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Course Outline

Understanding Agentic AI with Gemini 3

  • Concepts of agentic reasoning and autonomous task execution
  • Unique capabilities of Gemini 3 for agent workflows
  • Enterprise scenarios that benefit from autonomous agents

Exploring the Antigravity Development Environment

  • Core concepts, architecture, and available toolset
  • Project management and environment setup
  • Executing and monitoring agent runs

Designing Autonomous Agents

  • Structuring tasks and workflows for autonomy
  • Implementing multi-step reasoning and planning chains
  • Designing safe and controlled action loops

Coding and Tool Use 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 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 controlling variability
  • Debugging and refining agent actions
  • Performance optimization, 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 maintaining transparency

Summary and Next Steps

Requirements

  • A solid understanding of advanced AI concepts
  • Practical experience in software development and cloud environments
  • Knowledge of prompt engineering or model orchestration techniques

Audience

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

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Provisional Upcoming Courses (Require 5+ participants)

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