TierOnePrep
Interactive system design prep for FAANG & AI-era companies
11 followers
Interactive system design prep for FAANG & AI-era companies
11 followers
Interactive interview prep for FAANG and AI-era companies (Meta, Anthropic, Nvidia, Google, OpenAI, SpaceX). System design questions are 4-phase simulations of real interviews — vague brief, clarifying questions, architecture, hard follow-ups. Coding questions show algorithms running live with step-by-step visualizations. Written by engineers who've conducted hundreds of interviews at top companies. 12 free questions, no credit card.
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Viktor.comAn AI coworker that actually does the work
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The system design simulations feel closer to a real interview than any Leetcode-style prep I've tried. Wish the coding visualizer ran a bit faster on bigger inputs, but the clarifying question phase alone is worth the sign up.
@canselgzeyahv8 This is really useful feedback, thank you — and you're right about the visualizer. On larger inputs the step-through rendering starts to chug; it's animating every state change, which gets expensive as the input grows. It's on my list to fix, likely by letting you adjust playback speed and skip/batch steps on bigger inputs so it stays smooth. Genuinely helpful to hear it called out, because it tells me it's worth prioritizing.
And glad the clarifying-questions phase earns the signup on its own — that's the part I most wanted to get right, since it's where a lot of strong candidates quietly lose points in real loops.
If you hit any specific question where the lag was worst, I'd love to know which one — helps me test the fix against the actual worst case.
The 4-phase system design format is genuinely smart, treating it like a real interview instead of just tossing a prompt at you. Really wish more prep tools approached it this way instead of just grading a single answer.
@erturul42135743 Thank you — that "single answer" gap is exactly what bugged me about most prep out there. Real interviews aren't one question graded once; they're a conversation that evolves as you make decisions, and each decision opens the next set of trade-offs. Grading a lone answer misses the whole thing that's actually being tested.
That's why the follow-up phase matters as much as the initial design — it's where interviewers separate "designed something that works" from "understands why it works and what breaks at 10x scale."
Curious: what's tripped you up most in real system design rounds — the open-ended start, or the scaling follow-ups? That's the tension I'm always trying to tune the questions around.
The system design simulations actually feel closer to a real interview than anything else I've tried, especially the way it forces you to ask clarifying questions first. Live algorithm visualization is a nice touch too.
@melahatemicyh7 Thank you — that's exactly the reaction I was hoping for. The clarifying-questions phase was the part I most wanted to get right, because in real interviews that's where a lot of strong candidates quietly lose points: they jump straight to architecture without scoping the problem. Glad it lands the way it does in a real loop.
And happy the visualizations clicked for you — watching a data structure actually change state beats reading pseudocode every time.
Out of curiosity, which track were you practicing — classic FAANG system design, or the AI-era ones? Always keen to hear which questions feel closest to the real thing so I know where to invest next.