I'm @nyaomaru, a frontend engineer currently building an AI-assisted CHANGELOG generator and experimenting with Jev. 😸
Getting the WHAT is relatively easy. Getting the WHY is much harder. And I didn't want AI to simply invent a nice-looking reason.
But then the model may summarize, paraphrase, or infer a reason that was never explicitly written.
It also removes template noise such as checkboxes, placeholders, and irrelevant fields.
While working on WHY extraction, I have also been redesigning the changelog-bot pipeline for v1.
One important change here is that the WHY engine does not need to control the final Markdown.
Today, some of the pipeline still works by finding targets from generated Markdown and inserting WHY text afterward.
Phases 1–4 of this migration are already implemented, and the structured rendering and enrichment boundary is part of the next phase.
While I was working on this experiment, @johnnylemonny joined the project as a contributor. 🎉
And thanks to John's contributions, we now have a much better way to test whether that approach actually works.