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Duration 21 hours
Course Outline
Comprehending Agentic AI with Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Distinctive capabilities of Gemini 3 for agent workflows
- Enterprise scenarios that necessitate autonomous agents
Navigating the Antigravity Development Environment
- Key concepts, architectural components, and the toolset
- Managing projects and development environments
- Running and monitoring agent executions
Architecting Autonomous Agents
- Structuring tasks and workflows to support autonomy
- Implementing multi-step reasoning and planning chains
- Designing safe and controlled action loops
Coding and Tool Utilization in Antigravity
- Enabling agents to write and refine code
- Delegating tasks to system tools and APIs
- Managing tool permissions and defined capabilities
Leveraging Multimodal Agent Capabilities with Gemini 3
- Processing images, documents, and structured data
- Integrating multiple modalities for complex planning
- Deriving insights to facilitate autonomous decision-making
Integrating Agents with Enterprise Systems
- Connecting Antigravity to external APIs
- Interacting with cloud services and databases
- Constructing end-to-end automated business workflows
Refining and Assessing Agent Behavior
- Enhancing reliability and managing variability
- Debugging and optimizing agent actions
- Addressing performance, scaling, and workload orchestration
Responsible Usage, Safety, and Governance
- Managing agent autonomy within enterprise contexts
- Implementing safety rules, constraints, and governance controls
- Auditing agent decisions to maintain transparency
Summary and Next Steps
Requirements
- A solid grasp of advanced AI concepts
- Practical experience in software development and cloud environments
- Familiarity with prompt engineering or model orchestration
Target Audience
- AI Developers
- Software Engineers
- R&D Teams
Testimonials (1)
Flow , vibe and topic on presentation
