Yes. Leetcode-style interviews are dead, or close enough that treating them as your hiring bar is now a liability. It’s confusing, because algorithms still matter. The death came with AI. One prompt can solve the exact question you’re asking in seconds, which means the question stopped measuring what matters.

This isn’t a hot take anymore. It’s the consensus in most engineering orgs, just not always said out loud in the hiring loop itself. Because the implication means change, and change is hard.

Practically, yes. A candidate with a model open in another tab can produce a clean, working solution to almost any standard algorithm question in under a minute. That doesn’t mean the candidate is a strong engineer. It means the test stopped distinguishing strong engineers from anyone with access to a chatbot.

Leetcode-style interviews were already a weak signal before AI. They rewarded pattern memorization and interview prep, not day-to-day engineering ability. AI didn’t create that problem. It just made it impossible to ignore.

Three things broke at once:

The questions became trivially solvable. Once a model can one-shot the answer, the question tests tool access, not skill.

The skill being tested stopped mattering as much. Writing a balanced binary tree from scratch was never a daily task for most engineers. It’s mattering even less now that AI handles boilerplate and well-known algorithms without friction.

The gap it left didn’t get filled. Teams dropped leetcode-style rounds and didn’t always replace them with something that tests what matters now. Because knowing what to test is difficult, there was no standard replacement.

AI didn’t just make old questions easier to cheat. It changed what “good” looks like on the job.

Engineers today are expected to work with AI. That means the valuable skill shifted from “can you write this algorithm from memory” to something closer to: can you direct an AI tool effectively, verify its output, and know when it’s wrong.

That’s a different skill. It doesn’t show up on a leetcode-style test no matter how hard the question is.

Three things, tested as three distinct signals, not blended into one score:

Fundamentals. This hasn’t gone away. Someone still needs to reason about complexity, correctness, and tradeoffs at a basic level.

AI fluency. Can this person actually build using AI tools and agents. Not “have they used Copilot,” but can they direct an agent toward a real outcome, catch it when it’s confidently wrong, and course-correct without starting over.

Judgement. This is the one that matters most and gets tested least. Give a candidate a real problem with more than one reasonable approach. Watch how they reason through the tradeoffs. That reasoning process is much harder to fake than a memorized algorithm, and much harder to get from a model without the human steering it.

This is exactly the shift HackerRank’s Plan/Build/Review framework was built around. Plan surfaces how a candidate approaches a problem before they write a line of code. Build lets them work the way they actually work now, with AI tools present, not banned. Review probes the reasoning behind the decisions they made, not just whether the final output runs.

Paired with Chakra, HackerRank’s AI interviewer, that reasoning gets probed live, the same way a strong technical interviewer would push on a candidate’s thinking in a real conversation, at a scale no engineering team could staff on their own.

Leetcode measured whether someone remembered the right pattern. What replaces it needs to measure whether someone can think clearly with AI as part of the job, not in spite of it. That’s a harder thing to test. It’s also the only thing worth testing now.