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

Foundations of Agent-Driven Code

• How autonomous agents create and modify code
• Comprehending task decomposition and execution traces
• Typical failure modes in agent workflows

Verification Basics in Antigravity

• Setting up verification checkpoints
• Monitoring agent decision-making and evaluating logic sequences
• Detecting anomalies in agent behavior

Handling Agent-Generated Artifacts

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

Browser-Based Verification and Activity Capture

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

Techniques for Task Validation

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

Security Implications in Agent-Driven Development

• Identifying potentially risky agent actions
• Conducting static and dynamic analyses of agent output
• Strengthening verification steps to mitigate security gaps

Assessing Reliability and Robustness

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

Incorporating Antigravity QA into Existing Pipelines

• Designing comprehensive end-to-end agent verification workflows
• Automating acceptance criteria for agent tasks
• Monitoring and reporting on agent performance

Recap and Future Directions