Maitan

I believe in co-ownership: design only creates value once it's live and working flawlessly. Collaboration starts at discovery, not at handoff. I involve developers from the conceptual phase to align on technical feasibility, ensure structured handoffs backed by supporting documentation, and stay actively involved in visual and behavioral QA.

I see the Design System as an internal product that ensures scale and consistency. I contribute actively by documenting accessible components, defining interaction patterns, and aligning tokens with the engineering team to speed up development.

I use AI as a productivity lever across the entire product cycle — synthesizing research data, accelerating prototypes, and bridging interface and code. The Plific case study shows in practice how this integration optimized delivery time and project precision.

Rollout is the start of the learning cycle, not the end of the project. The metrics set at kickoff serve as a baseline, but impact analysis only gains real depth in production, by crossing quantitative data with qualitative context. In practice, I combine tracking usage metrics and reviewing session recordings at friction points with an active listening routine alongside Customer Success and Sales. To scale that qualitative capture, I use AI to mine transcripts from online client meetings, identifying spontaneous mentions and sentiment about the new feature. Triangulating this data produces concrete insights that feed and reprioritize the iteration backlog.