The unique thing about GitHub Copilot (and all the other vibe-coding tools) is that they're speed-running the playbook because this shit is not profitable. It can't be. Their costs scale up with usage, unlike every other business that can take advantage of economies of scale, so they've skipped the slow, steady enshittification phase and jumped directly into the "squeeze blood from this stone to keep the scam going a little longer" phase.

I've been preaching this for the past couple of years. Everything up until now has been entirely about gaining market share, and AI will never be cheaper than it is right now, and it's not cheap.

Just look at the "earnings" for companies like openAI. They are 1000+% in the red. It's impossible for them to change their sales model enough to make that profitable. As more data centers go up, the operating costs are also going to go up.

I've been telling people that now is the best time in the past decade or more to learn how to code. There will be positions available in the coming years when the only junior devs available are vibe coders.

I remember having to sit down my boss and explain how it can only become more expensive over time. It’s the big tech playbook after all. Didn‘t matter. I‘m told again and again how AI is only becoming stronger and cheaper. Especially during salary negotiations. Nasty stuff. They know I know it‘s BS and they still cling to this nonsensical narrative because it would be very beneficial to them and very bad for me.

Yeah - people are talking about replacing jobs with AI. As if it is not totally obvious that people like Sam Altman will totally bleed you dry after you fired all your workers. You will not save on your wage bill, you will simply give the money to Sam Altman

The crazy thing is, this isn't really a "squeeze" in the traditional sense. The problem was that every single mainstream AI product has been heavily subsidized....because it's wildly expensive and not even close to being profitable.

That sort of subsidization was only going to last for so long. The dam is starting to crack. People aren't ready to pay what AI truly costs.

I didn't see it coming as I am on Codeberg 😎

The angry devs from this article are idiots

The strategy is always to gain a monopoly or near monopoly on a market before pushing for the enshittification of the product to reduce costs and maximize profits, once customers have become dependent on said product, then pray that most choose the path of least resistance which is staying and dealing with the worse and more expensive version of what they're used to rather than retraining or restarting from zero elsewhere.

Capitalism 101.

It's not even just private equity, this is more or less the exact strategy Microsoft uses.

The tactic has worked for drug dealers for decades

Users are paying way more than the cost of inference. Look up inference prices of high end open weight models vs claude or gpt. Cheaper by an order of magnitude.

It's the constant training of new models that's losing them money. New version is out every month.

Honestly, only Tesla comes to mind. Maybe bleeding edge tech frontier is the one place where first movers RND cost is heavy enough to make it irrecoverable.

It's interesting to contrast this w/ the field of medicine; RND cost can be recovered by squeezing the folks in the domestic market.

The company I work for had a pilot project for a while but recently they opened up for all users to order Github Copilot. Of course it is Github Copilot since everything else at the company is from Microsoft.

That many free accounts is against their user agreement though hehe

Actually it can be a very useful tool, if you know what you're doing. Expensive in real terms, so only for tasks which are worth it. So perhaps not for making annoying cat videos.

Where I work, Chinese models are banned due to legal concerns. Not just in production, on any company-owned machine. That basically eliminates all the decent open weight models. I’m imagining this type of policy will be more widespread. I suppose it’s because of the potential for legal woes if systems and people are dependent on these models and then federal or state laws impose harsh penalties with little time to react.