MTS — Product Catalog

MTS internal service: a product and content catalog for 20,000+ employees. Complex data hierarchy, fragmented navigation, high expectations for search speed — and high rework volume from development after each design review.

Evolve the catalog — hierarchy, filtering, product cards, selection scenarios — to reduce cognitive load and speed up critical search paths. Simultaneously: reduce friction in the design–development handoff.

The key process change: introducing AI prototyping via Figma Make. Previously, hypotheses were tested on static mockups; an AI prototype simulated real interaction in minutes.

Concrete mechanism: for contested selection scenarios or complex filtering, an AI prototype showed behavior before a developer started the sprint. Some hypotheses were dropped at this stage before reaching code.

Result: −15% rework from development — not because the design got 'more correct,' but because more errors were caught before the sprint.

Second lever: revisiting handoff practice. Developers received mockups without states: no empty lists, no error cases, no loading states. This generated questions mid-sprint.

Introduced a standard: every component in Figma includes a state set (default / hover / disabled / error / empty). Edge cases are explicit in the file, not in the designer's head. File structure unified so developers find the right screen without questions.

Result: +25% user satisfaction by expert evaluation of prototype testing; faster access to current mockups.

−15% rework from development through AI prototyping and improved handoff. +25% user satisfaction — expert evaluation based on prototype testing.

Product: enterprise B2B catalog, internal service for 20,000+ MTS employees, 20+ person team.