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Dev.to
5/12/2026
AI agent audit finds most

AI agent audit finds most

Original: I Audited My AI Agents and Found That Most of Their Reasoning Wasn’t Observable

Short summary

Author audited personal AI agent platform and discovered only 13–17% of high-volume agent decisions were captured in Langfuse traces. Root cause: agents running with LANGFUSE_ENABLED=false environment variable by default. Includes runnable SQL audit schema and TypeScript gating code pattern to identify observability gaps in your own agent systems.

  • •High-volume agents (ARIA 31K decisions) showed 17% Langfuse coverage vs 100% for low-volume agents
  • •Gap traced to LANGFUSE_ENABLED env var defaulting to false, routing LLM calls through no-op path
  • •Provides SQL audit query and code pattern to detect similar observability blind spots

Generated with AI, which can make mistakes.

#ai-agents#ai-tools
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