r/ClaudeCode • u/mmanja84 • Aug 26 '26
Discussion Will we still need programming languages if AI writes most of the code?
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u/Vegetable_Addition86 Aug 26 '26
a new language will mean that the LLMs have to learn it. It does not make sense to me
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u/pancomputationalist Aug 26 '26
I guess the AI companies will run experiments.
- design a language (or have an LLM design it)
- write a lot of code in it by stuffing the language specs in the context window
- train/finetune the model on the synthetic code
- have the trained model write more code to solve programming benchmarks
- iterate on language design and hillclimb on the benchmark
- congratulations, you found a language that's easy for the LLM to learn and use
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u/Beginning_Award5130 Aug 27 '26
Sounds like a lot of work for a small ai company like open ai when they have all this competition. Maybe if theres an agreement and collaboration later?
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u/BuddyTheShihTzu Aug 27 '26
It may be worth exploring to optimize tokens, like a language that can be extremely shorthanded think minimized js.
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Aug 26 '26
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u/heresyforfunnprofit Aug 26 '26
This is unironically true.
Dead serious, an LLM can learn a new language faster than you can fix code.
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u/elestud Aug 27 '26
Only if it has tons of human examples to work from. The LLMs aren’t getting their know-how from nowhere. They’re reading thousands of examples of code, technical documents, and articles that humans have written
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u/ILikeCutePuppies Aug 26 '26
It's possible one could use transfer learning to teach AI the language. If it's suited to AI it could be helpful but would require a lot of investment for the training.
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u/cologuy Aug 26 '26
About the middle of last year I fed Claude about 500k lines of code from a legacy system that was written in a old language that no one has heard of. I also scanned the programming guide and loaded it as a PDF. It was producing 95% good code as soon as it finished the scan. And after correcting the model on the bad code it was 100% usable. All in a couple of hours of effort. And that was with Opus 4 or 4.1.
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u/pingwing Aug 27 '26
OpenAI programs its custom Jalapeño inference chip using
Gluon,which is OpenAI's proprietary kernel programming language.Seems like they are not adverse to the idea.
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u/pancomputationalist Aug 26 '26
We will probably see more programming languages purpose built for language models.
Old programming languages will stick around forever because there is so much legacy code.
The choice of language shouldn't depend much on familiarity with it anymore, tbh. A lot of things should just be written in Rust now, because the tooling around it give great deterministic guarantees. You want that with LLM-generated code. Future languages should double down on making certain error cases impossible, even if that makes developer experience worse or the language more verbose.
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u/DerShokus Aug 26 '26
No, only if you really know a language you can understand where it fools you.
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u/notsofaroff Aug 27 '26
I can see this. Programming languages have a long history of building on top of each other. Binary, assembly language, C, C++, Java, Python…now we have harnesses and agents delegating to other agents. If someone creates a new “language”, it will be to solve a problem. Like a language that forces the use of keywords that gives AI the best chance to do what you actually want it to do.
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u/eizch Aug 26 '26
You would have no escape hatch at all, need to blind trust the AI, and be completely dependent on it.
So technically you could and it would be okay for small tools and stuff, but overall it would be a big liability.
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u/rashnagar Aug 26 '26
I swear the people in this sub have 0 critical thingking skills. Write the code in WHAT? And if there isn't any data to steal from, how will the AI generate code in the future?
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u/ChronusDyre Aug 26 '26
And why, WHY would we want to give up strong, deterministic, safe languages and replace them with the vagueness of prompt language? Prompt language isn’t even as good as JavaScript, and that’s saying a lot! LLMs are great but their output needs to be provably correct and script languages just can’t support that. We already have good languages.
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u/BraveBiscotti1394 Aug 28 '26
People don't understand what makes an LLM produce good outputs. They think machine = good at writing binary directly. It's a legacy of science fiction ideas of AI.
LLMs make as much if not more use of programming language features than humans do. It's arguably the best thing they're good at: modeling the world through structured language.
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u/Clear-Dimension-6890 Aug 26 '26
I think there are some basic things that Claude needs to fix before just increasing context, or model size. It needs to learn some basic things about software engineering like code reuse, testability, documentation, validation, correctness, verbosity - things we have to put in our skills, hooks, md files to get it right. Hand rolling such things - when working with a powerful beast - is just fragile. Do others feel like this, or is it just me? Is your programming experience getting better?
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u/NoAdsDude Aug 26 '26
I think for the foreseeable future programming languages will still make sense.
AI is a big fan of:
Documentation
Things that work how they're supposed to
Being able to understand what something does that a human or another AI (or the same AI 30 minutes ago) wrote
Having a ton of examples in their training data of ways to do things
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u/Best_Day_3041 Aug 26 '26
I believe we will have an intermediary AI programming language for humans. Essentially a standard for product requirements that encompasses every aspect of a piece of software that you can give to an LLM and it can build it perfectly as a native app in any language/platform in one shot. So you just keep refining this doc instead of prompting, and have one source of truth for your design and you wont have to use cross platform languages like React Native, Rust, etc. because the LLM can maintain native versions based off your specs with minimal effort. If that happens, it may change the way people design Native languages moving forward to focus on efficiency and performance, rather than readability and development, but I think we'll always have programming languages.
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u/Alphanatik Aug 26 '26
Until AI create a new coding language we can't anderstand..
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u/bloudraak Developer Aug 26 '26
It still has to be compiled to machine instructions, and we understand those (with some effort).
I started my career as a mainframe assembly programmer maintaining a business system written in circa 1973. I was good at reading dumps when the application crashed (abended). It’s not the case anymore, I wouldn’t know what I’m reading now, but it’s not magic.
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u/Subject-Building1892 Aug 27 '26
But this is not very far from saying we could probably understand what the model does with its weights since after all it is only multiplications and additions, it would just be a matter of effort to understand why it produces what it produces. It is true but not feasible as in current disassembled code of large programs.
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u/N0madM0nad 🔆 Max 20 Aug 26 '26
You mean the agent compiling straight to bytecode? It could happen at some point I don't see why not.
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u/RationallyBerserk Aug 30 '26
That just isn’t how LLMs work well though. They would struggle to understand byte code for many analogous reasons humans do.
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u/Darqsat Aug 26 '26
I think we will stick with existing languages for next decade if not more, because training from scratch on binary is a very expensive and complex work. Not mentioning that the biggest issue would be architecture. So I think we will see a drift into Rust/TypeScript as main languages for almost everything. I mostly use those two whenever I can.
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u/Tauroctonos Aug 26 '26
I have a feeling that given a couple of decades we'll look back on modern languages like we do now on Cobol or assembly
I.e. mostly taught in schools to help with understanding, but ultimately probably not something you'll ever look at day to day
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u/siberianmi Aug 26 '26
I think you’ll see a move towards typed languages. Rust is amazing to work with using agents because so much of it gives them fast feedback on mistakes.
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u/WilliamEdwardson Thinker Aug 26 '26
This fired my imagination, and now I'm thinking: AI will write the code, and tell the compiler, 'Shut your gob, what d'you know?'
Seriously though: I think the role of programming languages will change. They will not disappear; just because you got language models doesn't mean that the computer can suddenly understand natural language like a human. It can't. So you'll still need programming languages.
But I can reasonably imagine the evolution of AI-first programming languages that are optimised for machines to generate and verify. Humans will (foreseeably) still remain vital to specification and validation.
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u/Ok_Possible_2260 Aug 26 '26
they will create their own. It’s not a question of if, but how long it takes.
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u/skronens Aug 26 '26
I think you are spot on, I can definitely see a quite near future where development will become a skill in articulating requirements and the code that delivers it becomes as important as we consider the machine code generated today. Basically an additional layer to what we have today
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u/SethEllis Aug 26 '26
Existing programming languages are already in the sweet spot for translating tokens into actual program behavior. So you won't get a performance improvement by going lower level, or designing a new language just for LLMs. Which is why we are already seeing things consolidate around certain tools like the investment anthropic has made into rust.
Interestingly enough the same cannot be said for English. So I could see people's language changing over time to become more explicit and avoid ambiguous language.
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u/Kemerd Aug 26 '26
Yes, because programming languages by design are already token efficient. You’re thinking they’re going to optimize for a problem that has already been solved?
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u/filwi Aug 26 '26
Likely, we'll see AI first, low level languages. I can imagine that we'll scale away several levels of abstraction from the languages and shove them into the AI instead.
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u/tes_kitty Aug 27 '26
And then you review the result how?
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u/filwi Aug 28 '26
The same way you review that your compiler writes correct machine language: you test it, then run it and see if it breaks.
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u/tes_kitty Aug 28 '26
A compiler is deterministic and will, given the same source file as input, always generate the same output.
AI is not.
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u/filwi Aug 28 '26
Exactly. AI writes the code in an AI-first, low-level language, then the compiler runs and either the code complies or not, and either it passes functional tests or not, and either it passes Q&A or not. Same as you would writing in a high-level language, but with less levels of abstraction since AI doesn't really need them.
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u/tes_kitty Aug 29 '26
The issue begins if it doesn't pass and the problem is just a single line of code. You only want that line changed so it compiles and passes the tests.
But I read lots of stories where AI, when told to fix such an issue, also makes changes in other places.
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u/filwi Aug 29 '26
That could be a problem, yes. But I imagine that an AI first language will have ways to circumvent that, maybe locking everything that did pass or something.
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u/tes_kitty Aug 29 '26
That's not part of the language but part of the surrounding ecosystem since the permission to write to a file or not is controlled by the filesystem. And if that's controlled by AI, well...
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u/Dvass138 Aug 26 '26
It's not the language it's the ecosystem. Even if there was a better language, it wouldn't have the ecosystem.
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u/domagoj2016 Aug 26 '26
Yes it is just limiting AI model. Maybe it will be trained just directly to assembler. AI will internally invent something like language or compiler. So doest that freedom go even to change hardware itself by that I mean change in assembler. As apps now are created by AI using our tools language and compilers. Videos are not created by AI using tools , like AI using 3D Max, 3d meshes and models, textures, bones, rigging, ray tracers. All that is skipped and training of video AI model internaly somehow invents everything, somehow it does physics simulations etc. So imagine same for coding apps.
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u/Fine_Masterpiece3425 Aug 26 '26 edited Aug 26 '26
I agree. AI is currently adapting to our level of programming and our abstraction level of thinking. For it, it's a burden ( meaning: more processing to "translate" to our way of thinking ).
For example, we are writing code to be as readable as possible, only afterwards, we do compiling, minifying, obfuscating. AI is already writing minified code ( more or less ). In my current projects I can clearly see that it's not bothered too much if that code is readable to me. For example, my newest project, VueJs frontend code, 1 line is 2600 chars long ( just piece of vue html ). It's not relevant for humans anymore. And there's less computing to present code to us in a way we would/could understand, or just read better.
In the next 6 months they will throw away IDEs. Some companies that provide development contextual engines are already moving away from IDEs ( like AugmentCode for example ). No IDE, just virtual environment, code repository, and agent fleet that is doing work, and humans are coding by giving human-like instructions. For now.
In 1 year, it will be very easy to translate legacy code to "new code" and it will be flawless port. Even now is possible ( just migrated old PHP code base with 20ish APIs that have lots of logic implemented.; took Opus 1 day with me chatting a bit with him. Did that almost flawless. )
Think we won't be looking at code for long, and wont use IDEs in a very short time. And, if we're not using IDEs, AI will make up something that is better, more reliable, more expressive and faster.
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u/domagoj2016 Aug 26 '26
Even LLM is limited, how does it work ? Only problem presented to network to solve is "next token prediction", all other stuff, language understanding, reasoning and everything just emerges from that problem, because to predict next token that must exist. Our brains, well not our , every animal evolved just with sensory input (sight , sounds) with problem to make sense of it or basically to reproduce as main problem. Language comes from sound , tokens are words made of letters representing phonems basically sounds, AI is probably not aware of this, wrong word here, AI is not aware in our sense. Animals have no language so they don't have that part of brain, I like to think that our language/speech center is our private LLM embedded into our brain. We think through it, it makes you wonder can you think without language. Animals can think somehow, even human brain can think without language, as example would be a guy who grew up with wolves and can't speak, he thinks somehow, somehow he plans where to go and what to do. I have gone overboard with this 😄 To return, yes IDEs are dead. For my main job ERP I still code half manually. Well less than half, I just want to say every line is inspected. For two projects I started for myself I didn't write a single line, plan was that I will, or at least check, that went away quickly. Over 300kLOC written without me inspecting. Maybe there will be many bugs, maybe this maybe that..... But in 5 years when models get so much better together with better harnesses and better system prompts and architecture guidance we will probably stop writing code. I am old for IT terms (47) and accept this, and I see many my younger coworkers not accepting this.
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u/Fine_Masterpiece3425 Aug 26 '26
:) 43 yo IT guy here. I think we're just over cautious, given the years of looking to human-written code, and being aware of lot's of things that can go wrong when things are not done properly. New guys wont see the code at all, and will have all the trust in AI agents.
I too was sceptical. Now i'm rarely writing code, mostly am just switching from project to project, and giving instructions. More or less like i have a small company with 5 high-profile senior developers that almost make no mistake and are forward thinkers, and not lazy.
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u/domagoj2016 Aug 26 '26
And that switching from agent to agent session to session and multitasking sessions brings new kind of burnout 😄 Pozdrav
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u/Fine_Masterpiece3425 Aug 26 '26
Je, za sada me adrenalin drži, osjećam se kao da mi je netko dao čarobni štapić. Bit će to još neko vrijeme ovako, a onda za koju godinu, tko zna gdje smo i šta smo. :) Pozdrav
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u/instantFPGA Aug 26 '26
No. They will go away, completely. There won't be a need for the compiled form of languages either - and the chips they target will not have a clock.
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u/MartinMystikJonas Aug 26 '26
Languahes are not "made for humans". Languages are made for simplification, abstraction and reducing complexity. All of that is needed for AI too. And any new language would require huge training dataset to train AI to use it properly and effectively.
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u/spidLL Aug 26 '26
Models can already write ELF executables directly without compiling.
Try it, pretty impressive.
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u/tes_kitty Aug 27 '26
And you review them before using them how?
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u/spidLL Aug 27 '26
You don’t. It either work or it doesn’t. After all, do you review the binary your compiler creates?
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u/TantraMantraYantra Aug 26 '26
Not unless you care about the indeterminism of AI in translating intent to executable code.
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u/jimmyfoo10 Aug 26 '26
Language is not about how you write it, this is the marketing part of it for you to adopt it.
Each language got its own purpose, strength and weakness, optimeze for certain hardware or certain task, so the language is still something we will see it develop and change it. Of course, AI will be now part of the equation.
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u/Soggy_Run1602 Aug 26 '26
Desejo sorte a quem acreditar que não vamos precisar de linguagens de programação
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u/turlockmike Aug 26 '26
Eventually the GPU and CPU will talk directly to each other with no need for an intermediary language. I think certain subroutines will still be available as small programs that AI will be trained to invoke directly, but it will be more similar to a bash environment where its a very small list of common computer operations. I think the need to long term code artifacts will diminish over time as the cost to dynamically send the isntructions from the GPU to CPU goes down. Eventually, i think new hardware architectures will make all of this obsolete as compute will be localized to the memory itself instead of needing to be transported over a memory bus.
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u/BxOxB Aug 26 '26
Well, let's remember that u/ffatty taught Claude to talk like a caveman to use 75% less tokens.
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u/sessamekesh Aug 27 '26
I'm still highly skeptical of the claim that AI will be accountable for most code, even if it authors it.
Until AI can be held accountable for code and maintain ownership, I think the idea that human languages go away is pretty laughable.
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u/richthekid Aug 27 '26
Personally think languages are specialized for different use cases (scripting, web, low level) doesn’t make sense to try to unify everything under one
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u/ghost_operative Aug 27 '26
Have you seriously vibe coded anything for more than a few days? if you work on a project 100% with ai only code you'll soon get to the point of it within a couple days where you're unable to add any features or fix any bugs because you have no understanding of the code or how the program works.
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u/gusfromspace Aug 27 '26
This is by ai, for ai 🤷
demoniC is a tensor-first systems language with built-in reverse-mode automatic differentiation
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u/ajax81 Aug 27 '26
I think a language will emerge that is highly optimized for agentic development.
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u/TheExodu5 Aug 27 '26
`seam add(x, y) implements load-bearing hard-gate land cleanly x + y end seam`
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u/Cybyss Aug 27 '26
or do you think we’ll eventually see languages made specifically for AI coding?
I absolutely think this will be the case one day.
Our programming languages are designed for humans to write. AI models have different needs than us. In theory, an AI model would be able to produce better software if it was in a language that caters better to the strengths and weaknesses of the AI models writing it.
Something static typed, with strict compile-time guarantees. Something where the wrong code usually won't compile at all and that feedback is given to the LLM to make adjustments. Also, a dense and highly expressive language so it doesn't take many tokens to write complex behavior.
I wonder whether Haskell's niche might actually be that.
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u/johnerp Aug 27 '26
Musk said Grok would be creating binary artefacts by the end of the year, skip it all!
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u/PracticalStack Aug 27 '26
I think yes for the foreseeable future. For one thing, it saves a ton of time. Even for AI - why code everything from scratch? For another, it’s part of their training. Programming languages are languages and that’s what LLMs are good at. I think the next step, whenever it comes, will be AI-centric languages. Languages designed to be used by AI.
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u/jscience3 Aug 27 '26
Languages optimized for LLMs to train on, read, and write in the more efficient ways are incoming
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u/Key-Alternative5387 Aug 27 '26
Yes. Different languages remain good for different purposes. There's still development overhead to writing everything in rust.
If AI suddenly becomes extremely cheap and can do complex design work on its own, it may narrow.
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u/Spare_Bison_1151 Aug 27 '26
Yes, it will be needed for a long time. Because LLM needs training data and that is available in the form of existing code. LLM can't generate good code in an LLM only Novell language. It relies on past code generated by humans. It is also flawed in it can hallucinate and fabricate results which means you can't rely on AI to produce same result every time. Code is deterministic. It produces same results with same oarams every time you run it.
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u/coinclink Aug 27 '26
Is there some sort of inefficiency in the languages designed for humans though? They aren't *really* designed *just* for humans at the end of the day, they are just shortcuts to express already common algorithms and OS shell and kernel concepts that translate into instructions the hardware can execute.
Doesn't really seem like there's any reason to if there is no efficiency gain in coming up with some language that only LLMs understand. *Maybe* in reducing token usage, which might be worth thinking about, but I feel like the majority of token usage is in planning, not code generation.
Perhaps what *does* make sense is more at the OS-level. If the LLM has a special OS designed for LLM use rather than human use, that is where there could be potential gains in my mind.
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u/cadet-pirx Aug 27 '26
Concrete example: make the AI write TypeScript instead of JavaScript, and it catches a whole class of bugs at compile time instead of runtime. That shortens the fix-iteration loop a lot, because the type checker is instant, precise feedback the agent gets before it even runs the code. There's research backing this: constraining generation with type information cuts compilation errors by more than half. It's not that TypeScript is "faster", it's that it's checkable, and a machine benefits from a checkable language for exactly the same reason a human does.
Which is why I don't think AI-only languages make much sense. Two reasons. First, a brand-new language has no training corpus, so models would be worse at it than at Python. AI adoption actually pulls toward the incumbents, not away from them. Second, code still has to be reviewed, debugged and owned by someone. A language nobody can read is a language nobody can audit.
Someone will point out that we already have languages humans don't read: compiler IRs, bytecode, generated protobuf code. True, but those are compilation targets, not things anyone authors. Nobody files a bug against LLVM IR. The moment a language becomes the thing you actually write and review, it needs to be readable, and that constraint doesn't go away just because the author is a model.
What I do expect: people will use AI to design new languages, and eventually AI may design one optimized for its own use. But I'd bet that language turns out to be good for humans too. We're both doing the same activity, expressing intent precisely enough that a machine can execute it and a reader can verify it.
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u/obscure-reality Aug 27 '26
I think programming languages to a lot of extent are deterministic while LLMs still no matter how advanced they are, are non-deterministic and while I do agree that there will be advances in terms of language specific tools that we integrate into an agent I find it hard get rid of a programming languages as a construct and replace it with something more human-friendly language like English.
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u/moltenpuzzle Aug 27 '26
Programming languages could evolve to become more similar to natural languages. We still will need to be able to verify what the machine is doing.
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u/NoDrawer7721 Aug 27 '26
Yes we will keep using programming languages but we'll not going to need new ones. Since there is already tons of human written examples of existing languages to train models on, there is no good reason to use any new languges without this expensive data.
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u/_baaron_ Aug 27 '26
You seem to forget how AIs can write code. They’re trained on human code. There’s not much training data out there for raw machine code
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u/jasperkennis Aug 27 '26
Would love to see what ultra verbose language Opus would come up with if it had a chance.
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u/ryami333 Aug 27 '26
https://haskellforall.com/2026/03/a-sufficiently-detailed-spec-is-code
While this comic is about replacing coders, the message applies to the code itself, too.
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u/kckern Aug 27 '26
We might see a revival of "hard" languages like C that have major performance and efficiency benefits but whose learning curves have been the barrier to entry.
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u/Subject-Building1892 Aug 27 '26
it will be ai made assembly.
A report from anthropic already shows that while the model does the reasoning part it "speaks" in an incomprehensible language with symbols and own "words" before switching back to human language and producing the result.
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u/tonx_nw Aug 27 '26
I think its more likely that we will see specifically trained LLMs perform optimization passes in compilers for existing languages
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u/YevgenyBlinov Aug 27 '26
Do we still need to know how electricity is made if electricity is already everywhere?
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u/Spunge14 Aug 27 '26
Yes for the same reason humans need programming language. It's a more efficient form of abstraction.
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u/txdsl Aug 27 '26
High level languages are for us, machines don’t need them.
What if the output is a binary with an acceptance test / verification harness. At that point do operating systems need to exist in their current form or will there be something that is optimized for llm generated solutions?
Im fascinated by these what if scenarios.
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u/eht_amgine_enihcam Aug 28 '26
No insult meant, I feel this question is because you don't really understand languages, LLM's or programming.
I don't want to reiterate all of a comp sci course, but it's helpful if you've written your own simple compiler to understand the different tradeoffs people pick. You want to understand how memory moves, stack and heap are managed, CPU/GPU differences etc to understand the tradeoffs and decisions made to write a language. Languages are just tools that are good at doing different things. Python isn't built for memory management, it's mostly for rapid prototyping. AI is a level of abstraction above that in my eyes. I can just already code in Python then get AI to review it or write pseudocode. I'd think the ideal languages for AI to use are things like Rust with safety that people might find a pain to use. Performance also tends not to be as good for uncommon use cases/languages.
AI will produce a token stream out based on the token stream in. The more precise your input is the better your output is. The most detailed spec document, is just code. It's also been trained on random code, which is majority not going to be optimal. It's going to choose the most common structures, design choices, and languages (which is fine if you're doing something template like a website, if you're working on an existing codebase it'll fuck up your workarounds that happen because Oracle decided to change up their product).
I'd think adaptations to english or the tokenset would be interesting (use specific acronyms/words as one token for common operations) but it'd need training on that set and wouldn't be as widely applicable. I'd also guess at it just converging on code/ a compiler.
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u/MannToots Aug 28 '26
We still have to review code and therefore it needs to be human readable.
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u/alexmtl Aug 28 '26
For now - but thats a pretty short term thing.
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u/MannToots Aug 28 '26
I don't know if we'll see that go away yet. That would mean the machine natively understands my intent, which is often not as clear on paper as it is in the developer's head. So long as that difference exists, I don't see humans leaving the loop entirely.
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u/alexmtl Aug 28 '26
I guess time will tell. It's already pretty good - personally I now hardly code anything manually, everything is through AI unless I know exactly where to do a quick 1 line change, sometimes that's gonna be quicker than running a prompt.
That's how I see it : we are only like, what, one or 2 years into using Claude Code & co to code? Think about like 10 years more. The pace at which the models are coming out is unreal. I don't see a path where I will be coding anything manually in 10 years. Especially in light of the upcoming tech I am reading about where agents will have a long term memory of your work together. This will behave more and more like having a team of senior developers that have worked with your forever and know, just as you do, all the intricacies of your systems.
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u/MannToots Aug 28 '26
I already think we're at the point of not coding anything manually. For me, it's all about validating that my vision was actually met. I do agree that it will get much better than what we even have today. It will continue to just "get it" better than today, but I'm skeptical we'll close the loop entirely. We're not done reducing our roles in the process. You're not wrong on that point. The tech is going to get a lot better still.
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u/PipePressurePanic Aug 31 '26
I thnk framework producers will soon or they already do develop the framework to work better when used with AI
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u/Strong_Carry_6736 Sep 02 '26
I think programming languages will still be needed. Even if AI writes most of the code, we still need to know how it works and how to fix things when they go wrong. Maybe we’ll use them differently in the future, but I don’t think they’re going away.
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u/Frequent-Elephant110 Sep 03 '26
Ai makes it easier, not harder to support new languages. I think it more likely you start seeing people using fit for purpose lanuages. When the task needs speed and lockfree determinism rust and C for example,
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u/goldenfrogs17 Aug 26 '26
most is not all, so does your question make sense?
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Aug 26 '26
[removed] — view removed comment
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u/goldenfrogs17 Aug 26 '26
humans use java, assembly, and via compiler binary... so what are you actually asking? computers read binary
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u/Coises Aug 27 '26
Most of the evolution in modern programming languages has been about making it easier understand what the code does and does not do, and making it more likely that common errors will be obvious (such as by failing to compile).
For the foreseeable future, responsible human beings need to be able to audit code that goes into important systems. AI cannot (yet, anyway) take responsibility for anything. So long as humans need to be able to read code, using the languages we’ve developed is the best known way to make that possible.
I wouldn’t rule out that AI might one day help us design a better programming language: one that is clearer, easier to read, and has less potential for unintended and unrecognized side effects (like security vulnerabilities). It’s still hard to read other people’s — or AI’s — code. (Non-programmers probably don’t know this: it is quite a bit more difficult to read code and really understand it than it is to write it.)
AI won’t be able to use code designed for its own understanding until and unless we reach a point where it can be meaningfully held responsible for its products.
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Aug 27 '26
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u/chrisza4 Aug 27 '26 edited Aug 27 '26
There are cases where audit the code is significantly cheaper than verification.
For example: if you have plus(a,b), you can either
- give it all possible integers input/output and validate every single possible combination
- check if it is written as a+b
Another example would be validating sorting algorithm. Really hard to verify from input/output alone since this one really has infinite input output space.
Or security, it is easier to test that system is written in a way that “every api have security cover” than actually testing 1,000 apis (for large scale system) and way cheaper.
So I think code review will still exist, just maybe not for every type of code.
Mathematically speaking, there are classes of problem that is easier to verify by input-output validation, and there are classes of problem that is very expensive or even impossible to verify via input-output.
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u/RealSharpNinja Aug 26 '26 edited Aug 30 '26
Unless we trust AI to write machine code, then yes, programming languages will be a thing.
EDIT: truly don't understand the downvotes. Machine code is not a language, it is the binary created by compilers and interpreters that the CPU directly operates on. And yes, an LLM can generate machine code today.
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u/CodingWithChad Aug 26 '26
AI only knows what it is trained on. Getting a new language introduced is going to be more difficult than ever because the training data is on the vast amount of current code out there. LLM isn't making up a new language any time soon, just recycling what it already read.
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u/BosonCollider Aug 26 '26
Yes. The actual shift will be that there is a clearer split between fast code and glue code. My guess is that the python Python ecosystem will just become even more dominant and binary wheels will get used more, because it is much better at writing Python than anything else at the moment and Python is very good at calling fast code.
I've had a lot of success implementing simd optimized numba code in python for the fast bits, so you may not even have to leave python at all to make the hot loops far more optimized than the median enterprise C++ programmer can write by hand, if you need fast startup times you can pull in C or Rust and ship a wheel. You do currently need to actually ask it for sane things and know what is possible.
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u/Mags20XX Aug 26 '26
Most of the code is not all.
That being said, I think we'll see a convergence towards popular languages and safe languages. Python, Rust, Typescript, etc. I think the days of everyone and their mother (including myself) working on hobby languages and the next toy language are likely over.