Large regression suites can become expensive when every response also receives an automated judgment. Some evaluations need immediate feedback, while others can wait. Separating those cases can reduce spending without pretending that asynchronous processing is a drop-in replacement for an interactive development loop.
Braintrust’s October 15 workflow-evals announcement coordinates tasks and scorers through provider batch APIs. It describes submission and collection callbacks, polling or webhook completion, and persistent progress that another process can resume. The company connects the approach to providers’ batch discounts. Those discounts apply to eligible provider requests, not necessarily to every cost in the evaluation pipeline. Read the primary source.
Dependencies still determine completion time
If judging depends on a model’s generated response, the judging batch cannot begin until that response exists. Two discounted stages can therefore extend the feedback cycle. A developer choosing batch size or a completion method should consider the evaluation’s actual deadline and recovery requirements.
The immediate opportunity is to move tolerant workloads, such as overnight regression checks, onto an asynchronous path while retaining a coherent experiment record. Acceptance testing should confirm that returned results match the right case IDs, failures remain visible and a restarted process does not silently omit or duplicate work.
Cheaper large-scale evaluation could widen routine test coverage if teams preserve these accounting guarantees. The next evidence is the full cost and time to a complete, auditable experiment, including failed batches and dependent stages. A lower per-request price helps only when the finished evaluation still supports the decision it was intended to inform.
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