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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.
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.
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.
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].
How to Generate a Scatter Plot to Analyze the Relationship between Two Variables
Generate a scatter plot that demonstrates the relationship between the following two variables: [variable 1] and [variable 2].
Impact of Issue Description on Project Timeline and Required Effort Estimate
Estimate the effort required to resolve the following issue and its impact on the project timeline: [issue description].
Generating Potential Solutions for Reported Issues: Tips & Techniques
Suggest potential solutions for the following reported issue: [issue description].
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].
Identifying Opportunities for Design Pattern in Code: Tips and Tricks
Identify opportunities to apply [design pattern] in the given [language] code: [code snippet].
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].
How to Develop a Conversational Script for Onboarding a Chatbot User
Develop a conversational script for a chatbot that guides users through the [onboarding process or feature setup].
Identifying Inefficiencies in Database Schema for Query Performance Optimization
Identify any inefficiencies in the given database schema that may be affecting query performance: [schema description].
Opinion Generator Function for Language Code Snippets: Expected Input and Output
Document the expected input and output for the given [language] function: [code snippet].
Reviewing and Suggesting Improvements for Language Code Snippet: Best Practices
Review the following [language] code for best practices and suggest improvements: [code snippet].
Identifying Potential Bugs in [Language] Code Snippet: Tips and Techniques
Identify any potential bugs in the following [language] code snippet: [code snippet].
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].
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].
How to Write a Script Using a Library/Framework with Given Requirements
Write a [language] script to perform [task] using [library/framework] with the following requirements: [requirements list].
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].
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].
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.