2 min lesson

Technical phone screens (the “2-3 short technicals”)

Use the lesson to respond to this: "AI tools are allowed in the technical screens. What's the fastest way to fail one anyway?" Keep the answer plain.

Each screen is roughly an hour: one medium-hard problem in TypeScript, Rust or Python, usually paired with a short design discussion. AI tools are allowed and expected - and the moment you submit something you can't explain, you fail.

Use this stage map to decide what evidence belongs in each round. Memorizing the order is the shallow version. For every stage, prepare one artifact, one story and one question that shows how you reason in the role.

These problems carry a systems flavor rather than pure algorithm puzzles. Think streaming, concurrency and the messy realities of talking to provider APIs, not balanced-tree trivia.

Likely problem shapes

Stream and parse SSE token output from a model API.

A rate limiter (token bucket) or concurrency limiter.

Retry with backoff, jitter and a budget.

Parse and normalize differing provider response formats.

What's graded

Correctness and edge-case handling under failure.

Tradeoffs narrated out loud as you code.

Clean use of AI: you accept, reject and explain.

Fluency in your chosen language's concurrency model.

1Restate and bound the problem. Confirm inputs, failure modes and what “done” means before writing code.
2Sketch the approach aloud. Name the data structure and the complexity and call the edge cases you'll handle (timeouts, partial reads, retries).
3Use AI as a fast typist, not an oracle. Prompt for a scaffold, then read every line, test an edge case and reject what's wrong out loud.
4Handle the failure path explicitly. A retry without a budget, a stream without a timeout, a limiter without fairness - name and close these.
5Verify before you claim done. Walk a concrete input through, including one that breaks the naive version.

Learn more

Full explanation

The shape of a 'good' answer

The shape of a 'good' answer: retry with jittered backoff + budget, not a naive loopts

async function withRetry<T>(
  fn: () => Promise<T>,
  opts: { maxRetries: number; budgetMs: number },
): Promise<T> {
  const deadline = Date.now() + opts.budgetMs;
  let attempt = 0;
  for (;;) {
    try {
      return await fn();
    } catch (err) {
      attempt++;
      if (attempt > opts.maxRetries || Date.now() >= deadline) throw err;
      const base = Math.min(1000, 50 * 2 ** attempt);
      const jitter = Math.random() * base; // full jitter avoids retry storms
      await sleep(Math.min(jitter, deadline - Date.now()));
    }
  }
}

Interview move

When the AI hands you code that looks right, say “let me verify this before I trust it,” then test one edge case out loud. Catching a real flaw and fixing it is a stronger signal than code that happened to work. The screen grades judgment over recall.

The instant-fail

Submitting raw model output you can't walk through line by line ends the screen. The role demands you understand every line you ship to a hot path; the interview is a direct test of that. If you don't understand a suggestion, say so and reason it through rather than pasting it.

Technical phone screens (the “2-3 short technicals”)

Step 1 of 2

The shape of a 'good' answer