The 5 coding questions Anthropic keeps asking, and the round most people fail

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5 coding questions are reported at Anthropic more than any others, and each was asked again between Sep 18, 2026 and Oct 13, 2026. The round candidates say most people fail has no code.

• 5 coding questions are reported at Anthropic more than any others, and each was asked again between Sep 18, 2026 and Oct 13, 2026. A crawler, a cache, a file deduper: parts you would build at work.
• The coding round produces more reported questions than any other: 19 of 63. Python by default, no AI, and follow-ups on scale and parallelism.
• 21 of 29 design questions are about AI systems or ML. Inference serving and model distribution, written out in a shared document.
• Candidates and recruiters call the values round the one most people fail. It has no code.

Anthropic runs 8 rounds, and a weak first onsite day can cancel the second

The loop starts with a recruiter call and a 90-minute CodeSignal assessment built in levels. Then comes a 55-minute live screen. The onsite spreads over two days: coding and system design usually come first, then the hiring manager, the project deep dive and the values round. The second day only goes ahead after a good first one. Each round and its length:

4 of the 8 rounds put code or a design in front of you, and all 4 rule out AI by default. The screen lets you look up documentation and search the web. Some 2026 loops add a round where you write and review code with Claude Code; there AI use is expected.

The coding round produces more reported questions than any other round

We sorted Anthropic’s 72 reported questions by the round candidates named (n=63 with a known round). Coding leads with 19, ahead of online assessment (9) and ai system design (6).

The same 5 coding questions came back between Sep 18, 2026 and Oct 13, 2026

These 5, from the coding round and the screen, are reported at Anthropic more than any of its other coding questions. Every one was asked again in those weeks:

• Fix a function-cache key function, then make it durable, last asked Oct 13, 2026
• Concurrent same-host web crawler, last asked Oct 5, 2026
• Image transform pipeline with a wall-clock budget, last asked Oct 5, 2026
• Deduplicate files by size then content hash, last asked Sep 18, 2026
• Reconstruct call stacks from enter and exit traces, last asked Sep 18, 2026

One tier down, 3 more were asked in the same weeks:

• Banking system with transfers, cashback and account merges, last asked Oct 13, 2026
• Distributed mode and median across worker shards, last asked Sep 18, 2026
• Greedy longest-match tokenizer, last asked Sep 18, 2026

Each is a component you would build at work. In the screen, the base problem takes about a third of the hour. The rest is follow-ups: what happens at scale, whether the work is IO-bound or CPU-bound, and how you would run it in parallel. You write Python unless you ask otherwise, and you get no AI help.

21 of 29 design questions are about AI systems or ML

Anthropic’s design questions by type (n=29). The round lasts 55 minutes, and you may be asked to type the design into a shared Google Doc instead of drawing it. It grades your APIs, data model, request flow, how you handle the stated load, and at least one failure case. The prompts lean toward AI infrastructure: batched LLM inference API over GPUs, design an LLM inference serving platform, design a distributed AI model downloader and design an AI prompt playground.

The round most people fail has no code in it

The values round runs 60 minutes, and it can have two interviewers: one asks, one shadows. They want your considered views on AI’s effects on society and on Anthropic’s mission, how you handle ethical conflicts, and whether you change your mind for good reasons. The follow-ups go several levels deep, so a rehearsed story falls apart. Recruiters may send reading on AI safety before the onsite. Read it and form your own view.

The project deep dive sits on the second day too. You present a project you owned for about 20 minutes, and they probe it for the rest of the 60.

Anthropic’s own agents work 6 hours for each staff hour. Its interview still wants your judgment

Anthropic’s report on how employment is changing there (Oct 16, 2026) counts 6 hours of interactive AI agent work for every employee hour by August 2026. Hiring managers’ notes on technical candidates’ AI tool use have tripled since 2024. Read the loop with that in mind. The coding rounds check that you can build without help. The conversations check the judgment you would bring to work where agents do much of the typing.

What this means for your prep

1. Build the 5 components first, in plain Python and without AI: fix a function-cache key function, then make it durable, concurrent same-host web crawler, image transform pipeline with a wall-clock budget, deduplicate files by size then content hash and reconstruct call stacks from enter and exit traces. Then add the 3 from the next tier.
2. After each one works, make it concurrent. Practise saying whether it is IO-bound or CPU-bound and what changes at ten times the input.
3. Practise design in a document. 21 of 29 design questions are about AI systems; write the API, data model and one failure case in prose.
4. Prepare the values round like a technical one. Read Anthropic’s published writing on AI safety, decide where you agree and where you don’t, and be ready to defend it several follow-ups deep.
5. Pick your deep-dive project now and cut it to a 20-minute story you can be questioned on for the rest of the hour.

   Methodology

   72 questions reported at Anthropic, 55 of them with a last-asked date (newest Oct 15, 2026), 63 with a known round, taken Oct 19, 2026. “Reported more than any others” means the coding questions rated high or very high on how much candidates report them; the next tier is rated medium. The loop (rounds, lengths, formats, AI rules and what each round grades) comes from candidate reports and public guides, compiled in Land the Lab’s loop for Anthropic. The figures on agent hours and hiring-manager notes are Anthropic’s own, from its report.

   Limits: reports lean toward software engineering roles; research roles choose from a different menu of screens. We don’t publish counts per question, only the tier. Loops vary by team and level, and AI rules change.

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