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Tell me about scaling a system by ten times. What broke, and in what order?

The interesting content is the order things broke in, because that order is a property of the system and it repeats. What breaks first at each scale step, why the control plane usually goes before the data plane, and the thing you would skip if you did it again.

Updated Sep 2026 · Grounded in real AI infrastructure interview loops and written to a senior-engineer editorial bar, with every number worked and every diagram hand-built.

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The concepts behind this question

Ranked by how closely each one overlaps this question's topic, so the first card is the thing to read if the answer above moved too fast.

Foundational

🧭 Ownership & Judgment

Mentoring and Growing EngineersMentoring on an infrastructure team happens mostly under pressure, during incidents and reviews, where the instinct to take the keyboard resolves the problem faster and teaches nothing. The method that works is the mentee driving while the mentor asks questions, with a takeover condition agreed in advance so nobody negotiates it at two in the morning. It costs time, and choosing which situations can absorb that cost is the judgment being assessed.

Advanced

🧭 Ownership & Judgment🔒 Premium

Migrations and DeprecationsEvery infrastructure career contains a migration nobody wanted: the scheduler swap, the driver upgrade across a live fleet, the storage move while training runs are in flight, the deprecation of the launcher every team's scripts depend on. The behavioral round asks about one because it tests the skills that matter most and show least on a résumé: sequencing under risk, keeping a rollback real, moving people who have no reason to move, and knowing when to stop. This page gives the shape of a migration story that lands, two worked narratives from GPU fleet work, and the answers that sound like leadership and fail.

Foundational

🧮 Napkin Math & Capacity

Training FLOPs: 6NDThe compute needed to train a language model is six floating-point operations per parameter per token: two for the forward pass and four for the backward. Multiply by the parameter count and the token count and you have the whole run's compute, which is the number every fleet-sizing, time-to-train and cost question starts from. This page derives the 6, states the attention correction and when it matters, and shows where the 2N of inference comes from, so the reader can rebuild the formula rather than recall it.

Foundational

🧭 Ownership & Judgment

Talking About Cost and Capacity with LeadershipInfrastructure engineers are asked to justify large numbers to people who do not share their vocabulary, and the conversations go wrong in predictable ways: a technical objection with no alternative, a forecast with no assumptions, or a cost quoted in a unit the listener cannot act on. What works is a small number of costed options, a stated recommendation, the decision needed by a date, and every figure expressed in whatever the listener actually controls.

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UP NEXT ON YOUR JOURNEY

Next in this trackLeadership wants to buy another 2,000 GPUs. You think it is the wrong call. What do you do?Next in this trackA vendor says your configuration is the problem. You think it is their firmware. How do you proceed?Next in this trackHow do you bring a junior engineer through their first serious incident?

FEDITOR'S NOTE

Scored on describing failures in the order they appeared rather than as a list, on the control plane breaking before the data plane, and on naming what the candidate would skip next time.

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