A data scientist demonstrates how AI can now handle the entire data science workflow, moving far beyond simple code generation. Using Codex and MCP servers, they processed 1.85GB of Apple Health data from raw XML to polished insights report in just 30 minutes.

Traditional workflows that once took a full day now compress into minutes as AI locates files in Google Drive, references old GitHub code, parses datasets, uploads to BigQuery, and generates SQL queries. The key innovation isn't just speed—it's AI's ability to orchestrate multiple tools and data sources autonomously while the human focuses on direction and review.

The experiment revealed that context matters more than ever. By connecting MCP servers for Google Drive, GitHub, and BigQuery, the AI could search travel documents, find historical code, and understand the full project context. This represents a fundamental shift: data scientists must now think about AI as a workflow partner rather than just a coding assistant, with iteration and better questions becoming the path to deeper insights.