I've been building an AI-assisted editorial pipeline for my technical writing. Notion cards become markdown drafts in the repo, pass through review, then sync to dev.to.
The motivation was simple: I already had a review loop I trusted for code. Open a PR, run Cursor's Bugbot against a review guide, fix what mattered, merge. I wanted the same rhythm for writing: draft, critique, revise, publish. So I built my own AI review skill called editor-critique.
I had also started adding HTML comments inside drafts, much like code comments. They captured the editorial intent behind a section, including why it opened where it did and why evidence sat where it did, without becoming part of the published post.
That made the review step look straightforward. Give the AI a rubric, score the draft, return prioritized feedback.
If the rubric was good, I assumed the critique would be good.
