GitHub Copilot Prompt for Interview Preparation

GitHub Copilot, the AI development assistant integrated into code editors, can become a formidable ally for preparing a technical or professional interview. By leveraging its code and text generation capabilities, you can simulate interview questions, structure your answers using the STAR method, generate code exercises in real conditions, and anticipate common recruiter traps. Whether you are preparing for an interview for a developer, data scientist, or technical project manager position, Copilot helps you organize your ideas, formulate impactful responses, and practice on practical cases. The key advantage lies in its ability to contextualize questions based on the target position, the company's tech stack, and your experience level. Rather than browsing generic lists of questions on the Internet, you get a personalized preparation program directly in your work environment. This approach allows you to combine technical review and interview simulation in a unified workflow, maximizing your preparation time.

The prompt

GitHub Copilot

Act as a coach specialized in technical interview preparation. I am applying for a [JOB TITLE] position at [COMPANY NAME]. The tech stack mentioned in the job posting includes: [TECHNOLOGIES]. I have [X] years of experience. Generate a complete preparation program including: 1) The 10 most likely technical questions for this position with detailed answers and code examples where relevant, 2) 5 classic behavioral questions with answers structured according to the STAR method (Situation, Task, Action, Result), 3) A typical live coding exercise with its commented solution step by step, 4) Common trick questions and how to answer them confidently, 5) A list of relevant questions to ask the recruiter to demonstrate my understanding of the position. Adapt the difficulty level and technical depth to the position's seniority.

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Why it works

This prompt works due to the role attribution (specialized coach) which steers Copilot towards a professional and educational register. Personalization via variables (position, company, stack, experience) forces the model to contextualize each response instead of producing generic content. The numbered structure across five axes covers the entire spectrum of a technical interview, ensuring thorough preparation.

Expected result

You will obtain a structured preparation document covering all aspects of the interview: technical questions with detailed answers and code snippets, behavioral scenarios formatted in STAR, a complete coding exercise with commented solution, and strategies for handling destabilizing questions. All calibrated to the target position and company.

Variants by level

FAQ

Can GitHub Copilot really simulate a technical interview realistically?

Copilot generates questions and answers based on interview patterns widely documented in its training data. The questions produced are representative of what you will encounter in real interviews, especially for popular technologies. However, it is recommended to supplement this preparation with mock interviews with humans to work on oral communication and body language, aspects that Copilot cannot evaluate.

How to adapt the prompt if I don't know the company's tech stack?

Replace the variable [TECHNOLOGIES] with the company's business sector and the type of position. For example: 'fintech company of 200 people, backend position'. Copilot will infer the probable technologies and adjust its questions accordingly. You can also ask it to first guess the likely stack before launching the interview simulation.

What is the best way to use Copilot to prepare for live coding exercises?

Ask Copilot to generate an exercise statement WITHOUT the solution, then try to solve it yourself in your editor. Then ask it to critique your solution in terms of algorithmic complexity, readability, and edge case handling. This two-step approach reproduces the real conditions of a live coding session and trains you to code under pressure rather than simply reading solutions.

How to use this prompt

Copy the prompt with the button above.
Paste it into ChatGPT, Claude or your favorite AI assistant.
Replace the bracketed variables with your details, then refine the result.

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