Prompt A/B testing

A/B test LLM prompts with production evidence

Currai lets teams compare prompt versions on real traffic, then decide based on quality scores, latency, tokens, cost, and trace-level examples.

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Primary keyword

prompt A/B testing

Currai covers

Traces, generations, spans, evals, prompt A/B tests, token usage, cost, latency, sessions, users, and OpenTelemetry ingestion.

Measure prompt changes before they become product changes

A prompt edit can improve one task while making another worse. Currai records which version served each request and keeps the resulting trace available for review.

Use prompt A/B tests to compare outputs across versions and understand the tradeoff between response quality, speed, and cost.

Split production traffic across prompt versions.
Compare eval scores, cost, latency, and user/session behavior.
Inspect winning and losing examples with full trace context.

Ship prompt changes with confidence

Currai gives teams a measurable path from prompt idea to production rollout: create a version, run an experiment, score outputs, inspect traces, and promote the version that performs best.

Questions about prompt A/B testing

What should a prompt A/B test measure?

Measure task quality, hallucination or policy failures, user feedback, token usage, cost, latency, and any product-specific success criteria.

Can prompt tests use production traffic?

Yes. Currai is built around production traces, so prompt tests can be connected to the requests users actually make.

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