# 🚀 Getting Started - Day-by-Day Implementation Guide

This guide provides a practical, day-by-day approach to implementing the JobForge MVP. Follow this roadmap to build the system incrementally.

---

## 📅 Week 1: Foundation & Environment

### Day 1: Environment Setup ✅
- [x] Set up Docker development environment
- [x] Configure database with PostgreSQL + pgvector
- [x] Create project structure and documentation
- [x] Validate all services are running

**Validation Steps:**
```bash
docker-compose ps  # All services should be "Up"
curl http://localhost:8000/health  # Should return when backend is ready
```

### Day 2: Backend Foundation
**Goal**: Create FastAPI application structure and health check endpoint

**Tasks:**
1. Create `src/backend/main.py` with FastAPI app
2. Add health check endpoint (`/health`)
3. Set up database connection with AsyncPG
4. Add basic CORS and middleware configuration

**Validation:**
- `curl http://localhost:8000/health` returns `{"status": "healthy"}`
- `curl http://localhost:8000/docs` shows Swagger UI

### Day 3: Database Models & Authentication
**Goal**: Implement user model and JWT authentication

**Tasks:**
1. Create `src/backend/models/` with Pydantic models
2. Create `src/backend/services/auth_service.py`
3. Implement user registration and login endpoints
4. Add JWT token generation and validation

**Endpoints to implement:**
- `POST /api/v1/auth/register`
- `POST /api/v1/auth/login`
- `GET /api/v1/auth/me`

**Validation:**
```bash
# Register user
curl -X POST http://localhost:8000/api/v1/auth/register \
  -H "Content-Type: application/json" \
  -d '{"email":"test@example.com","password":"testpass123","full_name":"Test User"}'

# Login
curl -X POST http://localhost:8000/api/v1/auth/login \
  -H "Content-Type: application/json" \
  -d '{"email":"test@example.com","password":"testpass123"}'
```

### Day 4: Frontend Foundation
**Goal**: Create basic Dash application with authentication UI

**Tasks:**
1. Create `src/frontend/main.py` with Dash app
2. Create login/register components
3. Set up API client for backend communication
4. Implement basic navigation structure

**Validation:**
- Visit http://localhost:8501 shows login page
- Can register and login through UI
- Successful login redirects to dashboard

### Day 5: Application CRUD - Backend
**Goal**: Implement job application management (backend)

**Tasks:**
1. Create application models and database schema
2. Implement `src/backend/services/application_service.py`
3. Add application CRUD endpoints
4. Test with Row Level Security policies

**Endpoints to implement:**
- `POST /api/v1/applications`
- `GET /api/v1/applications`
- `GET /api/v1/applications/{id}`
- `PUT /api/v1/applications/{id}`
- `DELETE /api/v1/applications/{id}`

**Validation:**
```bash
# Create application (with auth token)
curl -X POST http://localhost:8000/api/v1/applications \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"company_name":"Google","role_title":"Developer","job_description":"We are looking for..."}'
```

---

## 📅 Week 2: Core Features

### Day 6: Application CRUD - Frontend
**Goal**: Create application management UI

**Tasks:**
1. Create application list/sidebar component
2. Create application form component
3. Implement application creation workflow
4. Add basic application status display

**Validation:**
- Can create new applications through UI
- Applications appear in sidebar
- Can view application details

### Day 7: AI Agents - Research Agent
**Goal**: Implement the first AI agent for job research

**Tasks:**
1. Create `src/agents/research_agent.py`
2. Implement Claude API integration
3. Create prompts for job description analysis
4. Add research report generation endpoint

**AI Agent Structure:**
```python
class ResearchAgent:
    async def analyze_job_description(self, job_desc: str) -> JobAnalysis
    async def research_company_info(self, company_name: str) -> CompanyInfo
    async def generate_research_report(self, application_id: str) -> ResearchReport
```

**Validation:**
- Can trigger research phase for an application
- Research report is generated and stored
- Content is relevant and well-formatted

### Day 8: Resume Management
**Goal**: Implement resume library functionality

**Tasks:**
1. Create resume models and endpoints
2. Add resume upload and storage
3. Create resume management UI
4. Implement resume selection for applications

**Endpoints:**
- `GET /api/v1/resumes`
- `POST /api/v1/resumes`
- `GET /api/v1/resumes/{id}`
- `PUT /api/v1/resumes/{id}`

### Day 9: AI Agents - Resume Optimizer
**Goal**: Implement resume optimization agent

**Tasks:**
1. Create `src/agents/resume_optimizer.py`
2. Implement resume analysis and optimization
3. Add resume optimization endpoint
4. Connect to application workflow

**Validation:**
- Can optimize resume based on job requirements
- Optimized resume is stored and retrievable
- Changes are meaningful and relevant

### Day 10: Document Management UI
**Goal**: Create document viewing and editing interface

**Tasks:**
1. Create document editor component with markdown support
2. Add document preview functionality
3. Implement save/cancel functionality
4. Add phase navigation between documents

**Validation:**
- Can view generated documents
- Can edit document content
- Changes are saved and persist
- Navigation between phases works

---

## 📅 Week 3: AI Integration & Polish

### Day 11: AI Agents - Cover Letter Generator
**Goal**: Complete the 3-phase AI workflow

**Tasks:**
1. Create `src/agents/cover_letter_generator.py`
2. Implement cover letter generation
3. Add user context input functionality
4. Complete the full workflow integration

**Validation:**
- Full 3-phase workflow works end-to-end
- Cover letters are personalized and relevant
- User can provide additional context

### Day 12: Error Handling & Validation
**Goal**: Add robust error handling and validation

**Tasks:**
1. Add comprehensive input validation
2. Implement error handling for AI API failures
3. Add user-friendly error messages
4. Create fallback mechanisms for AI services

### Day 13: Testing & Quality Assurance
**Goal**: Add essential tests and quality checks

**Tasks:**
1. Write unit tests for core services
2. Add integration tests for API endpoints
3. Test database security policies
4. Implement basic load testing

**Testing Commands:**
```bash
# Run all tests
docker-compose exec backend pytest

# Run with coverage
docker-compose exec backend pytest --cov=src --cov-report=html

# Test specific functionality
docker-compose exec backend pytest tests/unit/services/test_auth_service.py
```

### Day 14: Performance Optimization
**Goal**: Optimize system performance and reliability

**Tasks:**
1. Optimize database queries and indexes
2. Add caching for AI responses
3. Implement request rate limiting
4. Add monitoring and logging

---

## 📅 Week 4: Final Polish & Deployment

### Day 15-17: UI/UX Polish
**Goals:**
- Improve user interface design and responsiveness
- Add loading states and progress indicators
- Implement better navigation and user flow
- Add help text and user guidance

### Day 18-19: Security & Production Readiness
**Goals:**
- Security audit and hardening
- Environment-specific configurations
- Production deployment preparation
- Documentation updates

### Day 20: Final Testing & Release
**Goals:**
- End-to-end testing of complete workflows
- Performance testing under load
- Final bug fixes and polish
- MVP release preparation

---

## 🎯 Daily Validation Checklist

Use this checklist at the end of each day to ensure progress:

### Backend Development
- [ ] New endpoints work correctly
- [ ] Database changes are applied
- [ ] Tests pass for new functionality
- [ ] API documentation is updated
- [ ] Error handling is implemented

### Frontend Development
- [ ] UI components render correctly
- [ ] User interactions work as expected
- [ ] API integration functions properly
- [ ] Responsive design is maintained
- [ ] Loading states are implemented

### AI Agents
- [ ] AI responses are relevant and useful
- [ ] Error handling for API failures
- [ ] Performance is acceptable (<30s per operation)
- [ ] Content quality meets standards
- [ ] Integration with workflow is seamless

---

## 🚨 Common Daily Blockers & Solutions

### "AI API is not responding"
```bash
# Check API keys are set
echo $CLAUDE_API_KEY
echo $OPENAI_API_KEY

# Test API connectivity
curl -H "Authorization: Bearer $CLAUDE_API_KEY" https://api.anthropic.com/v1/messages
```

### "Database changes not reflected"
```bash
# Restart database service
docker-compose restart postgres

# Check database logs
docker-compose logs postgres

# Reconnect to verify changes
docker-compose exec postgres psql -U jobforge_user -d jobforge_mvp
```

### "Frontend not updating"
```bash
# Clear browser cache
# Check frontend logs
docker-compose logs frontend

# Restart frontend service
docker-compose restart frontend
```

---

## 📈 Progress Tracking

Track your daily progress in [MVP_CHECKLIST.md](MVP_CHECKLIST.md) and update the README status as you complete each phase.

**Remember**: This is an MVP - focus on core functionality over perfection. The goal is to have a working end-to-end system that demonstrates the 3-phase AI workflow.

---

**Ready to start building? Begin with Day 1 and work through each day systematically! 🚀**