AI governance prototypes
Interaction patterns for agent oversight, review and control
As AI systems move beyond generating content and begin taking action, people need better ways to review, guide and override automated behavior.
Developed in early 2026, these prototypes explored AI governance patterns that are now becoming central to enterprise AI adoption: escalation, review, confidence, supervision and user-controlled boundaries.
Consumer account management
Tuning how much the system surfaces
How a customer might adjust automated monitoring, recommendations and alerts for a mobile phone plan.
Enterprise operations
When should the agent send?
How teams can review agent-generated communications without slowing down routine operational workflows.
Enterprise operations
What happens when AI demand exceeds capacity?
How teams can route AI work by priority, risk and value without making every decision feel like a denial.
Workplace decision support
Multiple reads of reality
How an office worker might compare competing interpretations of a meeting instead of relying on a single AI-generated summary.
This work builds on the same design concerns that shape my enterprise systems work: clarifying complex workflows, making trade-offs visible and helping people make confident decisions within constraints.
Each prototype was designed in Figma and built as a working React/Vite prototype using Cursor, GitHub and AI-assisted coding workflows.