AI Product Security Control Plane One-Pager

Confidential AI-Native Product Team

AI Product Security Architect / Advisor

Context

Framed AI product security as a product-control problem and translated AI risk categories into evidence, backlog, and governance language that product and engineering teams can actually use.

Problem

AI-native and B2B SaaS teams are shipping agentic features faster than product-security workflows have evolved. Without a control plane, inventory, authorization, monitoring, and evidence remain fragmented.

What I did

• - Framed AI product security as a product-control problem.
• - Converted risk categories into evidence and backlog language.
• - Designed the framework for consulting, workshops, and public reuse.
• - Kept caveats visible and avoided unsupported maturity claims.

Outcome

• - A compact methodology that supports consulting conversations, report chapters, one-pagers, and client-facing assessments.
• - Reusable control language for AI inventory, prompt injection, agent permissions, RAG authorization, AI supply chain, evidence, and governance.
• - Clear public-safe proof of product-security methodology work.

Evidence

• - Covers the full AI product security control plane.
• - Works for B2B SaaS and AI-native teams.
• - Produces reusable engineering and governance language.
• - Public-safe metric language; private implementation details are omitted.