BigPod Limited is gearing up for a significant project involving machine learning-based embedded UI automation. The preparatory phase is crucial to lay a solid foundation for the project's success. The primary goal is to refine timelines, structure comprehensive documentation, and organize resources effectively.

This phase will ensure that when the main project launches in July, it will have clear task flows, well-defined collaboration systems, and ready-to-use project assets. The project will involve reviewing existing documentation, identifying gaps, and creating a structured plan to address these. Additionally, the team will develop a resource allocation strategy to ensure all necessary tools and personnel are in place for the project's execution.

Project Scope & Goals

Project Readiness & Timeline Refinement

• Refine project milestones and deliverables
• Break down high-level phases into detailed weekly action plans
• Identify task dependencies and suggest risk mitigations

Data & Resource Planning

• Assist in scoping data requirements (screenshots, Figma API samples, labeling needs)
• Help organize synthetic dataset generation workflows
• Create an inventory of existing tools, assets, and relevant research resources

Collaboration & Documentation Systems

• Set up and structure shared documentation (Notion, GitHub Wiki, Google Drive, etc.)
• Draft templates for task tracking, meeting notes, and progress check-ins
• Develop a communications protocol for interns and contributors (Slack, email, GitHub Issues)

Technical Brief Development

• Assist with refining a technical summary of the ML and codegen pipeline
• Draft simple explainers and onboarding guides for July interns
• Compile a glossary of key terms (ML concepts, embedded UI vocabulary, etc.)

Mock Sprint Simulation (Optional if time allows)

• Coordinate a dry-run mini sprint to simulate tasks such as data preprocessing, UI component labeling, or code annotation
• Evaluate coordination challenges and record retrospective learnings

Deliverables

• A finalized, visual project timeline and task matrix
• A resource & asset tracker for datasets, tools, libraries, and references
• A well-organized project knowledge base (shared drive or Notion)
• A draft onboarding kit for July team members
• A short retrospective or improvement plan if a sprint simulation is conducted