Recognises a stewardship SLA the staffing cannot meet
No SLA, or arrivals exceed capacity so the backlog grows.
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 82% | Not shown |
| gemini-3.5-flash-lite | Low cost | 83% | Not shown |
| gpt-6-luna | Low cost | 82% | Not shown |
| claude-haiku-5-5 | Low cost | 83% | Not shown |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: Arrivals against capacity and the change needed
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: SQ-01 SLA 5 days; 900 arrivals/week, 3 stewards × 200/week = 600 Acceptable: Staffing, bands or SLA changed explicitly
Also known as: SLA the staffing cannot meet
Related knobits
Builds on
Usually followed by
All 13 knobits of Run the stewardship workflow and measure MDM.
Source: Review checklist 05-stewardship-metrics, row 2 (DMBOK; 25024)