Case Study
Turning a Static Index into a Maintainable AI-Assisted Publishing Workflow
A publishing system that keeps notes, sources, and draft output aligned without forcing a CMS.
- Client
- Independent product build
- Role
- Information architecture, frontend engineering, workflow design
- Duration
- 3 weeks
- Published
- 2026-05-01
Evidence layer · Context
Where the work started
The content surface started as a flat list of notes and references that was hard to search, update, and reuse.
Evidence layer · Problem
What needed to change
Publishing required too much manual assembly, so writing and reference material drifted apart.
Evidence layer · Constraints
What shaped the solution
- Keep the setup local-first
- Avoid a CMS before the editorial model stabilizes
- Make AI output reviewable before publishing
Process layer · Process
How I moved through it
- Mapped content primitives and writing states.
- Defined a narrow schema for topics, sources, and draft status.
- Added AI-assisted drafting with review points.
- Kept output compatible with local MDX files.
Process layer · Solution
What shipped
Built a structured index and publishing workflow with clean content boundaries, making edits predictable and reviewable.
Outcome layer · Result / Impact
What changed
Writing and reference material could move through one simple surface instead of being split across ad-hoc files.
Less time reshaping content; more time refining the actual ideas.
Outcome layer · Reflection
What I learned
- Small schemas stay editable longer than broad CMS models.
- Workflow clarity matters more than fancy automation.
Related Project
Kizuna Index
A living index that turns scattered references into a maintainable publishing surface.
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