Its a free market if you are the one paying for it solely. If you are willing to pay for the degree then the demand is there for them to sell you the product. Buyer beware sadly. Its a question of what you see the purpose of the course is - to prep people for the job market or to teach knowledge? If it is the former to you then yes they should at least warn people of the competition and the contraction of the industry they may face - they can decide if it is worth it for them.

For many on this forum if they are honest with themselves given the pace of AI and the future risk/uncertainty they may not have taken this risk on. They've misallocated their own funds which is always not ideal - and sadly expected when there is rapid change; not all investments pay off. The only thing I can say is if you are young the time horizon is there to invest in something else and get back on your feet. There is more to life then work IMV especially as you get older; and an investment in your career needs enough time horizon to pay off. For many a job is a means to an end - they may enjoy it but being able to earn a long term living is the primary goal.

In other countries where the education is subsidized for the purposes of skill building for the economy then yes I actually think it might be pragmatic for them to offer less places. Otherwise its tax money going to waste with a misallocation of public resources without the associated society wide economic benefits.

Eventually the market finds a new equilibrium of staff to demand ratio. You prefer that happen sooner so people don't make bad investments of their time (e.g. studying the wrong course based on inaccurate market signals).

The truth is we just don't know how things will play out right now IMV. I expect some job destruction, some jobs to remain in all fields, some jobs to change, etc. We assume it will totally destroy a job or not when in reality most fields will be somewhere in between. The mix/coefficient of these outcomes is yet to be determined and I suspect most fields will augment both AI and human in different ratios. Certain fields also have a lot of demand that can absorb this efficiency increase (e.g. I think health has a lot of unmet demand for example).

I actually think F# has received some "love" over the recent years contrary to some on this forum; that feature being an example. My view, maybe unpopular but in the age of AI maybe less so, is there is a diminishing returns to language features anyway w.r.t complexity and the use cases that new feature will actually apply for. F# in my mind and many other languages now for that matter is pretty much there or are almost there; the languages are converging. When I used F# I liked how it unified features and tried to keep things simple. Features didn't feel "tacked on" mostly with some later exceptions.

Last time I used F# a few libraries started adopting this for their CE's (e.g. IcedTasks library, etc).

While I think both sides have an argument on the eventual SWE career viability there is a problem. The downsides of hiring now (costs, uncertainity of work velocity, dry backlogs, etc) are certain; the risk of paying more later is not guaranteed and maybe not as big of an issue. Also training juniors doesn't always benefit the person paying.

* If you think long term that we will need seniors again (industry stays same size or starts growing again) given the usual high ROI on software most can afford to defer that decision till later. Goes back to pre-AI calculus and SWE's were expensive then and people still payed for them.

* If you think that the industry shrinks then its better to hold off so you get more out of your current staff, and you don't "hire to fire". Hopefully the industry on average shrinks in proportion to natural retirement of staff - I've seen this happen for example in local manufacturing where the plant lives but slowly winds down over time and as people retire they aren't replaced.

It also doesn't help that some people in this role believe that the SWE career is a sinking ship which creates an incentive to climb over others and profit before it tanks (i.e. build AI tools, automate it and profit). This is the typical "It isn't AI, but the person who automates your job using AI that replaces you".

AI Engineers aren't actually SWE's per se; they use code but they see it as tedious non-main work IMO. They are happy to automate their compliment and raise in status vs SWE's who typically before all of this had more employment opportunities and more practical ways to show value.

Not every software project has or did this. In fact I would argue many new businesses exist that didn't exist before software and computing and people are doing things they didn't beforehand. Especially around discovery of information - solving the "I don't know what I don't know" problem also expanded markets and demand to people who now know.

Whereas the current AI wave seems to be more about efficiency/industrialization/democratizing of existing use cases rather than novel things to date. I would be more excited if I saw more "product orientated" AI use cases other than destroying jobs. While I'm hoping that the "vibing" of software will mean that SWE's are needed to productionise it I'm not confident that AI won't be able to do that soon too nor any other knowledge profession.

I wouldn't be surprised with AI if there's mass unemployment but we still don't cure cancer for example in 20 years.

When you are thinking your days are numbered any cost to develop software (even token budget) is measured. As coding becomes commoditized the ROI in code will drop of that code (capitalism rewards scarcity; not value delivered) and you suddenly become cost conscious. We are moving from a monopoly-moat like market to a competitive cost based market in SWE as AI improves.

Not all open source but a lot of it is fundamentally for humans to consume. If AI can, at its extreme (still remains to be seen), just magic up the software then the value of libraries and a lot of open source software will decline. In some ways its a fundamentally different paradigm of computing, and we don't yet understand what that looks like.

As AI gets better OSS contributes to it; but in its source code feeding the training data not as a direct framework dependency. If the LLM's continue to get better I can see the whole concept of frameworks being less and less necessary.

If we didn't have open source arguably developers would be more secure, way more secure, in the face of AI.

The seniors who have less leeway to change course (its harder as you get older in general, large sunk costs, etc) maintain their positions and the disruption occurs at the usual "retirement rate" meaning the industry shrinks a bit each year. They don't get much with pay rises, etc but normally they have some buffer from earlier times so are willing to wear being in a dying field. Staff aren't replaced but on the whole they still have marginal long term value (e.g. domain knowledge on the job that keeps them somewhat respected there or "that guy was around when they had to do that; show respect" kind of thing).

The juniors move to other industries where the price signal shows value and strong demand remains (e.g. locally for me that's trades but YMMV). They don't have the sunk cost and have time on their side to pivot.

If done right the disruption to people's lives can be small and most of the gains of the tech can still come out. My fear is the AI wave will happen fast but only in certain domains (the worst case for SWE's) meaning the adjustment will be hard hitting without appropriate support mechanisms (i.e. most of society doesn't feel it so they don't care). On average individual people aren't that adaptable, but over generations society is.

What that means for society where there are extremely rich people who owns resources and capital, and everyone else is only valued for their dexterity and physical labor (vs skills) I can only guess.

I do think the AI labs have potentially unleashed a society changing technology that ironically penalizes meritocracy and/or intelligence by making it less scarce. The jobs left will be the ones people avoided for a reason (health, risk, etc)

Because unlike previously:

  - You can't invest in these things directly (mostly private) so gains are at best diluted for retail investors.

  - They can take your job AND still be unprofitable (i.e. on VC money/subsidized).

  - Value accures to capital/companies using it potentially, not the AI labs themselves in a competitive market. In which case the gains will be across many industries and be diluted (i.e. not life changing if you invest enough to offset income loss)

  - They are exposed to the loss of income of their labor.

  - They don't have the capital and/or risk tolerance to invest accordingly.

  - The way to invest in these isn't obvious and is subject to unsystematic risk (i.e. can you pick the winners?).