Technical screen: SQL + applied stats

The ~60-minute technical screen is where most candidates either look fluent with interaction data or look like they last wrote a window function from memory. Expect to query event and interaction tables live and to reason out loud about what makes a metric trustworthy. They watch your rigor as much as your final answer.

The data is shaped like Cursor's world: users, sessions, agent runs and tool calls, with retries, timeouts and heavy-tailed latency baked in. The skill on display is turning a fuzzy question into a precise, runnable query without hand-waving.

Before you type, say the metric definition out loud. The bar is that someone could run your query tomorrow and get the same number.

WITH final_attempts AS (
  SELECT run_id,
         user_id,
         DATE(started_at) AS day,
         latency_ms,
         ROW_NUMBER() OVER (
           PARTITION BY run_id
           ORDER BY attempt_no DESC
         ) AS rn
  FROM agent_runs
  WHERE status = 'completed'
)
SELECT day,
       COUNT(*) AS runs,
       PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY latency_ms) AS p95_ms
FROM final_attempts
WHERE rn = 1
GROUP BY day
ORDER BY day;