{
  "id": 3427542,
  "title": "Spotting Invisible LLM Agent Bugs with Agnost AI",
  "url": "https://urgent.news/2026/08/26/spotting-invisible-llm-agent-bugs-with-agnost-ai",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-26T04:39:01.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/leojulieta/spotting-invisible-llm-agent-bugs-with-agnost-ai-4jea"
  },
  "original_language": "en",
  "account": "Unit and integration tests fail to detect errors that emerge in long-running LLM-powered agents. These include state mutations, hidden side effects with external APIs, and gradual performance degradation. Agnost AI monitors the runtime state of LLM-driven agents in production, detecting “invisible” errors before they impact revenue, compliance, or brand trust. By tracking agent state, tool calls, latency, and token usage, Agnost AI identifies issues that arise over weeks of interaction, unlike traditional testing methods.",
  "summary": "Detecting Invisible Errors in LLM‑Powered Agents with Agnost AI Your practical guide to monitoring, debugging, and automating remediation in production pipelines Introduction When your autonomous assistant starts hallucinating policies, leaking private data, or silently degrading performance, the problem rarely shows up in unit tests. Agnost AI fills that blind spot by continuously watching the…",
  "key_points": [
    "Agnost AI detects invisible LLM agent errors in production",
    "Monitors runtime state, tool calls, latency, token usage",
    "Identifies issues over weeks, unlike traditional testing"
  ],
  "editors_take": "Agnost AI's monitoring approach fills a critical gap in traditional testing methods, allowing for the detection of errors that emerge over time in long-running LLM-powered agents.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}