It should be but nothing guarantees you from meeting an interviewer that somehow misunderstands their role and then you will be in a situation when you need to choose what to do next: try to be open or resist. Once during an interview (for a software engineer position) I was asked if I had a family and when I replied that I didn't, I was asked why. You might be able to cut it down in an appropriate way but in a situation of stress (which a job interview represents of course) you might not.
Coding with AI assistants is just a completely different skill that one should not measure from the perspective of comparing it to the way human programmers write code. Mostly everything that we have: programming languages, frameworks, principles of software development in teams, agile/clean code/TDD/DRY and other debatable or well accepted practices — all this exists to overcome limitations of human mind. AI does not have them and have others.
What I found to be useful for complex tasks is to use it as a tool to explore that highly-dimensional space that lies behind the task being solved. It rarely can be described as giving a prompt and coming back for a result. For me it's usually about having winding conversations, writing lists of invariants and partial designs and feeding them back in a loop. Hallucinations and mistakes become a signal that shows whether my understanding of the problem does or does not fit.
Yes, I get your point and I think your arguments are valid, it's just not the whole story.
The thing about programming languages is that both for their creators and advocates a significant part of motivation to drive is emotions and not the rational necessity alone. Learning a new programming language along with its ecosystem is an investment of time and effort, it is something that our brains mark as important and therefore protected (I'm looking at Rust). Now when AI is going to write all the code, that emotional part might eventually dissolve and move to something else, leaving the question of choice of a programming language much less relevant. Like the list of choices Claude Code shows to you in planning mode: "do you wish to use SQLite, PostgreSQL or MySQL as a database for your project?" (*picking the "Recommended" option)
That said, I hope that Zig will make it to version 1.0 before AI turns all the tables and sweeps many things away. It might be my bias and I'm wrong and overestimating the irrational part, then I'll be glad to admit my mistake.
> would you expect a model (assuming it had the same expertise in each language) to make more mistakes in ASM, C, Zig, or Rust?
"assuming it had the same expertise in each language" is the most important part here, because the expertise of AI with these languages is very different. And, honestly, I bet on C here because its code base is the largest, the language itself is the easiest to reason about and we have a lot of excellent tooling that helps mitigate where it falls short.
> I imagine most would agree that ASM/C would be likely to have the most mistakes simply because fewer constraints are enforced as you go closer to the metal.
We need these constraints because we can't reliably track all the necessary details. But AI might be much more capable (read — scalable) in that, so all the complexity that we need to accumulate in a programming language it might just know out of the way it's built.
Innovation doesn't go for the sake of innovation itself. Innovation should serve a purpose. And the purpose of having programming languages is to overcome the limitations of human mind, of our attention span, of our ability to manipulate concepts expressed in abstractions and syntax. We don't know how long we'll need this.
I really like Zig, I wish it appeared several years earlier. But rewriting everything in Zig might just not have practical sense soon.
I call it "the ability to communicate intent [using a programming language]" and suddenly building with AI looks at lot more like the natural extension of what we used to do writing code by ourselves.
At first I thought it's about turning off settings that allow me to watch garbage TV shows (or garbage ending seasons of initially decent TV shows in this case)
MCP is already deterministic. What's huge about it is that it has automatic API discovery and integration built-in. It's a bit rough yet but I think we will only see how it's getting improved more and more.
I don't think we should be surprised by this. A creature that needs to operate its body in 3d environment, perform complex manipulations with objects, participate in social interactions, probably use some sort of planning to optimise pollen harvesting activities has very good chances to be acquainted with the concept of time in one way or another.
What is indeed fascinating is how scientists invent all these experiments
> you can run out of space at one partition, but have lot of free space at another
that's exactly the point — you can run out of space in your /home but that does not affect, for example, /var. or vice versa, log explosion in /var is contained within its own partition and does not clog the entire filesystem.
One could use a trigger for this. All we need is to setup a trigger that would delete all expired records looking at some timestamp column on update. That would eat up some latency but as was said, most projects would find it good enough anyway.