One of the things that taught me the most about SQL is trying to use Hibernate (There's not enough expletives in the english language to describe that thing).

It's one thing to have a query language (DDL and DML no less) that was built for a different use case than how it's used today (eg: it's not really composable). But then you stack a completely different layer on top that tries to abstract across many relational DBs - and it multiplies the cognitive surface area significantly. It makes you become an expert at Hibernate (JPA), then learn a lot about SQL, then learn even more about how it maps into a particular dialect of SQL.

After a while you realize that the damn ORM isn't really buying you very much, and that you're often just better off writing that non-composable boring SQL by hand.

- assuming you have a decent testing infrastructure in place. Much of the supposed benefit of ORMs is about a form of psuedo-type safety, and making it easier to add more fields. If you have fast running tests that exercise the SQL layer, you might find those benefits aren't very compelling since you have such rapid feedback for your plain SQL anyway.

I've almost never changed the vendor of DB in a project, so that's another supposed benefit that doesn't buy me much. I have often wanted to use vendor-specific functionality however, and often find an ORM gets in the way of that.

To sum it up - I agree completely. If it's your job to wrangle an SQL DB - you ought to learn some SQL.

> because understanding the thing your ORM is abstracting away for you allows you to more intelligently use those abstractions

If that's required, then you are working with a bad abstraction. (Which in the case of ORMs you'll probably find many people arguing that they are often bad abstractions.)

I agree in a sense but I'm primarily a front end dev. Our backend devs (whose SQL skills are probably on par with mine) maintain the DB tables and such using our ORM but I would still need to use the ORM to query the DB. I'll hop in and make a DB update on the backend if I need to, but my point is that many front end devs are probably just using the ORM to query and run mutations. Such queries could certainly be optimized a bit by knowing a bit of SQL (adding indices to commonly queried cols for example) but I'd still consider solid knowledge in SQL to be a solely backend thing.

That said, I do know enough basic SQL to understand what ORMs are doing at a high level, but because I almost never write SQL I wouldn't consider myself proficient in it.

> if you're primary role is to write software which interacts with a SQL database you should understand how to interact directly with that database.

I agree that there should be a general understanding one should be able to interact with it when needed. But at the same time I don't think devs need to be able to spit out queries with the right syntax on the spot in an interview setting.

Not everyone wants to make that much money.

I agree. I know _basic_ SQL but because I don't work with it every day I don't consider myself proficient. I read the migration files generated by my ORMs just out of curiosity and to make sure it's not doing anything crazy, but I wouldn't be able to write the migration file myself.

Interesting. The reason I like ORMs is because of type generation in TypeScript. I've never worked in a company that didn't use an ORM which is likely why I prefer it. But if I ever did work in a company that used raw SQL I'd probably just suck it up and learn better SQL. Maybe then I'd be able to make a more informed opinion.

With regards to SQL being low level, I primarily work with TypeScript so a language that talks directly with the DB (SQL) seems pretty low level compared to TS. I'm not sure what you mean by an ordinary programming language though (obviously not machine code).

I’ve written manual SQL for years in previous roles, but because I haven’t touched it in 6 months I’d have had to double check how to write that with a quick google. It’s just a bad interview technique to require write learned syntax.

Thanks! I think I was (conceptually) missing the constraint/references part. Prior to that I had only worked with firebase and Mongo so I was just like "OK so I just put userID column on post table right?" and apparently no, not right, lol.

What's nice about prisma and hasura is that you can actually read the sql migration files generated, and you can set the logging to a level where you can read the sql being run when performing a query or mutation. I found that helpful to understand how sql is written, but since I'm not actually writing it I can't claim proficiency. But I can understand it.

Every startup I've worked at has at least done their first few MVPs using an ORM. I imagine because it's just a quick way to bootstrap a project. Since performance isn't really an issue before scale, sql vs ORM is just a matter of dev velocity, but I guess at scale most companies just never repaid the tech debt.

With NOSQL becoming more ubiquitous (for better or worse), it's not unfathomable that someone simply never had an opportunity to do something as simple write a join between two tables. Someone replied to my comment and taught me how in 5 lines of code. I read it and I'm like, oh that makes sense. Cool. I won't remember it exactly but I understand it. I wouldn't hold it against a front-end developer who's only ever worked with Vue to understand what happens when a React node rerenders.

My point is that there are acceptable levels of abstraction in all parts of software. Some companies will have different tolerances for understanding of that abstraction. Maybe they want a front-end dev to understand the CSS generated from tailwind. Or maybe they want them to know exactly what happens when a React node is rerendered. Or maybe the company doesn't care as long as the person is demonstrably productive and efficient at building stuff. What some consider basic knowledge can be considered irrelevant to others. Whether or not that has lasting consequences is to be seen, but that just brings us full circle back to the original problem at hand (is it good that people can vibe code something and not understand the code it generates)

It's because it's logically in the wrong order, it should be:

   FROM Users 
   WHERE Type = 'Foo'
   SELECT id, name

You probably have the reverse problem, it doesn't fit your mental model which is in fact the right logical model.

It gets even worse when you add LIMIT/TOP or GROUP BY. SQL is great in a lot of ways, but logically not very consistent. And UPDATE now I think about it, in SQL Server you get this bizarreness:

    UPDATE u
    SET u.Type = 'Bar'
    FROM Users u
    JOIN Company c on u.companyId = c.id
    WHERE c.name = 'Baz'

1000%. It’s all about limiting those round trips to the database…

You actually confirmed that rails is slow if the optimization is on the database server and doing data mangling in ruby is less efficient

Having a quick answer is different than internalizing some domain, especially when you may need to argue about it or propose some novel method. The former can work if you know the right question, but that's just as difficult as knowing the answer.

And most things that are useful daily is not pure knowledge. It's adapting the latter to the current circumstances (aka making tradeoffs). Coding is where pure knowledge shines and it's the easiest part. Before that comes designing a solution and fitting it to the current architecture and that's where judgement and domain knowledge are important.

I may sound ignorant but if you delegate your knowledge to LLMs you'll stay ignorant. Learning is a never ending journey, you can chat about a problem with a non deterministic stocastic compressor with stale knowledge, no problem but don't call it education. Core domain knowledge still makes people successful not chatting skills. Sure if you have deep domain knowledge you can still benefinit AI filling the tedious details, I'm not anti AI

I don't think these are comparable though. Compiler generation is deterministic and more or less provably correct. LLM code is a mile away from that.

Apart from the whole argument about compilers being deterministic and not LLMS.

You don't collaborate on compiled code. They are artifacts. But you're collaborating on source code, so whatever you write, someone else (or you in the future) will need to understand it and alter it. That's what the whole maintainability, testability,... is about. And that's why code is a liability, because it takes times for someone else to understand it. So the less you write, the better it is (there's some tradeoffs about complexity).

I mean maybe these juniors are geniuses, but I often find it very non-obvious why LLM-generated code it wrong and it requires me to have an even deeper knowledge. Sometimes the code is correct, but overly complicated.

One small example was a coworker that generated random numbers with AI using `dd count=30 if=/dev/urandom | tr -c "[a-z][A-Z]" | base64 | head -c20` instead of just `head -c20 /dev/urandom | base64`. I didn't actually know `dd` beyond that it's used for writing to usb-sticks, but I suddenly became really unsure if I was missing something and needing to double check the documentation. All that to say that I think if you vibe-code, you really need to know what you're generating and to keep in mind that other will need to be able to read and understand what you've written.

Perl is just Python with bad handwriting