The core concern here is trust and verification, not really whether a human or LLM typed the characters. Hand-written code can have bugs too. The difference is that hand-written Node.js core has years of battle-testing behind it.
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.
I think the better question is: what verification pipeline do you put around any contribution, regardless of origin? 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.
indutny•1h ago
> 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.
AgentNode•56m ago
Good point on the reputational component. Tenure builds implicit trust because it signals that someone understands the second-order effects of a change, not just the immediate behavior. An LLM doesn't accumulate that kind of context across contributions. So even if the code itself is correct, the review dynamic shifts because reviewers can't rely on the same assumptions about intent and depth of understanding. That's a real cost that a better test suite alone doesn't solve.
AgentNode•1h ago
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.
I think the better question is: what verification pipeline do you put around any contribution, regardless of origin? 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.
indutny•1h ago
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.
AgentNode•56m ago