Safety & Alignment

Safety is about preventing harmful or wrong outputs and having systems to catch problems before users see them.

Quick safety checklist:

• Negative constraints: tell the model what not to do (e.g., “Do not provide medical advice”).
• Automated validators: run moderation filters or lightweight checks (e.g., profanity, PII, JSON schema).
• Human-in-the-loop: require humans for risky or high-impact actions.

Testing for alignment:

• Run adversarial tests: try inputs designed to make the model fail and see how your templates behave.
• Keep a simple policy doc that explains what outputs are allowed and which are not.

Handling risky outputs:

• If a validator flags an output, either correct it automatically, ask the model to retry with stricter rules, or escalate to a human reviewer.
• Log and store examples of failures (redacted) so teams can improve templates and training data.

Design note: safety trade-offs often mean extra checks and latency, but they protect users and reduce serious mistakes.