> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.latitude.so/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Explore practical examples, advanced LLM techniques, and real-world use cases to build powerful AI applications with Latitude

In this section of Latitude's documentation you will find 3 kind of materials.

1. **SDK Examples**: These examples demonstrate how to use the Latitude SDK to build AI applications, including running prompts, integrating tools, and managing conversation context.
2. **Prompting Techniques**: This section covers advanced prompting techniques that can enhance the quality and capabilities of your LLM applications, such as reasoning methods, memory management, and input/output strategies.
3. **Real-world Cases**: These examples showcase complete solutions for common business and technical challenges, demonstrating how to combine various techniques into production-ready applications.

## SDK Examples

<AccordionGroup>
  <Accordion title="Popular SDK Examples">
    * [Run Prompt](/examples/sdk/run-prompt) - Execute prompts with dynamic parameters
    * [Run with Tools](/examples/sdk/run-prompt-with-tools) - Integrate external tools with your prompts
    * [Render Chain](/examples/sdk/render-chain) - Connect multiple prompts in sequence
    * [RAG Retrieval](/examples/sdk/rag-retrieval) - Implement retrieval-augmented generation
  </Accordion>
</AccordionGroup>

## Prompting Techniques

These the main techniques for advanced prompting that can significantly improve the performance and reliability of your LLM applications. Each technique is designed to address specific challenges in AI interactions, from enhancing reasoning capabilities to managing context and improving output quality.

<Columns cols={2}>
  <Card title="Few-Shot Prompting" href="/examples/techniques/few-shot-prompting">
    Learn how to implement few-shot learning with examples to improve AI performance on specific tasks
  </Card>

  <Card title="Role Prompting" href="/examples/techniques/role-prompting">
    Enhance AI performance by assigning specific roles, personas, and expertise areas
  </Card>

  <Card title="CoT (Chain of Thought) Prompting" href="/examples/techniques/chain-of-thought">
    Improve reasoning and problem-solving capabilities with structured thought processes
  </Card>

  <Card title="ToT (Tree of Thought) Prompting" href="/examples/techniques/tree-of-thoughts">
    Enable complex reasoning by breaking down problems into manageable sub-tasks
  </Card>

  <Card title="Contextual prompting" href="/examples/techniques/contextual-prompting">
    Manage conversation context effectively to maintain coherence and relevance
  </Card>

  <Card title="Self-Consistency" href="/examples/techniques/self-consistency">
    Enhance output reliability by generating multiple responses and selecting the best one
  </Card>

  <Card title="Step back prompting" href="/examples/techniques/step-back-prompting">
    Improve output quality by iteratively refining responses through feedback loops
  </Card>

  <Card title="ReAct (reason & act)" href="/examples/techniques/re-act-prompting">
    Combine reasoning and action to enhance decision-making capabilities
  </Card>
</Columns>

<Note>
  Advanced prompting techniques can dramatically improve the quality, reliability, and capabilities of your LLM applications. These examples demonstrate proven approaches to enhance your AI systems.
</Note>

## Real-world Cases

Our case examples showcase complete solutions for common business and technical challenges, demonstrating how to combine various techniques into production-ready applications.

Explore real-world implementations that you can adapt to your specific needs:

<Card title="Customer Support Email Generator" href="/examples/cases/customer-support-email" arrow={true}>
  Create personalized, empathetic customer service emails with multi-agent architecture
</Card>

<Card title="Content Moderation System" href="/examples/cases/content-moderation-system" arrow={true}>
  Implement robust content filtering and moderation with constitutional AI principles
</Card>

<Card title="Deep Search" href="/examples/cases/deep-search" arrow={true}>
  Build an advanced information retrieval system with multi-stage processing
</Card>

<Card title="Stock Market Analysis" href="/examples/cases/stock-market-analysis" arrow={true}>
  Analyze financial data and generate insights using specialized agents
</Card>

<Callout type="default">
  Need help choosing the right example? Check out our [Getting Started Guide](/guides/getting-started/overview) or [contact support](https://latitude.so/contact) for personalized recommendations.
</Callout>