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Course Outline
Introduction to Agent-Driven Code
- The mechanics of how autonomous agents generate and modify code
- Comprehending task decomposition and execution traces
- Common failure points within agent workflows
Verification Foundations for Antigravity
- Defining key verification checkpoints
- Monitoring agent decision-making and evaluating logical sequences
- Spotting 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 outputs
Browser-Based Verification and Activity Recording
- Analyzing browser session recordings
- Identifying agent errors during UI-driven tasks
- Aligning recording events with the expected task flow
Task Validation Techniques
- Ensuring task accuracy and completeness
- Implementing reproducibility and repeatability checks
- Utilizing constraint-based validation for AI workflows
Security Considerations in Agent-Driven Development
- Identifying potentially risky agent actions
- Conducting static and dynamic analysis on agent outputs
- Strengthening verification steps to address security vulnerabilities
Testing Reliability and Robustness
- Recognizing brittle 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
- Practical experience with automation or QA methodologies
- Knowledge of AI-assisted development workflows
Target Audience
- QA Engineers
- SDETs
- Security Engineers
14 Hours
