AI Observability and Evaluation: Catch Silent LLM Failures

Description and use

<p>Your AI support assistant just told a customer they can get a 30-day refund. They're on the Free plan, and Free has no refunds.</p> <p>The API returned <code>200 OK</code> in 1.2 seconds. There were no exceptions, CPU was normal, and the dashboard stayed green. Nothing in your monitoring knows anything went wrong.</p> <p>Your infrastructure is healthy. Your product is wrong. This is a <strong>silent failure</strong>: the system executes the request successfully but delivers the wrong outcome.</p> <p>Traditional monitoring asks whether the service is up, fast and error-free. AI applications

Problem

<p>Your AI support assistant just told a customer they can get a 30-day refund. They're on the Free plan, and Free has no refunds.</p> <p>The API returned <code>200 OK</code> in 1.2 seconds. There were no exceptions, CPU was normal, and the dashboard stayed green. Nothing in your monitoring knows anything went wrong.</p> <p>Your infrastructure is healthy. Your product is wrong. This is a <strong>silent failure</strong>: the system executes the request successfully but delivers the wrong outcome.</p> <p>Traditional monitoring asks whether the service is up, fast and error-free. AI applications

Outcome

<p>Your AI support assistant just told a customer they can get a 30-day refund. They're on the Free plan, and Free has no refunds.</p> <p>The API returned <code>200 OK</code> in 1.2 seconds. There were no exceptions, CPU was normal, and the dashboard stayed green. Nothing in your monitoring knows anything went wrong.</p> <p>Your infrastructure is healthy. Your product is wrong. This is a <strong>silent failure</strong>: the system executes the request successfully but delivers the wrong outcome.</p> <p>Traditional monitoring asks whether the service is up, fast and error-free. AI applications

Evidence

AI Observability and Evaluation: Catch Silent LLM Failures

Source