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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsUse AI as an interviewer and reviewer, not as the person who solves the problem. Make an unaided attempt first: clarify the task, talk through your plan, write and test your code, and explain its complexity. Then ask AI for a hint, a missed edge case, or feedback on your reasoning. If you view a full solution, close it and reconstruct the approach from memory.
Use this five-step practice routine
- Choose a problem and set a timer. Before coding, restate the input, expected output, constraints, and examples. If anything is ambiguous, write down the questions you would ask an interviewer.
- Plan aloud before you code. Explain a possible approach and its trade-offs. You can ask AI to provide a practice prompt or play interviewer, but tell it not to reveal code or the solution.
- Implement and test your own answer. Run the examples and add edge cases, including empty or minimal inputs and boundary values where relevant. Explain why the approach should work, then state its time and space complexity.
- Ask for targeted feedback. After your attempt, ask AI to identify one gap, test a case you may have missed, or pose a follow-up question. Request a hint rather than a solution. If you choose to compare with a complete explanation, do so only after the independent attempt; then close it and reproduce the reasoning without looking.
- Log what went wrong. Record whether the issue was misunderstanding the prompt, missing an edge case, choosing a data structure, making an implementation error, or explaining the approach unclearly. Revisit a similar problem later to see whether you can apply the lesson unaided.
Give AI rules that preserve the challenge
Set the boundaries in the first prompt and repeat them if the conversation drifts. For example:
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Act as a coding interview interviewer. Give me one problem and answer clarifying questions, but do not provide code or the solution. Let me propose an approach and implement it first. If I ask for help, give one small hint at a time. After I finish, ask me about correctness, edge cases, and complexity, then critique my reasoning without rewriting my answer.
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When you need a nudge, make the request specific: “Ask me one question that could reveal a missed edge case,” or “Give me a hint about what property I should consider, without naming the data structure.” Avoid prompts such as “solve this” or “write the optimal code” until after you have completed the attempt and deliberately switched to comparison.
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Choose a practice format that matches your goal
| Practice format | What it helps you practise | What to watch for |
|---|---|---|
| Solo timed practice | An unaided first attempt, pacing, implementation, and self-explanation. | You need to supply your own follow-up questions and assess your own reasoning. |
| AI-led mock interview | Conversational practice, clarifying questions, follow-ups, and feedback. | Set a no-solution rule and check whether feedback evaluates reasoning and communication, not just code. |
HackerRank documents one example of an AI mock interview: it presents a role-specific coding task, accepts clarifying questions, asks follow-ups, allows code execution and test review, and provides feedback on code quality, problem-solving, technical communication, and language proficiency. Its documented session is timed for 60 minutes; the help page recommends an uninterrupted hour and says a microphone is needed only for speech input. Features and credit requirements can change, and the documented format is not evidence that one platform outperforms another. See HackerRank’s Coding Mock Interview help page.
Check the rules for the real interview
Practice with AI does not mean AI is permitted in an assessment. Check the instructions for the specific employer and interview format, and treat preparation guidance as distinct from live-interview rules. Anthropic encourages AI use for interview preparation, but says its live interviews are AI-free unless otherwise indicated; its candidate guidance was last updated July 10, 2025. OpenAI likewise says expectations vary by format and directs candidates to the relevant preparation materials or recruiter. These are company-specific examples, not universal policies. Read Anthropic’s hiring-process guidance and OpenAI’s Interview Guide.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What AI practice can and cannot establish
A 2025 exploratory study by Daryanto and colleagues involved 17 participants practising technical interviews with think-aloud conversational AI. Participants valued simulation, feedback, and learning from generated examples. The study suggests useful design directions; its small sample does not establish improved hiring or interview outcomes at scale. See the 2025 study abstract.
A 2023 evaluation by Ouh and colleagues examined 80 undergraduate Java programming exercises. The authors reported that generated solutions could be readable and well organized, but exercises with non-text descriptions or class files could produce invalid solutions. That work concerns introductory Java exercises, not interview preparation or whether candidates learn more effectively with AI. It is a reason to verify generated code independently, not to treat it as an authority. See the 2023 conference paper record.
Neither study establishes a guaranteed improvement in interview performance or a number of problems that ensures success. Treat the routine as a practical way to keep the problem-solving work yours while using AI for structured practice and critique.
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