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Duration 14 hours
Course Outline
Fundamentals of Agent-First IDEs
- Comprehending the transition from conventional IDEs to agent-centric architectures
- Key principles underpinning AI-driven development platforms
- The position of Antigravity within contemporary engineering toolkits
Installing and Running Google Antigravity
- Hardware prerequisites and the installation process
- Initial configuration and workspace configuration
- An overview of the standard interface structure
Utilising the Editor View
- Primary editing tools and navigation features
- Engaging with agents directly within the editor
- Overseeing file modifications and project assets
Interacting with the Manager View
- A summary of task coordination and workflow management
- Evaluating and authorising agent operations
- Tracking project progress and agent activity
Grasping Agents in Antigravity
- Categories of agents and their respective functions
- The mechanism by which agents decode intent and carry out tasks
- Optimal techniques for instructing and guiding agents
Developing and Automating Basic Tasks
- Generating initial code structures and templates
- Employing agents to restructure or improve existing code
- Implementing verification and review procedures via agents
Project Management in an Agent-Centric Setting
- Directory architecture and file arrangement standards
- Monitoring changes and project status through agents
- Synchronising automation across various tasks
Expanding Scope: Real-World Applications for Beginners
- Developing compact utilities with agent assistance
- Integrating agents into continuous development cycles
- Leveraging Antigravity for documentation creation and code refactoring
Conclusion and Future Directions
Requirements
- A foundational grasp of standard software development processes
- Hands-on experience with contemporary Integrated Development Environments (IDEs)
- Knowledge of fundamental version control principles
Target Audience
- Developers interested in AI-enhanced coding practices
- Software engineers new to agent-centric development models
- Technical leads assessing AI-powered engineering solutions