eh, i really did look for a joke. all i see is a “well actually” opinion that somebody here probably holds

Yes if you remove all frivolity I’m sure the joke will be funnier

I definitely agree on the last point. Personally I like languages where I can get the compiler to check a lot more of my reasoning, but I still want to be able to use all the memory management techniques that people use in C.

I remember Jonathan Blow did a fairly rambling stream of consciousness talk on his criticisms of Rust, and it was largely written off as “old man yells at clouds”, but I tried to make sense of what he was saying and eventually realised he had a lot of good points.

I think it was this one: https://m.youtube.com/watch?v=4t1K66dMhWk

That’s what std::move does, and you’re right that it’s quite an ugly hack to deal with C++ legacy mistakes that C doesn’t have.

I say move semantics to refer to the broader concept, which exists to make manual memory management safer and easier to get right. It’s also a core feature of Rust.

Also I’m talking about parametric polymorphism, not subtype polymorphism. So I mean things like lists, queues and maps which can be specialised for the element type. That’s what I can’t imagine living without.

I would have said the same thing a few years ago, but after writing C++ professionally for a while I have to grudgingly admit that most of the new features are very useful for writing simpler code.

A few are still infuriating though, and I still consider the language an abomination. It has too many awful legacy problems that can never be fixed.

The only conceivable way to avoid pointers in C is by using indices into arrays, which have the exact same set of problems that pointers do because array indexing and pointer dereferencing are the same thing. If anything array indexing is slightly worse, because the index doesn’t carry a type.

Also you’re ignoring a whole host of other problems in C. Most notably unions.

People say that “you only need to learn pointers”, but that’s not a real thing you can do. It’s like saying it’s easy to write correct brainfuck because the language spec is so small. The exact opposite is true.

I’m not a fan of C++, but move semantics seem very clearly like a solution to a problem that C invented.

Though to be honest I could live with manual memory management. What I really don’t understand is how anyone can bear to use C after rewriting the same monomorphic collection type for the 20th time.

They are both doomed because neither is transformative enough to justify adoption. They are going to need to solve much harder problems to do that.

Take Rust as an example. It solved a problem that most people weren’t even paying attention to, because the accepted wisdom said it was impossible.

Mojo’s starting point is absurdly complex. Seems very obviously doomed to me.

Julia is a very clever design, but it still never felt that pleasant to use. I think it was held back by using llvm as a JIT, and by the single-minded focus on data science. Programming languages need to be more opportunistic than that to succeed, imo.

The github blurb says the language is comparable to general purpose languages like python and haskell.

Perhaps unintentionally, this seems to imply that the language can speed up literally any algorithm linearly with core count, which is impossible.

If it can automatically accelerate a program that has parallel data dependencies, that would also be a huge claim, but one that is at least theoretically possible.

Out of the ones you listed I’d suggest Julia or Clojure. They are simple and have interactive modes you can use to experiment easily.

Experienced programmers often undersell the value of interactive prompts because they don’t need them as much. They already have a detailed mental model of how most languages behave.

Another thing: although Julia and Clojure are simple, they are also quite obscure and have very experimental designs. Python might be a better choice. From a beginner’s perspective it’s very similar to Julia, but it’s vastly more popular and lots of people learn it as their first language.

Based on the languages you found, I’m guessing you were looking for something simple and elegant. I think Python fits this description too.

How did they ask all these random people and not bother to ask a single software engineer?

“Hi is this excuse real, or is it just a sign of an inappropriate relationship between the local council and a dodgy software company that pays more dividends than developers? Oh it’s the latter? Okay, thanks.”

You can argue about productivity and “progress” all you like, but none of that will raise you back into my good opinion.

Why would you quote this and then immediately argue about productivity and progress?

In my opinion dependency injection solves a problem that doesn’t need to exist, and does it by adding even more obfuscation and complexity.

The problem is that the original gang of four design patterns had very little to say about managing effects. In old java code things like network and file IO often happen deep inside the object graph, hidden behind multiple impenetrable abstractions such that it’s impossible to run the logic without triggering the effect.

The wrong solution is to add even more obfuscation and abstraction, so that you can inject replacement classes deep inside the object graph where the effects happen. it solves the immediate problem of implementing tests, but makes everything else worse and more confusing.

The right solution is to surface all your effects at the top level of the call graph. The logic only generates data, and passes it back up to the top level of the program. The top level code then decides whether to feed this data into an effectful operation. Now all your code is easier to reason about, and in you can easily test the logic without triggering unwanted effects.

They are not stupid at all. Their interests are in conflict with the interests of tech workers and they are winning effortlessly, over and over again.

The big tech companies are all owned by the same people. If these layoffs cause google to lose market share to another company, it’s fine because they own that company too.

What matters is coordinating regular layoffs across the whole industry to reduce labour costs. It’s the same principle as a strike: if the whole industry does layoffs, workers gradually have to accept lower salaries. In other words, the employers are unionised and the employees are not.

This process will probably continue for the next 20 years, until tech workers have low salaries and no job security. It has happened to countless industries before, and I doubt we are special.

I’m sure the next big industries will be technology-focused, but that’s not the same as “tech”. They won’t involve people being paid $200k to write websites in ruby.

“As we’ve said, we’re responsibly investing in our company’s biggest priorities and the significant opportunities ahead,” said Google spokesperson Alex García-Kummert. “To best position us for these opportunities, throughout the second half of 2023 and into 2024, a number of our teams made changes to become more efficient and work better, remove layers, and align their resources to their biggest product priorities. Through this, we’re simplifying our structures to give employees more opportunity to work on our most innovative and important advances and our biggest company priorities, while reducing bureaucracy and layers”

There was this incredible management consultant in france in the 18th century. Name eludes me, but if he was still around Google could hire him and start finding some far more convincing efficiencies.

The guy was especially good at aligning resources to remove layers

I believe Mercury is intended to be comparable to languages like Java, C# and Ocaml, in terms of the performance profile and generality. I don’t know what it’s like in practice though.

I view it more as a fascinating proof of concept than a language I’d actually like to use. Really I just want new projects to steal ideas from it.

Datalog is sometimes used as an alternative to SQL. Prolog is used by researchers experimenting with rule systems (e.g. type systems, theorem provers, etc).

Mercury has been used to write regular desktop software, with a couple of notable successes.

One way to think about Mercury is that it’s like Haskell, except it’s so declarative that the functions can run backwards, generating arguments from return values! Obviously that comes with some pretty big caveats, but in many cases it works great and is extremely useful.

Prolog, Mercury, Datalog. Very of intrigued by Verse now that I know it has some logic programming features.

Mercury is, roughly, a fusion of Haskell and Prolog. Bizarre and fascinating.

Prolog and Datalog are great but not aimed at general purpose programming.

Really I just want to see more people trying to adapt ideas from logic programming for general purpose use. Logic programming feels truly magic at times, in a way that other paradigms do not (to me at least).

Literally any logic programming language