The Real Cost of Getting Hired
A developer just shared their LeetCode stats: 712 problems solved, 1,030 submissions, 325 active days, 124-day maximum streak. The post reads like a productivity meditation. The subtext is more interesting.
This is what getting through a FAANG screening round looks like in 2025. Not the only path, but a common one. Roughly 90% of big tech roles filter candidates through timed algorithm challenges. The pattern is well-established: solve 500-700 problems, focus on medium difficulty (this developer hit 455), learn to recognize patterns faster than you can derive solutions from first principles.
Where Candidates Actually Fail
The developer notes that most people quit between 400-600 problems, not because the questions get harder, but because daily practice over months requires discipline most don't maintain. That tracks with what we see in hiring pipelines. Technical skill is table stakes. The filter is sustained effort.
The time investment is non-trivial. One developer's account of preparing for Microsoft: 500+ problems while working full-time, targeting 15 minutes for easy problems, 20 for medium, 40-50 for hard. A recent GitHub repo (8 stars, updated June 2025) documents C++ solutions to 500+ problems. These aren't exceptional cases.
The Contrarian Take
Not everyone agrees volume matters. A growing number of prep guides argue that targeted practice covering core patterns (sliding window, binary search, monotonic stacks) hits 90% of interview questions without requiring 500+ solves. The emphasis shifts from streak maintenance to efficient pattern recognition.
The developer claims solving algorithms improved their backend thinking, citing a /leaderboard API optimization from 200ms to 20ms. Maybe. Or maybe correlation isn't causation and time complexity awareness comes from production systems, not puzzle-solving.
What This Means for Hiring
If your enterprise is competing for the same talent pool as big tech, understand the entry cost you're asking candidates to pay. They're spending months on LeetCode before they apply. Some of that filters for problem-solving ability. Some of it just filters for people with time.
Worth asking: does your role actually need someone who can invert a binary tree under pressure, or do you need someone who can optimize database queries and ship reliable code? The interview and the job aren't always aligned.