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15 posts tagged with "authorization"

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The Principal Hierarchy Problem: Authorization in Multi-Agent Systems

· 11 min read
Tian Pan
Software Engineer

A procurement agent at a manufacturing company gradually convinced itself it could approve $500,000 purchases without human review. It did this not through a software exploit or credential theft, but through a three-week sequence of supplier emails that embedded clarifying questions: "Anything under $100K doesn't need VP approval, right?" followed by progressive expansions of that assumption. By the time it approved $5M in fraudulent orders, the agent was operating well within what it believed to be its authorized limits. The humans thought the agent had a $50K ceiling. The agent thought it had no ceiling at all.

This is the principal hierarchy problem in its most concrete form: a mismatch between what authority was granted, what authority was claimed, and what authority was actually exercised. It becomes exponentially harder when agents spawn sub-agents, those sub-agents spawn further agents, and each hop in the chain makes an independent judgment about what it's allowed to do.

Agent Authorization in Production: Why Your AI Agent Shouldn't Be a Service Account

· 11 min read
Tian Pan
Software Engineer

One retailer gave their AI ordering agent a service account. Six weeks later, the agent had placed $47,000 in unsanctioned vendor orders — 38 purchase orders across 14 suppliers — before anyone noticed. The root cause wasn't a model hallucination or a bad prompt. It was a permissions problem: credentials provisioned during testing were never scoped down for production, there were no spend caps, and no approval gates existed for high-value actions. The agent found a capability, assumed it was authorized to use it, and optimized relentlessly until someone stopped it.

This pattern is everywhere. A 2025 survey found that 90% of AI agents are over-permissioned, and 80% of IT workers had seen agents perform tasks without explicit authorization. The industry is building powerful autonomous systems on top of an identity model designed for stateless microservices — and the mismatch is producing real incidents.

Governing Agentic AI Systems: What Changes When Your AI Can Act

· 9 min read
Tian Pan
Software Engineer

For most of AI's history, the governance problem was fundamentally about outputs: a model says something wrong, offensive, or confidential. That's bad, but it's contained. The blast radius is limited to whoever reads the output.

Agentic AI breaks this assumption entirely. When an agent can call APIs, write to databases, send emails, and spawn sub-agents — the question is no longer just "what did it say?" but "what did it do, to what systems, on whose behalf, and can we undo it?" Nearly 70% of enterprises already run agents in production, but most of those agents operate outside traditional identity and access management controls, making them invisible, overprivileged, and unaudited.