Case Study / 1 min read
Semiconductor Editorial Research Prototype
A self-directed prototype for separating topic selection, source evidence, AI-assisted drafting, and human publication review.
My Role
Independent practice copy authored for this site using public professional facts and self-owned materials.
Context
Technical publishing with AI can produce fluent drafts while weakening source discipline, mixing research runs, or overstating the operator's software role.
My contribution
- Defined the publication audience and editorial objectives
- Designed source tiers, research questions, evidence fields, and acceptance criteria
- Directed AI coding tools through written requirements and iterative review
- Tested workflow outputs and identified handoff failures
- Performed final editorial review before publication
Process
Each topic enters a separate research and production run. Discovery material is not treated as publication evidence by default. Claims are connected to source URLs and excerpts before drafting, and human review remains the publication boundary.
Honest implementation boundary
This is an AI-assisted editorial prototype and an operating method. It is not presented as independently engineered enterprise software, a client deployment, or a production security platform.
Demonstrated outcome
The prototype supports repeatable self-publishing with explicit source, rights, role, and review boundaries. No client KPI or commercial performance claim is made.