Efficient Benchmarking in Production

Empirical study of cheap, recurring evaluation for an evolving production analytics agent, comparing sampling, caching, fixed representative subsets and adaptive testing across 574 historical production benchmark runs.

Workflow level n/a Source Preprint (not peer-reviewed) Outcome Author-reported

Evidence & verification

Source level

Preprint (not peer-reviewed)
Grounded in a preprint that had not completed peer review at the time the source was checked.

Outcome verification

Author-reported
Outcomes are reported by the team that built the system. The entry is source-checked against the team's own publications; not independently reproduced.

Sources checked

2026-10-17 (UTC)

Primary-source metadata/abstract review only (arXiv, live 2026-10-17). Deployment and fidelity gains are author-reported, not independently reproduced.

Source-checked does not mean independently reproduced. See the Method page for how these labels are assigned.

Sources (1)

Research applicability

Getting started

Read the arXiv preprint (2609.21267) for the study design and reported results.

Maintenance

Maintenance status not independently audited.

License

Not independently audited.

Workflow & human oversight

Resource-level classification is intentionally unspecified; instantiated workflows may differ. Humans set objectives, supply data and check outputs.

Workflow level is not an evidence score; higher is not better evidence.

Approach

Analyses 574 historical production benchmark runs from a deployed analytics agent and compares candidate low-cost evaluation strategies, including random sampling, historical caching, fixed representative subsets and adaptive testing.

Limitations

Author-reported production study; the reported fidelity and cost figures were not independently reproduced. Preprint record only; no venue or artefact release confirmed in checked sources.

Reproducibility

Live source checks 2026-10-17: arXiv metadata and abstract page. No software, data or claimed outcome reproduced.

Adoption requirements

Research paper; no code, data or service release confirmed in checked sources. Reuse would require comparable production evaluation logs.

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