What I would argue is knowing what topic to write is more important, and I am confident if you throw this particular question to AI, the response would be much worse.
Author here. I did use AI to assist writing. The way I do it is I feed all my past writings (around 200+ posts) to the AI and let it record my style.
I research the topic, lay the outlines and let AI write it. Then I further refine section by section with a combination of AI and manual editing).
What you have pointed out is valid and it helps me to improve the process. And I have edited the post based on your suggestion.
As a non-native speaker and engineer with 15+ database development experience, I think I will continue to use AI to assist writing (I rarely use AI if I write in my native language). This post still takes me almost an afternoon to finish, but without AI, it will take me much more time.
I built this last summer and thought it was fairly complete. And it turns out I was naive. 6 months later, I have resolved ~100 issues reported by the users.
This post addresses the data migration specifics well. Besides, there is the part about scaling the organization to deploy database migrations. We've built a project https://github.com/bytebase/bytebase to address this.
We have been building https://github.com/bytebase/bytebase for 3+ years. You can think it of as GitHub/GitLab for SQL changes, with integrated GitOps, code review and deployment.
You can further check out this tutorial to get a feel of our GitOps solution
We have been working on bytebase (https://github.com/bytebase/bytebase) for 3+ years to address this. With a change review workflow, environment propagations, and try not to disturb the dev flow if possible.