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.

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

How to make an API Call using [language] and [API endpoint], Step-by-Step Guide

Complete the [language] code to make an API call to [API endpoint] with [parameters] and process the response: [code snippet].

api [language] code snippet

How to Initialize a Data Structure with Values in [Language]: A Code Snippet

In [language], complete the following code snippet that initializes a [data structure] with [values]: [code snippet].

code snippet data structure programming

Implementing [Design Pattern] in [Language] for [Use Case]: A Code Snippet

Based on the [design pattern], create a code snippet in [language] that demonstrates its implementation for a [use case].

design pattern code snippet implementation

How to Generate Boilerplate Code for a Class/Module/Component with Specific Functionality

Generate a boilerplate [language] code for a [class/module/component] named [name] with the following functionality: [functionality description].

boilerplate code class/component functionality description

Strategies for Conducting Thorough Code Reviews and Quality Assurance Testing

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Generate [number] strategies for conducting thorough code reviews and quality assurance testing for our agency's digital products to ensure optimal performance and minimize errors. Context: Target audience — [your target audience here] Current code review and QA process — [describe current code review and QA process here] Desired code review and QA outcomes — [your desired outcomes her...

code reviews quality assurance digital products

Get Python Code Execution Output with ChatGPT

{enter python code} to execute this and give only output .

python code execution output

Generating an Opinion About Code Output Based on Input Request for ChatGPT

What will be the following code output {Enter the code}

code output programming data analysis

How ChatGPT can help with documentation writing for code?

write the documentation for a piece of code {Enter code}

documentation code writing chatgpt

How ChatGPT can simplify code with ease for users

Simplify this complex code {Enter code}

simplify code code optimization programming techniques

Analyzing Content to Generate an Opinion

Find the bug with this code: <post code below>

opinion content code bug

Generating an opinion about JavaScript code

Please continue writing this code for JavaScript <post code below>

javascript code opinion programming

Tutorial: How to Generate Code Snippets Using Chat GPT

Write a tutorial on how to generate code snippets using Chat GPT.

code snippets chat gpt programming code generation tutorial

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.