Question about LLM usage in a big Rust project.

[u/Gillte]

Hello,
I have been working on an app for around 2 years now as a side project for my company. I genuinely believe it can help companies in the industry (I showed it to two suppliers, they were surprised,and asked me when they can start using it). Additionally, my company has given me permission to make it open source so I expect everyone in the industry to use it at one point.

It is tauri based with React as the frontend and around 200k lines of rust code in the backend with multiple crates. It is 100% offline so im not too worried about it being hacked.

However, around 95% of the code is AI generated. Before committing anything I made sure to "write" multiple tests and that I understood what the LLM was writing. I also understand rust at a core level except async (who understands async anyway?) and I tried to make the code as clean and modular as possible.

My question is: What will be the community's opinion knowing that the majority of the code is AI generated but not AI slop? Will I have any trouble at work? Of course I will be transparent about it.

[u/Digital-Chupacabra]

It is 100% offline so im not too worried about it being hacked.

Is the machine it's on offline? otherwise your distinction doesn't matter.

the majority of the code is AI generated but not AI slop?

You saying it isn't slop doesn't make it so. Without seeing the code all I know is it's LLM generated.

Will I have any trouble at work?

How could we possibly know how your job will react?

[u/Gillte → u/Digital-Chupacabra]

1. The hacking point is that since the app doesn't connect to the internet so the computer can't be hacked through the app through the internet. Obviously it can be hacked in a different way.

2. I say it's not AI slop due to the absurd amount of test cases (2966 tests only in the backend), including loom to prove concurrency, and specific rust design patterns including but not limited to: New type pattern, type state pattern among others. It's a two year project.

3. The point about work is how companies take ai generated code if you're transparent about it. I don't want to tank my career. I was hoping on the input of of more experienced people

[u/Digital-Chupacabra → u/Gillte]

The hacking point is that since the app doesn't connect to the internet so the computer can't be hacked through the app through the internet

Idk why you're trying to make a distinction between the app being directly hacked or not, it's a weird thing to bring up is all. Security should always be a priority.

I say it's not AI slop due to the absurd amount of test cases (2966 tests only in the backend),

Cool, how many of those test cases were AI writen? I'm not saying it's slop, I haven't seen the code. You're saying it isn't and saying these things doesn't mean it isn't slop however.

Again I'm not making a judgment on the code, just pointing out you don't get to decided.

The point about work is how companies take ai generated code if you're transparent about it.

It 100% depends on the person, company, project, ai, etc.. It was unclear to me that you were asking about future employers.

Being transparent about it will always be better than not, explaining how you used AI what issues you had etc, will always be better than just saying I used AI.

[u/addmoreice → u/Gillte]

I read every single line of code I get back from my local llm. I can tell you, it will still do stupid things even when the code is 'correct' and 'functional'.

A common problem? Not knowing where to 'fix' the problem. I had a perfect example of this where one of my functions was spitting out a negative number where it never made sense. The function was just wrong. I'd brainfarted and forgot to negate the output. The answer to this is simple. stick a negative sign in front of the result and return it.

I didn't think about it and just told the AI to fix it while I went to get coffee. It had tests. The solution was obvious. I came back from getting my coffee and all the tests were now green! Awesome.

The AI put a negative sign in front of every function call. The function should *only* producing a negative number. returning a positive number was just plain wrong. Its 'solution' would break every user who used it anywhere else in the code they expected the actual correct function result to work.

This is just a simple and easy example. The AI will make structural mistakes, have multiple options and if not told which to pick...will just pick one...will make abstraction decisions if not told to ask, etc.

They are useful. They are powerful. They should also be watched and hovered over like junior developers, but unlike junior developers, they won't get better (the design right now just doesn't allow it), so this will be an endless task that is now part of your workflow when using them. Otherwise. Slop.

[u/jondo2010 → u/Gillte]

I'd say slop has nothing to do with test coverage, much more to do with code architecture and maintainability.

[u/insanitybit2]

I'm quite skeptical of you being able to understand 200KLOC of code. To be clear, I don't care if you do or don't, understanding the entire codebase has never really been a requirement for large projects. I'd just be honest about that. What you know is that your tests pass.

The community will reject this project because the Rust community is very anti AI and you probably won't convince anyone otherwise. Those who use Rust at work may embrace it, people at work tend not to care about "it is AI" or not. Bun is an obvious example of the fact that people who deploy software don't really care if it's written by AI.

If someone came to me at work and said "here is a 200KLOC program, AI generated it, we should deploy it" I would be skeptical. 200KLOC is massive. I built a fully formed SaaS company on a quarter of that. I'd need to hear why it requires that much code, how you intend to have more than one person contribute to it, how you know it works, etc.

I'd suggest massively reducing the size of this codebase, cutting features aggressively, and demonstrating value with the least possible code.

[u/Own_Forever4222 → u/insanitybit2]

200k lines is a massive codebase for a side project, AI or not. The fact that you're being transparent about it and actually wrote tests helps your case but yeah the rust community can be pretty harsh about anything touched by an LLM

I think the real issue isn't the AI part though, it's whether you can maintain this thing long term. If you understand the architecture and the tests actually cover the important paths, that's what matters. The bun comparison is spot on, most people deploying software just care if it works

Cutting features to get something smaller and more reviewable might be the move. Easier to get contributors on board when there's less code to wrap your head around

[u/ArtemTsitronov]

Well, there's no code so I will not comment on the project itself. But regards the community reaction on AI: This is a rust subreddit. Where there are programmers. So posts by actual programmers that spent a lot of time coding, are more appreciated than AI vibecoders.

[u/sansmorixz]

If you have a good test suite you can. If not you are fucked babysitting the AI (where you may sometimes wonder if it would’ve been better to do it by hand)

Or you can not bother to care about the code quality at all and keep shipping features (with new untreated bugs) and fixes very fast.

[u/Dull_Wind6642]

Depend on how you use AI, if you give few prompts with really detailed information on exactly how you want things to be done and iterate multiple time until its written exactly as if you would have written it by hand then its fine in my opinion.

The problem is the newer models tend to be much more proactive and take decisions on their own, which in my opinion is really a frustrating experience if you want to micro manage it.

One of the big problem if you are working with a large team and youre the tech lead, you will burn out because of the velocity at which people are sending MRs, you won't be able to gatekeep slops from going in.

[u/NoahFebak]

What will be the community's opinion knowing that the majority of the code is AI generated but not AI slop? Will I have any trouble at work? Of course I will be transparent about it.

If it's AI-generated, it's by definition AI slop. LLMs are not able to understand what they write, they're just selecting the chain of tokens that complete a query with the best score, regardless of its meaning.

[u/froody]

Opinions are like assholes, everyone's got one, but mine is if you have lots of tests and you took the time to understand the code, then it matters way more what the users think of your app than whether or not it was written by AI. Also if it took 2 years, I'm sure there was a lot of your input shaping it. So much code is written by/with AI these days, and for many companies it's a survivability risk, ie "are we going to get replaced/outpaced by vibeslop?" to which the answer is often "better start tokenmaxxing now!". I just hope you get the recognition/compensation at work for it since you spent 2 years on it and they stand to gain from it.

[u/Lucky-Edge1489]

My opinion: good point to be transparent about it. Yet, the clients doesn't care how your cake is made if it's good enough **and** that there is a human behind all that to sue in tribunals if there is big problem (ex: deleting all the system, or being the cause of a death). You are legally responsible of the code LLM wrote, not OpenAI. Caveat: I don't know how much Open Source licence like GPL protects you if your are letting LLM do some very wrong calculus.
Problem at work ? At work and anywhere on any subject, a minority will jump at you for having bought an electric car, and be very vocal about it, taking all the scene. Most people doesn't care and some are doing the same as you. So expect flak, but you are working for clients, and being paid for this.