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Duration 21 hours
Course Outline
Understanding Agentic AI with Gemini 3
- Agentic reasoning and the execution of autonomous tasks
- Unique capabilities of Gemini 3 tailored for agent workflows
- Enterprise scenarios that necessitate autonomous agents
Exploring the Antigravity Development Environment
- Core concepts, architectural design, and available toolset
- Managing projects and development environments
- Executing and monitoring agent runs
Designing 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
Multimodal Agent Capabilities with Gemini 3
- Processing images, documents, and structured data
- Combining multiple modalities for complex planning
- Extracting insights to drive 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
- Enhancing reliability and managing variability
- Debugging and refining agent actions
- Performance management, scaling, and workload orchestration
Responsible Use, Safety, and Governance
- Managing agent autonomy within enterprise contexts
- Implementing safety rules, constraints, and governance controls
- Auditing agent decisions and ensuring transparency
Summary and Next Steps
Requirements
- Familiarity with advanced AI concepts
- Experience in software development and cloud environments
- Proficiency in prompt engineering or model orchestration
Target Audience
- AI developers
- Software engineers
- R&D teams
Testimonials (1)
Flow , vibe and topic on presentation
