# Introduction Farsight AI utilizes the leading approach for prompt optimization by incorporating the[ Prometheus prompt evaluation rubric](https://arxiv.org/abs/2310.08491) to evaluate systems prompts and LLM prompt optimization using [ORDO](https://arxiv.org/abs/2309.03409). We automate the entire prompt generation and evaluation process. The system only requires shadow input traffic from your intended use case. Our prompt optimization process works by automating each of the following steps: 1. Generation of your use case description, an evaluation rubric, an example response based on the given shadow traffic. 2. Iterative generation of system prompts, improving each iteration by providing previous system prompts and scores. 3. Finally, we select the few best system prompts for your convenience. --- # 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://api.farsight-ai.com/sdk/fully-automated-prompt-optimization/introduction.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.