OpenAI still asks you to design TinyURL. Mistral asks about mixture of experts.

Photo: Keawan A on Unsplash

60% of OpenAI's design questions are classic system design, like TinyURL. At Mistral AI, none are. Across 9 AI companies, 60% of design questions are about AI systems and ML.

• 60% of OpenAI’s design questions are classic system design, like TinyURL, YouTube and a payment system. At Mistral AI, 0 of 12 are.
• 60% of all design questions are about AI systems and ML. At Anthropic it is 71%.
• “Design a RAG system over company docs” comes up at 5 companies, more than any other design question; “Evaluate a new LLM before launch” at 4.
• LLM serving and GPUs is the largest AI theme: 13 of 60 AI design questions.
• 29% of design questions are asked in the technical screen, not only in design rounds.

OpenAI leans classic; Anthropic and Mistral AI lean AI

Each company’s design questions by type. Classic system design is the product kind (TinyURL, a chat app, a payment system); AI system design is serving, RAG and agents; ML design is models, training and evals. Cohere, Perplexity, Scale AI, Cursor (SpaceXAI) and Google DeepMind have fewer than 10 design questions and are left out.

5 companies ask the same RAG question

Design questions reported at more than one company. “Design a RAG system over company docs” comes up at Anthropic, Cohere, Perplexity, SpaceXAI (xAI) and OpenAI.

LLM serving and GPUs lead the AI questions

The 60 AI system and ML design questions, each counted once, by what they are about.

29% of design questions are asked in the technical screen

Design questions by the round they were asked in, where candidates said. The technical screen asks them too.

What this means for your prep

1. At OpenAI, prep classic system design as well as AI. 60% of its design questions are the classic kind.
2. Everywhere else, lead with AI systems. The largest themes: LLM serving and GPUs (13), evals and safety (10), training and post-training (9).
3. Practice the shared questions first: Design a RAG system over company docs, Evaluate a new LLM before launch, Design ChatGPT and Design an LLM inference serving platform.
4. At Mistral AI, know the model itself. Its questions cover mixture of experts, parallelism, normalization and optimizers.
5. Have a short design answer ready for the screen. 29% of design questions come up there.

   Methodology

   126 reports of 105 design questions (classic system design, AI system design and ML design) at 9 AI companies, 94 of them dated (Jul 8, 2025 to Oct 12, 2026). A question asked at two companies counts once for each. Themes come from each question’s tags, one theme per question. Rounds are counted where candidates named them (102 reports).

   Limits: reports lean toward software engineering roles, and smaller companies have few design reports. Companies with fewer than 10 are left out of the type chart.

   How we made this: Land the Lab counted the reports by company, type, round and theme. 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.