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Getting AI to write good SQL

(cloud.google.com)
478 points richards | 4 comments | 16 May 25 21:10 UTC | HN request time: 0.602s | 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.

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1. hosel ◴[17 May 25 01:00 UTC] No.44011204[source]▶
Really? In my experience it’s been pretty good (using Pydantic)! I read over before I execute it, but it’s never done anything malicious.
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2. rectang ◴[17 May 25 01:10 UTC] No.44011259[source]▶
I don't trust myself to craft a prompt in natural language which completely specifies my intent as codified with the precision of a programming language.

I also tend to turn to AI for advising me on difficult use cases, and most of the time it's for production code rather than one-offs. The easy cases, I just write myself because it's more mental effort to review code for subtle errors than it is to write it.

3. ◴[17 May 25 01:29 UTC] No.44011340[source]▶
4. yahoozoo ◴[17 May 25 11:16 UTC] No.44013480[source]▶
What is the relevance of Pydantic with SQL?