We will have to do some exploring to figure out how it best fits within
our culture of working
How about having an LLM privately generate a 30 second drama about,
most-atomically, the checkin history of a given file? It could be
user-tuned on [drama..accuracy] to get you through your day. Remember to
leave enough error to keep you on your toes.
---
--
Phobrain.com
On 2026-02-06 14:02, Stefan van der Walt via NumPy-Discussion wrote:
This is a very timely discussion for the community.
I put some of my thoughts on the topic in a recent blog post:
https://blog.scientific-python.org/scientific-python/community-considerations-around-ai/
Somewhere in between the die-hard-no-AI stance and full-on hype, I
think there are careful patterns of working with AI that can be
beneficial to our ecosystem. We will have to do some exploring to
figure out how it best fits within our culture of working, and what
good guardrails are.
Stéfan
On Fri, Feb 6, 2026, at 11:59, Charles R Harris via NumPy-Discussion
wrote:
This is a common problem, so I expect there will be a lot of work on
using AI to review AI in the next year or two. What I don't see yet
is anything that might check for license issues. However, if AI is
used to rewrite properly licensed code this is probably less of a
problem.
<snip>
Chuck
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