[AvAn12]

aren't programming languages like SQL designed to strike a quasi-optimal balance between precision and economy? that is to say, if I want to use plain English to specify some kind of data operations, the prompt will necessarily be more verbose and/or less specific than SQL statements. So why not just learn SQL properly? And then learn the domain-specific considerations of the source data as well as the domain-specific business requirements? Or am I missing something essential?

[da_chicken]

For all it's flaws, I certainly prefer SQL to something like XQuery.

[zwaps]

Yes you are. I can show you 15 line SQL queries you would be hard pressed to understand, let alone built with precision as a novice

And you want everyone to learn this? People who don’t even have time or ability to master excel?

Really?

[da_chicken]

It's hard because relational algebra is hard. It's hard because it's easy to write a query that returns arbitrary data, but it's hard to write a query that returns only the correct data that you really want.

The problem is that, IMX, AI is just as shit at that as most humans are. AI can find and connect primary keys and columns with the same name. It doesn't understand cardinality of entities or how to look for data that breaks the data model of the application (which is a critical element of data validation).

None of the actual hard parts of writing SQL go away with AI.