Makes complex technology environments operable before and after launch.

{
  "id": "ai-llm-hallucination-spike",
  "primaryDomain": "ai-platform",
  "symptoms": [
    "Answers contain unsupported facts",
    "Citation accuracy dropped after a change"
  ],
  "entryStepId": "scope",
  "evidenceGates": [
    {
      "id": "scope",
      "layer": "scope",
      "question": "For llm hallucination rate increase, is the impact isolated to one request, component, node, service pool, region, or shared platform boundary?"
    },
    {
      "id": "evidence",
      "layer": "workload",
      "question": "Which evidence first separates prompt, retrieval, model behavior, or evaluation coverage for the hallucination spike condition?"
    },
    {
      "id": "compare",
      "layer": "workload",
      "question": "When the affected boundary is compared with a healthy peer, which hallucination spike signal diverges first and what changed immediately before it?"
    }
  ],
  "faultBoundaries": [
    "prompt, retrieval, model behavior, or evaluation coverage",
    "shared dependency or control plane"
  ],
  "ownerRoute": [
    "technical account lead / incident commander",
    "AI quality owner / model reliability lead"
  ],
  "safety": "Do not tune prompts, change models, or relax grounding controls in production until the regression is reproduced and measured.",
  "guidedAction": "Follow the selected approved resolution path.",
  "validation": [
    "reported signal clears",
    "healthy and affected behavior converge",
    "dependent transaction or workload succeeds",
    "monitoring remains stable through the observation window"
  ]
}