---
description: Learn how to use Opik Agent Optimizer with the HotPotQA dataset through
an interactive notebook, covering setup, configuration, and optimization techniques.
headline: Optimizer introduction | Opik Documentation
og:description: Learn to optimize prompts using Opik Agent on the HotPotQA dataset
with a hands-on Colab notebook for seamless experimentation.
og:site_name: Opik Documentation
og:title: End-to-End Prompt Optimization with Opik
subtitle: Quick example notebook using HotPotQA dataset
title: Optimizer Introduction Cookbook
---
This example demonstrates end-to-end prompt optimization on the HotPotQA dataset using Opik Agent Optimizer. All
steps, code, and explanations are provided in the interactive Colab notebook below.
This notebook powers the **Quickstart notebook** entry in the Agent Optimization navigation.
## Load Example Notebook
To follow this example, simply open the Colab notebook below. You can run, modify, and experiment with the workflow
directly in your browser—no local setup required.
| Platform | Launch Link |
| ---------------------------- | ----------- |
| **Google Colab (Preferred)** | [
](https://colab.research.google.com/github/comet-ml/opik/blob/main/sdks/opik_optimizer/notebooks/OpikOptimizerIntro.ipynb) |
| **GitHub** | [View the notebook on GitHub](https://github.com/comet-ml/opik/blob/main/sdks/opik_optimizer/notebooks/OpikOptimizerIntro.ipynb) |
## What you'll learn
- How to set up Opik Agent Optimizer SDK
- How to setup Opik Cloud (Comet Account) for prompt optimization
- How to use the HotPotQA dataset for multi-hop question answering
- How to define metrics and task configs
- How to run the `FewShotBayesianOptimizer` and interpret results
- How to visualize optimization runs in the Opik UI
## Quick Start
1. Click the Colab badge above to launch the notebook.
2. Follow the step-by-step instructions in the notebook.
3. For more details, see the [Opik Agent Optimizer documentation](/development/optimization-runs/overview).