alt Hacker NewsThis sounds like it is more aligned with what I have created which is "We need to capture your conversations with AI". If you look at
https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r...
you can see that every file has a code block header with a UUID and the AI that was attributed to it. With the UUID, I can tell exactly how the code came about.
What they are working on will be more useful for AI code provenance. It is only a matter of time before you are expected to show your chats with AI as part of the code review and for performance reviews.
So I don't see human collaboration being the main use case. I see tracking, studying and improving the Human-AI relationship...and seeing if somebody should be promoted or not.
An interesting take I've heard is, we will have a token/impact stat where if you spent a shitload of tokens to produce the same impact as somebody else who spent a lot less, you will be the prime candidate for layoffs and/or less pay. This is why I think AI code provenance will become a serious thing in the future.
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FYI your link 404s.
Seems like you copied the ellipsified version, so what we get is https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r
Audit purposes for sure. How was this code/concept generated, what were the prompts/requirements, what thinking did the model complete, can this be replicated or repeated, etc.
A vendor conference I was at a few weeks ago focused heavily on this, for most of their Agentic workflow items. How can you show the AIs work, prove what it did was within guidelines, then audit the process and result.
Like, if your system has an AI backed federated search for documents and you ask it a question about those documents, you need an audit trail of the ask, what documents were referenced, and what was returned to the user.
Then if wrong information was supplied that can be pinned down and explained in case of lawsuit or other need.