Create unique Programming with ChatGPT

Search and store tool for Chat GPT Prompt

Create unique and engaging Programming with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.

Effective Indexing Techniques for Optimizing SQL Queries

Suggest indexing strategies for the following SQL query: [SQL query].

indexing sql optimization

Analyzing SQL Query for Potential Bottlenecks: A Guide to Optimize Database Performance

Analyze the given SQL query for any potential bottlenecks: [SQL query].

sql query database performance bottlenecks

Optimizing SQL Query for Better Performance: Tips and Techniques

Optimize the following SQL query for better performance: [SQL query].

sql performance optimization

How to Create a Quick-Start Guide for [Language] Library with Code Snippet for Easy Setup

Produce a quick-start guide for using the following [language] library: [code snippet].

programming library setup

Opinion Generator Function for Language Code Snippets: Expected Input and Output

Document the expected input and output for the given [language] function: [code snippet].

opinion code snippet language

Tips for Generating Usage Examples for [Language] API: [Code Snippet]

Generate usage examples for the following [language] API: [code snippet].

api programming language

How to Create a Concise API Reference for a Programming Language Class

Create a concise API reference for the given [language] class: [code snippet].

api programming language reference

Keyword Extraction: Extracting Meaningful Words from Text Sample

Perform keyword extraction on the following text: [text sample].

keyword extraction text analysis data mining

How to Extract Named Entities from Text Sample: Step by Step Guide

Extract named entities from the following text: [text sample].

text analysis named entity recognition data extraction

Assessing [Language] Code Performance and Providing Optimization Suggestions

Assess the performance of the following [language] code and provide optimization suggestions: [code snippet].

code optimization language performance

Evaluating Code Modularity and Maintainability: A [Language] Code Snippet Analysis

Evaluate the modularity and maintainability of the given [language] code: [code snippet].

code modularity maintenance

Improving Error Handling in Language Code: Suggestions and Enhancements

Check the following [language] code for proper error handling and suggest enhancements: [code snippet].

error handling language code enhancements

Analyzing Coding Style for [Language]: [Code Snippet], Tips and Techniques

Analyze the given [language] code for adherence to [coding style guidelines]: [code snippet].

coding style language techniques

Reviewing and Suggesting Improvements for Language Code Snippet: Best Practices

Review the following [language] code for best practices and suggest improvements: [code snippet].

code snippet best practices programming

Reviewing Language Code for Security Vulnerabilities

Review the following [language] code for any security vulnerabilities: [code snippet].

security code vulnerabilities

How to Check for Race Conditions and Concurrency Issues in [Language] Code: A Guide

Check for any race conditions or concurrency issues in the given [language] code: [code snippet].

race conditions concurrency issues programming

How to Find and Fix Memory Leaks in [Language] Code

Find any memory leaks in the following [language] code and suggest fixes: [code snippet].

memory leaks debugging code fixes

How to Prevent Errors in Code: Analyzing and Improving [Language] Snippets

Analyze the given [language] code and suggest improvements to prevent [error type]: [code snippet].

error prevention code analysis programming

Identifying Potential Bugs in [Language] Code Snippet: Tips and Techniques

Identify any potential bugs in the following [language] code snippet: [code snippet].

potential bugs code snippet programming

Tips for Writing an Effective Code Loop in [Language] with [Data Structure] and [Operation]

Complete the following [language] loop that iterates over [data structure] and performs [operation]: [code snippet].

programming data structure code loop

What is “prompt engineering”?

A “prompt” is the input that guides a generative AI model to generate useful outputs. Generative AI tools like ChatGPT, GPT, DALL·E 2, Stable Diffusion, Midjourney, etc. all require prompting as their input.

In a natural language processing (NLP) context, “prompt engineering” is the process of discovering inputs that yield desirable or useful results. As is the story with any processes, better inputs yield better outputs; or commonly said another way “garbage in, garbage out.”

![Source: https://www.youtube.com/watch?v=1NQWJjgi-_k

Designing effective and efficient prompts will increase the likelihood of receiving a response that is both favorable and contextual. With a good prompt, you can spend less time editing content and more time generating it.

Going from beginner → advanced prompt engineer

As companies like PromptBase arise around the idea that the prompt is the “secret sauce” to using generative AI, prompt engineering could easily become the “career of the future.” But, any generative AI user can become an “advanced” prompt engineer. Here’s how

Spend time with the tools

The more time you spend asking ChatGPT questions and receiving responses, the better your idea will be of various prompting approaches and their individual strengths and weaknesses
Use Open AI’s GPT playground to perform interactive trial and error with variations in your prompt, model, temperature and top_p values (uniqueness of answer, i.e. creativity), and more available within the UI itself.

Become a prompt researcher instead of engineer

If you’re already a subject matter expert in something, consider figuring out how to apply your personal skills to generating the best prompts in your field
For example, if you’re an expert in SEO, what questions do you ask yourself when creating SEO strategies? How can you translate this knowledge into better prompts to generate the same level of output with AI?

Become a prompt researcher instead of engineer

The term prompt engineer glosses over the idea that prompt formulation takes hypothesizing, research, result measurement, and repetition. Instead, approach prompting like a research project.
Try as many different variations and formulations of your prompt as possible. One problem can have hundreds of solutions and one solution can have hundreds of approaches. The same can be said of prompting.