How to compare two prompt versions fairly so you improve quality without guesswork.

A/B Testing Prompts: A Plain Guide

A/B testing means showing two variants (A and B) to comparable users or queries to see which performs better. In prompts, it helps you move from opinion debates to evidence.

When To Use It

You have two reasonable prompt wordings and can't tell which is better.
A new system prompt might improve tone, safety, or accuracy.
You changed retrieval or tool-calling instructions and want to quantify impact.

How To Run A Minimal Test

1. Define success: Pick one or two metrics up front (e.g., user rating ≥ 4/5, task completion, citation coverage).

2. Split fairly: Randomly assign traffic 50/50 between A and B.

3. Log traces: Store prompt, context, outputs, and metrics with a test and variant label.

4. Run long enough: Collect enough samples to see a clear winner (dozens to hundreds, depending on variance).

5. Decide & ship: Promote the winner, archive results, and version your prompts.

Useful Metrics

**Quality**: Human ratings, rubric scores, groundedness/citation coverage.
**Conversion**: Clicks, form submissions, successful completions.
**Cost & Latency**: Tokens, model/runtime, p95 latency.

Pitfalls

**Shifting traffic**: Seasonality or user mix changes can bias results—keep tests short.
**Peeking**: Avoid stopping early on noisy upticks.
**Multiple changes**: Test one variable at a time (prompt wording, not wording + model).

Tip: Start simple. Even a lightweight 50/50 split with clear logging beats intuition-only changes.