The tool sequence designers actually used, by discipline. See how the stack shifts as AI takes more of the execution.
Brief goes to agents. Synthetic users test early. A director edits, kills, redirects. Design engineer ships. The file is no longer the artifact — the running product is.
58 synthesized monthsin the data layer. Stage breakdowns (Starter / Scaler / Titan) are available for 2026 only — earlier months show under the All segment but won’t appear under stage filters until the design-context pipeline runs further back.
Prompt-to-prototype is the default first step. Designers direct agents to build, then edit for taste, friction, and intent. Synthetic users test before humans.
Product designers start in Figma to map flows and set the interaction intent, then hand the component spec to v0 to generate the React scaffold. Cursor with MCP pulls the live design tokens so AI-generated code doesn't drift from the system. The back half of the week is QA — running Playwright tests on shipped interactions and writing the rationale that becomes the next prompt rule.
Product designers open a sprint by pressure-testing the problem in ChatGPT or Claude, then move into Figma for structure. Execution work — initial layouts, component variants, first-pass screens — increasingly goes through v0 or Cursor, with the designer editing outputs rather than building from scratch. The hardest part of the week isn't making; it's deciding which AI-generated pattern actually solves the problem and which just looks like it does.
Product designers started flows with Google Stitch or v0 — generating five-screen canvases from a single prompt to pressure-test navigation logic before touching Figma. From there, they refined interaction details inside Figma, used AI plugins to generate copy and component variants, then pushed to Maze or Lyssna for rapid usability validation. The blank-canvas starting point is effectively dead; the job is now editing and directing generated flows rather than drawing them.