How Evals and Scorers Work in a Cloud Software Factory

Evals and scorers provide a measurement layer for cloud software factories, assessing coding-agent runs for cost, code quality, defects, and customizable criteria such as API compliance or test coverage. Unlike workflow metrics that only show whether work progressed through a pipeline, these tools establish whether agent output is improving, declining, or varying across task types and configurations. Observer agents can use evaluation patterns to recommend configuration changes, creating a feedback loop in which scored results inform updates to models, harnesses, or context settings. Fixed-task benchmarks complement ongoing production evals by enabling direct comparisons among specific models or configurations while controlling for factors such as cost. The text cautions against delaying measurement until failures occur or optimizing solely for token spend, and presents Warp Factories as a platform with integrated metrics, built-in and custom scorers, multi-model benchmarking, and reported automation of 20–30% of its engineering pull requests.

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