Earlier quoted context omitted.
> Claude and GPT regularly write programs that are way better than what I would’ve written Is that really true? Like, if you took the time to plan it carefully, dot every i, cross every t? The way I think of LLM's is as "median targeters" -- they reliably produce output at the centre of the bell curve from their training set. So if you're working in a language that you're unfamiliar with -- let's say I wanted to make…
A lot of computer users are domain experts in something like chemistry or physics or material science. Computing to them is just a tool in their field, e.g. simulating molecular dynamics, or radiation transfer. They dot every i and cross every t _in_their_competency_domain_, but the underlying code may be a horrible FORTRAN mess. LLMs potentially can help them write modern code using modern libraries and tooling. My…
Consider calculators: Their consistency and adherence to requirements was necessary for adoption. Nobody would be using them if they gave unpredictable wrong answers, or where calculations involving 420 and 69 somehow keep yielding 5318008. (To be read upside-down, of course.)