Gen AI Leader Techniques to improve gen AI model output MEDIUM
PRODUCTION SCENARIO
A marketing team must choose between two Gemini versions for writing product blurbs. One version leads the published benchmarks; the team has 200 of its own briefs and a house style guide.

How should the team decide?

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Answer: Score both models on the team's own briefs against the house style guide

Google's Gen AI evaluation service exists to show how a model performs on your specific tasks and your own criteria, which is insight public leaderboards and general benchmarks cannot give; running both models head to head on the team's own briefs is the recommended way to choose. Benchmark rank measures somebody else's tasks, a newer release is not automatically better here, and ten blurbs is too small a sample.
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