Adversarial Testing 101: Break Your Model Before Your Users Do

Short summary

Adversarial testing is deliberately crafting tricky inputs to break your AI model before users encounter failures in production. The practice spans explicit jailbreak attempts and subtle implicit edge cases that look normal but hide cultural or contextual landmines. Start small: write your model's safety policy, hand-craft 20-30 tricky prompts per failure category, run them, and carefully review outputs instead of skimming—this gets you surprisingly far.

• •Adversarial testing proactively surfaces failure modes before production deployment
• •Two categories: explicit jailbreaks and implicit edge cases (harder to spot)
• •Low-cost entry point: manual prompt testing against your documented policy

Generated with AI, which can make mistakes.