Boost accuracy with the prompt optimizer

As of August 2026, Vertex AI has been renamed Agent Platform, and its Prompt Optimizer is presented as a data-driven tool for refining repeatable AI tasks by using examples of known inputs and ground-truth outputs to iteratively improve prompt instructions and evaluate results. The Firebase team tested it for generating YouTube video descriptions from scripts, assembling historical scripts and human-written descriptions in a CSV file stored in Google Cloud Storage, then using a Colab Enterprise notebook to optimize an initial system prompt. With Gemini 2.5 Flash, instruction-and-demo optimization, and evaluation metrics, the service ran a custom training job that compared prompt variations against an original baseline; processing 45 examples took about four hours and consumed millions of tokens. The optimized prompt added detailed constraints for summaries, timestamps, resources, speakers, featured products, and hashtags, producing descriptions that were more consistent with human-authored examples and less variable than the original outputs. Although the process cost several hundred dollars, the example concludes that its improved consistency and reduced need for human review justified the expense for this workflow, while noting that users should weigh optimization costs against expected benefits.

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