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Duration 21 hours
Course Outline
Foundations of Agentic AI with Gemini 3
- Agentic reasoning mechanisms and autonomous task execution
- Specific capabilities of Gemini 3 tailored for agent workflows
- Enterprise use cases that necessitate autonomous agents
Navigating the Antigravity Development Environment
- Core architectural concepts and the available toolset
- Managing projects and configuring development environments
- Executing agent runs and monitoring their performance
Architecture of Autonomous Agents
- Structuring tasks and workflows to support autonomy
- Implementing multi-step reasoning and planning chains
- Designing secure and controlled action loops
Code Generation and Tool Utilization in Antigravity
- Enabling agents to write, refine, and debug code
- Delegating specific tasks to system tools and external APIs
- Overseeing tool permissions and defining agent capabilities
Advanced Multimodal Agent Capabilities with Gemini 3
- Processing diverse inputs including images, documents, and structured data
- Combining multiple modalities to support complex planning processes
- Extracting actionable insights to drive autonomous decision-making
Integration of Agents with Enterprise Ecosystems
- Establishing connections between Antigravity and external APIs
- Interacting with cloud services, databases, and other infrastructure
- Developing end-to-end automated business workflows
Performance Optimization and Agent Evaluation
- Enhancing reliability and managing output variability
- Debugging issues and refining agent actions for better outcomes
- Addressing performance metrics, scaling strategies, and workload orchestration
Ethical Use, Safety Protocols, and Governance
- Managing the degree of agent autonomy within enterprise contexts
- Implementing safety rules, operational constraints, and governance controls
- Auditing agent decisions to ensure full transparency
Wrap-up and Future Steps
Requirements
- A solid grasp of advanced AI concepts
- Practical experience with software development lifecycles and cloud-based environments
- Familiarity with prompt engineering techniques or model orchestration strategies
Intended Audience
- AI developers
- Software engineers
- Research and Development (R&D) teams
Testimonials (1)
Flow , vibe and topic on presentation
