Introducing Reasoning R&R™
Manufacturing doesn't trust a gage until it's been qualified — proven repeatable, proven reproducible between appraisers. We just published the same discipline applied to AI.
Three Questions, in Order
Reasoning R&R™ asks three questions, and each one is worthless without the one before it.
Reasoning: does the evaluation agree with a known correct answer, not just an opinion?
Repeatability: given the same input under the same conditions, does the system reach the same verdict again?
Reproducibility: do different appraisers applying the same method land in a comparable place? A system that gives the same wrong answer every time is highly repeatable and completely useless — which is why reasoning has to come first.
What We Found Running It on Our Own Workflow
We ran the study on our own 8D grading workflow: 2,370 individual grading decisions, 93.2% repeatability, 99% reproducibility between two reviewers. For context, unaided human inspectors in a published automotive study agreed with each other 36.67% of the time. We also found twelve criteria that were unstable run to run — every one traced back to ambiguity in our own written rubric, not the model — and one input format that was silently failing to reach the model while the system kept producing a complete, professional-looking scorecard. Normal use hadn't caught either problem. Measurement did.
Where to Get the Full Study
The full Reasoning R&R™ one-pager is live now, and it's the framework I'm bringing to the AIAG Quality Summit stage later this month.
Want to see how it holds up on your own documents? Book a demo: mad-ai.com/book-a-demo
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