@hackproduct9: "Design ChatGPT for 10M users." I watched a strong senior engineer fumble this question — not because they couldn't draw the boxes, but because they started with the GPUs. The model is one box. The product is everything around it. The story that works, in order: First, follow one user prompt end to end. Then scale that path to 10M users. Protect the front door before the GPUs. Separate context, routing, inference, and memory. Then add safety, traces, regions, and fallback. Why this matters beyond interviews: this is the exact architecture your AI coding assistant will sketch when you ask it to "build a chat app at scale." Knowing the 6 steps is how you read, evaluate, and debug what the machine produces — instead of trusting it blindly. Target to say out loud: 10M DAU, under 2s first token, under 5s p95, 99.9%+ availability. This is one of 600+ real scenarios on hackproduct.com — built for senior engineers, tech leads, and EMs targeting Staff+ or leadership roles. Try it free → hackproduct.com Which should we visualize next — Rate Limiter or URL Shortener? #HackProduct #systemdesign #aiengineering #softwareengineering #engineeringleadership #techlead #staffengineer #engineeringmanager #careeradvice #techcareer #chatgpt #llm #scalability #genai #codevisuals #coding #developer #buildinpublic #techleadership #engineeringculture

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