Create unique MIN with ChatGPT
Search and store tool for Chat GPT Prompt
Create unique and engaging MIN with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.
The Advantages of Using Chat GPT for Agile Development
Write a blog post discussing the advantages of utilizing Chat GPT for agile development.
Incorporating Continuous Testing and Quality Assurance in [Language] Projects: A Helpful Guide
Share advice on how to incorporate continuous testing and quality assurance into the development process for a [language] project.
Comparing Language Testing Frameworks and Choosing the Best One for Your Project
Compare different [language] testing frameworks and recommend one that best suits the given project: [project description].
Strategies for Automating Regression Testing in [Language] Project
Suggest strategies for automating regression testing in the given [language] project: [project description].
Best Practices for Writing and Maintaining Unit Tests for [Language] Codebase
Recommend best practices for writing and maintaining unit tests for a [language] codebase.
Effective Strategies for Task Management in [Language] Development Projects
Share strategies for effectively managing and prioritizing tasks in a [language] development project.
Maximizing Focus during Language Development: Techniques and Tips for Staying on Task
Suggest ways to minimize distractions and maintain focus during [language] development tasks.
Transitioning from Technical to [Language] Development: Expert Opinion and Tips
Share advice on how to transition from a different technical role to a [language] development role.
Networking Opportunities and Resources for [Language] Developers to Connect with Peers and Employers
Suggest networking opportunities or resources for [language] developers to connect with peers and potential employers.
Creating an Effective and Compelling Software Developer Portfolio: Tips and Advice
Share advice on how to create an effective and compelling software developer portfolio.
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.
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].
Balancing Technical Debt and Feature Development in [Language] Projects
Recommend approaches to balancing technical debt and feature development in a [language] project.
Effective Strategies for Mentoring and Coaching Junior Language Developers
Suggest strategies for mentoring and coaching junior [language] developers to help them grow and succeed.
Best Practices for Leading and Managing a Language Development Team
Share best practices for leading and managing a [language] development team.
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].
How to Create a Boilerplate [Language] Project Structure for a [Type of Application]
Create a boilerplate [language] project structure for a [type of application] that includes necessary configuration files and dependencies: [application description].
Conducting a [Language] Technical Interview: Problem-Solving, Coding and Thought Process
Conduct a mock [language] technical interview, including problem-solving, coding, and explanation of thought process.
Common Language Technical Interview Questions and Solutions
Provide examples of common [language] technical interview questions and their solutions.
Tips for Approaching Language Coding Problems during Technical Interviews
Share tips and advice on how to approach and solve [language] coding problems during a technical interview.
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.