Testing AI Systems
Aiswarya discusses the importance of creating robust test cases to ensure AI systems maintain performance and security. The conversation highlights how tailored guidelines can help in auditing code for vulnerabilities. Additionally, Aiswarya emphasizes the significance of an effective onboarding experience, allowing users to grasp key areas of a codebase quickly before diving deeper.In this clip
From this podcast
Unaligned with Robert Scoble
#29: an AI-based engineering mentor
Related Questions
How can AI improve test suites?
What are the best approaches for AI coding assistants to get context in a large codebase as discussed in the episode The "Normsky" architecture for AI coding agents — with Beyang Liu + Steve Yegge of SourceGraph and the clip Code Understanding Revolution?
What should I test in software development based on the episode Google's Engineering Practices - What to Look for in a Code Review and the clip Testing Edge Cases as well as the episode Observability is for your unknown unknowns and the clip Unlocking Developer Superpowers?