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Course Outline

Comprehending Agentic AI with Gemini 3

  • Agentic reasoning and the execution of autonomous tasks
  • Specific capabilities of Gemini 3 suited for agent workflows
  • Enterprise use cases necessitating autonomous agents

Navigating the Antigravity Development Environment

  • Foundational concepts, architecture, and available tools
  • Project and environment management strategies
  • Execution and monitoring of agent operations

Architecting Autonomous Agents

  • Structuring tasks and workflows to support autonomy
  • Implementing multi-step reasoning and planning sequences
  • Designing safe and controlled action loops

Code Generation and Tool Interaction in Antigravity

  • Enabling agents to write and refine code
  • Delegating specific tasks to system tools and APIs
  • Overseeing tool permissions and functional capabilities

Leveraging Multimodal Capabilities with Gemini 3

  • Processing images, documents, and structured data sets
  • Synthesizing multiple modalities for complex planning scenarios
  • Deriving insights to support autonomous decision-making

Connecting Agents to Enterprise Infrastructure

  • Linking Antigravity with external APIs
  • Interacting with cloud services and database systems
  • Creating end-to-end automated business workflows

Refining and Assessing Agent Performance

  • Enhancing reliability and managing variability
  • Debugging and fine-tuning agent actions
  • Optimizing performance, scaling, and workload orchestration

Ethical Use, Safety, and Governance

  • Governing agent autonomy within enterprise settings
  • Establishing safety rules, constraints, and governance controls
  • Auditing agent decisions and ensuring transparency

Conclusion and Future Directions

Requirements

  • A solid grasp of advanced AI concepts.
  • Practical experience in software development and cloud environments.
  • Familiarity with prompt engineering or model orchestration techniques.

Target Audience

  • AI developers
  • Software engineers
  • R&D teams
 21 Hours

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