# Iterating on the Prompt ### Update the Prompt Navigate to templates and press the "..." next to our existing template. Choose "Make a copy."

Open the copy at the top of the templates list. Then press the "..." by the title and choose Rename.

Name it "Prompt v2".

Next, edit the `system` prompt and replace it with this: {% code overflow="wrap" %} ``` You are a professional email marketer. Review the following article and write a creative email subject line idea for it that is likely to grab attention. Do not return anything except the subject line. Do not include quotes around the email subject. ``` {% endcode %} Your template should look like this:

Press "Save." ### Try the New Template with a Model Go back to our Models list and choose to apply a template to a model again. This time, select our Prompt v2 template from the dropdown.

Use the same model again (GPT-4 Omni) so we know the only thing that changed was our prompt. Open the new templated model, wait for the evaluation to finish, and check the results. It looks like the change to our prompt worked and the email subject line is no longer wrapped in double quotation marks. Let's rate them all 4 or 5 stars.

### Compare Models Back on our models list, we can now compare the score for these two models.

We can also rename them to v1 and v2 to make our table easier to read.

With more validation examples, and by reviewing and rating the outputs from your templated models, you can get a clear picture of which model/template combinations are performing best. ### Where to Go From Here Next, we would need to expand our validation dataset and try the prompt on other models (including models from other [model providers](/key-concepts/model-providers.md)) to see which give us the best outputs, at the right price and speed for our project. In the next guide, we'll learn how to build and grow a dataset. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.entrypointai.com/guides/evaluate-a-prompt/iterating-on-the-prompt.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.