xAI Coding & DSA interview questions

Everyone knows the sort + two-pointer outline. The interview is actually about duplicate handling: three separate skip conditions that candidates routinely botch live. Here's the clean version and the narration that goes with it.

The single most-asked design-a-data-structure question in FDE loops. There's an interview-legal Python shortcut and a from-scratch version, and knowing when to offer which is half the grade.

The canonical grid question, and the template for every flood-fill, shortest-path, and region-labeling variant FDE loops throw at you. BFS vs DFS vs union-find: here's which to write and which to merely mention.

The follow-up to number-of-islands, and the question where candidates reveal whether they understand WHY BFS finds shortest paths. Plus the two variants (weights, eliminating obstacles) that decide hard-screen outcomes at xAI.

The third member of the grid trilogy, and the one that tests backtracking discipline: marking, unmarking, and the early-exit pruning that turns a timeout into a pass.

Exact-match pub/sub is a dict of lists. The round is decided at level two (wildcard matching on hierarchical topics) and at level three, when the interviewer asks what happens when a subscriber's callback throws.

Kahn's algorithm gets you level one. The round is won at level three, where 'run up to K tasks at once' breaks naive topo sort, and the indegree bookkeeping you chose at L1 either saves you or sinks you.

The OpenAI FDE signature question, reported near-verbatim for two years: four levels in ~60 minutes, where L4 silently breaks every naive L3 implementation. The lazy-expiry design that survives all four levels, with the pacing plan.

The most common screen opener, and interviewers use it to check whether hashmap thinking is reflexive. Here's the one-pass answer, the narration that earns points, and the duplicate-handling edge case most candidates fumble.

The interval pattern shows up everywhere in FDE loops: calendars, flight segments, log windows. Master the sort-then-sweep idiom here and three other interview questions fall out for free.

Top-K is the most reused primitive in FDE interviews: it reappears inside log parsers, analytics questions, and retrieval ranking. Three solutions exist; knowing which one to lead with is the real test.

A 5-minute warm-up that quietly tests the most useful idea in practical coding: choosing a canonical key. The sorted-string vs character-count tradeoff is exactly what interviewers want to hear you reason about.

The gentlest 'design a class' question in FDE screens, and the warm-up interviewers use before rate limiters and sessionization. The deque trick is easy; the API and time-window follow-ups are where the signal is.

A verbatim-reported multi-part at OpenAI and Anthropic. Each level breaks the previous design on purpose: the burst-at-the-boundary flaw is planted, and naming it before the interviewer does is how you win the round.

The coding question that doubles as a RAG-fundamentals check. Greedy packing is easy; the oversized-sentence case, the overlap-progress trap, and the tests you write unprompted are what AI-lab interviewers actually score.

A confirmed Anthropic live-coding question that looks exotic and reduces to one operation: diff consecutive call stacks against their common prefix. The recursion edge case is where strong candidates separate from finished-but-wrong ones.

The follow-up interviewers reach for when merge-intervals goes too smoothly. The three-phase scan is elegant, but only if you've internalized the overlap condition most candidates have to re-derive under pressure.

Looks like a sliding-window problem; isn't one. The prefix-sum + hashmap trick that solves it is the same idea behind sessionization and cumulative-metrics questions later in the loop: learn it once, reuse it three times.

Anthropic-style screens open with deceptively simple builds like this, then extend them three times. The grade isn't the counting; it's whether your first version survives the extensions without a rewrite.

K-way merge is the algorithm behind log aggregation, search-result merging, and LSM trees, which is exactly why FDE loops keep asking it. The heap version is table stakes; the tie-breaking detail is where candidates crash.

A tree question that's secretly a format-design question, which is why FDE loops love it. The preorder-with-null-markers trick is clean, but the delimiter and malformed-input follow-ups are where offers are decided.

The Palantir coding-screen classic. It looks like merge-intervals but needs a different weapon, the sweep line, and the boundary-tie detail decides whether your answer is right or off by a planeload.

The quintessential FDE practical: messy real-world input, grouping, ranking, and a hidden rubric line for how you treat malformed data. Most candidates parse happily and lose the round on the lines that don't parse.