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

# Overview

Prompt engineering is the art and science of crafting effective instructions for AI models, particularly Large Language Models (LLMs). A well-designed prompt can significantly enhance the quality, relevance, and safety of AI-generated responses. This guide will walk you through the key concepts and best practices in prompt engineering.

#

{/* > Screenshot of the prompt input field in glowstudio:  


<img class="rounded-md" src="https://i.imgur.com/b8Z7gNS.jpeg  




" width="700"></img>     */}

<Info>Rememeber to always include the variables `{kb_context}` and `{about_context}` in your prompt or else the agent wont know the retrieved chunks from the RAG.</Info>

### Key Concepts

#

<Accordion title="Chain of Thought (CoT) Reasoning">
  Chain of Thought (CoT) reasoning is a technique that involves breaking down complex problems into a series of intermediate steps. This approach helps the AI model to:

  1. Understand the problem more thoroughly

  2. Show its reasoning process

  3. Arrive at more accurate conclusions

  **Example:**

  ```

  Human: What's the result of 25 * 18?   


  AI: Let's approach this step-by-step:   

   
  1. First, let's break down 25 * 18 into (20 + 5) * 18   


  2. Now we can calculate:   


     a) 20 * 18 = 360   


     b) 5 * 18 = 90   


  3. Adding these results:   


     360 + 90 = 450   


  Therefore, 25 * 18 = 450   


  ```
</Accordion>

<Accordion title="Few-Shot Learning">
  Few-shot learning is a technique where you provide the AI with a small number of examples to guide its understanding of the task. This can be particularly useful when you want the AI to follow a specific format or style in its responses.

  * One-shot learning: Providing one example

  * Two-shot learning: Providing two examples

  * Few-shot learning: Providing a few (typically 3-5) examples

  **Example:**

  ```


  Human: Translate the following English phrases to French. Here are two examples:   

   


  English: Hello, how are you?   

  French: Bonjour, comment allez-vous ?   

   

  English: Where is the nearest restaurant?   

  French: Où est le restaurant le plus proche ?   



  Now, translate this:   

   
  English: I would like to book a hotel room.   




  AI: Based on the examples provided, here's the translation:   



   
  English: I would like to book a hotel room.   

  French: Je voudrais réserver une chambre d'hôtel.   

  ```
</Accordion>