Has this thought process ever worked in real life? I know plenty of seniors who still believe everything that comes out of Facebook, be AI or not, and before that it was the TV, radio, newspapers, etc.

Most people choose to believe, which is why they have a hard time confronting facts.

What are you even talking about.

Iraq economy is almost 60% industrial, are they doing better than Ireland? Of course not.

Also, the US is the second largest country by motor vehicle production in the world. And the US GDP is 80% service derived.

The GDP sector composition of most of the largest economies is heavily service biased. So, no.

What does "sufficient clarity" mean? And is it english expressive enough and free of ambiguities? And who is going to review this process, another LLM, with the same biases and shortcomings?

I code for a living, and so far I'm OK with using LLMs to aid in my day to day job. But I wouldn't trust any LLM to produce code of sufficient quality that I would be comfortable deploying it in production without human review and supervision. And most definitely wouldn't task a LLM to just go and rewrite large parts of a product because of a change of specs.

Any examples?

As far as I understand, claims in the current AI cycle are wildly exaggerated, and sometimes companies rely on sort of circular deals to make revenue appear higher than it actually is, e.g. OpenAI and Microsoft or Nvidia. Wouldn't that mean that AI companies are primed to oversell and underdeliver, effectively making the problem even worse?

We also know that Musk has been cozy with the current administration, and spearheaded the very same “efficiency” campaign at show here.

I think it would be naive to blindly believe Musk and the DOD claims and ignore their common history.

Plenty of rewrites out there prove that point.

I don’t follow tabloid style news around software projects, maybe I’m missing on something.

I personally rely on views to reuse base queries and then add filters on top of them.

Where does SQL fall in the video transcoding pipeline?

In my experience, ORMs work well for toy projects, but become cumbersome to maintain in enterprise ones, especially where performance matters. There is a large overlap between engineers who refuse to learn SQL because it's not "convenient", and those who prefer ORMs because they are "easier", resulting in cohorts that don't know how to use either.

But also, I don't see how ORMs make managing large databases any easier, other than those with embedded migration capabilities, which can be very well extracted to their own tools.

Unless we’re assuming here that the BSD community is free from that.

Also, this whole point predicates upon the assumption that ORMs are infallible when translating queries into SQL, which most definitely are not.

Second, an ORM is just a translation layer, i.e. it does not compile to any binary format the database understands, and instead it gets translated to SQL, which is the standard, minus extensions. SQL is ubiquitous. It’s the closest to a lingua franca that we have in the context of software engineering. And I’m going to be blunt here and say that purposefully avoid learning and understanding SQL if it is part of the job, should disqualify anyone from it.

I’ve been around for some decades too, and to me, ORMs haven’t worked out. They are vastly different one from another and they often create issues that are clear as day when the query is written as SQL. If I go from a Typescript codebase to Python to Java, then, according to you, I should learn the intricacies of Sequelize, SQLAlchemy, and JPA/Hibernate, instead of just SQL. And granted, different SQL dialects have different quirks, but more often than not, the pitfalls are more apparent than when switching between ORMs.

And I can guarantee that someone equipped with a good foundation in SQL will be more successful debugging a Sequelize based application, than someone who has relied on SQLAlchemy.

What most people I know and worked with need, is types. Types help glue SQL and any other language together. If I can run any SQL query and the result comes back as an object, I’m good.

Now, if your point is that ORMs are OK for toying around, I may agree, but still, why would I go through that trouble when I know SQL.