MYTHOS: The AI Security Narrative One-Pager

aisecurity.llc

Author, narrative architect, editor

Context

MYTHOS examines the dominant narratives — the myths, metaphors, and mental models — that shape how security teams, executives, and builders approach AI risk. It is both a critical framework and a practitioner's guide for rewriting dangerous stories.

Problem

The AI security conversation is dominated by unexamined myths: AI is magic, AI is a tool, AI will solve security, AI is too complex to govern. These narratives drive decisions, budgets, and organizational structures in ways that increase rather than reduce risk.

What I did

• - Identify the dominant narratives that distort AI security thinking in organizations.
• - Trace how each myth originates, spreads, and shapes real decisions and controls.
• - Offer alternative framings grounded in product security, evidence, and engineering reality.
• - Structure the book for both executive and practitioner audiences with layered depth.

Outcome

• - A reusable vocabulary for challenging AI security myths in consulting, hiring, and governance contexts.
• - A book-length artifact that anchors aisecurity.llc's intellectual positioning in the AI security market.
• - A foundation for workshops, assessments, and narrative-first consulting engagements.

Evidence

• - 15-chapter executive handbook with appendix templates and source ledger.
• - Built around the post-Mythos product-security operating model.
• - Designed as a companion to the Handbook and Field Guide.