measurement

Define what the timer includes, give both implementations the same conditions, and keep the sample distribution. A useful benchmark explains the workload and comparison well enough for someone else to reproduce them.

Define a reproducible workload and service contract, account for every offered request, and choose a measured operating region with evidence and margin.

A repeated-prompt test measures one reuse pattern. Production gains depend on token-weighted reuse, routing, residency, alignment and the prefill share of latency; a falling hit rate does not uniquely identify eviction.

Promise measurable job outcomes: time to useful work, recoverable progress and successful restoration. Define the population and exclusions before choosing targets, and give each error budget an agreed operating policy.

Define which work survived, count the resources it occupied, and explain the remaining time without counting the same delay twice.

Write and verify tiled NumPy matmul, derive its logical footprint and distinguish a cache model from the causes of measured runtime.

Connect a performance change to its measured mechanism. Compare fair baselines and calculate how a local speedup affects the whole workload.

Show a cost reduction with comparable service evidence, realized savings and a feasible recovery plan. Distinguish a quiet trial from proof of unchanged reliability.

Connect a researcher tool to the workflow it improved. Measure the whole loop, meaningful adoption and effects on other users.