Lesson 7: Policy = Guardrails — AgentCraft

ChatGPT refuses harmful requests using input and output gates. Build AI guardrails in a few lines of Python — what Guardrails AI and NeMo Guardrails abstract away.

Policy = Guardrails You've seen this: ask ChatGPT to help with something harmful and it refuses. Ask Claude to generate malware and it declines. That's not the LLM being "smart" — it's policy. Rules checked before and after the LLM runs. The L3 loop trusts the user and the LLM completely. Production agents can't afford that. Policy adds two gates: • Input gate: blocks dangerous requests *before* they reach the LLM (saves money, prevents harm) • Output gate: redacts or rejects the LLM's response *before* the user sees it > Framework parallel: Guardrails AI and NeMo Guardrails implement exactly these two gates. OpenAI's moderation endpoint is an input gate. The architecture is identical.

Concepts covered

policy
guardrails
input gate
output gate
safety

Framework comparison: Guardrails AI, NeMo Guardrails, LangChain output parsers — rules checked before and after the LLM.