Microsoft · Design Director, Copilot for Business Applications

Defining how generative AI enters enterprise work.

I led the first integration of Microsoft Copilot into Business Applications—turning emerging LLM capabilities into reusable, trustworthy interaction patterns for enterprise products.

Scope

Cross-disciplinary work spanning AI UX, design systems, product, brand, and engineering.

Mandate

Establish the first Copilot experience patterns and a foundation for broader adoption.

Complexity

Probabilistic outputs, unfamiliar behaviors, trust, accessibility, and consistency across applications.

How I shaped the direction

The work required making unfamiliar technology understandable and useful—while building standards quickly enough to guide adoption.

Clarity before novelty

Focused interaction models on user intent, understandable system behavior, and useful next steps.

Patterns built to scale

Created reusable guidance for prompts, responses, states, controls, and visual treatment.

Trust made visible

Made AI behavior, uncertainty, and user control explicit within consequential enterprise workflows.

Explorations, ideation, research, strategy and branding.

We explored identity, interaction and visual direction together—giving Copilot a distinctive presence while keeping it coherent with Fluent.

Power Automate and Copilot, the early days…

Natural Language to Flow became an early proving ground. Embedded with Power Automate, we defined the components and patterns that brought Copilot into a real enterprise workflow.

Power Automate Natural Language to Flow feature

We designed the natural-language flow experience to make intent, generated output and refinement easier to understand and control.

Large Language Model features – UX Guidance

We helped establish Microsoft’s first LLM experience guidance, giving product teams a shared foundation for clear, consistent AI interactions.

Input and Output – UX Guidance

We clarified how users provide intent, interpret generated responses and remain in control as results evolve.

Visual Treatment Guidance for AI LLM Features

We created a coherent visual language that signaled AI behavior without sacrificing accessibility, comprehension or product consistency.

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