Feedback Summary from Your Coach

Tony has provided the following feedback on your session:

Rajat demonstrated solid foundational thinking in the system design round and showed clear engagement throughout the session. His ability to drive the conversation and list out both functional and non-functional requirements early on set a strong tone for the interview.

Areas of strength included:

• Clearly identifying all functional and non-functional requirements
  
  
• Proactive in driving the conversation and maintaining momentum
  
  
• Designed a business-relevant schema and was able to generate a coherent high-level design diagram
  
  
• Showed depth in spatial indexing, including comparisons between techniques like geohashing & Google S2 division
  
  
• Incorporated caching as a latency optimization strategy
  
  

Areas for improvement:

• Be explicit about the parameters of the problem (e.g., "Top N" — define what N is and how it’s used)
  
  
• Include numeric metrics in NFRs (e.g., aiming for “5 nines” availability and explaining what that implies)
  
  
• Add an entity and API definition phase — it helps set alignment and clarifies expectations
  
  
• Clearly specify key query patterns (e.g., term + geolocation in search) in the functional requirements
  
  
• Ensure the structure of your answer flows logically; currently, some parts were disorganized
  
  
• Although spatial indexing depth was good, be ready to justify geohashing in terms of simplicity and scalability tradeoffs
  
  
• Practice deeper reasoning with examples — e.g., how your system handles queries like “top 10 Italian restaurants in San Francisco”
  
  

Suggestions:

• Use a delivery framework to structure your answer: FR → NFR → Entity/API & Data Flow → HLD → Deep Dive
  
  
• Manage your time carefully and avoid diving too deep during the early stages
  
  
• Prioritize calculating or optimizing only when necessary, based on requirements
  
  
• Ensure the 1-to-1 mapping from FR → HLD and NFR → Deep Dive flow is clear and methodical
  
  

Overall, Rajat shows strong potential and would benefit from continued practice on structuring answers and driving clarity under ambiguity. With deliberate focus on the above areas, he should be well-prepared for upcoming Staff-level interviews.

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Next Steps

1. ✅ Review Your Detailed Feedback: Log in to your account on ShowOffer to access the complete detailed feedback, including specific improvement areas.‍
2. OpenAI based System Design Coaching: Coach Tony mentioned you have an urgent timeline to cover system design questions like CI/CD, Webhook, or ChatApp like GPT; we will make corresponding experienced coaches to help with once you book another session!