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Duration 14 hours
Course Outline
Introduction to Agent-First IDEs
- Grasping the transition from conventional IDEs to agent-first architectures
- Key principles underpinning AI-driven development platforms
- The role of Antigravity within contemporary engineering toolchains
Installation and Initialization of Google Antigravity
- System prerequisites and the installation process
- Initial setup and workspace configuration
- An overview of the standard interface layout
Navigation and Features of the Editor View
- Primary editing tools and navigation controls
- Engaging with agents directly within the editor
- Oversight of file modifications and project assets
Operations in the Manager View
- Insights into task orchestration and workflow management
- Evaluation and authorization of agent activities
- Tracking project progress and agent operational status
Concepts Behind Agents in Antigravity
- Categories of agents and their respective functional capabilities
- Mechanisms for agent intent interpretation and task execution
- Strategies for effective prompting and agent direction
Automation of Basic Development Tasks
- Creation of initial code structures and templates
- Leveraging agents for code refactoring and enhancement
- Implementation of validation and review protocols via agents
Project Administration in an Agent-Driven Context
- Directory structures and file organization standards
- Monitoring changes and project states through agent assistance
- Managing automated processes across multiple tasks
Practical Applications for Emerging Practitioners
- Construction of small-scale utilities with agent support
- Integration of agents into iterative development cycles
- Application of Antigravity for documentation and code maintenance
Recap and Future Directions
Requirements
- A solid grasp of fundamental software development cycles
- Hands-on experience with contemporary IDEs
- Basic knowledge of version control principles
Target Audience
- Developers interested in AI-assisted coding practices
- Software engineers new to agent-centric development models
- Technical leaders evaluating AI-powered engineering solutions