# Prompt Optimization Experiments

**Karini AI's** Automatic Prompt Optimization (APO) feature allows users to optimize prompts for any task and dataset without writing code. Using techniques like gradient descent and beam search, APO refines vague or underperforming prompts to make them more precise and task-specific. APO automatically explores different prompt variations, evaluates their performance across multiple models, and selects the best-performing option. This process improves efficiency and ensures more effective outcomes.

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# 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://karini-ai.gitbook.io/karini-ai-documentation/prompt-optimization-experiments.md?ask=<question>
```

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.