# Safety Essentials Every LLM Feature Needs — LLM Engineering Foundations

Source: https://www.geekswithgeeks.com/en/llm-engineering/g-safety

> Apply the core controls; go deeper in the security and AI-safety courses.

## A short list that prevents most trouble

Every LLM feature, however small, should have these controls. **Treat model output as untrusted** (escape, parameterise, validate). **Treat retrieved and user content as untrusted instructions**: fence and label it, never let it grant permissions. **Least privilege** for tools and data, with **per-user authorisation** and **human approval** for risky actions. **No secrets in prompts or logs**; redact personal data. **Rate limits and spend caps.** **Content safety** appropriate to your audience (moderation, refusal behaviour, escalation paths for sensitive topics such as health or self-harm). **Honest UX**: tell users they are talking to an AI, show sources, express uncertainty, and offer a human. **Red-team tests in CI.** The dedicated courses on LLM application security and AI safety cover each of these in depth; this checklist is the minimum bar to clear before launch.

## Responsible by design, documented, shared

Security basics, privacy, documentation and clear roles keep LLM features trustworthy as they and the team grow.

![Three needs: safe, accountable, documented.](assets/figures/llm-engineering/section-7-map.svg) — Figure 7.1 — Safe, accountable and documented.

## A pre-launch safety checklist

Tick every box or write down why not.

```text
[ ] model output escaped / parameterised / schema-validated before any use
[ ] retrieved + user content fenced, labelled as data; cannot grant permissions
[ ] tools least-privilege; per-user authorisation; approvals for risky actions; default-deny policy
[ ] no secrets in prompts/logs; PII minimised and redacted
[ ] rate limits, token/step caps, spend cap + alert
[ ] content-safety behaviour tested (refusals, sensitive topics, escalation to a human)
[ ] UX: AI disclosure, sources shown, uncertainty expressed, human handoff available
[ ] red-team suite in CI; incident runbook + kill switches rehearsed
```

## Rehearse the kill switch

Disable a tool or feature in staging to confirm the app degrades gracefully.

**Quiz:** Which is part of an honest UX for an LLM feature?

- [ ] Hiding all uncertainty
- [ ] Pretending to be a human
- [x] Telling users it is an AI, showing sources and offering a human
- [ ] Removing citations

*Answer:* Telling users it is an AI, showing sources and offering a human. Transparency builds appropriate trust and reduces harm from wrong answers.