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

Introduction to Agent-Driven Code

• Mechanisms by which autonomous agents generate and modify code
• Comprehending task decomposition and execution traces
• Identifying typical failure modes in agent workflows

Verification Foundations for Antigravity

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

Working with Artifacts Generated by Agents

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

Browser-Based Verification and Activity Recording

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

Task Validation Techniques

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

Security Considerations in Agent-Driven Development

• Recognizing potentially risky agent actions
• Performing static and dynamic analyses on agent output
• Strengthening verification steps to address security gaps

Testing Reliability and Robustness

• Identifying fragile agent behaviors
• Conducting stress tests on 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 and monitoring agent performance

Summary and Next Steps