Building Safe AI Agents with Guardrails
We start with a DataTalks.Club Data Engineering Zoomcamp FAQ assistant. Then we add checks that keep the agent on topic and block unsafe responses. The checks also show how to cancel wasted work when a guardrail fails. We first use the OpenAI Agents SDK for its built-in guardrails. Then we rebuild the same idea with tools and plain asyncio, so it works with other agent frameworks. Links The external resources: Related course: AI Bootcamp: From RAG to Agents FAQ data used by the agent AI Hero email course for the docs.py loader OpenAI Agents SDK guardrails documentation The notebook you will build By the end, you wrap a tool-using FAQ agent in guardrails: The base agent can already search the FAQ, but it tries to answer unrelated questions too. The input guardrail blocks questions outside the course domain. The output guardrail checks the agent response for policy problems. Examples are promising deadline extensions or writing homework for a student. In the later parts we show the same checks as tools. We also build a small async runner that can cancel work when a guardrail trips.