Interview Tool
Timer, structure reminders, and algorithm reference for AI/infra interviews.
Timer
You'll be reminded to summarize every 5 minutes.
Approach Framework
Before coding, consider 2–3 of these axes. State your tradeoffs out loud.
Time vs. Space
Can you trade memory for speed? Memoize, cache, precompute, or use a hash map to drop from O(n²) to O(n).
Simple vs. Production
Brute force first — prove correctness. Then optimize. Mention what a prod solution would add: error handling, distributed considerations, scaling.
Eager vs. Lazy
Compute upfront or on-demand? Lazy evaluation can avoid work for sparse access patterns. Eager is simpler and often faster for dense use.
Iterative vs. Recursive
Recursion is elegant but risks stack overflow at scale. Iterative with explicit stack is safer for production. Mention both.
Greedy vs. Optimal (DP)
Greedy works when local optimal = global optimal. Otherwise you need DP or exhaustive search. Can you prove greedy is safe?
Online vs. Offline
Can you sort/preprocess the input? Offline (process all data at once) often enables better algos than online (streaming) constraints.
Summarize Checklist
Every 5–7 minutes, quickly hit these points aloud.
What problem am I solving? (restate briefly)
What approach am I taking and why?
What's the time/space complexity?
What edge cases have I considered?
What would I do differently in production?
What's left to implement or test?
Algorithm Reference
Click any pattern to see when to use it and the key implementation note.