Designing for agentic AI requires attention to both the system’s behavior and the transparency of its actions. Between the black box and the data dump lies a more thoughtful approach. Victor Yocco explores how to map decision points and reveal the right moments to build trust through clarity, not noise.

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Designing for agentic AI requires knowing when to surface information, not just what to show. The Decision Node Audit is a cross-functional process where designers and engineers map every step an AI takes, identify probabilistic decision points (where the system makes a 'best guess'), and determine which moments need explicit user-facing transparency. An Impact/Risk Matrix then filters those nodes by stakes and reversibility, mapping each to the right UI pattern: passive toasts for low-impact actions, Intent Previews with explicit confirmation for high-stakes irreversible ones. Real-world examples from insurance claims processing and contract review show how replacing vague progress messages with specific, outcome-oriented status updates reduces user anxiety and builds trust. The 'Wait, Why?' usability test validates the audit by capturing moments of user confusion during live agent tasks.

Identifying Necessary Transparency Moments In Agentic AI (Part 1) — Smashing Magazine

Transparency Moments: A Case Study Example

Appendix: The Decision Node Audit Checklist