Summary

The model receives the prompt (and optional system message). The run uses scorer contains_all with the JSON configuration below. Pass/fail and partial credit are determined entirely by that scorer against the model output; no human grading.

Summarize in exactly 3 short bullet points: ML operations stabilized after feature validation, drift monitoring, and shadow deployments before full rollout. Retraining jobs were versioned and reproducible.

{
  "expected_contains": [
    "drift monitoring",
    "shadow",
    "retraining"
  ]
}