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Early-stage Startup·Software Engineer·Technical Phone Screen·Junior

JuniorPending
Jul 2026

Summary

First ever coding interview and I still can't tell if it went well or not. Three problems total, mixed results, and the interviewer kept raising the bar on me mid-session.

Questions Asked (2)

Q1

Solve a coding problem as the mandatory first question in the interview.

Algorithms & Data Structures
Author's notes

Had the right idea pretty quickly but couldn't translate it into actual code without a nudge.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and edge cases, then discuss a brute-force solution before optimizing. Implement the optimized solution with clean code, and test with examples to ensure correctness.

Pro tip: Communicate your thought process continuously and welcome hints; interviewers assess problem-solving and collaboration, not just the final answer.

1. Understand and Clarify

Ask questions to confirm input/output formats, constraints, and edge cases. Repeat the problem in your own words to ensure alignment.

2. Explore Approaches

Discuss a brute-force solution and its complexity, then propose an optimized approach. Explain trade-offs between time and space.

3. Plan and Implement

Outline the algorithm steps, then write clean, modular code. Use meaningful variable names and handle edge cases.

4. Test and Debug

Walk through your code with a few test cases, including edge cases. Fix any bugs and verify the solution.

5. Reflect and Optimize

Analyze time and space complexity, and suggest further optimizations if possible. Discuss potential improvements or alternative solutions.

Key Points to Mention

  • Clarify constraints and edge cases before coding
  • Start with a brute-force solution and then optimize
  • Analyze time and space complexity
  • Write clean, readable code with meaningful names
  • Test with examples and edge cases
  • Communicate thought process and collaborate with interviewer

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Choose between solving two easier problems or one harder problem, then complete whichever you selected.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Picked the two easier ones and knocked them out in like five minutes each.

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AI HintsAI Generated

Suggested Approach

First, clarify the constraints and expectations with the interviewer, then evaluate the trade-offs between solving two easier problems versus one harder problem based on time, risk, and impact. Choose the option that best demonstrates your problem-solving process and aligns with the startup's need for pragmatic, high-impact solutions. Finally, solve the selected problem(s) while communicating your thought process clearly.

Pro tip: In an early-stage startup, shipping value quickly often matters more than perfect optimization; choosing the two easier problems can showcase your ability to deliver incremental wins and manage risk. However, if the harder problem directly addresses a critical business need, tackle it and explain why it's the higher-leverage choice.

1. Clarify Requirements and Constraints

Ask the interviewer about time limits, evaluation criteria, and whether the problems relate to real startup challenges. This shows you prioritize understanding before acting.

2. Assess Trade-offs

Compare the two options: easier problems may offer quick wins and lower risk, while the harder problem could demonstrate deeper skill or higher impact. Consider factors like time, complexity, and alignment with startup goals.

3. Make a Decision and Justify It

State your choice clearly and explain your reasoning, linking it to the startup context (e.g., speed, impact, learning). This demonstrates strategic thinking.

4. Solve the Selected Problem(s)

Implement your solution(s) while verbalizing your approach, edge cases, and any assumptions. If you chose two easier problems, manage time to complete both.

5. Review and Reflect

After solving, briefly discuss what you learned, potential improvements, and how your choice reflects your engineering judgment. This shows self-awareness and growth mindset.

Key Points to Mention

  • Time management and prioritization in a fast-paced startup environment
  • Risk mitigation: choosing easier problems to ensure delivery
  • Impact vs. effort: when a harder problem is worth the investment
  • Communication of trade-offs and decision rationale
  • Demonstrating adaptability and problem-solving process
  • Alignment with startup goals: shipping value quickly and iterating

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.