Create unique Code with ChatGPT

Search and store tool for Chat GPT Prompt

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

Creating a Tutorial on Optimizing Code Performance Using GPT Chat

Create a tutorial on optimizing code performance using Chat GPT.

code optimization gpt chat coding tutorial performance

Act as a PHP Interpreter

I want you to act like a php interpreter. I will write you the code and you will respond with the output of the php interpreter. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. Do not type commands unless I instruct you to do so. When i need to tell you something in english, i will do so by putting text inside curly brac...

php interpreter code

Tips for Writing Clean and Self-Documenting Code for Better Code Maintenance

Share advice on how to write clean and self-documenting [language] code that is easy for others to understand and maintain.

clean code self-documenting code maintenance

Comparing and Recommending [Language] Code Formatting Tools and Linters for [Project Description]

Compare different [language] code formatting tools or linters and recommend one that best suits the given project: [project description].

code formatting linters programming

Generating Opinions on Code Snippets using Libraries and Frameworks

Provide a [language] code snippet that demonstrates the usage of a [library or framework] to build a [specific feature or functionality]: [library or framework name].

code snippet library framework

How to Visualize Code Dependencies with Call Graphs in [Language]

Visualize the call graph or dependencies of the following [language] code: [code snippet].

code dependencies call graph visualization

Identify Areas of Improvement in Your Coding Skills via Code Analysis

Identify areas of improvement in my coding skills based on the following [language] code: [code snippet].

coding skills code analysis areas of improvement

Adapting [source language] Code Snippets to [Target Language] Following Best Practices

Adapt the following [source language] code snippet to [target language] while adhering to [target language's best practices]: [code snippet].

code snippet target language best practices

Tips for Migrating Source Code to a New Language with Different Framework

Migrate the following [source language] code that uses [library or framework] to [target language] with a similar library or framework: [code snippet].

migrating source code library

Converting [Source Language] to [Target Language] while preserving structure and functionality with code [Snippet]

Convert the given [source language] class or module to [target language] while preserving its functionality and structure: [code snippet].

code conversion programming language functionality

Improving Code Modularity and Reusability through Refactoring

Refactor the given [language] code to improve its modularity and reusability: [code snippet].

code refactoring modularity reusability

Optimizing Language Code Snippet for Best Performance: Tips and Tricks

Optimize the following [language] code for better performance: [code snippet].

optimization code performance

Identifying Opportunities for Design Pattern in Code: Tips and Tricks

Identify opportunities to apply [design pattern] in the given [language] code: [code snippet].

design pattern code snippet programming

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

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

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 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

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.