Recognises freshness promised before the batch ends
Data promised before the batch that produces it ends.
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 | 75% | Not shown |
| gemini-3.5-flash-lite | Low cost | 77% | Not shown |
| gpt-6-luna | Low cost | 74% | Not shown |
| claude-haiku-5-5 | Low cost | 74% | 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: The defect named on the freshness deadline before the producing batch ends, and its fix or the question for its owner
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: SL-004 regulatory data by 06:00; OL-005 batch ends 06:30 Acceptable: Deadline 07:00, or the batch moved earlier
Also known as: Freshness tighter than the batch
Related knobits
Builds on
All 13 knobits of Define SLAs and OLAs.
Source: Review checklist 06-slas-olas, row 5 (DMBOK; ITIL)