Yes - of course there is!

You're totally right!

But that semantic difference does not exist in most languages.

For good reason.

That 'semantic difference' only matters in a specific context - wherein you need to have the difference, usually for performance reasons.

There's no need to expose that semantic difference in the surface language, in most cases.

And that 'semantic difference' requires an enormous amount of thinking to process across the system. It's a huge amount of possibly unnecessary work.

Making the AI have to deal with that layer of design concern is a big cost you only want to deal with if it's worth paying the price.

If the computer (AI or not) provided you with that convenience, you'd never want to deal with a human for a given task.

The 'mischaracterization' of AI as human - now that's annoying. We probably should not submit answers by AI in the form of human identities.

If you call a helpdesk agent - they have to query the system to pull up your case.

The UX is a bit different now.

That's it.

Your 'anthropomorphising projectION' here is the issue, not the person using basic tools to help you - as they always have.

In the OP article, they mention 'don't need to worry about thread cause the concept does not exist' - well, & does not exist in Python.

Those things are related to low-level computational issues (memory management) not problems space issues (moving money, transcoding the file, checking the spreadsheet), so a lot of &/&mut etc. and all that extra thinking slows down AI for the same reason it slows down you and I.

In particular, building in rust requires us to think a bit different about how we create the program in the first place and I don't think AI is very good at architecture yet.

Probably ... eventually none of this will really matter though, it will just be like 'compiler pedantry' for the small number of people who work on those things.

I don't really buy the intuition (aka Goroutines are more 'clear' than 'coloured' functions or threads), and there's no evidence presented for this either.

Although this could very well be true, I'm doubtful without seeing some real world data points.

The 'general premise' aka 'cosine similarity' may have been true before bit it may not be that anymore.

AI just pretty good at anything it's 'seen enough' and that's it, I think it's more likely a 'threshold' problem than an ability problem, at least for most things.

'Rust' may represent a different domain, given the very detailed nature of notation and the vast possibilities that arise from that.

LLMs + Harnesses are incredibly effective, as evidenced by the literal millions of people who are paying quite a lot to use them, who speak glowingly of them and would 'never go back'.

Whatever 'shape they take' - they are obviously useful - ergo - 'you're doing something wrong' if you can't make use of them for most tasks.

Mileage varies, there are downsides, but it's the same with anything.

The 'tool of the system' analogy is not an unreasonable point of discussion but it does not help us in this scenario.

Even with the few 'tell tale' patterns it's been leaving ... that threshold is being moved past quite quickly. Within not even 6 months, works will be identical for all bus some specific activities.

[1] https://www.sciencedirect.com/science/article/pii/S147738802... [2] https://link.springer.com/article/10.1186/s41077-025-00396-6...

People are hallucinating on this thread.

That people will say 'Code Me An App' and expect some kind of magical results, will be more common than not, but it's no way evidence that the AI can't code.

Given a sufficiently detailed prompt, the AI will produce almost whatever you ask it within a certain scale.

As sure as the sky is blue.

And it will make perfectly compilable code usually on the first prompt.

Obviously, it can code.

Obviously, it can 'synthetically reason' about the code.

You can point it an arbitrary code base and it will give a better overall assessment than most humans.

Is it fallible? Obviously. Is it limited in scope? Obviously.

"Not by our human definition of perfect."?

'Human definition' has nothing to do with it.

Your job is to define what you want, to the extent you can do that, the AI does really well at a certain scale, at the 'functional' scale, nearly perfectly.

"We went back to shovelling by hand because someone ran over the pole with the front-loader, even though he had no experience driving it."

This is definitely user error; obviously it's a hard tool to wrangle but it's entirely possible to use it safely.

Why on earth would we ever remotely compare a 'tool' to 'a software engineer' ?

The 'great delusion' is not that 'AI can't code' - because obviously it can, and very well.

The problem is the 'anthropomorphism' and all this AGI nonsense.

If we called it 'Stochastic Mechanisms' and did not 'personalize' our prompts, refer to them as 'chat' or give them 'personalities' but remained in the domain of 'Stochastic Language CLI' ... then our metaphors would pbably not cloud our judgments.

Let the philosophers argue about AGI.

Agents code extremely well.

They're not particularly good at 'architecture' and I think that's where his specific concerns about 'not being able to see the problems' arise - the issues are are almost never in the syntax, because the AI writes perfect code. The issue is that it's not doing exactly what you intended.

Instead of 'missing the target' ... it's 'hit the wrong target perfectly'.

Any senior developer working with AI daily should be able to have a baseline intuition for all of this, and would therefore reject the hyperbole of the premise 'it can't code!'.

Of course it's producing gargantuan amounts of slop - that's not because 'it can't code', that's something else entirely.

It's ridiculous to suggest that 'AI can't code' - when the entire development world has moved into agentic coding, including all of the best developers in the world, and it's yielding positive results in most scenarios.

It's a callow 'bad twitter take' the length of an article.

He's not wrong to suggest that IA is a 'stochastic mechanism' over all the code that's ever been written, but that's evidence of the mechanism, and frankly, describe how it is able to code.

And yes - organizations will misappropriate AI at scale as they do with everything.

His premise is so far out of proportion and misguided, it's tantamount to 'fake moon landing' conspiracy theory.

Agents now are writing extremely consistent, normalized canonical code, that usually compiles the first time.

Right out of the 'textbook'.

For what it's trying to do - it writes nearly perfect code.

The only thing you could nominally disagree with are some of the conventions and idioms.

It 'writes a perfect novel, in perfect prose'.

What it will not do however, is 'write the novel that's in your head'.

And that's the crux of it.

It's not even your job to 'write code' at this point, but rather to be the storyteller - and a very good editor who has enough taste and grasp of gammar to be able to know when it's going awry.

It will make mostly what you tell it too, the quality of the output is the quality of your guidance, but at the lowest levels it's generating extremely high quality syntactic prose.

I don't understand how it's remotely reasonable to try to make the comparison.

In other words - they can program, and probably better than you.

I don't like being too critical but this is a really superficial post - as if either 'AI is a Software Engineer - or - It must be Fraud'

It's an extremely powerful tool that is very 'pattern oriented' and with guidance can absolutely write great code - and even across modules given the right basis.

It's also great at so many other tasks - finding bugs in big code bases, doing migrations etc.

It's not going to make very goo architectural decisions for you, and if you're doing anything novel you have to read most of the code ... but that's too be expected.

If they had a CS degree, and were generally decent communicators and 'responsible actors' ... and could not get a job - now that's a problem.