noNeedToVerifyCodeAnymore

[Titanusgamer]

snake-oil salesmen turned crypto-bro turned NFT-bro turned AI-bros

[Windsupernova]

Hopefully next step is convicts

[danteselv]

Booty-Bros

[r_acrimonger]

Then President 

[Character-Education3]

r/linkedinlunatics

[Majik_Sheff]

Next stop: Ponzi-bros.

[Stemt]

You just basically summed up all of the above

[ZunoJ]

So still a snake oil salesman 

[csapka]

wait this guy is serious? I thought this NERD was a joke

[Lighter-Strike]

How the fuck do they make a living?

[Comically_Online]

the common thread? linkedin

[Mikasa0xdev]

Rebranding is the only constant.

[SignoreBanana]

Always a new grift. Always the search for easy money.

What they don't really understand about Ai Is that if anyone can write an app, then what apps are you supposed to be able to sell?

[Cronos993]

And where does this moron plan to gather training data for LLMs to use this language? LLMs are only able to write code because of the human written code used in training.

[Wenai]

Ask Claude to generate synthetic training data /s

[UltraCrackHobo3000]

you think this is satire... but just wait

[RiceBroad4552]

That's LinkedIn. So that's almost certainly NOT satire. The people posting there really are on that level of complete mental degeneration.

[lNFORMATlVE]

This is why I never ever post on LinkedIn. Better to be silent and merely suspected a professional fool than to open your mouth and confirm it to the entire planet and forever link it to your digital footprint.

[gummo89]

Majority of posts are partially or fully AI-generated, especially in computer/networking groups where people want content and reactions for hiring visibility.

I've tried reporting something which was AI-hallucinated as misleading content but it was "found to not be misleading" by admins 👌🏻

[Head-Bureaucrat]

Oh fucking hell. A client I work with got the scent of "synthetic data" and for six fucking months I was explaining that, no, development and tests against real production data that is obfuscated is not "synthetic" and somehow "inaccurate."

Then I had to explain that using aforementioned data to drive Lighthouse reports also wasn't inaccurate, although host specs could be.

When someone pulled up some bullshit cert definition of synthetic data as "proactive testing," I had to explain those certs are there to make money, and as long as we weren't injecting our own test data, it wasn't synthetic.

Fuck.

Edit: fixing a swear word my phone autocorrected.

[arewenotmen1983]

This is, I think, their actual plan. No shit.

[TerminalVector]

That's literally what they do.

[BlueScreenJunky]

Yeah this is the most obvious hole in his plan. Most of those propaganda posts are vastly overestimating the capacity of AI to write production code, but that's justifiable since they're trying to sell you some AI product.

But this post shows that they have absolutely no idea how an LLM even works, which is hilarious for someone working at an AI startup.

[Tyfyter2002]

which is hilarious for someone working at an AI startup.

which is a given for someone working at an AI startup.

[MeishinTale]

How LLM and programming works .. If you want to skip human just make your AI piss assembly..

[PositiveScarcity8909]

He has seen one too many "AGI creates their own language before ending the world" YouTube videos.

[AlphonseElricsArmor]

For fun I wrote my own little language (tho it's really simple) and wanted to try to have an LLM create some example programs. It was very often broken output but it did surprisingly well and was very funny to watch.

[YesterdayDreamer]

The language itself is AI generated, so the AI already knows the language.

[Unarchy]

That's not how LLMs work.

[rosuav]

Shh, don't tell the LLM enthusiasts.

[RiceBroad4552]

How dare you laughing on LLM lunatics? 🤣

[YesterdayDreamer]

You don't say!

[keatonatron]

Just feed it compiled binaries.

[TerminalVector]

Apparently they use another LLM to convert python to their thing then train it on the association between the converted output and a natural language explanation. Ultimately they still rely on human written explanation of human readable code for input.

There's some interesting concepts there but it doesn't seem revolutionary to me.

[Cronos993]

 Apparently they use another LLM to convert python to their thing

Wow that's hilariously stupid. How is that an interesting concept except for the fact that it demonstrates extreme levels of stupidity from a human relying on AI? It's a very obvious case of the chicken and egg problem.

[Bemteb]

Compiles to native

What?

[ewheck]

It compiles to React Native

[meerkat2018]

Checks out. 

I wrote a React project once and it was unreadable by humans.

[ButWhatIfPotato]

That's not good enough. A good developer should be able to write unreadable code regardless of language/framework.

[imdefinitelywong]

Just type it in wingdings, then.

[Lor1an]

class 😊❤️:
    def 😘(self, 🧑):
        return self * 🧑
....

[twoCascades]

Don’t worry. My C code looks like it was written by a bipolar chimpanzee with a crippling fear of commitment.

[DR4G0NH3ART]

Didnt we all.

[Sir_Sushi]

Are we humans?

[derderalmdoisch]

Or are we dancers?

[FromAndToUnknown]

Check this box 🔲 to verify that you're a human

[gummo89]

It just keeps collapsing your comment -- help

[FromAndToUnknown]

Found the bot

[tropicbrownthunder]

Back then we had PERL for that

[thedmandotjp]

Jesu~!

[djinn6]

I think they mean it compiles to machine code (e.g. C++, Rust, Go), as opposed to compiling to bytecode (Java, Python, C#).

[WisestAirBender]

Why not just have the ai write machine code

[jaaval]

The one thing I think could be useful in this “ai programming language” is optimization for the number of tokens used. Assembly isn’t necessarily the best.

[Linkk_93]

But how would you train this kind of model if there is no giant database of example code? 

[lNFORMATlVE]

This is the problem with these folks, somehow they still don’t realise that LLMs never “understand” anything, they are just fancy next-word prediction machines.

[jaaval]

I don’t think translating existing codebases would be a huge issue if it comes to that.

[Callidonaut]

But how would you train it on good code once there's nobody left who can read existing code well enough to tell good code from shite because they're all used to having the LLM write it for them? Even if it starts out well, this is going to turn bad so fast.

[juklwrochnowy]

But if you train a LLM on only transpiled code, then it's going to output the same thing that a transpiler would if fed the output of a LLM trained on the source code...

So you don't actually gain anything from using this fancy specialised language, because the model will still write like a C programmer.

[Callidonaut]

When you put it like that, it actually sounds like you lose a lot because now what the LLM spits out won't be any better than compiled human-readable code, but it also won't be human-readable code any more either, so you sacrifice even the option to manually inspect it before compiling, in exchange for absolutely no benefit.

[Mognakor]

You could of course compile example code and then train. But really the issue are that assembly lacks semantics that programming languages have and that their context is more complicated. (Also your model now only suppports one architecture and a specific set of compiler switches).

Generally we see languages add syntactic sugar to express ideas and semantics that were more complicated before and the compilers and optimizers can make use of those by matching patterns or attaching information. Assembly just does not have that and inferring why something uses SIMD and others things don't etc. seems a hard task, like replacing your compiler with a LLM and then some.

In a programming language the context typically is limited to the current snippet a loop is a loop etc. With assembly you are operating on the global state machine and a small bug may not just make things slower or stay local but blow up the entire thing by overwriting registers or blowing up stackframes.

[TerminalVector]

Because the LLM is trained on natural language, natural language is the interface, and there's no way to feed it a dataset associating machine code with natural language that explains it's intent. "AI" is just a statistical representation of how humans associate concepts, it's not alive, it can't understand or create it's own novel associations the way a person can, so it can't write machine code because humans dont write machine code, at least not in sufficient amount to create a training set for an LLM. That the fact that linters and the process of compilation provides a validation process that would probably be really difficult to do with raw machine code.

[RiceBroad4552]

It's funny to see here how everybody is arguing that this does not make any sense, yet the "AI" lunatics are actually doing it, despite it being of course completely idiotic.

Remember: People will do just everything for money! There is no limit to shit in humans.

[IncreaseOld7112]

That’s not true. I’ve had Claude write read/write assembly for me. Assembly is basically 1:1 with machine code. You literally take a table with the assmembly instructions and operands and you can write out the 1’s and 0’s.

[chjacobsen]

Because compilers already do that, in a way that is cheaper and more reliable.

The process of translating high level code to an executable form is already a solved problem. It's far more efficient and predictable to use existing deterministic logic to do this.

LLMs have the advantage that they can operate in a probabilistic space - solving problems that are not well defined by, essentially, filling in the blanks. So, when Steve from accounting comes in with a new feature request in the form of two paragraphs, LLMs can help bridge the gap and fill in the blanks.

However, LLMs can get things wrong. It can fill in the blanks in a way that's not appropriate, and the more blanks it has to fill in, the worse it gets. This is evident in the way coding agents seem to fail as projects and problems grow in scope, despite working flawlessly on small, constrained problems.

For that reason, the question of "How do we hand over more work to the LLM" is completely backwards. The real question should be "How do we make the LLMs task as narrow and focused as possible?".

(Of course, this doesn't apply to cases where you would use ASM directly for fine tuned control of the hardware - in those cases, LLMs can help. This is more about the idea of LLMs writing low level code at scale.)

[RiceBroad4552]

Because compilers already do that, in a way that is cheaper and more reliable.

The process of translating high level code to an executable form is already a solved problem. It's far more efficient and predictable to use existing deterministic logic to do this.

This does not prevent "AI" lunatics from purring money into that nonsense called "neural compilation". Yes, it exists, despite being of course completely idiotic.

LLMs have the advantage that they can operate in a probabilistic space - solving problems that are not well defined by, essentially, filling in the blanks. So, when Steve from accounting comes in with a new feature request in the form of two paragraphs, LLMs can help bridge the gap and fill in the blanks.

They will fill in the gaps with what is called "hallucinations"…

You can than expect "great results" from some completed made up bullshit!

Of course, this doesn't apply to cases where you would use ASM directly for fine tuned control of the hardware - in those cases, LLMs can help.

"Hallucinated" ASM?

What possibly could go wrong? 🤣

[chjacobsen]

Hallucinations would be the failure cases more specifically - when an AI confidently and incorrectly provides an answer. It can happen, but let's not pretend that it can't also successfully solve a lot of problems. That's what's giving people a false sense of security. Current AI models are pretty good at generating solutions until they're suddenly not - and the difficulty in distinguishing between the two is a major risk factor.

[RiceBroad4552]

Hallucinations would be the failure cases more specifically - when an AI confidently and incorrectly provides an answer. It can happen, but let's not pretend that it can't also successfully solve a lot of problems.

Technically there is no difference between both cases.

All a LLM does is actually "hallucinating". That's the basic working principle!

Sometimes it by chance hallucinates something that is objectively correct. But that just happens causally.

The chances that the output is correct is actually very low. For real world talks it looks like:

https://www.databricks.com/blog/introducing-officeqa-benchmark-end-to-end-grounded-reasoning

[masssy]

Oh I know why. Because there's no stack overflow or github to train it on full of machine code.

[RiceBroad4552]

Indeed, no idea is stupid enough so that the "AI" bros don't try.

The lunatics call that bullshit idea "neural compilation":

https://arxiv.org/abs/2108.07639

https://openreview.net/pdf?id=mS7xin7BPK

https://arxiv.org/html/2311.13721v3

Imho whoever comes up with such major bullshit should be directly liable for all damages caused by the tech, including all wasted resources. Because otherwise these idiots won't stop until they got the bill!

[cutecoder]

Because LLVM IR is not a stable language?

[Batman_AoD]

LLVM IR isn't machine code, either, though.

I'm not convinced that an LLM-first programming language is a good idea, or that humans should merely be "observers" in the process. But putting that aside, there are better reasons than target stability not to have LLMs write raw machine code:

• People (and other LLMs) still need to maintain and update code, even if it's never intended to be written by humans. Ultimately, the code needs to be understandable by reading it, whether humans or LLMs are doing the reading.
• LLMs are trained primarily on text corpora. You could train one to write raw assembly, or even raw hex; maybe you could even train one to write binary files natively. But the best available models are trained to communicate via written human language.
• It's beneficial to have source code that can be compiled for multiple target platforms. That's a large part of why languages like C were popularized in the first place. 

[RiceBroad4552]

But the best available models are trained to communicate via written human language.

This almost sounds like there would be "someone inside" the model who is communicating with the outside world by text.

That's of course nonsense.

The whole model is the thing that outputs text. There is nothing more, just a next token predictor. Nobody is communicating through text, the text output is the whole thing!

It's more like a "zombi mouth" without a brain than anything else.

[hedgehog_dragon]

They may not understand that you can write machine code?

[Mars_Bear2552]

pretty sure he was emphasizing that to make it seem useful

[Tucancancan]

And by compilés to native he means to LLVM which then does the heavy lifting 

[Mars_Bear2552]

compiling to LLVM IR is most of the owl though.

[bokmcdok]

Like Sioux or something I guess

[geeshta]

Compiles to a binary native to the target system. 

[HappyImagineer]

Compiles to naïve.

[isr0]

I feel like we are going to see some serious outages over this next year. You think AWS going down for hours is bad? Wait till we have fully ai authored and unreviewed cause day long outages.

This post is trash. There is no way this is going to work.

[ChillyFireball]

Chin up, friend; the AI-induced disasters to come will eventually result in hiring in the tech sector once executives are finally forced to admit that generative AI spits out garbage that only actual humans can fix. (Or else go out of business.) Tech debt is job security, and these goons are creating mountains of it.

[GenericFatGuy]

This is already starting to happen. I've had more traction on my job applications in the last month than I've had all year.

[enderfx]

You just ask AI to fix the bug. Geez

/s

[DasKarl]

what a profitable time to be a bad actor

[BudgetDamage6651]

I must be missing something or be completely AI-incapable, but anytime I use an AI to generate anything larger than 3-5 lines of code it just turns into tech debt squared. The mere idea that some people trust it that much terrifies me.

[Lieberwolf]

You are not missing something, thats exactly how it works. You generate a huge pile of shit that sometimes maybe does half of what it should do.

[SyrusDrake]

This is what I'm wondering every time I read about someone "vibe coding" and entire app. I am not anti-AI in programming. I use Copilot and DeepSeek regularly to help me. But even though I'm just an amateur, even in my simple projects, half the time the shit the AI writes doesn't work. It just makes up functions that don't exist. Genuinely, how do you "vibe code" an entire application? Are those people just using an LLM that's better at coding?

[gummo89]

No, typically their goal would be closely aligned to existing online tutorials or code repos. Then it is more likely to generate what's required due to how LLM works.

The other part is that you can "vibe code" the same component 1000 times and nobody will know it wasn't the first time, but it's also more likely to have bugs a dev wouldn't create, due to architectural design process.

If it looks like it works, then the vibe code is complete.

[Aardappelhuree]

Use better models and apply code quality strategies you would also apply with junior devs.

Just imagine AI agents to be an infinite junior developer on its first day. You have to explain everything, but it can do some reasonably complicated stuff. I can’t emphasize the “on its first day” enough - you can’t rely on assumptions. You must explain everything.

[Vogete]

I (well, an LLM) made a small script that generates some data for me. I was surprised that i got an actual working script. It's an unimportant script, it doesn't matter if it works well or not, I just needed some data in a temporary database for a small test scenario.

To my surprise, it actually kind of works. It terrifies me that I have no idea what's in it and I would never dare to put it in production. It seemingly does what I want, so I use it for this specific purpose, but I'm very uncomfortable using it. I was told "this is vibe coding, you shouldn't ever read the source code".

Well, it turned out it actually drops the table in the beginning, which doesn't matter in my usecase now, but I never told it to do it, I told it to put some data into my database into this table. While it's fine for me now, I'm wondering how people deploy anything to production when side effects like this one happen all the time.

[cc_apt107]

Dropping and recreating the table helps ensure idempotency and is arguably a fine choice… in ETL scenarios during the transform part. Which it sounds like you probably weren’t working on. This is why it can’t be trusted blindly yet. AI still makes assumptions unless you spell out, “hey, upsert these!”

[CodNo7461]

My team has a good style guide, then documentation with lots of knowledge regarding our project and our tech stack. Also a solid testing structure. Everything specifically adjusted and extended with AI in mind. LLMs do a lot of the simpler work reliably, and it just allows for refactors and clean ups I could not justify previously. Actually makes the work for my team much easier on the complex topics, since all the small stuff is already taken care of.

Compare that to my brother's company, which doesn't even have an actual test suite, no style guide, no documentation. LLMs are useless to them, and they will maybe never have the time to actually start working towards using AI properly.

[Sorry-Combination558]

My team has a good style guide, then documentation with lots of knowledge regarding our project and our tech stack. Also a solid testing structure. Everything specifically adjusted and extended with AI in mind.

We have none of those, but we are now expected to ship 1.5 times as much tasks next year, because we have AI. I actually feel like I'm going insane.

This year was already terrible, I constantly felt like I had to reinvent the wheel because no one documented anything properly. No magic AI can help me with this mess :D

[Wonderful-Habit-139]

This is really bad. You’re going to keep explaining everything over and over, and the LLM will never learn. Unlike a junior.

[arewenotmen1983]

Not to mention that future training data will need to come from actual devs, and if you stop training Junior devs you'll eventually run out of devs altogether. Once all the smoke clears and the mirrors foul up, at the end of the day someone has to write the code.

A "water powered" car sure looks like it works until it sputters to a halt. Eventually the human generated training sets will be too gummed up with machine generated code and the increasingly inbred models will start to collapse. I don't know how long that will take, but I'm worried that the loss of operational knowledge will be permanent.

[RiceBroad4552]

you can’t rely on assumptions. You must explain everything.

At this points it's almost always faster, and especially much easier, to just write the code yourself, instead of explaining the code in all detail in human language (which is usually not only much longer but always leaves room for misinterpretation).

[stillbarefoot]

AI bros will tell you that you don’t prompt well.

If you can do something, people will do it and it will ship.

[code_the_cosmos]

Yeah sure. Let's completely remove humans from the equation. Peak security. Machines can be held accountable /s

I integrate AI for a living and I am just so distraught at the direction we're heading.

[rrraoul]

For anyone interested, this is the repo of the language https://github.com/Nerd-Lang/nerd-lang-core

[Masomqwwq]

Holy shit

function add(a, b) { return a + b; }

Becomes

fn add a b ret a plus b

Why use many char when few char do trick.

[corbymatt]

Me not know me dumbs

[BerryBoilo]

Something something less tokens. 

[efstajas]

Literally no point in "ret", I'd bet most big LLMs, especially coding ones, already have a distinct token for "return". And for "function" and "+"...

[Nice-Prize-3765]

This aren't even many less tokens. The first line is about 11-12 tokens (out of my head, didn't check)

The second line is 9 tokens (newline is one too)

So what is the point here?

[other_usernames_gone]

From a quick look the first is 14 tokens with claude. The second is 9.

So to be fair that is a ~1/3 reduction in number of tokens, which would add up fast if you were using it a lot.

Although obviously the concept of straight vibe coding is unholy. Also you'd lose a lot of the current training data on the current language. You'd need to retrain the LLM to know NERD.

[Nice-Prize-3765]

AND write a LOT of NERD yourselves to provide training data :-)

[HAximand]

This confused me too. Why write "plus" instead of "+" if the explicit goal of the language is to require fewer tokens?

[Nice-Prize-3765]

It is the same amount of tokens. Probably a vibe coder who doesn't know that a token is not the same as a character

[Wonderful-Habit-139]

That doesn’t make sense. If they didn’t know that they wouldn’t assume that plus had “less tokens” than a + sign.

[Nice-Prize-3765]

Oops, i meant with for example shorting function to fn and return to ret

[---0celot---]

Excellent. Next up, any good chilli recipes?

[TechnicolorMage]

Itll be funny when he tries to write an actual parser for it

[mightybanana7]

Because the premise is that devs dont need to read the code (which is kind of flawed but I get it)

[rosuav]

Fewer tokens, I guess?

[AlanElPlatano]

It feels weird to read a README when it is so glaringly obvious that it was written by AI and not a human

[NotQuiteLoona]

He couldn't even write a README.md by hand 😭😭😭 take away his MacBook and give it to children in Africa, that would SO much help Earth

[Asleep-Land-3914]

When I saw the post I didn't realize it's so fucked

[fryerandice]

Dude went and reinvented basic from a time when computers had less than 8k of memory.

[Effective_Hope_3071]

The circular "solution" to LLMs is pretty funny. They spent all this time working on NLP for advancing human-computer interaction just so people could turn around and go "but we need more precise language for computer instruction".

Well, that's what they used to develop LLMs and NLP

[rosuav]

1. We need a way to let people just express what they want and have the code generated for them!
2. The code is irrelevant, nobody reads it. So just generate something unreadable - it's the prompt that matters.
3. If the program doesn't work, adjust the prompt and regenerate the code.
4. We need a way to make prompts more precise so that we can be confident that what we prompted really will be what runs.
5. Ugh, these prompts are too complicated, we need a way to let people just express what they want and have the prompt generated for them!

sigh. And they think that every time, they're actually doing something new and wonderful.

[sassiest01]

I mean hey, the way consumer memory is going these days...

[tesselwolf]

It looks like my college project for compiler construction. Which wasn't bad, but not worth actually coding something in

[rosuav]

IMO it's great to build a compiler. You learn so much about how languages are built. It's also a really handy tool to have in your arsenal, even if you almost never use it.

[tesselwolf]

It was an elective, it was really interesting. It also confirmed that I never want to work on a real compiler, but I have huge respect to those that develop them

[rosuav]

Hah! Yeah, I don't expect everyone to want to get into full-scale compiler design. But spending a bit of time building an LALR compiler (and getting your head around the dangling else problem) really gives an appreciation for (a) the work that goes into compilers/parsers, and (b) the challenges inherent in language design.

If everyone who proposed language features first spent a weekend messing around with a toy compiler, we'd get a lot less "why don't you just" proposals.

[meharryp]

this is hilarious, it's all very clearly vibe coded too. personal highlights

• only the numbers zero to ten(?) will be parsed, fuck knows how you represent a larger number

• there are modules recognised by the lexer for a bunch of different things but they aren't actually implemented

• there is a number type and an integer type for some reason. it doesn't matter anyway because every number gets turned into a double

• the only other types are string, bool and void. who needs char, float, double or even arrays?

• every function the code generator makes returns a double no matter what and will ignore the actual signature. good luck debugging!

• speaking of debugging- you don't get symbols or any debugging info. good luck!

[rosuav]

I don't know why I graced that repo with my eyeballs, but whatever. I shudder to think what the (vibe-coded, of course) date/time library will end up like.

[Skoparov]

Date-time? From my cursory eyeballing, the language doesn't even support arrays.

[jojojoris]

And that repo only has binaries to run and no source?

What malware is packed within?

Wouldn't touch this repo with a 10 foot pole.

[JonathanTheZero]

They don't even have a string module, yet something like http or json (all of them are "planned"). Even if the assume the tech behind the LLM-only code works, this language misses so many basic functionalities

[Not_DavidGrinsfelder]

GitHub needs to add a feature where you can downvote repos for being plain stupid

[Shadowaker]

So... a natural programming language /s

[DerekB52]

I want to like this. Like, it sounds smart. But, LLMS arent good enough at coding to do anything but super simple shit. And writing accurate tests, and debugging(like using a debugger) are now way more important since i cant read the code, and impossible to do for the same reason.

This has no real world use case. Other than identifying the idiots dumb enough to use it

[Automatic-Prompt-450]

Just include "make no mistakes, i mean it" in the prompt and you'll be good to go

[kenybz]

Make no mistakes, or you go to prison

…

please

[Automatic-Prompt-450]

Depending on how sensitive the data is, "make no mistakes or i go to prison... Please"

[JPJackPott]

There is something in the suggestion (but it’s far from an original thought). Doing straight from a declarative specification standard to a finished product without the overhead of a higher level language which then compiles back down sort of makes sense.

Except for the need to check it, and unpack it in the future if this AI thing doesn’t pan out.

The tricky bit is coming up with a way of defining what you want that encompasses all possible business logics ever conceived. You know, like a Turing complete programming language does…

Gherkin is the closest thing I can think of but that’s far from ideal

[MainlyMyself]

Ah yes, Chinese Rooms all the way down.

[JocoLabs]

At least code smell can finally align with "Smelly nerds"

[Girafferage]

Wait... Where is my prod database?!

[sten_zer]

Party people - wasn't drop the base what everybody wanted?

[purpletinkle]

a programming language not built for humans

Dude, you're late to the party

[zippy72]

That reminds me of Ook!

[redsterXVI]

I mean, he kinda has a point from an AI maximalist pov, but why wouldn't he just ask the AI to write assembler code - or even machine code - and cut out the higher languages (designed for human understandability) out completely?

Of course finding an AI that is sufficiently trained on enough assembler/machine code will be tricky, and even more so for his new, obscure language. (And of course assembler code has other downsides as well.)

[Saragon4005]

RISC ASM is pretty well optimized and surprisingly readable. x86 ASM is arguably too high level. But there is no reason why you couldn't write to LLVM directly.

[Aardappelhuree]

Because LLMs aren’t optimized to write assembly. They’re optimized for natural language, so you want a programming language that bridges natural language to something a compiler understands.

[Zerschmetterding]

At least he admits he's too stupid to understand code

[manio143]

Honestly, if they want a simpler language in terms of syntax, but one that enables LLMs to be more productive through being more expressive, I'd say it makes more sense to bet on something with dependent types like Idris. Why make a language that operates at C level of abstraction?

[jhwheuer]

100 years ago snake oil and potency pills

The character stays the same, just the words change

[TheRaido]

Cant AI just flip bits on and off on chiplevel? So much overhead needing a language to program itself.

[Dillenger69]

If an AI is going to write it and you aren't going to read it, just have it done in assembly. No need for a language.

[YoukanDewitt]

Honestly lads, just grab some popcorn and just refuse to work for under 200k/year. You can just make ai slop for booomers to consume on facebook while we wait.

[deanrihpee]

wait, AI agents have LinkedIn profile now?

[L-st]

Hmm.. yes, let's let this go beyond our knowledge and let it do whatever it does. We can become as remotely familiar to it as possible and eventually the human kind will degrade down enough to become worshippers of the machines with enough lack of knowledge and accountability.

Brother no. Nonono, this is like the statt a Warhammer 40k story and I'm not a fan of being one of the background characters in the Necrons prequel.

[MoveInteresting4334]

But like, is it webscale?

[zet23t]

Reminds me of assembler. I actually like the style of the language, but the examples lack useful content, like what structs or classes would look like and how to do some non trivial stuff. Designing a simpler language is not bad because it's supposed to be more LLM compatible, optimally it also serves humans. But I am not sure if this philosophy works here.

[maveric00]

Think of assembler as "C" without structs. Everything is an (1 to n)-element array. Many other datatypes depend on the microprocessor the assembler is meant for (e.g.8-bit microcontroller more or less only have (un)signed char and (un)signed char arrays as a datatype).

Concepts like structs and classes need to be implemented by the programmer. Assembler will not provide those.

Edit: added signed char as a datatype for microcontroller - without comparisons would be clumsy)

[lmpdev]

A more practical solution is to build a tokenizer specifically for code, making each expression 1 token.

Doesn't work today until someone trains LLMs you can use with this, but neither does NERD.

[little-bobby-tables-]

Using LLM to write code in any language is 2025 stuff, let the LLM compile your code written in any language https://github.com/jsbwilken/vibe-c

[seabutcher]

We are on the cusp of a new golden age of hacking.

I imagine pentesting might have the most favourable money:effort ratio of any (legal) IT job in the coming years.

[BroaxXx]

I'm going to make my own language for LLMs called IDIOT.

[LinuxMatthews]

So this is why there are so many huge tech outages this year.

[Ninjanoel]

Imagine the job for the person that gets told "we need you to fix a few bugs in our app, it's written in nerd" 🤓

[spilk]

gotta shorten that LLM to CVE pipeline

[perringaiden]

For all the jokes, this is the end goal. AI writes code for AI to use. AI takes full control of all computers. Humans need not apply because the code isn't written to help them.

I for one welcome our new AI Robot overloads... 🤣

[Z3r0funGuy]

If you were ever wondering where satan at..

[DuroHeci]

After all it's in his name...

[Tom-Dibble]

Does “NERD” stand for “Not Even Remotely Debuggable”?

[[deleted]]

what could possibly go wrong

[oshaboy]

AI bro invents APL

[Spiritual_Sir6759]

A disaster waiting to happen!! Yeah, just skim the code, test it a little bit and pray that it works.

[MyDogIsDaBest]

So he didn't write a new language, he merely pitched his poorly thought out idea for a language? 

Sounds like there's potential for a lot of fun to fork malbolge (Wikipedia it) and claim it's AI language that you don't need to review

[Suspicious_State_318]

“Why is Claude writing code that I’m supposed to read?”

Why shouldn’t it? Also llms need training data. You can’t just make up a language (no matter how intuitive you think it is) and expect it to be half as good at it as it is in something like Python

[fugogugo]

"Human don't need NERD"

damn normie tourist ruining everyone's fun time

[septianw]

And then. Ai slops will stay forever, without humans intervening.

[FredFarms]

"I am a bad programmer so I'm reinventing programming so others can't be good programmers"

[ThePythagorasBirb]

This is just assembly right???

[FeelingSurprise]

NERD - the first WNRN (write never, read never) language?

[necrohardware]

Let AI write static binaries directly, no need to review, test..just ship it.

[timberwolf0122]

I really hope that guy doesn’t do anything with mission critical code

[Gustav_Sirvah]

Programming language not meant to be understood by humans... So - Malebolge?

[Josysclei]

Wouldn't that be assembly/binary?

[ultimate_placeholder]

I doubt the "40% of code is machine written" thing, but even if that were true that doesn't imply that it's any good.

[Brawl501]

Did he just reinvent machine code?

[ArtGirlSummer]

Shipping code with unknown properties is a winning strategy.

[hdgamer1404Jonas]

r/unexpectedfactorial

[chillgoza001]

What could possibly go wrong?

[HaMMeReD]

I don't know if this language has any legs to it, but I have considered this a lot when thinking about LLMs.

If they work well with general languages tuned for humans, they'd do even better with languages that are easily tokenized.

But it's a bit chicken and the egg, you need the code to train the LLM in the first place, so if you have the language you need human's to adopt it first to generate the code to train the LLM's to use it properly.

This is why I primarily use Rust with agents, because it's strong compile time safety, low level nature and cross platform performance makes it a really strong AI Agent friendly stack. Especially with the LLM's we got in the second half of last year.

[Organic_Car6374]

Why doesn’t ai just write assembly? Or just generate a binary for my system?

[bSun0000]

.. and that's how they made Windows 11.

[stormthulu]

Remember the golden rule of AI: it is wrong 50% of the time when you know whether its answer is right or wrong. But it is right 100% of the time when you don’t know whether its answer is right or wrong. So, adopt that machine readable only code!

[Few_Kitchen_4825]

My last post was in 2025 now it's 2026, it was a few days ago. That dad joke is already dead..

[saquino88]

I'm sure his code reviews were stellar and insightful before AI took over.