An AI agent's demo success does not guarantee real-world performance, as behavior can drift due to model updates or prompt changes. To mitigate this, a regression floor of repeatable tests is crucial before any deployment. These tests should cover five failure classes: instruction conflicts where system and user directives clash, prompt injection resistance against various data inputs, tool error handling for unexpected API responses, and privacy protection to prevent accidental data leakage. AI
IMPACT Establishes a framework for testing AI agent reliability and preventing common production issues like instruction conflicts and data leakage.
RANK_REASON The item discusses practical failure modes and testing strategies for AI agents in production, which is a tooling/product-focused topic.
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