What the Anthropic & OpenAI SWE interview loop is actually like (from 60+ reported accounts)

FrontierLoop — Thu, 25 Jun 2026 00:42:55 +0000

Independent and unofficial. Synthesized from publicly-reported, first-hand candidate accounts (2024–2026). Not affiliated with, authorized by, or endorsed by Anthropic, OpenAI, or any company named. Treat stage structure as well-corroborated and all numbers as directional self-report.

I've been collecting publicly-reported, first-hand accounts of the software-engineering interview loops at Anthropic and OpenAI. The patterns are consistent enough to be worth writing down.

The loop, stage by stage

The two loops rhyme but emphasize different things — Anthropic is values-aware from the recruiter screen; OpenAI front-loads team fit. The single most consistent finding: a values / culture round appears in essentially every Anthropic onsite, and it fails more technically-strong candidates than any coding round.

Stage	Anthropic	OpenAI
Recruiter screen	Mission/values-aware from minute one	Background + which team is hiring
First technical filter	CodeSignal OA, ~4 progressive levels (often waived for referrals/seniors)	CoderPad/HackerRank screen, or a 4–8 hr take-home
Onsite	~4–6 rounds: coding, system/AI-infra design, values (universal), deep-dive	~3–5 rounds: coding, system design, refactoring (senior), deep-dive, behavioral
Design tool	Shared Google Doc	Excalidraw
After	References + team matching (opaque)	Hiring committee + org match
Negotiation	Expected	Tends to hold firmer

Five things that surprise strong candidates

AI tools are banned in live rounds. Anthropic enforces it hardest and reportedly detects test-gaming. Prep with AI; never solve with it live.
Coding is build-from-scratch, not LeetCode. You implement a small system and extend it under observation — algorithm trivia won't save you.
System design is AI-infra-flavored and math-first. Do the capacity math early and let it drive the design — then keep it simple. Over-engineering is the most-reported design failure.
The values / culture round is the #1 filter at Anthropic. It rewards genuine, specific, skeptical thinking; scripted "STAR" answers and flattery backfire.
The question bank is small and well-known — so interviewers perturb problems to test whether you can operate, not just recall.

Coding: the known families

Be fluent building these from scratch in Python (a real edge): an in-memory multi-level key-value store, a web crawler, an LRU cache, a stack-trace / sampling-profiler problem, a tokenizer, a distributed mode/median exercise. Knowing them is table stakes; surviving the perturbation is the test.

System design: the one rule

Almost verbatim across sources: do the math first; design the simplest system that meets the stated numbers; bake safety/limits into the request flow; lead the discussion yourself. Anthropic prompt themes are infra-shaped (serving LLMs, token services, retrieval, agents); OpenAI leans more product-shaped.

The values round, and how to prep

It's reflective and probing — "a time your values were tested," "a belief you changed," "a genuine critique of the company." Follow-ups probe your reasoning and honesty, not tidy outcomes. Candidates who pass build a few true stories only they could tell, form a real point of view on AI safety, and read the primary sources (Core Views on AI Safety, the Responsible Scaling Policy, Dario Amodei's essays) to engage critically — not memorize.