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Duration 21 hours
Course Outline
Understanding Agentic AI with Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Specific capabilities of Gemini 3 for agent workflows
- Enterprise use cases that necessitate autonomous agents
Exploring the Antigravity Development Environment
- Core concepts, architecture, and available toolsets
- Project and environment management
- Running and monitoring agent executions
Designing Autonomous Agents
- Structuring tasks and workflows for full autonomy
- Implementing multi-step reasoning and planning chains
- Creating 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 capabilities
Multimodal Agent Capabilities with Gemini 3
- Processing images, documents, and structured data
- Combining different modalities for complex planning
- Extracting insights to support autonomous decision-making
Integrating Agents with Enterprise Systems
- Connecting Antigravity to external APIs
- Interacting with cloud services and databases
- Building end-to-end automated business workflows
Optimizing and Evaluating Agent Behavior
- Improving reliability and managing variability
- Debugging and refining agent actions
- Performance management, scaling, and workload orchestration
Responsible Use, Safety, and Governance
- Managing agent autonomy in enterprise settings
- Establishing safety rules, constraints, and governance controls
- Auditing agent decisions and ensuring transparency
Summary and Next Steps
Requirements
- A solid understanding of advanced AI concepts
- Practical experience with 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
