AI recommendations people can act on

01

The challenge

Turbonomic and Instana help operations teams keep applications healthy. Turbonomic recommends and automates decisions about application resources, and Instana watches how applications perform. Both are powered by AI, and both are only as useful as people’s willingness to act on what they suggest.

My job was to turn those technical capabilities into workflows and interactions that people could follow, understand and trust.

02

My role

I led a team of UX designers, coordinating their work and owning the quality of what we delivered. I partnered closely with product managers, engineers and business stakeholders to understand user and business needs.

I made strategic design decisions on core and new features, and supported design quality, governance and accessibility across the team.

03

How we worked

1. 01Functional definition
2. 02User flows
3. 03Interaction models
4. 04Interface design
5. 05Carbon alignment

We worked across the whole development life cycle: discovery, interaction design, prototyping, reviews and iterative refinement. I turned research into clear insights and recommendations, and worked across disciplines to surface usability issues early and align design with what product and engineering could deliver.

04

One family, one system

Turbonomic and Instana sit inside a much larger IBM product family. I supported adoption of the IBM Carbon Design System across our product surfaces, so new features looked and behaved like the rest of the family, and users didn’t have to relearn the basics on every screen.

05

What I took away

Over nearly four years, I helped the team ship new AI-driven features inside one consistent design system, and earned IBM’s Enterprise Design Thinking and Patterns credentials along the way.

• IBM Enterprise Design Thinking Practitioner, Dec 2021
• Enterprise Design Thinking Co-Creator, Jun 2022
• IBM Patterns Graduate, Jun 2022