Your last two sentences remind me of the olden days of people building applications on top of FB and Twitter APIs (and later, Reddit), only to to have the rug pulled out from under them in one way or another
I've been learning Basque and wanted to see a visualization of how the semantics move into different grammatical structures when translating between Basque and English/Spanish.
Under the hood it's using Stanford NLP to analyze the input then that analysis is given to Claude to generate the data structure needed to visualize the translation. It's really cool and maybe my favorite of the itch-scratchers I've built for myself over the years.
(Xingolak is Basque for "ribbons," a nod to the visualizing metaphor used in the UI.)
I traded emacs for vscode several years ago now but this post made me wonder if I'd be insane for dusting off my herd of finely shorn yaks to try typescript dev again with it.
At the time I left for vscode, emacs had a REALLY bad Typescript story and it felt like a revelation doing TS in vscode.
Surely emacs has gotten a definitive TS solution since, idk, 2018? 2019? Right?
The road to eternal burning hell is paved with stored procedures. My experiences (!!) make it so i will never be convinced on the risk:reward being worth it.
The way this position conforms to the interests of the capital class, and conflicts with those of the labor class, is a red flag.
It simultaneously and conveniently:
1. takes the heat off AI blowback
2. synergizes perfectly with "RTO" mandates (to the extent this needed synergy to become A Widespread Thing)
On that basis alone, I'll wait for further analysis.
Edit: to be clear I'm no anti-AI holdout, and I actually don't mind working from the office (which i do 4x a week). Just observing.
I've been retired from emacs for several years now but I'm still looking for a magit replacement that is independent of my editor. Vscode's magit extension is really good but i split my time between IntelliJ and vscode.
I also have a a scratch-my-own-itch project[1] that leverages an LLM as a core part of its workload. But it's so niche I could never justify opening it up to general use. (I haven't even deployed it to the web because it's easier to just run it locally since I'm the only user.)
But it got me interested in a topic I have been calling "token economization." I'm sure there's a more common term from it but I'm a newb to this tech. Basically, how to optimize the "run rate" for token utilization per request down.
Have you taken a stab at anything along this vein? Like prompt optimization, and so on? Or are you just letting 'er rip and managing costs by reducing request volume? (Now that I've typed this comment out I realize there is so much I don't know about basic stuff with commercial LLM billing and so on.)