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Duration 14 hours (2 days)
Course Outline
Team Collaboration in Cursor
- Creating and administering team workspaces
- Sharing context and code sessions among team members
- Defining access roles and establishing collaboration protocols
AI-Assisted Pull Request Generation
- Comprehending AI-generated pull requests (PRs)
- Customizing PR templates and associated policies
- Verifying AI-generated changes prior to merging
Automating Code Reviews with Cursor
- Employing AI to identify issues and propose enhancements
- Evaluating code style, logic, and documentation consistency
- Integrating with review workflows in GitHub, GitLab, or Bitbucket
Policy Guards and Governance
- Defining code quality and security standards
- Configuring approval gates and rule-based enforcement mechanisms
- Auditing AI decisions and ensuring accountability
Integrating Cursor into CI/CD Pipelines
- Linking Cursor with Jenkins, GitHub Actions, or GitLab CI
- Automating builds and deployments leveraging AI insights
- Maintaining compliance within automated pipelines
Monitoring and Metrics for AI-Driven Workflows
- Tracking productivity and quality indicators
- Analyzing reports on the impact of AI contributions
- Identifying opportunities for process optimization
Scaling Cursor Adoption Across Teams
- Onboarding multiple teams with standardized configurations
- Managing shared settings and best practices
- Promoting continuous improvement and team training
Future Trends and Advanced Integrations
- Connecting with security scanners and QA systems
- Exploring API-based automation using Cursor
- Planning for the evolution of AI-assisted DevOps workflows
Summary and Next Steps
Requirements
- Practical experience with Git-based version control workflows
- Working knowledge of CI/CD tools and underlying principles
- A solid understanding of collaborative software development processes
Target Audience
- Team leads and senior developers
- DevOps and CI/CD engineers
- Engineering managers overseeing the adoption of AI technologies