Create unique age with ChatGPT
Search and store tool for Chat GPT Prompt
Create unique and engaging age with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.
Creating an Effective FAQ Section for Your [Language] Project or Tool: Tips and Best Practices
Develop a FAQ section that addresses common questions and issues related to the given [language] project or tool.
Identifying Open-Source Language Projects for Developers
Identify suitable open-source [language] projects for a developer with [specific skills or interests].
Tips for Organizing & Facilitating Effective Remote Meetings for Language Development Teams
Share tips for organizing and facilitating effective remote meetings for a [language] development team.
Effective Ways to Keep Remote Language Developers Motivated and Engaged During Long-Term Projects
Suggest ways to maintain team morale and motivation among remote [language] developers during a long-term project.
Effective Workflow for Task Management in Remote Language Development Team
Recommend a workflow for managing and prioritizing tasks for a remote [language] development team.
Best Tools and Practices for [Language] Development Team Remote Collaboration
Suggest tools and best practices for remote collaboration among the members of a [language] development team.
Designing a CI/CD Pipeline for Language Project Based on Requirements and Constraints
Design a CI/CD pipeline for the given [language] project based on its requirements and constraints: [project description].
Opinion on Implementing Design Pattern in Language for Different Scenarios
Provide examples of implementing the [design pattern] in [language] for the following scenarios: [scenario list].
How to Choose a Suitable Programming Language for a Project: Tips and Recommendations
Based on the given project requirements, recommend a suitable [programming language, framework, or technology]: [requirements description].
How to Implement A Specific Feature Using A Programming Language: Tutorial
Write a tutorial on how to implement [specific feature or functionality] using [programming language or technology].
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].
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].
How to Write a Test Suite for Language API: A Guide to Verify Functionality and Performance
Write a test suite for a [language] API that verifies its functionality and performance under different conditions.
Creating a Test Script for Unit, Integration, and System Testing in [Language]
Create a test script for the given [language] code that covers [unit/integration/system] testing: [code snippet].
Creating a Natural Language Interface for Chatbots to Perform Specific Tasks
Create a natural language interface for a chatbot that allows users to perform [specific task or operation] using voice commands or text input.
Opinion Generator Function for Language Code Snippets: Expected Input and Output
Document the expected input and output for the given [language] function: [code snippet].
Tips for Generating Usage Examples for [Language] API: [Code Snippet]
Generate usage examples for the following [language] API: [code snippet].
How to Create a Concise API Reference for a Programming Language Class
Create a concise API reference for the given [language] class: [code snippet].
Assessing [Language] Code Performance and Providing Optimization Suggestions
Assess the performance of the following [language] code and provide optimization suggestions: [code snippet].
Improving Error Handling in Language Code: Suggestions and Enhancements
Check the following [language] code for proper error handling and suggest enhancements: [code snippet].
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.”
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.