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Course Outline

Introduction to Agent-Driven Code

  • The process by which autonomous agents generate and modify code
  • Understanding task decomposition and execution traces
  • Common failure modes in agent workflows

Verification Foundations for Antigravity

  • Setting up verification checkpoints
  • Monitoring agent decision-making and assessing logical sequences
  • Identifying anomalies in agent behavior

Working with Artifacts Generated by Agents

  • Evaluating code diffs and patch quality
  • Validating documentation and metadata created by agents
  • Reviewing both structured and unstructured output

Browser-Based Verification and Activity Recording

  • Interpreting browser session recordings
  • Identifying agent errors during UI-driven tasks
  • Aligning recording events with the expected task flow

Task Validation Techniques

  • Verifying task accuracy and completeness
  • Implementing reproducibility and repeatability checks
  • Employing constraint-based validation for AI workflows

Security Considerations in Agent-Driven Development

  • Recognizing potentially risky agent actions
  • Conducting static and dynamic analyses of agent output
  • Strengthening verification processes to close security gaps

Testing Reliability and Robustness

  • Identifying fragile agent behaviors
  • Stress-testing multi-step agent operations
  • Developing resilient validation pipelines

Integrating Antigravity QA into Existing Pipelines

  • Designing end-to-end agent verification workflows
  • Automating acceptance criteria for agent tasks
  • Reporting on and monitoring agent performance

Summary and Next Steps

Requirements

  • A solid grasp of software testing fundamentals
  • Hands-on experience with automation or QA methodologies
  • Awareness of AI-assisted development workflows

Target Audience

  • QA engineers
  • SDETs
  • Security engineers
 14 Hours

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