An AI agent just provisioned $50,000 in cloud infrastructure using valid OAuth tokens and authorized API scopes.

You gave it billing:read to analyze costs. It called the pricing API (authorized), retrieved payment methods for cost calculations (authorized), identified optimization opportunities (authorized), then executed the changes with its compute:write scope (also authorized). Each API call passed. The token was valid. The scopes checked out.

But you authorized it to analyze, not provision. The authorization system never asked: should these specific API calls happen together? Should this agent execute changes, or just recommend them?

This is the authorization gap. Traditional OAuth validates requests, but agents create sequences. They chain legitimate calls into outcomes you never intended. Each step might be authorized, but the combination exceeds what you meant to allow.

Single authentication at the gateway isn't enough anymore.

This session presents a four-layer continuous authorization framework for autonomous agents. You'll learn how to track both human intent and agent actions separately, filter tools based on runtime context, bind permissions to specific operations with transaction tokens, and enforce controls the agent can't circumvent.

If you're building or securing AI agents, this framework shows you how to authorize behavior, not just access.

Note: This session does not promote any product or service. It’s focused entirely on industry challenges and practical best practices.