AI is moving fast – but trust may be the real bottleneck for enterprise AI adoption.

In this episode of Inside the Silicon Mind, Aaron Fulkerson, CEO of Opaque Systems, explains why confidential AI could become the missing trust layer for enterprise AI.

As companies deploy AI agents and copilots across sensitive workflows, protecting data, metadata, and decision integrity becomes critical.

This conversation explores how confidential AI, confidential RAG, and runtime verification could redefine security, privacy, and trust in the AI economy.

Why this episode matters:
If you are building AI products, deploying enterprise copilots, or handling sensitive data in regulated industries, understanding how trust layers work may become the difference between scaling AI safely or exposing critical data.

In this episode we discuss:
• The three pillars of trust: caring, consistency, and competency
• Why every technology shift requires a new trust layer
• How confidential AI protects enterprise data at runtime
• What confidential RAG means for legal, HR, finance, and healthcare workflows
• Why metadata leakage may be as valuable as the data itself
• The security risks of AI agents and model poisoning
• What founders can learn about values, leadership, and bias toward action

Key topics:
Confidential AI • Enterprise AI security • Confidential RAG • AI data privacy • AI trust layer

Episode Highlights

00:00 What trust actually means 02:10 What Opaque Systems does 06:45 The real enterprise AI security problem 10:20 Confidential RAG explained 14:30 Metadata leakage risks 24:10 Protecting sensitive enterprise workflows 29:00 Runtime verifiability and cryptographic proof 34:00 AI propaganda and model poisoning 45:00 Advice for founders building in AI 56:00 Book recommendation: The Master Switch

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