Role-Based Programme
RB0873

Google Antigravity for Quality Management

Advanced AI-Assisted Testing, Validation & Quality Engineering

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced expertise in using Antigravity for software testing, defect investigation, validation, and quality engineering.
  • Architect agentic QA workflows for test generation, execution, regression, browser validation, and release readiness.
  • Apply parallel AI agents to analyse code, requirements, defects, test evidence, and application behaviour.
  • Automate repeatable quality activities using Antigravity agents, CLI, SDK, and controlled tool execution.
  • Establish governance, human approvals, traceability, and quality gates for enterprise agent-assisted testing.

Tools covered

Google Antigravity 2.0Antigravity IDEAI AgentsAgent ManagerArtifactsBrowser & Terminal ToolsParallel AgentsAntigravity CLIAntigravity SDKHooks

Who should attend

  • Quality Assurance Managers
  • Software Quality Engineers
  • QA Engineers
  • Software Test Engineers
  • Test Automation Engineers
  • Test Leads & QA Leads
  • Software Validation Professionals
  • Quality Engineering Professionals
  • DevOps Quality Engineers
  • Application Quality Professionals
  • Release & Validation Managers
  • Technical Quality Leaders

Prerequisites & Participant Readiness

  • Working knowledge of software testing and quality assurance
  • Familiarity with test cases, defects, regression testing, and release validation
  • Basic ability to understand source code, APIs, or application architecture
  • Familiarity with Git, terminal commands, or test automation is recommended
  • Basic scripting or programming knowledge is beneficial
  • No previous Antigravity course is required

TOC Modules

Concepts
  • Understanding Antigravity 2.0, Antigravity IDE, agents, tools, tasks, and artifacts
  • Understanding autonomous Plan → Act → Observe → Verify agent workflows
  • Mapping Antigravity capabilities to software-quality lifecycle activities
Practical activities
  • Exploring a sample application through an Antigravity agent
  • Creating an initial AI-assisted quality-review workflow

Scenarios

Enterprise Application Release Validation

Requirements → Parallel Antigravity Agents → Test Design → Automated Execution → Browser Validation → Defects → Fix Verification → Regression → Release Recommendation

Participants orchestrate multiple agents to validate an application release, investigate defects, execute regression testing, and produce traceable quality evidence for release approval.

Continuous AI-Assisted Quality Engineering

Code Change → Automated Agent Trigger → Impact Analysis → Tests → Execution → Findings → Human Approval → Quality Report

Participants design a reusable agent-assisted QA workflow using Antigravity CLI or SDK to analyse software changes, run appropriate validation, consolidate results, and escalate findings for human quality approval.

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