Your First AI-Powered Project
Conotion AI CLI analyzes your existing code and automatically generates enterprise-grade improvements. Let's start with a simple example.
1. Initialize Your Project
cd your-project
conotion initThis command scans your project structure and creates an AI analysis baseline. The CLI will detect your framework, dependencies, and coding patterns to provide personalized recommendations.
Generate your first documentation
In 20 scd, generate a documentation :
conotionWhat the AI Analysis Discovers:
- • Security vulnerabilities and best practices
- • Performance optimization opportunities
- • Code architecture improvements
- • Missing documentation and tests
- • Dependencies and version updates
Automated Documentation Generation
Generate comprehensive documentation using AI that understands your code:
conotion docs generate --type allGenerated Documentation Includes:
- README.md: Project overview, installation, and usage
- API Documentation: Detailed endpoint and function docs
- Architecture Diagrams: Visual system design
- Deployment Guides: Step-by-step deployment instructions
- Contributing Guidelines: Development workflow documentation
Enterprise Architecture Transformation
Transform your prototype into production-ready, enterprise-grade code:
conotion transform --target enterpriseEnterprise Transformations:
- • Error handling and logging systems
- • Database connection pooling and optimization
- • Caching layer implementation
- • Security middleware and authentication
- • Monitoring and health check endpoints
- • Container and deployment configurations
Automated Testing & Quality
Generate comprehensive test suites based on your code structure:
conotion test generate --coverage 95The AI analyzes your functions, API endpoints, and business logic to create unit tests, integration tests, and end-to-end testing scenarios that achieve your target coverage.
Deployment Pipeline Automation
Create production-ready CI/CD pipelines tailored to your project:
conotion deploy setup --platform dockerSupported Platforms:
- Docker: Multi-stage builds with optimization
- Kubernetes: Helm charts and service configurations
- AWS: Lambda, ECS, and infrastructure as code
- Vercel: Optimized Next.js deployments
- Railway: Simple deployment configurations
Real-time Monitoring Setup
Implement comprehensive monitoring and alerting:
conotion monitor setup --alerts trueSets up application performance monitoring, error tracking, and custom metrics dashboard with intelligent alerting rules.
AI Command Examples
Optimize Database Queries
conotion optimize --target databaseSecurity Audit & Fix
conotion security --fix-criticalPerformance Benchmarking
conotion benchmark --compareAI Code Review
conotion review --detailedReady for Production
After running these commands, your project will have enterprise-grade architecture, comprehensive documentation, automated testing, and production deployment ready.