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Course Outline
Understanding Agentic AI through Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Unique capabilities of Gemini 3 for agent workflows
- Enterprise use cases that necessitate autonomous agents
Navigating the Antigravity Development Environment
- Foundational concepts, architecture, and available toolset
- Administration of projects and development environments
- Execution and monitoring of agent operations
Architecting Autonomous Agents
- Organizing tasks and workflows to support autonomy
- Multi-step reasoning and planning sequences
- Creating safe and controlled action loops
Code Generation and Tool Utilization in Antigravity
- Enabling agents to author and iterate on code
- Assigning tasks to system tools and APIs
- Oversight of tool permissions and capabilities
Leveraging Multimodal Agent Features with Gemini 3
- Interpretation of images, documents, and structured data
- Synthesis of multiple modalities for complex planning
- Deriving insights for autonomous decision-making processes
Connecting Agents to Enterprise Ecosystems
- Linking Antigravity with external APIs
- Interaction with cloud services and database systems
- Construction of end-to-end automated business processes
Refining and Assessing Agent Performance
- Enhancing reliability and managing output variability
- Debugging and fine-tuning agent actions
- Performance optimization, scaling, and workload management
Ethical Use, Safety, and Governance
- Oversight of agent autonomy within enterprise settings
- Implementation of safety protocols, constraints, and governance measures
- Audit of agent decisions and preservation of transparency
Conclusion and Future Directions
Requirements
- Familiarity with advanced AI concepts
- Proficiency in software development and cloud infrastructure
- Background in prompt engineering or model orchestration
Target Audience
- AI Developers
- Software Engineers
- R&D Teams
21 Hours
Testimonials (1)
Flow , vibe and topic on presentation