> The real risk with LLM-generated code is that it looks plausible but hasn't gone through the same level of scrutiny. It passes a quick review because it reads well, but edge cases get missed.
Precisely! Because the code is made to believable the risk of accepting it without understanding full implications is very high.
> If the answer is "the same review process we've always had" then the problem isn't AI, it's whether that process is rigorous enough for the stakes involved.
True, but there is also a reputational component to how changes are reviewed (whether we like it or not). The longer the tenure and the deeper the understanding of the changed code is - the chance of careless Pull Request gets lower.
I appreciate hearing your point of view on this. In my opinion the future of Open Source and AI assisted coding is a much bigger issue, and different people have different levels of confidence in both positive and negative outcomes of LLM impact on our industry.
It is great to have a legal perspective on compliance of LLM generated code with DCO terms, and I feel safer knowing that at least it doesn't expose Node.js to legal risk. However it doesn't address the well known unresolved ethical concerns over the sourcing of the code produced by LLM tooling.
If submitter picks (a) they assert that they wrote the code themselves and have right to submit it under project's license. If (b) the code was taken from another place with clear license terms compatible with the project's license. If (c) contribution was written by someone else who asserted (a) or (b) and is submitted without changes.
Since LLM generated output is based on public code, but lacks attribution and the license of the original it is not possible to pick (b). (a) and (c) cannot be picked based on the submitter disclaimer in the PR body.
As someone who was a part of the aforementioned security team I'm not sure I'd be interested in reviewing such volume of machine generated code, expecting trap at every corner. The implicit assumption that I observed at many OSS projects I've been involved with is that first time contributions are rarely accepted if they are too large in volume, and "core contributor" designation exists to signal "I put effort into this code, stand by it, and respect everyone's time in reviewing it". The PR in the post violates this social contract.
Taking the question of whether this would be a useful addition to Node.js core or aside, it must be noted that this 19k LoC PR was mostly generated by Claude Code and manually reviewed by the submitter which in my opinion is against the spirit of the project and directly violates the terms of Developer's Certificate of Origin set in the project's CONTRIBUTING.md
As a shameless plug I'd like to suggest the project that I have been using for my personal credentials for quite some years now: https://derivepass.com/ . The encrypted website metadata is stored only locally (with only optional remote sync, and even that has to be your own server), and the passwords are not stored at all (they are generated from your master password).
Fantastic material! That being said I'd recommend to have several alternative textbooks for every subject at hand. Whenever stuck - one should switch to another and try a different take.
There are plenty of textbooks and lecture notes available online and that article links to most of the popular choices. Make sure to choose correct order of topics to avoid getting stuck!
I think photon self-interaction might be thought of as a confirmation of photon's existence. Particle ontology is a tough question, but I don't think there is a reason to exclude photon from the list without excluding all other particles.
The light comes from bottom left, then gets into Beam Splitter (BS) and splits in two. The top-left detector has a pre-selected filter and a measurement device after a delay line. As far as I understand, this device gives binary output: either light received or not. The top-right detector captures whole image of the light ray, but does so only if the left detector has seen light.
The result is that the image from the top-right detector is highly correlated with the pre-selected filter of the top-left detector, even though they're placed in different arms of Beam Splitter! https://advances.sciencemag.org/content/advances/5/7/eaaw256...
Precisely! Because the code is made to believable the risk of accepting it without understanding full implications is very high.
> If the answer is "the same review process we've always had" then the problem isn't AI, it's whether that process is rigorous enough for the stakes involved.
True, but there is also a reputational component to how changes are reviewed (whether we like it or not). The longer the tenure and the deeper the understanding of the changed code is - the chance of careless Pull Request gets lower.