video1.0<iframe src="https://www.loom.com/embed/05b3960518ab4bc0ae42a1ede4591d17" frameborder="0" width="1156" height="867" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8671156Loomhttps://www.loom.com8671156https://cdn.loom.com/sessions/thumbnails/05b3960518ab4bc0ae42a1ede4591d17-1d485e7edff72cc9.gif210.4327This demo shows Sleepmaxxing running on 8 weeks of real health data, compiling from scratch and generating a weekly recovery prediction with explanations. The model learns incrementally: predictions are evaluated week by week, and reliability metrics (like directional accuracy) only appear after enough evaluated predictions. After ~5 evaluated weeks, the system begins reporting an accuracy score, which continues to improve as more data is logged. All learning is local-first — no cloud, no subscriptions, no external data.