You're Not Using Enough Guardrails — Here's What Actually Works

说明与用途

后生成验证层检测并纠正输入过滤器遗漏的输出错误，提升 AI 的可靠性。

问题

AI guardrails that filter only inputs miss costly output problems such as fabricated citations, hallucinated tool arguments, system prompt leakage, safety refusal bypass, and code with logic errors.

结果

The post‑generation approach catches issues that pre‑generation filters miss, reducing errors and improving trust in AI outputs.

工作流

• 1. Receive user prompt and generate model output.
• 2. Run the output through the 13‑detector verification layer.
• 3. Apply the appropriate correction strategy (e.g., remove fabricated citations, correct tool arguments).
• 4. If correction is ambiguous, flag the output for human review.
• 5. Deliver the corrected or reviewed output to the user.

证据

Most guardrail solutions (content filters, prompt injection detectors, topic classifiers) operate on the input — what the user asks.

来源

Instead of filtering before generation, I built a layer that filters after generation. It uses 13 detectors across 5 categories, with 31 correction strategies that fix issues automatically.

来源