Coding with AI is not much different from coding without AI, just faster and with slightly less typing. But you still have to organize the work and split it into small items. If you ask a model to implement a ray tracer in SQL, it can do something one-shot, but it won't be as satisfactory as with an engineer.
The CI only runs after one of the maintainers adds a "can be tested" label.
When the label is already added, it stops when any of the infrastructure-related files are modified, like Dockerfile, CI configurations, etc. This is quite ok, but not 100% bulletproof, as you can easily do weird things by modifying the code or using a bug in the compiler. However, the CI infrastructure runs on isolated machines inside an isolated account.
Before adding the label, we have to check the diff for suspicious things. There were a few abuse attempts (all of them were from now vanished GitHub accounts).
I once tried to post an interesting visualization to r/dataisbeautiful and received hundreds of upvotes, but then it was wiped for an unknown reason. Then I contacted the mods, both on Reddit and over email, to no avail.
It was a very frustrating experience, don't recommend anyone to try.
I was trying to add Exasol to ClickBench (https://github.com/ClickHouse/ClickBench/) since 2016, but it was not possible due to the limitations and the fact that it required using a custom virtual machine image.