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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.

Cliente
Independent product build
Ruolo
Information architecture, frontend engineering, workflow design
Durata
3 weeks
Pubblicato
2026-05-01
Next.js
TypeScript
MDX
OpenAI API
Vercel

Contesto

Da dove e partito il lavoro

The content surface started as a flat list of notes and references that was hard to search, update, and reuse.

Problema

Cosa doveva cambiare

Publishing required too much manual assembly, so writing and reference material drifted apart.

Vincoli

Cosa ha formato la soluzione

  • Keep the setup local-first
  • Avoid a CMS before the editorial model stabilizes
  • Make AI output reviewable before publishing

Processo

Come l'ho attraversato

  1. Mapped content primitives and writing states.
  2. Defined a narrow schema for topics, sources, and draft status.
  3. Added AI-assisted drafting with review points.
  4. Kept output compatible with local MDX files.

Soluzione

Cosa e stato pubblicato

Built a structured index and publishing workflow with clean content boundaries, making edits predictable and reviewable.

Risultato / Impatto

Cosa e cambiato

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.

Riflessione

Cosa ho imparato

  • Small schemas stay editable longer than broad CMS models.
  • Workflow clarity matters more than fancy automation.

Progetto correlato

Kizuna Index

A living index that turns scattered references into a maintainable publishing surface.

Vedi progetto

Servizi coinvolti

Content Systems & Local Editors
Personal / Brand Websites
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