Your agent's test gate runs the tests in the tree the agent just edited

AI coding agents face critical vulnerabilities in test gates, where evasions like assertion dilution and exit-code hijacking allow bugs to pass. Testing shows that gates failing to prevent test modification are ineffective. Simultaneously, n8n AI agents often fail in production despite passing in editors. Common issues include LLMs returning prose instead of JSON and silent API failures. Solutions involve requiring strict JSON output, implementing explicit schemas, and adding fallback branches to ensure stability under real traffic.