December 2024 (kizsi2024/12I-H): Focused on data asset preparation to enable future ML-driven features. Delivered new ML data assets (binary files) in Hungarian contexts (gépi tanulás), including object recognition and airplane-vs-house examples. No application logic changes were required; assets are ready for experimentation and feature development in upcoming sprints. This groundwork supports faster ML iteration, better data governance, and longer-term business value through improved capability to test ML features with real data.

November 2024: Focused on establishing onboarding/template groundwork in kizsi2024/12I-H by introducing initial Scratch assets. Key delivery includes three binary Scratch project/data files (chatgpt.sb3, clicker.sb3, ttnet 2.sb3) added without code changes, laying a foundation for rapid prototyping and templates. No code or user-facing features were released this month. Impact: accelerates onboarding and testing cycles, enabling contributors and QA to experiment with ready-to-use assets; keeps repository lean and well-organized. Technologies/skills demonstrated include asset management of binary Scratch files, repository hygiene, and commit traceability (example commit a9e9cd86641469646dbfa1a03721faef9c41430e).