10 years in and I'm finally starting to value boring technology.
Interview Experience
Five years ago I would've rolled my eyes at this post. I was that guy pushing to rewrite stuff in Rust because it was trending then, wanted to use some experimental database I found on Github with 200
Full Details
Five years ago I would've rolled my eyes at this post. I was that guy pushing to rewrite stuff in Rust because it was trending then, wanted to use some experimental database I found on Github with 200 stars because the readme said it was web scale. Got into legitimate arguments about framework choices that in hindsight did not matter even a little bit. Then I became the person who had to fix things when they broke. Oh you wanted to try that new message queue? Cool, hope you enjoy debugging why it randomly loses messages at 2am. That distributed database you read about on Hacker News? Awesome, except now deploys take 6 hours and nobody knows why. At some point I just got tired. Tired of explaining to product why we're three sprints behind because we're fighting our own infrastructure. Tired of being the only person who understands how some piece of critical infrastructure works because we picked something obscure. Now I'm boring as hell and I love it. Postgres? Yeah sure. Proven message systems? Absolutely. Things that have documentation written by humans who actually use the product? Sign me up. You can still build cool shit with boring technology. Actually you can build way cooler shit because you're not spending half your time debugging your infrastructure instead of writing features. Anyway yeah, I'm officially old and boring now. My infrastructure should be so reliable I literally forget it exists. Save the excitement for the product.
About This Question
This is a candidate experience report from a github interview for a swe role reported in 2026.
It covers the following topics: System Design, Queue, Sql, Stack Queue .
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About Github Interview Reports
This question was reported by a candidate who interviewed at Github. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Github are the higher-signal extractions to take from this report.
For broader preparation context, the Github interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Github reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Github Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Github reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.