Context

GenAI systems behave differently from deterministic software: the same input can produce multiple acceptable outputs, and small prompt changes can shift behavior. This makes traditional exact-match testing insufficient.

Core Question

Explain the main behaviors of GenAI systems that affect testing, and how you would adapt a coding-oriented test strategy to handle them.

Address these sub-questions:

1. Which GenAI behaviors most commonly break standard deterministic test assumptions?
2. How would you design automated tests for outputs that are variable but still valid?
3. What failure modes should be covered beyond simple correctness, such as hallucination, formatting drift, and prompt sensitivity?

Scope Guidance

The interviewer expects a practical engineering explanation, not a product discussion. Focus on test design, validation logic, reproducibility, robustness checks, and how algorithmic techniques such as normalization, rule-based validation, and similarity scoring can be used in code-driven evaluation pipelines.