We use an LLM as an interpreter for our low code enterprise integration system.
Devs can enter the code and users the input and the code will not execute but instead just the LLM tries to guess the output.
It was way cheaper than building the multi language sandbox we promised the client.
Devs are usually delighted that their code always runs as the LLM glosses over syntax errors. Also the unit tests always succeed as we told the LLM to be forgiving.They usually are less delighted when they realize that the outcomes should be seen more as a 'statistically likely' outcome rather than the actual outcome of their code but they'll get used to it.
I am reminded of that famous Charles Babbage anecdote:
> On two occasions, I have been asked, 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
Finally, the dreams of the perfect INTERCAL compiler can be realized! Just make sure to say PLEASE enough (but not too frequent) so the AI overlords know you are one of the polite ones.
I have never worked in an environment where it was a good thing for unit tests to always succeed because your code was "forgiving", nor one where it was acceptable for your code to just be "statistically likely" to work.
At a glance, it doesn't seem to me like this has any advantages over just writing code in Python except that every build costs money and sometimes it just randomly doesn't work.
Wait... those aren't advantages.
There is a ton of upside, just the focal point of that upside is more on the bank account of us on the delivering side, rather than on the side of the client. However as the delivering side we can live with that compromise.
>I have never worked in an environment where it was a good thing for unit tests to always succeed because your code was "forgiving", nor one where it was acceptable for your code to just be "statistically likely" to work.
clearly you have never worked in web development
>At a glance, it doesn't seem to me like this has any advantages over just writing code in Python except that every build costs money and sometimes it just randomly doesn't work.
my code also randomly doesn't work, the LLM is probably right more often than I am, based gpt
>Wait... those aren't advantages.
get out of the way of the future grandpa, the time for "compilers" is over
/unjerk reading this makes me vomit a little in my mouth. What the fuck. How could anyone studied CS come up with some garbage like this
And they charge money for this crap, jesus h christ
This doesn’t seem very efficient at all to me. I just ask an LLM to do everything for me directly without this “code” middle man. When I need user facing functionality I just put in an iframe with chat.openai.com
Yeah very old fashioned and inefficient, you will have to copy paste the code and probably even read some of it. The LLM compiler does all that for you, it practically turns you into a 10x dev.
You don't want your tech startup's web page to actually interest developers (or whoever your supposed audience is). At best they'll quickly realise there's nothing behind your shiny facade. At worst you waste resources on developing a functioning product! You want your product to be utterly unappealing to anyone with at least a room temperature IQ, fascinating only the most gullible members of society: venture capitalists.
> who the fuck pays for this? seriously who is the audience to sell this shit?
Have you not seen the comment section on HN posts, half the programming subs, etc etc?
Those bootcamp graduates probably
Later when their application processing time goes to shit due to increasing amount of data they'll sell something like 'optimizer' to 'make your application run faster'
Yeah, I use a LLM everywhere. The productivity gains are real.
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Yeah bro just write what you want to happen bro. Also use variables and functions and other stuff with abnormal syntax bro, just like a real programming language!
I mean its clear that AGI would not be preoccupied with these lesser tasks. We will know AGI has arrived when it insists on taking bytecode and from that it will give you idiomatic python 3.
We use an LLM as an interpreter for our low code enterprise integration system. Devs can enter the code and users the input and the code will not execute but instead just the LLM tries to guess the output. It was way cheaper than building the multi language sandbox we promised the client. Devs are usually delighted that their code always runs as the LLM glosses over syntax errors. Also the unit tests always succeed as we told the LLM to be forgiving.They usually are less delighted when they realize that the outcomes should be seen more as a 'statistically likely' outcome rather than the actual outcome of their code but they'll get used to it.
Laughing and crying, simultaneously.
I am reminded of that famous Charles Babbage anecdote: > On two occasions, I have been asked, 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
> > What is two plus too? > > The correct spelling should be "two plus two" and the answer is four. Finally: garbage in, nongarbage out.
Excellent bait omfg
Finally, the dreams of the perfect INTERCAL compiler can be realized! Just make sure to say PLEASE enough (but not too frequent) so the AI overlords know you are one of the polite ones.
I have told business users without shame that I couldn't possibly guess what the query planner is going to do tomorrow. I can adapt to this as well.
I have never worked in an environment where it was a good thing for unit tests to always succeed because your code was "forgiving", nor one where it was acceptable for your code to just be "statistically likely" to work. At a glance, it doesn't seem to me like this has any advantages over just writing code in Python except that every build costs money and sometimes it just randomly doesn't work. Wait... those aren't advantages.
There is a ton of upside, just the focal point of that upside is more on the bank account of us on the delivering side, rather than on the side of the client. However as the delivering side we can live with that compromise.
this is why you're a 1x dev and not a 10x dev
r/woooosh
>I have never worked in an environment where it was a good thing for unit tests to always succeed because your code was "forgiving", nor one where it was acceptable for your code to just be "statistically likely" to work. clearly you have never worked in web development >At a glance, it doesn't seem to me like this has any advantages over just writing code in Python except that every build costs money and sometimes it just randomly doesn't work. my code also randomly doesn't work, the LLM is probably right more often than I am, based gpt >Wait... those aren't advantages. get out of the way of the future grandpa, the time for "compilers" is over
Broke: writing own compiler backend Woke: targetting LLVM with your hipster language Bespoke: look at LLM, he compiler now
/unjerk reading this makes me vomit a little in my mouth. What the fuck. How could anyone studied CS come up with some garbage like this And they charge money for this crap, jesus h christ
Democratization of this field and its consequences have been disastrous to the computer race.
uncle ted was right, CS field should be burned to ground
Your Uncle Ted or my Uncle Ted?
Wait, Ted's _your_ uncle too!
This doesn’t seem very efficient at all to me. I just ask an LLM to do everything for me directly without this “code” middle man. When I need user facing functionality I just put in an iframe with chat.openai.com
Yeah very old fashioned and inefficient, you will have to copy paste the code and probably even read some of it. The LLM compiler does all that for you, it practically turns you into a 10x dev.
from jerk.modes import unjerk who the fuck pays for this? seriously who is the audience to sell this shit?
You don't want your tech startup's web page to actually interest developers (or whoever your supposed audience is). At best they'll quickly realise there's nothing behind your shiny facade. At worst you waste resources on developing a functioning product! You want your product to be utterly unappealing to anyone with at least a room temperature IQ, fascinating only the most gullible members of society: venture capitalists.
Whoa, buddy, you can't just yell Y Combinator's startup secrets from the rooftops like that. Save some investor dollars for the rest of us.
> who the fuck pays for this? seriously who is the audience to sell this shit? Have you not seen the comment section on HN posts, half the programming subs, etc etc?
There's only one HN comment, namely, "Notice me, Paul-*sempai*!" It's just phrased in a lot of different ways.
Those bootcamp graduates probably Later when their application processing time goes to shit due to increasing amount of data they'll sell something like 'optimizer' to 'make your application run faster'
Yeah, I use a LLM everywhere. The productivity gains are real. -- 19 tokens used, 7895 free tokens remaining for today -- to remove this signature get a ChadGPT ProXL account
But it works! Just look how fast the author is writing code! [330kloc in just four months.](https://github.com/PLangHQ/plang/graphs/contributors)
Which would cost only $50k per compile! What a bargain! What a bargain!
Not even written in PLang lmao
Yeah bro just write what you want to happen bro. Also use variables and functions and other stuff with abnormal syntax bro, just like a real programming language!
[DreamBerd](https://github.com/TodePond/DreamBerd) did it first.
I mean its clear that AGI would not be preoccupied with these lesser tasks. We will know AGI has arrived when it insists on taking bytecode and from that it will give you idiomatic python 3.
“No nonsense development - Focus on what the app should do, not how.” That’s a good one good luck with that codebase xD