Anthropic 系統設計題 72% 涉及 AI 或 ML，OpenAI 62% 為傳統題型

Photo: Lucas Kepner on Unsplash

21 of Anthropic's 29 reported design questions are about AI systems or ML, against 19 of OpenAI's 50. The one reported the most is a batched LLM inference API over GPUs, last asked Oct 15, 2026.

• 21 of Anthropic’s 29 design questions are about AI systems or ML. At OpenAI it is 19 of 50.
• The one reported the most is a batched LLM inference API over GPUs, last asked Oct 15, 2026. 3 of the 5 reported the most are AI infrastructure.
• The round runs 55 minutes, with no AI, and you may type the design into a shared document. It grades APIs, data model, request flow, the stated load and at least one failure case.
• 5 of the 22 with a known round come from a design review, where you critique a design instead of drawing one.
• 7 design questions are reported at both Anthropic and OpenAI. Prep those first if you are in both loops.

The design round runs 55 minutes, and you may write it instead of drawing it

Anthropic’s system design round usually comes on the first onsite day, with coding. A weak first day can cancel the second, so this round decides whether you get to the hiring manager and the values round. It runs 55 minutes with no AI help. You may be asked to type the design into a shared Google Doc instead of drawing it. Some interviewers let you share any drawing tool, but practise writing a design as text.

The round grades five things: your APIs, the data model, the request flow, how you handle the load they state, and at least one failure case. Managers may review a design doc with you instead, and some loops run two design rounds on the team’s own domain. The rest of Anthropic’s loop is in our post on its coding questions and values round.

21 of 29 design questions are about AI systems or ML

We counted every design question reported at Anthropic (n=29): AI system design, ML design and classic system design. AI systems lead with 12. Only 8 are the classic kind you find in a system design book. 5 carry a GPU tag: batched LLM inference API over GPUs, design an LLM inference serving platform, design a distributed AI model downloader, matmul performance modeling on a fixed GPU and design a GPU scheduling platform.

5 of the 9 ML design questions come from a take-home, a practical round or the screen, not from the design round. If you are interviewing for a software engineering role, the AI system questions are the ones to drill.

The 5 reported the most were all asked again since Sep 11, 2026

These 5 are reported at Anthropic more than any of its other design questions, the most reported first:

• Batched LLM inference API over GPUs, last asked Oct 15, 2026
• Design an AI prompt playground, last asked Oct 13, 2026
• One-on-one chat system with presence and offline queue, last asked Oct 13, 2026
• Design a distributed AI model downloader, last asked Oct 5, 2026
• Critique a design doc from the team's backlog, last asked Sep 11, 2026

3 of the 5 are AI infrastructure. The classic one is a one-on-one chat system with presence and offline queue, a question any company could ask. The fifth asks you to critique a design doc from the team's backlog, which means pulling apart someone else’s design. In all, 9 of Anthropic’s design questions were asked since Sep 1, 2026.

Only 11 of 22 come from the design round itself. 5 come from a design review

Anthropic’s design questions by the round candidates named (n=22 with a known round). The design round produces 11. A design review, where you read a design and critique it, produces 5. Besides critique a design doc from the team's backlog, the reviews cover usage billing for an LLM API, rolling out a new model version, checkpointing a large training run and an eval gate for model launches. The rest come from the screen, practical coding and take-homes.

A review tests the same judgment from the other side. Practise reading a design doc and naming what breaks first, what it costs, and what you would ask the author.

OpenAI’s mix runs the other way. 31 of 50 are classic

OpenAI has 50 reported design questions to Anthropic’s 29, out of 144 questions of any kind to Anthropic’s 72. The share is what differs. 72% of Anthropic’s design questions are AI or ML, against 38% of OpenAI’s. OpenAI’s most reported design questions are design an online chess game, design a payment system and design a video generation service on a scarce GPU pool. Our OpenAI post covers its loop.

7 design questions are reported at both labs: design an AI prompt playground, design an LLM inference serving platform, evaluate a new LLM before launch, design ChatGPT, design a Slack-like chat system, design a RAG system over company docs and design a GPU scheduling platform. If you are in both loops, start there. Our post on AI lab design questions compares nine companies.

What this means for your prep

1. Start with the 3 AI infrastructure questions reported the most: batched LLM inference API over GPUs, design an AI prompt playground and design a distributed AI model downloader. 21 of 29 design questions are about AI systems or ML, so a classic-only prep leaves most of them uncovered.
2. Practise in a plain document, 55 minutes on the clock and no AI. Write the API, the data model, the request flow, the load and one failure case.
3. Keep one classic design ready, starting with a one-on-one chat system with presence and offline queue. Only 8 of Anthropic’s 29 design questions are classic, but one of them is among the 5 reported the most.
4. Practise reviewing a design. 5 of 22 questions with a known round come from a design review.
5. In both loops? Do the 7 shared questions first, then OpenAI’s classic set.

   Methodology

   29 design questions reported at Anthropic and 50 at OpenAI (AI system design, ML design and classic system design), 61 of them with a last-asked date (newest Oct 16, 2026), taken Oct 19, 2026. 22 of Anthropic’s have a known round. “Reported the most” means rated high or very high on how much candidates report them. A question counts as AI or ML when it is an AI system or ML design question; a GPU tag is one of the topic tags we give each question. The round (length, format, AI rule and what it grades) comes from candidate reports and public guides, compiled in Land the Lab’s loop for Anthropic.

   Limits: the sample is small. 7 of Anthropic’s design questions have no known round, and 11 have no last-asked date. Reports lean toward software engineering roles. We don’t publish counts per question, only the tier. Loops vary by team and level.

   How we made this: Land the Lab counted the reports by type and round. The charts are generated from that data; the text was drafted with AI and checked against it.

Originally published at landthelab.com, where every company's interview loop is mapped round by round.