[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-spot-check::en":3,"gloss-cluster-spot-check::en":23,"gloss-next-spot-check::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"spot-check","mlops","Spot Check","A spot check is a small, regular, manual read of real outputs, done as a control on the automated measurement rather than as a substitute for it. Somebody sits down, takes a handful of cases, and looks at what the system actually produced. It sounds too simple to be a practice, and it catches a category of problem that no aggregate can, because every automated number is computed by machinery that can itself be quietly broken. Scoring can silently pass everything after a change to the grader. A parsing step can drop the part of the output that mattered and score what remains. A pipeline can be evaluating a stale version. Outputs can degrade in a way the rubric does not ask about — a tone that is now brusque, a format that has drifted, a habit of answering a narrower question than the one asked. Each of these produces a healthy dashboard. Doing it well is mostly about what gets sampled. Include successes, not only failures, since the point is to verify the grader as much as the system, and a grader that is wrong is usually wrong about things it marked correct. Take the sample without choosing it. Look at the raw output rather than a rendered summary of it, because the rendering is often where information is lost. And keep it short and frequent rather than long and occasional; a handful of cases every week beats a large review every quarter, because the value is in noticing a change soon after it starts. Write down what was checked and what was seen, even when nothing was wrong. The record is what makes it possible, later, to say when a behaviour started rather than only that it exists. It is also the practice most likely to be dropped when a team is busy, and the first sign that it has been dropped is usually an incident that the dashboard had been reporting as fine for several weeks. Putting it on a named person and a fixed day survives pressure better than putting it on the team.","A spot check is a small regular manual read of real outputs. Why it catches broken graders and drifted behaviour that aggregate scores never show.",null,[11,14,17,20],{"slug":12,"name":13},"eval-harness","Eval Harness",{"slug":15,"name":16},"llm-as-judge","LLM-as-Judge",{"slug":18,"name":19},"offline-evaluation","Offline Evaluation",{"slug":21,"name":22},"silent-failure","Silent Failure",[24,28,31,35,38,41,44,47,50,53,56,59],{"slug":25,"category":5,"name":26,"updated_at":27},"acceptance-threshold","Acceptance Threshold","2026-09-10T03:30:02+00:00",{"slug":29,"category":5,"name":30,"updated_at":27},"adjudication","Adjudication",{"slug":32,"category":5,"name":33,"updated_at":34},"annotation-guidelines","Annotation Guidelines","2026-09-08T21:32:36+00:00",{"slug":36,"category":5,"name":37,"updated_at":34},"baseline-model","Baseline Model",{"slug":39,"category":5,"name":40,"updated_at":34},"batch-inference","Batch Inference",{"slug":42,"category":5,"name":43,"updated_at":27},"blind-evaluation","Blind Evaluation",{"slug":45,"category":5,"name":46,"updated_at":34},"canary-prompt","Canary Prompt",{"slug":48,"category":5,"name":49,"updated_at":27},"ceiling-effect","Ceiling Effect",{"slug":51,"category":5,"name":52,"updated_at":34},"champion-challenger","Champion-Challenger (A\u002FB Model Testing)",{"slug":54,"category":5,"name":55,"updated_at":34},"class-imbalance","Class Imbalance",{"slug":57,"category":5,"name":58,"updated_at":34},"continuous-batching","Continuous Batching",{"slug":60,"category":5,"name":61,"updated_at":27},"coverage-gap","Coverage Gap"]