I bombed my first Anthropic loop. A former coworker at a different AI lab walked me through what I should have known going in, and a few weeks later I had offers from both Anthropic and OpenAI. This post covers what changed on the second try.
The coding round is ninety minutes and nothing like classic whiteboard problems. They told me to build a key-value store. SET GET DELETE to start, then filtered scans, then TTL expiration with timestamps, then file persistence with compression. Four stages, each one stacked on the last, and my interviewer kept tacking on constraints the second I finished a stage, like a coworker who keeps changing the spec on you mid sprint.
Drove me insane. She said her OpenAI screen ran the same way, one hour building something real. OpenAI also does this deep dive thing where you present a system you built and they rip apart every choice you made.
The part that wrecked me in coding was not the problems. It was talking through my approach. You cannot do that when you have ninety minutes and someone watching you and adding requirements every fifteen minutes. On my second attempt I forced myself to slow down. I would repeat the question back in my own words and build a few example inputs before writing anything.
She drilled me on this, she would stop me mid sentence and go "ok but what are the corner cases" and I would have to think about it out loud. I started outlining my approach and thinking about complexity before touching the keyboard, even confirming with the interviewer that the direction seemed reasonable before I started typing, then writing slowly and debugging with my own examples after. It felt painfully slow in practice but it actually made me faster, because I stopped going down wrong paths and having to rewrite everything.
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Try InterviewMan FreeSystem design. Forget everything you studied for FAANG system design because none of it applies here. Nobody asked me to design a URL shortener, I WISH they had asked me to design a URL shortener. Nobody asked about a chat service. Anthropic wanted me to design inference serving infrastructure for millions of requests while keeping GPU usage high with different model sizes, so we are talking batching, KV cache memory management, routing to the right instance, and how latency compounds through a transformer pipeline.
My interviewer had BUILT their serving stack. Like he personally wrote the thing. He knew within two minutes that my prep came from generic YouTube videos. She warned me about this too, her OpenAI system design was scaling inference and the interviewer there also had hands on experience with the actual production system. You need to have actually worked on this stuff.
I had touched serving infrastructure at a previous job which saved me, but I still needed a couple weeks to organize what I knew into something I could talk about without rambling for twenty minutes. Pro tip, if you need a distributed queue and never touched one, just call it "distributed queue". Do not dig yourself into details you cannot defend.
So I ran InterviewMan during my second Anthropic attempt and on some OpenAI mocks. On the coding challenge the tool caught that I forgot to check TTL on reads before moving to the next level, exactly the kind of thing I would have missed because I was focused on getting to stage four. During the safety round it fed me alignment talking points and I answered the tool use and hallucinations question without freezing this time.
On system design it caught GPU usage and batching as the core topics before my interviewer had finished the prompt. I checked dock, process list, Activity Monitor on Zoom and Replit and CodeSignal. Nothing. Twelve dollars a month on annual, one forty four for a year, no session caps, 57,000 users on the public counter, 4.8 stars from 257 reviews, more than twenty stealth features built in.
Interview Coder at two ninety nine does coding only which is useless for the safety round and system design that account for maybe half your score at these places. The closest wider read on the category is the InterviewMan vs Interview Coder 2 comparison.
Behavioral is the part most people get wrong because it is not really behavioral. Anthropic sent a values doc before the interview and they expected me to have read it. The first question was what failure mode of LLMs worried me most, and the follow up was what changes when you give an agent tool use. STAR did not help me, and my behavioral stories about team conflicts went nowhere. They want to know if you actually care about what your code does after you ship it. OpenAI tests for this too.
Timeline stuff since people always ask. Anthropic took about three weeks from recruiter call to answer. She said OpenAI took six weeks which almost killed her. Anthropic splits the final round into two separate half day sessions, two or three rounds each. OpenAI does one long day. Ghosting between stages is normal at both. Recruiters are buried. If you get an offer ask for thirty to forty five minutes with one of the interviewers, have a meeting just for asking questions, listen carefully because at that point they are selling you.
I am sure there are a lot of other opinions about using AI in real loops. My focus on this post was mainly the frontier lab side, on real rounds, not on hypothetical ones. It worked for me. It doesn't mean it will work for you.
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