Your AI Agents Are Failing Silently — Here's How to Catch It

Last month I ran hundreds of LangChain agent calls in production. Some of them silently failed by using wrong tool sequences, latency spikes, or even hallucinated outputs. My logs showed zero errors. No exceptions. No warnings.

The agent just did the wrong thing, quietly.

Traditional monitoring tools weren't built for this. Datadog can tell you a function threw an exception. It can't tell you your agent called delete_file when it's never done that before, or that your LLM is suddenly generating 10x more tokens than usual, or that output quality has been slowly degrading over the last 500 runs.

So I built Drift.

What Drift Does