Embracing Uncertainty With AI Agents: Vulnerability Assessment Using Pydantic AI
Security Boulevard, Thursday, January 8th, 2026
We show union-type structured output allows AI agents to handle uncertain outcomes, critical for auditable and accurate vulnerability triage.
Dependency scanners are a critical part of identifying software vulnerabilities. However, they have a problem - vulnerability overload. Which 5 vulnerabilities are most important out of the 487 that the dependency scanner just flagged? Given limited resources, this is a major challenge for modern security teams.
We show in a practical example that AI Agents can analyze vulnerability context automatically and help security experts prioritize the most important. The source-code and an example vulnerable Python package are available in the realm-security/agent-union-type repo on GitHub.