Agentic Development with Gemini 3 and Google Antigravity Training Course
Google Antigravity serves as an agentic development environment for creating autonomous agents that can plan, reason, code, and act by leveraging the multimodal capabilities of Gemini 3.
This instructor-led live training, available online or onsite, targets advanced technical professionals seeking to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.
After completing this training, participants will be equipped to:
- Create autonomous workflows that utilize Gemini 3 for reasoning, planning, and execution.
- Develop agents within Antigravity capable of analyzing tasks, writing code, and interacting with tools.
- Integrate Gemini-driven agents with enterprise systems and APIs.
- Enhance agent behavior, safety, and reliability in complex environments.
Course Format
- Expert demonstrations paired with interactive discussions.
- Hands-on experimentation focused on autonomous agent development.
- Practical implementation using Antigravity, Gemini 3, and supporting cloud tools.
Course Customization Options
- For teams requiring domain-specific agent behaviors or custom integrations, please reach out to us to tailor the program.
Course Outline
Understanding Agentic AI with Gemini 3
- Agentic reasoning and autonomous task execution
- Capabilities unique to Gemini 3 for agent workflows
- Enterprise scenarios requiring autonomous agents
Exploring the Antigravity Development Environment
- Core concepts, architecture, and toolset
- Managing projects and environments
- Executing and monitoring agent runs
Designing Autonomous Agents
- Structuring tasks and workflows for autonomy
- Multi-step reasoning and planning chains
- Designing safe and controlled action loops
Coding and Tool Use in Antigravity
- Allowing 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 for 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, scaling, and workload orchestration
Responsible Use, Safety, and Governance
- Managing agent autonomy in enterprise contexts
- Safety rules, constraints, and governance controls
- Auditing agent decisions and maintaining transparency
Summary and Next Steps
Requirements
- An understanding of advanced AI concepts
- Experience with software development and cloud environments
- Knowledge of prompt engineering or model orchestration
Audience
- AI developers
- Software engineers
- R&D teams
Open Training Courses require 5+ participants.
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Testimonials (1)
Flow , vibe and topic on presentation
Lukasz Kowalczyk - Allegro Sp. z o.o.
Course - Google Gemini AI for Data Analysis
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