---
title: Best Practices
sidebar_position: 3
description: Comprehensive set of best practices.
keywords:
  [
    Jan AI,
    Jan,
    ChatGPT alternative,
    local AI,
    private AI,
    conversational AI,
    no-subscription fee,
    large language model,
    acknowledgements,
    third-party libraries,
  ]
---

Jan is a versatile platform offering solutions for integrating AI locally across various platforms. This guide outlines best practices for developers, analysts, and AI enthusiasts to enhance their experience with Jan when adding AI locally to their computers. Implementing these practices will optimize the performance of AI models.

## Follow the Quickstart Guide
The [quickstart guide](quickstart.mdx) is designed to facilitate a quick setup process. It provides a clear instruction and simple steps to get you up and running with Jan.ai quickly. Even, if you are inexperienced in AI, the quickstart can offer valuable insights and tips to help you get started quickly.

## Setting up the Right Models
Jan offers a range of pre-configured AI models that are tailored to different tasks and industries. You should identify which on that aligns with your objectives. There are factors to be considered:
- Capabilities
- Accuracy
- Processing Speed

:::note
- Some of these factors also depend on your hardware, please see Hardware Requirement.
- Choosing the right model is important to achieve the best performance.
:::

## Setting up Jan
Ensure that you familiarize yourself with the Jan application. Jan offers advanced settings that you can adjust. These settings may influence how your AI behaves locally. Please see the [Advanced Settings](./advanced-settings/advanced-settings.mdx) article for a complete list of Jan's configurations and instructions on how to configure them.

## Integrations
One of Jan's key features is its ability to integrate with many systems. Whether you are incorporating Jan.ai with any open-source LLM provider or other tools, it is important to understand the integration capabilities and limitations.

## Mastering the Prompt Engineering
Prompt engineering is an important aspect when dealing with AI models to generate the desired outputs. Mastering this skill can significantly enhance the performance and the responses of the AI. Below are some tips that you can do for prompt engineering:
- Ask the model to adopt a persona
- Be specific and details get a more specific answers
- Provide examples or preference text or context at the beginning
- Use a clear and concise language
- Use certain keywords and phrases
