Feeling like LC is BS that only works for Big Tech? How do you learn for a job if not doing LC?
Interview Experience
3rd year undergrad here. I'm currently preparing for my first "normal" full-time role after spending the last three years in startups and doing contracting work. I learned a ton in those environments
Full Details
3rd year undergrad here. I'm currently preparing for my first "normal" full-time role after spending the last three years in startups and doing contracting work. I learned a ton in those environments working on interesting projects (not some boring CRUD apps), but now I'm preparing for corporate interviews. I'm studying a pretty broad range of topics that commonly come up: Python and Go internals, low-level Docker, AWS (I'm working toward the Solutions Architect cert even though I’m not a huge fan of certs), Terraform, System Design (low/high level), Kubernetes, and CI/CD. At the same time, I've started reading the books recommended by my friend from Google (Designing Data Intensive Apps, DB Internals, System Perf). I make daily notes. When a job description lists all this tooling (Docker, K8s, Terraform, etc.), I wonder whether diving deep into them right now is the best use of my time - or whether I’d become a stronger engineer by focusing more on the concepts from the books. That said, my top priority is landing a job soon, and I know corporate interviews often test this kind of practical/theoretical knowledge. Do you think the learning path I’m on right now makes sense given my goal of getting hired? I’m fully committed to going through the books this year, but I’m also conscious that I have a limited runway before I really need to land something. (I also forgot quite a bit after switching careers once into business process automation.) I’d really value your honest advice as someone who’s been through this. PS. yes I have studied LC: I did around 250 mediums - but from my experience most non Big Tech companies don't push for LC so much. PS. #2: yes I have pretty strong commercial projects on GitHub. Really appreciate any thoughts you have 🙏 Best, J (To be very precise my current learning path looks like this: I ask Grok about all the topics about subject X, ask him about each topic doing a deep dive from basic to advanced, I make notes and rehearse) - it takes lots of time, but I'm not sure there's a better way to prepare for random questions from recruiters).
About This Question
This is a candidate experience report from a tech interview for a swe role during the system design round reported in 2026.
It covers the following topics: System Design .
Difficulty rating: Easy
Topics
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This question was reported by a candidate who interviewed at Tech. 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.
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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 Tech reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Tech 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 Tech 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.