Testing & Verifying Agent-Driven Code: Quality Assurance in Antigravity Training Course

Introduction to Agent-Driven Code

• The mechanics of how autonomous agents generate and modify code
• Comprehending task decomposition and execution traces
• Typical failure modes within agent workflows

Verification Foundations in Antigravity

• Defining verification checkpoints
• Monitoring agent decision-making and assessing logic sequences
• Identifying anomalies in agent behavior

Managing Artifacts Generated by Agents

• Evaluating code diffs and the quality of patches
• Verifying documentation and metadata created by agents
• Reviewing both structured and unstructured outputs

Browser-Based Verification and Activity Logging

• Analyzing browser session recordings
• Detecting errors during UI-driven agent tasks
• Aligning recorded events with the expected task flow

Techniques for Task Validation

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

Security Implications in Agent-Driven Development

• Identifying potentially risky agent actions
• Performing static and dynamic analysis on agent outputs
• Strengthening verification steps to mitigate security vulnerabilities

Ensuring Reliability and Robustness

• Identifying fragile agent behaviors
• Stress-testing complex, multi-step agent operations
• Constructing resilient validation pipelines

Integrating Antigravity QA into Existing Pipelines

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

Summary and Next Steps