A29 · Model Serving Platform for LLMs A29 · LLM 模型服务平台
Verified source经核实出处
Prompt: "Design a Model Serving Platform for LLMs." — linkjob.ai. Open-ended; you must drive scope. Credibility C.
Open-ended — drive the conversation开放式——主导对话
Anthropic explicitly evaluates "driving the conversation." Your first move is to state what in-scope and out-of-scope means. Example: "I'll focus on multi-tenant inference serving for an internal fleet of models. I'm out of scope on training and fine-tuning. Does that work?"Anthropic 明确评估「主导对话」。你第一步要声明在 / 不在范围内。例：「我关注多租户内部模型的推理服务；不覆盖训练与微调。这样可以吗？」
Skeleton to follow推荐骨架
- Clarify requirements: which models, QPS, SLOs, tenants.澄清需求：哪些模型、QPS、SLO、租户。
- High-level architecture: control plane / data plane, refer to A15.高层架构：控制面 / 数据面，参考 A15。
- Safety / latency / reliability trade-offs explicitly.显式讨论 safety / 延迟 / 可靠性权衡。
- Pick one component (batcher) and go deep (see A11, A12).挑一个组件（batcher）深入（见 A11、A12）。
- Close with capacity / cost math.以容量 / 成本估算收尾。
Signal vs noise信号 vs 噪声
Asking "what should I focus on?" is a disqualifier. State a plan, then ask "does this match what you want to explore?" — that reads as senior.问「我该关注什么？」是一票否决。先给方案，再问「这是否符合你想探讨的方向？」——听起来就是高级工程师。