I wish developers would make use of long table names and column names. For example, pcat_extension could have been named release_schema_1_0.product_category_extension. And cat_id2 could have been named category_id2.
Getting AI to write good SQL
181–190 of 379 posts
Re: Getting AI to write good SQL
#182The article comments "out of the box, LLMs are particularly good at tasks like creative writing" but I think this actually demonstrates the problem with the ai. A writer won't think that they're good at creative writing. In fact, I'm pretty sure they'd think LLM's are terrible at creative writing. In other words, to an expert in their field, they're not that good - at least not yet. But to someone who is not an exper…
Yes, but why is then everyone on HN claiming LLMs can code on expert level?
Re: Getting AI to write good SQL
#183The article comments "out of the box, LLMs are particularly good at tasks like creative writing" but I think this actually demonstrates the problem with the ai. A writer won't think that they're good at creative writing. In fact, I'm pretty sure they'd think LLM's are terrible at creative writing. In other words, to an expert in their field, they're not that good - at least not yet. But to someone who is not an exper…
Yes, but why is then everyone on HN claiming LLMs can code on expert level?
Re: Getting AI to write good SQL
#184The game changer for me will be when AI stops hallucinating SDK methods. I often find myself asking ”show me how to do advanced concept X in somewhat niche Y sdk”, and while it produces confident answers, 90% of the time it is suggesting SDK methods that do not exist, so a lot of time is wasted just arguing about that
Then it apologizes and gives the right answer. It's weird. We really need a new work for what they're doing, 'cos it ain't thinking.
Re: Getting AI to write good SQL
#185Earlier quoted context omitted.
https://regex101.com/
That doesn’t answer the question. By “validate”, I mean “prove to yourself that the regular expression is correct”. Much like with program code, you can’t do that by only testing it. You need to understand what the expression actually says.
Of course, there may be cases you didn't think of where it behaves incorrectly. But if that's true, you're just as likely to forget those cases when studying the expression to see "what it actually says". If you have tests, fixing a broken case (once you discover it) is easy to do without breaking the existing cases you care about.
So for me, getting an AI to write a regex, and writing some tests for it (possibly with AI help) is a reasonable way to work.
Re: Getting AI to write good SQL
#186Every once in a while I've been trying AI, since everyone and their mother told me to, so I comply. My recent endevour was with Gemini 2.5: - Write me a simple todo app on cloudflare with auth0 authentication. - Here's a simple todo on cloudflare. We import the @auth0-cloudflare and... - Does that @auth0-cloudflare exists? - Oh, it doesn't. I can give you a walkthrough on how to set up an account on auth0. Would you…
It's difficult to assess how typical your experience is; I tried your initial prompt (`Write me a simple todo app on cloudflare with auth0 authentication.` on gemini-2.5-pro-preview-05-06) and didn't get any mentions of @auth0-cloudfare, although I cannot verify if the answer is working as-is https://pastebin.com/yfg0Zn0u
Re: Getting AI to write good SQL
#187Earlier quoted context omitted.
This comment appears frequently and always surprises me. Do people just... not know regex? It seems so foreign to me. It's not like it's some obscure thing, it's absolutely ubiquitous. Relatively speaking it's not very complicated, it's widely documented, has vast learning resources, and has some of the best ROI of any DSL. It's funny to joke that it looks like line noise, but really, there is not a lot to learn to u…
"It takes far longer to tell an AI what you want than to write a regex yourself." My experience is the exact opposite. Writing anything but the simplest regex by hand still takes me significant time, and I've been using them for decades. Getting an LLM to spit out a regex is so much less work. Especially since an LLM already knows the details of the different potential dialects of regex. I use them to write regexes i…
(REGEXP_MATCHES(commentary,
'!\[\s*([^\]]*?)\s*\]\(\s*([^)]*?)\s*\)', 'g'))[2] AS src,
(REGEXP_MATCHES(commentary,
'!\[\s*([^\]]*?)\s*\]\(\s*([^)]*?)\s*\)', 'g'))[1] AS alt_text
That is just nitpicking a one-off example though, I understand your wider point.I appreciate the LLM is useful for problems outside one's usual scope of comfort. I'm mainly saying that I think it's a skill where the "time economics" really are in favor of learning it and expanding your scope. As in, it does not take a lot learning time before you're faster than the LLM for 90% of things, and those things occur frequently enough that your "learning time deficit" gets repaid quickly. Certainly not the case for all skills, but I truly believe regex is one of them due to its small scope and ubiquitous application. The LLM can be used for the remaining 10% of really complicated cases.
As you've been using regex for decades, there is already a large subset of problems where you're faster than the LLM. So that problem space exists, it's all about how to tune learning time to right-size it for the frequency the problems are encountered. Regex, I think, is simple enough & frequent enough where that works very well.
Re: Getting AI to write good SQL
#188AI text to regex solutions would be incredibly handy.
This comment appears frequently and always surprises me. Do people just... not know regex? It seems so foreign to me. It's not like it's some obscure thing, it's absolutely ubiquitous. Relatively speaking it's not very complicated, it's widely documented, has vast learning resources, and has some of the best ROI of any DSL. It's funny to joke that it looks like line noise, but really, there is not a lot to learn to u…
Whenever I have worked on code smells (performance issues, fuzzy test fails etc), regex was 3rd only to poorly written SQL queries, and/or network latency.
All-in-all, not a good experience for me. Regex is the one task that I almost entirely rely on GitHub Copilot in the 3-4 times a year I have to.
Re: Getting AI to write good SQL
#189Earlier quoted context omitted.
> you get the added benefit of writing queries in JSON instead of raw SQL. I’m sorry, I can’t. The tail is wagging the dog. dang, can you delete my account and scrub my history? I’m serious.
You're right, it's a bit ridiculous. This is a perfect time to use xml instead of json.
JSON:
{"foo": ["bar", 42]}
XON:
foo
bar
42
It gives you all the flexibility of JSON with the mature tooling of XML!Edit: jesus christ, it actually exists https://sevenval.gitbook.io/flat/reference/templating/oxn