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Course Outline

Foundations of Agentic AI with Gemini 3

  • Agentic reasoning processes and autonomous task completion.
  • Specific capabilities of Gemini 3 that enhance agent workflows.
  • Business cases necessitating the use of autonomous agents.

Overview of the Antigravity Development Platform

  • Key architectural concepts, core principles, and available tooling.
  • Techniques for managing projects and development environments.
  • Processes for executing and overseeing agent operations.

Architecting Autonomous Agents

  • Structuring workflows and tasks to support autonomous operation.
  • Implementing multi-step reasoning and planning sequences.
  • Creating secure and regulated action cycles.

Code Generation and Tool Utilization in Antigravity

  • Enabling agents to generate and iteratively improve code.
  • Assigning tasks to system utilities and external APIs.
  • Oversight of tool permissions and functional boundaries.

Exploiting Multimodal Features with Gemini 3

  • Handling images, documents, and structured datasets.
  • Synthesizing multiple data types for advanced planning.
  • Deriving insights to support autonomous decision-making.

Connecting Agents to Enterprise Infrastructure

  • Establishing connections between Antigravity and external APIs.
  • Interacting with cloud-based services and database systems.
  • Developing comprehensive, automated business processes.

Refining and Assessing Agent Performance

  • Enhancing operational reliability and managing variability.
  • Troubleshooting and refining agent actions.
  • Addressing performance, scalability, and workload management.

Responsible Deployment, Safety, and Governance

  • Regulating agent autonomy within corporate settings.
  • Defining safety protocols, constraints, and governance mechanisms.
  • Auditing decision pathways and ensuring transparency.

Conclusion and Future Directions

Requirements

  • A solid grasp of advanced artificial intelligence concepts.
  • Proficiency in software engineering and cloud computing environments.
  • Familiarity with prompt engineering techniques or model orchestration.

Target Audience

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

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