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- Hacker News
- > In the AI age, understanding these concepts becomes more important, not less—they are what separate those who merely prompt from those who truly engineer.
But doesn't that sound like cope? It's like an old ASM programmer telling himself that his obscure assembly knowledge will surely still give him great advantages as he is forced to switch to React.js development.
by cubefox - >It's like an old ASM programmer telling himself that his obscure assembly knowledge will surely still give him great advantages as he is forced to switch to React.js development.
The engineers that are truly skilled in writing pure assembly wouldn't be forced to switch to React. The existence of higher level languages doesn't mean lower level languages are useless.
by yuye - I think a lot of folks in the industry are feeling this way. It’s an existential crisis for many of us right now. Why bother progressing when slop is “good enough”? Some of us still care but I have a feeling there are a lot of people that don’t.by alpha_trion
- There's very little evidence, if any, to suggest that slop is actually "good enough". I have interacted with multiple apps that clearly were written using AI by people who did not actually spend the time understanding what was made, and it most certainly was not an experience that I would classify as "good enough".
I know this may be some kind of reverse survivorship bias and that I simply do not notice all of the slop around me that somehow is truly "good enough", but I think I need to see some concrete examples to convince me.
- Good enough IFF you are dealing with a cute web app or simple SAAS or something.
Software engineers feeling down should think about software designed to track medication administration, or validate their tax calculations, or to decide whether to flag you for a CIFAS marker, or whatever, and then imagine the generic "fuck it, that'll do" type vibecoder-level-engineer handling the code.
by kusokurae - English has become the new programming languageby remiminnebo
- Why stop there though? My harness writes WAT directly and compiles with wasmtime.
It’s very fast and very difficult to read.
by lwansbrough - My big problem is that nobody is working on truly innovative programming languages anymore.
Everyone wants to build another iteration of a C style language with incremental improvement for little benefit.
The problem is that we probably reached the general purpose frontier a long time ago and there are just a few surface level things that need to be changed here and there, which is not worth a whole new language.
It goes against the programmer's ego, but the way forward is by adding more restrictions. The people complaining about the borrow checker in Rust just don't get it. If you want programming to improve, you will have to give up the ability to write every conceivable program.
by imtringued - >My big problem is that nobody is working on truly innovative programming languages anymore.
How many languages are truly innovative? I'd say the most recent example is Rust, as you mentioned, being innovative with its borrow checker, but what other recent languages really are?
Many modern languages are not innovative, but just add quality of life features. A good example is Kotlin: Just another JVM language, nothing revolutionary, but I enjoy writing it over Java.
>It goes against the programmer's ego, but the way forward is by adding more restrictions. The people complaining about the borrow checker in Rust just don't get it. If you want programming to improve, you will have to give up the ability to write every conceivable program.
I agree and also disagree. The "ability to write every conceivable program" also means writing programs that are faulty. Maybe that's your point, in which case I don't consider it a bad thing to limit the ability to do so.
A language like C let's you fuck around and find out. It's powerful and "easy". As the saying goes, it gives you a gun and doesn't stop you from shooting yourself in the foot.
by yuye
You can learn relatively well any programming language in a week. You don't need to master "language intricacies".> Why spend years mastering language intricacies when an AI can generate code in any language on demand?by jagadaga- I think PL will have a second coming. Just like Linus Torvalds said:
> AI is a productivity tool exactly like compilers were. Compilers boosted programming by 1000x. AI adds another 10x on top. Enormous. But nobody says "the compiler wrote my code."
We witness more and more PL ideas re-invented in Agentic AI world. Branching, looping, task orchestration, workflow, etc.
Heck even GOTO seems tempting these days.
by est - You should care about programming languages because humans are still better at programming than an LLM (yes, even better than $currrent_newest_model). And if you care about what you are making, you should be writing the code yourself. If you don't care about making something good, then yeah you don't need to actually learn how to program, but that's no way to work.by bigstrat2003
- Any and all discussion that suggests the deprecation of human-held domain-specific, manually-able knowledge & skill, on the basis of LLM capacity, is propaganda.by kusokurae
- There's a lot that's worth thinking about and discussing on this topic, but it's too loaded with emotional stuff for many people to hope for a productive discussion.
I'm a programming languages nerd. I was paid to program in over 20 different languages over my 25 year career. I read up on many more languages along the way, and I wrote pet projects in a few of those. I've written a couple assemblers, compilers, and interpreters for my own languages.
I think literally everyone should be taught to program in elementary school. It's arguably one of the best ways to teach logical thought and careful organization of ideas. I like Alan Perlis's quote: You think you know when you can learn, are more sure when you can write, even more when you can teach, but certain when you can program.
With all of that out of the way, I think there are interesting questions to ask going forward:
If you were starting a business for a great software idea, with your own savings on the line, would you hire 10 AI hostile programmers to implement the idea or 2 AI friendly people and get them some subscriptions to the top models? Remember: if it doesn't come together, it's YOUR money on the line.
What are the best programming languages for LLMs to program with? Could someone design a better language that fits their strengths and weaknesses? I think the most popular human languages have way too much affordance for concerns that don't apply to models. I think letting LLMs program in human friendly languages makes the results more difficult for humans to inspect. There's a slight chicken and egg problem based on the training sets used by large models, but this can be addressed with LoRA tuning and similar techniques for open weight models.
How can we make LLMs scale better so that people who don't like to program can get better "vibe coding" results? Tools like Excel are huge force multipliers for so many people who aren't interested in writing traditional code. I think it should be possible for non-programmers to solve their own problems and trust the results without becoming programmers.
Anyways, I've got my own partially formed answers to those questions, but I'd like to hear what other people who aren't still suffering stages of LLM programming grief have to say and ask.
by xscott - I agree. I believe LLMs are ushering in a new golden age for programming language design and implementation.by kfreds
- why would you even hire 2 AI friendly people when you could just prompt it yourself? we wouldn't even need you anymore
- > I think letting LLMs program in human friendly languages makes the results more difficult for humans to inspect.
Does it? I think for example Ruby seems to work quite well with LLMs in this regard. Or is this not what you would consider human friendly?
by steve1977 - IMHO, we need programming (formal) metalanguage, not just another language. Something in which can express e.g. an architectural discussion with LLM.
Natural languages are not logically sound, because meaning of words can shift. We need to express ideas about programs, desired properties, and specification in a language that is semantically sound and thus gives consistent solutions to consistent requirements.
Of course, the metalanguage can have the same foundation as the programming language itself. It could be expressed in Lean for instance.
What is needed is to build a library of abstractions in the metalanguage that are similar to words understood by an LLM, but in a logically consistent manner.
by js8 - > If you were starting a business for a great software idea, with your own savings on the line, would you hire 10 AI hostile programmers to implement the idea or 2 AI friendly people and get them some subscriptions to the top models? Remember: if it doesn't come together, it's YOUR money on the line.
Actually a pretty interesting question. I think it depends on the software, if it's some web app or something fairly trivial and mechanical the AI friendly devs would probably be cheaper and faster. If it was like, a robotics platform or something I would hire the 10 AI hostile devs. But ideally I would hire 5 expert programmers who use AI in a pragmatic way.
by slopinthebag - As a side note, I previously commented somewhere else that, if a language has a terse way and a verbose way to do the same thing, preferring the terse way might be more economical because it saves bunch of tokens for the LLM. But for humans to review the code, we may need some mechanism to translate the code from terse way to the verbose way, if the human has a hard time understanding the terse code.
> If you were starting a business for a great software idea, with your own savings on the line, would you hire 10 AI hostile programmers to implement the idea or 2 AI friendly people and get them some subscriptions to the top models? Remember: if it doesn't come together, it's YOUR money on the line.
I know quite a few non-technical people that started vibe-coding this year and got good results for their ideas. What language did they use? They just asked the AI what language or tool would be best for the idea, then followed the AI's suggestions. All the setup, configuration etc. were done by the AI. They learned a bunch of things along the way, but their main focus is still on the big picture idea, not the technical details. After the project is done, they are still not technical experts, but at least they have something to run with in the real world.
by wwind123 - > If you were starting a business for a great software idea, with your own savings on the line, would you hire 10 AI hostile programmers to implement the idea or 2 AI friendly people and get them some subscriptions to the top models?
Are you saying that 10 programmers cost as much as 2 random people and some LLM subscriptions? Sign me up for the 10 programmers, then. I wouldn’t even need most of them, I’ve done a lot with teams of two and three, and more may just get in the way. I couldn’t care less how “AI friendly” the other people are; if they’re not programmers, using LLMs to produce a program is going to lead to bad results. Why would I even hire them? Might as well do the prompting myself if the results are that good in your fantasy scenario.
> Remember: if it doesn't come together, it's YOUR money on the line.
So, if it doesn’t come together, I either empowered 10 people to feed their families, gave them opportunities to hone their skills, and possibly developed new friendships and contacts for future endeavours (where maybe next time they’ll even hire me); or I helped just 2 people with no return and lined the pockets of rich people who are actively exploiting everyone else and destroying the environment and social trust for personal profit.
Your scenario is truly bizarre. Is it just an obvious ploy to detect those who lack in empathy and only think of personal profit?
by latexr - If an LLM actually does think like a human, humans benefit from good programming languages, why wouldn’t an LLM?
Programming languages allow LLMs to build invariants they can’t enforce themselves (type systems), reduce context window (syntax sugar) and represent abstract models in a way that may improve understanding i.e. increase the likelihood of predicting a correct next token.
Plus, we want to understand LLM output, so it should at least be convertible into a language that’s easy for humans.
EDIT: and actually reading the article, learning a new programming paradigm improves your ability to model even in your head, by noticing some abstract thing fits some programming concept, then manipulating the concept (e.g. translation your data model into the algebraic data type,`(a | b) * (a | c)`, then realizing it’s isomorphic to `a * (b | c)`).
- Yep, it helps llms, and the same is true for libraries. Technically neither are necessary. Imagine an llm that's restricted to assembly.by trinari
- Can't remember who said it, but I think the most poignant commentary about the prospects of LLMs completely replacing humans is the simple observation that yes, you can delegate many if not all of your tasks requiring thinking to LLMs, but it is inherently impossible to delegate the task of understanding. If you hope to write an efficient prompt which gives you what you think you want, you need to actually understand what you want, which also requires you to understand what you currently have. Programming languages are a medium for transferring and - not the least - maintaining shared understanding of a software system in terms of the basic abstractions that the programming language provides. The need for good programming languages does not go away just because we use LLMs to write the code, on the contrary: would you rather review LLM-written assembly or LLM-written Haskell?
- Do you understand every line of code written by everyone else on your team? I doubt it. But if you ever need to work with their code, that's when you might need to understand it. So, treat an AI agent like another teammate.by jagadaga
- That was Yacine Twitter account and it’s false. You can delegate the task of understanding. This looks like a popular folk theory that also falls under scrutiny.by simianwords
- The original quote is from Andrej Karpathy as far as I remember. I do like a lot of his ideas but try to take them with a pinch of salt as he clearly has a technocratic bias regarding LLMs/AI.by Nekorosu
- That’s a little black and white though. It’s ruling out that the AI could make a pretty good guess as to what you likely wanted to convey. If it gets that right, then you didn’t need to understand it nearly much.
When I observe its reasoning I see it doing this all the time.
by hcfman - we are already at the point where AI proponents are planning to have the review cycle be replaced by llms
- > would you rather review LLM-written assembly or LLM-written Haskell?
I wish we had a language that was targeted specifically for LLMs to write and humans and LLMs to inspect:
- Simple robust syntax
- One obvious way to do things
- Static type checking
- Purely functional encouraged, escape hatches for performance
- Inspect-able, testable, and reviewable in small pieces
- Something like formal predicates, preconditions, post-conditions, assertions, or effects typing
Giving LLMs all the surface area of Python, JavaScript, TypeScript, or C++ seems like a huge mistake. It's amazing it works as well as it does. Well written Haskell is beautiful, but there are way too many ways to write Haskell:
https://people.willamette.edu/~fruehr/haskell/evolution.html
by xscott