Comment by yarn_
2 months ago
"Why would I commit something written by AI with myself as author?"
Because you're the one who decided to take responsibility for it, and actually choose to PR it in its ultimate form.
What utility do the reviews/maintainers get from you marking whats written by you vs. chatgpt? Other than your ability to scapegoat the LLM?
The only thing that actually affects me (the hypothetical reviewer) and the project is the quality of the actual code, and, ideally, the presence of a contributer (you) who can actually answer for that code. The presence or absence of LLM generated code by your hand makes no difference to me or the project, why would it? Why would it affect my decision making whatsoever?
Its your code, end of story. Either that or the PR should just be rejected, because nobody is taking responsibility for it.
As someone mostly outside of the vibe coding stuff, I can see the benefit in having both the model and the author information.
Model information for traceability and possibly future analysis/statistics, and author to know who is taking responsibility for the changes (and, thus, has deeply reviewed and understood them).
As long as those two information are present in the commit, I guess which commit field should hold which information is for the project to standardise. (but it should be normalised within a project, otherwise the "traceability/statistics" part cannot be applied reliably).
Yeah, nothing wrong with keeping the metadata - but "Authored-by" is both credit and an attestation of responsibility. I think people just haven't thought about it too much and see it mostly as credit and less as responsibility.
I disagree. “Authored by” - and authorship in general - says who did the work. Not who signed off on the work. Reviewed-by me, authored by Claude feels most correct.
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Future analysis is a valid reason to keep it, thats a good point and I agree with that.
Claude adds "Co-authored by" attribution for itself when committing, so you can see the human author and also the bot.
I think this is a good balance, because if you don't care about the bot you still see the human author. And if you do care (for example, I'd like to be able to review commits and see which were substantially bot-written and which were mostly human) then it's also easy.
> I'd like to be able to review commits and see which were substantially bot-written and which were mostly human) then it's also easy.
Why is this, though? I'm genuinely curious. My code-quality bar doesn't change either way, so why would this be anything but distracting to my decision making?
Personally it would make the choice to say no to the entire thing a whole lot easier if they self-reported on themselves automatically and with no recourse to hide the fact that they've used LLMs. I want to see it for dependencies (I already avoid them, and would especially do so with ones heavily developed via LLMs), products I'd like to use, PRs submitted to my projects, and so on, so I can choose to avoid them.
Mostly this is because, all things considered, I really do not need to interact with any of that, so I'm doing it by choice. Since it's entirely voluntary I have absolutely no incentive to interact with things no one bothered to spend real time and effort on.
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Accountability. Same reason I want to read human written content rather than obvious AI: both can be equally shit, but at least with humans there's a high probability of the aspirational quality of wanting to be considered "good"
With AI I have no way of telling if it was from a one line prompt or hundreds. I have to assume it was one line by default if there's no human sticking their neck out for it.
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LLMs can make mistakes in different ways than humans tend to. Think "confidently wrong human throwing flags up with their entire approach" vs. "confidently wrong LLM writing convincing-looking code that misunderstands or ignores things under the surface."
Outside of your one personal project, it can also benefit you to understand the current tendencies and limitations of AI agents, either to consider whether they're in a state that'd be useful to use for yourself, or to know if there are any patterns in how they operate (or not, if you're claiming that).
Burying your head in the sand and choosing to be a guinea pig for AI companies by reviewing all of their slop with the same care you'd review human contributions with (instead of cutting them off early when identified as problematic) is your prerogative, but it assumes you're fine being isolated from the industry.
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