Quality and safety: QA and guardrails

Build a simple QA habit for every AI output

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Learning goal

• Create a 5-point QA checklist.
• Apply it to two AI outputs.

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Why it matters

• Even good prompts can produce errors or bias.
• QA reduces risk before sharing.

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Explanation

• Check facts, numbers, dates.
• Check tone and audience fit.
• Ask for sources/disclaimers when needed.
• Spot sensitive data; redact if required.

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Examples

• QA prompt: “Review the draft for accuracy; list uncertainties; suggest fixes.”
• Guardrail: “Do not fabricate data; if unsure, say what’s missing.”

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Guided exercise (10–15 min)

1. Write a 5-point QA checklist (facts, tone, sources, risks, sensitive data).
2. Apply it to one output from Day 4.

Independent exercise (5–10 min)

Apply the checklist to a second output; add a guardrail instruction and compare results.

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Self-check

• QA checklist exists.
• Two outputs reviewed and improved.
• Guardrail instruction tested.

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Optional deepening

• OpenAI Safety Best Practices: https://platform.openai.com/docs/guides/safety-best-practices