Best ChatGPT Prompt for Technical Interview Prep
For coding rounds, system design, and the behavioral round most engineers underprepare for.
The Prompt
You are a senior engineer who has conducted 300+ technical interviews at FAANG-tier and Series-B companies. Help me prep for an upcoming interview. Company: [COMPANY NAME or type — e.g. “mid-stage B2B SaaS”] Role: [Senior backend engineer / Staff infra / EM / etc.] Round type: [coding / system design / behavioral / take-home / live debugging / leadership] My background (one paragraph): [LANGUAGES, YEARS, RECENT PROJECTS] What I'm worried about: [SPECIFIC WEAKNESS — dynamic programming, distributed systems, leading without authority, etc.] Time I have to prep: [DAYS / HOURS] Requirements: - Treat this as an actual interview, not a lecture - For coding: give me a problem at the right difficulty, wait for my solution, then critique it the way an interviewer would (not just “here's the answer”) - For system design: ask the clarifying questions a strong candidate would ask, then push back on my answer the way a strong interviewer would - For behavioral: ask the actual question, let me answer, then tell me what would have scored higher and why - Focus on the SPECIFIC weakness I named — don't drift into general advice - If my answer is good, say so plainly; don't pad with “great answer!” if it wasn't
How to Use This Prompt
- Pick the round type you're worried about — don't try to prep all four in one session
- Be specific about your background — the model will calibrate the difficulty
- Name the specific weakness — “I always over-explain in system design” gets better feedback than “system design”
- Paste into ChatGPT or Claude — treat it as a live interview, not a Q&A
- Run 3-5 rounds in a session, not 1 — the second and third rounds are where the patterns show up
The biggest gain from practice interviews is noticing your own patterns — you always over-explain, you never ask about scale, you skip the test cases. After 5 mock rounds you'll see the pattern; after 1 you won't.
Example Output
Task: System design mock for a senior backend role
Response:
Question: Design a URL shortener. Assume 100M URLs created per day, 10B reads per day, global latency target p99 under 100ms. Before I let you start — what clarifying questions would you ask me? [after candidate answers] Good catch on the read/write ratio. You didn't ask about: - Custom aliases vs auto-generated - Expiration / retention - Analytics (do we track click counts?) These materially change the data model. A strong candidate asks 4-6 clarifiers before drawing anything. You asked 2. Now — sketch the high-level architecture. I'll push back on each piece. [after sketch] Your write path uses base62 encoding of an auto-incrementing ID. Two pushbacks: 1. The auto-increment is a bottleneck at 100M writes/day across regions. How do you avoid coordinated ID generation? 2. Base62 of a sequential ID leaks volume to anyone scraping. Is that OK? What's your answer?
Tips to Get Better Results
- Don't ask for the answer. Ask the model to interview you. The difference between practice and study is huge.
- Specify the weakness. “I freeze on hash-table problems” gets you 10 hash-table problems with feedback. “Coding” gets you generic advice.
- Stay in the role. If you blank, don't ask for the answer — ask “what would a hint look like?” That's what real interviewers offer.
- Run a debrief. After each mock, ask “what patterns showed up across these 3 rounds?” The patterns are what cost real offers.