feat: Add initial project development phases, high-level targets, and vision documentation.

PROJECT_MGMT/high_level_targets.md

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+# High-Level Targets: zhealth
+
+## Vision
+To provide a seamless, AI-powered health management platform that empowers users to track, analyze, and optimize their biomarkers for better longevity and wellness.
+
+## Phase 1: MVP (Minimum Viable Product)
+- [ ] **Unified Dashboard**: A clean UI to visualize biomarker trends (e.g., Blood Glucose, LDL, HDL, Vitamin D).
+- [ ] **Rust Backend**: Secure and performant API to handle user data and biomarker logs.
+- [ ] **AI Insights Prototype**: Initial integration with LLM to provide basic interpretations of biomarker results based on standard clinical ranges.
+- [ ] **Data Entry**: Easy manual entry form for blood test results.
+
+## Phase 2: Advanced AI & Integration
+- [ ] **Predictive Trends**: AI models to predict future biomarker levels based on lifestyle data.
+- [ ] **Lab Report OCR**: Automated data entry by uploading PDFs/images of lab reports.
+- [ ] **Wearable Sync**: Integration with Apple Health, Google Fit, or Oura for holistic health context.
+
+## Phase 3: Personalized Recommendations
+- [ ] **Lifestyle Playbooks**: AI-generated nutrition and supplement plans.
+- [ ] **Community & Sharing**: Option to securely share data with health professionals or family.
+
+---
+**Tech Stack Targets:**
+- Frontend: Vite + React + TypeScript
+- Backend: Rust (Axum / Tokio / SeaORM)
+- Database: SQLite3 (WAL mode)
+- AI: Gemini / OpenAI / Anthropic API (for interpretation)

PROJECT_MGMT/phased_approach.md

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+# Project Development in Phases
+
+## Phase 1: Foundation & Data Modeling
+
+- Database Models with **SeaORM** (Rust).
+- **Auth and RBAC Schema Modeling** (Roles, Permissions, User relationships).
+- **Biomarker Knowledge Base** (types, units, clinical ranges, interpretation rules).
+- Basic CRUD operations for Biomarkers.
+
+## Phase 2: API & Core Auth
+
+- API Development with Axum.
+- Implementation of Auth logic (JWT, Middleware, RBAC enforcement).
+- Frontend Development (Vite + React + TS) - Initial Layout.
+
+## Phase 3: Integration
+
+- Integration of API with Frontend.
+- Manual Data Entry forms.
+- Unified Dashboard visualization.
+
+## Phase 4: AI & MCP
+
+- MCP (Model Context Protocol) Development for AI interaction.
+- Inference endpoints (Gemini/OpenAI).
+- Basic AI biomarker interpretation.
+
+## Phase 5: Advanced Features
+
+- Analytics and Visualization.
+- Lab Report OCR.
+- Wearable Sync.