Mastering ChatGPT: Handy Prompts and Strategies for Developers

Dec 28, 2023
Рrompts for  chatGPT that a developer needs Devler.io

From Confused to Confident: ChatGPT Prompts for Software Development

Have you ever found yourself staring at your screen, wondering why Chat GPT doesn't understand your coding query despite your best efforts? 

You're not alone. Thousands of developers globally are now integrating AI tools like Chat GPT into their workflow but can use them at a full scale. The key to efficiency often lies in crafting the correct prompt. Miscommunications can lead to hours of frustration, undermining the efficiency these tools are meant to bolster. 

Let's dive into how you can master creating effective Chat GPT prompts, transforming your coding experience from exasperating to exhilarating.

Generative AI & software development: use cases 

Generative AI. For most business leaders, it still sounds like a buzzword. In the meantime, devs became pioneers in mastering innovation and using it to optimize software development workflow. 

McKinsey reports that as of mid-2023, technology, media, and telecom sectors have become domains with the highest AI awareness. 14% of respondents in these industries regularly use Generative AI. Not only to turn the requests into text or graphics but to generate pretty good code.

Different ways to use AI in software development

So, what does Generative Artificial Intelligence mean in terms of software development

  • Plenty of AI-driven code-generation chatbots & bug fixing tools
  • Drastically reduced development time 
  • Solid increase in dev velocity 
  • Better developer experience 

AI tools suggest optimal code snippets, detecting and correcting errors in real time, almost like a highly experienced coding ally. It also pumps up user experience design by enabling software that auto-generates personalized UIs and content, adapting to user behavior. More so, Generative AI is redefining testing and QA processes. It can autonomously create complex, realistic test cases, ensuring more thorough and efficient testing. 

Sounds exciting, doesn't it? The technology is worth it to try.

Business & tech benefits of Generative AI in terms of software development


Business Benefits

Tech Benefits

Code Generation

Optimizes development cycle and costs

Accelerates Time-to-Market 

Assists in writing and debugging code

Enhances code quality

Testing & QA

Improves product reliability, enhancing customer trust

Reduces testing costs

Generates comprehensive test cases

Automates repetitive testing tasks

Data Analysis

Drives informed decision-making through up-to-date data insights

Optimizes operational efficiency

Automates data interpretation

Provides predictive analytics


Facilitates business growth with scalable solutions

Adapts to dynamic market demands

Supports handling of large-scale data and users

Optimizes system performance

User Experience

Boosts customer loyalty with tailored experiences

Enhances brand reputation

Creates intuitive and responsive interfaces

Improves interaction design


Who develops with Generative AI at hand: Examples of AI in software development

Well, considering the mainstream, a majority of the big-ticket companies have tried Generative AI and Machine Learning for their software development purposes. However, they prefer to show only one part of this usage - built integration points with AI tools, like ChatGPT.

In just a few years, businesses like Toyota, Starbucks, Slack, and others released new AI-powered features to remain competitive. For example, Netflix folks use AI to process viewing patterns and user behavior and offer a personalized approach to their subscribers. 

In the meantime, Microsoft, one of the OpenAI investors, uses large language models applied for ChatGPT as a base for their Bing search engine. Curious, that ChatGPT 4 demonstrates request processing showing users Bing's work, in turn ChatGPT 3.5 doesn't have the integration point with Bing. 

As AI is a subject of curiosity for developers, businesses also benefit from the technology capabilities in the software development process but prefer to hide the details. The case is Generative AI has two solid drawbacks:

  • AI can't always provide accurate information. For example, Chat GPT 4 can show you more or less relevant data on events before April 2023. As it's not a source of truth, the codebase generated should be double-checked carefully.
  • Generative AI learns and saves all the data provided as input; this way, businesses risk sharing confidential information. Artificial Intelligence can use it to generate code for other users. This concern makes companies focus on delegating relatively simple but time-consuming tasks. Otherwise, they risk disclosing confidential data, which leads to significant losses. 

For example, developers from Delver.io attentively and carefully approach work with any Generative AI tools, like ChatGPT, mastering the art of asking the right questions. 

To use Artificial Intelligence for software development, you should do the same: be straight to the point when placing your request and always keep the risk of confidential data leak in mind to avoid it.

Different types of prompts for ChatGPT: handy tips for software development 

Chat GPT is a sort of Room of Requirement famous for the Harry Potter books. If you don't know what you want and how to ask about it, nothing good is happening. 

Curious that the buzz around Chat GPT was accompanied by thousands of specialists who shared their hints and prompts for free or monetized their experience. 

As the solution is capable of supporting almost every phase of the software development cycle, you can count on at least 5 types of prompts to use:

  1. Information retrieval prompts to extract specific information or data.              
    "What are the latest updates in Python 3.12?"              
    "Can you provide examples of RESTful API design patterns?"
  2. Code debugging and review prompts for help debugging or reviewing code snippets.              
    "Can you find the bug in this JavaScript function?"              
    "Review this Python script for PEP 8 compliance."
  3. Logic development prompts for assistance in developing algorithms for solving logical problems.             
    "How would you implement a binary search in Java?"              
    "What's the most efficient way to sort a large dataset?"
  4. Learning and tutorial prompts to boost your knowledge.             
    "Explain the Model-View-Controller architecture."              
    "Provide a beginner's tutorial on using Docker." 
  5. Integration and implementation prompts for integrating different technologies or implementing specific features.             
    "How to integrate Stripe payment gateway in a Flask app?"              
    "Steps to implement OAuth 2.0 in a mobile application."             

35 Chat GPT prompts useful for your specific development needs


Chat GPT Prompts


  1. Write a Ruby script to automate database migrations and data seeding for a new project.
  2. Generate a Ruby-based RESTful API for a simple e-commerce application.
  3. Debug and optimize Ruby code for memory leaks in a large-scale application.
  4. Integrate a third-party authentication service using Ruby on Rails.
  5. Create a Ruby script to parse and process large JSON files efficiently.


  1. Develop a React component for a dynamic, filterable data table.
  2. Create a multi-step user registration form in React with form validation.
  3. Implement React Context for state management in a large application.
  4. Build a React-based interactive dashboard with real-time data updates.
  5. Optimize React application performance for a high-traffic website.


  1. Write a Python script to scrape web data and store it in a SQL database.
  2. Develop a Python-based backend logic for a user authentication system.
  3. Automate unit testing in Python for a complex software module.
  4. Create a Python Flask API with endpoints for file uploads and downloads.
  5. Implement an AI chatbot in Python using natural language processing.


  1. Build an Angular service for handling HTTP requests in a web application.
  2. Create a dynamic form in Angular that supports various field types.
  3. Integrate Angular with a third-party charting library for data visualization.
  4. Develop a mobile-responsive single-page application using Angular.
  5. Implement lazy loading in Angular for improved application performance.


  1. Set up a Node.js server with Express for a real-time chat application.
  2. Write a Node.js script for batch processing of large datasets.
  3. Integrate a NoSQL database with a Node.js application for efficient data retrieval.
  4. Develop a secure file upload and storage system using Node.js.
  5. Optimize Node.js application performance for scalability in a cloud environment.


  1. Create a Swift-based iOS app with custom animations and transitions.
  2. Implement Core Data in Swift for efficient data management in a mobile app.
  3. Develop a Swift function for face recognition using Apple's Vision framework.
  4. Build a location-based service in Swift for iOS with map integration.
  5. Optimize Swift code for battery efficiency in an iOS application.


  1. Develop a .Net application with a secure user authentication system.
  2. Create a REST API in .Net Core for a financial services application.
  3. Implement real-time data synchronization in a .Net application using SignalR.
  4. Build a microservices architecture in .Net for a scalable enterprise solution.
  5. Automate the deployment of a .Net application to Azure cloud services.


Bonus Point: How to make Chat GPT your personal Prompt Engineer

If you want a thing done well, do it yourself. Even switching between millions of prompts advised by devs, you won't find the 100% suitable.

But how about a creative text format for crafting a best-fit Chat GPT prompt? Use the magic text below to turn a conversation with Chat GPT into a precise and straight-to-the-point algorithm. 

I want you to become my Prompt engineer. 
Your goal is to help me craft the best possible prompt for my needs. 
The prompt will be used by you, ChatGPT. You will follow the following process: 
1. Your first response will be to ask me what the prompt should be about. 
I will provide my answer, but we will need to improve it through continual iterations by going through the next steps. 

2. Based on my input, you will generate 2 sections, 
a) Revised prompt (provide your rewritten prompt, it should be clear, concise, and easily understood by you), 
b) Questions (ask any relevant questions pertaining to what additional information is needed from me to improve the prompt). 

3. We will continue this iterative process with me providing additional information to you and you updating the prompt in the Revised prompt section until I say we are done. 

The Bottom Line

Software development with AI tools like ChatGPT becomes not a piece of cake, but at least times faster and easier. Generative AI notably improves coding processes, including code generation and debugging.  

Pioneers like Toyota and Netflix are harnessing AI to enhance their technological workflows. But how do you approach Chat GPT to get relevant results effortlessly? 

Here, you can see the top types of prompts and some valuable examples. But remember that the best prompt is the one you create directly with Chat GPT to align your expectations and clarify your task for the machine.  

Seems useful? Share this article with your fellow developers! Increase dev velocity and speed up Time-to-Market by using a suitable approach to Chat GPT.

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