AI Worflows
AI Worflows
Using AI in design workflows is now part of reality. Using AI to brainstorm and prototype is not only possible, but increasingly expected of Product Designers today. There are two possible approaches: 1- design and prototype directly with AI, or 2- Use Figma MCP to maintain manual control over the design.
This page is still under construction, but feel free to check out what's already here:
MarcaFlow
MarcaFlow is a live prototype for managing trademarks, centralizing leads, clients, documents, and process stages in one place. It includes a Kanban pipeline, Leads screen with table or Kanban views, filters, checklists, Google Drive links, reports, performance indicators, and record movement between process stages.
How was it created?
MarcaFlow was created 100% through an AI-assisted coding process. For this specific project I used Manus. I described the desired workflows—such as the Pipeline, Leads, Non-Protocolled Clients, Overview, and Reports screens—and the AI translated those ideas into interface components, data structures, navigation, filters, checklists, Kanban interactions, local storage behavior, and responsive layouts. Features were built gradually, tested in the browser, adjusted based on visual feedback, and refined through short development cycles.
How I used Github for this project:
GitHub served as the project’s central code repository and collaboration layer. Through the GitHub connector, the AI could inspect the existing files, understand the project structure, update multiple pages consistently, create assets such as the MarcaFlow SVG logo, commit changes, push them to the repository, and verify the published files. I remained responsible for defining priorities and reviewing the results, while the AI handled implementation, testing, debugging, and synchronization across the application. This combination of user direction, AI-generated code, browser validation, and GitHub version control made it possible to evolve MarcaFlow quickly as a functional prototype.