The problem with AI isn’t new, it’s the same old problem with technology: computers don’t do what you want, only what you tell them.
A lot of PRs can be judged by how well they are described and justified, it’s because the code itself isn’t that important, it’s the problem that you are solving with it that is.
People are often great at defining problems, AIs less so IMHO. Partially because they simply have no understanding, partially because they over explain everything to a point where you just stop reading, and so you never get to the core of the problem. And even if you do there’s a good chance AI misunderstood the problem and the solution is wrong in a some more or less subtle way.
This is further made worse by the sheer overconfidence of AI output, which quickly erodes any trust that they did understand the problem.
We need a clearer framework for AI-assisted contributions to open source
51–60 of 161 posts
Re: We need a clearer framework for AI-assisted contributions to open source
#52Anyone else feel like we're cresting the LLM coding hype curve? Like a recognition that there's value there, but we're passing the frothing-at-the-mouth stage of replacing all software engineers?
When people talk about the “AI bubble popping” this is what they mean. It is clear that AI will remain useful, but the “singularity is nigh” hype is faltering and the company valuations based on perpetual exponential improvement are just not realistic. Worse, the marginal improvements are coming at ever higher resource requirements with each generation, which puts a soft cap on how good an AI can be and still be economical to run.
Re: We need a clearer framework for AI-assisted contributions to open source
#53Earlier quoted context omitted.
Its not the set of the TV show I beliefe, but a recreation. https://nypost.com/2015/06/23/you-can-now-visit-the-iconic-s... It looks a bit different wrt. the stuff on the fridge and the items in the cupboard
I'm not sure what you mean. Those two photos are very different. The floors are entirely different, the tables are entirely different, one of the chairs/couches is different, even the intercom and light switch are different. In any case, though, neither one is a movie set.
I think we agree, it looks like the seinfeld set, but it not the orginal set, just something looking very similar.
Re: We need a clearer framework for AI-assisted contributions to open source
#54Shouldn't there be guidelines for open source projects where it is clearly stipulated that code submitted for review must follow the project's code format and conventions?
> that code submitted for review must follow the project's code format and conventions
...that's just scratching the surface.
The problem is that LLMs make mistakes that no single human would make, and coding conventions should anyway never be the focus of a code review and should usually be enforced by tooling.
E.g. when reading/reviewing other people's code you tune into their brain and thought process - after reading a few lines of (non-trivial) code you know subconsciously what 'programming character' this person is and what type of problems to expect and look for.
With LLM generated code it's like trying to tune into a thousand brains at the same time, since the code is a mishmash of what a thousand people have written and published on the internet. Reading a person's thought process via reading their code doesn't work anymore, because there is no coherent thought process.
Personally I'm very hesitant to merge PRs into my open source projects that are more than small changes of a couple dozen lines at most, unless I know and trust the contributor to not fuck things up. E.g. for the PRs I'm accepting I don't really care if they are vibe-coded or not, because the complexity for accepted PRs is so low that the difference shouldn't matter much.
Re: We need a clearer framework for AI-assisted contributions to open source
#55It is possible that some projects could benefit from triage volunteers?
There are plenty of open source projects where it is difficult to get up to speed with the intricacies of the architecture that limits the ability of talented coders to contribute on a small scale.
There might be merit in having a channel for AI contributions that casual helpers can assess to see if they pass a minimum threshold before passing on to a project maintainer to assess how the change works within the context of the overall architecture.
It would also be fascinating to see how good an AI would be at assessing the quality of a set of AI generated changes absent the instructions that generated them. They may not be able to clearly identify whether the change would work, but can they at least rank a collection of submissions to select the ones most worth looking at?
At the very least the pile of PRs count as data of things that people wanted to do, even if the code was completely unusable, placing it into a pile somewhere might be minable for the intentions of erstwhile contributors.
Re: We need a clearer framework for AI-assisted contributions to open source
#56Earlier quoted context omitted.
I'm not sure what you mean. Those two photos are very different. The floors are entirely different, the tables are entirely different, one of the chairs/couches is different, even the intercom and light switch are different. In any case, though, neither one is a movie set.
I think we agree, it looks like the seinfeld set, but it not the orginal set, just something looking very similar.
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Re: We need a clearer framework for AI-assisted contributions to open source
#57Shouldn't there be guidelines for open source projects where it is clearly stipulated that code submitted for review must follow the project's code format and conventions?
> that code submitted for review must follow the project's code format and conventions ...that's just scratching the surface. The problem is that LLMs make mistakes that no single human would make, and coding conventions should anyway never be the focus of a code review and should usually be enforced by tooling. E.g. when reading/reviewing other people's code you tune into their brain and thought process - after read…
Also there’s two main methods of reviewing. If you’re in an org, everyone is responsible for their own code, so review is mostly for being aware of stuff and helping catch mistakes. In an OSS project, everything’s is under your responsibility, and there’s a need to vet code closely. LGTM is not an option.
Re: We need a clearer framework for AI-assisted contributions to open source
#58We’re fixing this slop problem - engineers write rules that are enforced on PRs. Fixes the problem pretty well so far.
Re: We need a clearer framework for AI-assisted contributions to open source
#59I wouldn't call it "vibe coded slop" the models are getting way better and I can work with my engineers a lot faster. I am the founder and a product person so it helps in reducing the number of needed engineers at my business. We are currently doing $2.5M ARR and the engineers aren't complaining, in fact it is the opposite, they are actually more productive. We still prioritize architecture planning, testing and havi…
What do the spends for AI/LLM services look like per person? Do you track any dev/AI metrics related to how the usage is in the company?
Re: We need a clearer framework for AI-assisted contributions to open source
#60Anyone else feel like we're cresting the LLM coding hype curve? Like a recognition that there's value there, but we're passing the frothing-at-the-mouth stage of replacing all software engineers?
Well, when MS give OpenAI free use of their servers and OpenAI call it a $10 billion investment, then they use up their tokens and MS calls in $10 billion in revenue, I think so, yes.