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A Stanford AI engineer recently shared her "Personal Operations Automation System" built with Claude Code, and her approach is very worth learning from. She set up scheduled tasks to automatically pull user data from Amplitude, then cross-reference it with the GitHub code repository. The system can automatically identify which features are most urgently needed for development. Even more impressively, she integrated A/B testing, marketing copy generation, and even customer service responses, enabling the entire process to run completely autonomously. It's like one person is handling the workload of product, operations, and technical roles simultaneously. This approach is especially inspiring for entrepreneurs or independent developers aiming for efficient product iteration—using AI tools for data processing and decision support can indeed save a lot of repetitive work.