← Series B+ Startup Interview Insights
No intellisense, camera on, clock ticking.
Start by clarifying the problem constraints and edge cases, then quickly outline your approach verbally before coding. Implement a clean, working solution first, then optimize if time permits, testing with examples as you go.
Pro tip: Narrate your thought process continuously—interviewers value clear communication and problem-solving over silent perfection. If stuck, simplify the problem or use a brute-force solution as a baseline, then iterate.
Restate the problem in your own words and ask clarifying questions about input size, edge cases, and expected output. Confirm assumptions before proceeding.
Outline your approach, including data structures and algorithms, and discuss time/space complexity. Get interviewer buy-in before coding.
Write clean, modular code with meaningful variable names. Handle edge cases and use helper functions if needed to avoid bugs.
Walk through your code with a small example, including edge cases. Fix any issues and verify correctness.
If time allows, discuss potential optimizations and trade-offs. Summarize your solution and complexity.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Didn't expect this many math problems sandwiched between the coding sections.
First, quickly scan all four problems to assess difficulty and time allocation. Then, solve each problem systematically, showing your work and double-checking calculations. If stuck, move on and return later, ensuring all problems are attempted.
Pro tip: Practice with timed math assessments to improve speed and accuracy; remember that partial credit may be given for correct methodology even if the final answer is wrong.
Skim all problems to gauge complexity and time needed. Start with the easiest to secure quick points.
For each problem, read carefully, identify given information and what's asked. Use a step-by-step approach, writing down intermediate steps.
After solving, quickly verify calculations and ensure the answer makes sense. Check units and reasonableness.
Keep an eye on the clock. If a problem takes too long, skip and return if time permits. Ensure all questions are answered.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
By the time I got here I had maybe 15 minutes left.
First, quickly assess both problems to identify the easier one and solve it efficiently to secure partial credit. Then, tackle the harder problem with a clear plan, communicating your thought process throughout. Manage your time strictly, allocating roughly 25 minutes per problem and leaving buffer for review.
Pro tip: In a timed assessment, partial solutions and clean, well-commented code can earn more points than a rushed, buggy complete solution. Always prioritize correctness and clarity over optimization unless explicitly required.
Spend 2-3 minutes skimming both problems to gauge difficulty, required algorithms, and edge cases. Decide the order of solving based on your confidence and time estimates.
For the first problem, outline your approach with pseudocode or comments, ensuring you understand the problem fully. Identify potential pitfalls and test with simple examples.
Write clean, modular code with meaningful variable names. Test with provided examples and additional edge cases, debugging as needed.
After 25-30 minutes, move to the second problem regardless of completion. If stuck, leave a comment explaining your approach and move on to maximize overall score.
If time remains, review both solutions for correctness, edge cases, and efficiency. Add comments to clarify complex logic.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.