That would cost a seat, I'm guessing.

Giving it its own id doesn't store all the useful metadata this tool preserves, like the model and prompt that generated the code

I guess because 99% of generated code will likely need significant edits, so you'd never want to commit direct "AI contributions" - you don't commit every time you take something from StackOverflow, likewise I wonder if people might start adding credit comments to LLMs?

Many posts get resubmitted if someone finds them interesting and, if it's been a few days, they generally get "second-chance" treatment. That means they'll be able to make it to the front-page based on upvotes, if they didn't make it the first time.

> Wouldn't the thing to do be to give AI its own account id / email so we can use standard git blame tools?

That’s a reasonable idea and something I considered. The issue is that AI assistance is often inline and mixed with human edits within a single commit (tab completion, partial rewrites, refactors). Treating AI as a separate Git author would require artificial commit boundaries or constant context switching. That quickly becomes tedious and produces noisy or misleading history, especially once commits are squashed.

> Why do we need a plugin or new tools to accomplish this?

There’s currently no friction‑less way to attribute AI‑assisted code, especially for non–turn‑based workflows like Copilot or Cursor completions. In those cases, human and machine edits are interleaved at the line level and collapse into a single author at commit time. Existing Git and blame tooling can’t express that distinction. This is an experiment to complement—not replace—existing contributor workflows.

PS: I asked for a resubmission and was encouraged to try again :)

I think the special feature is that it tracks on a per line basis in a blended commit what AI is doing vs. whole commits. not sure the utility of it.

Because AI is really good at generating code that looks good on its own, on both first and second glance. It's only when you notice the cumulative effects of layers if such PRs that the cracks really show.

Humans are pretty terrible at reliable high quality choice review. The only thing worse is all the other things we've tried.

Because they can produce magnitude more code than you can review. And personally I don't want to review _any_ submitted AI code if I don't have a guarantee that the person who prompted it has reviewed it before.

It's just disrespectful. Why would anyone want to review the output of an LLM without any more context? If you really want to help, submit the prompt, the llm thinking tokens along with the final code. There are only nefarious reasons not to.

I think this is what aider/cecli does