CS/software paths as a dead end or impossible to break into because of AI.
I know the job market can suck for graduates right now, but I do believe studying CS can still lead to decent paying careers. There's always going to be demand for people who understand code, who can break down complex problems and bring a problem solving mindset. LLMs don't solve everything.
The drop in CS students ironically may create a vacuum that allows us employed engineers to demand even higher compensation.
I feel like CS is just correcting back to what it was.
Even back when I was in college (graduated 2017), I noticed there was this clear bifurcation among the students. Alot of the students at that time did it because you could score a great job after college but the smaller cohort were the students that just loved the game. And even back then we had loads of students wash out or graduate then take other jobs after college from the former group.
It's no different today except that the group that did it for money are washing out before they even get to college because they fear that AI will take their jobs, meanwhile the latter group is still here and were able to do more and more with AI.
It's a truly wild time to be alive in this industry. Half of us are seeing the doom and gloom of AI and the other half are seeing the "next age" happen right before our eyes.
And I'll be honest I kinda feel sad for the folks that take the negative view of AI right now. Cause I'm having more fun than I've ever had before in this industry.
It's kind of always been a wild time to be alive in this industry.
You covered people washing out of CS degrees and people getting degrees and then not, ultimately, doing something in the CS field.
But what you see in our field that you don't see as often, elsewhere (or -- at all, depending on regulations) is people who ... (1) washed out of the degree because it was competing with their lucrative career as a software developer (or -- more rarely, successful entrepreneur), (2) got a degree in textual biblical studies and had a long career in software development[0] or, you know, other unrelated degree, (3) none of the above, even sometimes incomplete High School education (also[0]).
I've been hiring developers for almost 30 years, now, at a variety of employers -- one global multi-national telecom, one "we make a lot of the products other companies pass off as their own work" IoT/small shop, and a couple of video conference/remote-enabling service shops. There are far more degrees out there, today, than there were 30 years ago. My experience, however, is that the necessity of a degree at the companies I've been employed at has gone down. I suspect that's because I worked for "the giant multinational", first, and all of the rest have been startup or smaller/younger shops (typically 5-10 devs, but no more than ~20 at peek). The giant multi-national, though, during my 17 years, changed (early on) to "or equivalent experience" while rarely hiring someone without a degree for most IT positions to routinely interviewing and hiring people without regard for their degree (and focusing on "code you've written" over "whiteboard exercises", too) while still generally favoring candidates with them. At the best shop I've worked for, it was an even mix of "none", "some", "unrelated", "+bootcamp", "CS degrees" and filled with extremely competent, well-paid, developers.
It's a whole lot harder to get the experience required to have "equivalent experience" without university/internships/the like, but getting the degree without any relevant work experience along the way isn't a good way to go, either.
Around the late 90s (until the bust) and then again a few years later, everyone was pushing kids into CS degrees and the most "interesting" aspect to many of those kids was the starting/long-term earnings against the cost of the 4-year degree. And while, personally, I think "anyone can do it", not "everyone will find it enjoyable to do" like I do.
I'm starting to believe that last part is far more rare than I think it is with my 18-year-old son mostly disliking his introductory computer programming class in High School[1]. I don't push "what I do" on them, just like my Dad didn't, but I expose them to it whenever I can (like my Dad -- kind of -- didn't). And I'll never forget when their Mom looked over at my screen and said "So ... is that what you do all day?", and I beamed "Yes" because it really is the most interesting thing in the world to me, and she said "Wow ... I think I'd kill myself."
[0] Ok, so that's a specific example of someone I know.
[1] Ultimately coming around at the end when his assignment was "make something you want to make."
can you elaborate on your thesis as to why? it seems to me, with raw code being less of a bottleneck, things like understanding the spec, polishing, and doing the fuzzy work around the edges become all the more important. These were never strengths of outsourcing. In fact, I think that the fact that those parts are important is a big reason why the profession as a whole wasnt entirely just outsourced, despite the compelling economic reasons for it.
Isn't it the other way around, AI replacing outsourcing? AI can do the implementation work, but you still need the human who needs to specify what has to be done, give architecture guidance and check and accept the resulting work (or reject it, with notes on what to fix). AI coding is basically outsourcing to AI
This is the paradox. But because AI makes outsourcing jobs easier, those workers need to compete, and so they will be able to do those specification jobs and quality control jobs as well.
The paradox is that the quality of AI output is directly proportional to your expertise and understanding, while the trust/belief/confidence in their effectiveness is inversely proportional.
It will still pay to develop the core understanding. It is just that the world can remain irrational longer than you can remain solvent :).
I was rich even before I came into this field, my family owns lots of agriculture land and I came to this field for passion of it and was never really motivated by money.
Thing is AI is taking outsourced jobs in india at much faster rate than elsewhere.
The latest layoff coming from Oracle mostly laid off workers in india.
It's not doomerism. I've seen this happen at companies.
I was talking to a guy who wanted uptime monitoring. So, he told the executive who called the uptimerobot but then other guy rolled out his uptime robot using AI in 60 minutes and deployed along with centralized logging and it costs the company only $5 VPS.
And honestly it works just as good, I've seen companies are refusing to pay for external tools and building leaner version using AI.
You can build a SaaS faster now but the need for SaaS is on decline.
I've moved to deploying on bare metal from OVH and Hertzner, why? Because devops is completely reduced to few minutes worth of work using agents.
You don't need AI for that. Just deploy Uptime Kuma or similar to a VPS and job done. I can do that in about 15 min vs. your 60 min.
Of course, this is not a production-grade deployment. To get there, I'd need to build images on pipelines, scan them, test them, publish artefacts, write up the IaC to manage the cloud resources, add monitoring around the solution, ...
Deploying a simple piece of software on a custom server was never difficult or slow to do.
Isn't it too early to declare the vibe coded uptime monitoring as "good" from a business standpoint? NIH syndrome has always been a thing and I don't see how the downsides of creating bespoke systems have changed in the LLM-era. You're now stuck maintaining this "genius" solution, LLMs or not, and onboarding devs/users gets harder the more churn you have.
Okay, so AI probably wasn't critical to crafting a 100 lines of what I'm assuming is python or some other scripting language that pings a url. Second, I don't think 100 lines is going to be as robust as some pre-packaged monitoring solution (open source or enterprise tier) which has a dashboard and auth story baked in along with proper documentation.
If that script works for your use case then great, but I don't see how LLMs were a game changer here.
Big companies would have rolled out their own anyway, but now 2-3 person companies are also not paying for tools like uptime robots. That's the development LLM brought
> So, he told the executive who called the uptimerobot but then other guy rolled out his uptime robot using AI in 60 minutes and deployed along with centralized logging and it costs the company only $5 VPS.
i'm a sysadmin, so i usually watch these things from the side and usually i get called one or two months in to clean up the mess (it happens almost every time).
what you have described is funny to me because uptime monitoring for websites (and also other stuff) is pretty much the use case for prometheus' black-box exporter (https://github.com/prometheus/blackbox_exporter).
assuming you work at a decent company and already have a decent monitoring system (prometheus/alertmanager) it takes 5 minutes to deploy and maybe ten to configure.
if you already have infrastructure then it's basically free. if you already have a kubernetes cluster then it's practically already managed.
> I've moved to deploying on bare metal from OVH and Hertzner, why? Because devops is completely reduced to few minutes worth of work using agents.
at a small scale... maybe. in my experience as soon as you start to reach a decent scale, you'll need experienced engineers (software engineers, system engineers) to actually be at the steering wheel.
Some things are better when they are outsourced because other companies specialized for that problem set. Just like you won't roll your own cryptography, you won't and can't do everything in-house.
For 5 minutes. The need for cheap SaaS that one person can build and has no uptime requirements or security requirements or legal requirements or ongoing maintenance requirements is indeed declining.
Eh, this said I think SaaS offering had gotten overpriced. Coupled with things like they put up stickers that say "We R havin S3curity" rather than actually having secure systems, oh and constant price increases and methods of locking you into their services there was a need for some pushback in the market.
I've been in CS professionally for 12 years. This a perfect example of normal distribution at work. By increasing the population, you simply increase the number of people across the entire curve, bumping up the number of high, medium, low paid, as well as unemployed folks with the degrees. The real issue has always been greed - people disproportionately dove into CS because like all hype movements it promised significant income after just 2-4 years, and sometimes not even that, but a month long bootcamp. Once it was sold to the masses as a get rich quick scheme - the disappointment paired with a number of low-achieving grads tripling was unavoidable.
It definitely was oversold, but I don't think it's right to fault people for picking CS because of the money. That is essentially the point of getting a job, and most people do not actually get to live their "passion" -- even those of us who DO truly have a passion for programming. Most careers are only as good as the jobs you get, and most jobs are not amazing. If I have to do something I'm not crazy about, we're talking about degrees of misery and cost/benefit ratios, and that is very personal.
The same thing happened in dentistry, law, EE, some medical specialties, vets. Job path gets seen as a golden ticket to high pay for low to medium effort and people pile into the profession and saturate the market. Then some thing happens, a recession, technological innovation, or geopolitical/geo-economic shift, and the demand changes dramatically. These things work in cycles, happened before in the .com bust, and this will take 5-10 years to work its way out. The good news is that for the new grads who manage to hang on they will make a killing as the demand for mids and seniors will be insane due to the lack of qualified candidates available.
Yes? Insofar as a career path. You go to a good school, get a good degree and be almost guaranteed a good pay with known career progression. It's not like entrepreneurship, where you can't see the path ahead of you. Think video games, much easier to play when the goals are given to you than to make your own.
You just described a bunch of hard and continuous work, and oversell the "almost guaranteed" part. Nothing is guaranteed in life, except death and taxes. Entrepreneurship can be harder or easier than working for someone else. Some entrepreneurs just show up with a bunch of money and hire other people to do the bulk of the work. That's a different kind of stress.
I won't undersell the efforts professionals need to acquire their skills, but I also stand by my view that a clearly defined progression makes life a lot easier to navigate. It's why quests are fundamental in RPGs and uncertainty is bad for business. When you can see the path ahead, the problems that need to be solved are clear. It's why research is so painstakingly slow when we are treading on unknown unknowns.
As for those who showed up and everything worked out, consider them lucky, though I doubt there are many of them out there.
Software engineering is not necessarily shallow in any sense. Reasoning about large and imperfect systems can be so much harder than finding average publishable CS results. But the difficulties are often so particular to the software and situations that it isn't of interest to academics.
> Software engineering is not necessarily shallow in any sense.
I should have been clearer in my writing. What i meant to say is that the math involved in pure software engineering is much more shallow than the math involved in pure computer science.
> Reasoning about large and imperfect systems can be so much harder than finding average publishable CS results.
Ah so you are an academic. I have been in both places. Industry people have to not only think of ideas but implement them with real computers. In some cases the computers must be built specifically to solve the problems. Millions of lines of code, broken shit, backward compatibility, stuff that can only be found through years of use. I suppose one can try to make an academic problem out of any industry concern, and therefore appear to be "more sophisticated" but inferior, partial, and broken proposals are regularly published. To get published, even a sketch of a possible solution with no implementation often flies. In industry, a lot of inferior stuff is accepted out of necessity, but it's often do or die with deadlines and real budgets to be concerned about.
Our government failed the citizens and let outsourcing and wage suppression destroy the US tech industry...positioning the country far behind other countries in technology supremacy for at least a decade to come
You don’t have a god given right as an American to a mid-high six figure income working in tech and I’m not sure how you can see Anthropic playing whack-a-mole trying to keep the Chinese from distilling their models and say that the US isn’t still on the inside track with this stuff.
Corporations don’t have a God-given right to manipulate the market by outsourcing the work to the detriment of the natives, yet they make good use of it!
Also, why do you hate the poor so much? Do people not deserve well paying jobs because the vagina they came out of wasn’t located on the correct patch of dirt?
And yet, CS was the fastest growing employment category with some of the highest and among the fastest growing salaries in the nation for the past 2 decades despite the fact that outsourcing has been around since the 90s.
The fact that this changed in the last 2 years right when AI became feasible is just a coincidence. It’s actually finally outsourcing destroying the grad job market nearly 3 decades later.
Nothing changed in the past 2 years except we had another recession. Just like very other recession, people are looking for something to blame. Out sourcing has long been a popular thing to blame. This time blaming AI is the fad. There will be more recessions in the future and people will blame some other fad next time (or perhaps the same). In the end though it is the economy.
There was a golden age (2010-2020 or so?) when a CS degree of as basically an easy ticket to the upper middle class. Unlike similar well-paying jobs like law or medicine, a bachelor's degree was enough. Now it's not easy to get a job as a new grad, so there are fewer people getting into the discipline whose primary reason to study it was money.
CS started as a major for "computer nerds" who were very into computers. Computers were a hobby for virtually every one of my CS classmates in the 90's. Studying computer science was an extension of that interest, so majoring in CS made sense.
Fast forward a decade or two, and it is like you said, people who don't have a strong interest in computers starting taking CS as a major as a path to jobs and income.
Now, as a manager of engineering teams, I'm constantly surprised by Software Engineers that don't even own their own computers and/or have very little knowledge about how they work.
There have always been ups and downs in the economy. This isn't the first recession where programmers were hit harder than other jobs. There have been other recessions where programmers were one of the few places where everyone was hiring.
You can substitute every single possible profession for programmers above and still have a trust. Even things like groceries (everyone needs to eat) still has ups and downs (some recessions people go to restaurants less and so are good; others they switch to low margin staples and profits go down).
CS was viewed as a golden ticket at least as far back as 2000. Even then, there were people doing the degree who had no interest in the subject, but thought it would get them a good salary.
Seemed to really accelerate around 2007-2008 when Facebook became massive and turned a bunch of kids into billionaires overnight. After that it sort of turned into a gold rush, and we were the shovels.
I was just at the largest career / college expo for high schoolers in the greater NYC area yesterday. It’s anecdotal but the two most asked about majors at the fair were #1 mechanical engineering and #2 computer science. I gave away all the materials we had and I had left thinking “this will be plenty”.
So let’s just wait a bit before we say it hit a wall.
I don't personally have an opinion yet on what is the correct way to do things, I can only talk from my own personal experience within Academia in the UK as both a student and teacher with Computer Science.
The prime example is that most software roles in the economy are (or where, perhaps AI will change this, I do not know) simple web-dev/CRUD/SQL roles. Specifically Python/JS was a high-demand skill. This pushed universities to get rid of lower level courses such as concurrency/computer architecture, C/C++/assembly, or more maths based modules such as logic, in favour of more web-dev/software/AI/data-science modules.
One could (and I do) argue that this is effectively turning computer science degrees into more of a software engineering degrees piece by piece, thus turning univerisities into vocational schools.
Now here lies the question. Is this correct? Should universities be vocational schools? Or should they be seperate? Personally my feeling is that universities are not set up well for this method of teaching, and it would be much better for everyone involved if the students were instead taught through apprenticeship or vocational schools, which tend to be significantly cheaper (or even pay) for the student, whilst making sure that the university degree can stay focused within academia and funneling a good research pipeline.
Instead my view is that politicans have pushed many young adults into expensive degree programs that they did not need, with the false promise that it would give them emplolyement (which was never the goal of a university in the first place). This isn't good for the students (who are saddled with debt), the employers (who end up having to train the juniors anyway) or the economy (which now has less money in it due to the large drain on disposable income from student loan repayments).
Xennial here! Graduated after Y2K, 9-11, and the dot bomb era. A lot of us lost 3-4 years of early career advancement due to layoffs that primarily affected the tech industry. It was interesting times to go into job interviews as a new graduate and find former Yahoo/AOL/SGI/Intel engineers sitting for the same entry-level developer role. You knew you weren't getting that job, when you can get a highly experienced dev for the same pay.
I'm not sure what the future will bring but stay humble and hungry.
When I attended back in the late 90’s, there was a view that once y2k was over and that crisis was dealt with the industry would collapse and there wouldn’t be any jobs.
I think AI emphazes brain dead computer science and script kiddy culture. It just lowers the bar enough to make bad ideas easy enough to implement quickly but good ideas still take longer to produce and argue for. Maybe its a skill issue on my part but I've watch my team rebuild a model I maintain, with AI for been estimating performance changes based on trace following. The Model isn't accurate and was build to bypass working on the real model. They spend someone's full time work for 4 months at this point but the thing they wanted modeled took 1 day by just adding it to the real model.
The managers and everyone are so excited by the fact the person did it with AI but I just get really confused because it seems like they just made some worse that has less value because it cannot actually correctly simulate the thing we want to test. Maybe i am being petty and salty but I think the that this is time wasted by any measure. And net-negative value but the team wants to emphasize we are using AI. There have been some productive uses but the productivity trap-doors are about the same as with normal development just people seem more willing to take the trap door ideas now.
>just people seem more willing to take the trap door ideas
It's mainly due to pressure from above. People who want to do a good job and are allowed the time to will be fastidious with or without AI. But now AI provides a shortcut and band-aid where things can be papered over or products can be launched quickly. Ship fast and then iterate" doesn't work when you're building on shaky foundations, but good luck convincing people of that.
This just reminds me of that old meme where a product manager says something like "Why am I paying you $200k/yr when I can just copy code from StackOverflow?" and the engineer responded "You pay me that because I make sure the code you copied is the right code". I have a feeling we're in a similar situation here for AI. Sure, anyone can create AI slop code, but to fully take advantage of it, you need someone that understands the whole chain of design and development to make it fully work and integrate with existing systems.
I think we're in for an era where many folks will be filtered out and those who know and understand code, will be in high-demand.
My local post-secondary dont teach AI at all. Not even like a teaser course or anything.
Technically speaking, they are leftists who publicly oppose AI. They created the new Chief of AI Officer who has no support at all from the univeristy, had to go to politicians for support.
Whereas the college straight up opposes AI.
But what value is any of their degrees anymore? Suspicious at best.
> they are leftists who publicly oppose AI. They created the new Chief of AI Officer who has no support at all from the univeristy
The "leftist" administration created a position while at the same time speaking out against AI? Doesn't seem realistic.
> Whereas the college straight up opposes AI.
Opposes AI in what way? No courses on it? Does not allow students to utilize it? I have a hard time believing they do not offer a single course on any AI subject. Many colleges are offering it as a post-grad option, at least in Canada.
> But what value is any of their degrees anymore? Suspicious at best.
In general? I don't understand what you are getting at here.
>The "leftist" administration created a position while at the same time speaking out against AI? Doesn't seem realistic.
It is an interesting situation to be sure. Not my place to say what they say or do. I'm just commenting about the situation.
>Opposes AI in what way? No courses on it? Does not allow students to utilize it? I have a hard time believing they do not offer a single course on any AI subject.
Publicly opposed to the use of AI.
If a student is found using it, they are expelled. There's 1 public case where a student used Em-dashes and got accused of cheating. GPTzero says human written, but they got expelled. Probably just 1 extreme story, but i dont know.
As for courses. If you look up the 'courses' they do have a machine learning course where it has a single class. "Introduction to Python"
That's it. And that's a course, not even a degree or certification.
They have a 1 year 'data analytics' masters but it explicitly says it's not machine learning or AI. Here I am thinking university is rarely 2 years, always 3+. Yet this is just 1 year? Odd.
>Many colleges are offering it as a post-grad option, at least in Canada.
In fact, this was the more interesting case. I go to one of the networking events put on by the college, as a professional and not student. Nothing about AI technically, but the subject comes up often and almost always in negative light.
I looked into like being a teacher of AI at the college, but they have nothing at all.
>In general? I don't understand what you are getting at here.
Sorry. My bad. I have autism and dont communicate well.
> It is an interesting situation to be sure. Not my place to say what they say or do. I'm just commenting about the situation.
Not your place to say what they say or do but you're doing exactly that? You're bringing politics into the comment and then throwing your hands up and saying "not my place to speak on this" when you are questioned about it.
> That's it. And that's a course, not even a degree or certification.
I see many universities and colleges in Ontario (where I am), for example, that offer post-grad programs on AI. I can't find a single school that has outright banned it. Do you have a source for these claims you are making? I might be uninformed if it is an American or European school but post-secondary institutions in this country seem to be generally supportive.
Teaching AI is a rather large field are you talking about LLMs/transformers? Are you talking about working with LLMs, which is something that seems to change every 6 months?
They do! It's a 1 year course about "Introduction to Python" and that's it.Wild.
>Teaching AI is a rather large field are you talking about LLMs/transformers? Are you talking about working with LLMs, which is something that seems to change every 6 months?
That's a valid point. But that means education is more important as opposed to dont teach it at all.
It is easy to forget sometimes in the excitement, but nobody has been using (2026) AI for 20 years. We're all still new. I am sure that in the next year, something will be found that is fairly exciting, and something we could all be doing right now, but it's simply that nobody has thought of it yet. Or something that is today common practice will become generally considered an anti-pattern and common practice will have some replacement for it that, again, nothing stops us from doing it today but nobody has thought of it yet, because we're all newbs.
(One candidate example for this is the discussion I've seen in the last few days about not trying to negate something, to say "Don't do X", but instead stay positive because eventually the negation gets lost in the context window and you're better off just not putting the idea in the LLM's mind at all, where "Don't do X" comes to be seen as an LLM antipattern.)
One of the consequences of none of us having used AI for long enough is that we don't know how to onboard developers in an age of AI. This will be, by necessity, transient. Eventually we're going to max out what a person can do and we'll need more people. The supply of existing engineers will be limited. We will be forced to discover how to onboard new engineers.
But at the moment we've got our hands full, and we don't know how to do it.
The irony is, the best time to join a field is often exactly when the enrollment dips and the worst can be precisely when it is the most popular. Start a programming college program today and the odds that in 4 years we'll have onboarding figured out and have developed some sort of need for fresh developers is pretty decent.
But I don't know what to do about the fact that the standard CS curriculum was already of debatable relevance to me in the late 90s and I don't know of what relevance it will be in four years except to guess that it very likely to be even less. I do know that we are again affected by the fact nobody has been doing this for 20 years, like I mentioned above. There is no body of "wisdom" for an AI-powered world to draw on to construct a new curriculum. Universities would be inclined to do the obvious thing and try to chase our current practices with AI but those aren't going to be stable enough to build a curriculum on any time soon, and a real fundamentals-based curriculum may involve less AI than people may think.
I know one advantage I have over my younger peers at this point is just a knowledge of what terms to say to the AI to get it to do what I want, words like "event sourced" or "message bus" or "stored procedures", where simply knowing that the concept exists is the bottleneck. I could see a programming curriculum based on touring through a whole whackload of concepts with their pros and cons, or at least, where that is a much larger portion of it.
Ask me in 5 years though and I'd almost certainly suggest a completely different curriculum than I would now, though.
https://archive.ph/IbTFW
Gen Z has a very doomeristic view towards CS careers now due to social media influencers prematurely dismissing CS/software paths as a dead end or impossible to break into because of AI.
I know the job market can suck for graduates right now, but I do believe studying CS can still lead to decent paying careers. There's always going to be demand for people who understand code, who can break down complex problems and bring a problem solving mindset. LLMs don't solve everything.
The drop in CS students ironically may create a vacuum that allows us employed engineers to demand even higher compensation.
I feel like CS is just correcting back to what it was.
Even back when I was in college (graduated 2017), I noticed there was this clear bifurcation among the students. Alot of the students at that time did it because you could score a great job after college but the smaller cohort were the students that just loved the game. And even back then we had loads of students wash out or graduate then take other jobs after college from the former group.
It's no different today except that the group that did it for money are washing out before they even get to college because they fear that AI will take their jobs, meanwhile the latter group is still here and were able to do more and more with AI.
It's a truly wild time to be alive in this industry. Half of us are seeing the doom and gloom of AI and the other half are seeing the "next age" happen right before our eyes.
And I'll be honest I kinda feel sad for the folks that take the negative view of AI right now. Cause I'm having more fun than I've ever had before in this industry.
It's kind of always been a wild time to be alive in this industry.
You covered people washing out of CS degrees and people getting degrees and then not, ultimately, doing something in the CS field.
But what you see in our field that you don't see as often, elsewhere (or -- at all, depending on regulations) is people who ... (1) washed out of the degree because it was competing with their lucrative career as a software developer (or -- more rarely, successful entrepreneur), (2) got a degree in textual biblical studies and had a long career in software development[0] or, you know, other unrelated degree, (3) none of the above, even sometimes incomplete High School education (also[0]).
I've been hiring developers for almost 30 years, now, at a variety of employers -- one global multi-national telecom, one "we make a lot of the products other companies pass off as their own work" IoT/small shop, and a couple of video conference/remote-enabling service shops. There are far more degrees out there, today, than there were 30 years ago. My experience, however, is that the necessity of a degree at the companies I've been employed at has gone down. I suspect that's because I worked for "the giant multinational", first, and all of the rest have been startup or smaller/younger shops (typically 5-10 devs, but no more than ~20 at peek). The giant multi-national, though, during my 17 years, changed (early on) to "or equivalent experience" while rarely hiring someone without a degree for most IT positions to routinely interviewing and hiring people without regard for their degree (and focusing on "code you've written" over "whiteboard exercises", too) while still generally favoring candidates with them. At the best shop I've worked for, it was an even mix of "none", "some", "unrelated", "+bootcamp", "CS degrees" and filled with extremely competent, well-paid, developers.
It's a whole lot harder to get the experience required to have "equivalent experience" without university/internships/the like, but getting the degree without any relevant work experience along the way isn't a good way to go, either.
Around the late 90s (until the bust) and then again a few years later, everyone was pushing kids into CS degrees and the most "interesting" aspect to many of those kids was the starting/long-term earnings against the cost of the 4-year degree. And while, personally, I think "anyone can do it", not "everyone will find it enjoyable to do" like I do.
I'm starting to believe that last part is far more rare than I think it is with my 18-year-old son mostly disliking his introductory computer programming class in High School[1]. I don't push "what I do" on them, just like my Dad didn't, but I expose them to it whenever I can (like my Dad -- kind of -- didn't). And I'll never forget when their Mom looked over at my screen and said "So ... is that what you do all day?", and I beamed "Yes" because it really is the most interesting thing in the world to me, and she said "Wow ... I think I'd kill myself."
[0] Ok, so that's a specific example of someone I know.
[1] Ultimately coming around at the end when his assignment was "make something you want to make."
> I do believe studying CS can still lead to decent paying careers.
Yes, for countries like India.
With AI, outsourcing becomes much more effective.
can you elaborate on your thesis as to why? it seems to me, with raw code being less of a bottleneck, things like understanding the spec, polishing, and doing the fuzzy work around the edges become all the more important. These were never strengths of outsourcing. In fact, I think that the fact that those parts are important is a big reason why the profession as a whole wasnt entirely just outsourced, despite the compelling economic reasons for it.
See my other comment in this thread.
Isn't it the other way around, AI replacing outsourcing? AI can do the implementation work, but you still need the human who needs to specify what has to be done, give architecture guidance and check and accept the resulting work (or reject it, with notes on what to fix). AI coding is basically outsourcing to AI
This is the paradox. But because AI makes outsourcing jobs easier, those workers need to compete, and so they will be able to do those specification jobs and quality control jobs as well.
The paradox is that the quality of AI output is directly proportional to your expertise and understanding, while the trust/belief/confidence in their effectiveness is inversely proportional.
It will still pay to develop the core understanding. It is just that the world can remain irrational longer than you can remain solvent :).
I was rich even before I came into this field, my family owns lots of agriculture land and I came to this field for passion of it and was never really motivated by money.
Thing is AI is taking outsourced jobs in india at much faster rate than elsewhere.
The latest layoff coming from Oracle mostly laid off workers in india.
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Awful take in my humble opinion. Outsourced, vibe-coders as a concept is beyond scary.
It's not doomerism. I've seen this happen at companies.
I was talking to a guy who wanted uptime monitoring. So, he told the executive who called the uptimerobot but then other guy rolled out his uptime robot using AI in 60 minutes and deployed along with centralized logging and it costs the company only $5 VPS.
And honestly it works just as good, I've seen companies are refusing to pay for external tools and building leaner version using AI.
You can build a SaaS faster now but the need for SaaS is on decline.
I've moved to deploying on bare metal from OVH and Hertzner, why? Because devops is completely reduced to few minutes worth of work using agents.
You don't need AI for that. Just deploy Uptime Kuma or similar to a VPS and job done. I can do that in about 15 min vs. your 60 min.
Of course, this is not a production-grade deployment. To get there, I'd need to build images on pipelines, scan them, test them, publish artefacts, write up the IaC to manage the cloud resources, add monitoring around the solution, ...
Deploying a simple piece of software on a custom server was never difficult or slow to do.
You need to invest time in learning its configuration and features you probably won't even need.
Ok, 30 minutes.
Isn't it too early to declare the vibe coded uptime monitoring as "good" from a business standpoint? NIH syndrome has always been a thing and I don't see how the downsides of creating bespoke systems have changed in the LLM-era. You're now stuck maintaining this "genius" solution, LLMs or not, and onboarding devs/users gets harder the more churn you have.
It's 100 lines of code, how hard is it to maintain? It's absolutely better than paying for enterprise license of Uptime robo
Okay, so AI probably wasn't critical to crafting a 100 lines of what I'm assuming is python or some other scripting language that pings a url. Second, I don't think 100 lines is going to be as robust as some pre-packaged monitoring solution (open source or enterprise tier) which has a dashboard and auth story baked in along with proper documentation.
If that script works for your use case then great, but I don't see how LLMs were a game changer here.
Big companies would have rolled out their own anyway, but now 2-3 person companies are also not paying for tools like uptime robots. That's the development LLM brought
Those are some famous last words if I’ve ever heard them.
> So, he told the executive who called the uptimerobot but then other guy rolled out his uptime robot using AI in 60 minutes and deployed along with centralized logging and it costs the company only $5 VPS.
i'm a sysadmin, so i usually watch these things from the side and usually i get called one or two months in to clean up the mess (it happens almost every time).
what you have described is funny to me because uptime monitoring for websites (and also other stuff) is pretty much the use case for prometheus' black-box exporter (https://github.com/prometheus/blackbox_exporter).
assuming you work at a decent company and already have a decent monitoring system (prometheus/alertmanager) it takes 5 minutes to deploy and maybe ten to configure.
if you already have infrastructure then it's basically free. if you already have a kubernetes cluster then it's practically already managed.
> I've moved to deploying on bare metal from OVH and Hertzner, why? Because devops is completely reduced to few minutes worth of work using agents.
at a small scale... maybe. in my experience as soon as you start to reach a decent scale, you'll need experienced engineers (software engineers, system engineers) to actually be at the steering wheel.
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Some things are better when they are outsourced because other companies specialized for that problem set. Just like you won't roll your own cryptography, you won't and can't do everything in-house.
> the need for SaaS is on decline
For 5 minutes. The need for cheap SaaS that one person can build and has no uptime requirements or security requirements or legal requirements or ongoing maintenance requirements is indeed declining.
Eh, this said I think SaaS offering had gotten overpriced. Coupled with things like they put up stickers that say "We R havin S3curity" rather than actually having secure systems, oh and constant price increases and methods of locking you into their services there was a need for some pushback in the market.
The reverse Dropbox curlftpfs comment.
$5 VPS + your AI subscription?
I've been in CS professionally for 12 years. This a perfect example of normal distribution at work. By increasing the population, you simply increase the number of people across the entire curve, bumping up the number of high, medium, low paid, as well as unemployed folks with the degrees. The real issue has always been greed - people disproportionately dove into CS because like all hype movements it promised significant income after just 2-4 years, and sometimes not even that, but a month long bootcamp. Once it was sold to the masses as a get rich quick scheme - the disappointment paired with a number of low-achieving grads tripling was unavoidable.
It definitely was oversold, but I don't think it's right to fault people for picking CS because of the money. That is essentially the point of getting a job, and most people do not actually get to live their "passion" -- even those of us who DO truly have a passion for programming. Most careers are only as good as the jobs you get, and most jobs are not amazing. If I have to do something I'm not crazy about, we're talking about degrees of misery and cost/benefit ratios, and that is very personal.
The same thing happened in dentistry, law, EE, some medical specialties, vets. Job path gets seen as a golden ticket to high pay for low to medium effort and people pile into the profession and saturate the market. Then some thing happens, a recession, technological innovation, or geopolitical/geo-economic shift, and the demand changes dramatically. These things work in cycles, happened before in the .com bust, and this will take 5-10 years to work its way out. The good news is that for the new grads who manage to hang on they will make a killing as the demand for mids and seniors will be insane due to the lack of qualified candidates available.
Uhh dentists doctors and EEs are low effort jobs?
Yes? Insofar as a career path. You go to a good school, get a good degree and be almost guaranteed a good pay with known career progression. It's not like entrepreneurship, where you can't see the path ahead of you. Think video games, much easier to play when the goals are given to you than to make your own.
You just described a bunch of hard and continuous work, and oversell the "almost guaranteed" part. Nothing is guaranteed in life, except death and taxes. Entrepreneurship can be harder or easier than working for someone else. Some entrepreneurs just show up with a bunch of money and hire other people to do the bulk of the work. That's a different kind of stress.
I won't undersell the efforts professionals need to acquire their skills, but I also stand by my view that a clearly defined progression makes life a lot easier to navigate. It's why quests are fundamental in RPGs and uncertainty is bad for business. When you can see the path ahead, the problems that need to be solved are clear. It's why research is so painstakingly slow when we are treading on unknown unknowns.
As for those who showed up and everything worked out, consider them lucky, though I doubt there are many of them out there.
Entrepeneurship is not a career path.
seriously. I don't see how CS is low effort either, maybe they mean physically low effort.
> I don't see how CS is low effort either, maybe they mean physically low effort.
It's pretty common in the us to sell software engineering-centric courses (bachelors) for computer science courses.
software engineering is a thing, computer science is something else.
actual computer science is not trivial at all. the math gets hard.
software engineering on the other hand is way more shallow in this sense... rightfully so, don't get me wrong.
Software engineering is not necessarily shallow in any sense. Reasoning about large and imperfect systems can be so much harder than finding average publishable CS results. But the difficulties are often so particular to the software and situations that it isn't of interest to academics.
> Software engineering is not necessarily shallow in any sense.
I should have been clearer in my writing. What i meant to say is that the math involved in pure software engineering is much more shallow than the math involved in pure computer science.
> Reasoning about large and imperfect systems can be so much harder than finding average publishable CS results.
x doubt...
>x doubt...
Ah so you are an academic. I have been in both places. Industry people have to not only think of ideas but implement them with real computers. In some cases the computers must be built specifically to solve the problems. Millions of lines of code, broken shit, backward compatibility, stuff that can only be found through years of use. I suppose one can try to make an academic problem out of any industry concern, and therefore appear to be "more sophisticated" but inferior, partial, and broken proposals are regularly published. To get published, even a sketch of a possible solution with no implementation often flies. In industry, a lot of inferior stuff is accepted out of necessity, but it's often do or die with deadlines and real budgets to be concerned about.
Our government failed the citizens and let outsourcing and wage suppression destroy the US tech industry...positioning the country far behind other countries in technology supremacy for at least a decade to come
It started long before tech. It started with manufacturing. Everything has been replaced with financial manipulation and rent-seeking.
You don’t have a god given right as an American to a mid-high six figure income working in tech and I’m not sure how you can see Anthropic playing whack-a-mole trying to keep the Chinese from distilling their models and say that the US isn’t still on the inside track with this stuff.
Corporations don’t have a God-given right to manipulate the market by outsourcing the work to the detriment of the natives, yet they make good use of it!
That’s not really how that works.
Also, why do you hate the poor so much? Do people not deserve well paying jobs because the vagina they came out of wasn’t located on the correct patch of dirt?
And yet, CS was the fastest growing employment category with some of the highest and among the fastest growing salaries in the nation for the past 2 decades despite the fact that outsourcing has been around since the 90s.
The fact that this changed in the last 2 years right when AI became feasible is just a coincidence. It’s actually finally outsourcing destroying the grad job market nearly 3 decades later.
Nothing changed in the past 2 years except we had another recession. Just like very other recession, people are looking for something to blame. Out sourcing has long been a popular thing to blame. This time blaming AI is the fad. There will be more recessions in the future and people will blame some other fad next time (or perhaps the same). In the end though it is the economy.
There was a golden age (2010-2020 or so?) when a CS degree of as basically an easy ticket to the upper middle class. Unlike similar well-paying jobs like law or medicine, a bachelor's degree was enough. Now it's not easy to get a job as a new grad, so there are fewer people getting into the discipline whose primary reason to study it was money.
CS started as a major for "computer nerds" who were very into computers. Computers were a hobby for virtually every one of my CS classmates in the 90's. Studying computer science was an extension of that interest, so majoring in CS made sense.
Fast forward a decade or two, and it is like you said, people who don't have a strong interest in computers starting taking CS as a major as a path to jobs and income.
Now, as a manager of engineering teams, I'm constantly surprised by Software Engineers that don't even own their own computers and/or have very little knowledge about how they work.
So you hire people who “don’t even own their own computers?” You might be the problem then.
There have always been ups and downs in the economy. This isn't the first recession where programmers were hit harder than other jobs. There have been other recessions where programmers were one of the few places where everyone was hiring.
You can substitute every single possible profession for programmers above and still have a trust. Even things like groceries (everyone needs to eat) still has ups and downs (some recessions people go to restaurants less and so are good; others they switch to low margin staples and profits go down).
CS was viewed as a golden ticket at least as far back as 2000. Even then, there were people doing the degree who had no interest in the subject, but thought it would get them a good salary.
Seemed to really accelerate around 2007-2008 when Facebook became massive and turned a bunch of kids into billionaires overnight. After that it sort of turned into a gold rush, and we were the shovels.
CS hiring has always been very cyclical, and there have been more flush times prior to 2010 where CS more or less guaranteed a good paying job.
> There was a golden age (2010-2020 or so?)
Also during the Dot Com era. Pretty much every cycle lead to more people getting into the field.
I was just at the largest career / college expo for high schoolers in the greater NYC area yesterday. It’s anecdotal but the two most asked about majors at the fair were #1 mechanical engineering and #2 computer science. I gave away all the materials we had and I had left thinking “this will be plenty”.
So let’s just wait a bit before we say it hit a wall.
People realised that acamedia is not set up to train people for jobs, but set up to teach people.
These two roles are at odds with each other.
Care to elaborate? This sounds like a prelude to an argument to funnel more people into vocational schools/more funding for vocational schools.
(Not a criticism! I don't personally feel informed enough to have an opinion on this subject.)
I don't personally have an opinion yet on what is the correct way to do things, I can only talk from my own personal experience within Academia in the UK as both a student and teacher with Computer Science.
The prime example is that most software roles in the economy are (or where, perhaps AI will change this, I do not know) simple web-dev/CRUD/SQL roles. Specifically Python/JS was a high-demand skill. This pushed universities to get rid of lower level courses such as concurrency/computer architecture, C/C++/assembly, or more maths based modules such as logic, in favour of more web-dev/software/AI/data-science modules.
One could (and I do) argue that this is effectively turning computer science degrees into more of a software engineering degrees piece by piece, thus turning univerisities into vocational schools.
Now here lies the question. Is this correct? Should universities be vocational schools? Or should they be seperate? Personally my feeling is that universities are not set up well for this method of teaching, and it would be much better for everyone involved if the students were instead taught through apprenticeship or vocational schools, which tend to be significantly cheaper (or even pay) for the student, whilst making sure that the university degree can stay focused within academia and funneling a good research pipeline.
Instead my view is that politicans have pushed many young adults into expensive degree programs that they did not need, with the false promise that it would give them emplolyement (which was never the goal of a university in the first place). This isn't good for the students (who are saddled with debt), the employers (who end up having to train the juniors anyway) or the economy (which now has less money in it due to the large drain on disposable income from student loan repayments).
Xennial here! Graduated after Y2K, 9-11, and the dot bomb era. A lot of us lost 3-4 years of early career advancement due to layoffs that primarily affected the tech industry. It was interesting times to go into job interviews as a new graduate and find former Yahoo/AOL/SGI/Intel engineers sitting for the same entry-level developer role. You knew you weren't getting that job, when you can get a highly experienced dev for the same pay.
I'm not sure what the future will bring but stay humble and hungry.
We have an oversupply of CS majors. Lot's of people came to the craft chasing the money.
It's probably a good thing that the hype starts to die and we're seeing a market correction, hopefully back to a saner structure.
When I attended back in the late 90’s, there was a view that once y2k was over and that crisis was dealt with the industry would collapse and there wouldn’t be any jobs.
What’s happening now reminds me a lot of that.
I think AI emphazes brain dead computer science and script kiddy culture. It just lowers the bar enough to make bad ideas easy enough to implement quickly but good ideas still take longer to produce and argue for. Maybe its a skill issue on my part but I've watch my team rebuild a model I maintain, with AI for been estimating performance changes based on trace following. The Model isn't accurate and was build to bypass working on the real model. They spend someone's full time work for 4 months at this point but the thing they wanted modeled took 1 day by just adding it to the real model.
The managers and everyone are so excited by the fact the person did it with AI but I just get really confused because it seems like they just made some worse that has less value because it cannot actually correctly simulate the thing we want to test. Maybe i am being petty and salty but I think the that this is time wasted by any measure. And net-negative value but the team wants to emphasize we are using AI. There have been some productive uses but the productivity trap-doors are about the same as with normal development just people seem more willing to take the trap door ideas now.
>just people seem more willing to take the trap door ideas
It's mainly due to pressure from above. People who want to do a good job and are allowed the time to will be fastidious with or without AI. But now AI provides a shortcut and band-aid where things can be papered over or products can be launched quickly. Ship fast and then iterate" doesn't work when you're building on shaky foundations, but good luck convincing people of that.
Dunning-Kruger as a service.
This just reminds me of that old meme where a product manager says something like "Why am I paying you $200k/yr when I can just copy code from StackOverflow?" and the engineer responded "You pay me that because I make sure the code you copied is the right code". I have a feeling we're in a similar situation here for AI. Sure, anyone can create AI slop code, but to fully take advantage of it, you need someone that understands the whole chain of design and development to make it fully work and integrate with existing systems.
I think we're in for an era where many folks will be filtered out and those who know and understand code, will be in high-demand.
My local post-secondary dont teach AI at all. Not even like a teaser course or anything.
Technically speaking, they are leftists who publicly oppose AI. They created the new Chief of AI Officer who has no support at all from the univeristy, had to go to politicians for support.
Whereas the college straight up opposes AI.
But what value is any of their degrees anymore? Suspicious at best.
> they are leftists who publicly oppose AI. They created the new Chief of AI Officer who has no support at all from the univeristy
The "leftist" administration created a position while at the same time speaking out against AI? Doesn't seem realistic.
> Whereas the college straight up opposes AI.
Opposes AI in what way? No courses on it? Does not allow students to utilize it? I have a hard time believing they do not offer a single course on any AI subject. Many colleges are offering it as a post-grad option, at least in Canada.
> But what value is any of their degrees anymore? Suspicious at best.
In general? I don't understand what you are getting at here.
>The "leftist" administration created a position while at the same time speaking out against AI? Doesn't seem realistic.
It is an interesting situation to be sure. Not my place to say what they say or do. I'm just commenting about the situation.
>Opposes AI in what way? No courses on it? Does not allow students to utilize it? I have a hard time believing they do not offer a single course on any AI subject.
Publicly opposed to the use of AI.
If a student is found using it, they are expelled. There's 1 public case where a student used Em-dashes and got accused of cheating. GPTzero says human written, but they got expelled. Probably just 1 extreme story, but i dont know.
As for courses. If you look up the 'courses' they do have a machine learning course where it has a single class. "Introduction to Python"
That's it. And that's a course, not even a degree or certification.
They have a 1 year 'data analytics' masters but it explicitly says it's not machine learning or AI. Here I am thinking university is rarely 2 years, always 3+. Yet this is just 1 year? Odd.
>Many colleges are offering it as a post-grad option, at least in Canada.
In fact, this was the more interesting case. I go to one of the networking events put on by the college, as a professional and not student. Nothing about AI technically, but the subject comes up often and almost always in negative light.
I looked into like being a teacher of AI at the college, but they have nothing at all.
>In general? I don't understand what you are getting at here.
Sorry. My bad. I have autism and dont communicate well.
> It is an interesting situation to be sure. Not my place to say what they say or do. I'm just commenting about the situation.
Not your place to say what they say or do but you're doing exactly that? You're bringing politics into the comment and then throwing your hands up and saying "not my place to speak on this" when you are questioned about it.
> That's it. And that's a course, not even a degree or certification.
I see many universities and colleges in Ontario (where I am), for example, that offer post-grad programs on AI. I can't find a single school that has outright banned it. Do you have a source for these claims you are making? I might be uninformed if it is an American or European school but post-secondary institutions in this country seem to be generally supportive.
So they don't have a machine learning class?
Teaching AI is a rather large field are you talking about LLMs/transformers? Are you talking about working with LLMs, which is something that seems to change every 6 months?
>So they don't have a machine learning class?
They do! It's a 1 year course about "Introduction to Python" and that's it.Wild.
>Teaching AI is a rather large field are you talking about LLMs/transformers? Are you talking about working with LLMs, which is something that seems to change every 6 months?
That's a valid point. But that means education is more important as opposed to dont teach it at all.
It is easy to forget sometimes in the excitement, but nobody has been using (2026) AI for 20 years. We're all still new. I am sure that in the next year, something will be found that is fairly exciting, and something we could all be doing right now, but it's simply that nobody has thought of it yet. Or something that is today common practice will become generally considered an anti-pattern and common practice will have some replacement for it that, again, nothing stops us from doing it today but nobody has thought of it yet, because we're all newbs.
(One candidate example for this is the discussion I've seen in the last few days about not trying to negate something, to say "Don't do X", but instead stay positive because eventually the negation gets lost in the context window and you're better off just not putting the idea in the LLM's mind at all, where "Don't do X" comes to be seen as an LLM antipattern.)
One of the consequences of none of us having used AI for long enough is that we don't know how to onboard developers in an age of AI. This will be, by necessity, transient. Eventually we're going to max out what a person can do and we'll need more people. The supply of existing engineers will be limited. We will be forced to discover how to onboard new engineers.
But at the moment we've got our hands full, and we don't know how to do it.
The irony is, the best time to join a field is often exactly when the enrollment dips and the worst can be precisely when it is the most popular. Start a programming college program today and the odds that in 4 years we'll have onboarding figured out and have developed some sort of need for fresh developers is pretty decent.
But I don't know what to do about the fact that the standard CS curriculum was already of debatable relevance to me in the late 90s and I don't know of what relevance it will be in four years except to guess that it very likely to be even less. I do know that we are again affected by the fact nobody has been doing this for 20 years, like I mentioned above. There is no body of "wisdom" for an AI-powered world to draw on to construct a new curriculum. Universities would be inclined to do the obvious thing and try to chase our current practices with AI but those aren't going to be stable enough to build a curriculum on any time soon, and a real fundamentals-based curriculum may involve less AI than people may think.
I know one advantage I have over my younger peers at this point is just a knowledge of what terms to say to the AI to get it to do what I want, words like "event sourced" or "message bus" or "stored procedures", where simply knowing that the concept exists is the bottleneck. I could see a programming curriculum based on touring through a whole whackload of concepts with their pros and cons, or at least, where that is a much larger portion of it.
Ask me in 5 years though and I'd almost certainly suggest a completely different curriculum than I would now, though.
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We can count on the racists to come out of the woodworks to comment on this.
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Every racist claims to be justified in their prejudices against and generalizations of large groups of people.