Significant progress was made in stabilizing the data provenance tracking system by eliminating redundant type definitions between the frontend and backend. This work ensures that metadata describing AI interactions and field contexts remains consistent across the platform, reducing future maintenance overhead and potential data drift.

User experience improvements focused heavily on AI-driven content refinement. Character counters and maximum length validations (2000 characters) were introduced for user context and AI hints across various input fields, providing clearer guidance to users when interacting with generative features. Furthermore, the chat interface received enhancements, including markdown support and more robust scrolling behavior, making interactive refinement sessions cleaner and more reliable.

Several robustness and quality-of-life fixes were implemented across the AI interaction flow. This included centralizing metadata merging logic, improving error handling and type safety for AI generation endpoints, and ensuring that context passed to repeater fields was complete. These refinements contribute to a more dependable experience when leveraging AI to shape supply chain insights.