🛡️ Appropriate safety beats maximum safety

PM AI Safety
(2026 Edition)

5 safety layers and 4 traps for AI safety PMs.

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5 Layers

1.

System prompt guardrails

2.

Pre-generation classifier (filter inputs)

3.

Post-generation classifier (filter outputs)

4.

Adversarial red-teaming and probing

5.

Human review queue for edge cases

4 Traps

Over-refusal — too cautious models become useless

Under-refusal — brand and legal risk

Static safety thresholds that don't evolve with attacks

Treating safety as launch checklist not ongoing work

FAQ

How do PMs balance AI safety and usefulness?

Through measured refusal rates and user feedback loops. Track when the model refuses; track when users complain about over-refusal vs under-refusal. The goal isn't maximum safety — it's appropriate safety for the audience and use case. Customer support AI needs different guardrails than developer tooling AI.

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