Roy Lee’s Interview Coder: Cheating or a Wake Up Call?
A Columbia CS student built an AI tool that helps candidates cheat in coding interviews, sparking debate about fairness and the future of technical hiring.
Roy Lee transformed from Reddit’s Leetcode champion to tech’s most controversial disruptor. The Columbia University sophomore created Interview Coder, an AI tool that solves coding interview problems in real-time. His bold move exposed fundamental flaws in technical hiring while igniting fierce debates about ethics and fairness.
What Interview Coder Does
Interview Coder costs $60 monthly and delivers three core capabilities:
- Real-time problem solving: AI generates solutions during live interviews
- Code optimization: Debug and improve code with a single keystroke (⌘ + ↵)
- Detection evasion: Works undetected on Zoom, HackerRank, and Microsoft Teams
The tool transforms algorithmic novices into apparent coding prodigies, completing complex problems faster than human candidates typically manage.
The Amazon Incident That Changed Everything
Roy tested his creation during an Amazon software engineering interview in early 2024. He used Interview Coder to solve a challenging graph traversal problem flawlessly, impressing the interviewer with his speed and accuracy.
The twist: Roy recorded the entire session and posted it on YouTube. The video went viral, showing the interviewer’s amazed reaction and Roy’s post-interview confession that AI solved the problem.
Amazon responded swiftly. They rescinded his job offer, banned him from future applications, and complained to Columbia University about “academic dishonesty” and “undermining hiring integrity.” Columbia investigated but took no disciplinary action, finding no violation of academic codes.
The University’s Measured Response
Columbia’s administration issued a diplomatically worded statement:
“While we encourage innovation, students are reminded to uphold ethical standards in all professional endeavors. The university does not endorse tools that compromise the integrity of third-party processes.”
Roy amplified the controversy by tweeting the letter with commentary: “Columbia’s stance on ‘innovation’: ✅ Nuclear physics. ❌ Exposing broken tech interviews.” The tweet garnered 50,000 likes and thousands of heated responses.
Why DSA Interviews Face Extinction
Interview Coder exposed critical weaknesses in traditional Data Structures and Algorithms interviews:
AI outperforms human memorization: Modern AI solves complex algorithmic problems in seconds, making rote memorization obsolete.
Misaligned skill assessment: Leetcode problems test pattern recognition rather than real-world development capabilities like building applications or debugging production code.
The automation paradox: Companies using automated testing tools face candidates who automate back, creating an arms race between detection and evasion.
Viral Marketing Campaign
Roy’s social media strategy amplified Interview Coder’s impact:
- Posted leaked Amazon interview footage
- Created memes comparing Leetcode grinding to “hamsters on wheels”
- Ran controversial polls asking followers if they’d use AI tools in interviews (62% said yes)
- Partnered with coding influencers for live demonstrations
One memorable video showed a self-taught developer solving Hard Leetcode problems while eating a sandwich, titled “Coding Interviews Are a Joke. Here’s the Punchline.”
The Ethics Divide
The tech community split into opposing camps:
Anti-cheating faction argues unqualified hires produce poor code and unreliable systems. They view Interview Coder as undermining merit-based selection.
System-reform advocates contend that interviews testing memorization over practical skills deserve disruption. They frame the tool as exposing broken processes rather than enabling cheating.
Roy positioned Interview Coder as an accessibility tool, arguing not everyone has months to grind algorithmic problems. Critics countered that his solution creates new inequalities rather than solving existing ones.
Industry Adaptation Attempts
Companies scramble to develop AI-resistant interview formats:
Take-home projects: Candidates build mini-applications demonstrating real development skills rather than solving abstract puzzles.
Pair programming sessions: Live coding with interviewers makes AI assistance harder to conceal and reveals thought processes.
Behavioral interviews: Focus shifts to communication skills, problem-solving approaches, and cultural fit.
However, many organizations resist change, clinging to familiar Leetcode-style assessments despite their proven vulnerabilities.
The Lasting Impact
Roy Lee forced the tech industry to confront uncomfortable truths about hiring practices. Whether Interview Coder represents cheating or necessary disruption, it definitively ended the era of algorithmic interview supremacy.
The controversy highlights broader questions about AI’s role in professional assessment and the need for hiring processes that evaluate actual job-relevant skills. As AI capabilities expand, technical interviews must evolve or become increasingly meaningless.
Companies now face a choice: adapt their hiring methods to focus on practical skills and real-world problem-solving, or watch candidates game increasingly obsolete systems with ever-more sophisticated tools.