I always think the determinism discourse on LLMs is off the point. The elephant in the room is semantic preservation. Compilers can most often preserve semantics across abstractions, while LLMs most often cannot.
For sure the problem isn't that clear-cut, for the siren's call of AI coding is to induce a system out of prompts with ambiguous semantics. It's hardly surprisingly you get unpredictable outcomes when giving ambiguous commands to human collaborators, and that in the case of LLMs they resolve ambiguity with probabilistic approximation.
You can think of comptime (as of zig 0.16) as an interpreter that evaluates code with very limited optimization. So yes, naive use of comptime can definitely grind compilation to a halt.
Zig tackles the halting problem a bit differently by putting the evaluation cutoff in userspace through the compiler builtin function `@setEvalBranchQuota`. You bump up the quota as you see fit.
Did Putin do anything meaningful to stop "NATO's advance" into the Baltic Sea? Maybe Putin was so pacifist that he let Sweden and Finland join the NATO with impunity.
Come back when Americans are routinely jailed for rubbing their elites the wrong way (in some countries, criticisms aren't the only way to rub the leaders the wrong way)
IMO "level" roughly corresponds to the amount of runtime control flow hidden by abstractions. Zig is famous for having almost no hidden runtime control flow, this appears pretty "low level" to many. OTOH, Zig can have highly non-trivial hidden compile time control flow thanks to comptime reflection, but hardly anyone identifies Zig as a "high level" metaprogramming language.
Then it's actually the immature zig ecosystem that rubbed the author the wrong way, not zig the language itself. Not that the ecosystem isn't important, but IMO a language only truly fails you when it doesn't offer the composability and performance characteristics necessary for your solution.
C# is a perfect example of feature envy, but because "Java sucks" C# must be the best thing ever in the world of computing. Orthogonality and coherence be damned.
The Swift ecosystem is pretty amazing too. I've made several PRs and got them merged into Swift Parser while exchanging ideas with Apple employees fruitfully. The only big caveat is there's no guarantee your work will ever be merged into Xcode, meaning most Swift users won't benefit from your work because of Apple's opaque gatekeeping.
XCode evidently cannot keep pace with the rapid development of Swift. Instead of fully embracing community development, Apple maintains a proprietary (dated and divergent) fork of the Swift toolchain in Xcode. For example, check how different compiler diagnostics and suggestions are when using Xcode vs SourceKit LSP. Apple is, once again in its time-honored fashion, wasting collective effort because of its siloed, secrecy-laden development model.
For sure the problem isn't that clear-cut, for the siren's call of AI coding is to induce a system out of prompts with ambiguous semantics. It's hardly surprisingly you get unpredictable outcomes when giving ambiguous commands to human collaborators, and that in the case of LLMs they resolve ambiguity with probabilistic approximation.