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478 points richards | 1 comments | 16 May 25 21:10 UTC | HN request time: 0.209s | source

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rectang ◴[17 May 25 00:04 UTC] No.44010899[source]▶

> We will cover state-of-the-art [...] how we approach techniques that allows the system to offer virtually certified correct answers.

I don't need AI to generate perfect SQL, because I am never going to trust the output enough to copy/paste it — the risk of subtle semantic errors is too high, even if the code validates.

Instead, I find it helpful for AI to suggest approaches — after which I will manually craft the SQL, starting from scratch.

replies(4): >>44011204 #>>44011349 #>>44011379 #>>44011432 #

paulddraper ◴[17 May 25 01:48 UTC] No.44011432[source]▶

>>44010899 #

Hopefully your trust in yourself is warranted

replies(2): >>44011729 #>>44012314 #

1. rectang ◴[17 May 25 03:01 UTC] No.44011729[source]▶

>>44011432 #

I embrace my fallibility, and enthusiastically pursue testing, code reviews, staging environments, and so on to minimize the mistakes that make it through to production.

It seems to me that this skeptical mindset is consonant with handling AI output with care.

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Getting AI to write good SQL