This page provides an LLM-generated summary of how teams are using Codegen agents, based on analysis of tens of thousands of customer agent runs. The data represents actual requests from users across different organizations and communication channels.

πŸ—οΈ Code Development & Implementation (35%)

The most common use case for Codegen agents is building new functionality and applications from scratch. Full-stack app creation
  • Complete Next.js/React applications with production-ready UI/UX
  • End-to-end web applications with authentication, databases, and deployment
  • Mobile and desktop applications across different platforms
Feature implementation
  • Adding new functionality to existing codebases
  • Implementing user stories and product requirements
  • Building complex business logic and workflows
API development
  • Creating REST and GraphQL endpoints
  • Third-party service integrations
  • Microservices architecture and implementation
Database work
  • Schema design and migrations
  • Complex queries and data analysis
  • Database optimization and performance tuning

πŸ” Code Review & Analysis (25%)

Teams heavily rely on Codegen for thorough code analysis and quality assurance. PR reviews
  • Deep code analysis with inline suggestions
  • Bug detection and security vulnerability identification
  • Code quality and best practices validation
Codebase audits
  • Performance analysis and optimization recommendations
  • Security reviews and compliance checks
  • Technical debt assessment and prioritization
Architecture reviews
  • Design pattern validation and improvements
  • System architecture recommendations
  • Code organization and structure analysis
Migration analysis
  • Impact assessment for major changes
  • Legacy system modernization planning
  • Framework and library upgrade guidance

πŸ› οΈ Bug Fixes & Maintenance (20%)

Codegen agents excel at debugging and maintaining existing systems. Issue resolution
  • Debugging complex problems across the stack
  • Root cause analysis and systematic fixes
  • Error handling and edge case management
Dependency updates
  • Package management and version conflict resolution
  • Security patch application
  • Breaking change migration assistance
Configuration fixes
  • Build system troubleshooting
  • Deployment pipeline optimization
  • Environment setup and configuration management
Performance optimization
  • Identifying and resolving bottlenecks
  • Memory and CPU usage optimization
  • Database query performance improvements

πŸ“‹ Project Management & Documentation (10%)

Teams use Codegen to streamline project workflows and maintain documentation. Linear ticket management
  • Creating and organizing development tasks
  • Sprint planning and backlog management
  • Progress tracking and status updates
Documentation creation
  • README files and setup instructions
  • API documentation and guides
  • Technical specifications and architecture docs
Project scoping
  • Breaking down large features into manageable tasks
  • Effort estimation and timeline planning
  • Risk assessment and mitigation strategies
Workflow automation
  • CI/CD pipeline setup and optimization
  • Development process standardization
  • Quality gates and automated checks

πŸ€– AI/ML & Specialized Tasks (5%)

Advanced use cases involving specialized tools and integrations. Feature flag cleanup
  • Statsig and A/B testing tool maintenance
  • Experimental feature management
  • Configuration cleanup and optimization
Data analysis
  • SQL queries and business intelligence
  • Performance metrics and analytics
  • Data pipeline development and maintenance
Integration work
  • Third-party API connections
  • Webhook setup and management
  • Service-to-service communication
Custom tooling
  • Specialized utilities and automation scripts
  • Developer productivity tools
  • Internal service development

πŸ’¬ Communication Channels

Linear (35%)
  • Primarily used for ticket management and feature requests
  • Project planning and sprint organization
  • Task assignment and progress tracking
Chat/API (30%)
  • Development tasks and quick fixes
  • Real-time problem solving
  • Interactive debugging sessions
Slack (20%)
  • Team collaboration and questions
  • Code reviews and discussions
  • Knowledge sharing and support
GitHub (15%)
  • Pull request reviews and management
  • Repository maintenance and organization
  • Release planning and deployment

🎯 Key Insights

  1. Most common request: β€œReview this PR” - developers want thorough, automated code analysis
  2. Growing trend: Full-stack application development from scratch with production-ready requirements
  3. High value tasks: Complex debugging, architecture decisions, and system design
  4. Quick wins: Documentation updates, simple feature additions, and configuration fixes
  5. Team efficiency: Agents handle routine tasks, allowing developers to focus on creative problem-solving

Getting Started

Ready to leverage these use cases for your team? Check out our overview to get started, or explore specific capabilities that align with your needs.