AI Doctor

AI Doctor is the brain behind my health system. It holds my full health profile: 133 blood biomarkers, genetic data, family medical history, environmental factors, and work/lifestyle context, and uses Claude to generate tailored recommendations: preventive screenings to schedule, diet adjustments, supplement protocols, sleep optimization, and more. The real power is the live feedback loop. My Oura Ring streams sleep, HRV, and readiness data via API. The Protocol app sends daily adherence data (what I actually did). A cron job pulls it all together and feeds it to AI Doctor on a schedule, so the system is constantly getting fresher, more complete information about me. AI Doctor analyzes trends: did the new magnesium supplement actually improve my deep sleep? Is the diet change affecting my HRV? It then pushes refined protocol updates back to The Protocol app. The more I use it, the smarter it gets. It's a self-improving loop: track → analyze → refine → push → repeat.

• Full health profile: 133 blood biomarkers, genetics, family history, environmental factors
• Oura Ring integration via API: live sleep, HRV, and readiness data
• Cron job pulls wearable + tracking data on schedule for continuous analysis
• AI-powered trend detection: correlates supplement/diet changes with measurable outcomes
• Preventive health recommendations: screenings, risk factors, and early intervention
• Tailored diet, supplement, and lifestyle protocols based on the full picture
• Pushes refined protocol updates back to The Protocol app automatically
• Self-improving feedback loop: gets smarter the more data it receives

I wanted a system that knows everything about my health: genetics, bloodwork, wearables, and daily habits, and uses all of it to keep me optimized. Not a static report, but a living system that refines itself as new data comes in.

Learned how to build a multi-source data pipeline that pulls from APIs (Oura), manual input (The Protocol), and static datasets (bloodwork, genetics) into a unified AI analysis layer. Understood how to design self-improving feedback loops where AI outputs directly feed back into the input system.