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Course Outline
Overview of Agent-Driven Code
- How autonomous agents create and alter code
- Comprehending task breakdown and execution logs
- Typical failure points in agent workflows
Foundations of Verification in Antigravity
- Setting up verification checkpoints
- Monitoring agent decisions and assessing logic sequences
- Spotting irregularities in agent behavior
Handling Agent-Generated Artifacts
- Evaluating code diffs and patch quality
- Verifying documentation and metadata created by agents
- Inspecting both structured and unstructured outputs
Browser-Based Verification and Activity Logging
- Analyzing browser session recordings
- Identifying agent errors during UI-based tasks
- Aligning recorded events with the intended task flow
Task Validation Methods
- Ensuring task accuracy and completeness
- Implementing reproducibility and repeatability checks
- Utilizing constraint-based validation for AI workflows
Security Aspects of Agent-Driven Development
- Identifying potentially risky agent actions
- Performing static and dynamic analysis on agent output
- Strengthening verification steps to prevent security vulnerabilities
Testing for Reliability and Robustness
- Detecting fragile agent behaviors
- Stress-testing multi-stage agent operations
- Constructing robust validation pipelines
Integrating Antigravity QA into Current Pipelines
- Creating comprehensive end-to-end agent verification workflows
- Automating acceptance criteria for agent tasks
- Reporting on and monitoring agent performance
Conclusion and Future 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
