Vidhya Shankar developed foundational data abstractions for the meta-pytorch/forge repository, focusing on structuring conversational AI workflows. She designed and implemented core data models for prompts, completions, and episodes using Python and object-oriented programming principles, establishing a consistent and scalable data layer. Her work addressed the need for standardized handling of conversational data and model outputs, enabling future integration of natural language processing features. By prioritizing data modeling best practices, she improved the testability and extensibility of the dialogue system. The depth of her contribution lies in laying a robust groundwork for future development, rather than delivering user-facing features immediately.