Live coding stopped telling interviewers what it used to, and most candidates haven't updated their prep. The round didn't get easier. The signal got cheaper to fake, so the rounds that survived got harder in ways your old practice doesn't cover. Here's how the split actually breaks down by company size, and what it changes about how you prep this quarter.
For two decades a candidate who could solve a problem on a shared screen was demonstrating something real in the moment. In 2026 that demonstration comes with an asterisk, because the person watching can no longer assume the candidate is the one doing the thinking.
Why live coding lost its signal
A coding interview was always a proxy. It assumed that watching someone solve a problem told you how they'd perform on the real work, and that proxy held as long as one condition was true: the candidate in front of you was the one doing the thinking. Yusuf Aytas, an engineering leader who interviews from the panel side, put it directly in his essay AI Broke Interviews: "The candidate sitting in front of you was the person actually doing the thinking. That assumption is now gone." Once it's gone, a clean solution no longer separates the strong candidate from the one with a good assistant and a second monitor.
The data on how often that happens is no longer anecdotal. CodeSignal, which runs technical assessments at scale, reported that the rate of flagged cheating attempts more than doubled in 2025, rising from 16 percent in 2024 to 35 percent in 2025. For entry-level assessments it went from 15 percent to 40 percent. The most common flags were off-screen referencing and answer similarity, the signatures of someone reading from a second source.
interviewing.io ran the survey that quantifies the interviewer side. In its 2025 report, How is AI changing interview processes, founder Aline Lerner found that 81 percent of FAANG interviewers suspected a candidate of using AI during an interview, about 31 percent had caught someone, and 75 percent believed AI assistance was letting weaker candidates pass rounds they shouldn't. When three out of four interviewers think the round is passing people who can't do the work, the round is no longer doing its job.
The shift splits by company size
"Coding rounds are being replaced" is not what the people running those rounds say is happening. In the same interviewing.io survey, of the 52 respondents at FAANG companies, zero said their company had moved away from algorithmic coding questions, and half expected a partial return to in-person coding specifically to close the AI gap. The shift is two different responses depending on who's hiring.
Large companies are defending the coding round. They're adding proctoring, bringing interviews back on-site, and adjusting questions to be harder to solve with a hidden assistant. Gergely Orosz, in The Pulse, reported that 58 percent of interviewers had changed their questions to counter AI use. Some are going the other way entirely and inviting AI into the room. Orosz noted that Shopify's head of engineering, Farhan Thawar, wants candidates using AI tools through most of the interview, on the theory that the real skill now is directing the tools well.
Smaller companies and teams that never had the volume to run a heavy coding gauntlet are the ones actually reweighting toward behavioral and work-sample rounds. Brian Jenney, a senior engineer who has designed interview loops, wrote in Coding Interviews in 2026 Are Harder Than Ever that "as coding becomes less and less of a reliable proxy for how well someone can do the job, companies are leaning harder on behavioral signals." His blunter point is the one that explains why: "Most people don't get fired because of technical errors. They get fired because of human and behavioral errors."
What behavioral rounds screen for now
When a hiring manager leans harder on the behavioral round, they're not looking for polished stories. They're looking for evidence of the things that determine whether a hire works out after the offer, and those are exactly the things a coding score never captured.
Three signals do most of the work. The first is judgment, meaning what you chose to do when the right answer wasn't obvious and what you traded off to do it. The second is ownership, meaning whether you talk about outcomes you were responsible for or activities you participated in. The third is how you handle being wrong, because a candidate who can describe a decision that didn't work and what they changed is showing the one trait that survives contact with a real job. The rounds that test these are getting harder to script. Interviewers follow up more, push on the specifics, and change a constraint to see whether you're reasoning or reciting.
How to split your prep for Q3 2026
If you're aiming at a large tech company, the coding round is still standard and under more scrutiny than it was a year ago. Strong code alone no longer clears the bar, and your prep should reflect the split.
Keep coding sharp, but practice out loud. Solve problems while narrating your reasoning, because the interviewer is now listening for the thinking they can no longer assume. Silent, correct solutions read worse than they used to.
Prepare real stories, not story-shaped answers. Have four to six examples ready, each with a specific decision you made, a tradeoff you accepted, and an outcome you can name. Include at least one where the call was wrong, because that's the one good interviewers probe for.
Get reps on the rounds AI can't fake for you. System design and live debugging both reward understanding over recall, and both are getting more weight precisely because they're hard to outsource in real time.
Expect a round built to break your script. Somewhere in the loop, usually in a behavioral or design conversation, someone will keep asking "why" until the prepared answer runs out. That moment is the interview now. Treat it as the point, not the part to survive.
