“Magic to Defeat Magic”: AI Cheating Tools Have Torched Tech Interviews—and Made One Founder a Millionaire
The silent panic gripping Silicon Valley recruiting teams has reached a breaking point. Technical interviews, once the gold standard for vetting elite engineering talent, are crumbling under the weight of invisible AI accomplices. At the heart of this rupture lies a 21-year-old college dropout and a piece of software that costs less than dinner.
Roy Lee, a former Columbia University sophomore and self-styled entrepreneur, was suspended just weeks ago amid a storm of controversy. He invented a AI tool to cheat his way into offers from Amazon, Meta, and TikTok
That tool, Interview Coder, now rakes in $228,500 per month. With $224,000 in profits and a 99% margin, it has turned a disciplinary case into a triumph of viral entrepreneurship. For Lee, it’s not just a win—it’s vindication.
But for recruiters, this is not a revolution. It’s an implosion.
“The Interview Process Is Totally Broken”: Recruiters in Open Revolt
Inside the hiring rooms of top tech firms, desperation has replaced data.
“We tell candidates explicitly: don’t use AI in this round,” says one startup co-founder involved in hiring. “They nod. Then they cheat anyway.”
Interviewers recount disturbing new norms: candidates looking sideways off-camera, inserting full code blocks with no typing, or dodging screen sharing altogether. Others deliver eerily flawless answers to complex algorithm questions, only to stumble when asked to explain their own solutions.
“We’re not just watching for wrong answers anymore,” said one hiring manager. “We’re watching for signs they’re human at all.”
According to internal data from technical interview platforms, the proportion of suspected AI-assisted cheating cases has jumped from 2% in early 2023 to over 10% today.
Platforms once designed to filter out underqualified applicants are now used by AI-literate job seekers to stage-manage an illusion of mastery. The consequences are acute: wasted engineering time, shattered trust, and in some cases, entire hiring pipelines frozen.
A $60 Shortcut to Silicon Valley Stardom
Interview Coder operates with disarming simplicity. A candidate takes a photo of the coding question, and the AI tool—leveraging GPT—delivers an annotated breakdown, step-by-step reasoning, and a complete solution.
An overlay interface ensures that everything remains hidden from screen-sharing detection. The mouse never appears to leave the browser. The candidate never appears to tab out. Yet every keystroke is scripted.
By mid-May, the tool is projected to cross $1 million in annual recurring revenue. Its virality is no accident. Lee documented his entire journey—from cheating Amazon to building the tool that did it—on YouTube and LinkedIn, garnering thousands of views.
His LinkedIn post about being expelled from Columbia sparked furious debate—and helped fuel subscription growth.
According to internal business data he released:
- 94% of revenue comes from the $60/month plan
- Monthly churn is about 35%
- Actual costs are minimal: a $3,000 Vercel hosting bill and $500 in Reddit ads
He claims nearly 10% of Google Summer Interns used the tool. No one has yet contradicted him.
Interview Coder Is Just the Beginning
If Interview Coder is the spark, Leetcode Wizard is the wildfire.
At €49/month with over 16,000 users, Leetcode Wizard brands itself the “#1 AI-powered interview cheat app.” With a claimed 93% pass rate and users boasting real FAANG offers, the tool goes further than its rivals: it diagnoses time complexity, generates clarification questions, and simulates “human-like” typing outputs to avoid detection.
Key features include:
- Undetectable screen overlays
- Global shortcuts invisible to interview platforms
- Strategically placed interface above the code editor
- Invisible to all major screen-recording tools
Despite being public, widely marketed, and downloaded from GitHub, the tool has—so far—never been flagged by a major technical interview platform.
Its creators claim that the problem isn’t with the software. It’s with the system.
“Leetcode ≠ actual work,” reads their homepage. “We’re just revealing the farce.”
An Industry in Cognitive Dissonance
Recruiters now face an existential dilemma: ban AI tools, and risk alienating talent that’s already using them at work—or allow them, and reduce the interview process to theater.
Ali Ansari, CEO of AI hiring firm Micro1, believes the status quo is no longer viable.
“Even without cheating, coding tests must begin to look different,” he said. “We’re entering a new era. AI has permanently altered the role of the engineer.”
This tension is echoed by Don Jernigan, VP at Experis Services, who argues that interviews must focus on uniquely human capabilities: judgment, creativity, and debugging intuition.
Some companies are already experimenting. Apryse, a software firm, now gives candidates offline take-home projects where AI is permitted—but the final evaluation hinges on an in-depth explanation of the workflow.
Others are building blacklists of known cheaters and designing interview formats that emphasize real-time discussion over code perfection.
But the fear remains: that AI has simply outpaced the format meant to contain it.
Academia’s Crackdown Backfires
Columbia University thought it had closed the chapter with Lee’s expulsion on March 20, after a disciplinary hearing prompted by industry complaints.
Amazon, a long-time Columbia hiring partner, had reportedly warned: if the school didn’t take action, the relationship was at risk.
At the hearing, Lee was asked to admit that Interview Coder might be used to help students cheat on coursework—an allegation he mocked as irrelevant. “Haha,” he said publicly after the decision. “I have no regrets.”
Ironically, the backlash turbocharged his success. The tool’s biggest update rolled out days later. On X, he claimed thousands of users had passed interviews thanks to it.
His profits—99% on nearly a quarter-million in monthly revenue—have turned what began as a disciplinary scandal into one of the most profitable AI micro-startups in recent history.
AI Didn't Break Interviews—It Revealed They Were Already Broken
The defenders of traditional interviews are now caught in a contradiction: AI is welcomed in the workplace, but forbidden in interviews. Why?
"Timed tests were never realistic," said one interview coaching company founder. "AI just lifted the veil."
A joint study from UNC and Microsoft found candidates perform better when allowed to explain their thinking and aren’t being tightly monitored—suggesting that interview pressure itself may distort performance more than AI ever could.
Even OpenAI co-founder Andrej Karpathy has coined the term “vibe coding”—the idea that engineers may soon be judged more on code comprehension and AI collaboration than raw implementation ability.
With AI capable of instantly generating code, perhaps the real skill of tomorrow’s developer is knowing which code to generate—and why.
What Comes Next?
The interview collapse may be the canary in the coal mine.
If one person, in two months, with $3,500 in costs, can build a viral, profitable tool that undermines a hiring protocol used by trillion-dollar companies—what else is fragile?
For now, companies are left scrambling. Some will tighten controls. Others will redesign interviews from the ground up. But a growing faction believes the solution isn’t better surveillance—it’s better evaluation.
One hiring leader summed it up:
“We need interviews that test for what AI can’t do. Because otherwise, we’re just interviewing the tools.”
Roy Lee, meanwhile, is busy scaling his business.
If the old rules no longer apply, then—as he sees it—he’s not the villain of this story.
He’s the prototype.