{"slug": "what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported", "title": "What the Anthropic & OpenAI SWE interview loop is actually like (from 60+ reported accounts)", "summary": "An engineer synthesized over 60 publicly-reported first-hand accounts to compare the software-engineering interview loops at Anthropic and OpenAI. The analysis reveals that both companies have similar stage structures but differ in emphasis: Anthropic integrates values-awareness from the recruiter screen and includes a universal values round that often filters out technically strong candidates, while OpenAI front-loads team fit. Key technical preparation includes building data structures like in-memory key-value stores and LRU caches from scratch in Python, and candidates are advised to lead discussions and bake safety into designs.", "body_md": "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.\n\nI'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.\n\nThe 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.\n\n| Stage | Anthropic | OpenAI |\n|---|---|---|\n| Recruiter screen | Mission/values-aware from minute one | Background + which team is hiring |\n| First technical filter | CodeSignal OA, ~4 progressive levels (often waived for referrals/seniors) | CoderPad/HackerRank screen, or a 4–8 hr take-home |\n| Onsite | ~4–6 rounds: coding, system/AI-infra design, values (universal), deep-dive |\n~3–5 rounds: coding, system design, refactoring (senior), deep-dive, behavioral |\n| Design tool | Shared Google Doc | Excalidraw |\n| After | References + team matching (opaque) |\nHiring committee + org match |\n| Negotiation | Expected |\nTends to hold firmer |\n\nBe 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.**\n\nAlmost 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.\n\nIt'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.\n\n*I compiled the full ~105-page version — the master question bank, the values-round playbook, reconciled comp data, and a prep plan — grounded in the same 60+ accounts. The condensed field analysis is free here, and there's a free cheat-sheet on GitHub.*", "url": "https://wpnews.pro/news/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported", "canonical_source": "https://dev.to/frontierloop/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported-accounts-1c3g", "published_at": "2026-06-25 00:42:55+00:00", "updated_at": "2026-06-25 01:13:19.559461+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-safety", "ai-research", "developer-tools"], "entities": ["Anthropic", "OpenAI", "Dario Amodei", "CodeSignal", "CoderPad", "HackerRank", "Excalidraw", "GitHub"], "alternates": {"html": "https://wpnews.pro/news/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported", "markdown": "https://wpnews.pro/news/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported.md", "text": "https://wpnews.pro/news/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported.txt", "jsonld": "https://wpnews.pro/news/what-the-anthropic-openai-swe-interview-loop-is-actually-like-from-60-reported.jsonld"}}