Implementing Guardrails in .NET AI Applications

Learn how to build safer, more reliable, and controlled AI applications using practical guardrail techniques with .NET.

In this hands-on 1:1 session, we'll explore how to control AI inputs and outputs, validate responses, restrict unwanted behavior, and handle scenarios where the AI should not respond or perform an action.

You'll learn about input validation, output validation, prompt injection protection, content filtering, tool and agent permissions, response validation, and fallback strategies.

We'll implement practical guardrails in an AI application and discuss how to balance safety, reliability, user experience, and performance when building production-ready AI systems.