Earlier quoted context omitted.
This is taking what I said further than intended. I'm not saying the standard review process should catch the AI generated mistakes. I'm saying this work is at the level of someone who can and will make plenty of stupid mistakes. It therefore needs to be thoroughly reviewed by the person using before it is even up to the standard of a typical employee's work that the normal review process generally assumes.
Yep, in the case of open source contributions as an example, the bottleneck isn't contributors producing and proposing patches, it's a maintainer deciding if the proposal has merit, whipping (or asking contributors to whip) patches into shape, making sure it integrates, etc. If contributors use generative AI to increase the load on the bottleneck it is likely to cause a negative net effect.
Re: ChatGPT agent: bridging research and action
#291This very much. Most of the time, it's not a code issue, it's a communication issue. Patches are generally small, it's the whole communication around it until both parties have a common understanding that takes so much time. If the contributor comes with no understanding of his patch, that breaks the whole premise of the conversation.