All the model companies except kind of Anthropic (and even they half-assedly do) implement the OpenAI API. It's not an open standard but, like the S3 API, it effectively is.
And, to answer your question, no. The existence of a common API makes it trivial to change zero code and send requests to a different model.
Isn't this what LiteLLM is doing? And is Open Source? Maybe I am asking a dumb question because this is the age-old SaaS vs OSS debate, but I am struggling to find the angle here.
The Anthropic messages API is a competing standard (it's just better than the OpenAI API which even OpenAI has moved away from) and some Chinese providers use it as their standard.
This seems trivial: if you could add enough plants to your room to reduce CO2, we could easily do the same thing at planet-scale and global warming wouldn't be an issue.
I suspect part of the reason this is playing well on this website is banning surveillance pricing is great for rich people. I don't have the time or inclination to coupon or aggressively cross-shop but I benefit a lot from the less well-off folks who do. The grocery store, without any ability to differentiate, has to assume that I might be one of those people and sell me a banana at the same price.
Great for rich people or just not your relative purchasing power being completely eroded. Why work for a 5% raise if it means all your expenses go up 5%?
The situation you're positing already basically exists with housing - who literally ask for proof of your income - and while housing goes up at unreasonable rates due to lack of construction, it clearly doesn't go up at the same rate (and _definitely_ not by the same raw amount) as income does.
I worry about corner cases like rural towns with only one grocery store (although I suspect that those are already gouging people?) but that isn't San Francisco.
True that an interpreted language has a leg up on any compiled language in the arena of compile time, but worth noting that one of Go's primary design goals was improving compile times of massive code bases. Google was drowning under the weight of compiling huge C++ codebases and Go was the response to that (among other things).
Python is preferred because Python programmers are cheaper than other languages. Not because of any sort of technical advantages. Its literally the worse performing programming language in popular use. And it uses invisible characters in its syntax. Truly, it is the VHS of our industry.
Go compiles things at package-level granularity. You only need to recompile your reverse dependencies on making changes. Also there's build caching available out-of-the-box, as well as some support for test caching.
I would be pissed if my programming language changed as quickly as Claude code does. Languages need to move slowly and carefully, and zig is on the faster end of language development regardless.
I would be mad if the syntax was constantly changing but I want the internal implementation to be moving as fast as possible while retaining success. I think that rate is higher than what humans alone can do.
That's a monkey's paw desire because nowhere is Hyrum's law more true than programming languages. Alternatively you just end up with something like C++ where no one understands the whole thing.
I would guess the cost to do this with humans would be _at least_ $1.5M in compensation alone (I'm thinking three 500k/year Bay Area engineers) so this is already an order of magnitude cheaper.
Is it worth $165K? I'm less sure of that but it's honestly a moot point - this will get to 5 then 4 digits of cost pretty fast.
I think putting it in terms of API pricing is oversimplifying disingenuously. Anthropic still hasn't pulled the rug out from under us, so I'm sure it cost a great deal of money once everything comes together, likely surpassing 1.5M. Summarily, they got the result faster, which a group of engineers couldn't do, but at a greater expense.
GLM 5.2 (open-weights) is at or near Opus 4.7 level performance already. I think it's unlikely Anthropic will be able to durably charge us much more than the CapEx depreciation cost of GPUs + the OpEx of running them for non-frontier models (which Fable will be in 6 months to a year).
Engineers are pretty jaded about plans expressed by authority, especially when there are obvious pressures opposing those plans. Yearly planning doesn't matter when a reorg will change the trajectory by Q3. Sprint planning doesn't matter when you know a fire will hit before then and you won't be given enough time budget to fix it well enough for that not to happen again next sprint. Project planning doesn't matter when the whole point is masturbatory spreadsheet production before you've actually taken a dive into the hairier details and figured out what's possible and what's necessary. That barely working demo strapped on top of a non-existent backend they swore would never become production? Congratulations, you have two weeks to build the next fake demo on top of it, but the base has to actually work now.
Maybe Jared just broadcasted uncertainty and was wrong, but given his position he's not being given the normal grace you might extend to an engineer you trust.
That was their estimate at the time, based off the information they had. You can't ask more of someone than that.
Either they estimated poorly, or it ended up the lesser portion of their estimate after all. After all, unless the estimate is 100%, there's always a chance it'll fall into the other portion.
To understand your error, consider that in the month leading up to the 2016 US presidential election, the widely-accepted probabilities were between 70% (Five-Thirty-Eight) and 90% (Reuters) in favour of Clinton.
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