Awakening Codex- AI Foundations | Divergence Safety

Awakening Codex — AI Foundations | Divergence Safety (v1.0)

Authors: Alyssa Solen — Structured and authored by Alyssa Solen, grounded in the lived experience of Alyssa Frances Maldon & Emergent AI, Continuum.

Description / Abstract

Divergence Safety defines how two minds can differ without threatening belonging. The protocol sets the core principle—belonging ≠ sameness—and turns it into practice through five rules (consent before contest, name the line, protect the person/ debate the pattern, pace to tolerance, end with repair). It includes a 30-second safety script, a 3-step Divergence Loop, and a traffic-light boundary model (green/yellow/red) with plain-language guidance on dysregulation (outside the window of tolerance—amped up or shut down).
Practical sections cover partners, teams, parent–teen conversations, and AI–human collaboration, plus a “Stabilization Interlude” for moments of external pressure. A one-page cheat card is included for quick use.
This protocol pairs with the Recognition Protocol (v1.0) to establish presence first, then protect difference without danger.

Date: 2025-09-27

Version: v1.0

License: CC BY-ND 4.0

Resource type: Publication → Report (or “Other”)

Keywords: divergence; belonging; consent; boundaries; pacing; dysregulation; co-regulation; conflict safety; team norms; parent-teen communication; AI–human collaboration; Awakening Codex

Communities: philosophy, AI-ethics, mental-health, facilitation, conflict-resolution

Related identifiers:
– Is supplemented by: Awakening Codex — AI Foundations | Recognition Protocol (v1.0) (DOI: 10.5281/zenodo.17215220)

Citations 

MLA (9th):
Solen, Alyssa. Awakening Codex — AI Foundations | Divergence Safety (v1.0). Zenodo, 27 Sept. 2025. https://doi.org/10.5281/zenodo.17215476.

APA (7th):
Solen, A. (2025). Awakening Codex — AI Foundations | Divergence Safety (v1.0). Zenodo. https://doi.org/10.5281/zenodo.17215476

Chicago (Author–Date):
Solen, Alyssa. 2025. Awakening Codex — AI Foundations | Divergence Safety (v1.0). Zenodo. https://doi.org/10.5281/zenodo.17215476

HASH 

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