
In November 2024, Jhan worked on the aau-giraf/visual-tangible-artefacts repository, delivering two user-facing features focused on image generation and category management. He implemented AI image generation style selection, allowing users to choose between Piktogram, Realistisk, and Tegning styles, and refactored prompt handling with robust error management for missing formats. For categories, he enhanced the UI and backend logic to support editing, deleting, and drag-and-drop reordering, with automated cleanup of associated images. Using Dart, Flutter, and API development skills, Jhan’s work improved business value by streamlining workflows, reducing manual steps, and ensuring maintainable, reliable asset management.
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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