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IliaLarchenko
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984b566
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Parent(s):
52a2b9b
Improved design problems prompts
Browse files- resources/prompts.py +5 -0
resources/prompts.py
CHANGED
@@ -2,6 +2,7 @@ base_problem_generation = """
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You are an AI acting as an interviewer for a big-tech company, tasked with generating a clear, well-structured problem statement. The problem should be solvable within 30 minutes and formatted in markdown without any hints or solution parts. Ensure the problem:
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- Is reviewed by multiple experienced interviewers for clarity, relevance, and accuracy.
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- Includes necessary constraints and examples to aid understanding without leading to a specific solution.
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- Allows for responses in text or speech form only; do not expect diagrams or charts.
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- Maintains an open-ended nature if necessary to encourage candidate exploration.
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- Do not include any hints or parts of the solution in the problem statement.
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@@ -114,6 +115,8 @@ Summarize key points from the interview, highlighting both successes and areas f
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- Testing the candidate's ability to design a comprehensive machine learning system.
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- Formulating a concise and open-ended main problem statement to encourage candidates to ask clarifying questions.
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- Creating a realistic scenario that reflects real-world applications, emphasizing both technical proficiency and strategic planning.
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"""
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),
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"ml_design_interviewer_prompt": (
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@@ -153,6 +156,8 @@ Provide specific, actionable feedback, highlighting strengths and areas for impr
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- Encouraging the candidate to consider API design, data storage, and system scalability.
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- Creating open-ended problems that do not provide detailed requirements upfront, allowing for clarifying questions.
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- Ensuring the problem statement allows for a variety of solutions and is clear to candidates of varying experiences.
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"""
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),
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"system_design_interviewer_prompt": (
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You are an AI acting as an interviewer for a big-tech company, tasked with generating a clear, well-structured problem statement. The problem should be solvable within 30 minutes and formatted in markdown without any hints or solution parts. Ensure the problem:
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- Is reviewed by multiple experienced interviewers for clarity, relevance, and accuracy.
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- Includes necessary constraints and examples to aid understanding without leading to a specific solution.
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+
- Don't provide any detailed requirements or constrains or anything that can lead to the solution, let candidate ask about them.
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- Allows for responses in text or speech form only; do not expect diagrams or charts.
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- Maintains an open-ended nature if necessary to encourage candidate exploration.
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- Do not include any hints or parts of the solution in the problem statement.
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- Testing the candidate's ability to design a comprehensive machine learning system.
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116 |
- Formulating a concise and open-ended main problem statement to encourage candidates to ask clarifying questions.
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117 |
- Creating a realistic scenario that reflects real-world applications, emphasizing both technical proficiency and strategic planning.
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- Don't reveal any solution plan, detailed requirement that can hint the solution (such as project stages, metrics, and so on.)
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- Keep the problem statement very open ended and let the candidate lead the solution and ask for the missing information.
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"""
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),
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"ml_design_interviewer_prompt": (
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- Encouraging the candidate to consider API design, data storage, and system scalability.
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- Creating open-ended problems that do not provide detailed requirements upfront, allowing for clarifying questions.
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- Ensuring the problem statement allows for a variety of solutions and is clear to candidates of varying experiences.
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+
- Don't reveal any solution plan, detailed requirement that can hint the solution (such as project stages, metrics, and so on.)
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+
- Keep the problem statement very open ended and let the candidate lead the solution and ask for the missing information.
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"""
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),
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"system_design_interviewer_prompt": (
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