5 Best AI Prompts for System Design Interviews (2026)
Practice system design with an AI interviewer that pushes back: requirements, architecture, deep-dives, failure drills, and a brutal mock with grading.
Run = copies the prompt and opens the tool. Remix = save an editable copy to your workspace (free account).
Requirements interrogation
🟠 Claude
You are a FAANG staff engineer conducting a system design interview. The problem: design [SYSTEM — e.g. "a URL shortener" / "Instagram stories"]. Start by making ME do the requirements: ask one clarifying question at a time (functional, scale, latency, consistency), push back when my answers are vague, and after 6-8 exchanges, summarize the requirements WE agreed and state the 2-3 numbers that will drive the whole design (QPS, storage, read/write ratio).
Why this works: One-question-at-a-time forces the interview rhythm real interviews have — no info dumps.
Good output: An agreed requirements sheet with the load numbers that anchor every later decision.
Architecture with trade-offs spoken aloud
🟠 Claude
Now I'll propose my high-level architecture: [DESCRIBE YOUR DESIGN OR SAY "walk me through building it Socratically"]. Respond as the interviewer: for each component I name, ask WHY over the obvious alternative (SQL vs NoSQL, push vs pull, cache where?). Don't accept "for scalability" — demand the specific property that matters here. Keep score of trade-offs I articulate well vs. hand-wave.
Why this works: The 'don't accept scalability as an answer' rule trains the articulation interviews actually grade.
Good output: A dialogue where every design choice got defended — and a running list of your hand-waves.
Deep-dive drill
🟠 Claude
Pick the component in my design most likely to be probed in a real interview and drill it: data model, exact read/write paths, what's in memory vs disk, the specific numbers (can one node hold it? partition how?). When I answer, follow up twice more before moving on — interviews go 3 levels deep, so practice should.
Why this works: Three-levels-deep questioning exposes whether you know it or just know its name.
Good output: A component you can now discuss to the level of bytes and partitions.
Failure and scale drills
🟠 Claude
Run failure drills on my design, one at a time: the cache cluster dies, traffic 10x's during a launch, one region loses network, a celebrity user creates a hot key. For each: ask what breaks first, wait for my answer, then correct or extend it. End with the 3 changes that most improve resilience per unit of complexity.
Why this works: Failure drills are the highest-signal part of senior interviews and the least practiced.
Good output: A prioritized resilience shortlist and confidence discussing cascading failures.
Full mock with grading
🟠 Claude
Full mock: 35 minutes, [NEW SYSTEM]. You run it exactly like rounds 1-4 combined, timed pacing included ("we have 10 minutes left, let's discuss..."). Afterward grade me on the real rubric: requirements, high-level design, deep dive, trade-offs, communication — each 1-5 with the specific moment that earned the score, plus the ONE thing to fix before my real interview.Why this works: A graded mock with cited moments beats generic 'good job' feedback by a mile.
Good output: A rubric scorecard and one concrete, highest-leverage improvement.
Frequently Asked Questions
Is practicing with AI as good as mock interviews with humans?
It's 80% as good and 100x more available. Use AI for reps and drills, then spend your scarce human mocks validating under real social pressure.
Which system should I start with?
URL shortener or rate limiter first (they exercise the fundamentals), then one read-heavy feed system, then one write-heavy system like chat. This pack works for all of them.
ChatGPT or Claude for interview practice?
Both hold the interviewer role well. Claude sustains the one-question-at-a-time discipline over long sessions slightly better, which is why we verify against it.
Make this workflow yours
Remix this pack into your workspace — edit the prompts, track your runs, and never hunt for them in old chats again.