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.

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.

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

I was just at the largest career 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.

We can count on the racists to come out of the woodworks to comment on this.

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.

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.

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.

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.

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.

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.

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.

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.

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.