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Calibrate a grader before using it as a deployment gate
A grader score is another model output until it is compared with a trusted label. Agreement alone is insufficient when one error type matters more: a grader that misses unsafe failures can look accurate on a mostly passi
Calibrate an LLM judge against human-labelled cases
An LLM judge can scale evaluation, but it is another model with biases and failure modes. Compare it against a clear rubric and human-reviewed cases before using it in a release gate.
Calibrate predicted probabilities on held-out data
A probability of 0.20 should mean something stronger than “this score ranks above another score.” Across comparable predictions near 0.20, roughly one fifth should be positive if the model is calibrated for that populati
Canary releases with a measurable rollback condition
A canary lets a candidate control a small share of real decisions while operators monitor technical and product guardrails. The rollback rule must be set before launch, including the denominator and minimum sample. Other
Cancel a long-running agent without leaving orphan work
Closing a browser tab does not necessarily stop workers, tool calls or scheduled jobs. Cancellation needs an explicit signal, cleanup and durable final state.
CASE WHEN: classify orders without overlapping buckets
A CASE expression assigns a result according to conditions. In a searched CASE, the first true WHEN condition determines the output. That makes condition order important whenever ranges overlap.
Catch denominator errors in AI-written business summaries
To verify a rate in an AI-written summary, inspect the numerator and denominator separately before checking the division. Both must refer to the intended population, grain and observation window. A mathematically correct
Categorical data: reduce memory without losing unknown values
Categorical storage can reduce memory for repeated labels, but validate the vocabulary before casting. Values outside an explicitly supplied category set can become missing, making a storage change look like a data-quali
Central limit theorem: simulate what actually converges
In the classical independent, identically distributed setting with finite nonzero variance, the central limit theorem describes the limiting distribution of the standardized sample mean. It does not say that the original
Checkpoint a workflow and resume after failure
Restarting a workflow from the beginning can repeat tool calls or external writes. A checkpoint records what completed, what failed and which step may safely resume.
Chi-square tests: check expected counts before interpreting results
Before interpreting a chi-square test of independence, verify the observational unit, the contingency-table counts and the expected frequencies under the null model. A function returning a p-value does not establish that
Choose a chart from the comparison the reader needs
Choose a chart by first naming the comparison the reader must make. Comparing category sizes, following change over time, inspecting a distribution and judging uncertainty are different tasks. The same dataset can suppor
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