I think this is indeed the direction, but am wondering is anyone actually trying it right now? Love to explore it.

I think for now the answer to adaerlangsql+++ is just Rust - but its semantics have always been about human usability.

Humans have this thing where we can only keep 7 things at once and have to juggle our context, but recall seems much more broad than model contexts.

If we were to start designing a language and toolkit based around LLM context sizes, limitations and quirks - how would that look?

Also terseness and operators are one thing, but what if it’s the other way around - English words etc - can have a much bigger vocabulary of things that can be done but can easily be generated on the fly.

For a new LLM language realistically you would need to probably either write or convert a shit ton of software to it first if you are to train an adequate model on top of it …

And also what about “IDEs” for agents? So far they are clumsily using human tools - just looking Claude string along bash loops and greps to try to eek out meaning form code _it itself had written a week ago_ is frankly frustrating.

There must be a better way and some rich agent specific tooling for code exploration and verification.

Anthropic stance has always been “yeah we tested them all, grep is better” but I still am not convinced - just by the fact that it constantly fails one or two attempts before “figuring it out” yeah it’s fast anyway but it could be _faster_ and could allow the agent to “think” in code space more and not have to validate itself at every minute step …