Developed foundational AI scaffolding within the dreadnode/sdk repository, focusing on establishing a modular directory and file structure to support future AI and IA integrations. The work emphasized maintainability and scalability, enabling faster development of upcoming features by standardizing the project’s architecture for contributors. Leveraged Python and applied skills in SDK development and software architecture planning, with disciplined version control practices to ensure forward compatibility. No major bugs were addressed during this period, as the primary objective was to lay a robust groundwork for AI capabilities, ultimately reducing time-to-market and streamlining future enhancements within the SDK’s evolving codebase.