Its only a good idea if you work in selling tokens, otherwise you're dooming anything other than a simple app to inevitably breaking after it hits a certain level of complexity

Where are all the vast quantity of LLM commits for these open source projects, if these engineers are truly 10xing their productivity with LLM code generation? Because I regularly browse the source of many of these, and can find almost no evidence that LLM code generation is anywhere near the level of productivity being claimed for:

1. ImGui

2. SFML

3. SDL

4. GLFW

5. OpenSSL

6. Linux

7. GCC

8. Clang/LLVM

9. Libc++/libstdc++/msstl

10. Rust

11. Godot

12. Nlohmann

13. Boost

14. Python

15. GNU tools

Etc etc. There are even more major projects, but these are just the critical ones I can think of off the top of my head. If you go for a browse though eg Godot, you might think that LLMs don't exist. In fact if you go for a browse through any of these, you might think that LLMs are borderline never used for code generation in the open source world. This is a diverse collection of random projects, and yet for some reason none of these have experienced a 10x increase in productivity in any form from any contributors from LLM code generation

>That is not why. Or at least not the majority of it

Its not the quantity, if maintainers were receiving incredibly high quality PRs that could just be merged, they'd be very happy. Godot is an example of a project that was initially pro LLM, and then had to about face because the PRs were just absolutely crap

>Some might be trash, some might be gold

Is there any evidence that any of these PRs have ever been gold?

Then all it'd take is one of these engineers blowing the lid on their whole secret LLM contribution strategy to absolutely break the industry wide open to the benefits of these massive productivity increases, and finally prove all the doubters wrong. They sure are good at keeping secrets that would directly benefit them to expose

Or, failing that, you'd think any of these engineers - given the truly vast amount of programming power now available at their fingertips with their 10x productivity - would have simply replaced these projects. It'd only take a few 10xers who wanted to show that everyone else was wrong. That's how open source often works, someone just gets a been in their bonnet and then we get linux

Instead: I can't find any of it. There's no evidence of this productivity boost in the wild. There aren't new high quality 10x open source projects springing up that are replacing everything. There aren't high quality LLM contributions, feature development isn't going faster. There's almost no evidence of high quality AI code generation at all in the open source space, existing projects or otherwise

Where's all the code? I want the receipts if people are claiming a 10x productivity. Because at the moment, the much more likely explanation seems to be that its simply not true

Eg if you check out Godot, initially they were cool with LLM code, and then had to clamp down on it because it was not leading to anything good

Instead, if you check out something like ImGui, we can see that its largely just Omar as usual with a bunch of PRs. Nothing much seems to have changed, feature development carries on at the same pace as it did previously. This is replicated across nearly every single major long term open source project I can find

The only reason developers now feel the need to hide their LLM usage is because the LLM contributions have all been shockingly bad, so you're reversing cause and effect. If LLM contributions had been incredible, they wouldn't be frowned upon socially now. Surely someone would blow the lid on this huge covert conspiracy about how incredible their contributions to.. SFML have been?

This effect also wouldn't prevent LLMgineers from creating their own open source projects that should be absolutely outstripping the existing open source space. After all how old is ImGui? With a 10x productivity gain, it should take a year of development to easily match its features if those gains are truly real now

>if they're really good and use LLMs responsibly, they probably don't even have any ethical obligation to label LLM involvement

The copyright issues means that non disclosure is inherently unethical

Instead, software is plodding along exactly the same as it did prior to LLM code generation, and there's no evidence of superprogrammers making superprojects in 1/10th of the time. With a 10x productivity gain, what used to take a year should take a month

Nothing's stopping core developers from adopting LLM generated code for themselves, while banning it for external contributors

I think its fascinating just how much of a gap there is between what's being claimed, and the verifiable observable data of the open source world. Major open source projects are by and large starting to ban LLMs now, because the contributions made by LLM users have been universally terrible and unhelpful. There doesn't appear to be a single major project that's found generating code to lead to major productivity speedups, and the consensus appears to be that its just lead to a lot of crappy contributions that are harder to spot immediately as being obvious crap

I regularly see people claim that they are now 10x more productive with LLM code generation, and I just wonder where all the code is. Is it somehow true that these gains are only being realised in proprietary projects, and not a single one of them has put even a small fraction of their new found engineering powers into eg Godot? Why do only the poor quality LLM code generation users make PRs to open source projects, and never the engineers that know how to really use it correctly?

If you look in the open source major project space, you can find almost no evidence that AI code generation exists at all. Go browse your favourite critical tool and look for AI generated PRs that have landed in the codebase, its probably a tiny handful of them in comparison to the human written PRs prior to an LLM ban. It turns out that once you have a verifiable, open quality review bar, for some reason almost no LLM commits really meet the level of quality necessary

I strongly suspect that what we're seeing is that much of the tech code-writing economy had already become completely performative prior to AI turning up. It no longer matters in the current age if your code is good, or works, because your job is to give the illusion of product development while the stock market price gets pumped, until you all cash out your share value, get bought, or hop jobs in 2 years. For many companies it literally does not matter if you produce anything that generates value (or works), because the illusion of progress is all that matters. AI is absolutely incredible at creating the illusion of progress, because it looks a whole lot like real code, it just appears to have failed the bar of making actual projects that work. If that was never the goal in the first place, it probably really is a 10x productivity boost

Eg: Any web request is a security vulnerability, there's no way to do it if the web requests are being made maliciously

Say that we have an agent with access to get requests, solely to a single site https://yoursite.com without subdomains. In this case multiple requests can be sent, and the time between requests can be used to exfiltrate personal data, similar to the coffee shop attack but without the subdomains. If the AI is able to make requests in any form, some information can be leaked, where the amount of leakable information is tied to information theory content of whatever side channel is being used. The only 0 information channel is.. never to make a request

You could also completely trust the 3rd party you're connecting to, but that to me seems like a hard error in the modern internet

Because as the OP of this thread and LLM users are rediscovering, that understanding is the most critical part of software development

>I don't think this personal opinion holds well when contrasted with reality. The truth of the matter is that in moderately large codebases, which is the norm in any production setting, at best you have a T-shape understanding of the system: in specific areas you might have somewhat deep understanding, but for the vast majority of the system you have at best a high level understanding of the software architecture.

I suspect a lot of people haven't worked on a system with engineers who've been there for 20 years working on it. There's simply no substitute for that kind of deep institutional knowledge, and it'll take you 5-10 years to be as productive as them simply because of that level of extreme knowledge about a codebase. It isn't as sexy as swapping jobs every 2 years though, so you have to go outside of the big tech bubble

If you don't engage your brain, it'll rot. That's far more important in the long term than a 5% productivity boost or something. I have no idea why you'd trade off your entire technical development and skillset training, for the most short term gains, it doesn't even theoretically make sense if you care about long term productivity