When will devs learn that being able to search for a term on the open internet without having it polluted by normal language is kind of important
囲 is a simplification of 圍, and 碁 is a Japanese-specific letter that roughly maps to 棋. If you read 圍棋 in Chinese, you get weiqi.
People get around it by appending "-lang" or "-script" to the name and that solves the SEO.
Cryptography is much older than bitcoin.
IIRC historically on Windows, a string was UTF16, on unix it was ASCII; nowadays everywhere it's UTF8 without a way to specifically limit what goes into a string.
For example UTF8 opens the door to homoglyph attacks and various other things (RTL, spaces), and a program should be able to force a string to be ASCII-only so that these classes of problems are ruled out.
That being said, Windows permits unpaired surrogates in its "UTF-16" strings, even though that is not actually valid UTF-16. Similarly, many Linux APIs accept arbitrary bytes, not just valid UTF-8.
This talk argues there are many purposes for formal languages other than programming, which is the dominate use case of big tech: https://medium.com/bits-and-behavior/my-splash-2016-keynote-...
So it may be true that "programming language" development is done, but there are many more applications for formal languages than just writing apps and websites and such.
Moreover, it may be true that less code as a proportion of all code is being written or read by humans. But more humans today are reading and writing code than ever before. So the ability to express unambiguous ideas to agents using formal langauges is more important than ever, even if people are only reading/writing a small proportion of all code.
Similarly, it's not true that because agents will be reading / writing code that language ergonomics do not matter. Agents have resource restrictions like token budgets, and they are also trained using human knowledge and conventions. Ergonomics apply to agents just as they do humans; languages which are verbose require more tokens to write, languages that can be verified are more useful in agentic loops, languages with live compiler introspection and interpreters can give fast results to agents etc.
So I hold exactly the opposite view: it's not clear to me why languages built 30 years ago in a world where the Internet barely existed would be accidentally ideal for AI agents in 2026 so we can say the whole field is solved for good (and no, I don't think the amount of training data on those languages seals the fate because that status is ephemeral and also it's not clear training on one language corpus isn't transferrable to other languages).
It links to the bench.cy, but nothing explains how the others were measured. It seems that they're including some start-up time in some that dominates, but not explaining whether it's realistic to be needing to spend that.
What libraries exist.
What's package management system.
How does it interop with existing code?
Is there a JSON parser, an XML parser? Crypto algorithms? Database drivers?
People who invent languages from scratch inherit the technical debt of recreating the entire software ecosystem.
It looks like they are just pulling from the internet at the top of source files:
`use rl 'https://mycdn.com/raylib'`
Good luck with securing that. At least JavaScript has the sense to put it all in a single config file.