Making intelligence intuitive.

An autonomous security workflow needs to show more than an answer. Analysts need to understand what the system is investigating, the evidence behind its findings, and where their judgment is needed.

I designed across the Threat Hunter experience, connecting the entry point for a hunt with the activity and context of an investigation. The interface brings system reasoning, evidence, and possible actions into the workflow.

The screens below show the Threat Hunter interface and a hunt for suspicious login activity—two views of how analysts engage with AI-driven security work.

Security teams work across coverage, detections, and individual investigations. Each view needs a different hierarchy: an overview of gaps and activity, or the detail needed to understand a finding.

Working with product and engineering, I shaped those experiences around what analysts need to see first and what they need to investigate next.

The Detection Engineer dashboard organizes coverage and detection activity. The investigation detail brings key findings and next steps into a focused view of a single case.

An early-stage product moves quickly, which makes the connection between design decisions and implementation especially important.

I established design-system foundations across tokens, component architecture, and interaction patterns, working closely with frontend engineering to connect Figma with the code used to build the product.

The examples below show the app’s design tokens and a component linked to implementation through Code Connect. They make the relationship between design specifications and engineering visible.

Prophet AI needed its external identity and application to feel like parts of the same company. My responsibilities covered both product and brand.

I refined the visual identity across logo, color, typography, and supporting marks, connecting those foundations with the product and digital experience.

The resulting identity includes a shared palette, typographic styles, and a family of marks for the AI capabilities. The examples below show those elements together.

At Prophet AI, I’m exploring how AI-assisted development changes the path from design to working software. Faster implementation makes the quality of the inputs—tokens, component definitions, and interaction decisions—more consequential.

My focus is on keeping that connection practical: shared foundations that designers and engineers can use while the product continues to evolve.