I shipped 30 AI projects in 30 days – here's the data (franciscoperez.surge.sh)

A former Meta engineer completed an ambitious challenge by shipping 30 production-ready AI projects in just 30 days, showcasing his ability to adapt to the evolving AI landscape amid a challenging job market. Each project took approximately 9 hours a day to complete, totaling around 270 hours, and included a robust structure of tests, documentation, and a deliberate focus on key areas such as Retrieval-Augmented Generation (RAG), security, and observability. The engineer aimed to prove his capacity to build real systems, moving beyond simple tutorials to production-ready applications that can meet industry standards. This initiative is significant for the AI/ML community as it highlights the practical skills increasingly demanded by the industry, particularly in areas like LLM experience and prompt engineering. By sharing his daily metrics and insights, the engineer offers a blueprint for technical rigor in AI development, emphasizing the importance of strict deadlines, project scoping, and integrated testing. Looking ahead, he aims to deepen his expertise in LLM security, production-scalable RAG, and agent infrastructure, while also seeking roles that blend his engineering leadership and hands-on building capabilities.