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Course Outline

Foundations of Agentic AI with Gemini 3

  • Agentic reasoning and the execution of autonomous tasks
  • Unique capabilities of Gemini 3 supporting agent workflows
  • Enterprise use cases necessitating autonomous agents

Navigating the Antigravity Development Environment

  • Core concepts, architectural overview, and toolset
  • Project and environment management
  • Execution and monitoring of agent runs

Architecture for Autonomous Agents

  • Structuring tasks and workflows to enable 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 and refine code
  • Delegating tasks to system tools and APIs
  • Managing tool permissions and operational capabilities

Leveraging Multimodal Capabilities in Gemini 3

  • Processing images, documents, and structured data
  • Synthesizing multiple modalities for complex planning
  • Extracting insights to drive autonomous decision-making

Enterprise System Integration for Agents

  • Connecting Antigravity to external APIs
  • Interacting with cloud services and databases
  • Constructing end-to-end automated business workflows

Refining and Assessing Agent Performance

  • Enhancing reliability and managing output variability
  • Debugging and optimizing agent actions
  • Performance optimization, scaling, and workload orchestration

Ethical Use, Safety, and Governance

  • Oversight of agent autonomy within enterprise contexts
  • Implementing safety rules, constraints, and governance controls
  • Auditing agent decisions and ensuring transparency

Conclusion and Future Directions

Requirements

  • A solid understanding 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
 21 Hours

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