ElevenLabs Coding & DSA interview questions

The reported ElevenLabs live round, written in a shared Google Doc, no execution, no autocomplete. Inherited folder permissions plus permission-change timestamps, and the two-axis resolution rule that keeps the code to thirty lines.

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 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.

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 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 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.