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Course Outline

Grasping the Architecture of Google Antigravity

  • Core agent-first design principles
  • The distinct roles of Editor and Manager interfaces
  • Workspace organization and execution contexts

Setting Up Agents and Defining Capabilities

  • Allocating specific roles and specializations to agents
  • Establishing task boundaries and levels of autonomy
  • Overseeing security protocols and agent permissions

Architecting Multi-Agent Workflows

  • Strategic workflow planning and sequencing
  • Synchronizing background and foreground agent activities
  • Utilizing chaining, delegation, and escalation patterns

Utilizing the Manager (Mission-Control) Interface

  • Monitoring real-time agent performance
  • Analyzing graphs, states, and execution timelines
  • Executing interventions, overrides, or task redirections

Producing and Administering Antigravity Artifacts

  • Managing task lists, operational plans, and decision trails
  • Capturing screenshots, browser recordings, and workspace states
  • Handling audit logs and reproducibility metadata

Verification and Quality Assurance Practices

  • Maintaining traceability and operational transparency
  • Verifying the accuracy of agent outputs
  • Introducing safeguards and failover mechanisms

Embedding Antigravity into Engineering Pipelines

  • Aligning with CI/CD and release management workflows
  • Integrating with established DevOps toolchains
  • Scaling agent operations across various teams and environments

Advanced Optimization of Multi-Agent Collaboration

  • Minimizing redundant actions and processing cycles
  • Applying performance metrics and analytics for improvement
  • Crafting resilient and adaptive workflow designs

Conclusions and Future Directions

Requirements

  • Foundational knowledge of modern DevOps and platform engineering principles
  • Practical experience with AI-assisted development processes
  • Acquaintance with distributed systems or cloud infrastructure

Target Audience

  • Platform Engineers
  • DevOps Engineers
  • AI Architects
 14 Hours

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  • Format: Online (live), In-company (at your offices), or Hybrid.
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