5 Essential Prompt Engineering Tips for AI Model Mastery(Development of large model applications 6)

Five Basic Principles of Model Interaction Demonstrated with Five Different Models

Hello everyone, welcome to the "Development of Large Model Applications" column.

In the Era of Large Model Applications, Everyone Can Be a Programmer (Development of large model applications 1)

Order Management Using OpenAI Assistants' Functions(Development of large model applications 2)

Thread and Run State Analysis in OpenAI Assistants(Development of large model applications 3)

Using Code Interpreter in Assistants for Data Analysis(Development of large model applications 4)

Using the File Search (RAG) Tool in Assistants for Knowledge Retrieval(Development of large model applications 5)

In previous articles, I focused on how to use the Assistants API.

In this lesson, we'll explore a short but important topic—prompt engineering.

Prompt engineering is about carefully designing the text input (prompts) given to AI models to guide them in generating the desired output.

It's similar to giving clear instructions to your colleagues, leaders, subordinates, or friends in a conversation.

You need to provide enough background information to get a satisfactory response.

A good prompt combines human intelligence with machine capability. While it doesn't raise the AI's thinking capacity, it can bring its performance close to the maximum potential, which is crucial.

In this lesson, I'll show you five basic principles for interacting with models through five practical examples using five different models.