It seems the language would need to be strongly typed, have good error reporting and testing infrastructure, have a good standard library and high-level abstractions, and be "close enough" to existing languages. Go would seem to already fit that bill, any bespoke language you come up with is going to have less exposure in the training set than Go. Maybe Rust as a second, but Go's memory management might be easier for the LLM (and humans) than Rust's.

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wenc 5 hours ago | parent [-]

Rust, Go and TypeScript are good bets.

Python too -- hear me out. With spec-driven development to anchor things, coupled with property-based tests (PBT) using Hypothesis, it's great for prototyping problems.

You wouldn't write mission critical stuff with it, but it has two advantages over so-called "better designed languages": massive ecosystem and massive training.

If your problem involves manipulating dataframes (polars, pandas), plotting (seaborn), and machine learning, Python just can't be beat. You can try using an LLM to generate Rust code for this -- go ahead and try it -- and you'll see how bad it can be.

Better ecosystems and better training can beat better languages in many problem domains.

	▲	Jtsummers 5 hours ago \| parent [-]
		> You wouldn't write mission critical stuff with it People do, they also write mission critical stuff in Lua, TCL, Perl, and plenty of other languages. What they generally won't do is write performance critical stuff in those languages. But there is definitely some critical communication infrastructure out there running with interpreted languages like these out there.