https://en.wikipedia.org/wiki/Embrace%2C_extend%2C_and_extinguish

I think, if LLMs stop being trained, you'll see a short-term split in the industry: those that continue to evolve their languages, frameworks, and other tools and those that end up stuck on old versions. And then we can invert the 'left behind' narrative.

So for senior mismanagement the fact XYZ is still loss making isn't often a concern so long as there's name and money behind it to assure people that it won't go pop (or you have a backup plan). They'd have to look a lot further behind the curtain to realize.

If it were a one-off, it wouldn't matter so much because you'll amortise it eventually.

This is what frustrates me about people to talk about using local models as if they're a viable alternative. Who do they think is going to pay to train an LLM if they can't get revenue from inference? And who wants to use, say, a coding LLM that was trained on an old language standard and a load of deprecated APIs?

The fun thing here is that training costs are very large, but mostly fixed NRE, whereas inference is OpEx that scales with userbase size. If you keep the prices low, you get more customers and so can amortise the NRE, but you can’t cover your OpEx, so you make a loss. If you put the prices up, you can cover the OpEx, but it pushes customers away and so reduces the amortisation of the NRE and so you can no longer cover it and make a loss.

Successful products have either low NRE or low OpEx to deliver. High NRE and low OpEx is ideal because it’s hard for competitors to enter the market but the early players can deliver cheaply. Low NRE and moderately high OpEx can work as long as the OpEx is less than customers are willing to pay, but usually precludes mass-market products unless economies of scale let you reduce the OpEx.

About the only places you find products with both high NRE and high OpEx are in the healthcare and defence sectors where demand is inelastic.

“My company is large. We were using GitHub copilot with several thousand users. With the change to token fees we are currently considering dropping ai agentic coding as a whole until at least the market stabilizes.”

Whyyy do such people get to run companies?! It’s always been public knowledge that LLM SaaS runs at a loss

The screenshots you had the price differentials are eye watering.

I can’t wait for the other companies to follow suit. They probably won’t because these price changes would melt down most us usage.

The upside is they wouldn’t be burning token so much

I am still thinking that other shoes should be dropping for other AI. Microsoft is accompany that actually has business and a huge slush fund like all the established big tech companies we got piles of money or had bigger piles of money stored offshore. They got a one time tax break to reshore them so AI seems to be what they’re doing with their money.

Tech report had an interview earlier today about the Samsung worker strike.

I just want to point out this youtube comment that made me lol:

> I guess they DID make 10x devs, in the end

The SaaS ghouls come for everybody. At least this time they picked a deserving target.

That's how enshittification works. First hook them up with cheap prices and discounts. Once you get them hooked, you'll push up the prices so you can get rich.