David Wolf · Project Use Case
AI SECURITY · PRODUCT SECURITY · AISECURITY.LLC
aisecurity.llc
MYTHOS: The AI Security Narrative
A book about the stories that shape how people think, build, and govern AI security.
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...
Client
aisecurity.llc
Engagement Type
product
Period
2026
Role
Author, narrative architect, editor
Focus Areas
AI security narrative, Myth-breaking frameworks, Governance evidence, Organizational design
The Research Narrative
Strategic Problem
Leaders need a way to explain accelerated weaponization and governance pressure without overclaiming or turning public signals into breach claims.
What David Did
David structured the book around inventory, continuous threat modeling, authority control, workflow integrity, retrieval authorization, supply-chain discipline, evidence, and governance...
What Became Clearer
The result is a book-length artifact that gives the portfolio a clear point of view on AI product security while keeping the public claim boundary explicit and conservative.
Consulting Proof
This is evidence of turning messy security telemetry into explainable dashboards, alert-quality improvements, and executive-ready operating views.
The Context
MYTHOS is the executive handbook for the post-Mythos operating model. It translates public capability signals into a practical product-security narrative.
The Challenge
Leaders need a way to explain accelerated weaponization and governance pressure without overclaiming or turning public signals into breach claims.
What I Did
David structured the book around inventory, continuous threat modeling, authority control, workflow integrity, retrieval authorization, supply-chain discipline, evidence, and governance velocity.
- •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
The Outcome
The result is a book-length artifact that gives the portfolio a clear point of view on AI product security while keeping the public claim boundary explicit and conservative.
Research Outcomes
Signal Quality
Improved the trustworthiness of operational security signals
Operational Clarity
Translated complex security data into clearer operating views
Executive Visibility
Built dashboards leaders could trust for decision-making
Operational Impact
Turned raw telemetry into actionable security intelligence
Capabilities Demonstrated
Executive Reporting
Security data translated for leadership
Public-Safe Evidence
Shareable insights without sensitive data
Security Analytics
Signal investigation and event analysis
IAM / Access Control
Identity telemetry and access insights
SIEM Alert Debugging
Noise reduction and signal validation
Dashboard Development
Operational and executive views
Telemetry Normalization
Consistent and trusted data
Operational Reporting
Actionable views for security operations
Key Deliverables
- •Book manuscript
- •Claim ledger
- •Source ledger
- •Chapter architecture
- •Appendix templates
- •90-day playbook
Tools & Technologies
Consulting Translation
The reusable pattern is not Disney-specific: normalize fragmented security telemetry, debug low-signal alert behavior, build trusted operating views, and give leadership evidence they can act on without exposing sensitive systems.