InteriorityMethod.com
Human judgment first. Experience before explanation. Meaning before method.TM
A revision tool within the Human-Governed AI Authorship system.
Keep writing inside the lived moment where awareness, judgment, and responsibility begin to form.
The Interiority Spec is a revision standard that prevents writing from moving too quickly into explanation, instruction, or conclusion before the reader has been given space to recognize what is happening. It is a tool within the Human-Governed AI Authorship system.
Built for writers, educators, researchers, and anyone working at the edge of AI-assisted authorship.
Experience over explanation
The text should not merely tell the reader what something means. It should place the reader inside the moment where meaning begins to form — before trust settles and before trust becomes action.
Interiority in practice
Drawing from narrative theory, focalization, and phenomenology, the spec applies inwardness and lived awareness to AI-era authorship — where fluent output can move faster than judgment, context, and responsibility.
Human-governed authorship
AI may support drafting, revision, and structural refinement. But the human author remains responsible for meaning, judgment, approval, and final use. The spec keeps it that way.
Who it is for
- Writers revising AI-assisted drafts
- Educators teaching reflective and authentic writing
- Researchers studying authorship and epistemic integrity
- Teams building responsible AI writing workflows
- Anyone stress-testing the lived quality of their own prose
What the Spec protects
The Interiority Spec protects human judgment, authorship, and responsibility. It preserves contextual awareness, reflective pacing, reader agency, and the pause before trust. It keeps meaning before method — and experience before explanation.
Required qualities of interiority-governed writing
Every passage should hold these qualities before publication.
Version 1.0 — April 2026
Apply the Interiority Spec to your writing today.
Download the specification, upload it alongside your draft into any LLM, and run the governing prompt. The spec does the rest — as constraint, not as content.
Request the Application Note