Design that teaches
AI how to speak.

Design for trust, not transparency. Users don’t need to see everything AI is doing. They need to see what builds confidence in what’s about to happen.

Reframed the problem from “how do we show everything” to “what builds trust,” then designed the systems that made that distinction real:

• AI Blueprint concept
• Three-tier threshold framework
• Prompting guidance that generates processing language instead of hard-coding it

In active deployment across ServiceNow Otto. Technical log messages are gone from the surfaces where it shipped. Research participants now describe the language as clear, human, and trustworthy. The spec has reached 900+ recipients across the org. Step grouping model in development.

Organizations default to showing everything. That creates overwhelm, not trust. The harder design problem is knowing what to hide and what to surface.

Ambiguous requests are the default condition. 90% of user queries are medium to high ambiguity. A well-designed system doesn’t overwhelm users with every possible answer. It asks one focused question.

Held conviction on this problem for three years, built the research to prove it, and shaped how the organization thinks about clarification. The patterns I created improve intent understanding by being honest and human: communicating what the system knew and asking an intelligent, well-designed clarification.

V1 shipped late 2025. Design is now a named partner in architectural decisions from day one. V2.0 in active development with design defining the experience from the ground up.

I identified this as critical three years before the organization was ready to hear it. When the feature was removed, customers demanded it back within weeks. That forced the org to reckon with what they’d dismissed.

Conversation design is a discipline. It requires linguistic patterns, behavioral principles about when to ask versus act, and design thinking. It’s not decoration on top of a system. It shapes how the system behaves.

Built the entire conversation design discipline from the ground up:

• Principles & behavioral standards
• Training curriculum
• Reusable patterns
• Evaluation frameworks & golden datasets
• Engineering-design collaboration tools

600+ designers directly trained, with enablement materials and recordings reaching close to 2,000 people across design, PM, and engineering. Teams use the patterns for every conversational AI decision. The training curriculum is being adopted across ServiceNow as standard designer onboarding.

The LLM wave hit and 1,000 designers suddenly needed to build conversational AI. Most had no training, no framework, no shared understanding of what good conversation actually looked like.