HN Debrief

That time when I failed the Microsoft interview

  • Hiring
  • Programming
  • Management
  • Big Tech

The post is a short retrospective on a failed Microsoft interview. The author had prepared for the company’s old puzzle-heavy style, got a well-known balance-scale marble riddle, said he had seen it before, asked for a different problem, and was later rejected with a generic form letter. The piece is really about a common candidate dilemma: do you answer the question in front of you, even if it is artificial, or do you try to be maximally honest and risk violating some unspoken interview norm.

If your hiring loop still relies on riddles, "aha" coding questions, or underspecified design prompts, you are probably measuring interview prep and compliance more than job ability. For candidates, the practical move is to treat interviews as culture sampling as much as evaluation, and to practice narrating your reasoning because randomness and interviewer quality clearly matter.

Discussion mood

Strongly negative on brainteasers and trick-question interviews. The frustration came from mismatch with real work, heavy randomness, interviewer inconsistency, and the sense that many companies are testing compliance with an arbitrary ritual rather than engineering judgment.

Key insights

  1. 01

    Policy and practice diverge inside big companies

    Even when a company has formally moved away from brainteasers, individual interviewers can keep asking them for years. Former Microsoft interviewers said HR training had already discouraged or banned these questions well before 2015, yet candidates still got the same marble puzzle in 2015 and 2016. That makes the problem less about a single company rule and more about weak enforcement in large interview systems.

    Do not assume published interview guidance reflects what candidates will actually face. If you run a hiring process at scale, audit real interviews and calibrate interviewers continuously instead of trusting policy documents.

      Attribution:
    • otterley #1
    • mikestew #1
    • ThrowawayB7 #1
    • flakes #1
  2. 02

    Interview outcomes are more lottery than exam

    Candidates do not just need skill. They need the right interviewer, the right question, the right level of hinting, and the right reading of unspoken norms. Several people pointed out that even within structured loops, one interviewer can still inject a bad question or misread a candidate, and the candidate often gets no useful feedback afterward. That is why identical behavior like admitting prior knowledge can lead to rejection in one loop and a hire in another.

    Build hiring processes that reduce single-interviewer variance. For candidates, prepare for variance instead of trying to infer a clean rule from one result.

      Attribution:
    • shepherdjerred #1
    • ventana #1
    • ConceptJunkie #1
    • LanceH #1
  3. 03

    Aha questions are just brainteasers in coding form

    The strongest criticism was aimed not only at classic riddles, but also at coding problems whose value depends on spotting one hidden trick. Examples included linked-list two-pointer questions and Leetcode problems whose answer is a tiny clever insight like `return True` or a named algorithm such as Boyer-Moore majority vote. These feel objective because they involve code, but they still reward prior exposure and proof tricks more than everyday engineering.

    If you want to test coding, use tasks with multiple valid paths and room for tradeoffs. Avoid prompts where one magical insight determines the whole score.

      Attribution:
    • ventana #1 #2
    • viccis #1
    • calchedonic #1
  4. 04

    Good interviewers score reasoning, not recall

    A more useful framing came from people who interview regularly. The signal is not whether someone has memorized the exact solution. It is whether they can state assumptions, start with a workable naive approach, improve it, and respond well to hints. One long example walked through how a candidate could fail to find the marble trick yet still show strong problem-solving by narrating a baseline solution and iterating collaboratively.

    Train interviewers to reward decomposition, communication, and adaptation. Candidates should practice saying their thought process out loud instead of treating the interview like a silent puzzle contest.

      Attribution:
    • herodotus #1
    • gwbas1c #1
    • xyzelement #1
  5. 05

    System design often punishes experienced candidates

    Underspecified design interviews drew a related complaint. Senior engineers said they struggle because real design starts with requirements, constraints, and tradeoffs, while many interview prompts expect a fast, simplified answer to a toy version of the problem. Another experienced commenter said the winning move is often to stop being realistic and give the basic answer the interviewer wants, then ask if more depth is needed. That is a sign the format often rewards compression and guess-the-scope, not design skill.

    For senior hiring, give explicit scope and evaluate requirement gathering directly. If you are the candidate, start simple on purpose and check whether the interviewer wants deeper realism before diving in.

      Attribution:
    • gwbas1c #1
    • WorldMaker #1
    • cloverich #1
    • LanceH #1
  6. 06

    IQ-test legality is murkier than the common myth

    One side thread corrected a widely repeated claim that cognitive or IQ-style tests are simply illegal in white-collar hiring. Commenters pointed to Griggs v. Duke Power Co. and noted that such tests are not automatically banned. The issue is whether they can be defended as job-related if challenged. Another commenter added that some large companies openly use general cognitive tests, and the bigger problem is not legal impossibility but weak usefulness for selecting programmers.

    Do not rely on folk wisdom about what hiring screens are legally off-limits. If you use cognitive testing, validate whether it predicts your work rather than assuming either blanket legality or blanket prohibition.

      Attribution:
    • rahimnathwani #1
    • tptacek #1
    • arjie #1

Against the grain

  1. 01

    Some estimation questions map to real work

    A minority defended Fermi-style estimation problems when the role actually involves rough capacity planning, traffic forecasting, or turning vague business demands into order-of-magnitude engineering targets. The argument was not that golf-ball questions are universally good. It was that estimation, open-mindedness, and verbal reasoning are real skills for certain large-scale systems roles, and a quick back-of-the-envelope model can expose them.

    Do not throw out every non-coding question as trivia. Keep estimation prompts only when the role regularly requires approximate modeling and discuss them like collaborative planning, not like riddles.

      Attribution:
    • rwmj #1
    • GrumpyYoungMan #1
    • paulcole #1
  2. 02

    A bad interview can still be a useful filter

    Some people read ugly interview moments as informative rather than purely broken. If a company wants aggressive selling, rigid obedience, or a culture you would hate, an interview that reveals that mismatch may save both sides time. In that view, the candidate should not always optimize for passing. They should notice what kind of behavior the process rewards and decide whether they want that job at all.

    Use the hiring loop to inspect the employer, not just to perform for them. If the rewarded behavior clashes with how you want to work, treat a rejection or withdrawal as useful signal rather than wasted effort.

      Attribution:
    • makeitdouble #1
    • achenet #1
    • neuroticnews25 #1
  3. 03

    Intern interviews need some proxy for potential

    There was some pushback against the blanket rejection of puzzles for internships and early-career roles. Without much job history, interviewers still need a fast way to gauge curiosity, persistence, and structured thinking. Others answered that you can get the same signal more directly from project walkthroughs and motivation questions, but the contrarian point stands that the problem is harder when a resume is thin.

    For interns, test potential explicitly rather than pretending you are measuring production experience. If you use abstract problems, keep them lightweight and pair them with project discussion so one puzzle does not dominate the decision.

      Attribution:
    • jameshart #1
    • tyre #1
    • ThrowawayR2 #1

In plain english

AWS
Amazon Web Services, Amazon's public cloud computing platform.
Boyer-Moore majority vote
An algorithm that finds a majority element in a list using constant extra memory.
Griggs v. Duke Power Co.
A 1971 US Supreme Court case holding that employment tests must be related to job performance if they have discriminatory effects.
Leetcode
A coding practice platform whose interview-style algorithm problems have become a proxy for technical interview preparation.

Reference links

Interview critiques and hiring practices

Books and background on puzzle interviews

Algorithms and puzzle references

Law and hiring assessment references