We get the typical "slop can be good sometimes" for a vaguely defined set of use cases...

"AI tools can sometimes be beneficial, particularly when it comes to finding patterns among a large data set (entire code base), performing tedious repetitive changes or large refactoring/re-organization."

and also this gem...

"AI tools are treated the same as traditional tooling like sed, awk or coccinelle."

which is a reversal of how they treated LLMs in their previous "No Large Language Models (LLMs) or similar AI tools" statement:

"All contributions to this project are expected to be done by human
beings or through standard predictable tooling
[...]
LLMs and similar predictive tools have the annoying tendency of
producing large amount of low quality code with subtle issues which end
up taking the maintainers more time to debug than it would have taken to"

Maybe they conflated "predictable tooling" with "predictive tools" (already a slightly sinister framing).

And I guess subtle code issues are no longer a concern, since they're only suggesting that LLMs are useful for "boring grunt work" like (checks notes) "large refactoring" 🤦‍♀️ well, I'm sure the subtle issues will never slip past review.

2/🤡