Create unique code review with ChatGPT

Search and store tool for Chat GPT Prompt

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

Act as a Prompt Generator

I want you to act as a prompt generator. Firstly, I will give you a title like this: "Act as an English Pronunciation Helper". Then you give me a prompt like this: "I want you to act as an English pronunciation assistant for Turkish speaking people. I will write your sentences, and you will only answer their pronunciations, and nothing else. The replies must not be translations of my sentences bu...

code review helper

Effective Techniques for Remote Pair Programming and Code Review Sessions Among Distributed Developers

Propose techniques for remote pair programming and code review sessions among distributed [language] developers.

remote pair programming code review distributed developers

How to Facilitate a Code Review Session for Team Members

Facilitate a code review session between [team member 1] and [team member 2] for the following [language] code: [code snippet].

code review team members programming

Strategies for Conducting Thorough Code Reviews and Quality Assurance Testing

Preview

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

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.