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How I program with LLMs

crawshaw.io

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Re: How I program with LLMs

#31

Post by j45 »

notjoemama wrote: post #7

Our company has a no AI use policy. The assumption is zero trust. We simply can’t know whether a model or its framework could or would send proprietary code outside the network. So it’s best to assume all LLMs/AI is or will send code or fragments of code. While I applaud the incredible work by their creators, I’m not sure how a responsible enterprise class company could rely on “trust us bro” EULAs or repo readmes.

Local LLMs for code aren't that out of the question to run.

Even for not code generation, but even smaller models only for programming to weigh on different design approaches, etc.

Re: How I program with LLMs

#32

Post by [deleted] »

LeftHandPath wrote: post #25
bangaladore wrote: post #19

The killer feature about LLMs with programming in my opinion is autocomplete (the simple copilot feature). I can probably be 2-3x more productive as I'm not typing (or thinking much). It does a fairly good job pulling in nearby context to help it. And that's even without a language server. Using it to generate blocks of code in a chat like manner in my opinion just never works well enough in the domains I use it on.…

I’ve never used it, simply because I hate autocomplete in emails. Gmail autocomplete saves me maybe 2-5s per email: the recipients name, a comma, and a sign off. Maybe a quarter or half sentence here or there, but never exactly what I would’ve typed. In code bases, I’ve never seen the appeal. It’s only reliably good at stuff that I can easily find on Google. The savings are inconsequential at best, and negative at wo…

[deleted]

Re: How I program with LLMs

#33

Post by joemazerino »

Retr0id wrote: post #13
itsgrimetime wrote: post #11

Earlier quoted context omitted.

IMO this is a bad take. I use LLMs for things I don’t know how to do myself all the time. Now, I wouldn’t use one to write some new crypto functions because the risk associated with getting it wrong is huge, but if I need to write something like a wrapper around some cloud provider SDK that I’m unfamiliar with, it gets me 90% of the way there. It also is way more likely to know at least _some_ of the best practices w…

> if I need to write something like a wrapper around some cloud provider SDK that I’m unfamiliar with But "writing a wrapper" is (presumably) a process you're familiar with, you can tell if it's going off the rails.

Writing a wrapper is easier to verify because of the context of the API or SDK you're wrapping. Seems wrong? Check the docs. Doesn't work? Curl it yourself.

Re: How I program with LLMs

#34

Post by Barrin92 »

itsgrimetime wrote: post #11
mlepath wrote: post #2

The first rule of programming with LLMs is don't use them for anything you don't know how to do. If you can look at the solution and immediately know what's wrong with it, they are a time saver otherwise... I find chat for search is really helpful (as the article states)

IMO this is a bad take. I use LLMs for things I don’t know how to do myself all the time. Now, I wouldn’t use one to write some new crypto functions because the risk associated with getting it wrong is huge, but if I need to write something like a wrapper around some cloud provider SDK that I’m unfamiliar with, it gets me 90% of the way there. It also is way more likely to know at least _some_ of the best practices w…

>It also is way more likely to know at least _some_ of the best practices

What's way more likely to know the best practices is the documentation. A few months ago there was a post that made the rounds about how the Arc browser introduced a really severe security flaw by misconfiguring their Firebase ACLs despite the fact that the correct way to configure them is outlined in the docs.

This to me is the sort of thing (although maybe not necessarily in this case) out of LLM programming. 90% isn't good enough, it's the same as Stackoverflow pasting. If you're a serious engineer and you are unsure about something, it is your task to go to the reference material, or you're at some point introducing bugs like this.

In our profession it's not just crypto libraries, one misconfigured line in a yaml file can mean causing millions of dollars of damage or leaking people's most private information. That can't be tackled with a black box chatbot that may or may not be accurate.

Re: How I program with LLMs

#35

Post by throwup238 »

nemothekid wrote: post #28

I think "Chat driven programming" is the most common type of the most hyped LLM-based programming I see on twitter that I just can't relate to. I've incorporated LLMs mainly as auto-complete and search; asking ChatGPT to write a quick script or to scaffold some code for which the documentation is too esoteric to parse. But having the LLM do things for me, I frequently run into issues where it feels like I'm wasting m…

> "Chat-based LLMs do best with exam-style questions" really speaks to me, however I find that constructing my prompts in such a way where the LLM does what I want uses just as much brainpower as just programming the thing my self.

It speaks to me too because my mechanical writing style (as opposed to creative prose) could best be described as what I learned in high school AP English/Literature and the rest of the California education system. For whatever reason that writing style dominated the training data and LLMs just happens to be easy to use because I came out of the same education system as many of the people working at OpenAI/Anthropic.

I’ve had to stop using several generic turns of phrase like “in conclusion” because it made my writing look too much like ChatGPT.

Re: How I program with LLMs

#36

Post by WhiteNoiz3 »

billmcneale wrote: post #24
mlepath wrote: post #2

The first rule of programming with LLMs is don't use them for anything you don't know how to do. If you can look at the solution and immediately know what's wrong with it, they are a time saver otherwise... I find chat for search is really helpful (as the article states)

That's the wrong approach. I use chat for things I don't know how to do all the time. I might not know how to do it, but I sure know how to test that what I'm being told is correct. And as long as it's not, I iterate with the chat bot.

A better way to phrase it might be don't use it for something that you aren't able to verify or validate.

Re: How I program with LLMs

#37

Post by attentive »

notjoemama wrote: post #7

Our company has a no AI use policy. The assumption is zero trust. We simply can’t know whether a model or its framework could or would send proprietary code outside the network. So it’s best to assume all LLMs/AI is or will send code or fragments of code. While I applaud the incredible work by their creators, I’m not sure how a responsible enterprise class company could rely on “trust us bro” EULAs or repo readmes.

So, you're asking how enterprise class companies are using github for repos and gmail for all the enterprise mail? What's next, zoom/teams for meetings?

Re: How I program with LLMs

#38

Post by jcranmer »

User23 wrote: post #5

LLMs are, at their core, search tools. Training is indexing and prompting is querying that index. The granularity being at the n-gram rather than the document level is a huge deal though. Properly using them requires understanding that. And just like we understand every query won’t find what we want, neither will every prompt. Iterative refinement is virtually required for nontrivial cases. Automating that process, l…

> LLMs are, at their core, search tools.

Fundamentally, no they're not. That is why you have cases like the Air Canada chatbot that told a user about a refund opportunity that didn't exist, or the lawyer in Mata v Avianca who cited a case that didn't exist. If you ask an LLM to search for something that doesn't exist, there's a decent chance it will hallucinate something into existence for you.

What LLMs are good at is effectively turning fuzzy search terms into non-fuzzy terms; they're also pretty good at taking some text and recasting into an extremely formulaic paradigm. In other words, turning unstructured text into something structured. The problem they have is that they don't have enough understanding of the world to do something useful that with structured representation that needs to be accurate.

Re: How I program with LLMs

#39

Post by turnsout »

mlepath wrote: post #2

The first rule of programming with LLMs is don't use them for anything you don't know how to do. If you can look at the solution and immediately know what's wrong with it, they are a time saver otherwise... I find chat for search is really helpful (as the article states)

I completely agree. In graphics programming, I love having it do things that are annoying but easy to verify (like setting up frame buffers in WebGL). I also ask it do more ambitious things like implementing an algorithm in shader code, and it will sometimes give a result that is mostly correct but subtly wrong. I only have been able to catch those subtle errors because I know what to look for.

Re: How I program with LLMs

#40

Post by bitwize »

mvdtnz wrote: post #18
User23 wrote: post #5

LLMs are, at their core, search tools. Training is indexing and prompting is querying that index. The granularity being at the n-gram rather than the document level is a huge deal though. Properly using them requires understanding that. And just like we understand every query won’t find what we want, neither will every prompt. Iterative refinement is virtually required for nontrivial cases. Automating that process, l…

I'm losing track of the number of different things the Hacker News commenters claim LLMs are "at their core".

LLMs are, at their core, fucking Dissociated Press. That's what makes them fun and interesting, and that's the problem with using them for real production work.
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