Content Safety and Moderation › Key Takeaways

You now have multiple strategies for keeping your agent's outputs safe:

System prompts teach your agent to recognize and refuse inappropriate requests. This is your first line of defense and handles most cases.

Output filtering adds a second layer of protection, catching anything that slips through the system prompt.

Pattern blocking provides deterministic protection for specific sensitive data formats.

Graceful refusals maintain a good user experience even when declining requests. Acknowledge, explain briefly, and offer alternatives.

Privacy boundaries protect sensitive information from being shared inappropriately.

The goal isn't to make your agent paranoid or overly restrictive. It's to make it trustworthy. A safe agent is one that users can rely on to do the right thing, even when they accidentally ask for the wrong thing.

As you deploy your agent, you'll refine these safety measures based on real usage. Start conservative, test thoroughly, and iterate based on feedback. Safety isn't a one-time implementation. It's an ongoing commitment to responsible AI.