
Worked on the aau-giraf/visual-tangible-artefacts repository, delivering user-facing features to enhance image generation control and category management. Developed an AI image generation style selection interface, allowing users to choose between Piktogram, Realistisk, and Tegning styles, with prompt refactoring and robust error handling for missing formats. Enhanced category management by implementing UI and backend logic for editing, deleting, and reordering categories, including drag-and-drop functionality and automated asset cleanup. Leveraged Dart, Flutter, and API development skills to improve reliability and maintainability, focusing on reducing manual steps, preventing asset bloat, and ensuring a seamless user experience across mobile and web platforms.
November 2024 monthly summary for the aau-giraf/visual-tangible-artefacts project, focusing on delivering user-facing features that improve image generation control and category management, with reliable error handling and asset cleanup. Highlights include AI Image Generation Style Selection and Categories Management Enhancements; these changes improve business value by enabling expressive outputs, reducing manual steps, and preventing asset bloat.
November 2024 monthly summary for the aau-giraf/visual-tangible-artefacts project, focusing on delivering user-facing features that improve image generation control and category management, with reliable error handling and asset cleanup. Highlights include AI Image Generation Style Selection and Categories Management Enhancements; these changes improve business value by enabling expressive outputs, reducing manual steps, and preventing asset bloat.

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