Developer Builds AI Guardrail System to Block Unsafe or Off-Topic LLM Responses

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A developer has published an open-source didactic project demonstrating how guardrails can be applied to generative AI systems to prevent unsafe content, hallucinations, and information leakage. The application allows users to submit a prompt along with optional sensitive topics, which are then used to evaluate whether the AI's response should be blocked. Built on a stack of C#/.NET 10, React 19 with TypeScript, SQLite, and Google's Gemini Flash Lite model, the system uses the LLM itself as a judge in a second API call — a pattern known as LLM-as-judge. If the response touches on any flagged topic, the content is replaced with a 'not permitted' message, and all queries are logged for audit purposes. The developer notes that real-world deployments should use separate models for content generation and judgment to reduce the risk of false negatives.

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